Stem Cells

doi: 10.1002/stem.2591pmid: N/A

Cover Art: A scanning laser confocal image of mouse embryonic neural stem cells grown in culture and allowed to differentiate. Differentiating cells expressed GFAP (green) and Protein S (red). The nuclei are stained blue. See Zelentsova et al. beginning on page 679. Open in new tabDownload slide Open in new tabDownload slide Article PDF first page preview Close This content is only available as a PDF. © 2017 AlphaMed Press This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model)

Hamazaki, Takashi; El Rouby, Nihal; Fredette, Natalie C.; Santostefano, Katherine E.; Terada, Naohiro

doi: 10.1002/stem.2570pmid: 28100040

Abstract Recent advances in DNA sequencing technologies are revealing how human genetic variations associate with differential health risks, disease susceptibilities, and drug responses. Such information is now expected to help evaluate individual health risks, design personalized health plans and treat patients with precision. It is still challenging, however, to understand how such genetic variations cause the phenotypic alterations in pathobiologies and treatment response. Human induced pluripotent stem cell (iPSC) technologies are emerging as a promising strategy to fill the knowledge gaps between genetic association studies and underlying molecular mechanisms. Breakthroughs in genome editing technologies and continuous improvement in iPSC differentiation techniques are particularly making this research direction more realistic and practical. Pioneering studies have shown that iPSCs derived from a variety of monogenic diseases can faithfully recapitulate disease phenotypes in vitro when differentiated into disease-relevant cell types. It has been shown possible to partially recapitulate disease phenotypes, even with late onset and polygenic diseases. More recently, iPSCs have been shown to validate effects of disease and treatment-related single nucleotide polymorphisms identified through genome wide association analysis. In this review, we will discuss how iPSC research will further contribute to human health in the coming era of precision medicine. Genomics, Induced pluripotent stem cells, Experimental models Significance Statement Each person has a unique set of gene variations that affect susceptibility to and protection from both common and rare disorders. Although associations between human health and individual variabilities need to be validated in principle, it is still challenging to validate effects on actual biological processes. Human induced pluripotent stem cells provide a unique opportunity to dissect the roles of genetic variants for pathogenesis. This review overviews recent developments how induced pluripotent stem cell research will further contribute to human health in the coming era of precision medicine. Recent Advances in Human Genome Research Leading to an Era of Precision Medicine The first human reference genome was drafted in 2001 after an international collaborative effort between academic institutions, with the goal of characterizing genetic variations across the human genome [1, 2]. After completion of the human genome project, extended efforts to catalog these genetic variants have been made, the first of which was the international HapMap project, which aimed to build haplotype blocks of the most common genetic variations, namely, single nucleotide polymorphisms (SNPs) across human populations [3, 4]. The 1000 genomes project (http://www.1000genomes.org/) characterized common and rare genetic variations in 2,504 individuals from 26 different populations using next generation sequencing based methods and dense genotyping arrays [5]. With the influx of information and availability of genotyping platforms, it became possible to interrogate millions of SNPs simultaneously from hundreds to thousands of individuals through genome wide association analysis (GWAS). This approach has revolutionized the field of genetics, allowing for many genetic associations to be made through an agnostic, nonhypothesis driven approach. Since the first waves of GWAS publications in 2005, 23,058 SNP-trait associations have been published in the National Human Genome Research Institute - European (NHGRI–EBI) catalogue totaling 2,502 GWAS studies [6] Pharmacogenomics is a field dedicated to identifying genetic determinants of drug response or adverse effects and is key to the concept of precision medicine, which entails utilizing genotype to guide selection of medication. Despite a fruitful era of GWAS findings in pharmacogenomics, many of these variants have not yet made it to clinical utilization. A major hurdle of pharmacogenomics implementation is the unknown underlying mechanistic link(s) between drug response phenotype and genotype. While some SNPs are located in biologically relevant genes for the phenotype being studied, the majority of variants lie in noncoding areas of the genome, where a direct connection to phenotype is unknown and a role in gene regulation is presumed. Deciphering the role of the associated genetic signals to reveal how these variants function at a molecular and cellular level is crucial for a clear understanding of the disease process and implementation of personalized medicine. In 2015, the Obama administration announced the launch of a precision medicine initiative by the National Institutes of Health [7, 8] (https://www.nih.gov/precision-medicine-initiative-cohort-program) In this initiative, large scale cohort studies will be conducted to integrate individual lifestyle, environment, and genomic information, to build a comprehensive knowledge base which can predict individual disease risk and response to treatments. Genome sequencing and characterization of genetic variability were initial strides toward precision medicine goals of utilizing individual data to diagnose, treat, and predict response to medical treatments. With the advent of high throughput-next generation sequencing technologies and rapidly declining costs, it is feasible to perform whole genome, whole exome (protein coding), and transcriptome (RNA transcript) sequencing to probe the associations with phenotypic traits/disease conditions. Additionally, integrating multidimensional-omics data (e.g., genomics, transcriptomics, epigenomics, proteomics, and metabolomics) holds promise to elucidate biological interactions involved in complex diseases and to shed light on important genetic variants that may be missed with genetic approaches due to lack of strict statistical significance. Although associations between human health and individual variabilities need to be validated in principle, it is still challenging to validate effects on actual biological processes. The use of induced pluripotent stem cells (iPSC) is an attractive system for modeling genetic variants to study molecular consequences in a relevant cell type. iPSC technology reprograms a fully mature somatic cell into a pluripotent stem cell that retains all the genetic characteristics of an individual patient. These iPSCs can then be differentiated into multiple different tissue types (for a growing list of validated tissue differentiation milestones, see Cell Stem Cell 18, March 2016) [9, 10]. Gene editing systems such as CRISPR-CAS9 or TALEN will expand studies that aim to unravel the mechanisms and functional consequences of genetic variations [11, 12]. This can be done through editing single nucleotides, introducing or reversing mutations in iPSCs and observing the phenotypic changes in terminally differentiated cells. iPSCs to Find Cures of Monogenic Disorders Diseases can have monogenic or polygenic etiologies. Monogenic diseases, caused by the inheritance of a single defective gene are considered rare because the prevalence of each disease is quite low, usually less than 1/10,000 at birth. The number of diseases with known causal genetic loci has doubled in the last 10 years as seen in Online Mendelian Inheritance in Man (OMIM) entry statistics. Improvement of genetic diagnostics and implementation of screening programs (e.g., newborn screening and high-risk screenings) make it possible to identify people with such rare disease. As a result, rare genetic diseases affect 350 million people worldwide and the global prevalence of all single gene diseases at birth is approximately 1/100. Since the establishment of human iPSCs in 2007 [13, 14], there has been an extraordinary expectation to utilize the cells to model human “diseases in a dish” [15, 16]. Pioneering studies have shown that iPSCs derived from a variety of monogenic disorders can faithfully recapitulate disease phenotypes in vitro when differentiated into disease-relevant cell types [17, 18]. Generating iPSC lines from patients with these monogenic diseases is a useful approach to establish an enduring in vitro human model and has been demonstrated in numerous published studies [19–22]. Collaborative efforts among research communities have yielded a variety of disease-specific iPSC lines readily available through iPSC banks [23] and researchers may be able to find stem cell lines of interest to conduct further mechanistic studies or directly apply the cells for drug screening. Although many important discoveries have been made for monogenic diseases through iPSC research, one of the most exciting studies is a recent report on achondroplasia by Yamashita et al. [24]. Importantly, the authors carefully established a method to differentiate iPSCs into chondrocytes to form cartilaginous tissue. This was a critical step for Yamashita et al., because developing appropriate differentiation protocols for disease-relevant cell types can still be a limiting factor for iPSC research. They were able to successfully recapitulate abnormal cartilage formation during in vitro differentiation of iPSCs derived from patients with achondroplasia when compared to those from healthy controls. Furthermore, upon compound screening, they showed that statins, widely used lipid lowering medications, unexpectedly corrected the degraded cartilage in the iPSC model. This exemplary work clearly recapitulates disease processes in a dish and demonstrates the utility and promise of iPSC models to discover novel treatments for rare monogenic disorders. In addition to two-dimensional monolayer differentiation or basic three-dimensional (3D) aggregate differentiation, several groups have developed sophisticated 3D differentiation protocols, often termed “organoid culture” due to their ability to form organized structures reminiscent of developing organs. Notably, for central nervous system organoid culture, Lancaster et al. demonstrated that iPSCs derived from a microcephalic patient indeed formed a smaller brain organoid than iPSCs from a healthy control [25]. Similarly, several organoid culture techniques for iPSCs have evolved to generate other tissue types and organs (optic cup, pituitary gland) [26, 27]. Undoubtedly, these breakthrough discoveries will provide necessary complexity to more accurately model disorders and allow for greater opportunity for preclinical testing of treatment options for human cells in vitro. iPSCs to Define Further Phenotypic Variations in Monogenic Disorders In human monogenic disorders, a single gene mutation is predominantly responsible for the phenotype of the disease. In many cases, we can predict how a specific mutation in a single gene affects protein function (e.g., residual enzyme activity), which correlates with severity and presentation of a disease. It is, however, still challenging to accurately predict clinical symptoms, severity and onset of the disease from the type of mutation. An example of this challenge is Gaucher disease (GD), an autosomal recessive disorder caused by mutations in GBA gene that encodes glucocerebrosidase (GCase) [28]. GCase is a lysosomal enzyme that catalyzes the hydrolysis of the glycolipid glucocerebroside to ceramide and glucose. Patients with GD show a broad spectrum of clinical symptoms including hepatosplenomegaly, bone deformity, hematological abnormality, and neurological symptoms. The N370S mutation in GBA is frequently found in type 1 GD, which presents with non-neuronal symptoms. On the other hand, the L444P mutation is frequently found in type 2 or 3 GD, which does present with neurological symptoms. Recombination events of the GBA locus with a neighboring pseudogene have also been linked to some unusual clinical presentations [29]. Phenotypic variabilities, however, have been observed among patients with identical GBA mutations, such as between affected sibling pairs, and even between identical twins. In a monozygotic twins case, one was affected with GD but the other had no clinical symptoms even with low GCase activity [30]. In GD, deficiency of GCase leads to accumulation of the intermediate metabolite glucosphingolipids glucosylceramide, which is further metabolized into sphingosine by an extra lysosomal GCase, GBA2. interestingly, deletion of GBA2 in a GD mouse model rescued visceral and bone symptoms, suggesting that GBA2 could potentially be targeted to ameliorate certain debilitating manifestations of GD [31]. In another study, Awad et al. uncovered involvement of lysosomal dysfunctions and an autophagy block during the neurodegenerative process of GD by using neuronal cells derived from the iPSCs of patients with type 2 GD (neuropathic form). Upon rapamycin treatment, neuronal death was preferentially induced in neurons from type 2 GD-iPSCs, but not type 1 GD-iPSCs. Although expression of the transcription factor EB (TFEB), the master regulator of lysosomal genes was downregulated, overexpression of TFEB only partially restored the neurodegenerative process in neurons from type 2 GD-iPSCs [32]. These findings represent a promising avenue to identify genetic and nongenetic (epigenetic and/or environmental) modulators that influence disease-causing mutations. Since iPSCs can be generated from individuals with various genetic backgrounds, and genomic loci can be targeted in iPSCs, disease-relevant cell types obtained from such iPSCs will be an indispensable tool to validate newly proposed disease mechanisms and to screen environmental factors/small compounds to modulate disease phenotypes. iPSCs to Dissect the Roles of SNPs in Polygenic Disorders and Differential Drug Responses Many common human diseases and traits are influenced by several genetic and environmental factors. Polygenic diseases result from the additive inheritance of multiple subtle polymorphisms, culminating in an affected phenotype. In 2016, nearly 5,000 disease phenotypes have been cataloged and linked with causal genetic loci in OMIM (http://omim.org/statistics/entry). GWAS have successfully identified hundreds of genetic variants associated with various conditions and have provided valuable insights into diagnostics, prognosis, and therapeutic optimization for complex human diseases [33]. An example of a common, complex and polyfactorial disease is hypertension (HTN). HTN is a major health burden in the U.S. that affects approximately 80 million people [34] and direct patient treatment totals nearly 40 billion dollars a year [35]. Additionally, HTN is increases the risk for advance cardiovascular diseases such as stroke and heart failure [34, 36] Numerous antihypertensive agents such as diuretics, ACE inhibitors, angiotensin receptor blockers, beta blockers and calcium channel inhibitors are currently available, but their effectiveness on blood pressure varies among individuals. GWAS and case studies for candidate genes have identified several genetic variants which may regulate blood pressure or contribute to a drug's pharmacological pathway [37]. Animal models have been used intensively for studying systemic diseases like HTN, however they may not always be suitable for understanding the biological impact of human genetic variants. It is also difficult to obtain a large number of appropriate tissues of relevance for the phenotype of interest (e.g., vascular smooth muscle or endothelium) from a person with a specific genotype to test the biological or functional consequences of these genetic variations. To combat such challenges, Biel et al. constructed an iPSC repository from 17 HTN patients, whose genome-wide SNP variations as well as clinical responses to antihypertensive drugs were available [38]. The iPSCs were generated from a blood draw of peripheral blood mononuclear cells collected from participants of the Pharmacogenomic Evaluation of Antihypertensive Response (PEAR) study [39] (https://clinicaltrials.gov/NCT00246519). Biel et al. then differentiated these iPSCs into vascular smooth muscle cells and quantified their contraction in response to various physiological stimuli [38]. Furthermore, the study also demonstrated the ability of iPSCs to recapitulate a SNP-associated modification of PRKCA expression. The SNP rs16960228 has been well-documented in multiple GWAS cohorts to associate with a hypertensive drug response as well as differential expression levels of PRKCA. These data support the applicability and translational value of iPSCs in modeling GWAS findings. Another example of cardiovascular disease modeling using iPSCs is presented by Ebert et al. [40]. Ebert et al. studied a SNP in the gene coding for aldehydronease 2 enzyme, which confers a loss of cardioprotective effects and increases risk for coronary artery and ischemic heart disease. Cardiomyocytes (CM) differentiated from iPSCs derived from an east Asian population genotyped for a common ALDH2* SNP (MAF = 0.08), demonstrated that CMs carrying the ALDH2* genotype had increased levels of oxidative stress and aldehyde byproduct 4HNE buildup. Accumulation of these two byproducts resulted in dysregulated cell cycle and apoptosis signaling, which exacerbated damage and reduced cellular recovery to ischemic challenge in the CMs of ALDH2* carriers, thereby establishing the cellular mechanisms for increased disease susceptibility for a single SNP. Finally, it is well established that differences in susceptibility and drug response to HTN and multiple polygenic diseases varies by ethnic group (i.e., African American vs. Western European American), it will be important to understand the utility of such iPSCs libraries based on ethnic background. To address the challenge of diversity in disease genetics using iPSCs, Chang et al. reported the construction of an iPSC bank from ethnically diverse populations [41]. Taken together, these studies demonstrate that an iPSC library with defined SNPs and phenotypic data will be a useful resource to validate the effects of GWAS-identified SNPs and to facilitate mechanistic understanding of human physiological and pathological conditions. It is increasingly important to understand how specific risk variants functionally contribute to underlying pathogenesis. Compared with single gene mutation found in monogenic diseases, the effects of SNP variants can often be minor or subtle. It is important to utilize isogenic cells to decode the significance of such gene variants. Recent advances in genome-editing technology (e.g., CRISPR/Cas9 systems) have simplified the ability to target specific genetic loci for functional studies. Gene-editing methods in iPSC's has been reviewed in detail elsewhere [42, 43]. Soldner et al. demonstrated functional connect of GWAS-identified risk variants of Parkinson's disease in neurons derived from human iPSCs [44]. They focused on Parkinson's disease associated risk SNPs, which were located in an α-synuclein (SNCA) regulatory region based on genome-wide epigenetic information. By establishing TaqMan SNP genotyping assays for quantitative reverse transcription polymerase chain reaction, they were able to monitor subtle changes in allele-specific transcription of SNCA between two SNPs located in the SCNA enhancer region. As a follow up approach, they knocked-out the single allele of the SNPs using the CRISPR/Cas9 system to see how the SNPs affect SNCA expression. They found that allele-specific expression roughly translated to an increase of total SNCA expression of 1.06 times in neurons and 1.18 times in neural precursors. Furthermore, sequence-dependent binding of the brain-specific transcription factors EMX2 and NKX6-1 on this locus was revealed. As part of the Next Generation Genetic Association Studies (Next Gen) Program, various fields of researchers are now depositing iPSC resources, generated from individuals representing various conditions as well as healthy controls, with the goal of following up findings from functional genomics with mechanistic investigations. The program is aimed at generating iPSC lines from more than 1,500 individuals some of which are available through a public iPSC bank (http://www.wicell.org/home/stem-cell-lines/collections/collections.cmsx). Each iPSC line is linked with clinical data (e.g., lipid condition, QT interval and ECG cardiac trait, pulmonary HTN) as well as age, gender and ethnic background. SNP genotyping, gene expression, and -omics analysis data will be available for these lines in the future. It is critically important that high quality iPSC lines are also paired with high quality genetic and clinical data. This can be facilitated through large collaborations that generate harmonized phenotypes through established criteria for diagnosis and accurate phenotype definition, with an ultimate goal of reducing phenotype variability. The more accurately a phenotype is defined, the higher the likelihood of identifying the culprit gene and genetic variants [45]. With such standardized phenotypes, advancement of genetic discoveries and their replication can be made, which can be carried forward to iPSC studies using the tissues of relevance. A study by Akawi et al. shows that the value of deep sequencing information is decreased if it is not coupled with high quality phenotype data from patients [46]. An analogy can be made here as we think of the diminished value of iPSC if we do not have an accurately defined clinical phenotype that will be ultimately translated into a cellular phenotype in a dish. Therefore, it is increasingly important for the collaborative genetic consortia to establish procedures for phenotype ascertainment to reap the maximum benefit of iPSC modeling. iPSCs to Understand Genetic and Phenotypic Variations Beyond GWAS It has been recently shown that especially rare genetic variants, such as homozygous variant defects resulting in rare pathologies, can associate for increased risk of more common maladies as well. For example, having a pathogenic GBA mutation for Gaucher's Disease (GD) [28] (e.g., N370S, L444P) in one allele (carrier) will not usually manifest the full symptoms of GD, but does increase risk for Parkinson's disease [47, 48]. The odds ratio for the GBA mutation in PD was greater than 5, which is unusually high compared to risk loci found from GWAS [49]. On the other hand, there is an example where a rare genetic variant has a protective effect on a complex disease. SLC30A8 encodes an islet zinc transporter (ZnT8) and ZnT8 has been known as a key regulator of insulin secretion in pancreatic beta cells. [50]. Furthermore, large scale GWAS identified a common variant (p.Trp325Arg) on SLC30A8 that results in an increased risk for type 2 diabetes (T2D) [51–53]. Animal studies with this variant, however, showed conflicting results for pathogenesis of T2D. Breakthrough have been made through international collaborative studies, which aimed to find loss-of-function variants protective against T2D. Sequencing data from more than 150,000 people identified heterozygous individuals for a nonsense variant (p. Arg 138*) in a Finnish cohort exhibited a 60% reduced risk of type 2 diabetes [54]. Recently, Chen et al. proposed the reverse approach to find healthy individuals resilient to highly penetrant forms of genetic childhood disorders. They sequenced 874 genes in 589,306 genomes and found 13 adults carried mutations for 8 severe Mendelian conditions with no reported clinical manifestation of the indicated disease [55]. This could be a first step toward uncovering protective genetic variants, and further mechanistic studies are anticipated. As discussed above, iPSCs will serve as a powerful tool here as well to dissect molecular mechanisms of the genetic associations, hopefully leading to novel therapeutic discoveries. Conclusion Gathering our knowledge of human disease genetics, we start to realize that each person has a unique set of variants that contribute to susceptibility and protection for a variety to disorders. Phenotypes vary even within rare monogenic diseases based on their mutation types, genetic background and environmental factors. To further advance precision medicine, it will become increasingly important to dissect molecular mechanisms underlying these genotype-phenotype associations. Human iPSCs provide a unique opportunity to fill these knowledge gaps, and their anticipated increase in utilization by researchers via cellular repositories position them as a crucial reagent for the next generation of disease genomics studies (Fig. 1). Figure 1 Open in new tabDownload slide Stem cell tactic to advance precision medicine. Each person has a unique set of gene variations that affect susceptibility to and protection from both common & rare disorders. Human iPSCs provide a unique opportunity to dissect the roles of genetic variants for pathogenesis. Abbreviation: iPSCs, induced pluripotent stem cells. Figure 1 Open in new tabDownload slide Stem cell tactic to advance precision medicine. Each person has a unique set of gene variations that affect susceptibility to and protection from both common & rare disorders. Human iPSCs provide a unique opportunity to dissect the roles of genetic variants for pathogenesis. Abbreviation: iPSCs, induced pluripotent stem cells. Acknowledgments This work was supported in part by Japan Agency for Medical Research and Development, AMED, Practical Research Project for Rare/Intractable Diseases, National Institutes of Health (GM119977 and DK104194), American Heart Association (16GRNT30980002), and the University of Florida Clinical and Translational Science Institute (UL1TR001427). NCF is a recipient of postdoctoral fellowship T32 DK074367. Author Contributions N.E., N.F., and K.S.: Conception and design and manuscript writing; T.H. and N.T: Conception and design, manuscript writing, financial support, and administrative support. Disclosure of Potential Conflicts of Interest The authors indicate no potential conflicts of interest. References 1 Lander ES , Linton LM, Birren B et al. Initial sequencing and analysis of the human genome . 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Google Scholar Crossref Search ADS PubMed WorldCat Author notes Available online without subscription through the open access option © 2017 AlphaMed Press This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model)

Franco, Bénédicte; Malgrange, Brigitte

doi: 10.1002/stem.2554pmid: 28102558

Abstract It is commonly assumed that mammalian cochlear cells do not regenerate. Therefore, if hair cells are lost following an injury, no recovery could occur. However, during the first postnatal week, mice harbor some progenitor cells that retain the ability to give rise to new hair cells. These progenitor cells are in fact supporting cells. Upon hair cells loss, those cells are able to generate new hair cells both by direct transdifferentiation or following cell cycle re-entry and differentiation. However, this property of supporting cells is progressively lost after birth. Here, we review the molecular mechanisms that are involved in mammalian hair cell development and regeneration. Manipulating pathways used during development constitute good candidates for inducing hair cell regeneration after injury. Despite these promising studies, there is still no evidence for a recovery following hair cells loss in adult mammals. Progenitor cells, Cellular proliferation, Cell signaling, Differentiation Significance Statement Up to now there is no treatment to halt or replace hair cell in mammals. Recently progenitor cells have been identified and retained the capacity—at least at perinatal stages—to proliferate and/or differentiate. In this Review, we discuss recent progress in the identification of cochlear progenitor cells that could proliferate and/or differentiate into hair cells. We also review various signaling pathways that participate to cochlear development and discuss their potential use in hair cell regeneration both in vitro and in vivo. Introduction Neurosensory hearing loss affects a broad range of people worldwide and results mainly from an irreversible loss of cochlear hair cells. Environmental factors, ototoxic medications, and genetic predispositions are all important contributors to hair cell loss. The inner ear is an organ of exquisite organization, harboring the cochlea responsible for hearing and the vestibule responsible for balance. Both structures are organized in a sensory epithelium containing hair cells surrounded by supporting cells and neurons contacting the hair cells. In the cochlea, the hair cells and the supporting cells form the organ of Corti. In the vestibule, they are organized in different structures: saccule, utricule, and cristae. Hair cells detect mechanical stimuli, by deflection of stereocilia present at their apical surface, and then transmit the information to the neurons through their dendrites. The information is then carried by the axon to the proper region of the brain. The neurons are grouped in ganglia, either the spiral ganglion for the cochlea or the vestibular ganglion for the vestibule. In the mammalian cochlea, it has been long admitted that hair cells do not regenerate, hampering a possible recovery. Recent studies have uncovered mechanisms in which new hair cells can be formed from the surrounding supporting cells. These cells act as hair cell progenitors either by re-entering the cell cycle and dividing to give rise to new hair cells, or by direct differentiation into hair cells, to so-called transdifferentiation. In this Review, we will focus on the mechanisms and signaling pathways involved in such recovery of hair cell loss. Developmental Hair Cell Production The formation of the inner ear needs several signaling pathways orchestrated in space and time during embryogenesis. The development of the mouse inner ear is initiated as early as embryonic day 7.5 (E7.5) by specification of a particular region of the anterior ectoderm, the preplacodal region, which requires different signals [1]. From the mesoderm and the neural plate, fibroblast growth factor (FGF) signaling is important to induce otic fate [2]. FGF3 and FGF10 have been shown to be important for the formation of otic territory [3, 4]. Besides, FGF8 is also required for otic induction, as it acts to promote or maintain FGF10 expression. Moreover, otic induction requires the inhibition of Wnt and bone morphogenetic protein (BMP) signaling, which are both responsible for ectodermal formation [5, 6]. The preplacodal region is then characterized by the expression of several transcription factors such as Six1, Six4, Eya1, and Eya2 (reviewed in [7]). Once the preplacodal region has been specified, it thickens to give rise to the otic placode at around E9. The induction of the otic placode is under the control of signaling cascades such as FGFs and Wnts [8–10]. FGF signaling induces the expression of transcription factors from the paired box (Pax) family, such as Pax2 and Pax8. Pax2-positive cells then can give rise to either otic cells or epidermis [11]. For the induction of an otic fate, activation of Wnt signaling is necessary in these Pax2-positive cells. Indeed, Wnt1, 3a, 6, and 8 are secreted by the hindbrain and rhombomeres act instructively to direct Pax2-positive cells to an otic fate [8, 12, 13]. Afterward, the placode will start to invaginate to form the otic cup [14]. Then, the otic cup closes to form the otic vesicle, which will generate nearly all cell types of the inner ear. Starting around E12, the ventral part of the developing otocyst is specified in a so-called prosensory area, expressing Sox2, that will later give rise to the organ of Corti. This territory is spatially defined by a gradient of BMPs across the cochlear duct (increasing concentrations from the Kölliker's organ or inner sulcus, the prosensory domain to the outer sulcus) allowing the specification of sensory versus non-sensory domain [15]. Notch signaling through its ligand Jagged1 is also acting for prosensory induction and the formation of sensory patches [16]. Soon after the emergence of the prosensory domain (around E13.5), a non-proliferative zone appears with the expression of the cell cycle inhibitor p27kip1/CDKN1B [17]. The upregulation of CDNK1B could be downstream of Sox2, and in turn CDKN1B could repress Sox2 [18, 19]. Indeed, the expression of Sox2 is transient as at later stages during development Sox2 is down-regulated in mature hair cells and neurons [20, 21] and only remains in supporting cells. The reduced expression of Sox2 is essential for the induction of hair cells by activation of the transcription factor Atoh1 [22]. Between E14.5 and E15.5 a wave of differentiation is initiated from the base toward the apex of the cochlea, allowing the generation of hair cells and supporting cells upon Notch cascade by lateral inhibition [23]. This process ends between E17.5 and E18.5. At the same time, another gradient of differentiation occurs medially enabling the formation of the inner hair cells row at first, and then the three rows of outer hair cells [17, 24, 25]. During the cochlear formation, the specification of hair and supporting cells is subjected to a subtle combination of distinct signaling pathways, transcription factors expression and epigenetic regulations. Moreover, cells are rarely exposed to one stimulus at a time, and cross-talk (direct or indirect) between signaling pathways is evident and recently identified in the developing inner ear (reviewed in [26, 27]). Atoh1 While thinking about hair cells differentiation, one consensus is the major role of Atoh1, also named Math1, a basic helix-loop-helix transcription factor related to Drosophila melanogaster proneural gene, atonal [28]. Atoh1 starts to be expressed around E12.5 in the vestibular portion of the inner ear when hair cells start to differentiate [29]. In the cochlear portion, the expression of Atoh1 is visible from E14.5, next to the emergence of the CDKN1B non-proliferative zone [30]. Paradoxically, while cells become post-mitotic in an apical-to-basal gradient, Atoh1 expression and hair cell differentiation begin in the basal turn and progress in the opposite direction [30]. Deletion of Atoh1 gene leads to the absence of hair cells formation while its overexpression induces ectopic hair cells [31, 32]. Besides its role in early hair cells specification, Atoh1 is also important later during development by promoting their survival and maturation [33, 34]. Notch Notch signaling is important for the specification of hair cells and supporting cells by lateral inhibition [35, 36]. Nascent hair cells start to express Notch ligands Jagged2 and Delta1, while surrounding cells express the Notch receptor and differentiate into supporting cells through the induction of Hes genes that inhibit Atoh1, an essential protein for hair cells. The acquired supporting cell fate is not solely due to absence of Atoh1, but is also dependent on activation of transcriptional signature upon Notch activation [37]. microRNAs Regulation of transcript expression through microRNAs (miRNAs) is also involved in the specification of hair cells versus supporting cells. miR-183 family members, that include miR-183, miR-182, and miR-96, are expressed in hair cells but not in supporting cells [38]. Down-regulation of these miRNAs results in the production of fewer hair cells [39]. Moreover, mutations within the miR-96 gene have been associated with human hereditary hearing loss [40, 41]. More recently, miR-124 has also been involved in cochlear development. Indeed, by targeting secreted frizzled-related protein 4 (Sfrp4) and Sfrp5, two inhibitors of the Wnt pathway, miR-124 controls the Wnt pathways that contribute to hair cells differentiation and polarization in the organ of Corti [42]. Wnt Pathway Canonical Wnt pathway activation is responsible for cell proliferation in the prosensory domain [43]. Indeed, continuous Wnt/β-catenin activation using TCF/Lef/H2B-GFP reporter mouse cochleae upregulates Sox2 prosensory cell numbers and confers a more progenitor-like character. This increased proliferation is observed both within the early E12 proliferative and the late E13.5–E14.5 post-mitotic prosensory domain. Subsequently, Wnt/β-catenin pathway is also required for hair cells differentiation. Inhibition of Wnt signaling through use of pharmacological agents or loss of β-catenin results in a failure of hair cells to differentiate [43, 44]. At that developmental stage, the canonical Wnt/β-catenin pathway controls the expression of Atoh1 [45]. Once specified, Atoh1-positive hair cells are not any more dependent on Wnt/β-catenin pathway [44]. FGFs FGFs signaling has essential functions at several stages of inner ear development. Early during development, that is, at E9–E10 in mouse, FGF signaling is important for the specification of otic territory [4]. FGFs are also required for cell fate decision in the organ of Corti (after E15 in mouse). Indeed, loss of FGF receptor type 3 leads to an increased number of hair cells [46], while deletion of FGF8 induces a loss of Pillar cells, a particular type of supporting cells [47]. Generation of New Hair Cells After Loss: Regeneration In non-mammalian vertebrates, such as birds, replacement of hair cell loss occurs spontaneously for a long period after birth (for review see [48]). The formation of new hair cells can occur via two modes: mitotic regeneration, in which surrounding supporting cells re-enter the cell cycle and divide to give rise to new hair cells, and direct transdifferentiation in which supporting cells change their fate to become hair cells, even in the presence of antimitotic drugs [49–52] (Fig. 1). Figure 1 Open in new tabDownload slide Examples of signaling pathways that induce hair cell formation from supporting cells. The Lgr5-positive cells represent the most potent pool of progenitor cells. Different stimuli such as hair call loss, inhibition of Notch pathway, forced expression of Atoh1, activation of Wnt canonical pathway, or inhibition of EphrinB2 signaling can trigger supporting cells proliferation and/or their transdifferentiation. Figure 1 Open in new tabDownload slide Examples of signaling pathways that induce hair cell formation from supporting cells. The Lgr5-positive cells represent the most potent pool of progenitor cells. Different stimuli such as hair call loss, inhibition of Notch pathway, forced expression of Atoh1, activation of Wnt canonical pathway, or inhibition of EphrinB2 signaling can trigger supporting cells proliferation and/or their transdifferentiation. Although the cochlea is assumed to be unable to regenerate in mammals, some evidences showed that during the first 2 weeks after birth, cochlear and vestibular cells retain the capacity of sphere formation, a stem cell-like behavior [53, 54]. If sphere formation can be achieved in the mammalian inner ear, it might reflect that some cells have the ability to proliferate or differentiate. As in birds, these cells have been identified as the supporting cells. Indeed, CDKN1B-GFP supporting cells from neonatal mice isolated and placed in culture have been shown to divide and differentiate into hair cell-like cells [55]. In the same line, using different cell surface markers and fluorescence-activated cell sorting (FACS), dissociated cell from the perinatal (postnatal day 3, P3) cochlea can be separated into four different populations of non-sensory cells. Among these, numerous are able to re-enter the cell cycle and proliferate. However, only supporting cells are able to give rise to new hair cells [56]. More recently, studies have shown that Lgr5-positive supporting cells are the progenitors that can regenerate hair cells [57, 58]. Besides their ability to differentiate in vitro, supporting cells can also generate new hair cells in vivo after ablation of hair cells [59, 60]. This mitotic hair cell regeneration occurs only at neonatal stages. Indeed, when hair cell ablation occurs at 1 week of age, no regeneration is observed. Such a limited ability of regeneration with a short time-window is currently being unraveled. It is already clear that both cell intrinsic (such as senescence, cell cycle alterations) as well as extrinsic factors (such as alterations in the regenerative environment) play significant roles [61]. The neonatal mouse cochlea is pre-hearing and not mature in respect to its anatomy and physiology. For example, the tunnel of Corti is not formed, and all the cells of the greater epithelial ridge (the future inner sulcus) are still present. With maturation, the organ of Corti is no longer able to regenerate, the opening of the tunnel of Corti could be responsible of the loss of this ability by separating the pool of progenitors from the hair cells. In addition, cell-cell junctions can also act to inhibit regenerative processes during postnatal development. Indeed, there is a changing expression of connexins corresponding to a maturation of gap junctions between supporting cells contributing to antagonizing proliferation (reviewed in [62]). In parallel to this cochlear anatomy modification, many changes in cell signaling occur within the postnatal organ of Corti and contribute to a decreased regenerative capacity. Molecular Pathways Involved in Hair Cell Regeneration During cochlea formation, as mentioned above, Notch signaling is very important for the specification of supporting cells versus hair cells. Similarly, Notch inhibition, either in conditional knock-out mice or by treatment with γ-secretase inhibitors, enhances supporting cells proliferation and formation of new hair cells in the perinatal cochlea [63]. Moreover, treatment with γ-secretase inhibitors in vivo induces new hair cells and can cause partial recovery of hearing following noise trauma [64, 65]. However, a recent study showed that the response of supporting cells to Notch inhibition drops dramatically during the first postnatal week in mice, concomitant with a down-regulation of many components of the Notch signaling pathway [66]. This suggests that manipulating Notch pathway alone is unlikely to promote significant hair cell regeneration in the postnatal/adult organ of Corti, and that supplementary interventions should be considered. Indeed, recent studies are much more focused on manipulation of at least two crucial signaling pathways involved in cochlear development. Activation of Wnt canonical pathway is also an interesting strategy for hair cell regeneration. Indeed, upon genetic or chemical (using GSK3β inhibitor) β-catenin stabilization, Lgr5-positive progenitor cells are able to re-enter in proliferation and generate new hair cells [67, 68]. Wnt activation followed by Notch inhibition strongly promotes the mitotic regeneration of new hair cells in both normal and neomycin-damaged cochleae [69]. However, the newly generated hair cells still underwent incomplete maturation. A combined activation of Wnt pathway, through β-catenin overexpression, with Notch knock-down and forced expression of Atoh1 in Lgr5-positive cells enhances greatly the formation of hair cells and the expression of genes implicated in hair cells maturation [70]. The proliferative state of Lgr5+ cells could be due to the activation of Wnt canonical pathway and the inhibition of Notch pathway, while the differentiation into hair cells is triggered by ectopic expression of Atoh1. Indeed, ectopic activation of Atoh1 induces new hair cells in young postnatal mice [71, 72]. Moreover, in the young adult deafened guinea pig, forced expression of Atoh1 is able to induce hair cell regeneration and hearing threshold [73]. However, only a subset of these cells and at early postnatal stages is able to give rise to new hair cells, unraveling a more complex genetic regulation, and the cells produced do not always reach terminal differentiation, as Atoh1 should be lowered at the end of the differentiation process [74]. Nevertheless, the reactivation of proliferation and differentiation cues is able to form hair cells from surrounding supporting cells, but it appears that there is a tight interplay between different signaling molecules. Ephrins and their receptors Eph also contribute to supporting cell differentiation into hair cells. Indeed, EphA4 receptor is present in hair cells while Ephrin-B2 is present in supporting cells [75]. This complementary pattern of expression is necessary for the establishment of compartment boundary between hair cells and supporting cells. When this Ephrin signaling is disrupted, using either Ephrin-B2 conditional knockout mice, shRNA-mediated gene silencing or soluble inhibitors, the organ of Corti harbors supernumerary hair cells that are generated from direct supporting cells transdifferentiation. Further studies using lineage tracing experiments are needed to rigorously validate this hypothesis. Importantly, those new hair cells directly integrate the hair cell layer and, therefore, could be more rapidly able to fit into functional circuitry. Whether Ephrin signaling acts in isolation or as part of a complex network of regulatory pathways remains to be determined. Interestingly, Ephrin-B2 and Notch are expressed in similar supporting cell types throughout the development [35]. Ephrin-B2 is a direct Notch target whose expression is induced by Notch signaling [76]. Therefore, following Notch lateral inhibition, Ephrin-B2 could be required to segregate the supporting cells from adjacent hair cells. Conclusion In mammals, it has been described that hair cells do not regenerate, impairing the ability to restore hearing. However, growing body of evidence has demonstrated that in particular cases, some regenerative properties can be encountered in the inner ear. Although during adulthood, few example of restoration have been found. Different signaling pathways have been characterized to have the capacity of inducing supporting cells proliferation and differentiation into hair cells. The newly formed cells express markers for hair cells and are also reached by spiral ganglion fibers, but are not yet mature and synapses are not perfectly formed. Knowing in details how the formation of hair cells is achieved is the starting point to discover new mechanisms that could help to identify the molecules that could be induced in supporting cells to allow them to transdifferentiate; and how the maturation of the organ of Corti is correlated to an inability to spontaneously regenerate. 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Selvaraj, Prabhuanand; Xiao, Lan; Lee, Cheol; Murthy, Saravana R. K.; Cawley, Niamh X.; Lane, Malcolm; Merchenthaler, Istvan; Ahn, Sohyun; Loh, Y. Peng

doi: 10.1002/stem.2511pmid: 27709799

Abstract Embryonic neurodevelopment involves inhibition of proliferation of multipotent neural stem cells (NSCs) followed by differentiation into neurons, astrocytes and oligodendrocytes to form the brain. We have identified a new neurotrophic factor, NF-α1, which inhibits proliferation and promotes differentiation of NSC/progenitors derived from E13.5 mouse cortex. Inhibition of proliferation of these cells was mediated through negatively regulating the Wnt pathway and decreasing β-catenin. NF-α1 induced differentiation of NSCs to astrocytes by enhancing Glial Fibrillary Acidic Protein (GFAP) expression through activating the ERK1/2-Sox9 signaling pathway. Cultured E13.5 cortical stem cells from NF-α1-knockout mice showed decreased astrocyte numbers compared to wild-type mice, which was rescued by treatment with NF-α1. In vivo, immunocytochemistry of brain sections and Western blot analysis of neocortex of mice showed a gradual increase of NF-α1 expression from E14.5 to P1 and a surge of GFAP expression at P1, the time of increase in astrogenesis. Importantly, NF-α1-Knockout mice showed ∼49% fewer GFAP positive astrocytes in the neocortex compared to WT mice at P1. Thus, NF-α1 is critical for regulating antiproliferation and cell fate determination, through differentiating embryonic stem cells to GFAP-positive astrocytes for normal neurodevelopment. Carboxypeptidase E, Neurotrophic factor-α1, Astrocytes, Stem cell, Wnt pathway Significance Statement Embryonic development of the central nervous system is tightly regulated by trophic factors synthesized and secreted by local cells, including multipotent neural stem cells (NSCs). We discover a new neurotrophic factor (NF-α1) expressed in mouse embryonic NSCs which inhibits self-proliferation and promotes their differentiation specifically to astrocytes versus neurons (both majority functional cells in brain). NF-α1 inhibits NSC proliferation by decreasing β-catenin, a Wnt pathway molecule which enhances cell growth. NF-α1 increases NSC differentiation into astrocytes by activating ERK1/2-Sox9 signaling pathway. Genetically engineered mice lacking NF-α1 have fewer astrocytes and cognitive deficits. Thus, NF-α1 is key in embryonic neural development. Introduction Embryogenesis is a complex process involving multiple developmental events tightly regulated at various levels [1]. One important stage in embryogenesis is the neural development process that leads to the formation of the central nervous system, which is carefully orchestrated by a series of timed genetic events. At specific times, certain genes are activated and then turned off when not needed, and these landmarks are regulated by transiently expressed transcription factors. Numerous studies have identified growth factors and transcription factors and their signaling pathways that mediate neural induction and differentiation [2–4]. Recently, studies revealed a number of proteins and transcription factors that are responsible for controlling the proliferation of newly formed neural precursors and for specification of multipotent neural plate stem cells to yield neural progenitors, which ultimately differentiate into neurons and glia cells to form the brain [3]. Neural stem cells (NSCs) are usually located in the sub-ventricular zone of the developing neocortex. Some NSCs and neural progenitors are also present in the adult brain, primarily in the dentate gyrus of the hippocampus and the subventricular zone of the lateral ventricle [3, 5]. NSCs are multipotent self-renewing cells and give rise to a number of progenitors, which then differentiate into neurons, astrocytes or oligodendrocytes [6]. They first undergo inhibition of proliferation (cell cycle arrest) and then differentiate into the different cell types. Generally, inhibition of proliferation and differentiation are mediated by different factors, rather than a single protein. While many factors for the promotion of proliferation and differentiation of NSCs have been identified, the mechanisms underlying the inhibition of proliferation of these cells are less well explored. To study the role of stem cells in embryonic development of the nervous system, efforts have focused on producing a population of NSCs in vitro that can be manipulated to yield differentiated cells found in the brain [5, 7]. Research has led to identification of many trophic factors (such as fibroblast growth factor, brain derived neurotrophic factor and transforming growth factor-beta) that interact with their respective receptors on NSCs. This triggers signaling pathways such as Wnt, Notch, Sonic hedgehog, BMP, Ras/MAPK and JAK/STAT/FGF to promote proliferation and/or differentiation to specific cell types during embryonic development [8–15]. Binding of the appropriate ligands to their signaling receptors leads to activation of transcription factors or coactivators, such as β-catenin, Hes, Sox, Gli, Smad, and Stat proteins, that regulate the downstream genes involved in the induction and differentiation of NSCs [15–17]. Other factors derived from the NSC niche known to modulate the self-renewal, differentiation capacity, and survival of differentiated NSCs include BDNF, LIF or CNTF, and some vitamin derivatives, for example, retinoic acid and vitamin D3 (in vitro) [18–23]. Molecules such as GDF11, IL-17, urocortin, and homocysteine are involved in inhibiting the proliferation of NSCs during development but not in promoting differentiation [24–27]. Recently, we found a new neurotrophic factor, neurotropic factor-α1 (NF-α1), also known as carboxypeptidase E (CPE) that is highly expressed in adult NSCs in the subventricular niche of mice [28]. It has effects on inhibiting proliferation of neurospheres [28] and, because it is also expressed during early embryonic development, could be important in embryonic neural differentiation [29]. CPE/NF-α1-knockout mice are obese, infertile, and have neurological disorders [30]. NF-α1 mRNA is differentially expressed in various regions at early embryonic stages of the rat and is especially high in brain and spinal cord [29, 31]. Various nonenzymatic roles of CPE/NF-α1 have also been found: it is a sorting receptor that targets proneuropeptides to the regulated secretory pathway and the cytoplasmic tail of the transmembrane form of CPE facilitates secretory vesicle movement in neuroendocrine cells [30, 32, 33]. Additionally, in vitro studies indicate that NF-α1 is a powerful neuroprotectant. Exogenous addition of recombinant NF-α1 rescued embryonic cortical rat neurons from oxidative stress in vitro [34]. Mice subjected to mild chronic restraint stress showed increased NF-α1 expression, leading to enhanced levels of BCL2, a pro-survival protein, in the hippocampus to protect neurons from stress-induced neurodegeneration [35]. While there has been a report indicating the expression and function of NF-α1/CPE in pro-neuropeptide processing [29] late rat embryos the function of NF-α1 in antiproliferation and determining cell fate during early embryonic development has not been explored. In the present study, we investigated the role of NF-α1 as both an antiproliferation and differentiation factor in NSCs. Materials and Methods Animals All animals were given food and water ad libitum in a humidity and temperature controlled room under a 12-hour light: dark cycle. Mice (3-12 weeks old) were purchased from Taconic Farms, Inc., (Derwood, MD, www.taconic.com). Timed pregnant mice were generated by mating C57BL6 mice in our animal facility and embryonic 13.5 or P1 NF-α1-wild type (WT)/NF-α1-knockout (KO) pups were produced by mating male and female heterozygote mice (since homozygotes are infertile [36]) at the NIH animal facility. All animal procedures were approved by the Animal Care and Use Committee, NICHD, NIH. Recombinant NF-α1 Purified recombinant wild type NF-α1 and enzymatically inactive NF-α1 (E300Q) mutant were custom generated by GenScript USA Inc, Piscataway, NY, www.genscript.com as previously described [34]. In Situ Hybridization Animals and tissue: All embryos were generated from timed-pregnant C57BL6 female mice. Data reported are from at least one litter for each age group and at least 3 embryos at each age. The embryos (E10, E11, and E12) were collected and freshly frozen, or embedded directly in OCT compound without prior fixation. Sagittal cryostat sections were prepared as described [29, 37]. In situ Hybridization: A cRNA probe was generated using linearized pGEM-T-Easy plasmid vector containing 980 bp corresponding to nucleotides 540–1520 of murine CPE mRNA (NM_013494) and labeled with 35S-UTP. The details of the hybridization procedure are described elsewhere [38, 39]. The slides from all animals were processed together to eliminate differences from interassay variation. Quantitative RT-PCR of NF-α1 Total RNA isolation, cDNA synthesis and qPCR was performed as described previously [40]. The qPCR cycling conditions were: 10-minutes denaturation at 95°C and 40 cycles of DNA synthesis at 95°C for 15 seconds and 60°C for 1 minute and the results analyzed using SDS 1.9.1 software (Applied system, Foster City, CA, www.appliedbiosystems.com). Primer sequences for mouse CPE/NF-α1 and 18S RNA can be found in Supporting Information Table S1. All qPCRs were performed in triplicates and the relative amount of CPE/NF-α1 mRNA was normalized to 18S rRNA. Preparation of Mouse E13.5 Cortical Cells Preparation of E13.5 cortical cells has been described previously [41]. The final cell pellet was resuspended in Dulbecco's modified Eagle's medium (DMEM)/F12 (Sigma Aldrich, St. Louis, MO, www.sigmaaldrich.com) containing B27 (1X) (Gibco, Waltham, MA, www.thermofisher.com), Penicillin-Streptomycin (1X) (Gibco), 2 μg/ml heparin (Sigma Aldrich, St.Louis, MO, www.sigmaaldrich.com), and 15 mM HEPES (Gibco,Waltham, MA, www.thermofisher.com), and used in proliferation and differentiation studies. Neurosphere Culture Preparation, Proliferation and Differentiation Assays Cortical cells were cultured as described previously [7, 41]. Cells were grown for 5-7 days at 37°C in the presence of 5% CO2, with supplementation of additional EGF (20 ng/ml)/bFGF2 (10 ng/ml) every 2 days. Proliferation Assay: cells were cultured in 96-well plates at a density of 500 cells per 100 µl in the presence of growth factors (EGF/bFGF), treated with or without 200 nM recombinant NF-α1 on day 0 and grown for 5 days. At the end of 5 days, images were taken to count the number and size of the neurospheres using imageJ software. Ethynyldeoxyuridine (Edu) incorporation method: Five day neurosphere cultures were treated with or without NF-α1 (200 nM), incubated with 10 µM EdU for 1 hour and immediately dissociated to single cells using Accutase (StemPro Accutase, Life Technologies, Waltham, MA, www.thermofisher.com) followed by neutralization by trypsin inhibitor from Glycine max (soybean) (Sigma Aldrich, St.Louis, MO, www.sigmaaldrich.com). Cells were plated on poly-l-lysine coated chamber slides and grown in DMEM/F12 media with 1% FBS (no growth factors) overnight at 37°C. The cells were then processed according to the manufacturer's instructions to visualize nuclear EdU (Click-it EdU Imaging Kit, Invitrogen, Life Technologies). Slides were examined using a fluorescence microscope (Nikon Eclipse 80i, Tokyo, Japan, www.nikonusa.com, Waltham, MA, www.thermofisher.com). Nine images (x10 magnification) from randomly selected fields containing ∼55-60 cells were assessed for EdU positive staining. Differentiation Assay: 7 day neurosphere cultures were dissociated into single cells, plated at the density of 50,000 cells per well in a 2 well chamber slide coated with poly-l-lysine, and cultured in DMEM/F12 media with 1% FBS (no growth factors). Cells were then treated with or without 200 nM NF-α1 and grown for an additional 5 or 10 days and then analyzed by immunocytochemistry. Phenotypic Characterization of Differentiated Cells by Immunocytochemistry Immunocytochemistry was performed using standard protocols and examined using a fluorescence microscope (Nikon Eclipse 80i, Tokyo, Japan, www.nikonusa.com). Cell types analyzed were astrocytes (GFAP), neurons (Tuj1 or βIII Tubulin), oligodendrocytes (CNPase) and nestin (Nestin, a stem cell marker). For quantification, cells in 8-10 images taken at x20 magnification from randomly selected fields (∼45-50 cells per field) were counted and averaged. Treatment of Neural Stem/Progenitor Cellswith NF-α1 with or without ERK Inhibitor NSCs from dissociated neurospheres were plated on poly-l-lysine coated dishes and incubated with 200 nM NF-α1 for 0, 15, 30, 60 and 180 minutes, after which the cells were harvested and lysates analyzed by Western blot for p-ERK and total-ERK. Alternatively, cultured NSCs were preincubated with or without the ERK inhibitor, U0126 (5 µM) (Sigma Aldrich, St.Louis, MO, www.sigmaaldrich.com), for 30 minutes after which 200 nM NF-α1 was added and incubated for a further 30 minutes. The cells were then harvested and the cell lysates analyzed by Western blot for p-ERK and total-ERK. Inhibition of Sox9 in NSCs Using RNA Interference Double-stranded small-interfering RNAs (siRNAs) and control (scramble) RNA for mouse sox9 were obtained commercially (Santa Cruz Biotechnology Inc, Santa Cruz, CA, www.scbt.com). Using the RNAiMAX (Life Technologies, Waltham, MA, www.thermofisher.com) transfection procedure, neural stem/progenitor cells plated on poly-l-lysine coated cells, were transfected with Sox9/scramble siRNA and treated with or without NF-α1. After 48 hours, the cells were harvested and extracted for RNA which was used to prepare cDNA. RT-PCR was performed to study mRNA levels of Sox9 and Gfap. The primer sequences for mouse sox9 and Gfap mRNA can be found in Supporting Information Table S1. The relative amount of Sox9 and Gfap mRNA was normalized to 18S rRNA. For detailed RT-PCR protocol and cycling conditions please refer to the above method section. Immunoprecipitation of Embryonic Tissue To check whether NF-α1 was expressed at the protein level during early embryonic development, we harvested embryos from pregnant mice at different developmental stages. We pooled 4-5 embryos/stage for immunoprecipition and Western blot. Briefly lysates from each embryonic stage (whole embryos: E8.5, E10.5, and E11.5 and head alone: E12.5 and E13.5) were immunprecipitated [42] using rabbit polyclonal anti-NFα-1 (generated in our laboratory) and analyzed by Western blot with mouse monoclonal anti-NF-α1 (1:2,000) (BD bioscience, San Jose, CA, www.bdbiosciences.com). Western Blot Cell lysates were prepared from E13.5, E14.5, E15.5, E16.5, E17.5, P1 cortex, neurospheres, and differentiated cells as described previously [34]. Twenty microgram of protein from the supernatants were analyzed by standard Western blotting procedures using nitrocellulose. Protein bands were visualized and quantified by the Odyssey infrared imaging system and software v2.1 (LI-COR, Lincoln, NE, www.licor.com). The protein expression level for each sample was normalized to β-actin. A complete list of the antibodies used can be seen in Supporting Information Table S2. Immunohistochemistry of Mouse Brains For immunohistochemistry (IHC) of E14.5, E15.5, E16.5, E17.5 and P1 mouse brains, pups were sacrificed by decapitation and processed as described previously [43]. The sections were processed also as described previously [43] and incubated with primary antibodies listed in Supporting Information Table S2. Slides were examined using a fluorescence microscope (Nikon Eclipse 80i, Tokyo, Japan, www.nikonusa.com). The cortical layer was examined for astrocyte (GFAP), NF-α1 and neuron (MAP2) immunostaining intensity. Coronal sections (4 consecutive sections, 16 µm thick from each embryo were used for quantification, totaling 12 sections per phenotype from 3 NF-α1-WT and 3 NF-α1-KO pups or 3 WT mice at each developmental stage, from 3 independent litters). The intensity of the GFAP, NF-α1 and MAP2 immunostaining within 8 rectangular boxed fields (400 x 166 µm) (8 random areas/section, 4 sections/embryo, N = 3 embryo/phenotype) in each section representing the whole neocortex was analyzed and quantified using imageJ software. Low magnification (×10) images were used to show immunostained cell pictures and high magnification (×20) images were used for quantification. The same number of coronal sections was used for counting individual GFAP+ and MAP2+ cells in 3 NF-α1-WT and 3 NF-α1-KO pups. For GFAP- and MAP2- immunopositive cell counting, 2 images/section, in the neocortical region [squared area, 140 x 140 µm] were captured by a confocal microscope (Zeiss LSM 510 Inverted Meta, Oberkochen, Germany, www.zeiss.com) with ×60 magnification and oil immersion lens. High magnification (×60) images were used for counting the immunostained cells manually in each square area. Statistical Analysis Data were analyzed by Student's paired, unpaired t test and one-way analysis of variance (ANOVA) followed by Tukey's multiple comparisons tests where noted. Significance was set at p < .05. Results Temporal and Spatial Expression of NF-α1 in Mice during Embryonic Development Using qRT-PCR, NF-α1 mRNA expression was detected in all embryonic stages analyzed (E5.5–E14.5 and E17.5 and P1). For clarity, since the earliest stage that we could dissect was E5.5, the levels of NF-α1 mRNA at all other embryonic stages were normalized to this level (Fig. 1A). NF-α1 expression increased from E6.5-E8.5 and gradually fell to very low levels at E10.5 and E11.5. This was followed by a rapid increase from E12.5 to E14.5 and at E17.5 (whole body). Head alone samples also showed an increase from E12.5 to P1. In situ hybridization, using a 35S-UTP-labeled mouse NF-α1 probe, showed that at E10.5, NF-α1 mRNA was highly expressed in the telencephalon, diencephalon, and spinal cord regions (Fig. 1B). At E11.5 and E12.5, in addition to those brain regions seen at E10.5, there was expression in the mesencephalon of the brain, heart, and in somites (Fig. 1B). Western blot data confirmed the presence of NF-α1 protein in E8.5, E10.5, E11.5, E12.5, and E13.5 embryos (Fig. 1C). These data indicate that NF-α1 could play a role in neural development since it is expressed at the appropriate times in neural tissue in the embryo during development. Figure 1 Open in new tabDownload slide Temporal and spatial distribution of NF-α1 in embryos. (A): Bar graphs show NF-α1 mRNA expression in E6.5 embryos to postnatal day1 (P1) (head only) relative to E5.5 embryos. Values are mean ± SEM; N = 3, n = 3 per embryo stage. (B): In situ hybridization indicates NF-α1 mRNA highly expressed in embryonic brain especially di (diencephalon), te (telencephalon), som (somites), me (mesencephalon), and h (heart) (N = 3). (C): NF-α1 was immunoprecipitated with polyclonal rabbit anti-NF-α1 Ab from whole embryos (E8.5-11.5) or embryo head (E12.5 and E13.5) and probed with mouse anti-NF-α1 Ab. NF-α1 protein is detectable at early embryonic stages (E8.5, 10.5, 11.5, 12.5, and 13.5). Abbreviation: NF-α1, neurotrophic factor-α1. Figure 1 Open in new tabDownload slide Temporal and spatial distribution of NF-α1 in embryos. (A): Bar graphs show NF-α1 mRNA expression in E6.5 embryos to postnatal day1 (P1) (head only) relative to E5.5 embryos. Values are mean ± SEM; N = 3, n = 3 per embryo stage. (B): In situ hybridization indicates NF-α1 mRNA highly expressed in embryonic brain especially di (diencephalon), te (telencephalon), som (somites), me (mesencephalon), and h (heart) (N = 3). (C): NF-α1 was immunoprecipitated with polyclonal rabbit anti-NF-α1 Ab from whole embryos (E8.5-11.5) or embryo head (E12.5 and E13.5) and probed with mouse anti-NF-α1 Ab. NF-α1 protein is detectable at early embryonic stages (E8.5, 10.5, 11.5, 12.5, and 13.5). Abbreviation: NF-α1, neurotrophic factor-α1. NF-α1 Negatively Regulates the Proliferation of NSCs The early developmental expression pattern of NF-α1 prompted us to investigate its role in neuronal proliferation and differentiation, particularly in NSCs using neurospheres as a model system. To study proliferation, neocortical cells isolated from E13.5 embryos were treated with or without recombinant NF-α1 protein for 5 days. Total neurospheres generated in NF-α1-treated cells were reduced by 41% compared to controls (Control: 215.0 ± 5.03; NFα-1: 126.3 ± 3.18; n = 6, p = .0001; Fig. 2A). Moreover, the number of neurospheres less than 100-149 µm in diameter was significantly reduced in the NF-α1-treated cells compared to the controls (Control, 42.67 ± 1.45; NF-α1, 19.00 ± 1.15; n = 6, p < .001; Fig. 2B). The EdU proliferation assay revealed a small but significant decrease in neural stem/progenitor proliferation on day 5 of neurosphere cultures treated with NF-α1 compared to control cultures (Control: 40.00 ± 0.94; NFα-1: 34.80 ± 0.91; n = 5, p = .004; Fig. 2C, 2D). These data collectively indicate that exogenously added NF-α1 inhibits proliferation of NSCs. As a control analysis, both the neocortical cells and neurospheres express NF-α1 protein (Fig. 2E). Figure 2 Open in new tabDownload slide NF-α1 negatively regulates neurosphere proliferation. Neocortical cells from E13.5, were grown for 5 days in 96 well plate in the presence of growth factors (FGF2 and EGF) and treated with or without 200 nM recombinant NF-α1 at day 0. At the end of 5 days, images were taken and analyzed using ImageJ software. Exogenous addition of recombinant NF-α1 significantly reduced the numbers of neurospheres compared to control (A) and also affected the size of the neurospheres under 100-149 μm in diameter category (B) (N = 3; **, p < .004; ***, p < .0007). (C): Representative ICC pictures (x10) of untreated and NF-α1 treated cells. Scale bar = 100 µm. (D): Bar graph shows the percentage of Edu labeled cells compared to total (DAPI). NF-α1 treatment on neural stem/progenitors significantly decreased proliferation of the cells (N = 2; **, p < .004). (E): NF-α1 immunoprecipitation assay showed both the starting material (cortical cells) and the end product (neurosphere) express NF-α1 protein. The values represent the mean ± SEM, t test. Abbreviations: Edu, ethynyldeoxyuridine; NF-α1, neurotrophic factor-α1. Figure 2 Open in new tabDownload slide NF-α1 negatively regulates neurosphere proliferation. Neocortical cells from E13.5, were grown for 5 days in 96 well plate in the presence of growth factors (FGF2 and EGF) and treated with or without 200 nM recombinant NF-α1 at day 0. At the end of 5 days, images were taken and analyzed using ImageJ software. Exogenous addition of recombinant NF-α1 significantly reduced the numbers of neurospheres compared to control (A) and also affected the size of the neurospheres under 100-149 μm in diameter category (B) (N = 3; **, p < .004; ***, p < .0007). (C): Representative ICC pictures (x10) of untreated and NF-α1 treated cells. Scale bar = 100 µm. (D): Bar graph shows the percentage of Edu labeled cells compared to total (DAPI). NF-α1 treatment on neural stem/progenitors significantly decreased proliferation of the cells (N = 2; **, p < .004). (E): NF-α1 immunoprecipitation assay showed both the starting material (cortical cells) and the end product (neurosphere) express NF-α1 protein. The values represent the mean ± SEM, t test. Abbreviations: Edu, ethynyldeoxyuridine; NF-α1, neurotrophic factor-α1. NF-α1 Inhibits NSC Proliferation Through Wnt/β-Catenin Signaling Pathway To examine the possibility that NF-α1 inhibits NSC proliferation through the Wnt/β-Catenin signaling pathway, neocortical cells were grown with NF-α1 treatment at day 0. Neurosphere lysates were collected at different time points (24 hours, 72 hours, and 5 days) after NF-α1 treatment and β-Catenin protein levels were measured. After 24 hours, neurospheres treated with NF-α1 showed slightly decreased levels of β-Catenin. By 72 hours and 5 days, the levels of β-Catenin were significantly decreased (∼30%-35%) in NF-α1-treated cultures compared to controls (72 hours Control, 100.00 ± 3.76; NF-α1, 64.71 ± 3.36; n = 12, p < .0001 and 5 days Control, 100.00 ± 2.72; NF-α1, 62.50 ± 3.27; n = 6, p < .0001) (Fig. 3). Figure 3 Open in new tabDownload slide NF-α1 decreases the neurosphere proliferation through Wnt3a/β-catenin signaling. Cell lysates were prepared, at different time points (24 hours, 72 hours, and 5 days), from neurospheres grown in the presence of growth factors and treated with or without NF-α1 on day 0. Upper panels (A-C) represent Western blots of β-Catenin and β-actin at each time point. Quantification of the Western blots (D-F) shows a significant decrease in β-catenin levels in NF-α1 treated cultures at 72 hours and 5 days compared to untreated controls (E, F). N = 3; ***, p < .0001, t test. Abbreviation: NF-α1, neurotrophic factor-α1. Figure 3 Open in new tabDownload slide NF-α1 decreases the neurosphere proliferation through Wnt3a/β-catenin signaling. Cell lysates were prepared, at different time points (24 hours, 72 hours, and 5 days), from neurospheres grown in the presence of growth factors and treated with or without NF-α1 on day 0. Upper panels (A-C) represent Western blots of β-Catenin and β-actin at each time point. Quantification of the Western blots (D-F) shows a significant decrease in β-catenin levels in NF-α1 treated cultures at 72 hours and 5 days compared to untreated controls (E, F). N = 3; ***, p < .0001, t test. Abbreviation: NF-α1, neurotrophic factor-α1. NF-α1 Promotes the Differentiation of NSCs into Astrocytes Neurosphere-derived cells were cultured with or without NF-α1 and then immunostained for markers of astrocytes, neurons, and oligodendrocytes (Fig. 4A). There was a significant increase in the GFAP+ (astrocyte marker) population (∼1.4-fold), and a trend toward a decrease in the Tuj1+ (neuronal marker) population in NF-α1- treated cells compared to the controls. No change in CNPase+ (oligodendrocyte) populations was observed between the two groups (% of GFAP+ cells: Control, 42.20 ± 2.95; NF-α1, 58.00 ± 1.78; n = 5, F(5, 24) = 179.3, p < .001; % of Tuj1+ cells: Control, 26.20 ± 0.86; NF-α1, 22.20 ± 1.31; n = 5, F(5, 24) = 179.3, p > .05; Fig. 4B). Similar results were seen when a nonenzymatically active form of NF-α1 (E300Q) [44] was used (% of GFAP+ cells: Control, 43.80 ± 2.74; E300Q-NF-α1, 61.20 ± 3.39; n = 5, F(5, 24) = 134.4, p < .05; % of Tuj1+ cells: Control, 28.60 ± 1.40; NF-α1, 22.20 ± 0.58; n = 5, F(5, 24) = 134.4, p > .05; Fig. 4C), confirming that the enzymatic activity of NF-α1 is not necessary for promoting the differentiation of NSCs into astrocytes. Figure 4 Open in new tabDownload slide NF-α1 and E300Q-NF-α1 (nonenzymatic mutant of NF-α1) promotes the differentiation of neural stem/progenitors into astrocytes. Neurospheres dissociated into single cells were grown for 5 days in the presence of 1% FBS (differentiation media) and treated with or without NF-α1 or E300Q-NF-α1 on day 0. At the end of day 5 single immunocytochemistry (ICC) staining for astrocytes (anti-GFAP), neurons (anti-β-III tubulin), and oligodendrocytes (CNPase), as well double immunostaining for astrocyte (anti-GFAP) and nestin (anti-Nestin) was carried out. (A): Representative ICC pictures (x20), of control (left) and NF-α1 treated neural stem/progenitor cells (right). Scale bar = 100 µm. (B, C): Bar graph shows the percentage of each cell phenotype population. Either NF-α1 or E300Q-NF-α1 treatment on neural stem/progenitor cells significantly increased the number of astrocytes (***, p < .0001) (open bars), without significantly altering the percentage of the neuron (shaded bars) and oligodendrocyte (solid bars) populations. (D): Representative ICC pictures of control (untreated) (left) and NF-α1 treated cells double immunostained for Nestin and GFAP (right). (E): Bar graph shows the percentage of differentiated phenotype populations. NF-α1 treatment on neural stem/progenitors significantly increases differentiation into GFAP+ alone, concomitant with a reduction in the Nestin+/GFAP+ cells population (***, p < .0001) without significantly altering the percentage of Nestin+ population. N = 3, the values represent the mean ± SEM, one-way ANOVA (Tukey's multiple comparison test). Abbreviations: GFAP, glial fibrillary acidic protein; NF-α1, neurotrophic factor-α1. Figure 4 Open in new tabDownload slide NF-α1 and E300Q-NF-α1 (nonenzymatic mutant of NF-α1) promotes the differentiation of neural stem/progenitors into astrocytes. Neurospheres dissociated into single cells were grown for 5 days in the presence of 1% FBS (differentiation media) and treated with or without NF-α1 or E300Q-NF-α1 on day 0. At the end of day 5 single immunocytochemistry (ICC) staining for astrocytes (anti-GFAP), neurons (anti-β-III tubulin), and oligodendrocytes (CNPase), as well double immunostaining for astrocyte (anti-GFAP) and nestin (anti-Nestin) was carried out. (A): Representative ICC pictures (x20), of control (left) and NF-α1 treated neural stem/progenitor cells (right). Scale bar = 100 µm. (B, C): Bar graph shows the percentage of each cell phenotype population. Either NF-α1 or E300Q-NF-α1 treatment on neural stem/progenitor cells significantly increased the number of astrocytes (***, p < .0001) (open bars), without significantly altering the percentage of the neuron (shaded bars) and oligodendrocyte (solid bars) populations. (D): Representative ICC pictures of control (untreated) (left) and NF-α1 treated cells double immunostained for Nestin and GFAP (right). (E): Bar graph shows the percentage of differentiated phenotype populations. NF-α1 treatment on neural stem/progenitors significantly increases differentiation into GFAP+ alone, concomitant with a reduction in the Nestin+/GFAP+ cells population (***, p < .0001) without significantly altering the percentage of Nestin+ population. N = 3, the values represent the mean ± SEM, one-way ANOVA (Tukey's multiple comparison test). Abbreviations: GFAP, glial fibrillary acidic protein; NF-α1, neurotrophic factor-α1. Neurosphere-derived cells cultured with or without NF-α1 were double immunostained for Nestin and GFAP. The majority of the NSCs stained for both Nestin and GFAP (Fig. 4D). A small portion of the stem cell population that stained for Nestin alone showed no difference between the NF-α1 treated and untreated groups in 5 days cultures. However, a significant increase (∼2-fold) in GFAP+ alone (% of cells: Control, 15.17 ± 0.83; NF-α1, 29.50 ± 1.85; n = 6, F(5, 30) = 314.4, p < .0001) and a decrease (∼1.18-fold) in Nestin+/GFAP+ cells (% of cells: Control, 60.50 ± 1.64; NF-α1, 51.50 ± 1.64; n = 6, F(5, 30) = 314.4, p < .0001) cells was observed in NF-α1-treated compared to untreated cultures (Fig. 4E). Similar results were observed in 10-day cultures (data not shown). NF-α1 Induces NSC Differentiation to Astrocytes During Embryonic Neural Development We performed loss-of-function and gain-of-function experiments in neurosphere-derived cells generated from NF-α1-KO and NF-α1-WT E13.5 embryos and subjected to the differentiation protocol. Neurosphere-derived cells from NF-α1-KO and NF-α1-WT embryos were cultured with or without NF-α1 and immunostained for markers of astrocytes, neurons, and oligodendrocytes. Figure 5A, 5B (upper panels, representative ICC) and Figure 5C--5E (bar graphs, quantification) show that NF-α1-KO mice had ∼30% fewer GFAP+ cells than WT mice (Fig. 5C, open bars,% of GFAP+ cells: KO control, 34.33 ± 2.29; WT control, 49.17 ± 1.62; n = 6, F(5,30) = 121.2, p < .0001) and ∼34% more Tuj1+ cells than WT mice (% of Tuj1+ cells: KO control, 52.17 ± 1.90; WT control, 34.67 ± 3.10; n = 6, F(5,30) =121.2, p < .0001; Fig. 5D, open bars). Moreover, there was a higher % of Tuj1+ neurons (52%) than GFAP+ cells (34%) in the KO mice (% of Tuj1+ cells: KO control, 52.17 ± 1.90 vs % of GFAP+ cells: KO control, 34.33 ± 2.29; n = 6, p < .0001, t test) (compare open bars in Fig. 5D vs. 5C for KO), whereas this distribution appeared to be reversed in the WT cells. This differentiation profile was reversed upon treatment of the cells from NF-α1-KO mice with recombinant NF-α1, resulting in higher % of GFAP+ cells (48%) than Tuj1+ cells (40%), (% of GFAP+ cells: NF-α1 treated; 47.00 ± 2.25 and % of Tuj1+ cells: NF-α1 treated; 39.67 ± 1.961, n = 6, p = .03, t test; compare solid bars in Fig. 5C vs. 5D for KO). Irrespective of KO and WT derived neural progenitors, NF-α1 treatment showed a significant increase in GFAP+ cells and decrease in Tuj1+ cells. Figure 5 Open in new tabDownload slide NF-α1-KO/NF-α1-WT generated neural stem/progenitors indicate a modulatory role of NF-α1 in altering the differentiation cell phenotype. Neural stem/progenitors generated from NF-α1-KO and NF-α1-WT were grown for 5 days in differentiation media and treated with or without NF-α1 on day 0. At the end of day 5 the cells were stained and analyzed for GFAP, β-III tubulin and CNPase positive cells. Representative ICC pictures (x20) from NF-α1-KO (A) and NF-α1-WT (B) cells. Scale bar = 100 µm. Left and right side panels indicate controls and NF-α1 treated cells. (C-E) show bar graph analysis comparing between NF-α1-KO and NF-α1-WT for individual cell (GFAP+, Tuj1+ and CNPase+) phenotypes. Differentiated NPCs derived from NF-α1-KO (control) showed a significant ∼30% decrease in GFAP+ cells (C) and ∼34% increase in Tuj1+ cells (D) when compared to NF-α1-WT controls. Irrespective of NF-α1-KO and NF-α1-WT cultures, NF-α1 treatment increased GFAP+ cells and decreased Tuj1+ cells (C, D). +, p = .03; #, p < .001; ***, p < .0001, N = 3, the values represent the mean ± SEM, one-way ANOVA (Tukey's multiple comparison test) and t test. Abbreviations: GFAP, glial fibrillary acidic protein; NF-α1, neurotrophic factor-α1; NF-α1-WT, NF-α1-wild type; NF-α1-KO, NF-α1-knockout. Figure 5 Open in new tabDownload slide NF-α1-KO/NF-α1-WT generated neural stem/progenitors indicate a modulatory role of NF-α1 in altering the differentiation cell phenotype. Neural stem/progenitors generated from NF-α1-KO and NF-α1-WT were grown for 5 days in differentiation media and treated with or without NF-α1 on day 0. At the end of day 5 the cells were stained and analyzed for GFAP, β-III tubulin and CNPase positive cells. Representative ICC pictures (x20) from NF-α1-KO (A) and NF-α1-WT (B) cells. Scale bar = 100 µm. Left and right side panels indicate controls and NF-α1 treated cells. (C-E) show bar graph analysis comparing between NF-α1-KO and NF-α1-WT for individual cell (GFAP+, Tuj1+ and CNPase+) phenotypes. Differentiated NPCs derived from NF-α1-KO (control) showed a significant ∼30% decrease in GFAP+ cells (C) and ∼34% increase in Tuj1+ cells (D) when compared to NF-α1-WT controls. Irrespective of NF-α1-KO and NF-α1-WT cultures, NF-α1 treatment increased GFAP+ cells and decreased Tuj1+ cells (C, D). +, p = .03; #, p < .001; ***, p < .0001, N = 3, the values represent the mean ± SEM, one-way ANOVA (Tukey's multiple comparison test) and t test. Abbreviations: GFAP, glial fibrillary acidic protein; NF-α1, neurotrophic factor-α1; NF-α1-WT, NF-α1-wild type; NF-α1-KO, NF-α1-knockout. NF-α1 Promotes NSC Differentiation via MAPK/MEK-Sox9 Signaling Pathway Signaling pathways were examined in neurosphere-derived cultures treated with or without NF-α1 which included notch, hedgehog, SMAD (data not shown) and MAPK/MEK. Only MAPK/MEK showed a response to NF-α1 treatment (Fig. 6A). NF-α1 treatment led to increased phosphorylation of ERK1/2, a component of the MAPK/MEK signaling pathway, in a time-dependent manner with a maximum increase at 15 minutes compared to the control cells (% protein expression: Control (15 minutes), 100.00 ± 13.10; NF-α1, 951.2 ± 83.45; n = 5, F(4,20) = 69.54, p < .0001) (Fig. 6B). Furthermore, we detected maximum upregulation of the expression of the ERK-targeted downstream transcription factor Sox9 at 15 and 30 minutes, concomitant with the increase of pERK1/2, in NF-α1-treated cells (% protein expression: Control (15 minutes), 100.00 ± 7.85; NF-α1, 242.6 ± 46.88; n = 5, F(4,20) =3.857, p < .05) (Fig. 6C, 6D). In the presence of the ERK inhibitor, U0126, NF-α1-induced pERK was reduced by ∼3-fold (NF-α1, 140.5 ± 6.65; U0126 + NF-α1, 47.75 ± 6.84; n = 4, F(3,12) = 59.03, p < .0001), confirming that NF-α1 signals through the ERK pathway. NF-α1 increased Sox9 protein levels by ∼1.3-fold compared to untreated control, whereas U0126 decreased Sox9 levels by ∼2.4-fold compared to the NF-α1 treated cells (NF-α1, 130.10 ± 7.59; U0126 + NF-α1, 53.42 ± 5.48; n = 4, F(3,12) =36.42, p < .0001; Fig. 6E compare Sox9 lanes 2 and 4). RT-PCR data from Sox9 knockdown experiments (Fig. 6F, upper panel) showed that Sox9 mRNA levels were significantly downregulated in si-Sox9 RNA transfected NSCs compared to si-scrambled RNA (control) (si-scrambled, 1.00 ± 0.16; si-Sox9, 0.63 ± 0.15; n = 8, F(3,28)=74.23, p < .05). A significant increase in fold change of Sox9 and GFAP expression was found in control samples by treatment with NF-α1, (Sox9 mRNA fold change: si-scrambled, 1.00 ± 0.16; si-scrambled + NF-α1, 1.63 ± 0.10; n = 8, F(3,28)=74.23, p < .0001 and GFAP mRNA fold change: si-scrambled, 1.00 ± 0.13; si-scrambled + NF-α1, 1.86 ± 0.12; n = 8, F(3,28) = 33.17, p < .0001), but this effect of NF-α1 was absent in the si-Sox9 RNA transfected cells (Fig. 6F, lower panel). Figure 6 Open in new tabDownload slide NF-α1 increases Sox9 mRNA and protein levels in NPCs signaling via the ERK pathway. (A, C): Neural stem/progenitors were cultured for the indicated periods of time in the presence or absence of 200 nM NF-α1. Total cell lysates were examined by Western blot analysis using pERK and total ERK antibody. NF-α1 increased pERK and Sox9 protein ∼9 and ∼2.4-fold respectively at 15 minutes and decreased with time compared with the Control group. N = 3; values are mean ± SEM; *, p < .05; ***, p < .0001. (B, D): Represents the bar graph of the Western blot results (A, C). (E): ERK inhibitor U0126 treatment of neural stem/progenitors for 30 minutes blocked the NF-α1 induced pERK signaling by ∼3-fold. NF-α1 increased Sox9 protein levels by ∼1.3-fold in the absence of U0126. U0126 prevented the increase and reduced the levels of Sox9 by ∼2.4-fold. N = 2; values are mean ± SEM, *, p < .05; **, p < .001; ***, p < .0001. (F): Neural stem/progenitors were transfected with si-scrambled and si-Sox9 RNA, followed by NF-α1 treatment and cultured for 48 hours. Sox9 mRNA expression was significantly reduced in si-Sox9 treated cells compared to si-scrambled. Sox9 and GFAP mRNA levels were significantly increased in NF-α1 treated scrambled cells compared to untreated. N = 2; values are mean ± SEM; ****, p < .0001, one-way ANOVA (Tukey's multiple comparison test). Abbreviation: NF-α1, neurotrophic factor-α1. Figure 6 Open in new tabDownload slide NF-α1 increases Sox9 mRNA and protein levels in NPCs signaling via the ERK pathway. (A, C): Neural stem/progenitors were cultured for the indicated periods of time in the presence or absence of 200 nM NF-α1. Total cell lysates were examined by Western blot analysis using pERK and total ERK antibody. NF-α1 increased pERK and Sox9 protein ∼9 and ∼2.4-fold respectively at 15 minutes and decreased with time compared with the Control group. N = 3; values are mean ± SEM; *, p < .05; ***, p < .0001. (B, D): Represents the bar graph of the Western blot results (A, C). (E): ERK inhibitor U0126 treatment of neural stem/progenitors for 30 minutes blocked the NF-α1 induced pERK signaling by ∼3-fold. NF-α1 increased Sox9 protein levels by ∼1.3-fold in the absence of U0126. U0126 prevented the increase and reduced the levels of Sox9 by ∼2.4-fold. N = 2; values are mean ± SEM, *, p < .05; **, p < .001; ***, p < .0001. (F): Neural stem/progenitors were transfected with si-scrambled and si-Sox9 RNA, followed by NF-α1 treatment and cultured for 48 hours. Sox9 mRNA expression was significantly reduced in si-Sox9 treated cells compared to si-scrambled. Sox9 and GFAP mRNA levels were significantly increased in NF-α1 treated scrambled cells compared to untreated. N = 2; values are mean ± SEM; ****, p < .0001, one-way ANOVA (Tukey's multiple comparison test). Abbreviation: NF-α1, neurotrophic factor-α1. Expression of NF-α1 in GFAP+ in Brain During Development from E14.5 to P1 Western blot analysis (Fig. 7A) showed that the expression of NF-α1 in brain gradually increased from E14.5 to P1 (Fig. 7B). GFAP protein (Figs. 7A, 7C) expression was at a low level between E14.5 and 17.5 with a surge occurring at P1 at time of increased astrogenesis. Immunohistochemical staining of expression of NF-α1 (Fig. 7D) and GFAP (Fig. 7E) from E14.5 to P1 mice showed similar pattern of changes as the Western blot analysis (see images in Supporting Information Fig. 1). Expression of NF-α1 from immunostained sections showed gradual increase in intensity from E14.5 to P1 (Fig. 7D), while GFAP-immunoreactive staining showed low intensity from E14.5 to E17.5 and a surge at P1 (Fig. 7E). High magnification images showed colocalization of GFAP with NF-α1 in astrocytes at P1 (Fig. 7F). Figure 7 Open in new tabDownload slide Developmental expression of NF-α1 and GFAP and reduced astrocyte population observed in NF-α1-KO compared to NF-α1-WT in neocortex. Brains from E14.5 to P1 mice were extracted and protein analyzed by Western blot. Neocortex coronal sections (16 µm) from E14.5-P1 mice and NF-α1-KO and -WT mice at P1 stage were immunostained for NF-α1, GFAP (astrocytes) or MAP2 (neuron). (A): Western blot and bar graphs of NF-α1 (B) and GFAP (C) showing quantification of protein expression in brain during development. Each lane contains 2 brains pooled. NF-α1 expression increased gradually from E14.5 to P1 (B), while GFAP showed a major increase at P1(C), corresponding to the time of increased astrocyte differentiation. F(4,5)= 5.27 for (B) and F(4,5)=152.2 for (C), values are mean ± SD, *, p < .05 and **, p < .01, one way ANOVA (Tukey's multiple comparison test). (D, E): Developmental expression of NF-α1 (D) and GFAP (E) was quantified by immunohistochemistry (IHC) in brain sections from E14.5 to P1 mice (see Supporting Information Fig. 1 and methods). Eight random areas/section in the neocortex from 4 sections per brain and 3 brains for each stage were quantified. The rectangular box in the immunostained panels is representative of the size of the box (400 x 166 µm) used to measure the intensity of NF-α1 and GFAP staining (Supporting Information Fig 1). Expression of NF-α1 from immunostained sections showed a gradual increase in intensity from E14.5 to P1 (D), while GFAP immunoreactive staining showed low intensity from E14.5 to E17.5 and a surge at P1 (E). F(4,10)=39.73 for (D) and F(4,10)= 289.4 for (E), respectively, values are mean ± SEM, *, p < .05 and **, p < .01, N = 3, one way ANOVA (Tukey's multiple comparison test). (F): IHC showing the colocalization of NF-α1 (red) and GFAP (green) in astrocytes (see arrows in merged image) at P1. Scale bar = 20 μm (G–L): Eight random areas/section from four consecutive sections/brain, 12 total sections per phenotype from 3 independent litters (P1 mice) were used to quantify GFAP and MAP2 staining in the neocortex of WT and KO mice. The rectangular box in the immunostained panels is representative of the size of the area in the neocortex used to measure the intensity of GFAP and MAP2 staining (see methods). (G and H) GFAP+ immunostaining in WT and KO mice Scale bar = 100 µm. (K): Bar graph showing quantification of GFAP+ immunoreactive staining intensity in WT and KO neocortex represented in panels G and H. A significant decrease in GFAP+ expression was found in KO compared to WT mice. *, p < .05, N = 3. (I, J): MAP2+ immunostaining intensity was observed in NF-α1-KO and NF-α1-WT mice. (L): Bar graph showing MAP2+ immunoreactive staining in WT and KO neocortex represented in panel I and J. No significant difference was observed between WT and KO mice. (M): Schematic representative of P1 coronal section; the square box indicates the neocortex region which was used to count the GFAP and MAP2 stained cells. Two square areas/section, four sections/brain and 3 brains/phenotype which came from 3 NF-α1-WT and 3 NF-α1-KO pups from 3 independent litters were quantified. (N, O): GFAP+ immunostained astrocytes in WT and KO neocortex respectively. GFAP+ astrocytes were significantly decreased in NF-α1-KO compared to NF-α1-WT. Scale bar = 20µm. (R): Bar graph showing GFAP+ astrocyte numbers represented in panels N and O. There was a significant decrease in astrocyte numbers in NF-α1-KO embryos compared to NF-α1-WT. The values represent the mean ± SEM, *, p < .05, N = 3, t test. Scale bar = 20 µm). (P, Q): MAP2+ immunostained neurons in WT and KO neocortex respectively. No significant difference in MAP2+ immunostaining was observed between NF-α1-KO and NF-α1-WT. (S): Bar graph showing MAP2+ neurons represented in panels P and Q. The values represent the mean ± SEM, N = 3, t test. Scale bar = 20 µm. Abbreviations: GFAP, glial fibrillary acidic protein; KO, knockout; NF-α1, neurotrophic factor-α1; WT, wild type. Figure 7 Open in new tabDownload slide Developmental expression of NF-α1 and GFAP and reduced astrocyte population observed in NF-α1-KO compared to NF-α1-WT in neocortex. Brains from E14.5 to P1 mice were extracted and protein analyzed by Western blot. Neocortex coronal sections (16 µm) from E14.5-P1 mice and NF-α1-KO and -WT mice at P1 stage were immunostained for NF-α1, GFAP (astrocytes) or MAP2 (neuron). (A): Western blot and bar graphs of NF-α1 (B) and GFAP (C) showing quantification of protein expression in brain during development. Each lane contains 2 brains pooled. NF-α1 expression increased gradually from E14.5 to P1 (B), while GFAP showed a major increase at P1(C), corresponding to the time of increased astrocyte differentiation. F(4,5)= 5.27 for (B) and F(4,5)=152.2 for (C), values are mean ± SD, *, p < .05 and **, p < .01, one way ANOVA (Tukey's multiple comparison test). (D, E): Developmental expression of NF-α1 (D) and GFAP (E) was quantified by immunohistochemistry (IHC) in brain sections from E14.5 to P1 mice (see Supporting Information Fig. 1 and methods). Eight random areas/section in the neocortex from 4 sections per brain and 3 brains for each stage were quantified. The rectangular box in the immunostained panels is representative of the size of the box (400 x 166 µm) used to measure the intensity of NF-α1 and GFAP staining (Supporting Information Fig 1). Expression of NF-α1 from immunostained sections showed a gradual increase in intensity from E14.5 to P1 (D), while GFAP immunoreactive staining showed low intensity from E14.5 to E17.5 and a surge at P1 (E). F(4,10)=39.73 for (D) and F(4,10)= 289.4 for (E), respectively, values are mean ± SEM, *, p < .05 and **, p < .01, N = 3, one way ANOVA (Tukey's multiple comparison test). (F): IHC showing the colocalization of NF-α1 (red) and GFAP (green) in astrocytes (see arrows in merged image) at P1. Scale bar = 20 μm (G–L): Eight random areas/section from four consecutive sections/brain, 12 total sections per phenotype from 3 independent litters (P1 mice) were used to quantify GFAP and MAP2 staining in the neocortex of WT and KO mice. The rectangular box in the immunostained panels is representative of the size of the area in the neocortex used to measure the intensity of GFAP and MAP2 staining (see methods). (G and H) GFAP+ immunostaining in WT and KO mice Scale bar = 100 µm. (K): Bar graph showing quantification of GFAP+ immunoreactive staining intensity in WT and KO neocortex represented in panels G and H. A significant decrease in GFAP+ expression was found in KO compared to WT mice. *, p < .05, N = 3. (I, J): MAP2+ immunostaining intensity was observed in NF-α1-KO and NF-α1-WT mice. (L): Bar graph showing MAP2+ immunoreactive staining in WT and KO neocortex represented in panel I and J. No significant difference was observed between WT and KO mice. (M): Schematic representative of P1 coronal section; the square box indicates the neocortex region which was used to count the GFAP and MAP2 stained cells. Two square areas/section, four sections/brain and 3 brains/phenotype which came from 3 NF-α1-WT and 3 NF-α1-KO pups from 3 independent litters were quantified. (N, O): GFAP+ immunostained astrocytes in WT and KO neocortex respectively. GFAP+ astrocytes were significantly decreased in NF-α1-KO compared to NF-α1-WT. Scale bar = 20µm. (R): Bar graph showing GFAP+ astrocyte numbers represented in panels N and O. There was a significant decrease in astrocyte numbers in NF-α1-KO embryos compared to NF-α1-WT. The values represent the mean ± SEM, *, p < .05, N = 3, t test. Scale bar = 20 µm). (P, Q): MAP2+ immunostained neurons in WT and KO neocortex respectively. No significant difference in MAP2+ immunostaining was observed between NF-α1-KO and NF-α1-WT. (S): Bar graph showing MAP2+ neurons represented in panels P and Q. The values represent the mean ± SEM, N = 3, t test. Scale bar = 20 µm. Abbreviations: GFAP, glial fibrillary acidic protein; KO, knockout; NF-α1, neurotrophic factor-α1; WT, wild type. Decrease in GFAP+ Cells in NF-α1-KO Versus NF-α1-WT in P1 Brains NF-α1-KO and NF-α1-WT brain sections (P1) were immunostained for GFAP and MAP2. A significant ∼25.6% decrease in GFAP immunostaining intensity measured over the whole neocortex was observed in NF-α1-KO embryos compared to WT embryos (GFAP intensity/brain: NF-α1-WT, 60428 ± 2154; NF-α1-KO, 44988 ± 2376; mean ± SEM, n = 3, p < .01, Fig. 7G, 7H, 7K). Counting GFAP+ cell numbers in randomly selected areas of the neocortex (M) revealed ∼49.4% fewer cells (GFAP cell numbers/brain: NF-α1-WT, 94.67 ± 5.6; NF-α1-KO, 50 ± 3.2; mean ± SEM, n = 3, p < .01) in the NF-α1-KO embryos compared to WT mice (Fig. 7N, 7O, 7R). There was no difference in the intensity of MAP2 staining in the neocortex close to the same regions where the cells were counted between NF-α1-WT and NF-α1-KO mice (Fig. 7I, 7J, 7L). This was confirmed by counting MAP2 stained neurons in similar areas where GFAP+ cells were counted (Fig. 7P, 7Q, 7S). Discussion In this study, we report a new stem cell antiproliferation/differentiation factor, NF-α1, which functions independent of its previously identified carboxypeptidase activity, (CPE, Fig. 4). We showed that NF-α1 mRNA is expressed as early as E5.5, primarily in neural primordium and continues to be expressed in the telencephalon and diencephalon of mouse embryos at later developmental stages. Moreover, we demonstrated that NF-α1 is expressed in NSCs derived from E13.5 mouse neocortex, indicating that NF-α1 is poised to act as an intrinsic neural cell fate determinant. Neural cell fate determination involves multifaceted steps and is influenced by various extrinsic and intrinsic factors that control the initiation and inhibition of proliferation and differentiation of cells [45]. Our in vitro data indicates that NF-α1 inhibits NSC proliferation, a prerequisite step to differentiation. Other proteins such as PTEN and MD20 are transiently expressed in select neural cell populations of embryos and regulate proliferation of NSCs [46, 47]. We propose that in vivo at a specific time during neural development, NF-α1 could be transiently expressed to downregulate NSC proliferation in an autocrine/paracrine fashion. Several signaling studies have shown that the Wnt/β-catenin pathway plays a critical role in regulating NSC proliferation and fate determination processes in embryonic development [48–50]. Our study show that NF-α1 regulates neurospheres proliferation by controlling the expression of β-Catenin, a molecule normally found to enhance proliferation [51, 52]. Indeed, we have previously reported that NF-α1 negatively regulates the canonical Wnt signaling pathway via interaction with its receptor, frizzled [53]. Thus, based on our findings, we propose that NF-α1 mediates inhibition of NSC proliferation through decreasing β-catenin levels via the Wnt signaling pathway. Our NSC differentiation data indicate that the majority of differentiated cells were astrocytes, followed by neurons and very low numbers of oligodendrocytes. This is consistent with neural progenitor differentiation profile data reported by others [54]. The differentiation of NSCs depends on the trophic factors and growth factors secreted by the NSC niche [55–57]. Our study shows that addition of NF-α1 to NSCs significantly increased the differentiation of NCSs to astrocytes without affecting the differentiation to neurons and oligodendrocytes. Likewise, EGF-responsive stem cells (cerebellar- derived) in the presence of CNTF have been shown to differentiate into more astrocytes rather than neurons and oligodendrocytes [58]. In contrast, addition of BDNF to stem cells derived from cortical and/or striata showed an increase in neurons and oligodendrocytes rather than astrocytes [18, 10]. In another study, neocortex-derived stem cells subjected to Neurotorphin-3 treatment promoted more neuronal differentiation [59, 60], Similarly, addition of GDNF to mesencephalon-derived neurosphere cultures showed an increase in the number of neuronal cells rather than astrocytes [61]. These studies indicate that some trophic factors such as BDNF, GDNF and Neurotrophin-3 promote neurogenesis, while others such as CNTF and NF-α1 promote astrogenesis. NF-α1/CPE is secreted at the germinal zones of mouse brain and by NSCs, astrocytes and neurons [28, 62, 63], and we showed that NF-α1 is expressed and presumably secreted by the embryonic NSCs (neurospheres). Therefore, NF-α1 is present in the right location in vivo to regulate the differentiation of NSC during neural development in an autocrine/paracrine fashion. Interestingly, exogenous addition of NF-α1 to neurospheres generated from adult mouse subventricular zone had no effect on differentiation to astrocytes, neurons, or oligodendrocytes [28]. This difference in response to NF-α1 suggests that NF-α1 may be primarily acting as a cell fate determinant during embryonic development. Our data also show that astrocytes are primarily derived from a population of NSCs immunopositive for both Nestin and GFAP protein and these in fact represent the majority of cells differentiated from the neurospheres. Evidence in support of this comes from our observation that treatment with NF-α1 decreased the number of Nestin+/GFAP+ cells and increased cells that were positive for GFAP alone, which are the mature astrocytes, to a similar extent. Increase in GFAP+ cells during differentiation of multipotent neural precursors is considered as an indication of maturation to the astrocyte phenotype [64–66]. In vivo, neural development is regulated by a complex environment under the influence of various growth factors and transcription factors that switch on and off in a coordinated manner to reprogram the cells and determine their fate [67–69]. These factors activate different signaling pathways such as NOTCH, BMP, ERK1/2, TGFβ1, known to regulate differentiation of NSCs into astrocytes [9, 13, 14, 70–72]. Here we showed that NF-α1 activated the Raf/MEK/ERK pathway, which then upregulated the expression of Sox9. Sox9 is an important transcription factor that plays a central role in transmitting the signals for major signaling pathways that regulate astrogliogenesis/astrocyte differentiation [11, 73, 74] and its expression could be suppressed by ERK1/2 inhibition [75, 76]. Indeed, we showed that in the presence of the ERK1/2 inhibitor (U0126) and knockdown of Sox9 gene expression by siRNA, NF-α1 induced GFAP mRNA expression was blocked. These results demonstrate that NF-α1 regulates the differentiation of NSCs into astrocytes by signaling through the ERK1/2 pathway, which enhances expression of the Sox9 transcription factor and GFAP. Our in vitro data on NF-α1-KO embryos showed a significant difference in differentiated cell phenotype. There were less astrocytes among the cells derived from the NF-α1-KO neurospheres compared to those from NF-α1-WT mice. In contrast, there were more neurons derived from the NSCs in the NF-α1-KO compared to NF-α1-WT embryos. These results reaffirm that NF-α1 plays an important role in inducing differentiation of NSCs to astrocytes. This was further confirmed by rescue experiments showing that addition of exogenous NF-α1 to the NSCs from KO embryos increased the astrocyte population and decreased the neuronal population. To demonstrate that NF-α1 plays a role in the induction of astrogenesis in vivo, we examined its developmental expression together with GFAP in mouse embryos and P1 pups, as well as the number of GFAP+ astrocytes in NF-α1-KO versus WT mice. Our data showed a steady increase in expression of NF-α1 in the brain of E14.5 to P1 mice. At P1, the time of significant astrogenesis in mice, [77], there was a surge in the expression of GFAP and an increase in numbers of GFAP+ astrocytes which also showed coexpression of NF-α1 in these cells. The presence of NF-α1 in these astrocytes suggests that it could have played a regulatory role in the differentiation of NSCs to astrocytes. More importantly, we demonstrated that the lack of NF-α1 perturbed normal astrogenesis in mice at P1 in vivo. Brain sections from the neocortex of NF-α1-KO mice revealed a significant (49%) decrease in the number of GFAP+ cells and a reduction in their staining intensity compared to the NF-α1-WT P1 mice. The extent of the decrease was even greater than the decrease in GFAP+ astrocytes observed in E13.5 cortex derived NSCs in the KO versus WT embryos. This finding together with the in vitro evidence showing decreased GFAP+ astrocytes in neocortex neurosphere cultures which could be rescued with addition of exogenous NF-α1, strongly indicate a regulatory role of NF-α1 in astrocyte differentiation. Unlike the in vitro studies, MAP2 staining was similar in intensity, suggesting no difference in the neuronal population between KO and WT mice in this brain region. This could be due to compensatory mechanisms that exist in vivo. Given the importance of astrocytes in supplying neurons with substrates for energy metabolism, modulating the immune response and synaptic transmission and control of extracellular water and electrolyte homeostasis [78, 79], NF-α1's role in promoting differentiation of NSCs to astrocytes during development is pivotal in building an optimally functioning CNS. Indeed, decreased astrocyte numbers in the cortex may contribute to cognitive deficits in CPE/NF-α1 knockout mice [30]. In conclusion, this study has uncovered a novel neurotrophic factor, NF-α1, which has the unique ability to perform the dual role of switching off proliferation and activating differentiation of embryonic NSCs, offering greater efficiency in this process. We propose that by upregulating NF-α1 expression in specified NSCs at a specific time during neurodevelopment, this switch from proliferation to differentiation could be activated. Moreover, NF-α1 is a cell fate determinant, promoting NSC differentiation into astrocytes. Its importance in normal brain development in vivo was evident in NF-α1-KO mice which exhibited decreased astrocyte numbers in the neocortex. Indeed, deficits in astrocyte numbers and function during neurodevelopment have been linked to human neurological diseases [80]. Conclusion Our studies have shown that NF-α1 is expressed during embryonic development. NF-α1 inhibits the proliferation of NSCs by negatively regulating the Wnt/β-catenin signaling pathway. It promotes the differentiation of NSCs into astrocytes by GFAP expression through activating the ERK1/2-Sox9 signaling cascade. These findings reveal a new neurotrophic factor, NF-α1, involved in embryonic neural development. Acknowledgments This research was supported by the Intramural Research Program of the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), National Institutes of Health, USA. We thank Dr. Marianne Bronner (CALTECH, Pasadena, Ca.) for her critical reading of this manuscript, and Lynn Holtzclaw and Dr. Vincent Schram (NICHD Microscopy Core Facility) for their assistance in microscopy. Author Contributions P.S.: Designed and performed most of the experiments and wrote the manuscript; L.X.: Designed and performed the immunocytochemistry and Western blot experiments done on mouse embryonic brains; C.L.: Technical advice in experiment design and interpreting the data; S.R.K.M.: Designed the in situ probes, performed and analyzed the in situ data; M.L.: Performed in situ experiment and analyzed the in situ data; N.C.: Provided overall technical advice and details in designing the in vitro CPE/NF-α1-KO experiments, helped in analyzing the results and interpreting the data, and edited the manuscript; I.M.: Analyzed the in situ data, read and corrected the manuscript; S.A.: Provided intellectual input in designing the experiment and helps in correcting the manuscript; Y.P.L.: Conception and design, financial support, provision of study material, data analysis and interpretation, manuscript editing, and final approval of manuscript. 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Google Scholar Crossref Search ADS PubMed WorldCat © 2016 AlphaMed Press This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model)

Teotia, Pooja; Chopra, Divyan A.; Dravid, Shashank Manohar; Van Hook, Matthew J.; Qiu, Fang; Morrison, John; Rizzino, Angie; Ahmad, Iqbal

doi: 10.1002/stem.2513pmid: 27709736

Abstract Glaucoma is a complex group of diseases wherein a selective degeneration of retinal ganglion cells (RGCs) lead to irreversible loss of vision. A comprehensive approach to glaucomatous RGC degeneration may include stem cells to functionally replace dead neurons through transplantation and understand RGCs vulnerability using a disease in a dish stem cell model. Both approaches require the directed generation of stable, functional, and target-specific RGCs from renewable sources of cells, that is, the embryonic stem cells and induced pluripotent stem cells. Here, we demonstrate a rapid and safe, stage-specific, chemically defined protocol that selectively generates RGCs across species, including human, by recapitulating the developmental mechanism. The de novo generated RGCs from pluripotent cells are similar to native RGCs at the molecular, biochemical, functional levels. They also express axon guidance molecules, and discriminate between specific and nonspecific targets, and are nontumorigenic. Glaucoma, Retinal ganglion cells, Induced pluripotent stem cells, Embryonic stem cells, Directed differentiation, Chemically defined medium Significance Statement The degeneration of retinal ganglion cells (RGCs) in glaucoma is the prevalent cause of irreversible blindness. Unfortunately, there is no effective treatment for glaucomatous RGC degeneration. Here, we demonstrate a facile method for de novo generation of RGCs, which are functional, safe, and target specific, for stem cell approaches to understand and treat RGC degeneration. Introduction Glaucoma represents a group of diseases, which are associated with multiple risk factors and genetic variants [1]. The unifying theme is the progressive degeneration of retinal ganglion cells (RGCs) that carry information from the retina to the brain for visual perception, and their degeneration leads to irreversible loss of vision. It is projected that by 2020, approximately 80 million people worldwide will suffer from open angle glaucoma and angle closure glaucoma [2]. Currently, there is no effective treatment for RGC degeneration. Neuroprotective approaches, proven successful in animal models of glaucoma [3, 4], are of limited practical use as their efficacy has not been demonstrated in clinics and they do not address RGCs that have already succumbed to the disease [5]. A comprehensive approach requires answers to the following questions: (a) Why are RGCs vulnerable in glaucoma? (b) How can degenerated cells be functionally replaced? The answers may lie in stem cell technology, wherein underlying pathological mechanisms can be studied in a dish, using patient-specific, induced pluripotent (iPS) stem cells [6–9] and degenerated RGCs may be replaced using ex vivo stem cell approaches [10]. The success of these approaches depends upon de novo generation of RGCs from pluripotent cells with stable molecular, cellular, and physiological phenotypes. The reproducibility of directed RGC generation, ascertained at multiple levels, is essential for unambiguous screening of the pathological phenotype in patient-specific iPS cells. Most importantly from the perspective of ex vivo stem cell approaches, these RGCs should be able to discriminate between specific and nonspecific targets to establish functional connections with bona fide ones. The efficient and reproducible generation of stable RGCs requires the development of a protocol that recapitulates a normal RGC developmental mechanism, generates cells with guidable axons, and is clinically safe. Current published protocols for RGC generation have exploited the default potential of ES/iPS cells to generate optic vesicle-like structure containing complements of all retinal cell types, rather than predominantly RGCs [8, 11, 12]. Here, we present a chemically defined approach, based on developmental mechanism, that leads to directed differentiation of retinal progenitor cells (RPCs) along the RGC lineage. This approach is comprehensively tested on RPCs derived from both mouse and human pluripotent cells in parallel with native RPCs. We demonstrate that the step-wise temporal recruitment of Shh, Notch, Fibroblast growth factor (FGF), and transforming growth factor beta (TGFβ) signaling allows native or pluripotent cell-derived RPCs to recapitulate the hierarchical gene expression that underlies initiation, differentiation, and maturation of RGCs, enabling directed acquisition of RGC phenotypes. The resulting RGCs, like those differentiated from the native RPCs, were defined by small soma and extensive processes and expressed multiple RGC-specific markers. The similarity in transcriptional signatures between RGCs differentiated from the pluripotent RPCs and RGCs enriched from the retina further reflected the stability of the acquired phenotype at the molecular and genomic levels. Examination of these cells at the physiological levels revealed electrophysiological properties characteristic of RGCs [13–15]. A species-specific difference in the physiological maturity of RGCs was observed, dependent on the expression of REST (Repressor Element 1-Silencing Transcription Factor), a negative regulator of RGC differentiation [16]. Silencing of its expression in mouse ES cell derived RGCs (mESC-RGCs) restored the physiology observed in human iPSC derived RGCs (hiPSC-RGCs). More importantly, from the viewpoint of ex vivo stem cell approach for RGC degeneration, the de novo-generated RGCs expressed a battery of molecules necessary for axonal guidance to seek appropriate targets. Our method led to complete silencing of pluripotency genes: these cells failed to form teratomas, demonstrating their safety for clinical use. Taken together, our approach, based on developmental principles, can efficiently and reproducibly generate stable and safe RGCs for a disease in dish model of glaucoma, providing a practical and safe ex-vivo stem cell approach. Materials and Methods Detailed materials and methods are described in the Supporting Information materials and methods. Generation of RPCs Mouse embryonic stem cells (mESCs) (D3) were maintained on mitotically inactivated mouse embryonic fibroblasts as previously described [17]. A human iPSC line, derived from the foreskin fibroblasts, was maintained in feeder-free conditions as previously described [18]. Differentiation of mESCs along retinal lineage was induced as described previously [19]. Retinal induction of hiPSCs was performed using the protocol published previously [20]. E18 rat RPCs were enriched using neurosphere assay as previously described [21, 22]. Differentiation of RPCs into RGCs RPCs derived from E18 retina/mESCs and human iPSCs were plated onto PDL/Laminin, and matrigel coated dishes, respectively and cultured in basal medium with the following stage-specific inducers/growth factors: RGC differentiation was initiated by treating cells for 2 days with Shh (250 ng/ml), FGF8 (100 ng/ml), and (N-[N-(3,5-difluorophenacetyl)-l-alanyl]-S-phenylglycine t-butyl ester) (DAPT [3 μM]); RGCs differentiation was facilitated by treatment with Follistatin (100 ng/ml), Cyclopamine (0.25 μg/ml) and DAPT (3 μM) for 1 day, followed by Follistatin (100 ng/ml) and DAPT (3 μM) for 2 days. Finally, RGCs maturation and survival was promoted by supplementing medium with brain-derived neurotrophic factor (BDNF) (100 ng/ml), Forskolin (5 μM), NT4 (5 ng/ml), cilliary neurotrophic factor (CNTF) (10 ng/ml) cAMP (400 μM), Y27632 (10 μM) and DAPT (3 μM) for the next 10 days. Medium was changed every 2-3 days. All reagents were purchased from R&D systems (R&D Systems, Minneapolis, MN, https://www.rndsystems.com) Immunocytochemical Analysis Immunocytochemistry analysis was performed as published elsewhere [19]. Sholl analysis was performed with the software ImageJ using the plugin Sholl Analysis (v1.50) with a 20 μm ring interval from neural rosettes [23]. Results Developmental Signaling Pathways for RGC Differentiation Among seven different cell types in the vertebrate retina, RGCs are specified first, regardless of species, suggesting an underlying evolutionarily conserved mechanism for their generation. The mechanism may involve an instructive niche that facilitates differentiation of early RPCs along the RGC lineage. In support of this premise, it has been demonstrated that retinal cells isolated from the initial stage of early histogenesis, either from a chick, rat, or mouse retina, elaborate potent RGC-promoting activities capable of inducing differentiation of retinal and nonretinal progenitors, including those derived from pluripotent cells into RGCs [22, 24–26]. Together, these observations suggested that RPCs are malleable in response to their environment through cell-to-cell interactions. Based on this premise, we designed an approach that recapitulated the cell-signaling dependent initiation, differentiation, and maturation of RGCs in vitro (Fig. 1A, 1B). This approach was exhaustively tested on RPCs derived from the rat retina and mESCs first before applying on those derived from hiPSCs. Figure 1 Open in new tabDownload slide Recapitulation of developmental mechanism for de novo generation of RGCs. Schematic of retinal development and cell-extrinsic factors involved in RGC differentiation (A). Schematic representation of sequential steps involved in initiation, differentiation and maturation of in vitro generated retinal progenitor cells along RGC lineage by stage-specific manipulation of signaling pathways using recombinant growth factors and small molecules (B). mESC-RPCs, under both conditions differentiated into RGCs as ascertained by cells expressing Atoh7+βIII tubulin and Brn3+βIII tubulin immunoreactivities (C-F). Each bar represents mean ± SD Scale bar: 20 μm. Abbreviations: BDNF, brain-derived neurotrophic factor; cAMP, Adenosine-3′,5′-cyclic monophosphate; CDM, chemically defined medium; CM, conditioned medium; CNTF, cilliary neurotrophic factor; DAPT, (N-[N-(3,5-difluorophenacetyl)-l-alanyl]-S-phenylglycine t-butyl ester); FGF8, fibroblast growth factor 8; NT4, neurotrophin-4; RGC, retinal ganglion cells; Shh, sonic hedgehog. Figure 1 Open in new tabDownload slide Recapitulation of developmental mechanism for de novo generation of RGCs. Schematic of retinal development and cell-extrinsic factors involved in RGC differentiation (A). Schematic representation of sequential steps involved in initiation, differentiation and maturation of in vitro generated retinal progenitor cells along RGC lineage by stage-specific manipulation of signaling pathways using recombinant growth factors and small molecules (B). mESC-RPCs, under both conditions differentiated into RGCs as ascertained by cells expressing Atoh7+βIII tubulin and Brn3+βIII tubulin immunoreactivities (C-F). Each bar represents mean ± SD Scale bar: 20 μm. Abbreviations: BDNF, brain-derived neurotrophic factor; cAMP, Adenosine-3′,5′-cyclic monophosphate; CDM, chemically defined medium; CM, conditioned medium; CNTF, cilliary neurotrophic factor; DAPT, (N-[N-(3,5-difluorophenacetyl)-l-alanyl]-S-phenylglycine t-butyl ester); FGF8, fibroblast growth factor 8; NT4, neurotrophin-4; RGC, retinal ganglion cells; Shh, sonic hedgehog. Evidence has emerged that the initiation of RGC differentiation begins in the center of the developing retina, presumably coordinated by FGF, Shh, and Notch signaling pathways (Fig. 1A). For example, it has been observed that transient FGF signaling by FGF8 and FGF3 facilitates initial RGC differentiation in the central retina [27, 28]. Shh is likely to be similarly involved. However, beyond the initiation of RGC differentiation, Shh may promote proliferation, thus maintaining RPCs for subsequent differentiation [27–30]. A coordinated decrease in Notch signaling is essential for RPCs to commit along the RGC lineage [31, 32]. Based on these observations, our strategy to initiate RGC differentiation in vitro included transiently activating FGF and Shh signaling and inhibiting Notch activities for the first 48 hours in culture, as outlined in Fig. 1B. Subsequently, FGF8 was removed from the culture and cyclopamine added to inhibit the Shh elaborated by the nascent RGCs that could adversely affect differentiation. Notch signaling, like Shh signaling, was kept inhibited to prevent any drift of committed precursors back into the proliferative mode. To keep the committed precursors on the RGC differentiation track, we left the TGFβ pathway inhibited, given that activation of the TGFβ pathway by GDF11, secreted by differentiating RGCs, has been observed to be a potent inhibitor of RGC differentiation [33]. The survival of nascent RGCs depends upon neurotrophins to prevent the activation of programmed cell death (PCD) [34]. To facilitate RGC maturation without excessive cell death, BDNF, NT4, and CNTF, all known to prevent PCD in RGCs [35–38], were included with general promoters of cell survival, Forskolin and Rock inhibitor [35, 39, 40]. We first tested the three-stage chemically defined medium (CDM) protocol on late RPCs, which are developmentally constrained from giving rise to early born neurons such as RGCs [31] (Supporting Information Fig. S1A). The CDM protocol was examined in parallel to that of a previously described method involving the induction of RGCs under conditioned media obtained from E14 rat retinal cells (E14 CM) [19]. We observed that the majority of late RPCs under the CDM protocol expressed immunoreactivities corresponding to RGC-specific markers, Atoh7, Islet1, and Brn3++βIII tubulin+ at the end of day 15 in culture (Supporting Information Fig. S1B, S1D). The numbers of cells expressing RGC-specific immunoreactivities were comparable when late RPCs were differentiated under E14CM (Supporting Information Fig. S1C, S1E). Temporal analysis of the pattern of gene expression during RGC differentiation revealed decreasing levels of transcripts corresponding to RPCs and concordant increase of those encoding regulators (Atoh7, Brn3b, Isl1) and mature markers (Thy1) of RGCs (Supporting Information Fig. S1F). Whole cell patch recordings and recordings in lose-patch conditions of RGCs differentiated under the influence of CDM revealed robust, inward, voltage-gated sodium, and outward potassium currents (Supporting Information Fig. S2A, S2B) and spontaneous currents (Supporting Information Fig. S2C), respectively, similar to those observed in cells differentiated along the RGC lineage under the influence of E14 CM (Supporting Information Fig. S2D–S2F). Having confirmed CDM influence in conferring the RGC phenotype on late RPCs, we carried out a comprehensive examination of its ability to differentiate RPCs derived from mESCs along the RGC lineage. As a reference for the efficiency, stability, and fidelity of RGC differentiation, the method was again examined in parallel with RPC induction under the influence of E14 CM [19]. Under both protocols Atoh7++βIII tubulin+ (Supporting Information Fig. S3A) and Brn3++βIII tubulin+ (Supporting Information Fig. S3B) cells were first detected at day 3, albeit at a low number. Their number increased steadily: at day 15 of differentiation, 84.50 ± 13.013% and 68.44 ± 18.639% of the total cells were Atoh7++βIII tubulin+ and Brn3++βIII tubulin+ (Fig. 1C--1F), respectively. The Atoh7++βIII tubulin+ cells reflected an immature state, and therefore their numbers were relatively higher than the latter. Similarly, the number of cells expressing the matured RGC marker, Thy1, confirmed for RGC lineage by the coexpression of Brn3, was lower than Atoh7++βIII tubulin+ and Brn3++βIII tubulin+ cells (Fig. 2C, 2E). These cells (mESC-RGCs), regardless of the protocol, displayed small soma and long processes. Together, the immunocytochemical analyses suggested that CDM was equivalent to E14CM in promoting the expression of RGC-specific markers in mESC-RPCs. Figure 2 Open in new tabDownload slide Temporal expression pattern of retinal ganglion cells (RGCs) regulatory genes during RGC differentiation under the influence of CDM. A schematic representation of gene regulatory hierarchy for RGC specification and differentiation is given in (A). Q-PCR analysis revealed a temporal increase in transcripts corresponding to RGC regulators (Atoh7, Brn3B, and Islet1) and mature markers (Thy1 and GAP43) under the influence of CDM (B) and E14 CM (D). A subset of cells expressed Brn3 + Thy1 immunoreactivities corroborating the acquisition of mature phenotype under both conditions (C, E). Scale bar: 20 μm. Abbreviation: REST, repressor element 1-silencing transcription factor. Figure 2 Open in new tabDownload slide Temporal expression pattern of retinal ganglion cells (RGCs) regulatory genes during RGC differentiation under the influence of CDM. A schematic representation of gene regulatory hierarchy for RGC specification and differentiation is given in (A). Q-PCR analysis revealed a temporal increase in transcripts corresponding to RGC regulators (Atoh7, Brn3B, and Islet1) and mature markers (Thy1 and GAP43) under the influence of CDM (B) and E14 CM (D). A subset of cells expressed Brn3 + Thy1 immunoreactivities corroborating the acquisition of mature phenotype under both conditions (C, E). Scale bar: 20 μm. Abbreviation: REST, repressor element 1-silencing transcription factor. Hierarchical Regulatory Gene Expression for RGC Differentiation The specification and differentiation of RGCs in the developing vertebrate retina requires temporal activation of hierarchical gene expression. Recent studies suggest that in this complex genetic hierarchy, instructive information is likely to flow through the nodes that are occupied by Atoh7, Isl1, and Brn3b (Fig. 2A) [41–45]. We were interested to know whether the CDM was capable of influencing this RGC gene regulatory network, essential if the RGC phenotype displayed at the end of day 15 were to remain stable. A temporal expression analysis during RGC induction under CDM and E14CM revealed a decrease in levels of transcripts corresponding to Rx and Pax6 (data not shown) and reciprocal increase in Atoh7 over time, suggesting a progressive commitment of RPCs and their specification along the RGC lineage (Fig. 2B, 2D). The temporal increase in transcripts corresponding to Brn3b/Islet1 and GAP43/Thy1 suggested their differentiation and maturation into RGCs, respectively. The presence of cells expressing immunoreactivities of both Brn3 and Thy1 at day 15 in vitro corroborated gene expression analysis of the acquisition of the matured RGC phenotype (Fig. 2C, 2E). We were next interested in whether mESC-RGCs differentiated under the two different conditions had acquired the similar genomic signature of the native RGCs. We immune-panned mESC-RGCs differentiated under the influence of CDM and E14CM using Thy1.2 antibodies [19]. The two populations of mESC-RGCs, CDM-RGCs, and CM-RGCs, were first subjected to RNA-seq analysis (Fig. 3A). A comparison of transcriptional profiles between CDM- and E14CM-derived RGCs by Scatterplot using the log2 of expression levels as fragment per kilo base of transcripts per million mapped reads (FPKM) revealed similar patterns of expression between the two populations, where Spearman correlation coefficiency (ρ) was 0.96 (Fig. 3B). Next, the transcription profiles of CDM-RGCs were compared with those obtained from RGCs, similarly enriched from the PN2 mouse retina (Retinal-RGCs). The analysis found high correlations (ρ = 0.83) between the de novo generated and native RGC population transcriptomes (Fig. 3C). Analysis of number of genes expressed (FPKM > 0.5) revealed that the CDM-RGCs shared 80.7% of those with the retinal-RGCs (Fig. 3D) and their GO analysis represented shared biological processes, for example, those associated with neuronal differentiation, axonogenesis, cell cycle and cytoskeleton regulation (Fig. 3E). The shared expression included 382 RGC-associated genes (e.g., Atoh7, Brn3b, Isl1, Shh, SMARCA2, Irx2, Robo2, NRP1, SNCG, RPF1, EphA4, WT1) previously identified using different approaches [42, 46, 47] (data not shown). To identify the key pathways encoded by the expressed gene sets, analysis of the curated KEGG pathway repositories was carried out. The enriched KEGG signaling pathways included those involved in RGC differentiation (e.g., Notch and Shh pathways), survival (e.g., Neurotrophin signaling and JAK-STAT pathways), and communication (axon guidance and mTOR signaling pathways) (Fig. 3F). Figure 3 Open in new tabDownload slide Global gene expression pattern in de novo generated and native RGCs. A Schematic representation of Thy1.2 antibody-based enrichment of RGCs, derived under the influence of E14CM (CM-RGCs), CDM (CDM-RGCs), and from PN2 mouse retina (Retinal-RGCs) (A). Correlation of expressed genes by Scatterplot between CM-RGCs and CDM-RGCs (B) and CDM-RGCs and retinal-RGCs (C). ρ = Spearman correlation coefficiency. Venn diagram of genes expressed (FPKM > 0.5) by CDM-RGCs and retinal RGCs alone and by both (D). GO analysis of biological processes that are significantly enriched within the shared expressed genes (p values; Bonferroni) (E). The enriched KEGG signaling pathways reveal those involved in RGC development and biology (F). Abbreviations: CDM, chemically defined medium; RGC, retinal ganglion cells; RPCs, retinal progenitor cells. Figure 3 Open in new tabDownload slide Global gene expression pattern in de novo generated and native RGCs. A Schematic representation of Thy1.2 antibody-based enrichment of RGCs, derived under the influence of E14CM (CM-RGCs), CDM (CDM-RGCs), and from PN2 mouse retina (Retinal-RGCs) (A). Correlation of expressed genes by Scatterplot between CM-RGCs and CDM-RGCs (B) and CDM-RGCs and retinal-RGCs (C). ρ = Spearman correlation coefficiency. Venn diagram of genes expressed (FPKM > 0.5) by CDM-RGCs and retinal RGCs alone and by both (D). GO analysis of biological processes that are significantly enriched within the shared expressed genes (p values; Bonferroni) (E). The enriched KEGG signaling pathways reveal those involved in RGC development and biology (F). Abbreviations: CDM, chemically defined medium; RGC, retinal ganglion cells; RPCs, retinal progenitor cells. Functional Properties of RGCs and the Role of REST Next, we wanted to know if the de novo differentiated mESC-RGCs possessed pan-neuronal and RGC-specific electrophysiological properties. Examination of current profiles by whole cell, patch clamped recordings yielded different results for mESC-RGCs generated under the two different conditions. When currents were evoked by a series of voltage steps (−100 to +20 mV) in an identical condition of holding potential of −90 mV, 30% of mESC-RGCs under CDM displayed only delayed and sustained outward potassium currents, and no fast inward currents corresponding to voltage-gated sodium channel were observed (Fig. 4A). In contrast, 62.5% of mESC-RGCs under E14CM revealed the presence of fast inward and delayed but sustained outward currents (Fig. 4C). Examination of the fast inward and outward currents in mESC-RGCs generated under E14CM showed an I-V relationship typical of voltage–gated sodium and delayed potassium currents, respectively (Fig. 4D). Such I-V relationships, observed in isolated native RGCs [13–15], could not be detected in mESC-RGCs derived under the influence of CDM conditions due to the absence of voltage-gated sodium currents (Fig. 4B). We argued that the non-neuronal electrophysiological signature of mESC-RGCs derived under CDM despite acquiring RGC-specific molecular and chemical phenotypes could be due to a less than favorable stoichiometric ratio of the expressed RGC-specific genes required to confer functional maturity. Such a notion could be explained by the inhibitory effects on hierarchical gene expression imposed by residual expression of REST, a global inhibitor of neuronal genes that has emerged as a known negative regulator of RGC differentiation [16]. To see if REST is involved in the functional maturity of RGCs, we first determined its relative expression in E18-RGCs and mESCs-RGCs under CDM conditions. We observed significantly higher levels of transcripts corresponding to REST in the latter than in the former (Supporting Information Fig. S4). When we reduced REST transcript levels in RPCs by shRNA-mediated REST loss-of-function (LOF) and then subjected them to RGC differentiation (Fig. 4E), we observed a significant increase in levels of transcripts corresponding to Atoh7, Brn3b, and Islet1, compared to controls (Fig. 4F). Subsequent whole cell patch clamp recording of differentiated cells revealed prominent voltage-dependent sodium currents, which had been previously absent (Fig. 4G) and had displayed a symmetrical RGCs-like I-V relationship (Fig. 4H). Furthermore, we found 66.6% of REST LOF cells capable of generating depolarization evoked action potential when clamped in loose patch conditions (Fig. 4I). Together, these observations suggested that inhibition of REST is essential for functional maturity of mESCs-RGCs. Figure 4 Open in new tabDownload slide Restoration of functional maturity in mouse ES cell derived RGCs (mESC-RGCs) generated under the influence of CDM following Repressor Element 1-Silencing Transcription Factor loss-of-function (REST-LOF). Whole cell patch clamp analysis of cells, performed at the end of differentiation, revealed that mESCs-RGCs induced by CDM displayed only delayed outward currents but no inward currents (A) and lacked typical I-V relationship due to absence of voltage gated sodium currents (B). mESC-RGCs induced by E14 CM displayed fast inward and delayed outward currents in 62.5% of cells (C) and demonstrated I-V curve indicative of typical voltage-gated sodium channels and delayed potassium currents, respectively (D). mESCs-RPCs were transduced with REST shRNA + GFP/Control GFP lentivirus and subjected to RGC differentiation using CDM (E). REST shRNA transduced cells showed significant increase in the expression of RGCs specific markers (Atoh7, Brn3b, and Islet1) and decrease in the expression of REST, as compared to controls (F). Whole cell patch clamp of recorded mESC-RGCs after REST knockdown showed voltage dependent sodium currents (G), typical IV curve of sodium and potassium currents (H), and evoked action potential in 66.6% of cells (I). Abbreviations: CDM, chemically defined medium; RGC, retinal ganglion cells; RPCs, retinal progenitor cells. Figure 4 Open in new tabDownload slide Restoration of functional maturity in mouse ES cell derived RGCs (mESC-RGCs) generated under the influence of CDM following Repressor Element 1-Silencing Transcription Factor loss-of-function (REST-LOF). Whole cell patch clamp analysis of cells, performed at the end of differentiation, revealed that mESCs-RGCs induced by CDM displayed only delayed outward currents but no inward currents (A) and lacked typical I-V relationship due to absence of voltage gated sodium currents (B). mESC-RGCs induced by E14 CM displayed fast inward and delayed outward currents in 62.5% of cells (C) and demonstrated I-V curve indicative of typical voltage-gated sodium channels and delayed potassium currents, respectively (D). mESCs-RPCs were transduced with REST shRNA + GFP/Control GFP lentivirus and subjected to RGC differentiation using CDM (E). REST shRNA transduced cells showed significant increase in the expression of RGCs specific markers (Atoh7, Brn3b, and Islet1) and decrease in the expression of REST, as compared to controls (F). Whole cell patch clamp of recorded mESC-RGCs after REST knockdown showed voltage dependent sodium currents (G), typical IV curve of sodium and potassium currents (H), and evoked action potential in 66.6% of cells (I). Abbreviations: CDM, chemically defined medium; RGC, retinal ganglion cells; RPCs, retinal progenitor cells. Differentiation of Human iPSCs into Functional RGCs Next, we examined whether or not the CDM was equally effective in differentiating RPCs derived from human pluripotent cells into RGCs (hiPSC-RGCs). hiPSCs were cultured in enhanced IGF signaling and reduced BMP and Wnt signaling to obtain neural rosettes, as previously described [20]. Immunocytochemical examination of neural rosettes revealed cells coexpressing RPC markers, Rx and Pax6 (Supporting Information Fig. S5A–S5D). The proportion of cells expressing immunoreactivities corresponding to Pax6 and Rx was 91.27 ± 2.92% (Supporting Information Fig. S5D). Results obtained by immunocytochemical analysis were corroborated by a significant increase in levels of transcripts corresponding to Rx and Pax6, compared to those in uninduced hiPSCs (Supporting Information Fig. S5E, S5F). Exposure of these cells to three-stage CDM protocol led to a remarkable change in their morphology, with small soma and elongated network of processes at day 15 in culture (Fig. 5A, 5B). Immunocytochemical analysis revealed the majority of these cells (91.87 ± 12.13%) coexpressed Atoh7 and βIII tubulin immunoreactivities. The proportions of cells coexpressing Brn3 and βIII tubulin and Brn3 and Thy1 were 27.92 ± 13.38% and 25.75 ± 25.55%, respectively, (Fig. 5C, 5D, 5G). In contrast, a minor proportion of cells expressed immunoreactivities corresponding to other early born neurons, s-opsin (7.89 ± 7.84) (cone photoreceptors) and Prox1 (4.92 ± 4.94) (horizontal cells), suggesting RGC differentiation of hiPSCs (Fig. 5E–5G). This premise was further supported by the absence of cells expressing rhodopsin, a marker corresponding to rod photoreceptors and a Muller glia specific marker, Glast (data not shown). Analysis of cell-type-specific gene expression corroborated these results. The expression of Rx and Pax6 decreased significantly at day 15 in culture, compared to controls, demonstrating the loss of RPC properties in the presence of CDM (Supporting Information Fig. S6). In contrast, levels of transcripts corresponding to Atoh7, Brn3b, and Islet1 increased ∼1.5-fold, and those of Thy1 doubled in cells at day 15 in culture versus controls. These observations and others, such as these cells also expressed the vesicular glutamate transporter 2 (VGluT2), the vesicular glutamate transporter expressed in RGCs [48] (Supporting information Fig. S7A), suggested that CDM induced directed differentiation of hiPSC-RPCs along the RGC lineage. We used electrophysiolgical analysis of hiPSC-RGCs to test for the hallmarks of neuronal function in cells with neuronal morphology. These cells backfilled with Lucifer yellow-expressed Brn3b, identifying them as RGCs (Fig. 6A). Whole-cell, voltage-clamp recordings of these cells revealed the presence of fast inward Na+ currents and outwardly-rectifying K+ currents (Fig. 6B). Na+ currents were reversibly blocked by tetrodotoxin (1 µM) and had mean amplitude of 655 ± 341 pA measured at −26 mV (n = 7) (Fig. 6C). Examination of fast inward currents and outwardly rectifying currents displayed an I-V relationship typical of voltage–dependent Na+ currents and delayed potassium currents (Fig. 6D). In current clamp recordings from cells with particularly large INa (n = 2 cells tested; peak INa = 2064 and 2191 pA), depolarizing current injections evoked action potentials (Fig. 6E). These results suggest that the three-stage CDM approach was effective in generating functional RGCs across species by recruiting normal developmental mechanisms. Figure 5 Open in new tabDownload slide Differentiation of hiPSC into RGCs using CDM. (A): Schematic showing experimental protocol used for stepwise differentiation of hiPSCs into RGCs. (B): A panoramic view of five images of hiPSC-RGCs coexpressing Atoh7 and βIII tubulin immunoreactivities, revealed long and complex network of processes. Immunostaining showing a subset of cells coexpressing immunoreactivities corresponding to Brn3+βIII tubulin (C, G) and Brn3 +Thy1 (D, G). A minor subset of Brn3 negative cells expressed S-opsin (E, G) and Prox1 immunoreactivities (F, G), corresponding to early born retinal neurons, cone photoreceptors, and horizontal cells, respectively. Scale bar: Panels B-F 50 μm; Inset: 20 μm. Abbreviations: CDM, chemically defined medium; hiPSCs, human induced pluripotent stem cells; RGC, retinal ganglion cells. Figure 5 Open in new tabDownload slide Differentiation of hiPSC into RGCs using CDM. (A): Schematic showing experimental protocol used for stepwise differentiation of hiPSCs into RGCs. (B): A panoramic view of five images of hiPSC-RGCs coexpressing Atoh7 and βIII tubulin immunoreactivities, revealed long and complex network of processes. Immunostaining showing a subset of cells coexpressing immunoreactivities corresponding to Brn3+βIII tubulin (C, G) and Brn3 +Thy1 (D, G). A minor subset of Brn3 negative cells expressed S-opsin (E, G) and Prox1 immunoreactivities (F, G), corresponding to early born retinal neurons, cone photoreceptors, and horizontal cells, respectively. Scale bar: Panels B-F 50 μm; Inset: 20 μm. Abbreviations: CDM, chemically defined medium; hiPSCs, human induced pluripotent stem cells; RGC, retinal ganglion cells. Figure 6 Open in new tabDownload slide Electrophysiological properties of hiPSC-RGCs. Whole cell patch clamp recording of Brn3+ hiPSC-RGCs, identified by backfilling of cells with lucifer yellow (LY) (A) revealed fast inward and delayed outward currents, evoked by depolarizing steps (−66 to +4 mV) from a holding potential of −76 mV; the former being TTX sensitive (B, C). The fast inward and outward currents showed I-V relationship typical of voltage-gated sodium (INa) and delayed potassium (IK) currents, respectively (n = 7 cells) (D). Voltage traces from the same cell in a current-clamp recording showed responses to depolarizing and hyperpolarizing current injections (E). Scale bar: 20 μm. Figure 6 Open in new tabDownload slide Electrophysiological properties of hiPSC-RGCs. Whole cell patch clamp recording of Brn3+ hiPSC-RGCs, identified by backfilling of cells with lucifer yellow (LY) (A) revealed fast inward and delayed outward currents, evoked by depolarizing steps (−66 to +4 mV) from a holding potential of −76 mV; the former being TTX sensitive (B, C). The fast inward and outward currents showed I-V relationship typical of voltage-gated sodium (INa) and delayed potassium (IK) currents, respectively (n = 7 cells) (D). Voltage traces from the same cell in a current-clamp recording showed responses to depolarizing and hyperpolarizing current injections (E). Scale bar: 20 μm. Target Specificity and Safety of De Novo-Generated Human RGCs The utility of hiPSC-RGCs in ex vivo stem cell approaches required functional maturity of differentiated cells to elaborate guidable axons that can reach bonafide targets for recovering lost vision. Therefore, we examined whether or not hiPSC-RGCs express receptors for axon guidance molecules. RT-PCR analysis of hiPSC-RGCs revealed that they expressed transcripts corresponding to ROBO2, which facilitates guidance within the retina and at the optic chiasm, DCC, which is required for the exit of the axons at the optic disc, NEUROPILIN 1 (NRP1), for keeping the axons coalesced and EPHs for establishing the spatial gradient of connections in the superior colliculus (SC) [49]. We observed that the expression of transcripts corresponding to these molecules, which was not detectable in un-induced hiPSCs and hiPSC-RPCs, was activated in hiPSC-RGCs under the influence of CDM (Fig. 7A). We also examined the expression of GAP43, a cytoplasmic protein essential for guiding axons from the optic chiasm into the optic tracts (Supporting Information Fig. S6) [49]. Immunocytochemical analysis of select guidance molecules revealed the expression of immunoreactivities corresponding to ROBO2 and GAP43 in hiPSC-RGCs, corroborating the PCR results at the cellular levels (Supporting Information Fig. S7B, S7C). Together, these observations suggested that hiPSC-RGCs had the molecular make-up necessary to respond to guidance cues for target selection. To test the premise that these cells possess the target specificity of native RGCs, we cultured carboxy- fluorescein diacetate (CFDA)-labeled hiPSC-RGCs across cell aggregates from either the SC or inferior colliculus (IC), obtained from the rat midbrain [19]. Given the fact that retino-colliculi connections are phylogenetically old [50], molecules mediating these connections are expected to be evolutionarily conserved and thus functional across the species. We observed that the CFDA-labeled hiPSC-RGCs elaborated long processes in the presence of SC explants and oriented them toward the SC cells, the specific target of RGC axons in the mid brain (Fig. 7B). The esterified fluorchrome complexes of CFDA do not stain the newly elaborated process and remain trapped within the cell body, thus highlighting it. The CFDA-stained hiPSC-RGCs, when cultured in the presence of the IC cells (a target of the auditory neurons), elaborated short processes that failed to orient themselves toward the explants (Fig. 7C). Sholl analysis of the processes emanating from hiPSC-RGCs (neural rosettes identified as center of analysis) revealed a significant increase in their length when cultured in the proximity of SC cells, compared to those close to IC cells (Fig. 7D). We next wanted to know if the presence of SC cells affected the function of hiPSC-RGCs. In cells cocultured with SC explants for 9 days, depolarizing steps revealed the presence of outwardly rectifying potassium currents and fast inward sodium currents that were reversibly blocked by Tetrodotoxin (TTX) (1 µM) (Fig. 7E). Measured at −26 mV, INa had a mean amplitude of 1261 ± 222 pA (n = 8 cells), twice that recorded from hiPSC-RGCs in non-coculture conditions (Fig. 7F). Examination of fast inward currents and outwardly rectifying currents displayed an I-V relationship typical of voltage–dependent Na+ currents and delayed potassium currents (Fig. 7G). In current-clamp recordings, depolarizing current injections evoked action potentials in these cells (8/8 cells) (Fig. 7H). Action potentials were somewhat variable in amplitude, peaking at ∼0 mV (−3.3 ± 4.4 mV; range: +17 to −24 mV). The action potential amplitude positively correlated with the amplitude of the sodium current (r = 0.74, p < .05, Pearson correlation). In a handful of recorded cells (3/6 cells tested) a 2-second puff of L-glutamate onto the soma evoked a small inward current (12.6 ± 2.0 pA, n = 3) that was reversibly inhibited by the AMPA/Kainate antagonist CNQX (30 µM), suggesting that those cells expressed functional ionotropic glutamate receptors (Fig. 7I). Together, these results suggested that hiPSC-RGCs possessed the molecular and cellular wherewithal for axonal guidance and were capable of discriminating specific and nonspecific targets while maintaining their physiological properties, features essential for an ex vivo stem cell approach to RGC degeneration. Also essential in this regard was ensuring that hiPSC-RGCs had fully differentiated and lost the propensity of the iPS cells to form tumors. To test this premise, we first screened hiPSC-RGCs for the expression of pluripotency genes. Q-PCR analysis of hiPSCs and hiPSC-RGCs revealed that transcripts corresponding to Oct4 and Nanog, easily detected in the former, were absent in the latter (Supporting Information Fig. S8A). These observations suggested that the three-stage CDM protocol effectively silenced the pluripotency genes and therefore generated hiPSC-RGCs that might not be tumorigenic. To test this, hiPS cells/hiPSC-RGCs were injected in NOG mice. Those injected with hiPSCs formed teratomas in 6 weeks and those with hiPSC-RGCs remained free of teratomas at 12 weeks post-injection, when the recipient mice were sacrificed (Supporting Information Fig. S8B, S8C). Our results demonstrate that the three-stage CDM protocol could efficiently generate hiPSC-RGCs with the molecular, cellular, and functional attributes of native RGCs, capable of target specificity and safe for ex vivo replacement of degenerated RGCs in glaucomatous neuropathy. Figure 7 Open in new tabDownload slide Target specificity of hiPSC-RGCs. RT-PCR analysis revealed the expression of transcripts corresponding to axon guidance molecules (ROBO2, DCC, NRP1, EPHA3, EPHA4, EPHB2, and EPHB3) in hiPSC-RGCs compared to un-induced iPSCs and hiPSC-RPCs (A). CFDA-tagged hiPSC-RGCs elaborated long processes toward SC cells aggregate (B), compared to the one cocultured with IC cells aggregate (C). Sholl analysis of processes of hiPSC-RGCs co cultured with SC and IC cell aggregates, displayed a significant difference in the length of processes elaborated toward SC/IC cells aggregate (D). Whole cell patch clamp recording of hiPSC-RGCs cocultured with SC cells aggregate, revealed fast inward and delayed outward currents, evoked by depolarizing steps (−66 to +24 mV) from a holding potential of −76 mV; the former being TTX sensitive (E, F). The fast inward and outward currents showed I-V relationship typical of voltage-gated sodium (INa) and delayed potassium (IK) currents, respectively (n = 8 cells) (G). Voltage traces from the same cell in a current-clamp recordings showed responses to depolarizing and hyperpolarizing current injections (H). Inward currents evoked in response to a 2-second puff of L-glutamate (1 mM) in control conditions, in the presence of 30 µM CNQX, and following washout of CNQX (I). Scale bar: 50 μm. Abbreviations: M, marker lane; IC, inferior colliculus; iPSCs, induced pluripotent stem cells; RGC, retinal ganglion cells; RPCs, retinal progenitor cells; SC, superior colliculus. Figure 7 Open in new tabDownload slide Target specificity of hiPSC-RGCs. RT-PCR analysis revealed the expression of transcripts corresponding to axon guidance molecules (ROBO2, DCC, NRP1, EPHA3, EPHA4, EPHB2, and EPHB3) in hiPSC-RGCs compared to un-induced iPSCs and hiPSC-RPCs (A). CFDA-tagged hiPSC-RGCs elaborated long processes toward SC cells aggregate (B), compared to the one cocultured with IC cells aggregate (C). Sholl analysis of processes of hiPSC-RGCs co cultured with SC and IC cell aggregates, displayed a significant difference in the length of processes elaborated toward SC/IC cells aggregate (D). Whole cell patch clamp recording of hiPSC-RGCs cocultured with SC cells aggregate, revealed fast inward and delayed outward currents, evoked by depolarizing steps (−66 to +24 mV) from a holding potential of −76 mV; the former being TTX sensitive (E, F). The fast inward and outward currents showed I-V relationship typical of voltage-gated sodium (INa) and delayed potassium (IK) currents, respectively (n = 8 cells) (G). Voltage traces from the same cell in a current-clamp recordings showed responses to depolarizing and hyperpolarizing current injections (H). Inward currents evoked in response to a 2-second puff of L-glutamate (1 mM) in control conditions, in the presence of 30 µM CNQX, and following washout of CNQX (I). Scale bar: 50 μm. Abbreviations: M, marker lane; IC, inferior colliculus; iPSCs, induced pluripotent stem cells; RGC, retinal ganglion cells; RPCs, retinal progenitor cells; SC, superior colliculus. Discussion The selective degeneration of RGCs in glaucoma leads to irreversible blindness. The universal vulnerability of RGCs in this complex group of disorders remains unexplained and practical strategies to replace degenerated cells remain elusive. Pluripotent stem cell technology may shed light on the intractable degenerative disease. The patient-specific iPSCs, may reveal why these neurons are susceptible to glaucoma risk factors and lead to better diagnosis and formulation of therapeutic approaches. The ex vivo stem cell approaches using RGCs derived from pluripotent cells may replace degenerated neurons. The success of both cases depends on the generation of RGCs in a dish that faithfully resembles their native counterparts in structure, function, and in existing as final output neurons of the retina that are capable of discriminating between authentic and nonspecific targets. Several approaches have been reported for the de novo generation of RGCs, the majority of them based on the default retinal potential of pluripotent cells, exposed when they are cultured in conditions that facilitate the formation of optic vesicle-like structures [8, 11, 12, 51, 52]. This is a reproducible approach wherein retinal cells are generated in an evolutionarily conserved, temporal sequence observed in vivo. Early born neurons including RGCs are differentiated earlier than late born neurons, for example, rod photoreceptors. However, this method and its variations do not promote directed differentiation of RPCs into RGCs; therefore, the end stage culture represents complements of all retinal cell types, including Muller glia, which may not be desirable for generating an RGC disease model or for ex-vivo stem cell approaches [51]. Several studies have also shown that in the optic vesicle-like structures, expression of RPC (e.g., Pax6, Rx, and Chx10) and or photoreceptor (e.g., Crx) regulators [8, 11, 12, 53–55] remain upregulated, raising the issue of the existence of cells in sustained transitional states. This is supported by a recent observation that Brn3-positive cells generated by a similar method coexpressed retinal progenitor markers [8]. Such transitional states may affect phenotype stability and function. Therefore, our goal was to develop a CDM-based protocol, underpinned by a normal RGC development mechanism, wherein RPCs generated from pluripotent cells were constrained to preferentially differentiate along the RGC lineage. In this method, CDM influenced two interacting processes required for RGC differentiation; it adversely affected the maintenance of RPCs as demonstrated by a temporal decrease in the expression of RX and Pax6, and channeled their commitment along the RGC lineage by activating the stage-specific expression of key RGC regulators, Atoh7, Brn3b, and Isl1. Their expression was detected at the specification (day2) of RPCs and later became stage-specific. For example, the expression of Atoh7 peaked during the early stages of differentiation of RGCs (day 5). In contrast, the expression of more distal regulators in the hierarchical gene regulatory network, Brn3b and Isl1 increased significantly at day 15, timed with RGC differentiation and maturation. This ability of CDM to reproducibly influence the RGC gene regulatory network in a stage-specific manner in both native and pluripotent cell-derived RPCs may underlie the acquisition of transcriptional signature and electrophysiological properties similar to that of native RGCs. However, a difference in species-specific response was observed when RPCs were exposed to CDM. While RGCs generated from rat RPCs and hiPSC-RPCs obtained functional maturity as ascertained by electrophysiological criteria, those from mESC-RPCs did not despite expression of all other RGC features. This was attributed to a persistent REST expression in the latter because a loss of function of REST restored functionality, similar to that of rat and hiPSC-RGCs. This observation suggests two possibilities. First, the inability of CDM to suppress REST expression in mouse pluripotent cells may be the function of species or pluripotent cell-specific (ESCs vs. iPSCs) epigenetic signatures. Second, if REST remains expressed the stoichiometry of RGC-specific gene expression remains below the threshold of facilitating functional maturity. The method presented here is rapid and efficient in generating RGCs. In 15 days, RPCs were differentiated into matured RGCs, a faster rate than published methods of 40 to 90 days [8, 11, 12, 53, 56]. Quantification of cells at the end of differentiation revealed ∼90% of total mouse and human cells expressed immunoreactivities corresponding to Atoh7 and βIII tubulin, demonstrating that the CDM committed the majority of cells along the RGC lineage. This was demonstrated by either the absence (Muller glia) or the presence of other retinal cell types (cone photoreceptors and horizontal cells) as a minor Brn3 negative population in the culture. Further, unlike the observation associated with the default pathway-based methods, immunoreactivities corresponding to Pax6 and Rx were not detected in Brn3 positive cells, demonstrating that the CDM effectively silenced the regulators of RPCs. Still, the transition of Atoh7++βIII tubulin+ positive cells into more matured RGCs, that is, those expressing Brn3+/Brn3 + Thy1+ immunoreactivities, was not synchronous and appeared delayed, regardless of species. It may be that recently committed RGCs remain in different stages of development and at that stage of culture only a subset of those have advanced to a stage of maturity, displayed by the coexpression of Brn3 and Thy1. Nevertheless, the pluripotent cell-derivatives at day 15 had irreversibly committed along lineage-specific differentiation so as to lose their atavistic tumorigenic potential. The function of RGCs as projection neurons of the retina depends upon their ability to form contacts with central targets such as the lateral geniculate nucleus (LGN) and SC for conscious and subconscious visual perception, respectively. This requires expression of guidance molecules that help RGC axons navigate to their targets. The generation of an accurate disease model of glaucomatous degeneration or ex vivo stem cell therapy to replace degenerated RGCs necessitates the demonstration of RGCs’ ability to guide their axons to bona fide targets. The RGCs generated under the influence of CDM fulfill the criteria of projection neurons. They express a battery of guidance molecules confirming their molecular competence as native RGCs for guiding the axons within the retina, at the optic chiasm, and for their topographical connections in the central targets, SC and LGN. They also discriminate between cells from SC and IC by extending processes when exposed to the former not the latter. This suggests patient-specific or normal RGCs generated under the influence of CDM could be evaluated for the characteristics of native RGCs, with the potential to replace cells degenerated in glaucomatous neuropathy. Conclusion Our observations demonstrate that pluripotent cells, regardless of species and origin, can be directly and rapidly differentiated into functional, target-specific, and safe RGCs by recapitulating developmental mechanisms through stage-specific chemically defined conditions. These attributes of the de novo generated RGCs posit these cells as a valuable and practical reagent for understanding and addressing glaucomatous RGC degeneration. Acknowledgments This research was supported by NIH/NEI: R01-EY022051 (IA), Research to Prevent Blindness, NIH/NEI:R01 EY010145 (J.C.M.) and P30 EY010572 (Casey Core grant). We thank Dr. Larisa Poluektova for providing NOG (NOD/Shi-scid/IL-2Rγnull) mice. Author Contributions P.T. and I.A: Conception and design, collection and/or assembly of data, data analysis and interpretation, and manuscript writing; D.C., S.M.D., and M.V.H.: Collection and/or assembly of data, data analysis, and interpretation; F.Q: Data analysis and interpretation; J.M.: Conception and design; A.R.: Provision of study material or patients. Disclosure of Potential Conflicts of Interest The authors indicate no potential conflicts of interest. References 1 Ahram DF , Alward WL, Kuehn MH. The genetic mechanisms of primary angle closure glaucoma . Eye (Lond) 2015 ; 29 : 1251 – 1259 . Google Scholar Crossref Search ADS PubMed WorldCat 2 Quigley HA , Broman AT. The number of people with glaucoma worldwide in 2010 and 2020 . Br J Ophthalmol 2006 ; 90 : 262 – 267 . Google Scholar Crossref Search ADS PubMed WorldCat 3 Danesh-Meyer HV , Levin LA. Neuroprotection: Extrapolating from neurologic diseases to the eye . Am J Ophthalmol 2009 ; 148 : 186 – 191 . e182. 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Uchida, Naoya; Haro-Mora, Juan J.; Fujita, Atsushi; Lee, Duck-Yeon; Winkler, Thomas; Hsieh, Matthew M.; Tisdale, John F.

doi: 10.1002/stem.2517pmid: 27739611

Abstract Human embryonic stem (ES) cells and induced pluripotent stem (iPS) cells represent an ideal source for in vitro modeling of erythropoiesis and a potential alternative source for red blood cell transfusions. However, iPS cell-derived erythroid cells predominantly produce ε- and γ-globin without β-globin production. We recently demonstrated that ES cell-derived sacs (ES sacs), known to express hemangioblast markers, allow for efficient erythroid cell generation with β-globin production. In this study, we generated several iPS cell lines derived from bone marrow stromal cells (MSCs) and peripheral blood erythroid progenitors (EPs) from sickle cell disease patients, and evaluated hematopoietic stem/progenitor cell (HSPC) generation after iPS sac induction as well as subsequent erythroid differentiation. MSC-derived iPS sacs yielded greater amounts of immature hematopoietic progenitors (VEGFR2 + GPA−), definitive HSPCs (CD34 + CD45+), and megakaryoerythroid progenitors (GPA + CD41a+), as compared to EP-derived iPS sacs. Erythroid differentiation from MSC-derived iPS sacs resulted in greater amounts of erythroid cells (GPA+) and higher β-globin (and βS-globin) expression, comparable to ES sac-derived cells. These data demonstrate that human MSC-derived iPS sacs allow for more efficient erythroid cell generation with higher β-globin production, likely due to heightened emergence of immature progenitors. Our findings should be important for iPS cell-derived erythroid cell generation. Pluripotent stem cells, Erythroid differentiation, Primitive and definitive hematopoiesis, Hemogenic endothelium Significance Statement We generated βS-globin expressing definitive erythroid cells thorough hemangioblast-like iPS sacs derived from both stromal cells and erythroid progenitors in sickle cell disease patients. The stromal cell-derived iPS sacs allow for more efficient erythroid cell generation with higher βS-globin production, and this occurs through a heightened emergence of immature hematopoietic progenitors in stromal cell-derived iPS sacs. The reliable production of βS-globin from iPS cells is important to investigate pathogenic erythropoiesis in vitro and develop therapeutic strategies with genetic modification for sickle cell disease. Introduction Red blood cell (RBC) transfusion is central to the management of a number of severe congenital and acquired anemias, including hematological malignancies, aplastic anemia, thalassemias, and hemoglobinopathies. RBC transfusion-related complications were significantly reduced by infectious screening and blood group matching; however, every transfusion has associated risks, such as alloimmunization, transmitting infectious disease, and immediate transfusion reactions, among others [1]. Efforts to find potential alternative sources for RBC transfusion have recently been pursued by the development of in vitro erythroid differentiation techniques from human CD34+ cells, peripheral blood mononuclear cells (PBMCs), embryonic stem (ES) cells, and induced pluripotent stem (iPS) cells [2, 3]. Reprogramming methods with genome editing techniques may allow the creation of identical and, if necessary, genetically corrected RBCs for transfusion, especially for diseases such as sickle cell disease (SCD) [4–9]. Autologous iPS cell-derived RBCs can circumvent the significant problem of alloimmunization in bone marrow (BM) failure or hemoglobinopathy patients. In mammalian development, primitive hematopoiesis begins in the yolk sac, which directly generates primitive RBCs expressing ε-globin. Subsequently, definitive hematopoiesis commences in the aorta-gonad-mesonephros (AGM) region, fetal liver, and BM, where definitive RBCs expressing γ-globin or β-globin are produced [10–15]. In the AGM region, hemangioblasts produce both endothelial cells and hematopoietic cells through hemogenic endothelia. The hemogenic endothelia give rise to hematopoietic stem/progenitor cells (HSPCs) [16–20]. Therefore, hemangioblast formation during in vitro differentiation of ES/iPS cells might be crucial for the derivation of definitive erythroid cells [21–23]. In traditional embryoid body (EB)-based in vitro differentiation methods, iPS cell-derived erythroid cells predominantly produce ε-globin and γ-globin without β-globin expression, even though small amounts of β-globin production is observed in ES cell-derived erythroid cells [24–31]. We recently demonstrated that ES cell-derived sacs (ES sacs), known to express hemangioblast markers, allow for efficient erythroid cell generation with β-globin production [23, 32]. The ES sac-derived definitive erythroid cells with β-globin expression were mainly derived from CD34+ HSPCs in ES sacs [32]. We speculated that the iPS cells are more efficiently differentiated to target cells when the iPS cells are generated from a similar source of cells due to epigenetic memory [33]. In addition, difference among iPS cell clones may affect the differentiation abilities. Our initial hypothesis for this study was that erythroid progenitor (EP)-derived iPS cells are more efficiently differentiated to erythroid cells. On the other hand, erythroid specific epigenetic memory might induce direct erythroid differentiation during iPS sac generation and ε-globin expressing primitive erythroid cell generation. It raised the second hypothesis that BM stromal cell (MSC)-derived iPS cells more efficiently generate iPS sacs and emerge immature HSPCs, leading to the generation of definitive erythroid cells expressing higher levels of β-globin. In the current study, we investigated erythroid cell generation using iPS cell lines derived from different starting cell types, including cells from SCD patients, through iPS sac induction. Materials and Methods Transgene-Free iPS Cell Generation with Lentiviral Transduction We generated several iPS cell lines which were derived from either (a) EPs (6 clones) which were differentiated from PBMCs or (b) MSCs (5 clones) from SCD patients (Supporting Information Table). All human subject materials were collected under a protocol approved by the Institutional Review Board of the National Heart, Lung, and Blood Institute (07-H-0113). All patients gave written informed consent. PBMCs were separated from blood of an SCD patient with the homozygous sickle mutation (HbSS), and 2x10e6 PBMCs were differentiated to CD36 + CD71+ EPs (>90% of positivity) for 9-12 days [34], and these EPs were transduced with an Oct4, Klf4, Sox2, and c-Myc encoding lentiviral vector (hSTEMCCA-loxP) at multiplicity of infection (MOI) 5 [35, 36]. BM cells from another SCD patient with HbSS were cultured in α-minimum essential medium (α-MEM; Life Technologies, Grand Island, NY, http://www.thermofisher.com/us/en/home.html) containing 20% fetal bovine serum (FBS; Thermo Fisher Scientific, Waltham, MA, http://www.thermofisher.com/us/en/home.html) and 2 mM L-glutamine (Life Technologies) [37], and the MSCs were confirmed as a spindle-shaped morphology of attached cells (which were separated from blood cells with a round shape of suspension cells). The 1.0 × 10e5 MSCs were transduced with the same reprogramming lentiviral vector at MOI 15 or 25, and 3-5 days after transduction, the transduced cells were cultured on irradiated mouse embryonic fibroblast feeder cells (CF1-MEF, GlobalStem, Gaithersburg, MD, https://www.mti-globalstem.com/) in Dulbecco's Modified Eagle Medium/Nutrient Mixture F-12 (Life Technologies) containing 20% Knockout Serum Replacement (Life Technologies), 10 ng/ml basic fibroblast growth factor (PeproTech, Rocky Hill, NJ, https://www.peprotech.com/en-US), 0.1 mM Nonessential Amino Acids (Life Technologies), 1 mM L-glutamine, and 0.1 mM 2-mercaptoethanol (Life Technologies). 3-6 weeks later, we picked iPS cell-like colonies, and the reprogramming cassette was later excised by Cre recombinase [35]. The iPS cells were evaluated by immunostaining (Nanog, Oct4, SSEA4, Tra1-60, and Tra1-81), alkaline phosphatase stain, karyotyping, and teratoma assay, as previously described [38]. As pluripotent control cells, we used the human H1 ES cell line (WiCell, Madison, WI, https://www.wicell.org/) and established human iPS cell lines (CTRL-2 c1 and CTRL-1 c3) [38]. The CTRL-2 c1 cells were derived from BJ1 neonatal foreskin fibroblasts (American Type Culture Collection (ATCC), Manassas, VA, https://www.atcc.org/), and CTRL-1 c3 cells were derived from adult dermal fibroblasts from a healthy donor. Human ES/iPS Cell-Derived Erythroid Cell Differentiation Through ES/iPS Sacs Human ES/iPS cell-derived erythroid cells were generated through ES/iPS sacs using a four-step culture method, as we previously described (Fig. 2A) [23, 32]. Briefly, in step 1 (ES sac culture phase), small clumps of ES/iPS cells (1.0 × 10e5 cells per 100 mm dish) were cultured on irradiated C3H10T1/2 feeder cells (1.0 × 10e6 cells per 100 mm dish) (ATCC) for 15 days in Iscove's Modified Dulbecco's Medium (IMDM; Sigma Aldrich, Saint Louis, MO, http://www.sigmaaldrich.com/united-states.html) supplemented with 0.2 mg/ml insulin (Lilly, Indianapolis, IN, https://www.lilly.com/home.aspx), 0.11 mg/ml transferrin (Sigma Aldrich), 0.1 µg/ml sodium selenite (Sigma Aldrich), 0.45 mM α-mono-thioglycerol (Sigma Aldrich), 50 μg/ml ascorbic acid (Sigma Aldrich), 20 ng/ml human vascular endothelial growth factor (VEGF; Perpro Tech), 2 mM L-glutamine, and 15% FBS. The ES sac culture media were replaced on days 3, 6, 9, 11, and 13. After 15 days of culture, we observed ES/iPS sacs structures. In step 2 (transfer phase), ES/iPS sacs were gently crushed using a 1,000 μl pipette, passed through a 40 µm cell strainer, and cultured on irradiated OP9 feeder cells (ATCC) for 2 days in the same media used in the culture phase supplemented with 50 ng/ml stem cell factor (SCF; R&D systems, Minneapolis, MN, https://www.rndsystems.com/), 50 ng/ml fms-related tyrosine kinase 3 ligand (R&D systems), 50 ng/ml thrombopoietin (R&D systems), 5 μg/ml interleukin-3 (IL3; R&D systems), 10 ng/ml bone morphogenetic protein 4 (R&D systems) and 5 U/ml erythropoietin (EPO; AMGEN, Thousand Oaks, CA, http://www.amgen.com/). In step 3 (erythroid differentiation phase), only suspension cells were collected and transferred onto fresh OP9 feeder cells for 5 days in IMDM media containing 10 ng/ml SCF, 1.0 ng/ml IL3, 2.0 U/ml EPO, 1.0 μM dexamethasone (VETone, Boise, ID, http://www.vetone.net/), 1.0 μM estradiol (Pfizer, NY, NY, http://www.pfizer.com/), and 20% FBS [39, 40]. In step 4 (erythroid maturation phase), the erythroid differentiation media were replaced with IMDM media containing 2.0 U/ml EPO, 10 ng/ml insulin, 0.56 mg/ml transferrin, 2% bovine serum albumin (Roche, Indianapolis, IN, http://www.roche.com/), 2 mM L-glutamine, and 20% FBS [39, 40]. The cells were cultured for 8 days, and the erythroid maturation media were replaced on days 25 and 28. After the ES/iPS sac-derived erythroid differentiation culture (day 30), we evaluated the morphology and enucleation by Wright-Giemsa staining, as previously described [32]. Colony Forming Unit Assay Following the transfer phase (day 17), we cultured the suspension cells (1.0 × 10e5 per 35-mm dish) in semisolid media (MethoCult H4434 Classic; Stem Cell Technologies, Vancouver, BC, Canada, https://www.stemcell.com/), as previously described [41]. After 2-week culture, the colony forming units (CFUs) were counted by microscope. Flow Cytometry We performed cell surface analysis using a FACSCalibur flow cytometer (Becton Dickinson, East Rutherford, NJ, http://www.bd.com/). The following monoclonal antibodies were used for identifying and characterizing cell subsets: CD31 (clone WM59), CD34 (clone 581 or 563), CD41a (clone HIP8), CD43 (clone 1G10), CD45 (clone HI30), CD71 (clone M-A712), CD73 (clone AD2), vascular endothelial cadherin (VE-cadherin (CD144); clone 55-7H1), glycophorin A (GPA (CD235a); clone GA-R2), VEGF receptor-2 (VEGFR2 (CD309); clone 89106) (all from Becton Dickinson) as well as delta like ligand 4 (DLL4; clone MHD4-46) (Miltenyi, San Diego, CA, http://www.miltenyibiotec.com/en/). Apoptotic cells were evaluated by Annexin V: FITC Apoptosis Detection Kit I (Becton Dickinson). The surface marker-positive (or negative) cell numbers were calculated by multiplying the percentage of surface markers by total cell amounts at the time of evaluation. All cell number data were obtained from the same initial amounts of ES/iPS cells (1.0 × 10e5). Reverse Transcription Quantitative Polymerase Chain Reaction After a 13-day erythroid differentiation culture (day 30 of ES/iPS sac generation protocol), erythroid cells were collected and evaluated to determine RNA expression levels of ɛ-globin, γ-globin, β-globin, and α-globin as we previously described [42]. Quantitative PCR assay was performed using gene-specific primers and probes in the Mx3000P (Agilent Technologies, Santa Clara, CA, http://www.agilent.com/home). The following primer and probe sequences were used: ɛ-globin forward primer, 5′-TGG CAA GGA GTT CAC CCC T-3′; ɛ-globin reverse primer, 5′-AAT GGC GAC AGC AGA CAC C-3′; ɛ-globin probe, 5-ROX- TGC AGG CTG CCT GGC AGA AGC -IBRQ-3′; γ-globin forward primer, 5′-GGC AAC CTG TCC TCT GCC TC-3′; γ-globin reverse primer, 5′-GAA ATG GAT TGC CAA AAC GG-3′; γ-globin probe, 5′-Cy5-CAA GCT CCT GGG AAA TGT GCT GGT G -IBRQ-3′; β-globin forward primer, 5′- CTC ATG GCA AGA AAG TGC TCG-3′; β-globin reverse primer, 5′-AAT TCT TTG CCA AAG TGA TGG G-3′; β-globin probe, 5′-FAM- CGT GGA TCC TGA GAA CTT CAG GCT CCT-IBRQ-3′, α-globin forward primer, 5′-TCC CCA CCA CCA AGA CCT AC-3′, α-globin reverse primer, 5′-CCT TAA CCT GGG CAG AGC C-3′, α-globin probe, 5′-HEX-TCC CGC ACT TCG ACC TGA GCC A -IBRQ-3′ [43–46]. We used a control plasmid containing one copy of ε-, γ-, β-, and α-globin cDNA, and calculated relative amounts of ɛ-, γ-, and β-globin RNA which were standardized by α-globin signals. Reverse Phase High Pressure Liquid Chromatography For globin protein analysis, we collected erythroid cells following 13-day erythroid differentiation (day 30) from ES/iPS sacs. After washing three times with phosphate buffered saline (Corning, One Riverfront Plaza, NY, https://www.corning.com/worldwide/en.html), the cell pellet was resuspended in 100 μl high pressure liquid chromatography grade water (Sigma-Aldrich) and vortexed to lyse the cells followed by a centrifugation at 16,000g for 20 minutes at 4°C. The 90 μl supernatant was mixed to 10 μl of 100 mM Tris (2-carboxyethyl) phosphine (Thermo Fisher Scientific) and incubated for 5 minutes at room temperature. After incubation, we added 85 μl solution containing 0.1% trifluoroacetic acid (TFA) (Thermo Fisher Scientific) and 32% acetonitrile (Honeywell Burdick & Jackson, Morris Plains, NJ, https://labchemicals-honeywell.com/) and well mixed it by a vortex. After a centrifugation at 16,000g for 5 minutes at 4°C, the supernatant was transferred to a sample vial (SUN-Sri, Rockwood, TN, https://www.sun-sri.com/). Ten microliters of the samples were injected and analyzed in 0.8 ml per minute flow for 45 minutes using the Agilent 1100 HPLC (Agilent Technologies) equipped with a reverse phase column, Aeris 3.6 μm Widepore C4 200 (250 × 4.6mm, Phenomenex, Torrance, CA, http://www.phenomenex.com/) with two solvents: solvent A, 0.12% TFA in water and solvent B, 0.08% TFA in acetonitrile. The gradient for the separation of globin protein was started with 35% of solvent B and changed % of solvent B as follows: 3 minutes at up to 41.2%, 3 minutes at up to 41.6%, 5 minutes at up to 42%, 4 minutes at up to 42.4%, 6 minutes at up to 42.8%, 6 minutes at up to 44.4%, 6 minutes at up to 47%, 7 minutes at up to 75% and re-equilibrated for 10 minutes at 35%. The globin types were detected at 215 nm and confirmed by Agilent HPLC-6224 mass spectrometer equipped with an ESI interface and a time-of-flight mass detector (Agilent Technologies) as described [47, 48]. Hemoglobin Electrophoresis After a 13-day erythroid differentiation culture (day 30), erythroid cells were collected and evaluated to determine the hemoglobin types by hemoglobin electrophoresis (HELENA LABORATORIES, Beaumount, TX, http://www.helena.com/) according to the manufacturer's instructions. Statistical Analysis Statistical analyses were performed using the JMP 11 software (SAS Institute Inc., Cary, NC, http://www.sas.com/en_us/home.html). The sample sizes (n) were defined by biological replicates. All experiments were performed in triplicate. The averages in various conditions were evaluated by Tukey's honest significant difference test (one-way analysis of variance among all groups) using all raw data. The variabilities among iPS clones were evaluated by standard deviations of average data in each clone, which were shown as error bars in all figures. The variances among cell sources and clones (or MOIs) were evaluated by analysis of variance with random effects. A p value of <.01 or .05 was deemed significant. Results Generation of iPS Cells Derived from BM Stromal Cells and Peripheral Blood Erythroid Progenitors in SCD Patients To test our two hypotheses; (a) EP-derived iPS cells are more efficiently differentiated to erythroid cells, and (b) MSC-derived iPS cells more efficiently emerge immature HSPCs which results in greater erythroid cell generation, we generated several iPS cell lines which were derived from both MSCs (5 clones) and peripheral blood EPs (6 clones) in SCD patients (Fig. 1A, 1B). We transduced MSCs and EPs with a reprogramming lentiviral vector, and obtained iPS cell-like colonies followed by excision of the reprogramming cassette [35]. Pluripotent stem cell markers were detected by immunostaining, which were comparable to H1 ES cells (Fig. 1C). In teratoma assays, all clones of iPS cells were differentiated to various tissues including three germ layers (Fig. 1D). We also observed a normal karyotype in all of iPS cell clones. Figure 1 Open in new tabDownload slide Generation of iPS cells derived from bone marrow stromal cells (MSCs) and peripheral blood erythroid progenitors (EPs) in sickle cell disease (SCD) patient. (A and B) We generated several clones of iPS cells which were derived from (A) MSCs (5 clones) and (B) peripheral blood EPs (six clones) which were differentiated from PBMCs in SCD patients. We transduced MSCs and EPs with a reprogramming lentiviral vector, and obtained iPS cell-like colonies followed by excision of the reprogramming cassette. (C): Pluripotent stem cell markers were detected by immunostaining (Nanog, Oct4, SSEA4, Tra1-60, and Tra1-81) and ALP staining. (D): All clones of iPS cells were differentiated to various tissues including three germ layers in teratoma assays. We observed a normal karyotype in all clones of iPS cells. Abbreviations: ALP, alkaline phosphatase; ES cells, embryonic stem cells; iPS, induced pluripotent stem; MOI: multiplicity of infection; PBMCs, peripheral blood mononuclear cells. Figure 1 Open in new tabDownload slide Generation of iPS cells derived from bone marrow stromal cells (MSCs) and peripheral blood erythroid progenitors (EPs) in sickle cell disease (SCD) patient. (A and B) We generated several clones of iPS cells which were derived from (A) MSCs (5 clones) and (B) peripheral blood EPs (six clones) which were differentiated from PBMCs in SCD patients. We transduced MSCs and EPs with a reprogramming lentiviral vector, and obtained iPS cell-like colonies followed by excision of the reprogramming cassette. (C): Pluripotent stem cell markers were detected by immunostaining (Nanog, Oct4, SSEA4, Tra1-60, and Tra1-81) and ALP staining. (D): All clones of iPS cells were differentiated to various tissues including three germ layers in teratoma assays. We observed a normal karyotype in all clones of iPS cells. Abbreviations: ALP, alkaline phosphatase; ES cells, embryonic stem cells; iPS, induced pluripotent stem; MOI: multiplicity of infection; PBMCs, peripheral blood mononuclear cells. More Efficient Generation of β-Globin-Expressing Erythroid Cells Using Stromal Cell-Derived iPS Cells The MSC- and EP-derived iPS cells, previously established control iPS cells (fibroblast (FB)-derived iPS cell clones), and H1 ES cells were used to generate ES/iPS sacs supplemented with VEGF for 15 days [23]. After 2-day culture of ES/iPS sac-derived spherical cells on OP9 feeder cells, the suspension cells were differentiated into erythroid cells for 13 days (Fig. 2A) [39]. After a 13-day erythroid differentiation culture (day 30), we observed eosinophilic erythroid cells with a high density of chromatin (0.5%-1.4% of enucleated cells), which were differentiated from iPS sacs as well as ES sacs (Supporting Information Fig. 1). Figure 2 Open in new tabDownload slide More efficient generation of β-globin-expressing erythroid cells using bone marrow stromal cells (MSC)-derived iPS cells. (A): The MSC- and erythroid progenitor (EP)-derived iPS cells and controls (fibroblast [FB]-derived iPS cells and embryonic stem [ES] cells) were used to generate ES/iPS cell-derived sacs (ES/iPS sacs) supplemented with VEGF for 15 days [23]. After 2-day culture of ES/iPS sac-derived spherical cells on OP9 feeder cells, the suspension cells were differentiated into erythroid cells for 13 days [39]. (B): At the end of ES/iPS sac maturation (15 days), greater amounts of CD34 + CD45+ hematopoietic stem/progenitor cells emerged in both MSC- and EP-derived iPS sacs, compared to FB-derived iPS sacs. (C): After an additional 2 weeks of erythroid differentiation, we observed greater amounts of GPA+ erythroid cells from both MSC- and EP-derived iPS sacs, compared to FB-derived iPS sacs. Interestingly, MSC-derived iPS sacs resulted in greater amounts of GPA+ erythroid cells, compared to EP-derived iPS sacs. (D): Higher β-globin RNA expression was observed in erythroid cells from MSC-derived iPS sacs, compared to EP- and FB-derived iPS sacs, which was comparable to ES sac-derived erythroid cells. (E): We detected βS-globin protein (β-globin with the sickle mutation) production in erythroid cells from MSC-derived iPS sacs by a reversed phase high-performance liquid chromatography, which amounts are similar to β-globin protein in ES sac-derived erythroid cells. However, either βS- or β-globin protein was not detectable in erythroid cells from EP- and FB-derived iPS sacs. (F): HbS in MSC-derived erythroid cells was detected by hemoglobin electrophoresis. **, p < .01; *, p < .05 evaluated by Tukey's honest significant difference test. Abbreviations: BMP4, bone morphogenetic protein 4; EPO, erythropoietin; FL, fms-related tyrosine kinase 3 ligand; eHb, embryonic hemoglobin; HbA, adult hemoglobin; HbF, fetal hemoglobin; HbS, sickle hemoglobin; IL3, interleukin 3; iPS, induced pluripotent stem; SCF, stem cell factor; TPO, thrombopoietin; VEGF, vascular endothelial growth factor. Figure 2 Open in new tabDownload slide More efficient generation of β-globin-expressing erythroid cells using bone marrow stromal cells (MSC)-derived iPS cells. (A): The MSC- and erythroid progenitor (EP)-derived iPS cells and controls (fibroblast [FB]-derived iPS cells and embryonic stem [ES] cells) were used to generate ES/iPS cell-derived sacs (ES/iPS sacs) supplemented with VEGF for 15 days [23]. After 2-day culture of ES/iPS sac-derived spherical cells on OP9 feeder cells, the suspension cells were differentiated into erythroid cells for 13 days [39]. (B): At the end of ES/iPS sac maturation (15 days), greater amounts of CD34 + CD45+ hematopoietic stem/progenitor cells emerged in both MSC- and EP-derived iPS sacs, compared to FB-derived iPS sacs. (C): After an additional 2 weeks of erythroid differentiation, we observed greater amounts of GPA+ erythroid cells from both MSC- and EP-derived iPS sacs, compared to FB-derived iPS sacs. Interestingly, MSC-derived iPS sacs resulted in greater amounts of GPA+ erythroid cells, compared to EP-derived iPS sacs. (D): Higher β-globin RNA expression was observed in erythroid cells from MSC-derived iPS sacs, compared to EP- and FB-derived iPS sacs, which was comparable to ES sac-derived erythroid cells. (E): We detected βS-globin protein (β-globin with the sickle mutation) production in erythroid cells from MSC-derived iPS sacs by a reversed phase high-performance liquid chromatography, which amounts are similar to β-globin protein in ES sac-derived erythroid cells. However, either βS- or β-globin protein was not detectable in erythroid cells from EP- and FB-derived iPS sacs. (F): HbS in MSC-derived erythroid cells was detected by hemoglobin electrophoresis. **, p < .01; *, p < .05 evaluated by Tukey's honest significant difference test. Abbreviations: BMP4, bone morphogenetic protein 4; EPO, erythropoietin; FL, fms-related tyrosine kinase 3 ligand; eHb, embryonic hemoglobin; HbA, adult hemoglobin; HbF, fetal hemoglobin; HbS, sickle hemoglobin; IL3, interleukin 3; iPS, induced pluripotent stem; SCF, stem cell factor; TPO, thrombopoietin; VEGF, vascular endothelial growth factor. At the end of ES/iPS sac maturation (15 days), 3.5-4.8-fold greater amounts of CD34 + CD45+ HSPCs emerged in both MSC- and EP-derived iPS sacs, compared to FB-derived iPS sacs (p < .01) (Fig. 2B). After an additional 2 weeks of erythroid differentiation, we observed 4.5-8.7-fold greater amounts of GPA+ erythroid cells from both MSC- and EP-derived iPS sacs, compared to FB-derived iPS sacs (p < .01) (Fig. 2C). Interestingly, MSC-derived iPS sacs resulted in 1.4-2.0-fold greater amounts of GPA+ erythroid cells (p < .01), compared to EP-derived iPS sacs (Fig. 2C). The ES/iPS sac-derived erythroid cell generation was more strongly affected by cell sources than variations among iPS cell clones (80.8% vs. 19.2%) as well as MOIs used in reprograming vector transduction (64.5% vs. 35.5%) (Supporting Information Fig. 2). We observed 2.6-4.9-fold higher β-globin (21.5 ± 4.3%, p < .01), similar γ-globin (1.0-1.2-fold), and 6.8-18.6-fold lower ɛ-globin RNA expression in erythroid cells from MSC-derived iPS sacs, compared to EP- and FB-derived iPS sacs, which were comparable to ES sac-derived erythroid cells (Fig. 2D). The βS-globin protein (β-globin with the sickle mutation) production was detected by an RP-HPLC in erythroid cells from MSC-derived iPS sacs, and the amounts were similar to β-globin protein (1.9-fold) in ES sac-derived erythroid cells (Fig. 2E). However, either βS- or β-globin protein was not detectable in erythroid cells from EP- and FB-derived iPS sacs. Importantly, sickle hemoglobin in MSC-derived erythroid cells was easily detectable by hemoglobin electrophoresis (Fig. 2F), demonstrating the robustness of this approach as an in vitro model of sickle erythropoiesis. These data demonstrated that MSC-derived iPS sacs allow for more efficient erythroid cell generation with higher β-globin production, compared to EP- and FB-derived iPS sacs. Increased Immature Hematopoietic Progenitor Cells in Stromal Cell-Derived iPS Sacs We evaluated total cell counts during erythroid differentiation from ES/iPS sacs, and found that MSC-derived iPS cells expanded more robustly at the late phase of erythroid differentiation, compared to EP- and FB-derived cells (Fig. 3A). At 5 days after erythroid differentiation (day 22), both MSC- and EP-derived cells contained 11.9-12.2-fold greater amounts of CD45+ hematopoietic cells, compared to FB-derived cells (Fig. 3B). These data suggest that MSC-derived iPS sacs require a longer culture duration to be differentiated to erythroid cells which might be mediated by partially differentiated CD45+ cells [49]. Figure 3 Open in new tabDownload slide More efficient generation of immature hematopoietic stem/progenitor cells (HSPCs) in bone marrow stromal cells (MSC)-derived iPS sacs. (A): The MSC-derived cells expanded more robustly during the late phase of erythroid differentiation, as compared to erythroid progenitor (EP)- and fibroblast (FB)-derived cells, suggesting that MSC-derived iPS sacs might contain greater amounts of immature progenitor cells. (B): At 5 days after erythroid differentiation (day 22), both MSC- and EP-derived cells contained relatively greater amounts of CD45+ hematopoietic cells, compared to FB-derived cells. (C, D): We evaluated immature HSPC markers (including hemogenic endothelia) at day 15, and observed greater amounts of VEGFR2 + GPA- cells (C) and slightly greater amounts of CD31 + CD34+ cells in MSC-derived iPS sacs (D), as compared to EP- and FB-derived iPS sacs. (E): Relatively greater amounts of GPA + CD41a+ megakaryoerythroid progenitors were observed in MSC-derived iPS sacs, compared to EP- and FB-derived iPS sacs (day 15); however, there was no significant difference. (F): When we evaluated more specific hemogenic endothelium markers at day15, greater amounts of VE-cad + CD43-CD73-DDL4-GPA- cells were observed in EP-derived iPS sacs, as compared to MSC- and FB-derived iPS sacs. **, p < .01; *, p < .05 evaluated by Dunnett's test (compared to fibroblast-derived iPS cells) in Figure 3A, and evaluated by Tukey's honest significant difference test in Figures 3B-3F. Abbreviations: GPA, glycophorin A; ES cells, embryonic stem cells; iPS, induced pluripotent stem. Figure 3 Open in new tabDownload slide More efficient generation of immature hematopoietic stem/progenitor cells (HSPCs) in bone marrow stromal cells (MSC)-derived iPS sacs. (A): The MSC-derived cells expanded more robustly during the late phase of erythroid differentiation, as compared to erythroid progenitor (EP)- and fibroblast (FB)-derived cells, suggesting that MSC-derived iPS sacs might contain greater amounts of immature progenitor cells. (B): At 5 days after erythroid differentiation (day 22), both MSC- and EP-derived cells contained relatively greater amounts of CD45+ hematopoietic cells, compared to FB-derived cells. (C, D): We evaluated immature HSPC markers (including hemogenic endothelia) at day 15, and observed greater amounts of VEGFR2 + GPA- cells (C) and slightly greater amounts of CD31 + CD34+ cells in MSC-derived iPS sacs (D), as compared to EP- and FB-derived iPS sacs. (E): Relatively greater amounts of GPA + CD41a+ megakaryoerythroid progenitors were observed in MSC-derived iPS sacs, compared to EP- and FB-derived iPS sacs (day 15); however, there was no significant difference. (F): When we evaluated more specific hemogenic endothelium markers at day15, greater amounts of VE-cad + CD43-CD73-DDL4-GPA- cells were observed in EP-derived iPS sacs, as compared to MSC- and FB-derived iPS sacs. **, p < .01; *, p < .05 evaluated by Dunnett's test (compared to fibroblast-derived iPS cells) in Figure 3A, and evaluated by Tukey's honest significant difference test in Figures 3B-3F. Abbreviations: GPA, glycophorin A; ES cells, embryonic stem cells; iPS, induced pluripotent stem. Since we observed an overall increased erythroid output from MSC-derived iPS sacs, we hypothesized that MSC-derived iPS sacs might contain greater amounts of immature HSPCs (including hemogenic endothelia) and/or immature EPs (including megakaryoerythroid progenitors), and we sought to examine the quantitative and qualitative differences of iPS sac differentiation in MSC-derived iPS cells. We evaluated immature HSPC markers (including those found on hemogenic endothelia) at the end of ES/iPS sac maturation [50], since the cell population (day 15) should contain both suspension cells and adhesion cells (maybe including hemogenic endothelia). We observed 7.7-fold greater amounts of VEGFR2 + GPA- cells (p < .01) (Fig. 3C) and 1.3-1.4-fold greater amounts of CD31 + CD34+ cells in MSC-derived iPS sacs (Fig. 3D), compared to EP- and FB-derived iPS sacs (not detectable VEGFR2 + GPA- cells in EP-derived iPS sacs). 1.8-2.4-fold greater amounts of GPA + CD41a+ megakaryoerythroid progenitors were also observed in MSC-derived iPS sacs, compared to EP- and FB-derived iPS sacs (day 15); however, there was no significant difference (Fig. 3E). Interestingly, when we evaluated more specific hemogenic endothelium markers (more immature) at day15, 3.4-18.2-fold greater amounts of VE-cad + CD43-CD73-DDL4-GPA- cells were observed in EP-derived iPS sacs, as compared to MSC- and FB-derived iPS sacs and ES sacs (p < .01) (Fig. 3F) [29, 51]. These data suggest that EP-derived iPS sacs contains greater amounts of hemogenic endothelia; however, these cells could not efficiently generate HSPCs. Next, we evaluated ES/iPS sac-derived suspension cells 2 days after harvest of spherical cells from ES/iPS sacs (day 17), to test whether suspension cells might contain more hematopoietic cells and less endothelial cells. We observed 10.9-13.9-fold greater amounts of CD34 + CD45+ HSPCs in both MSC- and EP- derived iPS sacs, compared to FB-derived iPS sacs (p < .01) (Fig. 4A). 3.2-16.4-fold greater amounts of GPA + CD41a+ megakaryoerythroid progenitors were also observed in MSC-derived iPS sacs, compared to EP- and FB-derived iPS sacs (p < .05) (Fig. 4B). Additionally, we observed 6.2-22.5-fold greater amounts of GPA-CD41a+ megakaryocyte progenitors in MSC-derived iPS cells, as compared to EP- and FB-derived iPS sacs and ES sacs (p < .01) (Supporting Information Fig. 3), suggesting more efficient generation of megakaryoerythroid progenitors. In CFU assays, 1.8-40.4-fold greater amounts of erythroid, myeloid, and mixed colonies were observed in MSC-derived iPS sacs, compared to EP- and FB-derived iPS sacs (p < .01) (Fig. 4C). In addition, 1.7-8.4-fold greater amounts of apoptotic cells were observed in EP-derived cells, compared to MSC- and FB-derived cells (Fig. 4D), suggesting that EP-derived iPS sacs contains greater amounts of cells which could not be differentiated to erythroid cells. These data suggest that MSC-derived iPS sacs more efficiently produce immature HSPCs and immature EPs, which results in more efficient generation of erythroid cells with β-globin production. Figure 4 Open in new tabDownload slide More efficient generation of megakaryoerythroid progenitors in bone marrow stromal cells (MSC)-derived iPS sacs. (A): We evaluated ES/iPS sac-derived suspension cells 2 days after harvest from ES/iPS sacs (day 17). Greater amounts of CD34 + CD45+ HSPCs were observed in both MSC- and EP- derived iPS sacs, compared to fibroblast (FB)-derived iPS sacs. (B): Greater amounts of GPA + CD41a+ megakaryoerythroid progenitors were observed in MSC-derived iPS sacs, compared to EP- and FB-derived iPS sacs. (C): In colony forming unit assays, greater amounts of erythroid, myeloid, and mixed colonies were observed in MSC-derived iPS sacs, compared to EP- and FB-derived iPS sacs. (D): Relatively greater amounts of apoptotic cells were observed in EP-derived cells. **, p < .01; *, p < .05 evaluated by Tukey's honest significant difference test. Abbreviations: GPA, glycophorin A; ES cells, embryonic stem cells; iPS, induced pluripotent stem. Figure 4 Open in new tabDownload slide More efficient generation of megakaryoerythroid progenitors in bone marrow stromal cells (MSC)-derived iPS sacs. (A): We evaluated ES/iPS sac-derived suspension cells 2 days after harvest from ES/iPS sacs (day 17). Greater amounts of CD34 + CD45+ HSPCs were observed in both MSC- and EP- derived iPS sacs, compared to fibroblast (FB)-derived iPS sacs. (B): Greater amounts of GPA + CD41a+ megakaryoerythroid progenitors were observed in MSC-derived iPS sacs, compared to EP- and FB-derived iPS sacs. (C): In colony forming unit assays, greater amounts of erythroid, myeloid, and mixed colonies were observed in MSC-derived iPS sacs, compared to EP- and FB-derived iPS sacs. (D): Relatively greater amounts of apoptotic cells were observed in EP-derived cells. **, p < .01; *, p < .05 evaluated by Tukey's honest significant difference test. Abbreviations: GPA, glycophorin A; ES cells, embryonic stem cells; iPS, induced pluripotent stem. Discussion We generated MSC- and EP-derived iPS cells from SCD patients (Fig. 1) based upon the notion that EP-derived iPS cells would generate erythroid cells more efficiently, and surprisingly demonstrated that MSC-derived iPS sacs allow for more efficient erythroid cell generation with higher β-globin production, as compared to not only FB-derived iPS cells but also EP-derived iPS cells (Fig. 2C). Even when compared to H1 ES cells, efficient production of erythroid cells (54.6%) can be obtained from MSC-derived iPS sacs, which express equivalent amounts of β-globin (21.5%) and ɛ-globin (0.63%) (Fig. 2D). The MSC-derived iPS cells more efficiently produce cells with an immature HSPC phenotype in iPS sacs (Fig. 3C, 3D), which could result in the generation of β-globin expressing definitive erythroid cells. Furthermore, the erythroid cell generation is strongly affected by the cell source for iPS cells generation (Supporting Information Fig. 2). Our findings could be meaningful for development of alternative RBC transfusion methods using in vitro erythroid differentiation. Importantly, the erythroid differentiation methods that we have developed should prove useful for the evaluation of potential novel therapeutic applications in RBC disease, such as an iPS cell-based RBC disease model, that is, genome editing at the β-globin locus to treat iPS cells derived from cells in SCD patients. Before starting this study, we expected that EP-derived iPS cells should be the best resource to generate erythroid cells in vitro. However, MSC-derived iPS cells generated greater amounts of definitive erythroid cells with higher β-globin expression, as compared to EP-derived iPS cells (Fig. 2D, 2E). We previously demonstrated that CD34+ cells with an HSPC phenotype contained within ES sacs can be differentiated to definitive erythroid cells with higher β-globin expression, while GPA+ cells with an erythroid progenitor phenotype within ES sacs predominantly produces ɛ-globin after further maturation [32]. These data suggest that greater emergence of immature HSPCs may be more crucial to generate definitive erythroid cells than direct differentiation from iPS cells to erythroid cells (not mediated by HSPCs). In this study, MSC-derived iPS cells more expanded during a late phase of erythroid differentiation (after day 22), as compared to EP- and FB-derived iPS cells, and this pattern was similar to the cell growth curve of ES cells (Fig. 3A). In addition, we detected higher amounts of β-globin and lower amounts of ɛ-globin in erythroid cells differentiated from MSC-derived iPS cells, as compared to EP- and FB-derived iPS cells, which was comparable to ES cell-derived erythroid cells (Fig. 2D, 2E). These data suggest that MSC-derived iPS sacs could more efficiently induce definitive hematopoiesis (or erythropoiesis), and efficient definitive erythropoiesis might result from greater emergence of immature HSPCs on a niche-like place within iPS sacs. We then investigated the hypothesis that MSC-derived iPS sacs could more efficiently produce immature hematopoietic progenitors including hemogenic endothelia and megakaryoerythroid progenitors. We observed greater amounts of VEGFR2 + GPA- immature HSPCs (day 15) (Fig. 3C, 3D) and GPA + CD41a+ megakaryoerythroid progenitors (day 17) (Figs. 3E, 4B) in MSC-derived iPS cells, as compared to EP-derived iPS cells, which may explain the more efficient definitive erythroid generation with higher β-globin expression we observed. In addition, greater amounts of erythroid, myeloid and mixed colonies were observed in MSC-derived iPS cells, as compared to EP- and FB-derived iPS cells (Fig. 4C). These data also suggest that MSC-derived iPS sacs contain greater amounts of hematopoietic (and erythroid) progenitor cells. Interestingly, when we evaluated more specifically hemogenic endothelium population (day 15) using detailed cell surface analysis (VE-cad + CD43-CD73-DDL4-GPA-) [29, 51], greater amounts of hemogenic endothelia were observed in EP-derived iPS sacs, as compared to MSC- and FB-derived iPS sacs and ES sacs (Fig. 3F), while EP-derived iPS sacs produced fewer amounts of CD34 + CD45+ HSPCs (Fig. 2B) and GPA+ erythroid cells (Fig. 2C), as compared to MSC-derived iPS sacs. These data suggest that greater amounts of hemogenic endothelia were generated in EP-derived iPS sacs, while the hemogenic endothelia were less efficiently differentiated to HSPCs as compared to MSC-derived iPS sacs. We observed greater amounts of VEGFR2 + GPA- immature HSPCs in MSC-derived iPS sacs as compared to ES cells, while fewer amounts of erythroid cells were obtained from MSC-derived iPS sacs as compared to ES cells. The iPS cell-derived erythroid cell production was reported to decrease by apoptosis during erythroid differentiation, when using a traditional EB-based differentiation method [52]. In our iPS sac-based method, apoptotic cell amounts relatively increased in EP- and MSC-derived cells among the suspension cells at day 17, as compared to ES cells (Fig. 4D). The apoptosis may explain the less efficient erythroid cell generation from EP- and MSC-derived iPS cells than ES cells. In addition, we observed relatively less apoptosis in MSC-derived iPS cells as compared to EP-derived iPS cells, which may explain the greater amounts of erythroid cell generation from MSC-derived iPS cells. The process of ES/iPS sac generation could be suitable for not only erythroid cell generation but also platelet generation [23]. In the current study, we observed greater amounts of GPA-CD41a+ megakaryocyte progenitors in MSC-derived iPS cells at day 17, as compared to EP- and FB-derived iPS cells and ES cells (Supporting Information Fig. 2). These data also suggest that MSC-derived iPS cells can efficiently generate megakaryoerythroid progenitors. MSC-derived iPS sacs might therefore be suitable for in vitro platelet generation. We established an RP-HPLC method to separately analyze β-globin protein and βS-globin protein in ES/iPS-sac derived erythroid cells. We confirmed βS-globin protein production in erythroid cells from MSC-derived iPS sacs (Fig. 2E). The βS-globin protein amounts are similar to β-globin amounts in ES sac-derived erythroid cells, while we could not detect the βS- or β-globin protein in erythroid cells in EP- and FB-derived iPS sacs. Now, we are performing gene correction of the sickle mutation in an MSC-derived iPS cell line, and the RP-HPLC should allow us to evaluate both β-globin and βS-globin production in iPS sac-derived erythroid cells with gene correction. SCD is caused by the point mutation in the β-globin intron 1. β-globin expression is confined to erythroid cells, and specific conditions (such as high-concentration βS-globin and low oxygen) are required for sickling in vitro [53]. Previous data demonstrated a gene correction in iPS cells with the sickle mutation, noted similar erythroid differentiation in gene-corrected and uncorrected iPS cells as compared to normal iPS cells [54]. These data suggest that the sickle mutation does not strongly affect iPS cell biology. When we generated erythroid cells from MSC-derived iPS sacs, we obtained 88 (70-107) erythroid cells per single iPS cell, which are around half amounts of ES sac-derived erythroid cells (160 per cell) and comparable to in vitro erythroid differentiation from mobilized CD34+ cells [30]. In this study, we observed more efficient definitive erythroid differentiation from MSC-derived iPS sacs (Fig. 2C), while greater amounts of hemogenic endothelia were obtained in EP-derived iPS sacs (Fig. 3F). If hemogenic endothelium generation in EP-derived iPS sacs could be followed by definitive erythroid differentiation in MSC-derived iPS sacs, total amounts of definitive erythroid cells might be improved. Regarding the erythroid differentiation culture, around 10-fold more efficient erythroid cell production from human CD34+ cells was reported in a previous study [55], as compared to our erythroid cell production in the same protocol (maybe due to the lot of FBS). Our iPS sac-derived erythroid differentiation protocol is ideal as an in vitro erythroid cell production assay at present; however, further optimization to increase expansion would be required for clinical application. Conclusion In summary, we demonstrated that human MSC-derived iPS sacs allow for more efficient erythroid cell generation with higher β-globin production, and we provide evidence that this occurs through a heightened emergence of immature hematopoietic progenitors (likely including hemogenic endothelia) in MSC-derived iPS sacs. The reliable production of β-globin is important for modeling erythropoiesis in vitro as efforts to produce erythroid cells from iPS cells from patients with SCD has been hampered by the lack of production of the β-globin equivalent in SCD leading to sickle hemoglobin production. This system will now allow comprehensive testing of genetic strategies aimed at correction of the SCD mutation, an important advance for eventual clinical translation of these strategies. Our findings should also be important for in in vitro iPS cell-derived erythroid cell generation with high β-globin expression. Acknowledgments This work was supported by the intramural research program of the National Heart, Lung, and Blood Institute (NHLBI) and the National Institute of Diabetes, Digestive, and Kidney Diseases (NIDDK) at the National Institutes of Health (NIH). We thank Kayo Uchida for statistical analysis. Author Contributions N.U.: Conception and design, data analysis and interpretation, manuscript writing; J.H. and D.L.: Collection and/or assembly of data, data analysis and interpretation; A.F.: Conception and design, collection and/or assembly of data, data analysis and interpretation; T.W. and M.H.: Provision of study material or patients; J.T.: Conception and design, financial support, final approval of manuscript. Disclosure of Potential Conflicts of Interest The authors indicate no potential conflicts of interest. References 1 Kuriyan M , Carson JL. Blood transfusion risks in the intensive care unit . Crit Care Clin 2004 ; 20 : 237 – 253 , ix. Google Scholar Crossref Search ADS PubMed WorldCat 2 Ramesh B , Guhathakurta S. Large-scale in-vitro expansion of RBCs from hematopoietic stem cells . Artif Cells Nanomed Biotechnol 2013 ; 41 : 42 – 51 . Google Scholar Crossref Search ADS PubMed WorldCat 3 Singh VK , Saini A, Tsuji K et al. 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Gonzalez, J. Patrick; Kyrychenko, Sergii; Kyrychenko, Viktoriia; Schneider, Joel S.; Granier, Celine J.; Himelman, Eric; Lahey, Kevin C.; Zhao, Qingshi; Yehia, Ghassan; Tao, Yuan-Xiang; Bhaumik, Mantu; Shirokova, Natalia; Fraidenraich, Diego

Stryjewska, Agata; Dries, Ruben; Pieters, Tim; Verstappen, Griet; Conidi, Andrea; Coddens, Kathleen; Francis, Annick; Umans, Lieve; van IJcken, Wilfred F. J.; Berx, Geert; van Grunsven, Leo A.; Grosveld, Frank G.; Goossens, Steven; Haigh, Jody J.; Huylebroeck, Danny

doi: 10.1002/stem.2521pmid:

O'Brien, Carmel M.; Chy, Hun S.; Zhou, Qi; Blumenfeld, Shiri; Lambshead, Jack W.; Liu, Xiaodong; Kie, Joshua; Capaldo, Bianca D.; Chung, Tung-Liang; Adams, Timothy E.; Phan, Tram; Bentley, John D.; McKinstry, William J.; Oliva, Karen; McMurrick, Paul J.; Wang, Yu-Chieh; Rossello, Fernando J.; Lindeman, Geoffrey J.; Chen, Di; Jarde, Thierry;

Kano, Fumiya; Matsubara, Kohki; Ueda, Minoru; Hibi, Hideharu; Yamamoto, Akihito

doi: 10.1002/stem.2534pmid: 27862629

Abstract Peripheral nerves (PNs) exhibit remarkable self-repairing reparative activity after a simple crush or cut injury. However, the neuronal transection involving a nerve gap overwhelms their repairing activity and causes persistent paralysis. Here, we show that an implantation of the serum-free conditioned medium from stem cells from human exfoliated deciduous teeth (SHED-CM) immersed in a collagen sponge into the nerve gap formed by rat facial nerves transection restored the neurological function. In contrast, SHED-CM specifically depleted of a set of anti-inflammatory M2 macrophage inducers, monocyte chemoattractant protein-1 (MCP-1) and the secreted ectodomain of sialic acid-binding Ig-like lectin-9 (sSiglec-9) lost the ability to restore neurological function in this model. Notably, the combination of MCP-1 and sSiglec-9 induced the polarization of M2 macrophages in vitro, resulting in the expression of multiple trophic factors that enhanced proliferation, migration, and differentiation of Schwann cells, blood vessel formation, and nerve fiber extension. Furthermore, the implantation of a collagen graft containing MCP-1/sSiglec-9 into the nerve gap induced anti-inflammatory M2 macrophage polarization, generated a Schwann-cell bridge instead of fibrotic scar, induced axonal regrowth, and restored nerve function. The specific elimination of M2 macrophages by Mannosylated-Clodrosome suppressed the MCP-1/sSiglec-9-mediated neurological recovery. Taken together, our data suggest that MCP-1/sSiglec-9 regenerates PNs by inducing tissue-repairing M2 macrophages and may provide therapeutic benefits for severe peripheral nerve injuries. Peripheral nerve injury, Dental pulp stem cells, Macrophages, Monocyte Chemoattractant Protein-1, Sialic acid-binding Ig-like lectin-9 Significance Statement The implantation of a collagen graft soaked with SHED-CM into the nerve gap promotes neuronal regeneration. A set of tissue-repairing M2 macrophages inducer in SHED-CM, MCP-1 and sSiglec-9, was essential for nerve regeneration. MCP-1/sSiglec-9-activated M2 macrophages expressed multiple trophic factors for Schwann cells and enhanced their proliferation, migration, and differentiation. Implantation of a MCP-1/sSiglec-9 fully recapitulated the neroregenerative activity of SHED-CM. This is the first report demonstrating the remarkable therapeutic benefits of the stem cell-derived M2 inducers for regenerating severely injured peripheral nerves. We propose that defined factors secreted by stem cells may provide a previously unrecognized therapeutic strategy for the field of stem cell-based regenerative medicine. Introduction Following peripheral nerve injury (PNI), Schwann cells (SCs) and macrophages cooperatively promote nerve regeneration. The damaged axons and myelin sheaths distal to the lesion undergo Wallerian degeneration, in which migrated macrophages remove the myelin and axonal debris from the injury site, while the mature SCs then dedifferentiate and proliferate to form the bands of Bünger, a series of tubular structure that produces trophic factors and extracellular matrix molecules that accelerate axonal regrowth toward their original targets [1–3]. Recent studies have also shown that fibroblasts and endothelial cells/blood vessels in the PNI promote the sorting and directional migration of SCs, respectively, [4, 5]. Thus, the temporal and spatial coordination of multiple cell types promotes peripheral nerve (PN) regeneration. However, while the self-reparative activities of PNs successfully repair crush or cut-induced neuronal injuries, they do not fully repair transection-induced nerve gaps, which are replaced with fibrotic scars. In the clinic, long nerve gaps are commonly treated with autologous nerve grafts. Nevertheless, this approach has a number of disadvantages. There is a limit to the amount of nerve that can be grafted, and loss of function is possible at the site from which the nerve is taken [6]. Biodegradable synthetic nerve conduits, including collagen, polyglycolic acid, aliphatic polyesters, and chitosan, are currently being examined as replacements for autologous nerve grafts. Furthermore, growth factors can be attached to these grafts to enhance their PN-regenerative abilities [7, 8]. However, thus far, these approaches are reported to result in only partial nerve regeneration. The diverse activation states of macrophage-monocyte lineages play pivotal roles in inflammation and tissue homeostasis [9–11]. The pro-inflammatory M1- and anti-inflammatory M2-type macrophages are thought to represent the extreme activation states of macrophages at each end of a continuum. Classically activated M1 cells initiate inflammation and accelerate tissue destruction by releasing high levels of pro-inflammatory cytokines, reactive oxygen species, and nitric oxide (NO), whereas M2 cells counteract pro-inflammatory M1 conditions by secreting anti-inflammatory cytokines, scavenging cellular debris, and suppressing fibrosis. In wound healing, the balance of these polarized macrophages is thought to be important for tissue repair and regeneration [11, 12]. The implantation of scaffolds containing the classical M2 macrophage inducer IL-4 into the transected sciatic nerve in rats was recently shown to promote PN regeneration [13]; however, the mechanistic basis of the M2-mediated PN regeneration is currently unclear. Stem cell transplantation-based therapy is a promising approach for patients with severe PNI [7, 8]. The transplantation of various types of scaffolds containing bone marrow mesenchymal stem cells [14, 15], adipose-derived stem cells [16, 17], umbilical cord-derived mesenchymal stem cells [18, 19], or dental pulp stem cells [20, 21] into the transected nerves of rodents promotes substantial functional recovery. Notably, in most of these studies, neurological function is recovered primarily through paracrine/trophic mechanisms. Stem cells secrete a broad repertoire of trophic and immunomodulatory factors that can be collected as serum-free conditioned medium (CM). We previously reported that the engrafted stem cells from human exfoliated deciduous teeth (SHEDs) and SHED-CM exert similar therapeutic effects for Central Nervous System (CNS) injuries, acute liver failure, and lung injuries [22–26]. Furthermore, we recently reported that the implantation of a silicone tube filled with SHED-CM into the transected rat sciatic nerve promotes PN regeneration [27]. However, the therapeutic mechanisms and factors in SHED-CM responsible for PN regeneration are still largely unknown. We recently reported that the SHED-CM-mediated functional recovery after rat spinal cord injury is associated with the induction of anti-inflammatory M2 macrophage polarization [26]. Furthermore, we identified a novel set of anti-inflammatory M2 macrophage inducers, consisting of monocyte chemoattractant protein-1 (MCP-1) and the secreted ectodomain of sialic acid-binding Ig-like lectin-9 (sSiglec-9), in SHED-CM. MCP-1 is a chemokine that recruits immune cells to inflamed tissues [28], and Siglecs are a large family of sialic-acid-binding type-I transmembrane immunoglobulin-like lectins that modulate immune signaling on various types of immune cells [29]. Notably, MCP-1 and sSiglec-9 synergistically repair the injured rat spinal cord. However, the mechanisms involved in peripheral nerve regeneration are largely dependent on SCs, and are thus distinct from those in repairing CNS injuries. The therapeutic potential of MCP-1/sSiglec-9 in peripheral nerve regeneration has not been examined. In this study, we investigated the roles of MCP-1/sSiglec-9 in SHED-CM-mediated recovery from rodent facial nerve injury (FNI) and the mechanistic basis of the MCP-1/sSiglec-9-mediated regeneration of PNs. Materials and Methods Preparation of SHED-CM SHEDs and SHED-CM were prepared as described previously [30]. In brief, exfoliated deciduous teeth, which were extracted for clinical purposes from three independent donors (aged 6-12 years), were collected at Nagoya University School of Medicine, under the approved guidelines set by Nagoya University (H-73, 2003). Ethical approval was obtained from the Ethics Committee of Nagoya University (permission number 8-2). All participants provided written informed consent. After separating the crown and root, the dental pulp was isolated and then digested in a solution of 3 mg/ml collagenase type I and 4 mg/ml dispase for 1 hour at 37°C. Single-cell suspensions (1-2 × 104 cells/ml) were plated on culture dishes in Dulbecco's modified Eagle's Medium (DMEM, Sigma-Aldrich, St. Louis, MO, http://www.sigmaaldrich.com) supplemented with 10% fetal calf serum (Sigma-Aldrich), and then incubated at 37°C in an atmosphere containing 5% CO2 at 100% humidity. After several (3-9) passages, SHEDs at 70%-80% confluency were washed with phosphate-buffered saline (PBS) twice, and the culture medium was replaced with serum-free DMEM. After a 48-hours incubation, the medium was collected and centrifuged for 3 minutes at 440g. The supernatants were then collected and centrifuged for 3 minutes at 4°C and 17,400g. The resulting supernatants were used as SHED-CM in various experiments. The protein concentration in the SHED-CM was measured using the Bicinchoninic acid protein assay kit (Pierce, Rockford, IL, http:www.thermo.com/pierce), and adjusted to 3 μg/ml with DMEM. CM Cytokine Measurement and Protein Depletion To deplete sSiglec-9 or MCP-1 from SHED-CM, anti-Siglec-9 or anti-MCP-1 antibodies (Abs), prebound to Protein-G Sepharose (GE Healthcare, Piscataway, NJ, http://www.gelifesciences.co.jp), were added to the SHED-CM. The mixtures were incubated overnight at 4°C, and then the Ab beads were removed by centrifugation. For comparison to the dSHED-CM, SHED-CM from the same patient was treated with IgG-beads. The depletion of sSiglec-9 and MCP-1 was confirmed by Enzyme-Linked ImmunoSorbent Assay (ELISA; RayBio Human Siglec-9 ELISA kit, Ray Biotech, Norcross, GA, http://www.raybiotech.com; Human MCP-1 ELISA kit, R&D Systems, Minneapolis, MN, https://www.rndsystems.com). Animals and Surgical Procedures Eight-week-old adult female Sprague Dawley rats weighing 200-230 g were anesthetized with an intraperitoneal injection of ketamine (60-90 mg/kg) and xylazine (100-150 mg/kg). Anesthetized rats were maintained at a constant temperature of 37°C on a warming plate. Under a surgical microscope (Olympus, Tokyo, Japan, http://www.olympus-global.com), the shaved facial skin was opened with a preauricular incision on the left side to expose the branches of the facial nerve. A FNI was created by unilaterally removing 5-mm segments of the Buccal and Marginal branches at sites that were 10 mm distal to the stylomastoid foramen. Next an atelocollagen sponge (CSH-10, KOKEN, Tokyo, Japan, http://www.kokenmpc.co.jp), impregnated with 20 μl CM, DMEM, recombinant human MCP-1 (300-04; Peprotech, London, U.K., https://www.peprotech.com), recombinant human sSiglec-9 (1139-SL; R&D Systems), or PBS was placed in the nerve gap. All of the animal studies were conducted in accordance with the National Institutes of Health Guide for the Care and Use of Laboratory Animals and were approved by the Animal Research Committee of Nagoya University. Vibrissae Movement Scoring The neurological recovery of the transected facial nerve was assessed by examination of vibrissae movements (VMs) [31] using the following scoring system: 0, no movement; 1, barely detectable movement; 2, slight movement; 3, significant but asymmetric movement; 4, symmetric movement. The scores of the observed VMs were recorded by two blinded observers every two weeks throughout the 8-week period, and then the scores of the different treatment groups were compared by statistical analysis. Analysis of Vibrissa Motor Performance VM recovery was measured using digital videos recorded six weeks after FNI. Rats were inserted into a body-restraining apparatus and left in place for approximately 5 minutes to calm down. Digital videos were then recorded using a video camera (HDR-CX370; Sony, Tokyo, Japan, http://www.sony.jp). The videos were recorded at 30 frames/seconds, shutter speed of 10 ms, and resolution of 1024 × 1024. The frequency of VMs and degree of vibrissal protraction were analyzed by movie analysis software (Premiere Elements, Adobe, CA, https://www.adobe.com). Three reference points, demonstrated in Figure 1C, 1D, were used in this analysis, according to the method of Tomov et al. [32]: (1) a point corresponding to the lateral angle of the left orbital, (2) a point corresponding to the lateral angle of the right orbital, and (3) a point in the medial sagittal line, designated as the Frontal-Occipital line (Fr-Occ, perpendicular to the line connecting the two orbital angles), close to the end of the nose. We measured the rostrally open angle between Fr-Occ and most frontal hair shaft. The amplitude was the difference between the maximal protraction and maximal retraction, in degrees. Figure 1 Open in new tabDownload slide Therapeutic effects of SHED-CM or MCP-1/sSiglec-9 in facial nerve injury. (A, B): VM recovery after facial nerve resection. (A) Sham, n = 3; SHED-CM, n = 8; d-SHED-CM, n = 8; DMEM, n = 8. (B) MCP-1/sSiglec-9 (1 μg, n = 9; 100 ng, n = 9; 10 ng, n = 9); sSiglec-9 (100 ng, n = 8); PBS, n = 8. ANOVA with Tukey's post hoc test. Data represent the mean ± SD; *, p < .05; **, p < .01. (C): Precise measurement of the angles and angular velocity of the intact (left) and operated side (right) during protraction (C) and retraction (D) of the vibrissae. The operated side was paralyzed. There was a significant change in the rostrally open angle between Fr-Occ and the most frontal hair shaft during protraction and retraction on the intact side. (D): Quantification of whisking amplitude and Angular velocity. Student's t test. (n = 6 per group) Data represent the mean ± SD. Abbreviations: DMEM, Dulbecco's modified Eagle's medium; MCP-1, monocyte chemoattractant protein-1; PBS, phosphate-buffered saline; sSiglec-9, sialic acid-binding Ig-like lectin-9; SHED, conditioned medium from stem cells from human exfoliated deciduous teeth. Figure 1 Open in new tabDownload slide Therapeutic effects of SHED-CM or MCP-1/sSiglec-9 in facial nerve injury. (A, B): VM recovery after facial nerve resection. (A) Sham, n = 3; SHED-CM, n = 8; d-SHED-CM, n = 8; DMEM, n = 8. (B) MCP-1/sSiglec-9 (1 μg, n = 9; 100 ng, n = 9; 10 ng, n = 9); sSiglec-9 (100 ng, n = 8); PBS, n = 8. ANOVA with Tukey's post hoc test. Data represent the mean ± SD; *, p < .05; **, p < .01. (C): Precise measurement of the angles and angular velocity of the intact (left) and operated side (right) during protraction (C) and retraction (D) of the vibrissae. The operated side was paralyzed. There was a significant change in the rostrally open angle between Fr-Occ and the most frontal hair shaft during protraction and retraction on the intact side. (D): Quantification of whisking amplitude and Angular velocity. Student's t test. (n = 6 per group) Data represent the mean ± SD. Abbreviations: DMEM, Dulbecco's modified Eagle's medium; MCP-1, monocyte chemoattractant protein-1; PBS, phosphate-buffered saline; sSiglec-9, sialic acid-binding Ig-like lectin-9; SHED, conditioned medium from stem cells from human exfoliated deciduous teeth. Retrograde Labeling of the Facial Nucleus Six weeks after generation of the FNI, the buccal branch was exposed and a micro-incision was made 5 mm from the distal end of the graft, where we placed an atelocollagen sponge impregnated with 20 μl of 4% Fluoro-Gold (FG; Fluorochrome, Denver, CO, http://fluorochrome.com), a fluorescent neuronal tracer. After a 2-week labeling period, the brain stem was isolated and sectioned. All of the FG+ nuclei in the facial nucleus were counted. Total number of FG-labeled cells from three individuals in parallel experiments were counted. Morphological Evaluation of Regenerated Nerve Segments Six weeks after the induction of FNI, the tissue segments covering the nerve-resected area were isolated from three rats per each group and fixed with 2.5% glutaraldehyde overnight at 4°C. The proximal halves of the segments were postfixed with 1% osmium tetroxide (OsO4) for 2 hours, carefully dehydrated, and embedded in epoxy resin. Semi-thin sections (1-μm) were cut vertically with an ultramicrotome (EM UC7i, Leica Microsystems, Denver, CO, http://www.leica-microsystems.com), stained with 1% toluidine blue solution, and examined under a light microscope (BZ-9000, Keyence, Osaka, Japan, http://www.keyence.co.jp). The density of the myelinated fibers (fibers/2500 mm2) was analyzed from five nonoverlapping visual fields per specimen. Ultra-thin sections (60-nm) were stained with lead citrate and uranyl acetate, and then examined under a transmission electron microscope (TEM; JEM-1400; JEOL, Tokyo, Japan, http://www.jeol.co.jp). Photographs of the tissue were captured in ten random fields from each ultra-thin section. We chose axons exhibiting a comparable diameter and evaluated the G-ratio as the ratio of the inner axonal diameter to the total outer diameter. Immunohistochemical Analysis Rats from each group were deeply anesthetized before undergoing intracardiac perfusion with PBS and then with 4% paraformaldehyde. The tissue segments were isolated from three rats per each group and embedded in OCT compound (Sakura Finetek, Tokyo, Japan, http://www.sakura-finetek.com), and 4-μm sagittal sections were generated with a cryostat (Leica CM3050S, Leica Biosystems, Denver, CO, http://www.leicabiosystems.com). The sections were permeabilized with 0.1% (v/v) Triton X-100 in PBS for 20 minutes, blocked with 5% (v/v) bovine serum albumin for 30 minutes, and incubated overnight with the following primary Abs: mouse anti-CD11b IgG (1:1,000, ab33827, Abcam, Cambridge, U.K., http://www.abcam.com), rabbit anti-iNOS (inducible nitric oxide synthase) IgG (1:500, ab15323, Abcam), rabbit anti-CD206 IgG (1:1,000, ab64693, Abcam), and rabbit anti-S-100b (1:3,000, ab41548, Abcam). The following secondary Abs were used: anti-mouse IgG–Alexa Fluor 488, anti-rat IgG–Alexa Fluor 488, anti-rabbit IgG–Alexa Fluor 546, anti-goat IgG–Alexa Fluor 546, and anti-rabbit IgG–Alexa Fluor 647. After counterstaining with DAPI, (Sigma-Aldrich), tissue images were captured with a universal fluorescence microscope (BZ9000; Keyence). Cells were counted in at least five images from three individuals in parallel experiments. Real-Time Quantitative Polymerase Chain Reaction Total RNA was quantified by a spectrophotometer, and RNA integrity was checked on 1% agarose gels. Reverse transcription reactions were performed with Superscript III reverse transcriptase (Invitrogen, Carlsbad, CA, http://www.thermofisher.com) using 0.5 μg total RNA in a 25 μl total reaction volume. Real-time quantitative polymerase chain reaction was performed using the THUNDERBIRD SYBR qPCR Mix (Toyobo, Osaka, Japan, http://www.toyobo-global.com) and the StepOnePlus Real-Time PCR System (Applied Biosystems, Forster City, CA, http://www.appliedbiosystems.com). The primers were designed using Primer3 (Supporting Information Table 1). Bone Marrow Macrophage Induction Assay Bone marrow cells from the femurs of 8-week-old female Sprague Dawley rats were plated on 6-cm dishes (2.0 × 106 cells per dish) and differentiated into macrophages in DMEM supplemented with 20 ng/ml macrophage colony stimulating factor at 37°C in 5% CO2 for 7 days. The macrophages were then incubated with serum-free DMEM, 100 ng/ml recombinant human MCP-1 (300-04, Peprotech) and recombinant human sSiglec-9 (1139-SL, R&D Systems), or 20 ng/ml IL-4 (204-IL, R&D Systems) for 24 hours. Phase contrast images of the induced macrophages were captured with a microscope digital camera (Leica DFC290 HD, Leica). The mRNA expression of M2-type cell markers or trophic factors was examined by qPCR analysis. Human SC Proliferation and Migration Analyses Passage 5 human SCs were obtained from Sciencell Research Laboratories (Cat. #1700, Carlsbad, CA, https://www.sciencellonline.com). The cells were cultured for 24 hours with serum-free DMEM, 100 ng/ml MCP-1/sSiglec-9, or MCP-1/sSiglec-9-induced M2 macrophage CM (M2 (MCP-1/sSiglec-9)-CM). For quantitative analysis of cell proliferation, 10 μl of WST-8 solution (Cell Counting Kit-8, Dojindo, Kumamoto, Japan, http://www.dojindo.co.jp) was added to each well. After an incubation at 37°C for 1 hour in a humidified CO2 incubator, the absorbance at 450 nm was monitored with a microplate reader (SmartSpec3000; BIO-RAD, Tokyo, Japan, http://www.bio-rad.com). Human SC-migration was assessed using transwell membrane chambers (8-μm pore size, D Falcon, Bedford, MA, http://www.bd.com) as described previously [33]. Briefly, human Schwann cells were seeded into the upper chambers at 1 × 105 cells per well in 700 μl serum-free DMEM, and 1,400 μl of serum-free DMEM (control), DMEM with MCP1/sSiglec-9, or M2 (MCP-1/sSiglec-9)-CM was added to the lower chambers. After incubation for 48 hours at 37°C in 5% CO2, the nonmigrating cells in the upper chamber were removed with cotton swabs, and the membranes were fixed in 4% paraformaldehyde and stained with hematoxylin. The cells that had migrated across the membrane were counted under an inverted microscope. Neurite Growth Assay of Dorsal Root Ganglion Neurons Dorsal root ganglion (DRG) neurons were harvested from 3-day-old SD rats as described previously [34]. The neurons were resuspended in neurobasal medium (Gibco, Waltham, MA, https://www.thermofisher.com/) containing 2 mM l-glutamine (Gibco), 2% B27 (Gibco), and antibiotic—antimycotic solution (Gibco), and then seeded onto poly-d-lysine/laminin-coated 24-well plates at 400-500 neurons per well. The DRG neurons were incubated with DMEM (-), MCP-1/sSiglec-9, M0-CM, M2 (IL-4)-CM, or M2 (MCP-1/sSiglec-9)-CM for 48 hours. The neurons were then fixed in 4% paraformaldehyde for 15 minutes and incubated with a primary monoclonal antibody against Neurofilament (1:500; Sigma-Aldrich) overnight at 4°C, followed by incubation with an Alexa Fluor 633-conjugated anti-mouse IgG secondary antibody (1:500; Invitrogen) for 30 minutes at room temperature. The stained neurons were examined under a fluorescence microscope (BZ9000; Keyence). The average neurite length was quantitatively analyzed using BZ9000 analysis software (Keyence). In Vivo M2 Macrophage Depletion Analysis M2 macrophages were depleted from FNI rats by using the Mannocylated-Clodrosome Macrophage Depletion Kit (SKU # 8901, Encapsula NanoSciences LLC, Nashville, TN, http://www.encapsula.com). Ten microliter of mannosylated-Clodrosome (m-Clodrosome) or Encapsome (control liposomes) was implanted in the nerve gap together with an atelocollagen sponge containing MCP-1/sSiglec-9. Statistical Analysis An unpaired two-tailed Student's t test was used to compare two groups. To analyze three or more independent groups, we used repeated-measures ANOVA with Tukey's post hoc test (SPSS version 19.0). A p value < .05 was considered to be statistically significant. Results SHEDs Promote Functional Recovery of the Resected Facial Nerve Through MCP-1/sSiglec-9-Mediated Signals First, we evaluated the therapeutic effects of the SHED-secreted factors in the rat FNI model. The SHEDs used in this study exhibit a fibroblastic morphology with a bi-polar spindle shape, express MSC markers (CD90, CD73, and CD105), but not endothelial/hematopoietic markers (CD34, CD45, CD11b/c, or HLA-DR), and are capable of undergoing adipogenic, chondrogenic, and osteogenic differentiation [30]. SHED-secreted factors were collected in the SHED-CM and absorbed by a collagen sponge that was implanted unilaterally in the nerve-resected area. The recovery in neurological function was evaluated by vibrissae movement (VM) assessment (see Materials and Methods). Our results showed that the DMEM-treated control rats exhibited severe paralysis during the entire observation period, while the SHED-CM-treated rats exhibited markedly improved VMs that were synchronized with that of the contralateral uninjured side 5 weeks after injury (Fig. 1A). Administration of SHED-CMs from three independent donors exhibited similar levels of functional recovery (data not shown). To examine the role of MCP-1 and sSiglec-9 in the SHED-CM-mediated functional recovery after FNI, both MCP-1 and sSiglec-9 were specifically immunodepleted from SHED-CM (dSHED-CM; Supporting Information Table 2). Notably, the dSHED-CM-treated rats exhibited severe paralysis that was similar to that of the DMEM-treated control rats (Fig. 1A). These results demonstrated that MCP-1 and sSiglec-9 were essential for the SHED-CM-mediated functional recovery after FNI. MCP-1/sSiglec-9 Promotes Functional Recovery After Rat FNI Next, we examined the therapeutic effects of MCP-1/sSiglec-9 at three different doses (10, 100, or 1,000 ng of each protein) in comparison to that of sSiglec-9 alone at 100 ng. We found that rats receiving the intermediate or high dose of MCP-1/sSiglec-9 exhibited VMs that were comparable to those of the SHED-CM-treated rats, while the low-dose MCP-1/sSiglec-9- or sSiglec-9-treated rats exhibited minimal improvement (Fig. 1B). We also evaluated the recovery of the amplitude and angular velocity of the VMs by digital video recording (see Materials and Methods). Six weeks after the operation, the mean amplitude of the operated side of the PBS and MCP-1/sSiglec-9 groups was approximately 12.3% and 70.5% of that of the contralateral side, respectively. The angular velocity of the VMs in the PBS and MCP-1/sSiglec-9 groups was approximately 0.42% and 72.9% of that of the contralateral side, respectively (Fig. 1C, 1D). These results demonstrated that MCP-1 and sSiglec-9 acted synergistically to promote the functional recovery of the transected facial nerve. MCP-1/sSiglec-9 Promotes FN Regeneration To evaluate FN regeneration, we performed a histological analysis of semi-thin sections of the nerve segments from the middle of the collagen-engrafted area. Six weeks after FNI, the facial nerves of both the SHED-CM and MCP-1/sSiglec-9 treatment groups displayed remarkable regeneration, each exhibiting a large nerve fascicle containing many myelinated axons. In contrast, the transected facial nerves in the DMEM, PBS, and dSHED-CM treatment groups were filled with fibrotic tissue and contained a minimal number of small fascicles (Fig. 2A). Quantitative analysis of the fiber densities showed that the SHED-CM and MCP-1/sSiglec-9 treatment groups exhibited significantly higher fiber densities than the DMEM, dSHED-CM and PBS treatment groups (Fig. 2B). Furthermore, histological analysis of the ultra-thin sections with TEM revealed that the diameter of the myelinated fibers and myelination thickness in the SHED-CM- and MCP-1/sSiglec-9-treated rats were significantly greater than those of the DMEM- and PBS-treated rats (Fig. 2C). The ratio of the inner axonal diameter to the total outer diameter (g-ratio) is commonly used as a functional and structural index of axonal myelination [35]. The theoretical g-ratio associated with optimal nerve conduction velocity is 0.6, while that of an unmyelinated nerve is 1.0. The g-ratios of the SHED-CM and MCP-1/sSiglec-9 treatment groups were between 0.602 and 0.692, reflecting strong remyelination, and similar to that of the Sham-operated group, while that of the DMEM-treated control group was significantly higher (Fig. 2D). Figure 2 Open in new tabDownload slide Morphological evaluation of the regenerated facial nerve by toluidine blue-stained of semi-thin sections and transmission electron microscope analysis of ultra-thin sections. (A): Toluidine blue-stained semi-thin sections of nerve segments taken from the middle of the collagen engrafted areas six weeks after facial nerve injury (FNI). Scale bar, 25 μm. (B): Quantification of myelinated fiber densities. (C): Osmium staining of sections of the axial facial nerve taken from the middle of the collagen-engrafted area 6 weeks after FNI. (D): Quantitative analysis of G-ratios (the ratio of the inner axonal diameter to the total outer diameter). ANOVA with Tukey's post hoc test (n = 3 per group). Data represent the mean ± SD; *, p < .05; **, p < .01. Scale bar, 50 μm. Abbreviations: DMEM, Dulbecco's modified Eagle's medium; MCP-1, monocyte chemoattractant protein-1; PBS, phosphate-buffered saline; sSiglec-9, sialic acid-binding Ig-like lectin-9; SHED, conditioned medium from stem cells from human exfoliated deciduous teeth. Figure 2 Open in new tabDownload slide Morphological evaluation of the regenerated facial nerve by toluidine blue-stained of semi-thin sections and transmission electron microscope analysis of ultra-thin sections. (A): Toluidine blue-stained semi-thin sections of nerve segments taken from the middle of the collagen engrafted areas six weeks after facial nerve injury (FNI). Scale bar, 25 μm. (B): Quantification of myelinated fiber densities. (C): Osmium staining of sections of the axial facial nerve taken from the middle of the collagen-engrafted area 6 weeks after FNI. (D): Quantitative analysis of G-ratios (the ratio of the inner axonal diameter to the total outer diameter). ANOVA with Tukey's post hoc test (n = 3 per group). Data represent the mean ± SD; *, p < .05; **, p < .01. Scale bar, 50 μm. Abbreviations: DMEM, Dulbecco's modified Eagle's medium; MCP-1, monocyte chemoattractant protein-1; PBS, phosphate-buffered saline; sSiglec-9, sialic acid-binding Ig-like lectin-9; SHED, conditioned medium from stem cells from human exfoliated deciduous teeth. Effect of MCP-1/sSiglec-9 on FNI-Induced Inflammatory Response We next examined the mRNA expression profiles of factors involved in pro- and anti-inflammatory responses. Twenty-four hours after FNI, the expression of the pan-macrophage marker, EMR-1, was unchanged in the transected FNs of both the PBS and MCP-1/sSiglec-9 treatment groups. The inflammatory mediator mRNAs, Il-1β, Tnf-α, Il-6, and iNOS were upregulated in the PBS group, but were markedly suppressed in the MCP-1/sSiglec-9 group (Fig. 3A). In contrast, the anti-inflammatory mRNAs Arg-1, Cd206, and Il-10 were uniquely upregulated in the MCP-1/sSiglec-9 treatment group. Immunohistological analysis of the resected area of the FNI showed that the number of CD11+ cells was significantly increased in the MCP-1/sSiglec-9 group. Notably, the proportion of iNOS+ M1 macrophages was markedly reduced, but that of CD206+ M2 macrophages was increased in the MCP-1/sSiglec-9 group compared to the PBS control group (Fig. 3B–3D). These results indicated that MCP-1/sSiglec-9 treatment shifted the FNI-induced pro-inflammatory M1 environment to an anti-inflammatory M2 one. Figure 3 Open in new tabDownload slide MCP-1/sSiglec-9 suppresses the facial nerve injury (FNI)-induced pro-inflammatory M1 response and generates the anti-inflammatory M2 response. (A): qPCR analysis of the indicated mRNAs in the resected nerve 24 hours after FNI. Results are expressed relative to the level in the sham-operated model. ANOVA with Tukey's post hoc test (n = 3 rats per group). Data represent the mean ± SD; *, p < .05; **, p < .01. (B, C): Representative images of immunohistological staining of macrophages accumulating at the resected area of the FNI at 24 hours after FNI. (B) iNOS+/CD11b+ M1 macrophages and (C) CD206+/CD11b+ M2 macrophages in the PBS and MCP-1/sSiglec-9 treatment groups. Scale bars in left column are 200 μm. (D): Quantification of CD11b+cells and ratio of iNOS+/CD11b+ versus CD206+/CD11b+ cells. Student's t test (n = 3 per group). Data represent the mean ± SD; *, p < .05. Abbreviations: MCP-1, monocyte chemoattractant protein-1; PBS, phosphate-buffered saline. Figure 3 Open in new tabDownload slide MCP-1/sSiglec-9 suppresses the facial nerve injury (FNI)-induced pro-inflammatory M1 response and generates the anti-inflammatory M2 response. (A): qPCR analysis of the indicated mRNAs in the resected nerve 24 hours after FNI. Results are expressed relative to the level in the sham-operated model. ANOVA with Tukey's post hoc test (n = 3 rats per group). Data represent the mean ± SD; *, p < .05; **, p < .01. (B, C): Representative images of immunohistological staining of macrophages accumulating at the resected area of the FNI at 24 hours after FNI. (B) iNOS+/CD11b+ M1 macrophages and (C) CD206+/CD11b+ M2 macrophages in the PBS and MCP-1/sSiglec-9 treatment groups. Scale bars in left column are 200 μm. (D): Quantification of CD11b+cells and ratio of iNOS+/CD11b+ versus CD206+/CD11b+ cells. Student's t test (n = 3 per group). Data represent the mean ± SD; *, p < .05. Abbreviations: MCP-1, monocyte chemoattractant protein-1; PBS, phosphate-buffered saline. MCP-1 and sSiglec-9 Synergistically Induce the Polarization of M2 Macrophages, Which Express Multiple Trophic Factors for SCs Bone marrow macrophages (BMMs) induced by M-CSF displayed a spherical cell shape, and were designated as M0 macrophages. BMMs treated with MCP-1/sSiglec-9 or IL-4 exhibited an elongated shape and increased expression of the M2 marker mRNAs, CD206 and Arg-1 (Fig. 4A, 4B). Furthermore, the MCP-1/sSiglec-9-induced M2 macrophages also expressed increased levels of multiple mRNAs encoding SC trophic factors, including Igf-1 (Insulin-like growth factor-1), Nrg1 (Neuregulin-1), Bdnf (Brain-derived neurotrophic factor), Vegf-α (Vascular endothelial growth factor-α), Cntf (Ciliary neurotrophic factor), Hgf (Hepatocyte growth factor), Tgf-β (Transforming growth factor β), and Fgf2 (Fibroblast growth factor 2) (Fig. 4B). Figure 4 Open in new tabDownload slide MCP-1/sSiglec-9 induces M2 macrophages in vitro. (A): Representative phase contrast images of rat primary BMMs treated with DMEM, 100 ng/ml MCP-1/sSiglec-9, or 20 ng/ml IL-4. Scale bar, 100 μm. (B): qPCR analysis of the indicated mRNAs. Results are expressed relative to the level in the DMEM-treated cells. ANOVA with Tukey's post hoc test (n = 4 per group). Data represent the mean ± SD; *, p < .05; **, p < .01. Abbreviations: Bdnf, brain-derived neurotrophic factor; Cntf, ciliary neurotrophic factor; DMEM, Dulbecco's modified Eagle's medium; Fgf2; fibroblast growth factor 2; Hgf, hepatocyte growth factor; Igf-1, insulin-like growth factor-1; MCP-1, monocyte chemoattractant protein-1; Nrg1, neuregulin-1; sSiglec-9, sialic acid-binding Ig-like lectin-9; Tgf-β, transforming growth factor β; Vegf-α, vascular endothelial growth factor-α. Figure 4 Open in new tabDownload slide MCP-1/sSiglec-9 induces M2 macrophages in vitro. (A): Representative phase contrast images of rat primary BMMs treated with DMEM, 100 ng/ml MCP-1/sSiglec-9, or 20 ng/ml IL-4. Scale bar, 100 μm. (B): qPCR analysis of the indicated mRNAs. Results are expressed relative to the level in the DMEM-treated cells. ANOVA with Tukey's post hoc test (n = 4 per group). Data represent the mean ± SD; *, p < .05; **, p < .01. Abbreviations: Bdnf, brain-derived neurotrophic factor; Cntf, ciliary neurotrophic factor; DMEM, Dulbecco's modified Eagle's medium; Fgf2; fibroblast growth factor 2; Hgf, hepatocyte growth factor; Igf-1, insulin-like growth factor-1; MCP-1, monocyte chemoattractant protein-1; Nrg1, neuregulin-1; sSiglec-9, sialic acid-binding Ig-like lectin-9; Tgf-β, transforming growth factor β; Vegf-α, vascular endothelial growth factor-α. MCP-1/sSiglec-9-Induced M2 Macrophages Promote the Proliferation, Migration, and Differentiation of SCs and Stimulate the Neurite Outgrowth of DRG Neurons Our quantitative WST-8 analysis showed that treating cultured SCs directly with the MCP-1/sSiglec9 proteins had only a minimal effect on SC proliferation, and a trans-well cell migration assay showed that MCP-1/sSiglec-9 had only minimal effects on SC migration (Fig. 5A, 5B). In contrast, treating SCs with the CM from M0, or from IL-4- or MCP-1/sSiglec-9-induced M2 macrophages [M2 (IL-4) or M2 (MCP1/sSiglec-9), respectively], significantly increased the SC proliferation and migration. Furthermore, treating SCs with M2 (IL-4 or MCP1/sSiglec-9)-CM, but not with MCP-1/sSiglec-9 proteins, increased the expression of an immature SC gene (Oct-6), mature SC genes (Krox-20, Mbp, and Mpz), and neurotrophic factors involved in SC maturation (Bdnf and Igf-1) (Fig. 5C). Furthermore, CM from M2 (MCP1/sSiglec-9), but not MCP1/sSiglec-9 proteins, stimulated neurite outgrowth of the DRG neurons (Fig. 5D). Quantitative analysis showed that the neurite extension activity of M2 (MCP1/sSiglec-9)-CM was significantly greater than that of M2 (IL-4)-CM or M0-CM (Fig. 5E). Figure 5 Open in new tabDownload slide Secreted factors from MCP-1/sSiglec-9-induced M2 macrophages accelerate Schwann cells (SCs) proliferation, migration, maturation and DRG neuronal outgrowth in vitro. (A): Representative phase contrast images of human SCs treated with DMEM, 100 ng/ml MCP-1/sSiglec-9, or M2 (MCP-1/sSiglec-9)-CM. (B): SC proliferation rates determined by WST assay (left) and SC migration in a modified Boyden chamber assay (right) (see Materials and Methods). (C): qPCR analysis of the indicated mRNAs. Results are expressed relative to the level in the DMEM-treated control cells. (D): Representative immunofluorescent images of neurofilaments from DRG neurons. (E): Quantitative analysis of average neurite length. The average neurite outgrowth was significantly higher in neurons treated with M2 (MCP-1/sSiglec-9)-CM than in other treated groups: n = 4 per group. Scale bar, 100 mm. ANOVA with Tukey's post hoc test (n = 4 per group). Data represent the mean ± SD; *, p < .05; **, p < .01. Abbreviations: DMEM, Dulbecco's modified Eagle's medium; MCP-1, monocyte chemoattractant protein-1; sSiglec-9, sialic acid-binding Ig-like lectin-9. Figure 5 Open in new tabDownload slide Secreted factors from MCP-1/sSiglec-9-induced M2 macrophages accelerate Schwann cells (SCs) proliferation, migration, maturation and DRG neuronal outgrowth in vitro. (A): Representative phase contrast images of human SCs treated with DMEM, 100 ng/ml MCP-1/sSiglec-9, or M2 (MCP-1/sSiglec-9)-CM. (B): SC proliferation rates determined by WST assay (left) and SC migration in a modified Boyden chamber assay (right) (see Materials and Methods). (C): qPCR analysis of the indicated mRNAs. Results are expressed relative to the level in the DMEM-treated control cells. (D): Representative immunofluorescent images of neurofilaments from DRG neurons. (E): Quantitative analysis of average neurite length. The average neurite outgrowth was significantly higher in neurons treated with M2 (MCP-1/sSiglec-9)-CM than in other treated groups: n = 4 per group. Scale bar, 100 mm. ANOVA with Tukey's post hoc test (n = 4 per group). Data represent the mean ± SD; *, p < .05; **, p < .01. Abbreviations: DMEM, Dulbecco's modified Eagle's medium; MCP-1, monocyte chemoattractant protein-1; sSiglec-9, sialic acid-binding Ig-like lectin-9. MCP1/sSiglec-9 Induces the Formation of a SC Bridge in the Transected FN Immunohistochemical analysis of the proximal stump 24 hours after FNI revealed that the number of S-100+ SCs was significantly increased in the MCP-1/sSiglec-9 group compared to the PBS control (Fig. 6A, 6B). Furthermore, 14 days after the FNI, MCP-1/sSiglec-9 treatment induced the infiltration of a number of spindle-shaped mature SCs into the nerve gap and promoted the formation of a SC bridge and extension of the transected nerve fiber (Fig. 6C). Figure 6 Open in new tabDownload slide MCP-1/sSiglec-9 enhances the proliferation of SCs in the nerve stump and promotes formation of a SC bridge across the gap. (A, C): Representative images of the immunohistological staining of S100β+ and neurofilament in a sagittal section of the FN at 24 hours (A) and 14 days (C) after facial nerve injury (FNI). (B): Quantification of S100β+ cells at proximal stump at 24 hours after FNI. Scale bars in (A) and (C), 200 μm. (D): Representative images of retrograde FG-labeled motor neurons in the facial nucleus. Scale bar, 500 μm. The number of FG-labeled neurons was quantitatively evaluated and compared by statistical analysis. Data represent the mean ± SD; *, p < .05; **, p < .01. Student's t test (n = 3 per group). Abbreviations: MCP-1, monocyte chemoattractant protein-1; PBS, phosphate-buffered saline; sSiglec-9, sialic acid-binding Ig-like lectin-9. Figure 6 Open in new tabDownload slide MCP-1/sSiglec-9 enhances the proliferation of SCs in the nerve stump and promotes formation of a SC bridge across the gap. (A, C): Representative images of the immunohistological staining of S100β+ and neurofilament in a sagittal section of the FN at 24 hours (A) and 14 days (C) after facial nerve injury (FNI). (B): Quantification of S100β+ cells at proximal stump at 24 hours after FNI. Scale bars in (A) and (C), 200 μm. (D): Representative images of retrograde FG-labeled motor neurons in the facial nucleus. Scale bar, 500 μm. The number of FG-labeled neurons was quantitatively evaluated and compared by statistical analysis. Data represent the mean ± SD; *, p < .05; **, p < .01. Student's t test (n = 3 per group). Abbreviations: MCP-1, monocyte chemoattractant protein-1; PBS, phosphate-buffered saline; sSiglec-9, sialic acid-binding Ig-like lectin-9. MCP-1/sSiglec-9 Treatment Rebuilds the Neural Circuit After FNI We next quantified the reinnervation of the injured buccal branch of the FN by retrograde labeling with Fluor-Gold (FG). In the brain stems of the sham-operated control rats, FG-positive neurons were localized to the facial nucleus. We found that the number of FG-positive neurons in the control PBS-treated group was severely reduced compared with that of the Sham group, but was significantly restored in the MCP-1/sSiglec-9 treatment group (Sham, 3153 ± 220; PBS, 580 ± 38; MCP-1/sSiglec-9, 3093 ± 198; p < .05, all experimental groups vs. PBS; Fig. 6D). MCP-1/sSiglec-9-Mediated Functional Recovery of Rat FNI Requires M2 Macrophages We next examined how M2 macrophage depletion by m-Clodrosome affects the MCP-1/sSiglec-9-mediated FN regeneration. Treatment with m-Clodrosome, but not the control liposome (Encapsome), prevented the MCP-1/sSiglec-9-mediated conversion of the FNI-induced pro-inflammatory environment to an anti-inflammatory one (Fig. 7A). Notably, we found that m-Clodrosome prevented the MCP-1/sSiglec-9-mediated functional recovery of the transected FN in rats (Fig. 7B). Figure 7 Open in new tabDownload slide Effects of M2 depletion on MCP-1/sSiglec-9-mediated functional recovery after facial nerve injury (FNI). (A): qPCR analysis of the indicated mRNAs in the resected nerve 24 hours after FNI. Results are expressed relative to the level in the sham-operated model. ANOVA with Tukey's post hoc test (n = 3 rats per group). Data represent the mean ± SD; *, p < .05; **, p < .01. (B): Recovery of vibrissa movement after FNI. MCP-1/sSiglec-9 + m-Clodrosome, n = 6; MCP-1/sSiglec-9 + Encapsome, n = 6. ANOVA with Tukey's post hoc test. Data represent the mean ± SD; *, p < .05; **, p < .01. Abbreviations: MCP-1, monocyte chemoattractant protein-1; PBS, phosphate-buffered saline; sSiglec-9, sialic acid-binding Ig-like lectin-9. Figure 7 Open in new tabDownload slide Effects of M2 depletion on MCP-1/sSiglec-9-mediated functional recovery after facial nerve injury (FNI). (A): qPCR analysis of the indicated mRNAs in the resected nerve 24 hours after FNI. Results are expressed relative to the level in the sham-operated model. ANOVA with Tukey's post hoc test (n = 3 rats per group). Data represent the mean ± SD; *, p < .05; **, p < .01. (B): Recovery of vibrissa movement after FNI. MCP-1/sSiglec-9 + m-Clodrosome, n = 6; MCP-1/sSiglec-9 + Encapsome, n = 6. ANOVA with Tukey's post hoc test. Data represent the mean ± SD; *, p < .05; **, p < .01. Abbreviations: MCP-1, monocyte chemoattractant protein-1; PBS, phosphate-buffered saline; sSiglec-9, sialic acid-binding Ig-like lectin-9. Discussion Dental pulp stem cells secrete a broad repertoire of trophic and immunomodulatory factors that have the potential to treat various types of intractable diseases [22–26, 36–41]. We previously showed that the factors in SHED-CM improve PNI in a rat model of sciatic nerve transection; however, the mechanisms involved in repairing the damaged nerve have been elusive. Here we show that the combination of MCP-1 and sSiglec-9 is essential for SHED-CM-mediated functional recovery after FNI in rats. Notably, MCP-1/sSiglec-9 induced the polarization of M2 macrophages, which antagonized the pro-inflammatory M1 conditions associated with FNI, promoted the proliferation, migration and differentiation of SCs, and enhanced neurite extension of PN. A single implantation of a collagen scaffold containing MCP-1/sSiglec-9 into the FNI-induced nerve gap promoted SC bridge formation, regenerated myelinated axonal bundles, and restored the function of the transected facial nerve. Importantly, treatment of the rats with m-Clodrosome, which specifically eliminates M2 macrophages, prevented the MCP-1/sSiglec-9-mediated recovery. This is the first report, to our knowledge, demonstrating the remarkable therapeutic benefits of MCP-1/sSiglec-9 for the treatment of severe PNI. Monocyte–macrophage lineages play central roles in tissue destruction and regeneration after PNI [42]. Previous studies have shown that both genetic and chemical depletion of macrophages leads to defective PN regeneration [43, 44]. Macrophages primed by skin-derived precursor SCs promote functional recovery after PNI [45, 46]. IL-4-induced M2 macrophages were recently shown to enhance SC mitosis and migration and to promote PN regeneration [13]. Our data showed that MCP-1/sSiglec-9 treatment increased the number of macrophages, which exhibited M2 polarization, in the nerve gap. In vitro experiments revealed that M2 (MCP-1/sSiglec-9)-CM activated the proliferation and migration activity of SCs, but also increased the expression of a group of SC-intrinsic molecules, Oct-6, Krox-20, MBP, and P0, which function as positive regulators of myelination [47]. Thus, our data suggest that MCP-1/sSiglec-9-induced M2 macrophages have the potential to promote SC differentiation. Furthermore, M2 (MCP-1/sSiglec-9)-CM enhanced the neurite extension of the PN. Taken together, these results suggest that multiple trophic effects associated with MCP-1/sSiglec-9-induced M2 macrophages could promote the formation of a SC bridge and axonal extension across the nerve gap. Recent studies have shown that the inclusion of various types of bioactive molecules in the biodegradable synthetic nerve conduits accelerates PN regeneration. Most of the effective molecules are factors involved in axonal growth and/or neuroprotection (such as nerve growth factor, BDNF, Neurotrophin-3, -4, -5, IGF-I, and CNTF) or in the proliferation and/or migration of cells that support axonal growth (including SCs and vascular endothelial cells), such as HGF, VEGF, Glial cell-derived neurotrophic factor, and FGF [7, 8]. These trophic factors function at different times during PN regeneration, but do not support the entire PN regenerative process. Here, we showed that MCP-1/sSiglec-9-induced M2 macrophages expressed six factors that are known to affect the functional properties of SCs. IGF-I stimulates both SC proliferation and differentiation in vitro [48], and the percentage of myelinated axons and the thickness of myelin sheaths are significantly increased in IGF-I transgenic mice [49]. NRG1 is upregulated after PNI, signals through tyrosine kinase family receptors, and promotes SC differentiation and remyelination [50]. BDNF plays a role in SC myelination by activating the small GTPase, Rac1 [51]. VEGF is a well-known angiogenetic factor that stimulates the proliferation, migration, and formation of new blood vessels. VEGF is also involved in axonal outgrowth, and enhances SC survival and proliferation [52]. CNTF stimulates SC proliferation via the ERK pathway [53]. HGF also promotes SC proliferation [54]. Furthermore, our previous study showed that M2 (MCP-1/sSiglec-9)-CM protects primary cerebral granular neurons against the neurotoxic effects of chondroitin sulfate proteoglycans [26]. Taken together, these multiple trophic and immunoregulatory factors expressed in MCP-1/sSiglec-9-induced M2 macrophages have the potential to generate a microenvironment that could suppress scar formation and activate the therapeutic potential of SCs, thereby promoting axonal regeneration after severe PNI. MCP-1 is known to be a prominent chemokine that contributes to the pro-inflammatory M1 response by recruiting macrophages to inflamed tissues [55]. However, we recently demonstrated a unique anti-inflammatory function for MCP-1, in which it acts via its cognate receptor, CCR2, in concert with sSiglec-9, to induce M2 macrophage polarization [26]. Sialic acids are terminal acidic monosaccharides on glycoconjugates that influence their chemical and biological features [56]. The Siglecs are a large family of sialic acid-binding type-I transmembrane Ig-like lectins that modulate immune signaling on various types of immune cells through cytoplasmic immunoreceptor tyrosine-based inhibitory motifs [29, 57]. The function of the secreted Siglec in inflammation and other cellular responses is largely unknown. In PNI, a full-length Siglec-4, known as myelin associated glycoprotein, is expressed on SCs, acts as a ligand of the Nogo-66 receptor [58, 59], and plays important roles in maintaining the myelin structures [60]. Taken together, these findings suggest that Siglecs play important roles in various types of intercellular signaling, and may function both as ligands and receptors. The detailed mechanistic basis of MCP-1/sSiglec-9-mediated M2 macrophage induction remains to be clarified in future studies. Conclusion In summary, we found that MCP-1 and sSiglec-9 were essential for SHED-CM-mediated functional recovery after severe PNI. The implantation of a collagen graft containing MCP-1/sSiglec-9 into the nerve gap induced anti-inflammatory M2 macrophage polarization, generated a SC bridge instead of fibrotic scar, induced axonal regrowth, and restored nerve function. Our data suggest that the unique combination of MCP-1 and sSiglec-9 may provide therapeutic benefits for severe PNI. We further propose that defined factors secreted by stem cells may provide a previously unrecognized therapeutic strategy in the field of stem cell-based regenerative medicine. Acknowledgments We are grateful to H. Kiyama (Nagoya University) and T. Isa (Kyoto University) for their critical review of the manuscript and to Y. Sugimura-Wakayama and J. Ishikawa for technical support. We thank the Division of Experimental Animals and Medical Research Engineering, Nagoya University Graduate School of Medicine, for housing the mice and for microscope maintenance, respectively. This work was supported by Grants-in-Aid for Scientific Research on Priority Areas from the Ministry of Education, Culture, Sports, Science and Technology of Japan. Author Contributions F.K.: Conducted all of the FNI experiments and cowrote the manuscript; K.M.: Provided support for the FNI experiments; A.Y.: Designed the experiments and wrote the manuscript. H.H., M.U., and A.Y.: Supervised the project. 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