Background: Cystic echinococcosis is a worldwide chronic zoonotic disease caused by infection with the larval stage of Echinococcus granulosus. Previously, we found significant accumulation of myeloid-derived suppressor cells (MDSCs) in E. granulosus infection mouse models and that they play a key role in immunosuppressing T lymphocytes. Here, we compared the long non-coding RNA (lncRNA) and mRNA expression patterns between the splenic monocytic MDSCs (M-MDSCs) of E. granulosus protoscoleces-infected mice and normal mice using microarray analysis. Methods: LncRNA functions were predicted using Gene Ontology enrichment and the Kyoto Encyclopedia of Genes and Genomes pathway analysis. Cis- and trans-regulation analyses revealed potential relationships between the lncRNAs and their target genes or related transcription factors. Results: We found that 649 lncRNAs were differentially expressed (fold change ≥ 2, P < 0.05): 582 lncRNAs were upregulated and 67 lncRNAs were downregulated; respectively, 28 upregulated mRNAs and 1043 downregulated mRNAs were differentially expressed. The microarray data was validated by quantitative reverse transcription-PCR. The results indicated that mRNAs co-expressed with the lncRNAs are mainly involved in regulating the actin cytoskeleton, Salmonella infection, leishmaniasis, and the vascular endothelial growth factor (VEGF) signaling pathway. The lncRNA NONMMUT021591 was predicted to cis-regulate the retinoblastoma gene (Rb1), whose expression is associated with abnormal M-MDSCs differentiation. We found that 372 lncRNAs were predicted to interact with 60 transcription factors; among these, C/EBPβ (CCAAT/enhancer binding protein beta) was previously demonstrated to be a transcription factor of MDSCs. Conclusions: Our study identified dysregulated lncRNAs in the M-MDSCs of E. granulosus infection mouse models; they might be involved in M-MDSC-derived immunosuppression in related diseases. Keywords: Echinococcus granulosus, Myeloid-derived suppressor cells, Long non-coding RNAs, Expression profile, Microarray analysis * Correspondence: email@example.com; firstname.lastname@example.org National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention, Shanghai 200025, China Full list of author information is available at the end of the article © The Author(s). 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Yu et al. Parasites & Vectors (2018) 11:327 Page 2 of 9 Background expressed lncRNAs may be new candidates for the im- Cystic echinococcosis is a worldwide chronic zoonotic munosuppressive mechanism of M-MDSCs in parasitic disease caused by accidental ingestion of eggs of the diseases. genus Echinococcus and typically affects the liver and lungs . It is endemic in pastoral regions around the Methods world , causes a huge disease burden, and is charac- Mice, parasites, and infection terized by long-term growth of hydatid cysts in humans Female BALB/c mice (aged 6–8 weeks) were purchased and mammalian intermediate hosts. The cysts are filled from SLAC Laboratory. The Eg-psc were obtained from with hydatid cyst fluid and protoscoleces . the hydatid cysts of naturally infected sheep livers under Previously, we found significant accumulation of aseptic conditions, and washed three times using 0.9% NaCl myeloid-derived suppressor cells (MDSCs) in mouse containing 1000 mg/ml penicillin and 1000 U/ml strepto- models infected with E. granulosus protoscoleces (Eg-psc) mycin (Invitrogen, Frederick, MD, USA). Thirty BALB/c  and that they play a key role in downregulating the im- mice were intraperitoneally injected with a 200 μlsuspen- mune response of T lymphocytes. MDSCs are a heteroge- sion containing 2000 live Eg-psc in 0.9% NaCl; the controls neous population of myeloid cells composed of terminally were 30 BALB/c mice injected with 200 μl0.9%NaCl. All differentiated macrophages, granulocytes, or dendritic cells. mice were housed in specific pathogen-free conditions. Various pathological conditions, such as cancer [5, 6], sepsis  and parasitic infection  result in aberrant MDSC ex- pansion. MDSCs consist of two major subsets based on Cell isolation their phenotypic and morphological features: polymorpho- Splenic M-MDSCs were isolated immediately after the nuclear (PMN)-MDSCs and monocytic (M)-MDSCs. In BALB/c mice were sacrificed under sterile conditions mice, they are historically characterized by concurrent ex- at eight months after infection. Single-cell suspensions pression of the myeloid markers CD11b and Gr-1. The two were enriched with magnetic cell sorting (MACS; major subsets can be identified more accurately based on Miltenyi Biotec, Bergisch Gladbach, Germany) accord- the expression of Ly6G and Ly6C markers: PMN-MDSCs, ing to the manufacturer’s protocol. The M-MDSCs + + low + - hi CD11b Ly6G Ly6C ; M-MDSCs, CD11b Ly6G Ly6C ) were separated on mini MACS columns (Miltenyi [9, 10]. M-MDSCs and PMN-MDSCs inhibit immune Biotec, Bergisch Gladbach, Germany) and yielded ap- function via different mechanisms. M-MDSCs suppress proximately 90% pure cells. Then, we randomly se- Tcell function via both antigen-specific and nonspecific lected splenic M-MDSCs from three mice each in the mechanisms by producing nitric oxide (NO) and cytokines infected and normal groups for the detection of [11, 12], and are more immunosuppressive than their lncRNA and mRNA arrays. counterparts when assessed on a per cell basis [13–15]. Long non-coding RNAs (lncRNAs) are commonly de- fined as transcribed RNAs of more than 200 nucleotides Microarray profiling in length and lack protein-coding ability [16, 17]. The lncRNA and mRNA expression patterns were de- Increasing evidence indicates that lncRNAs participate tected in the splenic M-MDSCs of three Eg-psc-infected in several important biological processes, including mice and three normal mice. The experiments were per- carcinogenesis, cell differentiation, metabolism, and im- formed at OE BioTechCorporation (Shanghai, China). munity responses [18–20], acting as signal molecules, Agilent mouse lncRNA Microarray (4*180K, Design ID: decoys, guides, and scaffolds [21–23]. Although numer- 049801) was used in this experiment. Total RNA was ex- ous lncRNAs have been discovered in recent years, only tracted and purified with a RNeasy Mini Kit (Qiagen, p/n a limited number have been well characterized. At the 74104, Boston, MA, USA) and quantified using NanoDrop same time, knowledge of the genome scale of lncRNAs ND-2000 (Thermo Fisher Scientific, Waltham, MA, USA). and their underlying biological functions in MDSCs in RNA integrity was assessed using an Agilent Bioanalyzer parasitic infections remains limited. Moreover, MDSC 2100 (Agilent Technologies, Santa Clara, CA, USA). functional plasticity via epigenetic modification leads to Sample labeling, microarray hybridization, and wash- their characteristics reshaping . ing were performed based on the manufacturer’s In the present study, we used microarray analysis to standard protocols. Briefly, total RNA was transcribed investigate the lncRNA and mRNA expression profiles to double-stranded complementary DNA (cDNA), in the splenic M-MDSCs of normal and Eg-psc-infected synthesized into complementary RNA (cRNA), and mice, and performed bioinformatics analysis of the dif- labeled with Cyanine 3-CTP. The labeled cRNA was ferentially expressed lncRNAs to explore the possible hybridized onto the microarray. After washing, the ar- biological processes and pathways associated with rays were scanned using an Agilent Scanner G2505C M-MDSCs. The results demonstrate that aberrantly microarray scanner (Agilent Technologies). Yu et al. Parasites & Vectors (2018) 11:327 Page 3 of 9 Differential expression analysis Here, the lncRNAs identified showed high Pearson’s The raw data were analyzed using Feature Extraction correlation with the neighboring protein-coding genes, software (version 10.7.1.1; Agilent Technologies) and suggesting that they act in cis on protein-coding then normalized using percentile normalization. Probes genes to regulate M-MDSC functions. As it has been with least one of two conditions flagged in “P” were indicated that transcription factors regulate lncRNA chosen for further data analysis. Differentially expressed production, we therefore used hypergeometric distri- lncRNAs were identified through fold change and the bution testing to predict the potential transcription fac- P-value as calculated with the t-test. Aberrantly tors that may regulate the production of the differentially expressed lncRNAs and mRNAs were defined as fold expressed lncRNAs. change ≥ 2.0 and P < 0.05. Subsequently, Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Statistical analysis Genomes (KEGG) analyses were used to explore the Statistical analysis was performed using SPSS 19.0 (SPSS, roles of the differentially expressed mRNAs. Hierarchical New York, USA). All measurement data are reported as the clustering was performed on six mouse splenic tissue mean ± standard deviation (SD). Differentially expressed samples using Cluster 3.0 (Stanford University School of lncRNAs were identified using t-tests or nonparametric Medicine, California, USA) and TreeView 2.0 (Baryshni- tests. P < 0.05 was considered statistically significant. kova Lab, Princeton University, New Jersey, USA) to distinguish the distinguishable gene expression pattern among the samples. Results Co-expression network analysis Differentially expressed lncRNAs in M-MDSCs The co-expression of lncRNAs and the protein-coding The raw data were analyzed using Feature Extraction genes was calculated using Pearson correlation coefficients software (version 10.7.1.1, Agilent Technologies) and with Cytoscape version 3.1.1 (US National Institute of were normalized with the quantile algorithm. Gene- General Medical Sciences). Correlations with P <0.05 Spring (version 13.1, Agilent Technologies) was used for were considered statistically significant. basic raw data analysis. Probes with at least 100% of the values in any one out of all conditions flagged as Functional enrichment analysis “Detected” were selected for further analysis. Differentially The functions of lncRNA co-expressed mRNAs were an- expressed mRNAs or lncRNAs were identified through alyzed using GO enrichment analysis which was divided fold change and the P-value as calculated with the t-test. into three functional categories: molecular function, bio- The threshold set for upregulated or downregulated RNAs logical process and cellular component. The pathways of was fold change ≥ 2.0 and P <0.05. the co-expressed mRNAs were analyzed using KEGG We detected 54,030 lncRNAs and 33,420 mRNAs in pathway analysis. the M-MDSC samples. Microarray scanning and normalization determined that 649 lncRNAs and 1071 Quantitative reverse transcription-PCR (qRT-PCR) mRNAs were differentially expressed. Among them, 582 qRT-PCR was performed to validate the microarray lncRNAs were upregulated and 67 lncRNAs were results according to the manufacturer’sprotocol with downregulated (Additional file 2: Table S2), and 28 a SYBR Green RT-PCR Kit (QuantiFast SYBR Green upregulated and 1043 downregulated mRNAs were PCR Master Mix, Qiagen) on a Bio-Rad CFX96 sys- differentially expressed (Additional file 3: Table S3). tem. The primers used for the qRT-PCR are shown in Compared with the controls, FR208893 (fold change of Additional file 1: Table S1. The lncRNA expression 133.45992) was the most upregulated lncRNA, while levels were quantified based on the threshold cycle FR325025 (fold change of 4.1526523) was the most (Ct) values. β-Actin served as the internal control. downregulated lncRNA in the M-MDSCs. The relative gene expression was analyzed using the Figure 1 shows a volcano plot of the differentially comparative Ct [2(-ΔΔCt)] method . Three bio- expressed lncRNAs, where red and green indicate logical replicates were performed for each group. significantly upregulated and downregulated lncRNAs, respectively. To identify gene expression patterns, hier- Cis- and trans-regulation analysis archical clustering was performed among samples using LncRNAs have been shown to enhance the expression of Cluster 3.0 and TreeView 2.0. Many lncRNAs were iden- nearby genes through cis-regulation  and as the tified as differentially expressed between the two groups, mRNA loci were within 300 kbp windows upstream and indicating that the significantly altered expression of downstream of the given lncRNAs, we identified them these lncRNAs may be involved in the immunoregula- as cis-regulated mRNAs of the corresponding lncRNAs. tory function of M-MDSCs (Fig. 2). Yu et al. Parasites & Vectors (2018) 11:327 Page 4 of 9 positive regulation of protein complex assembly in biological processes (Fig. 4a); nuclear envelope, mitotic spindle, and trans-Golgi network in cellular component (Fig. 4b), and enzyme regulator activity, lipoteichoic acid binding, and NADH dehydrogenase activity in molecular functions (Fig. 4c). It is widely believed that disorder of the signaling pathways under pathological conditions contributes to the development of suppressive myeloid cells . KEGG pathway analysis indicated that the co-expressed mRNAs were mainly involved in regulating the actin cytoskeleton, Salmonella infection, leishmaniasis, and the vascular endothelial growth factor (VEGF) signaling pathway (Fig. 4d). MDSCs accumulate in lymphoid or- gans under parasitic infection (as in cancer), and can mi- grate to and invade the adjacent tissues and vasculature. Some key proteins involved in the actin cytoskeleton are linked to cancer cell invasion and metabolism . As cystic echinococcosis is considered an infectious and inflammatory disease, the aberrantly expressed lncRNAs might regulate these processes. Fig. 1 Aberrant expression of lncRNAs between the two groups. The X-axis indicates the fold change. The horizontal green line represents the filter criterion (threshold P ≥ 0.05); red dots, upregulated lncRNAs; Cis-regulation of lncRNAs blue dots, downregulated lncRNAs We found that 288 lncRNAs were considered cis-regula- tory lncRNAs of their sense-overlapping genes, and we found that lncRNA NONMMUT021591 was predicted to cis-regulate the Rb1 (Additional file 4: Figure S1). Rb1 qRT-PCR validation expression had been reported to be associated with To verify the results of lncRNA microarray, we used abnormal M-MDSC differentiation .The lncRNA qRT-PCR to detect the expression of 10 lncRNAs NONMMUT021591 may play a role in the immunosup- selected randomly from the differentially expressed pressive functions of MDSCs. lncRNA transcripts with splenic M-MDSCs samples with three biological replicates in each group. The qRT-PCR results were consistent with the lncRNA array LncRNA-transcription factor network analysis analysis, and these lncRNAs are likely to play roles in re- As it was indicated that transcription factors regulate sponse to the biological functions of MDSCs in parasitic lncRNA production, we used hypergeometric distribution infections (Fig. 3). testing to predict the transcription factors that could regu- late the differentially expressed lncRNAs, and constructed LncRNAs-mRNAs co-expression network a core network of the top 100 lncRNA-transcription factor We constructed a co-expression network to investigate pairs by ranking the P-value (Fig. 5). We predicted that the correlation between each differentially expressed 372 lncRNAs would interact with 60 transcription factors, lncRNA in M-MDSCs and the target mRNAs. We forming an interaction network of 1746 connections. ranked each lncRNA-mRNA correlation according to These lncRNAs were mostly regulated by IL6, FOSL1, the P-value and selected the top 500 lncRNA functional YY1, PGR, TMEM37, PBX1, POU3F2, FOXF2, FOS, terms for functional enrichment analysis, and counted JUNB, JUND, CEBPD, RB1, MAX, E2F1, C/EBPβ,HER- the numbers of differently expressed lncRNAs enriched PUD1, E2F4 and ZBTB16. Among the transcription in the functional terms. These functional terms were factors, C/EBPβ (CCAAT enhancer-binding transcription used to predict the functions of the given lncRNAs factor)  has been demonstrated to be a MDSC based on GO enrichment and KEGG pathway analyses transcription factor. C/EBPβ regulates myeloid cell devel- of the co-expressed mRNAs. opment and differentiation, and controls emergency gran- For GO analysis, differentially expressed lncRNAs were ulopoiesis induced by cytokines and infections [7, 30]. mostly enriched in nuclear envelope organization, positive Increased C/EBPβ expression is a characteristic biochem- regulation of target of rapamycin (TOR) signaling and ical feature of MDSCs. Yu et al. Parasites & Vectors (2018) 11:327 Page 5 of 9 Fig. 2 Hierarchical clustering of differentially expressed lncRNAs between the splenic M-MDSCs of normal and Eg-psc-infected mice. In the heat map, red indicates increased relative expression and green indicates decreased relative expression LncRNA-target-transcription factor network analysis For further identification of the functions of each dys- regulated lncRNA in M-MDSCs, we analyzed the top 50 differentially expressed lncRNAs and their co-expressed mRNAs pairs according to the P-value to conduct the lncRNA-target-transcription factor network (Fig. 6). The network revealed several most likely transcription factors for these lncRNAs, and included FOSL1, YY1, IL6 and PGR. LncRNAs FR049933, FR291292, FR110455 and FR400826 are predicted to be mainly regulated by these transcription factors and participate in mitogen-activated protein kinase (MAPK) signaling pathway and VEGF signaling pathway, which are involved in MDSC function. Discussion Cystic echinococcosis is a worldwide chronic zoonotic dis- ease in pastoral regions around the world . Transmission is through predator-prey interactions between carnivore definitive hosts and herbivore intermediate hosts [31, 32]. Fig. 3 qRT-PCR verification of 10 randomly selected differentially expressed lncRNAs from the microarray data. Previously, we showed significant accumulation of + + The qRT-PCR results were consistent with the lncRNA array CD11b Gr-1 myeloid cells in the spleen and peripheral analysis. Results are presented as log2 fold changes in blood in Eg-psc-infected mouse models  . Under infected expression ± standard error conditions, myeloid cells are arrested in an immature state Yu et al. Parasites & Vectors (2018) 11:327 Page 6 of 9 Fig. 4 Top 20 terms in the gene enrichment and pathway analysis of differentially expressed lncRNAs induced by Eg-psc infection. a Biological process. b Cellular component. c Molecular function. d The most significant KEGG pathway for the differentially expressed lncRNAs and possess a potential capacity to suppress immune cell immunosuppressive effects depending on the expanding sub- responses by creating a suppressive environment; such cells type, the disease stage and the site where immunosuppres- are termed MDSCs. MDSCs have gained much attention sion is occurring , and their mechanism may change due to their roles in immunosuppression and in the promo- with the disease progression or the affected organ. tion of angiogenesis  and metastasis . MDSCs exert M-MDSCs suppress T-cell function via both antigen-specific Fig. 5 Network of the top 100 most related lncRNA-transcription factor pairs according to the P-value. Red arrowheads, lncRNAs; blue diamonds, transcription factors Yu et al. Parasites & Vectors (2018) 11:327 Page 7 of 9 Fig. 6 Network of the top 50 most related lncRNA-target-transcription factors. Red arrowheads, lncRNAs; green diamonds, mRNAs; blue diamonds, transcription factors and nonspecific mechanisms by producing high amounts of and compare the lncRNA expression profile of M-MDSCs arginase 1, NO and immunosuppressive cytokines [11, 12]. and to discover the role and significance of lncRNAs in Under infection conditions, the capacity of MDSCs to differ- M-MDSCs, which indicated that lncRNA is a mediator that entiate into macrophages and dendritic cells is inhibited. recruits MDSCs in Eg-psc-infected models. MDSCs are more immunosuppressive than their counter- We compared the lncRNA expression profiles between parts when assessed on a per cell basis [13–15]. The mech- splenic M-MDSCs from Eg-psc-infected mice and nor- anism associated with MDSC regulation is becoming mal mice to identify the lncRNAs that may be important accepted as another means of regulating immune responses, in M-MDSC differentiation and function. Compared and MDSCs are potential therapeutic targets in multiple in- with the normal mice, 582 lncRNAs were upregulated fectious and inflammatory diseases. While the underlying and 67 lncRNAs were downregulated, and 28 upregu- molecular mechanisms of MDSCs and their sub-populations lated mRNAs and 1043 downregulated mRNAs were remain unclear, epigenetic modification of MDSC function differentially expressed in the infected mice. The expres- could provide some molecular evidence concerning MDSC sion differences in the microarray detection were con- accumulation and immunosuppression. Studies have con- sistent with that of qRT-PCR detection. For further firmed that a number of lncRNAs are crucial in biological analysis of the differentially expressed lncRNAs, we con- processes, including regulating gene expression, cell develop- structed a co-expression network to investigate the cor- ment and metabolism, which are disordered in disease [18, relation between each aberrant lncRNA and their target 19, 36]. A global lncRNA expression profile specific to a mRNAs. GO analysis and KEGG pathway analysis were functional MDSC population is not known. In the present carried out to investigate the biological functions of study, we selected splenic M-MDSCs for lncRNA microarray lncRNAs. The GO enrichment assay showed that the analysis based on previous studies [4, 13, 15]toinvestigate differentially expressed lncRNAs were mostly enriched Yu et al. Parasites & Vectors (2018) 11:327 Page 8 of 9 in positive regulation of TOR signaling in biological pro- Conclusions cesses. The TOR pathway is well recognized as being LncRNAs are critical in modulating the immune micro- related to cell proliferation and metabolism. Moreover, environment and MDSCs; our findings provide a new mammalian TOR (mTOR) is an intrinsic factor essential understanding of M-MDSCs, and the data we present for M-MDSC differentiation and immunosuppressive could guide the exploration of lncRNA-mediated function . KEGG pathway analysis showed that the immunosuppression in long-term parasitic infection. mRNAs co-expressed lncRNAs were mainly involved in Although the sensitivity and specificity of lncRNA bio- regulation of the actin cytoskeleton, leishmaniasis, and markers in M-MDSCs should be further investigated, the VEGF signaling pathway, which have been widely the functional lncRNAs can be explored as potential bio- researched and demonstrated to be associated with MDSCs markers or novel treatment strategies for immunoregu- . These differentially expressed lncRNAs also partici- lation in related diseases. Understanding the underlying pate in inflammatory signaling pathways, such as the mechanisms and functions of these immunosuppressive MAPK signaling pathway, tumor necrosis factor (TNF) sig- cell populations will pave the way for new parasite vac- naling pathway, and the nuclear factor kappa B (NF-κB) cine strategies. signaling pathway [38, 39]. Moreover, these inflammatory pathways have been widely researched and demonstrated Additional files to be associated with MDSCs function. The vascular endothelial growth factor (VEGF) is an important molecule Additional file 1: Table S1. Primers used in qPCR detection of selected involved in angiogenesis. Ostrand-Rosenberg et al.  lncRNAs. (XLSX 10 kb) demonstrated that inflammation could increase MDSCs Additional file 2: Table S2. Significantly and differentially expressed lncRNAs in M-MDSCs. (XLSX 49 kb) levels by protecting MDSCs from Fas-mediated apoptosis Additional file 3: Table S3. Significantly and differentially expressed through activation of the MAPK pathway. IL-33 in- mRNAs in M-MDSCs. (XLSX 83 kb) duced arginase-1 expression and activated the NF-κBand Additional file 4: Figure S1. The lncRNA NONMMUT021591 was MAPK signaling pathways, augmenting the immunosup- predicted to cis-regulate the protein-coding gene Rb1. Red dots, genomic pressive ability of MDSCs. To further study the roles of location of lncRNAs; blue dots, the corresponding genes; rho value, correlation coefficient. (TIF 13 kb) specific lncRNAs in M-MDSCs, we predicted their corre- sponding mRNAs through cis-and trans-targeting. We found that 288 lncRNAs were considered cis-regulatory Abbreviations C/EBPβ: CCAAT/enhancer binding protein beta; Eg-psc: Echinococcus lncRNAs of their sense-overlapping genes; among them, granulosus protoscoleces; GO: Gene Ontology; KEGG: Kyoto Encyclopedia of NONMMUT021591 was predicted to cis-regulate Rb1. Rb1 Genes and Genomes; lncRNA: long non-coding RNA; MAPK: mitogen- expression is associated with abnormal M-MDSC differenti- activated protein kinase; MDSCs: myeloid-derived suppressor cells; M- MDSCs: monocytic myeloid-derived suppressor cells; mTOR: mammalian TOR; ation. Youn et al.  demonstrated a novel regulatory NF-κB: nuclear factor kappa B; NO: nitric oxide; PMN- mechanism of myeloid cells in cancer. Transcriptional silen- MDSCs: polymorphonuclear myeloid-derived suppressor cells; TNF: tumor cing of the Rb1 gene altered M-MDSC differentiation necrosis factor; TOR: target of rapamycin; VEGF: vascular endothelial growth factor into macrophages and dendritic cells to preferential differ- entiation towards PMN-MDSCs. Furthermore, M-MDSCs Acknowledgements in tumor-bearing mice could acquire the phenotypic and The authors are grateful to Professor Junying Ma at the Qinghai Institute for morphological features of PMN-MDSCs. Three hundred Endemic Disease Prevention and Control for her help in collecting the and seventy-two lncRNAs were predicted to interact with parasite samples in Qinghai Province, China. 60 transcription factors; several among them, namely FOSL1, YY1, IL6 and PGR, were the most enriched terms. Funding This work was supported by the National Natural Science Foundation of Among these transcription factors, C/EBPβ  has been China (Nos: 81772224 and 81371842 to YS; 81501771 to JZ; 81601792 to YW; demonstrated to be a MDSC transcription factor, and and 81702030 to JY), and the Fourth Round of Three-Year Public Health under inflammation and infection conditions, C/EBPβ Action Plan of Shanghai, China (No. 15GWZK0101 to JC]. The funders had no role in the study design, data collection and analysis, the decision to publish, could regulate myeloid cell development and differen- or preparation of the manuscript. tiation and control emergency granulopoiesis [7, 30]. Increased expression of the transcriptional regulator C/ Availability of data and materials EBPβ is a characteristic biochemical feature of MDSCs. In The datasets supporting the conclusions of this article are included within the present study, FR015378 was predicted to be regulated the article. by C/EBPβ and participates in the VEGF signaling path- way in KEGG analysis. Therefore, it is reasonable to Authors’ contributions YS and JC conceived and designed the study. AY, YS, JY, JZ, YW and SC propose that the aberrantly expressed lncRNAs participate performed the experiments and data analysis. YS, JC, YW, JZ and JY in parasitic infection induction of M-MDSCs by acting contributed reagents and materials. YA and YS wrote and JC revised the with their correlated mRNAs and transcription factors. paper. All authors read and approved the final manuscript. Yu et al. Parasites & Vectors (2018) 11:327 Page 9 of 9 Ethics approval 15. Haverkamp JM, Smith AM, Weinlich R, Dillon CP, Qualls JE, Neale G, et al. This study was carried out in strict accordance with the recommendations of Myeloid-derived suppressor activity is mediated by monocytic lineages the Guide for the Care and Use of Laboratory Animals of the Ministry of maintained by continuous inhibition of extrinsic and intrinsic death Science and Technology, China. The protocol was approved by the pathways. Immunity. 2014;41:947–59. Laboratory Animals Welfare and Ethics Committee (LAWEC) of the National 16. Guttman M, Rinn JL. Modular regulatory principles of large non-coding Institute of Parasitic Diseases, Chinese Center for Disease Control and RNAs. Nature. 2012;482:339–46. Prevention (Permit number: IPD 2013-006). A special effort was made to 17. Ulitsky I, Bartel DP. lincRNAs: genomics, evolution, and mechanisms. Cell. reduce the number of mice used in the study, to provide them with the 2013;154:26–46. most comfortable conditions, and to minimize animal suffering wherever 18. Liu YR, Tang RX, Huang WT, Ren FH, He RQ, Yang LH, et al. Long noncoding possible. RNAs in hepatocellular carcinoma: novel insights into their mechanism. World J Hepatol. 2015;7:2781–91. 19. Moyo B, Nicholson SA, Arbuthnot PB. The role of long non-coding RNAs in Competing interests hepatitis B virus-related hepatocellular carcinoma. Virus Res. 2016;212:103–13. The authors declare that they have no competing interests. 20. Chauhan R, Lahiri N. Tissue- and serum-associated biomarkers of hepatocellular carcinoma. Biomark Cancer. 2016;8:37–55. 21. Wang KC, Chang HY. Molecular mechanisms of long noncoding RNAs. Publisher’sNote Mol Cell. 2011;43:904–14. Springer Nature remains neutral with regard to jurisdictional claims in 22. Fang Y, Fullwood MJ. Roles, functions, and mechanisms of long non-coding published maps and institutional affiliations. RNAs in cancer. Genom Proteom Bioinform. 2016;14:42–54. 23. Rinn JL, Chang HY. Genome regulation by long noncoding RNAs. Annu Rev Author details 1 Biochem. 2012;81:145–66. National Institute of Parasitic Diseases, Chinese Center for Disease Control 2 24. Livak KJ, Schmittgen TD. Analysis of relative gene expression data using and Prevention, Shanghai 200025, China. Key Laboratory of Parasite and 3 real-time quantitative PCR and the 2 (-Delta Delta C (T)) method. Methods. Vector Biology, MOH, Shanghai 200025, China. National Center for 4 2001;25:402–8. International Research on Tropical Diseases, Shanghai 200025, China. WHO 25. Trimarchi T, Bilal E, Ntziachristos P, Fabbri G, Dalla-Favera R, Tsirigos A, et al. Collaborating Centre for Tropical Diseases, Shanghai 200025, China. Genome-wide mapping and characterization of Notch-regulated long noncoding RNAs in acute leukemia. Cell. 2014;158:593–606. Received: 17 February 2018 Accepted: 17 May 2018 26. Trikha P, Carson WE 3rd. Signaling pathways involved in MDSC regulation. Biochim Biophys Acta. 2014;1846:55–65. 27. Yamaguchi H, Condeelis J. Regulation of the actin cytoskeleton in cancer References cell migration and invasion. Biochim Biophys Acta. 2007;1773:642–52. 1. McManus DP, Gray DJ, Zhang W, Yang Y. Diagnosis, treatment, and 28. Youn JI, Kumar V, Collazo M, Nefedova Y, Condamine T, Cheng P, et al. management of echinococcosis. BMJ. 2012;344:e3866. Epigenetic silencing of retinoblastoma gene regulates pathologic 2. Budke CM, Carabin H, Ndimubanzi PC, Nguyen H, Rainwater E, Dickey M, differentiation of myeloid cells in cancer. Nat Immunol. 2013;14:211–20. et al. A systematic review of the literature on cystic echinococcosis 29. Marigo I, Bosio E, Solito S, Mesa C, Fernandez A, Dolcetti L, et al. Tumor- frequency worldwide and its associated clinical manifestations. Am J Trop induced tolerance and immune suppression depend on the C/EBPbeta Med Hyg. 2013;88:1011–27. transcription factor. Immunity. 2010;32:790–802. 3. Monteiro KM, de Carvalho MO, Zaha A, Ferreira HB. Proteomic analysis of 30. Dai J, Kumbhare A, Youssef D, Yao ZQ, McCall CE, El Gazzar M. Expression of the Echinococcus granulosus metacestode during infection of its C/EBPβ in myeloid progenitors during sepsis promotes immunosuppression. intermediate host. Proteomics. 2010;10:1985–99. Mol Immunol. 2017;91:165–72. 4. Pan W, Zhou HJ, Shen YJ, Wang Y, Xu YX, Hu Y, et al. Surveillance on the 31. Ito A, Budke CM. The echinococcoses in Asia: the present situation. Acta status of immune cells after Echinnococcus granulosus protoscoleces Trop. 2017;176:11–21. infection in Balb/c mice. PLoS One. 2013;8:e59746. 32. Craig P, Mastin A, van Kesteren F, Boufana B. Echinococcus granulosus: 5. Marvel D, Gabrilovich DI. Myeloid-derived suppressor cells in the tumor epidemiology and state-of-the-art of diagnostics in animals. Vet Parasitol. microenvironment: expect the unexpected. J Clin Invest. 2015;125:3356–64. 2015;213:132–48. 6. Ostrand-Rosenberg S, Sinha P. Myeloid-derived suppressor cells: linking 33. Yang L, DeBusk LM, Fukuda K, Fingleton B, Green-Jarvis B, Shyr Y, et al. inflammation and cancer. J Immunol. 2009;182:4499–506. Expansion of myeloid immune suppressor Gr+CD11b+ cells in tumor-bearing 7. McClure C, McPeak MB, Youssef D, Yao ZQ, McCall CE, El Gazzar M. Stat3 host directly promotes tumor angiogenesis. Cancer Cell. 2004;6:409–21. and C/EBPbeta synergize to induce miR-21 and miR-181b expression during 34. Talmadge JE, Gabrilovich DI. History of myeloid-derived suppressor cells. sepsis. Immunol Cell Biol. 2017;95:42–55. Nat Rev Cancer. 2013;13:739–52. 8. Schmid M, Zimara N, Wege AK, Ritter U. Myeloid-derived suppressor cell 35. Kumar V, Patel S, Tcyganov E, Gabrilovich DI. The nature of myeloid- functionality and interaction with Leishmania major parasites differ in derived suppressor cells in the tumor microenvironment. Trends C57BL/6 and BALB/c mice. Eur J Immunol. 2014;44:3295–306. Immunol. 2016;37:208–20. 9. Youn JI, Nagaraj S, Collazo M, Gabrilovich DI. Subsets of myeloid-derived 36. Taft RJ, Pang KC, Mercer TR, Dinger M, Mattick JS. Non-coding RNAs: suppressor cells in tumor-bearing mice. J Immunol. 2008;181:5791–802. regulators of disease. J Pathol. 2010;220:126–39. 10. Bronte V, Brandau S, Chen SH, Colombo MP, Frey AB, Greten TF, et al. 37. Wu T, Zhao Y, Wang H, Li Y, Shao L, Wang R, et al. mTOR masters Recommendations for myeloid-derived suppressor cell nomenclature and monocytic myeloid-derived suppressor cells in mice with allografts or characterization standards. Nat Commun. 2016;7:12150. tumors. Sci Rep. 2016;6:20250. 11. Marigo I, Dolcetti L, Serafini P, Zanovello P, Bronte V. Tumor-induced 38. Ostrand-Rosenberg S, Sinha P, Chornoguz O, Ecker C. Regulating the tolerance immune suppression by myeloid derived suppressor cells. suppressors: apoptosis and inflammation govern the survival of tumor- Immunol Rev. 2008;222:162–79. induced myeloid-derived suppressor cells (MDSC). Cancer Immunol 12. Lindau D, Gielen P, Kroesen M, Wesseling P, Adema GJ. The Immunother. 2012;61:1319–25. immunosuppressive tumour network: myeloid-derived suppressor cells, 39. Ichikawa M, Williams R, Wang L, Vogl T, Srikrishna G. S100A8/A9 regulatory T cells and natural killer T cells. Immunology. 2013;138:105–15. activate key genes and pathways in colon tumor progression. Mol 13. Dolcetti L, Peranzoni E, Ugel S, Marigo I, Fernandez Gomez A, Mesa C, Cancer Res. 2011;9:133–48. et al. Hierarchy of immunosuppressive strength among myeloid-derived 40. Xiao P, Wan X, Cui B, Liu Y, Qiu C, Rong J, et al. Interleukin 33 in tumor suppressor cell subsets is determined by GM-CSF. Eur J Immunol. 2010; microenvironment is crucial for the accumulation and function of myeloid- 40:22–35. derived suppressor cells. Oncoimmunology. 2016;5:e1063772. 14. Movahedi K, Guilliams M, Van den Bossche J, Van den Bergh R, Gysemans C, Beschin A, et al. Identification of discrete tumor-induced myeloid-derived suppressor cell subpopulations with distinct T cell-suppressive activity. Blood. 2008;111:4233–44.
Parasites & Vectors – Springer Journals
Published: May 30, 2018
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