On the InsideMinorsky, Peter V.
doi: 10.1104/pp.20.00033pmid: 33814624
How To Make A Lazy Plant Weep LAZY genes, discovered through the characterization of rice (Oryza sativa) mutants with unusually wide tiller angles, encode proteins that function in gravitropism. Gravitropism begins with a perception process that ultimately causes a difference in the cell elongation rate across the organ, stemming from the redistribution of the growth hormone auxin to the lower side of the organ. The perception event (i.e. the settling of statoliths) is not affected in lazy mutants. Etiolated hypocotyls of an Arabidopsis (Arabidopsis thaliana) lazy quadruple mutant (atlazy1;2;3;4) are essentially agravitropic but display a robust phototropic response, which also depends on auxin redistribution. These and other results indicate that LAZY proteins function in a gravity-specific process downstream of statolith sedimentation but upstream of the auxin redistribution process. LAZY genes encode moderate-sized proteins with no known or predictable biochemical function. Yoshihara and Spalding (pp. 1039–1051) have mutated each of five conserved regions of the AtLAZY1 gene and measured how well the transgenic expression of the resulting protein variant rescued the large inflorescence branch angle of an atlazy1 mutant. The most interesting results were found in region II, where it was determined that two conservative amino acid substitutions (L92A/I94A) had the profound effect of switching shoot gravity responses from negative (upward bending) to positive (downward bending), resulting in a weeping inflorescence phenotype. Mechanical weakness of the stem was not the cause. Instead, the L92A/I94A change to AtLAZY1 reversed the auxin gradient normally established across stems by the gravity-sensing mechanism. This discovery opens up new avenues for studying how auxin gradients form across organs and new approaches for engineering plant architecture. Malate Transport and Apple Tartness Acidity is a major contributor to apple (Malus domestica) fruit quality, including fruit overall taste and flavor. Organic acids collectively are responsible for acidity, but malic acid accounts for more than 90% of the total acid and largely controls apple fruit acidity. Most of the malic acid in apple fruits resides in the vacuole of the parenchyma cells. While malate synthesis and degradation can affect fruit malate level, apple fruit acidity appears to be primarily determined by intracellular transport of malate between the cytosol and the vacuole. Malic acid accumulates in the vacuole via an acid-trap mechanism. Low fruit acidity in Arabidopsis is strongly associated with truncation of Ma1, an ortholog of ALUMINUM-ACTIVATED MALATE TRANSPORTER9. Li et al. (pp. 992–1006) report that both the full-length protein, Ma1, and its naturally occurring truncated protein, ma1, localize to the tonoplast in Nicotiana benthamiana. When expressed in Xenopus laevis oocytes and N. benthamiana cells, Ma1 mediates a malate-dependent inward-rectifying current, whereas the ma1-mediated transmembrane current is much weaker, indicating that ma1 has significantly lower malate transport activity than Ma1. RNA interference suppression of Ma1 expression in various apple calli results in a significant decrease in malate level. Genotyping and phenotyping of 186 apple accessions from a diverse genetic background of 17 Malus species combined with the functional analyses described above indicate that Ma1 plays a key role in determining fruit acidity and that the truncation of Ma1 to ma1 is genetically responsible for low fruit acidity in apple. Natural Variation in the Amylose Content of Starch Starch is the major storage carbohydrate in plants. It occurs as semicrystalline, insoluble granules consisting of two Glc polymers: amylopectin and amylose. Amylopectin, the major polymer, gives rise to the semicrystalline matrix of the granule. Amylose is believed to reside in amorphous regions within the granule matrix. Amylose is not necessary for granule formation: mutant plants lacking amylose form essentially normal semicrystalline granules. The enzyme responsible for amylose synthesis, GRANULE-BOUND STARCH SYNTHASE (GBSS), differs from the other isoforms of starch synthase that synthesize amylopectin in being exclusively located within starch granules. Amylose makes up approximately 10% to 30% (w/w) of all the natural starches thus far examined, but mutants of crop and model plants that produce amylose-free starch are generally indistinguishable from their wild-type counterparts with respect to growth, starch content, and granule morphology. To explore the extent of variation in the amylose content of starch in a wild species, Seung et al. (pp. 870–881) used the genetic resources from the 1,135 sequenced natural accessions of Arabidopsis to identify a subset of accessions containing polymorphisms in GBSS, which proved to encompass unprecedented intraspecies variation in amylose content. The authors identified 18 accessions that are predicted to have polymorphisms in GBSS that affect protein function, and five of these accessions produced starch with no or extremely low amylose. Three mechanisms were elucidated by which GBSS sequence variation led to different amylose contents: (1) altered GBSS abundance, (2) altered GBSS activity, and (3) altered affinity of GBSS for binding PROTEIN TARGETING TO STARCH1, a protein that targets GBSS to starch granules. These findings demonstrate that amylose in leaves is not essential for the viability of some naturally occurring Arabidopsis genotypes, at least over short time scales and under some environmental conditions, and open an opportunity to explore the adaptive significance of amylose. The Nuclear Envelope and Stomatal Dynamics Eukaryotic nuclei are double membrane-bound organelles with distinct inner nuclear membranes (INM) and outer nuclear membranes (ONM). The site where the INM and ONM meet forms the nuclear pore, where nucleocytoplasmic transport occurs. Spanning the INM and the ONM are protein complexes known as linkers of the nucleoskeleton and cytoskeleton (LINC). LINC complexes contribute to nuclear morphology, nuclear movement and positioning, chromatin organization, and gene expression. LINC complexes are composed of Klarsicht/ANC-1/Syne Homology (KASH) ONM proteins and Sad1/UNC-84 (SUN) INM proteins that interact in the lumen of the nuclear envelope (NE), thus forming a bridge between the nucleoplasm and the cytoplasm. Plant-unique KASH proteins have recently been identified and named SUN domain-interacting NE proteins (SINE1–SINE4 in Arabidopsis). In Arabidopsis leaves, SINE1 is exclusively expressed in guard cells and their developmental precursors. Biel et al. (pp. 1100–1113) have now established that SINE1 and SINE2 play an important role in stomatal opening and closing in Arabidopsis. Loss of SINE1 or SINE2 results in abscisic acid (ABA) hyposensitivity and impaired stomatal dynamics but does not affect stomatal closure induced by the bacterial elicitor flg22. The ABA-induced stomatal closure phenotype is, in part, attributed to impairments in Ca2+ dynamics and F-actin regulation. Together, the data suggest that SINE1 and SINE2 act downstream of ABA but upstream of Ca2+ and F-actin. This study makes an unanticipated connection between stomatal regulation and nuclear envelope-associated proteins and adds two new players to the increasingly complex system of guard cell regulation. Shared Genetic Control of Root Traits across Taxa Root system architecture (RSA) plays a crucial role in plant productivity and tolerance to environmental stresses. The maize (Zea mays) root system, composed of the embryonic primary root and variable numbers of seminal roots, as well as postembryonic shoot-borne and lateral roots, is both different and more complex than that of the model plant Arabidopsis. [The sorghum [Sorghum bicolor] root system is similar to that of maize although it lacks seminal roots.] Based on the fundamental morphological differences between grasses and Arabidopsis, it is unlikely that a complete understanding of the genetic regulation of RSA in grasses can be elucidated from studies of Arabidopsis. Genome-wide associated study (GWAS) offers the opportunity to identify genes affecting natural variation of quantitative traits via the association of markers across the genome with phenotypic variation within diversity panels. With the ready availability of large numbers of genetic markers, phenotyping has become the bottleneck for GWAS. To overcome this bottleneck, Zheng et al. (pp. 977–991) have developed a high-throughput pipeline for the cleaning of field-grown roots as well as a semiautomated pipeline for the extraction of RSA traits from images. Comparative analyses of maize and sorghum GWAS results provide strong evidence for shared genetic control of RSA in these two species and the conservation of functional roles for syntenic orthologous gene pairs. Auxin and Microtubule Array Patterning The Arabidopsis hypocotyl is a valuable model for studying axial growth phenomena in flowering plants, owing to its dramatic cell elongation in the absence of cell division and its sensitivity to environmental cues. When grown in the dark, a hypocotyl rapidly elongates, using the energy reserves in the seed to drive the cotyledons upward into the light. Once light is detected, axial cell growth slows in favor of more radial cell growth due to the action of light receptors and myriad downstream signaling targets. The composition of the cell wall and the spatial organization of polymerous wall materials provide a means to guide cell expansion to produce cell shape. Microtubules, too, are essential for specifying axial cell elongation in plants. Cortical microtubules are organized into patterns that influence cell shape by directing the deposition of new cell wall materials. Drugs that perturb the microtubule cytoskeleton do not block cell growth per se but lead to apparent swelling and distention in growing cells, indicating a block to the mechanisms controlling cellular morphogenesis. Although auxin plays a central role in controlling plant cell growth and morphogenesis, our present understanding of how cell growth (i.e. increase in size) is coordinated with the cytoskeleton to determine hypocotyl cell shape (i.e. cellular morphogenesis) is limited. To examine the requirements for auxin-induced microtubule array patterning, True and Shaw (pp. 892–907) used an Arabidopsis double auxin f-box (afb) receptor mutant, afb4-8 afb5-5, that responds to auxin (indole-3-acetic acid) but has a strongly diminished response to the auxin analog, picloram. The authors show that picloram induces immediate changes to microtubule density and later transverse microtubule patterning in wild-type plants but does not cause microtubule array reorganization in the afb4-8 afb5-5 mutant. Additionally, auxin-induced microtubule array reorganization was found to occur in a dominant mutant (axr2-1) for the auxin coreceptor AUXIN RESPONSIVE2 (AXR2). The authors also observed that brassinosteroid application mimicked the auxin response, showing microtubule array effects and inducing transverse patterning in the axr2-1 mutant. Application of auxin to the brassinosteroid synthesis mutant, diminuto1, induced transverse array patterning but did not produce significant axial growth. Thus, exogenous auxin induces transverse microtubule patterning through the TRANSPORT INHIBITOR1/AFB transcriptional pathway and acts independently of brassinosteroids. Author notes www.plantphysiol.org/cgi/doi/10.1104/pp.20.00033 © 2020 American Society of Plant Biologists. All Rights Reserved. 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)
The Protein Phosphatase PP2A-B′γ Takes Control over Salicylic Acid to Suppress Defense and Premature SenescenceMhamdi, Amna
doi: 10.1104/pp.19.01466pmid: 32005741
Long thought to be unselective and often referred to as housekeeping enzymes, type 2A protein phosphatases (PP2As) have emerging specific regulatory functions in cell signaling (Luan, 2003; Durian et al., 2016; Máthé et al., 2019). PP2As interact with several pathways to activate signal transduction and adaptive responses while preventing unnecessary investment of energy. PP2A is a heterotrimer, with the core enzyme consisting of a scaffold A subunit, a catalytic C subunit, and a regulatory and variable B subunit with at least 17 isoforms in Arabidopsis (Arabidopsis thaliana). PP2A-B′γ acts as a negative regulator of pathogenesis responses and controls daylength-dependent responses to intracellular oxidative stress (Trotta et al., 2011; Li et al., 2014; Segonzac et al., 2014). However, how this phosphatase affects plant metabolism and defense remains to be established, simply because only a few targets of PP2A-B′γ have been identified. In this issue of Plant Physiology, Durian et al. (2020) define the mechanisms by which PP2A-B′γ prevents defense responses and delays senescence (Fig. 1). First, the authors provide evidence for an interaction between PP2A-B′γ and CALCIUM-DEPENDENT PROTEIN KINASE1 (CPK1), a kinase that positively regulates defense against the necrotrophic fungal pathogen Botrytis cinerea (Coca and San Segundo, 2010). Under control conditions, pp2a-b′γ mutants displayed increased in-gel kinase activity of CPK1. Treatment with B. cinerea increased CPK1 abundance, and this was particularly strong in the pp2a-b′γ background (Durian et al., 2020). Even though CPK1 was previously implicated in salicylic acid (SA)-related gene expression in response to Fusarium oxysporum, in this study, analysis of cpk1 mutants revealed that CPK1 is not required for the accumulation of PATHOGENESIS RELATED1 (PR1) proteins after B. cinerea infection. Figure 1. Open in new tabDownload slide Overview of PP2A-B′γ function in plant immunity and senescence. On the one hand, PP2A-B′γ controls responses to B. cinerea by interaction with the kinase CPK1. On the other hand, it regulates the development of premature senescence by suppressing SA signaling and biosynthesis. Future work will aim to gain evidence for PP2A-B′γ functions through direct interaction with other kinases or through modulating the phosphorylation state of enzymes involved in SA synthesis (PBS3 and ICS1). Question marks highlight knowledge gaps related to the possible function of PP2A-B′γ. Figure 1. Open in new tabDownload slide Overview of PP2A-B′γ function in plant immunity and senescence. On the one hand, PP2A-B′γ controls responses to B. cinerea by interaction with the kinase CPK1. On the other hand, it regulates the development of premature senescence by suppressing SA signaling and biosynthesis. Future work will aim to gain evidence for PP2A-B′γ functions through direct interaction with other kinases or through modulating the phosphorylation state of enzymes involved in SA synthesis (PBS3 and ICS1). Question marks highlight knowledge gaps related to the possible function of PP2A-B′γ. A second mechanism by which PP2A-B′γ controls disease resistance and the development of leaf senescence involves suppressing SA signaling. Transcriptome and metabolite profiling demonstrated that pp2a-b′γ mutants are primed for stress and accumulate markers of defense, in particular SA, camalexin and SA-related transcripts including PR1, PR2, and PR5, and WRKY transcription factors (Durian et al., 2020). Consistent with this, the pp2a-b′γ mutants exhibited premature leaf senescence in the apical parts of leaves, associated with the accumulation of PR1 and SENESCENCE ASSOCIATED GENE12 proteins. Durian et al. (2020) demonstrate that the premature leaf-yellowing phenotype requires SA biosynthesis via SALICYLIC ACID INDUCTION DEFICIENT2/ISOCHORISMATE SYNTHASE1 (ICS1). Furthermore, PP2A-B′γ function interferes with SA signaling through NONEXPRESSER OF PR GENES1 (Fig. 1). The report by Durian et al. (2020) enhances our understanding of how PP2A shapes the phosphoproteome to control plant senescence and illustrates how a regulatory subunit has evolved to regulate specifically one immune signal, SA. During plant development, PP2A-B′γ takes control over SA biosynthesis and signaling to suppress immune functions in young plants and inhibit the initiation and progression of senescence in mature leaves of older plants. However, we are only looking at the tip of the iceberg, as phosphatase substrate identification is still a tough task for researchers working in this field. Several key questions remain about how this phosphatase functions. For example, does the PP2A-B′γ regulatory role require another kinase-phosphatase interaction to control SA-dependent early senescence (e.g. interaction with SENESCENCE-INDUCED RECEPTOR-LIKE KINASE [SIRK/FRK1]; Asai et al., 2002), a kinase involved in early defense signaling? Or does it act on SA synthesis by dephosphorylating AvrPphB SUSCEPTIBLE3 (PBS3; Rekhter et al., 2019), a cytosolic enzyme recently shown to catalyze the last step of isochorismate conversion to SA? LITERATURE CITED Asai T , Tena G, Plotnikova J, Willmann MR, Chiu WL, Gómez-Gómez L, Boller T, Ausubel FM, Sheen J ( 2002 ) MAP kinase signalling cascade in Arabidopsis innate immunity . Nature 415 : 977 – 983 Google Scholar Crossref Search ADS PubMed WorldCat Coca M , San Segundo B ( 2010 ) AtCPK1 calcium-dependent protein kinase mediates pathogen resistance in Arabidopsis . Plant J 63 : 526 – 540 Google Scholar Crossref Search ADS PubMed WorldCat Durian G , Jeschke V, Rahikainen M, Vuorinen K, Gollan PJ, Brosché M, Salojärvi J, Glawischnig E, Winter Z, Li S, et al. ( 2020 ) PROTEIN PHOSPHATASE 2A-B′γ controls Botrytis cinerea resistance and developmental leaf senescence . Plant Physiol 182 : 1161 – 1181 Google Scholar Crossref Search ADS PubMed WorldCat Durian G , Rahikainen M, Alegre S, Brosché M, Kangasjärvi S ( 2016 ) Protein Phosphatase 2A in the regulatory network underlying biotic stress resistance in plants . Front Plant Sci 7 : 812 Google Scholar Crossref Search ADS PubMed WorldCat Li S , Mhamdi A, Trotta A, Kangasjärvi S, Noctor G ( 2014 ) The protein phosphatase subunit PP2A-B′γ is required to suppress day length-dependent pathogenesis responses triggered by intracellular oxidative stress . New Phytol 202 : 145 – 160 Google Scholar Crossref Search ADS PubMed WorldCat Luan S ( 2003 ) Protein phosphatases in plants . Annu Rev Plant Biol 54 : 63 – 92 Google Scholar Crossref Search ADS PubMed WorldCat Máthé C , Garda T, Freytag C, M-Hamvas M ( 2019 ) The role of serine-threonine protein phosphatase PP2A in plant oxidative stress signaling: Facts and hypotheses . Int J Mol Sci 20 : 3028 Google Scholar Crossref Search ADS WorldCat Rekhter D , Lüdke D, Ding Y, Feussner K, Zienkiewicz K, Lipka V, Wiermer M, Zhang Y, Feussner I ( 2019 ) Isochorismate-derived biosynthesis of the plant stress hormone salicylic acid . Science 365 : 498 – 502 Google Scholar Crossref Search ADS PubMed WorldCat Segonzac C , Macho AP, Sanmartín M, Ntoukakis V, Sánchez-Serrano JJ, Zipfel C ( 2014 ) Negative control of BAK1 by protein phosphatase 2A during plant innate immunity . EMBO J 33 : 2069 – 2079 Google Scholar Crossref Search ADS PubMed WorldCat Trotta A , Wrzaczek M, Scharte J, Tikkanen M, Konert G, Rahikainen M, Holmström M, Hiltunen HM, Rips S, Sipari N, et al. ( 2011 ) Regulatory subunit B′γ of protein phosphatase 2A prevents unnecessary defense reactions under low light in Arabidopsis . Plant Physiol 156 : 1464 – 1480 Google Scholar Crossref Search ADS PubMed WorldCat Author notes 2 Senior author. www.plantphysiol.org/cgi/doi/10.1104/pp.19.01466 © 2020 American Society of Plant Biologists. All Rights Reserved. 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)
A Tale of Two Isoforms: Calcium-Dependent Inhibition of SnRK2 by SnRK-Calcium-Binding SensorJulkowska, Magdalena
doi: 10.1104/pp.19.01554pmid: 32005742
Reacting to the environment requires not only activating signaling cascades but also modulating the activity of individual components in a context- and time-dependent manner. For example, under nonstress conditions, protein phosphatases 2C (PP2C) keep the SnRK2 abscisic acid (ABA)-dependent protein kinases in an inactive state (Dupeux et al., 2011). Upon exposure to stress, ABA activates the PYR/PYL receptors, which interact with the PP2Cs (Park et al., 2009), releasing the SnRK2 protein kinases (Fig. 1). ABA-dependent SnRK2s have important functions in regulating stomatal closure and growth (Fujii and Zhu, 2009), but their activity is only transient (Boudsocq et al., 2007; McLoughlin et al., 2012). SnRKs interact with other proteins that modify their activities, including calcium-binding proteins. Previously, Bucholc et al. (2011) screened for proteins interacting with osmotic stress-activated protein kinase, a member of the SnRK2 family in Nicotiana tabacum. One of the SnRK2 interactors identified is a calcium-binding protein they named SnRK-Calcium-binding Sensor (SCS), which inhibits SnRK2 kinase activity upon Ca2+ binding (Bucholc et al., 2011). SCS was established to play a role in seed germination, but the nature of the interaction between SnRK2 and SCS, and its significance for other ABA-dependent processes, were unknown. Figure 1. Open in new tabDownload slide Overview of SnRK2 kinase regulation and role of SCS. Under nonstress conditions, the SnRK2 activity is inhibited by PP2C phosphatases. Under stress conditions, the PP2Cs are targeted by ABA receptors (PYR/PYL) and release SnRK2 to phosphorylate itself as well as target proteins. SCS-A inhibits the SnRK2 activity in a calcium-dependent manner, while SCS-B, an isoform of SCS resulting from an alternative transcription site, inhibits SnRK2 activity independently of calcium concentration. Tarnowski et al. (2020) found that the N-terminal domain of SCS-A regulates calcium-dependent inhibition of SnRK2 by affecting the stability of the C-terminal domain of the SCS. Figure 1. Open in new tabDownload slide Overview of SnRK2 kinase regulation and role of SCS. Under nonstress conditions, the SnRK2 activity is inhibited by PP2C phosphatases. Under stress conditions, the PP2Cs are targeted by ABA receptors (PYR/PYL) and release SnRK2 to phosphorylate itself as well as target proteins. SCS-A inhibits the SnRK2 activity in a calcium-dependent manner, while SCS-B, an isoform of SCS resulting from an alternative transcription site, inhibits SnRK2 activity independently of calcium concentration. Tarnowski et al. (2020) found that the N-terminal domain of SCS-A regulates calcium-dependent inhibition of SnRK2 by affecting the stability of the C-terminal domain of the SCS. In this issue of Plant Physiology, Tarnowski et al. (2020) describe two isoforms of SCS that result from alternative transcription start sites. SCS-A was initially identified by Bucholc et al. (2011) as the SnRK interactor. It contains one canonical EF-hand motif at the N-terminal end of the protein and three EF-hand-like motifs. The SCS-B isoform is shorter by 110 amino acids and contains only two EF-hand-like motifs (Fig. 1). While canonical EF-hand motifs are known to facilitate Ca2+ binding (Lewit-Bentley and Réty, 2000), the contribution of EF-hand-like motifs is less studied. Although both isoforms were able to bind Ca2+, only SCS-A requires Ca2+ to inhibit SnRK activity. By examining the conformational changes of SCS-A and SCS-B through circular dichroism spectroscopy and hydrogen/deuterium exchange, Tarnowski et al. (2020) observed that only SCS-A undergoes detectable conformational changes upon binding to Ca2+. The group found that the C-terminal domain is stable in SCS-B but not in SCS-A. Binding Ca2+ by SCS-A results in a conformational change of the protein, which makes the C-terminal part more similar to SCS-B, stabilizing the region near the third EF-hand-like motif. SCS-A was previously shown to be involved in promoting seed germination (Bucholc et al., 2011), but the role of both SCS isoforms in other processes was not known. Both isoforms were transcriptionally induced upon ABA and salt stress exposure, although SCS-A transcript was more abundant than SCS-B. The Arabidopsis (Arabidopsis thaliana) plants with no functional SCS exhibited improved drought tolerance, similar to lack of function in other SnRK2 inhibitors, like PP2C (Tarnowski et al., 2020). The overexpression of either individual isoform did not completely reverse the sensitivity to drought stress to the wild-type levels, suggesting that both isoforms of SCS could play distinct, nonoverlapping roles in the inactivation of SnRK. Therefore, these two differentially regulated isoforms have different, important parts in the tale of how plant cells integrate the calcium signaling input into protein kinase activity at specific time points. LITERATURE CITED Boudsocq M , Droillard MJ, Barbier-Brygoo H, Laurière C ( 2007 ) Different phosphorylation mechanisms are involved in the activation of sucrose non-fermenting 1 related protein kinases 2 by osmotic stresses and abscisic acid . Plant Mol Biol 63 : 491 – 503 Google Scholar Crossref Search ADS PubMed WorldCat Bucholc M , Ciesielski A, Goch G, Anielska-Mazur A, Kulik A, Krzywińska E, Dobrowolska G ( 2011 ) SNF1-related protein kinases 2 are negatively regulated by a plant-specific calcium sensor . J Biol Chem 286 : 3429 – 3441 Google Scholar Crossref Search ADS PubMed WorldCat Dupeux F , Antoni R, Betz K, Santiago J, Gonzalez-Guzman M, Rodriguez L, Rubio S, Park SY, Cutler SR, Rodriguez PL, et al. ( 2011 ) Modulation of abscisic acid signaling in vivo by an engineered receptor-insensitive protein phosphatase type 2C allele . Plant Physiol 156 : 106 – 116 Google Scholar Crossref Search ADS PubMed WorldCat Fujii H , Zhu JK ( 2009 ) Arabidopsis mutant deficient in 3 abscisic acid-activated protein kinases reveals critical roles in growth, reproduction, and stress . Proc Natl Acad Sci USA 106 : 8380 – 8385 Google Scholar Crossref Search ADS PubMed WorldCat Lewit-Bentley A , Réty S ( 2000 ) EF-hand calcium-binding proteins . Curr Opin Struct Biol 10 : 637 – 643 Google Scholar Crossref Search ADS PubMed WorldCat McLoughlin F , Galvan-Ampudia CS, Julkowska MM, Caarls L, van der Does D, Laurière C, Munnik T, Haring MA, Testerink C ( 2012 ) The Snf1-related protein kinases SnRK2.4 and SnRK2.10 are involved in maintenance of root system architecture during salt stress . Plant J 72 : 436 – 449 Google Scholar Crossref Search ADS PubMed WorldCat Park SY , Fung P, Nishimura N, Jensen DR, Fujii H, Zhao Y, Lumba S, Santiago J, Rodrigues A, Chow TFF, et al. ( 2009 ) Abscisic acid inhibits type 2C protein phosphatases via the PYR/PYL family of START proteins . Science 324 : 1068 – 1071 Google Scholar PubMed OpenURL Placeholder Text WorldCat Tarnowski K , Klimecka M, Ciesielski A, Goch G, Kulik A, Fedak H, Poznanski J, Lichocka M, Pierechod M, Engh RA, et al. ( 2020 ) Two SnRK2-interacting calcium sensor isoforms negatively regulate SnRK2 activity by different mechanisms . Plant Physiol 182 : 1142 – 1160 Google Scholar Crossref Search ADS PubMed WorldCat Author notes 2 Senior author. www.plantphysiol.org/cgi/doi/10.1104/pp.19.01554 © 2020 American Society of Plant Biologists. All Rights Reserved. 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)
An Online Database for Exploring Over 2,000 Arabidopsis Small RNA Libraries Feng, Li; Zhang, Fei; Zhang, Hong; Zhao, Yan; Meyers, Blake C.; Zhai, Jixian
doi: 10.1104/pp.19.00959pmid: 31843802
Abstract Small RNAs (sRNAs) play a wide range of important roles in plants, from maintaining genome stability and enhancing disease resistance to regulating developmental processes. Over the past decade, next-generation sequencing technologies have allowed us to explore the sRNA populations with unprecedented depth and accuracy. The community has accumulated a tremendous amount of sRNA sequencing (sRNA-seq) data from various genotypes, tissues, and treatments. However, it has become increasingly challenging to access these “big data” and extract useful information, particularly for researchers lacking sophisticated bioinformatics tools and expensive computational resources. Here, we constructed an online website, Arabidopsis Small RNA Database (ASRD, http://ipf.sustech.edu.cn/pub/asrd), that allows users to easily explore the information from publicly available Arabidopsis (Arabidopsis thaliana) sRNA libraries. Our database contains ∼2.3 billion sRNA reads, representing ∼250 million unique sequences from 2,024 sRNA-seq libraries. We downloaded the raw data for all libraries and reprocessed them with a unified pipeline so that the normalized abundance of any particular sRNA or the sum of abundances of sRNAs from a genic or transposable element region can be compared across all libraries. We also integrated an online Integrative Genomics Viewer browser into our Web site for convenient visualization. ASRD is a free, web-accessible, and user-friendly database that supports the direct query of over 2,000 Arabidopsis sRNA-seq libraries. We believe this resource will help plant researchers take advantage of the vast next-generation sequencing datasets available in the public domain. Small RNAs (sRNAs) in plants, generally 20–24 nucleotides (nt) in size, are regulatory RNA molecules functioning in growth and developmental processes, as well as in protecting plants against viruses, transgenes, and transposable elements (TEs; Baulcombe, 2004; Carthew and Sontheimer, 2009; Chen, 2009; Ruiz-Ferrer and Voinnet, 2009; Bologna and Voinnet, 2014; Borges and Martienssen, 2015; Meyers and Axtell, 2019). There are two major classes of sRNAs: microRNAs (miRNAs) and small interfering RNAs (siRNAs; Axtell, 2013). For miRNA biogenesis, RNA polymerase II transcribes miRNA genes into long, single-stranded primary miRNAs, then these single-stranded primary miRNAs form imperfectly matched foldback structures and can be further processed by Dicer-like1 (DCL1) protein into mature miRNA/miRNA* duplexes (Carthew and Sontheimer, 2009; Voinnet, 2009; Axtell, 2013). In contrast, siRNAs are processed by DCLs other than DCL1, with their perfectly matched double-stranded precursors produced by RNA-dependent RNA polymerases (RDRs; Carthew and Sontheimer, 2009; Axtell, 2013). Transacting siRNAs (ta-siRNAs) are usually 21 nt in length and their biogenesis depends on RDR6 and DCL4 activity for their generation, triggered by either “two-hits” (Allen et al., 2005; Axtell et al., 2006) or a single 22-nt miRNA/siRNA (Fei et al., 2013). The production of 24-nt siRNAs is generally initiated by RNA polymerase IV (Pol IV) transcription, followed by RDR2 activity to form a complementary strand that is subsequently cleaved by DCL3. These 24-nt siRNAs can mediate transcriptional gene silencing by targeting DNA methylation and repressive histone modifications (Matzke and Mosher, 2014; Cuerda-Gil and Slotkin, 2016). The development of next-generation sequencing (NGS) technologies has drastically improved sensitivity and accuracy in detecting sRNA molecules. A large number of sRNA sequencing (sRNA-seq) datasets have been stored in public databases, such as the Gene Expression Omnibus (GEO; Clough and Barrett, 2016) and the Sequence Read Archive (SRA; Leinonen et al., 2011), which include samples from various genotypes, tissues, and treatments. However, it is difficult to directly compare sRNA data across publications using the original results because different pipelines and methods were usually used to analyze these sRNA-seq libraries in each study. Thus, it is difficult for researchers, especially those with a wet-lab background, to take advantage of the vast collection of public NGS datasets. RESULTS To address this challenge, here we present the Arabidopsis Small RNA Database (ASRD), an online database with integrated, multifaceted functions for exploring published Arabidopsis (Arabidopsis thaliana) sRNA-seq libraries (Fig. 1). ASRD currently hosts 2,024 sRNA-seq libraries collected from GEO and SRA databases. The raw sequencing data of these libraries were downloaded and processed with a unified pipeline so that we can compare the normalized abundances of sRNAs across all libraries. ASRD provides easy-to-access links to download the raw, trimmed, and mapped reads so that researchers can apply their favorite tools to these published libraries with ease. ASRD supports a “Google-like” search through querying of a single sRNA sequence, miRNA ID, miRNA name, miRNA sequence, gene ID, library ID, or library-related keyword (Fig. 2, A and B). ASRD also supports “Advanced options” for narrowing down the search area. All search results can be downloaded via a simple click and be further analyzed using Microsoft Excel. We also added a built-in online Integrative Genomics Viewer (IGV) interface (Robinson et al., 2011) to visualize and browse sRNA alignments (Fig. 2C). Functions of ASRD are described in the following sections (please see the online video tutorial for a step-by-step instruction on how to use the website): Figure 1. Open in new tabDownload slide Overflow of the ASRD. A total of 2,024 publicly available Arabidopsis sRNA-seq libraries were collected from GEO and SRA databases, and processed with a unified pipeline for cross-library comparisons, and all the sRNA-related information can be accessed via keyword-based searching on the ASRD Web site (http://ipf.sustech.edu.cn/pub/asrd/). Figure 1. Open in new tabDownload slide Overflow of the ASRD. A total of 2,024 publicly available Arabidopsis sRNA-seq libraries were collected from GEO and SRA databases, and processed with a unified pipeline for cross-library comparisons, and all the sRNA-related information can be accessed via keyword-based searching on the ASRD Web site (http://ipf.sustech.edu.cn/pub/asrd/). Figure 2. Open in new tabDownload slide Basic functions of ASRD. A, Input can be an sRNA sequence, an miRNA sequence, an miRNA ID, an miRNA name, a keyword, a library ID, or a gene ID. B, The introduction of ASRD main page functions. ASRD supports a “Google-like” search that allows the users to search each item in one single input box. “All libraries” shows the detailed information of libraries; “Examples” presents different types of queries; “Tutorials” links to instructions to users; “Advanced options” describes various additional filters. C, Display of search results, including the information, data table, data plot, and online IGV, based on different queries of “sRNA,” “miRNA,” “gene,” and “library.” All results can be downloaded to a local computer. Figure 2. Open in new tabDownload slide Basic functions of ASRD. A, Input can be an sRNA sequence, an miRNA sequence, an miRNA ID, an miRNA name, a keyword, a library ID, or a gene ID. B, The introduction of ASRD main page functions. ASRD supports a “Google-like” search that allows the users to search each item in one single input box. “All libraries” shows the detailed information of libraries; “Examples” presents different types of queries; “Tutorials” links to instructions to users; “Advanced options” describes various additional filters. C, Display of search results, including the information, data table, data plot, and online IGV, based on different queries of “sRNA,” “miRNA,” “gene,” and “library.” All results can be downloaded to a local computer. An “All libraries” Table To give an overview of all 2,024 sRNA-seq libraries in ASRD (Supplemental Table S1), we provided a table with detailed information of each library, including description, genotype, ecotype, tissue, the counts of raw, transfer/ribosomal/small nuclear/small nucleolar RNAs (t/r/sn/snoRNA)-matched, genome-matched total and distinct reads, the transcripts per million (TPM) levels of sRNAs produced from miRNA, protein-coding (PC), and Pol IV loci. A table with more information (such as size distribution of total sRNAs and different classes of sRNAs in each library) can be downloaded via the link on the “All libraries” page. Search by sRNA Sequence or miRNA ID/Name For querying the information of a single miRNA or sRNA, ASRD supports searches by a single sRNA sequence, miRNA ID, miRNA name, or miRNA sequence, and it will return the statistics of expression levels across all libraries. Taking the query of miR158a-5p as an example, Figure 3A shows the maximum, median, mean, and minimum TPM levels of miR158a-5p in all libraries. The violin plot shows the overall TPM distribution of miR158a-5p, and the bar diagram displays the number of miR158a-5p expressed libraries grouped by different TPM intervals (Fig. 3B). The result table with the raw count, TPM, TP5M, and TP10M of miR158a-5p in each library is also downloadable. Furthermore, users can narrow down the query results via the “Advanced options” by applying a combination of filters including tissue, ecotype, genotype, TPM level, keyword, and release date (Fig. 3C). The integrated online IGV interface can be used to browse the mapped miR158a-5p sequences on the genome in one or more libraries (Fig. 3D). Figure 3. Open in new tabDownload slide Example of a query using miR158a-5p. A, Example data for miR158a-5p, such as the statistics of maximum, median, mean, and minimum TPM levels in all libraries, as well as genome hits and their annotations on miRBase. B, The violin plot shows the overall TPM distribution, and each point represents the TPM level of miR158a-5p in a library. The bar diagram displays the number of libraries in different TPM intervals. C, The result table displays the read count, TPM, TP5M, and TP10M levels of miR158a-5p in all libraries. The advanced options can be used to filter the results by tissue, ecotype, genotype, release date, TPM level, or keyword. Right-clicking on each column of this table shows more operations, such as adding, removing, or sorting a column, linking a library to the National Center for Biotechnology Information, or adding a library to online IGV. D, The online IGV browses the mapped miR158a-5p sequences in the DRX012741 library. Figure 3. Open in new tabDownload slide Example of a query using miR158a-5p. A, Example data for miR158a-5p, such as the statistics of maximum, median, mean, and minimum TPM levels in all libraries, as well as genome hits and their annotations on miRBase. B, The violin plot shows the overall TPM distribution, and each point represents the TPM level of miR158a-5p in a library. The bar diagram displays the number of libraries in different TPM intervals. C, The result table displays the read count, TPM, TP5M, and TP10M levels of miR158a-5p in all libraries. The advanced options can be used to filter the results by tissue, ecotype, genotype, release date, TPM level, or keyword. Right-clicking on each column of this table shows more operations, such as adding, removing, or sorting a column, linking a library to the National Center for Biotechnology Information, or adding a library to online IGV. D, The online IGV browses the mapped miR158a-5p sequences in the DRX012741 library. Search Library Using ID or Keyword This function supports querying of a single library ID or library-related keyword. ASRD shows not only the library-related information gathered from the GEO or SRA database but also the statistics of sRNA expression levels across libraries. Read counts include raw, trimmed, mapped, t/r/sn/snoRNA-matched, genome-matched total and distinct reads. TPM levels are for sRNAs generated from miRNA, PC, Pol IV, TE, ta-siRNA loci (TAS), and others. The files of raw, trimmed, and mapped reads can be downloaded via a single click and fed into other analysis tools that the users prefer (Fig. 4A). For characterizing different classes of sRNAs, the pie diagram shows their corresponding percentage, and the line diagrams describe the size distributions of genome-matched total and distinct sRNAs (Fig. 4B). For a quick glance at each library, ASRD also provides the read counts and TPM levels of sRNAs from each of the miRNA, TAS, and “Top-100” PC, Pol IV, and TE loci ranked by TPM (Fig. 4C). The “Advanced options” can also be used to filter the search results by the TPM levels of sRNAs produced from different classes of loci. Figure 4. Open in new tabDownload slide Examples of queries using library ID and gene ID. A to C, Search by library ID. A, The library information includes statistics of the raw, trimmed, mapped, t/r/sn/snoRNA-matched, genome-matched total and distinct reads, and the TPM levels of sRNAs generated from miRNA, TAS, Pol IV, TE, PC, and other classes of loci. B, The pie diagram exhibits the percentage of each class of sRNAs in the library, and the line diagrams show the size distributions of genome-matched total and distinct sRNAs from each class, with x axis indicating sRNA size (nt), and y axis showing the percentage of sRNAs. C, The tables display the read counts and TPM levels of sRNAs derived from each of miRNAs, TAS, Pol IV, TE, and the Top-100 abundant PCs. The advanced options additionally allow the users to filter the results by the TPM levels of sRNAs produced from different classes of loci. d and E, Search by gene ID. D, The diagram with scatters and boxes describes the TPM levels of sRNAs on the queried locus across all libraries. The gray, orange, and blue colors represent 18–28-nt sRNAs, sense, and antisense sRNAs, respectively. E, The table shows the TPM levels of 18–28-nt, sense, and antisense sRNAs generated from that locus in each library. Figure 4. Open in new tabDownload slide Examples of queries using library ID and gene ID. A to C, Search by library ID. A, The library information includes statistics of the raw, trimmed, mapped, t/r/sn/snoRNA-matched, genome-matched total and distinct reads, and the TPM levels of sRNAs generated from miRNA, TAS, Pol IV, TE, PC, and other classes of loci. B, The pie diagram exhibits the percentage of each class of sRNAs in the library, and the line diagrams show the size distributions of genome-matched total and distinct sRNAs from each class, with x axis indicating sRNA size (nt), and y axis showing the percentage of sRNAs. C, The tables display the read counts and TPM levels of sRNAs derived from each of miRNAs, TAS, Pol IV, TE, and the Top-100 abundant PCs. The advanced options additionally allow the users to filter the results by the TPM levels of sRNAs produced from different classes of loci. d and E, Search by gene ID. D, The diagram with scatters and boxes describes the TPM levels of sRNAs on the queried locus across all libraries. The gray, orange, and blue colors represent 18–28-nt sRNAs, sense, and antisense sRNAs, respectively. E, The table shows the TPM levels of 18–28-nt, sense, and antisense sRNAs generated from that locus in each library. Search by Gene/TE ID ASRD supports searches by any of the 38,621 gene/TE IDs annotated in the most recent Araport11 release (Cheng et al., 2017; Fig. 4A). To give an overview of sRNAs generated from a given locus, the “Data Plot” page shows the TPM levels of 18–28 nt sRNAs across all libraries (Fig. 4D), and the “Data table” page details the size distribution, sense, and antisense abundances in each library (Fig. 4E). This table can be downloaded for local use. IGV Visualization ASRD integrates an online IGV interface to browse genome-matched sRNAs in any number of libraries. Besides the links on the “Information” pages, the users can use several input boxes and a submit button to easily explore sRNAs at any genomic region in one or more libraries. We extended the IGV function to allow the users to submit a single library ID; genotype-, ecotype-, or tissue-related keyword; SRA study ID (to simultaneously select multiple libraries included in the same study); gene ID, gene symbol, or alias; TAS family members’ name and ID; and miRNA name. DISCUSSION Many excellent web-based resources have been developed for hosting sRNA data, such as the MPSS Web site (Nakano et al., 2006), the UCSC Genome Browser (Kent et al., 2002), the Anno-J Browser (Lister et al., 2008), and the EPIC-CoGe Browser (Nelson et al., 2018). Compared to these existing resources that are mostly designed for a single project or multiple projects, ASRD can easily and quickly extract the information from more than 2,000 Arabidopsis sRNA-seq libraries using a simple “Google-like” search and enables the direct comparison of sRNA abundances across different libraries by reprocessing all the raw data from scratch. In the future, we plan to update ASRD on a regular basis by adding more recently published sRNA-seq libraries, and we also intend to experiment with new functions that allow the users to upload their own sRNA-seq libraries and host them at ASRD. MATERIALS AND METHODS Data Collection, Processing, and Analysis We collected Arabidopsis (Arabidopsis thaliana) sRNA-seq data published until July 2019 from GEO and SRA databases by searching with the following combinations of keywords: “([sRNA] OR [sRNAs] OR siRNA OR smallRNA OR smallRNAs OR miRNA OR sRNA OR sRNAs OR siRNAs OR miRNAs) and Arabidopsis.” We obtained a total of 2,024 nonredundant libraries from the NGS platform (Illumina) with raw sequencing data. Figure 1 describes the data collection, processing, and database construction pipeline. The raw datasets in SRA format were downloaded, processed, and analyzed by in-house scripts (all of our scripts are available upon request). In brief, we used the fastq-dump from the SRA Toolkit (v2.8.2; https://www.ncbi.nlm.nih.gov/books/NBK158900/) to convert raw data from sra to fastq format; if a 3′ adapter sequence was not provided, we would predict and trim it with the software tools DNApi (Tsuji and Weng, 2016) and Cutadapt v1.16 (Martin, 2011); if 5′ barcoding was used, we would also chopped the 5′ barcode sequence off; we then processed the remaining 18–28 nt reads in the fasta file to tag_count format. To annotate sRNA features, we mapped these reads to the Arabidopsis reference genome (The Arabidopsis Information Resource 10) using the program BowTie v1.2.1.1 (Langmead et al., 2009), allowing zero mismatches (−v 0) and multiple hits (−a). We used Araport11-annotated t/r/sn/snoRNAs to flag corresponding types of sRNAs in each bam file. After importing all sRNAs, our database contains 2,357,941,025 genome-matched sRNAs representing 254,678,199 distinct sRNAs. Analysis of sRNA Abundance The annotation of 426 mature Arabidopsis miRNAs, including both miRNA and miRNA* sequences (named as miRNA-5p and miRNA-3p), was obtained from the program miRbase (v22.1; Kozomara et al., 2019). Eight TAS loci (TAS1a, TAS1b, TAS1c, TAS2, TAS3, TAS3b, TAS3c, and TAS4) were used for calculating TAS abundance. The annotations of 38,621 genes were from Araport11. The list of 7,632 P4-siRNA loci was the same as described in Zhai et al. (2015). The 27,655 PC genes and 3,901 TEs annotated in Araport11 were used to calculate the abundance of PC gene-generating siRNAs and TE-generating siRNAs, respectively. The abundance of sRNAs in each library was calculated as TPM by normalizing to the total number of genome-matched reads excluding t/r/sn/snoRNA-derived ones. The TPM of sRNAs at a given locus was the sum of genome hits-normalized TPMs for all mapped reads at that locus. Supplemental Data The following supplemental materials are available. Supplemental Table S1. The information of 2,024 publicly available libraries in ASRD. ACKNOWLEDGMENTS We thank all the research groups that contributed sRNA-seq data to the public domain, and we apologize for not being able to cite all the related articles in the main text due to limited space. References for all libraries that we used are listed in Supplemental Table S1. LITERATURE CITED Allen E , Xie Z, Gustafson AM, Carrington JC ( 2005 ) microRNA-directed phasing during trans-acting siRNA biogenesis in plants . Cell 121 : 207 – 221 Google Scholar Crossref Search ADS PubMed WorldCat Axtell MJ ( 2013 ) Classification and comparison of small RNAs from plants . Annu Rev Plant Biol 64 : 137 – 159 Google Scholar Crossref Search ADS PubMed WorldCat Axtell MJ , Jan C, Rajagopalan R, Bartel DP ( 2006 ) A two-hit trigger for siRNA biogenesis in plants . Cell 127 : 565 – 577 Google Scholar Crossref Search ADS PubMed WorldCat Baulcombe D ( 2004 ) RNA silencing in plants . Nature 431 : 356 – 363 Google Scholar Crossref Search ADS PubMed WorldCat Bologna NG , Voinnet O ( 2014 ) The diversity, biogenesis, and activities of endogenous silencing small RNAs in Arabidopsis . Annu Rev Plant Biol 65 : 473 – 503 Google Scholar Crossref Search ADS PubMed WorldCat Borges F , Martienssen RA ( 2015 ) The expanding world of small RNAs in plants . Nat Rev Mol Cell Biol 16 : 727 – 741 Google Scholar Crossref Search ADS PubMed WorldCat Carthew RW , Sontheimer EJ ( 2009 ) Origins and mechanisms of miRNAs and siRNAs . Cell 136 : 642 – 655 Google Scholar Crossref Search ADS PubMed WorldCat Chen X ( 2009 ) Small RNAs and their roles in plant development . Annu Rev Cell Dev Biol 25 : 21 – 44 Google Scholar Crossref Search ADS PubMed WorldCat Cheng CY , Krishnakumar V, Chan AP, Thibaud-Nissen F, Schobel S, Town CD ( 2017 ) Araport11: A complete reannotation of the Arabidopsis thaliana reference genome . Plant J 89 : 789 – 804 Google Scholar Crossref Search ADS PubMed WorldCat Clough E , Barrett T ( 2016 ) The Gene Expression Omnibus Database . Methods Mol Biol 1418 : 93 – 110 Google Scholar Crossref Search ADS PubMed WorldCat Cuerda-Gil D , Slotkin RK ( 2016 ) Non-canonical RNA-directed DNA methylation . Nat Plants 2 : 16163 Google Scholar Crossref Search ADS PubMed WorldCat Fei Q , Xia R, Meyers BC ( 2013 ) Phased, secondary, small interfering RNAs in posttranscriptional regulatory networks . Plant Cell 25 : 2400 – 2415 Google Scholar Crossref Search ADS PubMed WorldCat Kent WJ , Sugnet CW, Furey TS, Roskin KM, Pringle TH, Zahler AM, Haussler D ( 2002 ) The human genome browser at UCSC . Genome Res 12 : 996 – 1006 Google Scholar Crossref Search ADS PubMed WorldCat Kozomara A , Birgaoanu M, Griffiths-Jones S ( 2019 ) miRBase: From microRNA sequences to function . Nucleic Acids Res 47 ( D1 ): D155 – D162 Google Scholar Crossref Search ADS PubMed WorldCat Langmead B , Trapnell C, Pop M, Salzberg SL ( 2009 ) Ultrafast and memory-efficient alignment of short DNA sequences to the human genome . Genome Biol 10 : R25 Google Scholar Crossref Search ADS PubMed WorldCat Leinonen R , Sugawara H, Shumway M; International Nucleotide Sequence Database Collaboration ( 2011 ) The sequence read archive . Nucleic Acids Res 39 : D19 – D21 Google Scholar Crossref Search ADS PubMed WorldCat Lister R , O’Malley RC, Tonti-Filippini J, Gregory BD, Berry CC, Millar AH, Ecker JR ( 2008 ) Highly integrated single-base resolution maps of the epigenome in Arabidopsis . Cell 133 : 523 – 536 Google Scholar Crossref Search ADS PubMed WorldCat Martin M ( 2011 ) Cutadapt removes adapter sequences from high-throughput sequencing reads . EMBnet J 17 : 10 – 12 Google Scholar Crossref Search ADS WorldCat Matzke MA , Mosher RA ( 2014 ) RNA-directed DNA methylation: An epigenetic pathway of increasing complexity . Nat Rev Genet 15 : 394 – 408 Google Scholar Crossref Search ADS PubMed WorldCat Meyers BC , Axtell MJ ( 2019 ) MicroRNAs in plants: Key findings from the early years . Plant Cell 31 : 1206 – 1207 Google Scholar Crossref Search ADS PubMed WorldCat Nakano M , Nobuta K, Vemaraju K, Tej SS, Skogen JW, Meyers BC ( 2006 ) Plant MPSS databases: Signature-based transcriptional resources for analyses of mRNA and small RNA . Nucleic Acids Res 34 : D731 – D735 Google Scholar Crossref Search ADS PubMed WorldCat Nelson ADL , Haug-Baltzell AK, Davey S, Gregory BD, Lyons E ( 2018 ) EPIC-CoGe: Managing and analyzing genomic data . Bioinformatics 34 : 2651 – 2653 Google Scholar Crossref Search ADS PubMed WorldCat Robinson JT , Thorvaldsdóttir H, Winckler W, Guttman M, Lander ES, Getz G, Mesirov JP ( 2011 ) Integrative genomics viewer . Nat Biotechnol 29 : 24 – 26 Google Scholar Crossref Search ADS PubMed WorldCat Ruiz-Ferrer V , Voinnet O ( 2009 ) Roles of plant small RNAs in biotic stress responses . Annu Rev Plant Biol 60 : 485 – 510 Google Scholar Crossref Search ADS PubMed WorldCat Tsuji J , Weng Z ( 2016 ) DNApi: A De Novo Adapter Prediction Algorithm for small RNA sequencing data . PLoS One 11 : e0164228 Google Scholar Crossref Search ADS PubMed WorldCat Voinnet O ( 2009 ) Origin, biogenesis, and activity of plant microRNAs . Cell 136 : 669 – 687 Google Scholar Crossref Search ADS PubMed WorldCat Zhai J , Bischof S, Wang H, Feng S, Lee TF, Teng C, Chen X, Park SY, Liu L, Gallego-Bartolome J, et al. ( 2015 ) A one precursor one siRNA model for Pol IV-dependent siRNA biogenesis . Cell 163 : 445 – 455 Google Scholar Crossref Search ADS PubMed WorldCat Author notes 1 This work was supported by the National Key R&D Program of China Grant (2019YFA0903903), the National Natural Science Foundation of China (31871234 to J.Z.), the Program for Guangdong Introducing Innovative and Entrepreneurial Teams (2016ZT06S172), and the Shenzhen Sci-Tech Fund (KYTDPT20181011104005). [OPEN] Articles can be viewed without a subscription. 2 These authors contributed equally to this article. 4 Senior author. The author responsible for distribution of materials integral to the findings presented in this article in accordance with the policy described in the Instructions for Authors (www.plantphysiol.org) is: Jixian Zhai ([email protected]). J.Z. and B.C.M. conceived the original research plan; J.Z. supervised the analysis; L.F. collected and processed publicly available sRNA-seq data; L.F., H.Z. and Y.Z. analyzed sRNA-seq data; L.F. and F.Z. built the database and website; L.F. wrote the article; all authors revised the article. www.plantphysiol.org/cgi/doi/10.1104/pp.19.00959 © 2020 American Society of Plant Biologists. All Rights Reserved. © The Author(s) 2020. Published by Oxford University Press on behalf of American Society of Plant Biologists. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
Rapid Single-Step Affinity Purification of HA-Tagged Plant Mitochondria Kuhnert, Franziska; Stefanski, Anja; Overbeck, Nina; Drews, Leonie; Reichert, Andreas S.; Stühler, Kai; Weber, Andreas P.M.
doi: 10.1104/pp.19.00732pmid: 31818904
Abstract Photosynthesis in plant cells would not be possible without the supportive role of mitochondria. However, isolating mitochondria from plant cells for physiological and biochemical analyses is a lengthy and tedious process. Established isolation protocols require multiple centrifugation steps and substantial amounts of starting material. To overcome these limitations, we tagged mitochondria in Arabidopsis (Arabidopsis thaliana) with a triple hemagglutinin tag for rapid purification via a single affinity-purification step. This protocol yields a substantial quantity of highly pure mitochondria from 1 g of Arabidopsis seedlings. The purified mitochondria were suitable for enzyme activity analyses and yielded sufficient amounts of proteins for deep proteomic profiling. We applied this method for the proteomic analysis of the Arabidopsis bou-2 mutant deficient in the mitochondrial Glu transporter À BOUT DE SOUFFLE (BOU) and identified 27 differentially expressed mitochondrial proteins compared with tagged Col-0 controls. Our work sets the stage for the development of advanced mitochondria isolation protocols for distinct cell types. In all eukaryotic organisms, mitochondria are the major source of ATP, which is produced via the oxidative phosphorylation (OXPHOS) pathway, thus playing a vital role in cellular energy metabolism. Mitochondria also participate in amino acid metabolism as well as in photorespiration in photosynthetic eukaryotes. Analysis of the biochemical and physiological functions of mitochondria frequently requires the isolation of intact mitochondria. Mitochondria can be isolated from leaf tissue in less than 1 h by differential centrifugation. This method yields mitochondria with good integrity and appropriate enzyme activity; however, mitochondria are frequently contaminated with plastids and peroxisomes. Hence, in many cases, a combination of differential centrifugation and Percoll density gradient is used (Millar et al., 2001; Werhahn et al., 2001; Keech et al., 2005). Whereas this produces a pure fraction of respiratory active mitochondria with low plastid and peroxisome contamination, such procedures generally take several hours and require up to 50 g of starting material for producing sufficient yields (Keech et al., 2005). Moreover, traditional protocols are not practical for the isolation of mitochondria from mutants with severely impaired growth or from less-abundant tissue types such as flowers and for the analysis of mitochondrial metabolites. Furthermore, media used for the isolation of mitochondria typically contain high concentrations of sugars and other metabolites that can potentially interfere with mass spectrometry (MS)-based metabolite analyses. Recently, Chen and coworkers reported a method for the rapid isolation of mitochondria from human HeLa cell cultures via coimmunopurification (co-IP; Chen et al., 2016). The authors generated transgenic HeLa cell lines expressing a triple hemagglutinin (HA)-tagged enhanced GFP (eGFP) fused to the outer mitochondrial membrane (OMM) localization sequence of OMP25 (3×HA-eGFP-OMP25). Because the epitope tag was displayed on the surface of mitochondria, these transfected cell lines could be used to rapidly enrich mitochondria after cell homogenization. The HA-tagged mitochondria were captured and pulled down using magnetic beads coated with an anti-HA-tag antibody. Given the small size (1-µm diameter) and nonporous behavior of anti-HA-tag beads, these beads performed better than the porous agarose matrix for the enrichment of mitochondria. Thus, the authors established a method that ensures a high yield of pure mitochondria in approximately 12 min. The isolated mitochondria showed high purity, integrity, and functionality. Additionally, the authors developed a simple potassium-based buffer system that maintains mitochondrial intactness and is compatible with downstream analyses, such as metabolite analysis by liquid chromatography (LC)/MS (Chen et al., 2016). Photorespiration plays a crucial role in photosynthesis by detoxifying 2-phosphoglycolate, which is produced by the oxygenation of Rubisco and acts as an inhibitor of several plastidial enzymes (Ogren and Bowes, 1971; Kelly and Latzko, 1976; Husic et al., 1987). Plants reclaim 2-phosphoglycolate in the complex pathway of photorespiration, yielding 3-phosphoglycerate, which is returned to the Calvin Benson cycle. The photorespiratory pathway includes several enzymatic steps that occur in four subcellular compartments: plastids, peroxisomes, mitochondria, and the cytosol (Eisenhut et al., 2019). Knockout mutants of genes encoding enzymes and transporters involved in photorespiration often show a photorespiratory phenotype, characterized by chlorotic leaves and growth inhibition under ambient carbon dioxide (CO2) conditions, which can be rescued in a CO2-enriched environment (Peterhansel et al., 2010). A key step in photorespiration is the conversion of two Gly molecules into one Ser residue in the mitochondrial matrix, accompanied by the release of CO2 and ammonia. This step is catalyzed by the Gly decarboxylase (GDC) multienzyme system, comprising the P-protein (GLDP), H-protein (GDCH), L-protein (GDCL), and T-protein (GLDT), in combination with Ser hydroxymethyltransferase (SHM; Voll et al., 2006; Engel et al., 2007). In green tissues, these proteins constitute up to 50% of the total protein content of the mitochondrial matrix, indicating the importance of Gly oxidation in mitochondria (Oliver et al., 1990). The Arabidopsis (Arabidopsis thaliana) bou-2 mutant was previously identified as lacking the mitochondrial Glu transporter À BOUT DE SOUFFLE (BOU), which is involved in photorespiration (Eisenhut et al., 2013; Porcelli et al., 2018). Plants lacking the inner mitochondrial membrane (IMM) protein BOU show a pronounced photorespiratory phenotype under ambient CO2 conditions, significantly elevated CO2 compensation point, and highly reduced GDC activity in the isolated mitochondria (Eisenhut et al., 2013). Because BOU is coexpressed with genes encoding components of the GDC complex and the bou-2 mutant shows a similar metabolic phenotype as the shm1 mutant, it was hypothesized that BOU transports a metabolite necessary for the proper functioning of GDC (Voll et al., 2006; Eisenhut et al., 2013). Recently, it was demonstrated that heterologously expressed BOU functions as a Glu transporter (Porcelli et al., 2018). Glu is neither a substrate nor a product of the reaction catalyzed by GDC. Besides its role in amino acid and nitrogen metabolism, Glu is necessary for the glutamylation of tetrahydrofolate (THF), a cofactor of GLDT and SHM (Suh et al., 2001). Glutamylation of THF increases its stability. Moreover, THF-dependent enzymes generally prefer polyglutamylated folates over monoglutamylated folates as a substrate (Suh et al., 2001). However, because (1) BOU is not the only Glu transporter in mitochondria, and (2) glutamylation of folates is not restricted to mitochondria, the exact physiological function of BOU remains unclear (Hanson and Gregory, 2011; Monné et al., 2018). Notably, a Glu/Gln shuttle across the mitochondrial membrane was previously suggested to support the reclamation of ammonia released during photorespiration (Linka and Weber, 2005). Building on the previous work of Chen et al. (2016), we developed an affinity-tagging strategy for the rapid isolation of mitochondria from Arabidopsis. We generated transgenic Arabidopsis lines carrying an HA-tagged TRANSLOCASE OF THE OMM5 (TOM5) and isolated highly pure and intact mitochondria from these lines in less than 25 min. The isolated mitochondria were successfully subjected to proteomics and enzyme activity analyses. Moreover, we applied the isolation strategy to the bou-2 mutant, revealing differential protein abundance and enzyme activities. RESULTS Identification of TOM5 as a Suitable Anchor Peptide and Generation of Affinity-Tagged Arabidopsis Lines Recently, Chen et al. (2016) reported a rapid protocol for the isolation of intact mitochondria from transgenic HeLa cells expressing the mitochondrial fusion protein 3×HA-eGFP-OMP25 using co-IP. The Arabidopsis genome does not encode an ortholog of OMP25. Therefore, we screened the available Arabidopsis mitochondrial proteome data, including the OMM proteins with known topology and function, and identified TOM5 as a potential candidate for our mitochondria affinity-tagging approach. Together with TOM6, TOM7, TOM20, TOM22/9, and TOM40, TOM5 forms the protein import apparatus of plant mitochondria (Werhahn et al., 2003). In yeast (Saccharomyces cerevisiae), TOM5 is an integral protein of the OMM. It has a negatively charged N-terminal domain, which faces toward the cytosol (Dietmeier et al., 1997) and can be fused to GFP without altering the subcellular localization of TOM5 (Horie et al., 2003). The protein import machinery is well conserved among eukaryotes. The predicted N-terminal cytosolic domain of Arabidopsis TOM5 is necessary for the recognition of cytosolically synthesized mitochondrial preproteins (Wiedemann et al., 2004). Therefore, we generated an N-terminal translational fusion of the Arabidopsis TOM5 gene with the triple HA-tagged synthetic GFP (sGFP) gene under the control of the Arabidopsis UBIQUITIN10 promoter (UB10p; UB10p-3×HA-sGFP-TOM5; Supplemental Fig. S1). The construct was used to stably transform Arabidopsis ecotype Columbia (Col-0) and bou-2 mutant. Expression and localization of the fusion protein was verified in root and leaf tissues of 10-d-old Arabidopsis seedlings via confocal laser scanning microscopy. Arabidopsis lines expressing the 3×HA-sGFP-TOM5 protein in leaf and root mitochondria of Col-0 (tagged Col-0) and bou-2 (tagged bou-2) seedlings were identified based on the colocalization of the fluorescent signal of GFP signal with that of the mitochondrial marker CMXRos (Fig. 1). CMXRos is a lipophilic cationic dye that accumulates in the mitochondria because of the negative membrane potential; thus, it solely stains mitochondria with an intact respiratory chain (Pendergrass et al., 2004). Because the fluorescent signals of the 3×HA-sGFP-TOM5 protein (green) fully overlapped with those of the MitoTracker (red), we conclude that overexpression of the UB10p-3×HA-sGFP-TOM5 construct in Col-0 and bou-2 does not affect mitochondrial intactness. Notably, tagged Col-0 or bou-2 lines showed no apparent phenotypic differences compared with nontagged Col-0 or bou-2 plants (control), respectively, under our culture conditions (Supplemental Fig. S2). Figure 1. Open in new tabDownload slide Confocal microscopy of epitope-tagged mitochondria in leaf and root tissues of 10-d-old Arabidopsis Col-0 and bou-2 lines expressing the UB10p-3×HA-sGFP-TOM5 construct. A to D, Images of tagged Col-0 leaf (A) and root (B) tissues and tagged bou-2 leaf (C) and root (D) tissues expressing the 3×HA-sGFP-TOM5 protein. Pictures were taken of the epidermal layer of the first leaf pair (A and C) and the epidermal and cortex layer of the main root (B and D). Green color represents GFP signal, whereas red color represents the signal of mitochondrial marker MitoTracker red CMXRos. Bright field is shown in gray and merged images are shown in yellow. Scale bars = 10 µm. Figure 1. Open in new tabDownload slide Confocal microscopy of epitope-tagged mitochondria in leaf and root tissues of 10-d-old Arabidopsis Col-0 and bou-2 lines expressing the UB10p-3×HA-sGFP-TOM5 construct. A to D, Images of tagged Col-0 leaf (A) and root (B) tissues and tagged bou-2 leaf (C) and root (D) tissues expressing the 3×HA-sGFP-TOM5 protein. Pictures were taken of the epidermal layer of the first leaf pair (A and C) and the epidermal and cortex layer of the main root (B and D). Green color represents GFP signal, whereas red color represents the signal of mitochondrial marker MitoTracker red CMXRos. Bright field is shown in gray and merged images are shown in yellow. Scale bars = 10 µm. Affinity-Based Purification of Intact Mitochondria Tagged Col-0 and bou-2 lines were used for the isolation of intact HA-tagged mitochondria via co-IP using magnetic anti-HA beads. We chose HA as the epitope tag for purification because it has a high affinity for its cognate antibody, and Chen and coworkers previously demonstrated that the size and nonporous behavior of the anti-HA beads yields a high amount of mitochondria (Chen et al., 2016). Additionally, we used the LC/MS-compatible buffer containing KCl and KH2PO4 (KPBS) developed by Chen et al. (2016). Our purification procedure included five steps: homogenization of plant material in KPBS (1 min), filtration of the homogenate (1 min), two centrifugation steps (5 and 9 min), and co-IP (7 min, including washing steps). All together, mitochondria were purified from plant material in less than 25 min (Fig. 2). If the first low-speed centrifugation step used to remove contaminating chloroplasts and cell debris is omitted, the isolation time can be reduced to 18 min. The purified mitochondria were verified by immunoblot analyses using known organelle-specific protein markers. Mitochondria were enriched via co-IP only from lines harboring the mitochondrial 3×HA-sGFP-TOM5 protein (tagged line), as demonstrated by immunoblot analyses with antibodies directed against different mitochondrial marker proteins including isocitrate dehydrogenase (IDH; mitochondrial matrix), alternative oxidase 1/2 (AOX1/2; IMM), and voltage-dependent anion channel1 (VDAC1; OMM). No enrichment of mitochondria was observed in control Col-0 lines, indicating that the beads bind specifically to the HA-tag on mitochondria in tagged lines (Fig. 3; Supplemental Fig. S3A). Comparison with classical mitochondria isolation protocols using differential centrifugation and density gradient purification revealed that the mitochondrial fraction enriched using our affinity-tagging method showed significantly less contamination with proteins from plastids, peroxisomes, the endoplasmic reticulum (ER), nuclei, and the cytosol (Fig. 3; Supplemental Fig. S3B). The following proteins were used as markers for different organelles: Rubisco large subunit (RbcL; plastid), catalase (Cat; peroxisome), lumenal-binding protein2 (BiP2; ER), histone H3 (nucleus), and heat shock cognate protein70 (HSC70; cytosol). Contamination with thylakoids, which are a major contaminant of leaf mitochondria, was assessed by determining the chlorophyll-to-protein ratio of isolated mitochondria. Rapidly enriched mitochondria show minor contamination by thylakoids (0.18 ± 0.08 µg Chl mg−1 protein). The here-presented chlorophyll-to-protein ratio is 2-fold lower compared to classical mitochondria isolations (0.34 ± 0.08 µg Chl mg−1 protein; Keech et al., 2005). Figure 2. Open in new tabDownload slide Workflow showing the rapid isolation of epitope-tagged mitochondria via co-IP from Arabidopsis. Tagged lines harboring the UB10p-3×HA-sGFP-TOM5 construct were harvested and homogenized in a Warren blender. The extract was filtered and centrifuged to obtain a crude mitochondrial fraction. Epitope-tagged mitochondria were purified via co-IP using 50–250 µL magnetic anti-HA beads. The purified mitochondria were washed and either lysed for immunoblot analysis or extracted for proteomics. As a control, nontagged Col-0 was used. Figure 2. Open in new tabDownload slide Workflow showing the rapid isolation of epitope-tagged mitochondria via co-IP from Arabidopsis. Tagged lines harboring the UB10p-3×HA-sGFP-TOM5 construct were harvested and homogenized in a Warren blender. The extract was filtered and centrifuged to obtain a crude mitochondrial fraction. Epitope-tagged mitochondria were purified via co-IP using 50–250 µL magnetic anti-HA beads. The purified mitochondria were washed and either lysed for immunoblot analysis or extracted for proteomics. As a control, nontagged Col-0 was used. Figure 3. Open in new tabDownload slide Assessment of the contamination of enriched mitochondria via co-IP or classical methods. Mitochondria isolations were performed on 10-d-old Col-0 and tagged Col-0 lines via co-IP using 150 µL magnetic anti-HA beads or on 10-d-old Col-0 via classical methods using differential centrifugation and gradient purification. Samples were taken after tissue homogenization (whole cell, extract), enrichment of mitochondria via co-IP (anti-HA-IP), differential centrifugation (DC), and density gradient purification (purified). Protein amounts were loaded as described in the “Materials and Methods.” Names of organelle marker proteins are shown on the left side of the blots, and their subcellular localization is indicated on the right. Figure 3. Open in new tabDownload slide Assessment of the contamination of enriched mitochondria via co-IP or classical methods. Mitochondria isolations were performed on 10-d-old Col-0 and tagged Col-0 lines via co-IP using 150 µL magnetic anti-HA beads or on 10-d-old Col-0 via classical methods using differential centrifugation and gradient purification. Samples were taken after tissue homogenization (whole cell, extract), enrichment of mitochondria via co-IP (anti-HA-IP), differential centrifugation (DC), and density gradient purification (purified). Protein amounts were loaded as described in the “Materials and Methods.” Names of organelle marker proteins are shown on the left side of the blots, and their subcellular localization is indicated on the right. The intactness of mitochondria isolated from HA-tagged lines via co-IP was assessed based on respiratory measurements with the Seahorse Analyzer, the latency of malate dehydrogenase (MDH) activity, and mitochondrial staining with the mitochondrial marker CMXRos (Fig. 4). Mitochondria isolated with our affinity-tagging approach showed respiratory coupling with succinate as substrate. Respiration is inhibited by the respiratory chain inhibitor Antimycin A. Addition of the complex III inhibitor lead to a significant reduction of the oxygen consumption rate in the mitochondria but not the control samples (Fig. 4A). Intactness and activity was further verified by latency experiments with MDH. Activity of MDH was only present in detergent-treated samples containing enriched mitochondria but not the control or nontreated samples, indicating intactness of the OMM and IMM (Fig. 4B). Moreover, affinity-purified mitochondria retained the mitochondrial marker CMXRos that solely stains mitochondria with an active respiratory chain (Fig. 4C; Pendergrass et al., 2004). Figure 4. Open in new tabDownload slide Intactness of rapidly enriched mitochondria isolated from 10-d-old tagged Col-0 lines via co-IP. Oxygen consumption rates (OCR) of purified mitochondria bound to magnetic anti-HA beads were measured using the Seahorse XFe96 Analyzer as described in the “Materials and Methods” (A). OCR were measured in the presence (black boxes) or absence (blue boxes) of the respiratory chain inhibitor antimycin A and before (b.i.) and after (a.i.) injection of antimycin A. Control (gray boxes) did not contain mitochondria. Data are shown in box and whiskers (min to max) of means of two (mitochondria + antimycin A, control) and three biological replicates (mitochondria). Different letters indicate statistically significant differences between means (P < 0.05; two-way ANOVA). Latency of malate dehydrogenase (MDH) activity was measured as described in the “Materials and Methods” (B). As control isolations were performed on Col-0 lines. Data represent mean ± sd of three biological replicates (each four technical replicates). Different letters indicate statistically significant differences between means (P < 0.05; one-way ANOVA). Purified mitochondria retain the mitochondrial marker MitoTracker red CMXRos that is able to stain mitochondria with an active membrane potential (C). Staining experiments were performed as described in the “Materials and Methods.” As control isolations were performed on Col-0 lines. Data represent mean ± sd of three biological replicates (each four technical replicates). Asterisks indicate statistically significant differences (***P < 0.001; Student’s t test). Figure 4. Open in new tabDownload slide Intactness of rapidly enriched mitochondria isolated from 10-d-old tagged Col-0 lines via co-IP. Oxygen consumption rates (OCR) of purified mitochondria bound to magnetic anti-HA beads were measured using the Seahorse XFe96 Analyzer as described in the “Materials and Methods” (A). OCR were measured in the presence (black boxes) or absence (blue boxes) of the respiratory chain inhibitor antimycin A and before (b.i.) and after (a.i.) injection of antimycin A. Control (gray boxes) did not contain mitochondria. Data are shown in box and whiskers (min to max) of means of two (mitochondria + antimycin A, control) and three biological replicates (mitochondria). Different letters indicate statistically significant differences between means (P < 0.05; two-way ANOVA). Latency of malate dehydrogenase (MDH) activity was measured as described in the “Materials and Methods” (B). As control isolations were performed on Col-0 lines. Data represent mean ± sd of three biological replicates (each four technical replicates). Different letters indicate statistically significant differences between means (P < 0.05; one-way ANOVA). Purified mitochondria retain the mitochondrial marker MitoTracker red CMXRos that is able to stain mitochondria with an active membrane potential (C). Staining experiments were performed as described in the “Materials and Methods.” As control isolations were performed on Col-0 lines. Data represent mean ± sd of three biological replicates (each four technical replicates). Asterisks indicate statistically significant differences (***P < 0.001; Student’s t test). Typically, we used 5–10 g of Arabidopsis seedlings grown on agar plates for the isolation of mitochondria, and this yielded 400–700 µg of total mitochondrial protein. However, mitochondria could also be isolated from 1 g of starting material, yielding 50–200 µg of total mitochondrial protein. This is advantageous for very young seedlings or mutants with severely impaired growth. Isolation from less than 1 g of starting material may also result in an appropriate yield of mitochondria, but this was not tested in this study. We found that recovery of mitochondria with our method was 7.1% ± 3.3%. Taken together, our data indicate that mitochondria can be rapidly isolated via co-IP using a simple LC/MS-compatible buffer. Enzyme Assays Using Mitochondria Affinity Purified from Tagged Col-0 and bou-2 Mutant Lines We used our rapid mitochondria isolation method to study the effect of the mitochondrial carrier protein BOU on mitochondrial metabolism in Arabidopsis. To assess the effect of the bou-2 mutant allele on mitochondrial metabolism, we rapidly isolated mitochondria from 10-d-old tagged Col-0 and bou-2 seedlings grown under elevated CO2 conditions (0.3%) and seedlings sampled 5 d after shift to ambient CO2 conditions (0.038% CO2), with three independent biological replicates included for each treatment. Mitochondria were lysed and used to measure the activity of MDH, Asp aminotransferase (AspAT), Glu dehydrogenase (GluDH), Ala aminotransferase (AlaAT), γ-aminobutyric acid transaminase (GABA-T), and formate dehydrogenase (FDH). Enzyme activities were calculated from the initial slopes. Enzyme activities in tagged bou-2 mutant lines were compared with those in tagged Col-0 lines, which were set to 100% for both experimental conditions. The activities of MDH and FDH were not affected in tagged bou-2 mutant lines under any of the conditions tested (Fig. 5, A and B). The activities of AspAT and GABA-T in tagged mutant lines were similar to those in tagged Col-0 lines, when mitochondria were isolated from seedlings grown under elevated CO2 conditions, but were significantly reduced in tagged mutant lines after the shift to ambient CO2 conditions (Fig. 5, C and D). The activity of AlaAT was significantly reduced (Fig. 5E), whereas that of GluDH was significantly increased in tagged mutant lines under elevated CO2 conditions; however, enzyme activity of the latter reverted back to the levels in tagged Col-0 when seedlings were shifted to ambient CO2 conditions (Fig. 5F). Together, our results suggest a possible involvement of BOU in mitochondrial amino acid and nitrogen metabolism. Figure 5. Open in new tabDownload slide Characterization of enzyme activities in mitochondria isolated via co-IP from 10-d-old tagged Col-0 and bou-2 lines. Plants were sampled following growth under 0.3% CO2 (HC) and 5 d after shift to 0.038% CO2 (5 d LC). A, Malate dehydrogenase (MDH) activity. Average tagged Col-0 activity: 38.2 ± 1.5 µmol min−1 mg−1 (HC), 49.4 ± 1.5. µmol min−1 mg−1 (5 d LC). B, Formate dehydrogenase (FDH) activity. Average tagged Col-0 activity: 17.8 ± 0.5 nmol min−1 mg−1 (HC), 33.6 ± 1.5 nmol min−1 mg−1 (5 d LC). C, Asp aminotransferase (AspAT) activity. Average tagged Col-0 activity: 4.31 ± 0.08 µmol min−1 mg−1 (HC), 3.74 ± 0.01 µmol min−1 mg−1 (5 d LC). D, γ-aminobutyric acid transaminase (GABA-T) activity. Average tagged Col-0 activity: 96.2 ± 4.3 nmol min−1 mg−1 (HC), 137.4 ± 1.0 nmol min−1 mg−1 (5 d LC). E, Ala aminotransferase (AlaAT) activity. Average tagged Col-0 activity: 0.92 ± 0.02 µmol min−1 mg−1 (HC), 0.75 ± 0.04 µmol min−1 mg−1 (5 d LC). F, Glu dehydrogenase (GluDH) activity. Average tagged Col-0 activity: 0.83 ± 0.05 µmol min−1 mg−1 (HC), 2.03 ± 0.04 µmol min−1 mg−1 (5 d LC). Activities were calculated from initial slopes. Enzyme activities in tagged Col-0 grown under elevated CO2 conditions and 5 d after shift to ambient CO2 conditions were each set to 100%. Data represent mean ± sd of three biological replicates (each four technical replicates). Different letters indicate statistically significant differences between means for each enzyme (P < 0.05; one-way ANOVA). WT, wild type. Figure 5. Open in new tabDownload slide Characterization of enzyme activities in mitochondria isolated via co-IP from 10-d-old tagged Col-0 and bou-2 lines. Plants were sampled following growth under 0.3% CO2 (HC) and 5 d after shift to 0.038% CO2 (5 d LC). A, Malate dehydrogenase (MDH) activity. Average tagged Col-0 activity: 38.2 ± 1.5 µmol min−1 mg−1 (HC), 49.4 ± 1.5. µmol min−1 mg−1 (5 d LC). B, Formate dehydrogenase (FDH) activity. Average tagged Col-0 activity: 17.8 ± 0.5 nmol min−1 mg−1 (HC), 33.6 ± 1.5 nmol min−1 mg−1 (5 d LC). C, Asp aminotransferase (AspAT) activity. Average tagged Col-0 activity: 4.31 ± 0.08 µmol min−1 mg−1 (HC), 3.74 ± 0.01 µmol min−1 mg−1 (5 d LC). D, γ-aminobutyric acid transaminase (GABA-T) activity. Average tagged Col-0 activity: 96.2 ± 4.3 nmol min−1 mg−1 (HC), 137.4 ± 1.0 nmol min−1 mg−1 (5 d LC). E, Ala aminotransferase (AlaAT) activity. Average tagged Col-0 activity: 0.92 ± 0.02 µmol min−1 mg−1 (HC), 0.75 ± 0.04 µmol min−1 mg−1 (5 d LC). F, Glu dehydrogenase (GluDH) activity. Average tagged Col-0 activity: 0.83 ± 0.05 µmol min−1 mg−1 (HC), 2.03 ± 0.04 µmol min−1 mg−1 (5 d LC). Activities were calculated from initial slopes. Enzyme activities in tagged Col-0 grown under elevated CO2 conditions and 5 d after shift to ambient CO2 conditions were each set to 100%. Data represent mean ± sd of three biological replicates (each four technical replicates). Different letters indicate statistically significant differences between means for each enzyme (P < 0.05; one-way ANOVA). WT, wild type. In addition, we found that the activity of MDH was strongly reduced in 4-week-old tagged bou-2 mutant plants (Supplemental Fig. S4). However, no change was observed in MDH activity in 10-d-old tagged bou-2 plants, suggesting pleiotropic effects in older leaf tissues due to accumulating photorespiratory intermediates. Proteomic Analysis of Mitochondria Affinity Purified from Tagged Col-0 and bou-2 Mutant Lines Mitochondria were isolated from 10-d-old tagged Col-0 and bou-2 seedlings grown under elevated CO2 conditions, with four independent biological replicates included. Proteome analysis of the isolated mitochondria revealed 15,688 peptides belonging to 1240 proteins present in at least three of the four replicates (Supplemental Tables S1 and S2). Subcellular localization of the quantified proteins was annotated using the SUBAcon database (Hooper et al., 2017). Summing up the label-free quantitation intensities of the spectra showed that 80% of the identified proteins in our study resulted from proteins localized or predicted to be localized to the mitochondria, 11.5% from plastid-localized proteins, and 5.7% from proteins with no clear subcellular localization (designated as ambiguous). If we apply the evaluation on all quantified peptides in this study, more than 90% of all identified peptides were assigned to mitochondria-localized proteins. Contamination of the mitochondrial proteins by proteins from peroxisomes, the ER, the Golgi, vacuoles, endomembranes, plasma membranes, nuclei, and the cytosol was less than 1% each (Supplemental Tables S1 and S2). These results indicate high purity of the rapidly isolated mitochondria, which was comparable with the purity of classically isolated mitochondria (Klodmann et al., 2011; Senkler et al., 2017). Next, we compared our proteome data with previous proteomic analyses and quantified proteins and some of the subunits of known mitochondrial complexes (Supplemental Tables S1 and S2). The OXPHOS pathway of mitochondria consists of five protein complexes (I–V) located in the IMM. Complexes I to IV represent oxidoreductases, which comprise the respiratory chain that regenerates oxidized forms of cofactors involved in mitochondrial metabolism, thereby creating an electron flow. This leads to the simultaneous export of protons into the intermembrane space (IMS). The built-up proton gradient is used by complex V to generate ATP. Complex I is the largest complex involved in the OXPHOS pathway and comprises at least 47 protein subunits that form the so-called membrane and peripheral arms (Peters et al., 2013; Meyer et al., 2019). Except NDUA1, NDUB2, Nad4L, and Nad6 (At3g08610, At1g76200, AtMg00650, and AtMg00270, respectively), we could identify all complex I subunits in our proteomic data set, including eight previously proposed assembly factors (Meyer et al., 2019), five γ-carbonic anhydrases, and five additional proteins proposed to form a matrix-exposed domain attached to complex I (Sunderhaus et al., 2006). In addition to its function in the OXPHOS pathway, complex II also participates in the tricarboxylic acid cycle (TCA). Six out of eight subunits of complex II (Millar et al., 2004) and the assembly factor SDHAF2 were identified in our data set. Additionally, peptides of all proteins and isoforms of complex III as well as eight of its assembly factors (Meyer et al., 2019) were identified in our data set. The cytochrome c oxidase complex (complex IV) consists of 16 proposed subunits in Arabidopsis (Mansilla et al., 2018). Of these, nine subunits and 11 assembly factors of complex IV were identified in our proteomic data set. Complex V consists of 15 subunits, of which 13 were identified in our proteomic data set; Atp6 (AtMg00410 and AtMg011701) and Atp9 (AtMg01080) were the only two subunits that could not be identified. In addition, we found three of the five proposed assembly factors (Meyer et al., 2019). Furthermore, we identified three proteins involved in the assembly of OXPHOS supercomplexes as well as alternative NADPH dehydrogenases and alternative oxidases that have previously been defined as alternative pathways (Meyer et al., 2019). Except for the abovementioned subunits of the SDH complex, all proteins of the TCA cycle, including the pyruvate dehydrogenase complex, and the GDC multienzyme system were identified in the rapidly isolated mitochondria. Additionally, our proteomic data set contained a number of pentatricopeptide and tetratricopeptide repeat proteins involved in RNA metabolism as well as heat shock proteins and ribosomal proteins involved in protein control and turnover (Supplemental Table S1 and S2). In Arabidopsis, the majority of mitochondrial proteins are encoded by nuclear genes, translated in the cytosol, and then imported into the mitochondria. The import and sorting of nuclear-encoded mitochondrial preproteins requires functional TOM and sorting and assembly machinery in the OMM, mitochondrial IMS import and assembly machinery in the IMS, and translocase of the IMM in the IMM (Murcha et al., 2014). In this study, we identified all proteins necessary for functional protein import into mitochondria in our proteome data set, except for the OMM protein TOM6, IMS protein ERV1, IMM protein PRAT5, and matrix proteins MGE1 and ZIM17. Additionally, we identified plant-specific import components, including OM64, PRAT3, and PRAT4 in the OMM (Murcha et al., 2015), and plant homologs to proteins of the mitochondrial contact site and cristae organizing system (MICOS), which connects the IMM to OMM (van der Laan et al., 2016). Other notable OMM proteins identified in our proteomic data set included GTPases MIRO1 and MIRO2, lipid biosynthesis protein PECT, and β-barrel proteins VDAC1to VDAC4 (Supplemental Table S1 and S2). Recently, it was shown that the cytosolic protein GAPC interacts with VDAC (Schneider et al., 2018); we also identified GAPC in our proteomic data set. Overall, we conclude that mitochondria isolated using our rapid isolation method are suitable for proteomic analyses. Differential Analysis of the Mitochondrial Proteome of Tagged Col-0 and bou-2 Lines To assess the effect of bou-2 mutation on the mitochondrial proteome, we performed comparative proteomic analysis of tagged Col-0 and bou-2 lines. A total of 47 proteins showed significantly increased abundance in the mutant, of which five were localized to the mitochondria. Additionally, 44 proteins showed significantly decreased abundance in the tagged bou-2 samples, of which 22 were predicted to be localized to the mitochondria (Table 1); among these proteins, BOU was the least abundant. The bou-2 line is a GABI-Kat line that carries a T-DNA insertion in the second exon of the BOU gene (Kleinboelting et al., 2012; Eisenhut et al., 2013). We identified two peptides of BOU in at least three of the four replicates of tagged bou-2 samples. Both peptides were translated from the first exon of the gene. Because the T-DNA was inserted in the second exon of the gene, it is possible that the first exon was translated. However, a functional protein is not synthesized in the knockout mutant (Eisenhut et al., 2013). Among the mitochondrial proteins showing significantly reduced abundance in tagged bou-2 seedlings, we identified six proteins of the OXPHOS pathway (three complex I proteins and one protein each of complexes II, III, and V), two proteins involved in protein translocation, two proteins involved in metabolite transport, two proteins involved in lipid metabolism, three proteins involved in protein turnover/synthesis, one protein involved in the TCA cycle, and six proteins (including FDH) involved in other processes. Among the proteins with significantly increased abundance in tagged bou-2 mutant, we identified two proteins involved in RNA/DNA metabolism, one protein involved in THF metabolism, one MIRO-related GTPase, and one LETM1-like protein (Table 1). List of signal changes for proteins showing significant differences in protein abundance between 10-d-old Col-0 UB10p-3×HA-sGFP-TOM5 and bou-2 UB10p-3×HA-sGFP-TOM5 Table 1. List of signal changes for proteins showing significant differences in protein abundance between 10-d-old Col-0 UB10p-3×HA-sGFP-TOM5 and bou-2 UB10p-3×HA-sGFP-TOM5 Difference was calculated as change of log2 of normalized intensity. List includes only proteins that show mitochondrial localization. List ranges from most downregulated in bou-2 UB10p-3×HA-sGFP-TOM5 (top) to most upregulated bou-2 UB10p-3×HA-sGFP-TOM5 (bottom). Significance was calculated with Student’s t test, *P < 0.05, ** P < 0.01, *** P < 0.001. AGI . Gene Symbol . Gene Description . Difference . Significance . AT5G46800 BOU Mitochondrial substrate carrier family protein −8.66407 *** AT2G42310 AT2G42310 ESSS subunit of NADH:ubiquinone oxidoreductase (complex I) protein −2.0953 * AT5G41685 AT5G41685 Mitochondrial outer membrane translocase complex, subunit Tom7 −1.90711 ** AT3G03100 AT3G03100 NADH:ubiquinone oxidoreductase, 17.2-kDa subunit −1.33356 * AT5G53650 AT5G53650 ABC transporter A family protein −1.25252 * AT5G67590 FRO1 NADH-ubiquinone oxidoreductase-like protein −1.0968 * AT5G40810 AT5G40810 Cytochrome C1 family −1.06444 * AT3G27280 PHB4 Prohibitin 4 −0.94888 * AT3G27380 SDH2-1 Succinate dehydrogenase 2-1 −0.764682 * AT4G37660 AT4G37660 Ribosomal protein L12/ATP-dependent Clp protease adaptor protein ClpS family protein −0.732468 * AT2G42210 OEP16-3 Mitochondrial import inner membrane translocase subunit Tim17/Tim22/Tim23 family protein −0.710023 * AT3G55400 OVA1 Methionyl-tRNA synthetase/Met-tRNA ligase/MetRS (cpMetRS) −0.705525 * AT5G14780 FDH Formate dehydrogenase −0.697987 ** AT2G38670 PECT1 Phosphorylethanolamine cytidylyltransferase 1 −0.606253 * AT5G63400 ADK1 Adenylate kinase 1 −0.603703 * AT1G79230 MST1 Mercaptopyruvate sulfurtransferase 1 −0.587758 * AT4G30010 AT4G30010 ATP-dependent RNA helicase −0.545131 * AT3G03420 AT3G03420 Ku70-binding family protein −0.531796 ** AT4G31810 AT4G31810 ATP-dependent caseinolytic (Clp) protease/crotonase family protein −0.461768 * AT1G19140 AT1G19140 Ubiquinone biosynthesis COQ9-like protein −0.455841 * AT4G31460 AT4G31460 Ribosomal L28 family −0.430804 * AT1G54220 AT1G54220 Dihydrolipoamide acetyltransferase, long form protein −0.324755 * AT3G59820 LETM1 LETM1-like protein 0.42657 * AT5G27540 MIRO1 MIRO-related GTP-ase 1 0.447933 * AT3G10160 DFC DHFS-FPGS homolog C 0.507662 *** AT1G71260 ATWHY2 WHIRLY 2 0.51931 * AT5G15980 AT5G15980 Pentatricopeptide repeat (PPR) superfamily protein 0.8335 * AGI . Gene Symbol . Gene Description . Difference . Significance . AT5G46800 BOU Mitochondrial substrate carrier family protein −8.66407 *** AT2G42310 AT2G42310 ESSS subunit of NADH:ubiquinone oxidoreductase (complex I) protein −2.0953 * AT5G41685 AT5G41685 Mitochondrial outer membrane translocase complex, subunit Tom7 −1.90711 ** AT3G03100 AT3G03100 NADH:ubiquinone oxidoreductase, 17.2-kDa subunit −1.33356 * AT5G53650 AT5G53650 ABC transporter A family protein −1.25252 * AT5G67590 FRO1 NADH-ubiquinone oxidoreductase-like protein −1.0968 * AT5G40810 AT5G40810 Cytochrome C1 family −1.06444 * AT3G27280 PHB4 Prohibitin 4 −0.94888 * AT3G27380 SDH2-1 Succinate dehydrogenase 2-1 −0.764682 * AT4G37660 AT4G37660 Ribosomal protein L12/ATP-dependent Clp protease adaptor protein ClpS family protein −0.732468 * AT2G42210 OEP16-3 Mitochondrial import inner membrane translocase subunit Tim17/Tim22/Tim23 family protein −0.710023 * AT3G55400 OVA1 Methionyl-tRNA synthetase/Met-tRNA ligase/MetRS (cpMetRS) −0.705525 * AT5G14780 FDH Formate dehydrogenase −0.697987 ** AT2G38670 PECT1 Phosphorylethanolamine cytidylyltransferase 1 −0.606253 * AT5G63400 ADK1 Adenylate kinase 1 −0.603703 * AT1G79230 MST1 Mercaptopyruvate sulfurtransferase 1 −0.587758 * AT4G30010 AT4G30010 ATP-dependent RNA helicase −0.545131 * AT3G03420 AT3G03420 Ku70-binding family protein −0.531796 ** AT4G31810 AT4G31810 ATP-dependent caseinolytic (Clp) protease/crotonase family protein −0.461768 * AT1G19140 AT1G19140 Ubiquinone biosynthesis COQ9-like protein −0.455841 * AT4G31460 AT4G31460 Ribosomal L28 family −0.430804 * AT1G54220 AT1G54220 Dihydrolipoamide acetyltransferase, long form protein −0.324755 * AT3G59820 LETM1 LETM1-like protein 0.42657 * AT5G27540 MIRO1 MIRO-related GTP-ase 1 0.447933 * AT3G10160 DFC DHFS-FPGS homolog C 0.507662 *** AT1G71260 ATWHY2 WHIRLY 2 0.51931 * AT5G15980 AT5G15980 Pentatricopeptide repeat (PPR) superfamily protein 0.8335 * Open in new tab Table 1. List of signal changes for proteins showing significant differences in protein abundance between 10-d-old Col-0 UB10p-3×HA-sGFP-TOM5 and bou-2 UB10p-3×HA-sGFP-TOM5 Difference was calculated as change of log2 of normalized intensity. List includes only proteins that show mitochondrial localization. List ranges from most downregulated in bou-2 UB10p-3×HA-sGFP-TOM5 (top) to most upregulated bou-2 UB10p-3×HA-sGFP-TOM5 (bottom). Significance was calculated with Student’s t test, *P < 0.05, ** P < 0.01, *** P < 0.001. AGI . Gene Symbol . Gene Description . Difference . Significance . AT5G46800 BOU Mitochondrial substrate carrier family protein −8.66407 *** AT2G42310 AT2G42310 ESSS subunit of NADH:ubiquinone oxidoreductase (complex I) protein −2.0953 * AT5G41685 AT5G41685 Mitochondrial outer membrane translocase complex, subunit Tom7 −1.90711 ** AT3G03100 AT3G03100 NADH:ubiquinone oxidoreductase, 17.2-kDa subunit −1.33356 * AT5G53650 AT5G53650 ABC transporter A family protein −1.25252 * AT5G67590 FRO1 NADH-ubiquinone oxidoreductase-like protein −1.0968 * AT5G40810 AT5G40810 Cytochrome C1 family −1.06444 * AT3G27280 PHB4 Prohibitin 4 −0.94888 * AT3G27380 SDH2-1 Succinate dehydrogenase 2-1 −0.764682 * AT4G37660 AT4G37660 Ribosomal protein L12/ATP-dependent Clp protease adaptor protein ClpS family protein −0.732468 * AT2G42210 OEP16-3 Mitochondrial import inner membrane translocase subunit Tim17/Tim22/Tim23 family protein −0.710023 * AT3G55400 OVA1 Methionyl-tRNA synthetase/Met-tRNA ligase/MetRS (cpMetRS) −0.705525 * AT5G14780 FDH Formate dehydrogenase −0.697987 ** AT2G38670 PECT1 Phosphorylethanolamine cytidylyltransferase 1 −0.606253 * AT5G63400 ADK1 Adenylate kinase 1 −0.603703 * AT1G79230 MST1 Mercaptopyruvate sulfurtransferase 1 −0.587758 * AT4G30010 AT4G30010 ATP-dependent RNA helicase −0.545131 * AT3G03420 AT3G03420 Ku70-binding family protein −0.531796 ** AT4G31810 AT4G31810 ATP-dependent caseinolytic (Clp) protease/crotonase family protein −0.461768 * AT1G19140 AT1G19140 Ubiquinone biosynthesis COQ9-like protein −0.455841 * AT4G31460 AT4G31460 Ribosomal L28 family −0.430804 * AT1G54220 AT1G54220 Dihydrolipoamide acetyltransferase, long form protein −0.324755 * AT3G59820 LETM1 LETM1-like protein 0.42657 * AT5G27540 MIRO1 MIRO-related GTP-ase 1 0.447933 * AT3G10160 DFC DHFS-FPGS homolog C 0.507662 *** AT1G71260 ATWHY2 WHIRLY 2 0.51931 * AT5G15980 AT5G15980 Pentatricopeptide repeat (PPR) superfamily protein 0.8335 * AGI . Gene Symbol . Gene Description . Difference . Significance . AT5G46800 BOU Mitochondrial substrate carrier family protein −8.66407 *** AT2G42310 AT2G42310 ESSS subunit of NADH:ubiquinone oxidoreductase (complex I) protein −2.0953 * AT5G41685 AT5G41685 Mitochondrial outer membrane translocase complex, subunit Tom7 −1.90711 ** AT3G03100 AT3G03100 NADH:ubiquinone oxidoreductase, 17.2-kDa subunit −1.33356 * AT5G53650 AT5G53650 ABC transporter A family protein −1.25252 * AT5G67590 FRO1 NADH-ubiquinone oxidoreductase-like protein −1.0968 * AT5G40810 AT5G40810 Cytochrome C1 family −1.06444 * AT3G27280 PHB4 Prohibitin 4 −0.94888 * AT3G27380 SDH2-1 Succinate dehydrogenase 2-1 −0.764682 * AT4G37660 AT4G37660 Ribosomal protein L12/ATP-dependent Clp protease adaptor protein ClpS family protein −0.732468 * AT2G42210 OEP16-3 Mitochondrial import inner membrane translocase subunit Tim17/Tim22/Tim23 family protein −0.710023 * AT3G55400 OVA1 Methionyl-tRNA synthetase/Met-tRNA ligase/MetRS (cpMetRS) −0.705525 * AT5G14780 FDH Formate dehydrogenase −0.697987 ** AT2G38670 PECT1 Phosphorylethanolamine cytidylyltransferase 1 −0.606253 * AT5G63400 ADK1 Adenylate kinase 1 −0.603703 * AT1G79230 MST1 Mercaptopyruvate sulfurtransferase 1 −0.587758 * AT4G30010 AT4G30010 ATP-dependent RNA helicase −0.545131 * AT3G03420 AT3G03420 Ku70-binding family protein −0.531796 ** AT4G31810 AT4G31810 ATP-dependent caseinolytic (Clp) protease/crotonase family protein −0.461768 * AT1G19140 AT1G19140 Ubiquinone biosynthesis COQ9-like protein −0.455841 * AT4G31460 AT4G31460 Ribosomal L28 family −0.430804 * AT1G54220 AT1G54220 Dihydrolipoamide acetyltransferase, long form protein −0.324755 * AT3G59820 LETM1 LETM1-like protein 0.42657 * AT5G27540 MIRO1 MIRO-related GTP-ase 1 0.447933 * AT3G10160 DFC DHFS-FPGS homolog C 0.507662 *** AT1G71260 ATWHY2 WHIRLY 2 0.51931 * AT5G15980 AT5G15980 Pentatricopeptide repeat (PPR) superfamily protein 0.8335 * Open in new tab Previously, Eisenhut and colleagues showed that GDC activity is reduced in mitochondria isolated from 4-week-old bou-2 mutant plants (Eisenhut et al., 2013). The authors showed that the bou-2 mutant accumulated higher amounts of Gly than the wild type and exhibited differential amount and status of the P protein. Immunoblot analysis showed no differences in the levels of other GDC proteins in the bou-2 mutant compared with the wild type (Eisenhut et al., 2013). In our proteomic data set, none of the proteins of the GDC complex or SHMT showed significant differences between tagged Col-0 and bou-2 seedlings (Table 2). However, the amounts of GLDP1, GLDP2, GDCH1, GDCL1, GDCL2, and GLDT were slightly reduced, whereas those of SHM1, SHM2, and GDCH3 were increased in the tagged mutant compared with tagged Col-0. Among these proteins, the strongest reduction was detected in the amount of GDCH1. However, differences in protein levels between tagged Col-0 and bou-2 seedlings were not statistically significant. Only one peptide related to GDCH2 was detected in our data set; however, because it was detected in only one of the four replicates, it is not listed (Supplemental Table S1). List of changes in protein abundance of Gly decarboxylase proteins, SHM, and the enzymes MDH, FDH, ASP, γ-aminobutyric acid transaminase (POP2), AlaAT, and Glu dehydrogenase (GDH) Table 2. List of changes in protein abundance of Gly decarboxylase proteins, SHM, and the enzymes MDH, FDH, ASP, γ-aminobutyric acid transaminase (POP2), AlaAT, and Glu dehydrogenase (GDH) Difference was calculated as change of log2 of normalized intensity. Significance was calculated with Student’s t test, P < 0.05. AGI . Gene Symbol . Gene Description . Difference . Significant . AT4G33010 GLDP1 Gly decarboxylase P-protein 1 −0.373902 no AT2G26080 GLDP2 Gly decarboxylase P-protein 2 −0.155379 no AT2G35370 GDCH1 Gly decarboxylase H-protein 1 −0.760396 no AT1G32470 GDCH3 Gly decarboxylase H-protein 3 0.173202 no AT1G11860 GLDT Gly cleavage T-protein family −0.164196 no AT1G48030 GDCL1 Mitochondrial lipoamide dehydrogenase 1 −0.0284281 no AT3G17240 GDCL2 Mitochondrial lipoamide dehydrogenase 2 −0.217162 no AT4G37930 SHM1 Ser hydroxymethyltransferase 1 0.109162 no AT5G26780 SHM2 Ser hydroxymethyltransferase 2 0.696879 no AT5G14780 FDH formate dehydrogenase −0.697987 yes AT5G18170 GDH1 Glu dehydrogenase 1 0.91113 no AT5G07440 GDH2 Glu dehydrogenase 2 0.105005 no AT3G22200 POP2 γ-aminobutyric acid transaminase 0.345683 no AT1G17290 AlaAT1 Ala aminotransferase 1 0.640894 no AT1G72330 AlaAT2 Ala aminotransferase 2 0.223008 no AT2G30970 ASP1 Asp aminotransferase 1 0.399954 no AT1G53240 mMDH1 Lactate/malate dehydrogenase family protein 0.564951 no AT3G15020 mMDH2 Lactate/malate dehydrogenase family protein 0.0343099 no AGI . Gene Symbol . Gene Description . Difference . Significant . AT4G33010 GLDP1 Gly decarboxylase P-protein 1 −0.373902 no AT2G26080 GLDP2 Gly decarboxylase P-protein 2 −0.155379 no AT2G35370 GDCH1 Gly decarboxylase H-protein 1 −0.760396 no AT1G32470 GDCH3 Gly decarboxylase H-protein 3 0.173202 no AT1G11860 GLDT Gly cleavage T-protein family −0.164196 no AT1G48030 GDCL1 Mitochondrial lipoamide dehydrogenase 1 −0.0284281 no AT3G17240 GDCL2 Mitochondrial lipoamide dehydrogenase 2 −0.217162 no AT4G37930 SHM1 Ser hydroxymethyltransferase 1 0.109162 no AT5G26780 SHM2 Ser hydroxymethyltransferase 2 0.696879 no AT5G14780 FDH formate dehydrogenase −0.697987 yes AT5G18170 GDH1 Glu dehydrogenase 1 0.91113 no AT5G07440 GDH2 Glu dehydrogenase 2 0.105005 no AT3G22200 POP2 γ-aminobutyric acid transaminase 0.345683 no AT1G17290 AlaAT1 Ala aminotransferase 1 0.640894 no AT1G72330 AlaAT2 Ala aminotransferase 2 0.223008 no AT2G30970 ASP1 Asp aminotransferase 1 0.399954 no AT1G53240 mMDH1 Lactate/malate dehydrogenase family protein 0.564951 no AT3G15020 mMDH2 Lactate/malate dehydrogenase family protein 0.0343099 no Open in new tab Table 2. List of changes in protein abundance of Gly decarboxylase proteins, SHM, and the enzymes MDH, FDH, ASP, γ-aminobutyric acid transaminase (POP2), AlaAT, and Glu dehydrogenase (GDH) Difference was calculated as change of log2 of normalized intensity. Significance was calculated with Student’s t test, P < 0.05. AGI . Gene Symbol . Gene Description . Difference . Significant . AT4G33010 GLDP1 Gly decarboxylase P-protein 1 −0.373902 no AT2G26080 GLDP2 Gly decarboxylase P-protein 2 −0.155379 no AT2G35370 GDCH1 Gly decarboxylase H-protein 1 −0.760396 no AT1G32470 GDCH3 Gly decarboxylase H-protein 3 0.173202 no AT1G11860 GLDT Gly cleavage T-protein family −0.164196 no AT1G48030 GDCL1 Mitochondrial lipoamide dehydrogenase 1 −0.0284281 no AT3G17240 GDCL2 Mitochondrial lipoamide dehydrogenase 2 −0.217162 no AT4G37930 SHM1 Ser hydroxymethyltransferase 1 0.109162 no AT5G26780 SHM2 Ser hydroxymethyltransferase 2 0.696879 no AT5G14780 FDH formate dehydrogenase −0.697987 yes AT5G18170 GDH1 Glu dehydrogenase 1 0.91113 no AT5G07440 GDH2 Glu dehydrogenase 2 0.105005 no AT3G22200 POP2 γ-aminobutyric acid transaminase 0.345683 no AT1G17290 AlaAT1 Ala aminotransferase 1 0.640894 no AT1G72330 AlaAT2 Ala aminotransferase 2 0.223008 no AT2G30970 ASP1 Asp aminotransferase 1 0.399954 no AT1G53240 mMDH1 Lactate/malate dehydrogenase family protein 0.564951 no AT3G15020 mMDH2 Lactate/malate dehydrogenase family protein 0.0343099 no AGI . Gene Symbol . Gene Description . Difference . Significant . AT4G33010 GLDP1 Gly decarboxylase P-protein 1 −0.373902 no AT2G26080 GLDP2 Gly decarboxylase P-protein 2 −0.155379 no AT2G35370 GDCH1 Gly decarboxylase H-protein 1 −0.760396 no AT1G32470 GDCH3 Gly decarboxylase H-protein 3 0.173202 no AT1G11860 GLDT Gly cleavage T-protein family −0.164196 no AT1G48030 GDCL1 Mitochondrial lipoamide dehydrogenase 1 −0.0284281 no AT3G17240 GDCL2 Mitochondrial lipoamide dehydrogenase 2 −0.217162 no AT4G37930 SHM1 Ser hydroxymethyltransferase 1 0.109162 no AT5G26780 SHM2 Ser hydroxymethyltransferase 2 0.696879 no AT5G14780 FDH formate dehydrogenase −0.697987 yes AT5G18170 GDH1 Glu dehydrogenase 1 0.91113 no AT5G07440 GDH2 Glu dehydrogenase 2 0.105005 no AT3G22200 POP2 γ-aminobutyric acid transaminase 0.345683 no AT1G17290 AlaAT1 Ala aminotransferase 1 0.640894 no AT1G72330 AlaAT2 Ala aminotransferase 2 0.223008 no AT2G30970 ASP1 Asp aminotransferase 1 0.399954 no AT1G53240 mMDH1 Lactate/malate dehydrogenase family protein 0.564951 no AT3G15020 mMDH2 Lactate/malate dehydrogenase family protein 0.0343099 no Open in new tab In this study, we showed that tagged mitochondria of the bou-2 mutant displayed reduced AlaAT activity, increased GluDH activity, and no change in MDH, AspAT, GABA-T, and FDH activities under elevated CO2 conditions compared with tagged Col-0 (Fig. 5). Except for FDH, none of the assayed enzymes showed significantly altered amounts in our proteomic data set (Table 2). The amount of FDH was significantly reduced in tagged bou-2 samples; however, its activity was not altered in the tagged mutant under elevated CO2 conditions compared to tagged Col-0, indicating posttranslational modification of FDH. The level of AlaAT was slightly increased in the tagged mutant but showed only 60% activity compared with tagged Col-0 under both elevated and ambient CO2 conditions. The activities of MDH, AspAT, and GABA-T did not differ between tagged Col-0 and tagged bou-2 mutant under elevated CO2 conditions, although these proteins were more abundant in tagged mutant samples. The activity of GluDH was significantly increased in the tagged mutant compared with tagged Col-0 under elevated CO2 conditions, which may be associated with the increased amount of protein detected in the tagged bou-2 seedlings in our proteomic data set. However, this increase was not statistically significant. Overall, we conclude that differences in the activities of MDH, AspAT, GluDH, AlaAT, GABA-T, and AlaAT measured in this study and that of GDC measured in a previous study most likely do not relate to changes in protein abundance in mitochondria of tagged Col-0 versus tagged bou-2 mutant but instead might be caused by metabolic impairment or posttranslational modifications. DISCUSSION Recently, analyses of mitochondrial proteome content, complexome composition, posttranslational modifications, energy metabolism, OXPHOS complex formation and function, protein translocation, and metabolite shuttles have been conducted to further our understanding of mitochondrial metabolism in Arabidopsis (König et al., 2014; Fromm et al., 2016; De Col et al., 2017; Rao et al., 2017; Senkler et al., 2017; Porcelli et al., 2018; Hu et al., 2019; Kolli et al., 2019; Meyer et al., 2019; Nickel et al., 2019). Many of these analyses required the isolation of intact mitochondria. Here, we report a procedure for the rapid isolation of HA-tagged mitochondria from tagged Arabidopsis lines via co-IP. Mitochondria isolated using this method showed high enrichment of mitochondrial marker proteins with only minor contamination, as demonstrated by immunoblot and quantitative proteomic analyses (Fig. 3; Supplemental Tables S1 and S2). The method reported here enables the isolation of intact mitochondria from Arabidopsis seedlings in less than 25 min (Figs. 2– 4). Moreover, by omitting the first low-speed centrifugation step, the method duration could be shortened to 18 min, although the resulting mitochondrial fraction contained a higher level of other contaminating cellular components. The mitochondrial fraction used for proteomic analyses in this study was obtained using the slightly longer protocol that results in lower contamination with nonmitochondrial proteins. Nevertheless, this isolation method is significantly faster than the standard isolation procedures that generally take up to several hours. To date, we have been able to successfully isolate mitochondria from whole seedlings, leaves, and roots (data not shown). Moreover, this method could be used for the rapid isolation of mitochondria from other plant tissues, such as flowers and developing seeds, because (1) the expression of the affinity tag is driven by the ubiquitous UB10p promoter (Supplemental Fig. S1) and (2) only a small amount of starting material (as low as 1 g) is needed. Additionally, this method is advantageous for the isolation of mitochondria from very young tissues or mutants with growth defects or reduced biomass accumulation. The rapid isolation method is superior to the standard isolation protocols with respect to the yield of mitochondria; we were able to isolate 200 µg of total mitochondrial protein from 1 g of starting material and up to 700 µg total mitochondrial protein from 10 g of whole Arabidopsis seedlings. By contrast, the standard isolation protocols yield only 1.2 mg mitochondria from 50 g of leaves (Keech et al., 2005). Generally, a higher yield is expected using our isolation method, as the HA-tag has high affinity for its cognate antibody. However, yield strongly depends on the amount of beads per gram tissue and the extract-to-bead ratio. Further optimization of both may result in stable amounts of isolated mitochondria and even higher yields. The purity of affinity-purified mitochondria was similar to that of mitochondria isolated using standard protocols including density gradients (Senkler et al., 2017). Immunoblot analysis revealed only minor contamination with proteins of the ER or peroxisomes in affinity-purified mitochondria (Fig. 3). These results were corroborated by quantitative proteomic analysis. Less than 3% of all quantified proteins were assigned to peroxisomes, the ER, the Golgi, vacuoles, endomembranes, plasma membranes, nuclei, and the cytosol. The highest contamination was due to plastid-localized proteins (Supplemental Tables S1 and S2). However, we cannot exclude the possibility that some of the contaminants bound nonspecifically to the beads, despite extensive washing. Approximately 80% of the identified proteins and 90% of the identified peptides showed mitochondrial localization (Supplemental Tables S1 and S2). Thus, we conclude that the purity of mitochondria isolated using the rapid affinity purification method is comparable with that of mitochondria isolated using traditional methods. Isolated mitochondria show respiratory coupling that is comparable with previous isolations using traditional methods (Keech et al., 2005). Consistent with this result, we could show that the mitochondrial marker CMXRos, a dye that solely stains mitochondria with an intact respiratory chain, was retained in the mitochondria after affinity purification. We could not efficiently elute the mitochondria from the magnetic beads with HA peptide. However, mitochondria could be efficiently eluted using SDS-PAGE or detergent lysis buffer. Elution of intact mitochondria might be achievable by integrating a protease cleavage site between the HA-tag and GFP; this will be explored in future studies. In our data set, we were able to identify 96% and 99% of the proteins detected by Klodmann et al. (2011) and Senkler et al. (2017), respectively, in previous analyses of mitochondrial proteomes and their complexome composition (Supplemental Tables S1 and S2). On the basis of a recent review on the composition and function of OXPHOS in mitochondria (Meyer et al., 2019), we were able to identify 86% of all the predicted subunits and assembly factors. To date, all of the proteins reviewed in Meyer et al. (2019) have not been confirmed, and it might require an in-depth analysis or membrane enrichment to confirm their presence in mitochondria in proteomic studies. Previously, it was reported that the subunit ND4L is difficult to detect in proteomic studies because of its hydrophobic nature (Peters et al., 2013). Consistent with this observation, we also could not identify this protein in our proteome or in the list of quantified peptides (Supplemental Tables S1 and S2). However, we were able to detect all proteins of the TCA cycle (except two subunits of complex II), all GDC proteins, the majority of the proteins and subunits of the TIM/TOM protein import apparatus, metabolite transporters of amino acids, dicarboxylic acids, cofactors, ions and energy equivalents (e.g. BOU, BAC, UCP, DCT, SAMC, NDT, APC, AAC, and PHT), as well as many proteins involved in protein synthesis/turnover and DNA/RNA metabolism (Supplemental Tables S1 and S2). Thus, our rapidly isolated mitochondria showed good purity, integrity, and functionality. Among all of the identified proteins, 20% could not be assigned to mitochondria. These proteins included components of PSI and PSII; these could be clearly categorized as contamination. However, we also identified proteins with unknown function and no clear prediction of localization. In addition, we detected proteins such as GAPC, which was previously shown to interact with the OMM protein VDAC (Schneider et al., 2018). Therefore, we predict that some of the proteins classified as contaminants might represent novel mitochondrial proteins, for example, as part of OMM protein complexes in the cytosol or as components of complexes at organellar contact sites. However, this needs to be evaluated in more detail in the future. Application of the novel method to a mutant lacking the mitochondrial Glu transporter BOU resulted in the detection of surprisingly few changes in protein abundances compared with tagged Col-0. Only 22 mitochondrial proteins showed a significant reduction in abundance in the tagged bou-2 mutant, whereas five proteins were significantly increased in abundance. However, only changes in a mitochondrial folylpoly-Glu synthetase (FGPS) and in FDH, which contributes to the production of CO2 in the mitochondria by oxidizing formate, might be connected to photorespiration. Formate is released from 10-formyl-THF by 10-formyl deformylase, an enzyme involved in the maintenance of the THF pool in mitochondrial matrix (Collakova et al., 2008). Reduced GDC activity in bou-2 might result in a lower production of formate and finally a reduced abundance of FDH. FGPS is involved in vitamin B9 metabolism by catalyzing the glutamylation of THF, a cofactor of GLDT and SHM (Hanson and Gregory, 2011). No significant changes were detected in the abundance of any of the proteins of the GDC multienzyme system. SHM1, SHM2, and GDCH3 were slightly more abundant in the mutant than tagged Col-0, whereas the others seem to be slightly reduced; however, this trend did not meet the significance threshold (Table 2). The observed changes were not pronounced and did not explain why the GDC activity was reduced to approximately 15% of the Col-0 level in the bou-2 mutant. A possible explanation could be that Eisenhut and coworkers used 4-week-old rosettes (Eisenhut et al., 2013), whereas we used 10-d-old seedlings in this study. This possibility is supported by the observation that no difference in MDH activity could be detected between 10-d-old mutant and tagged Col-0 seedlings (Fig. 5A). However, in 4-week-old leaves, the MDH activity was significantly reduced in the mutant compared with tagged Col-0 (Supplemental Fig. S2). In contrast to GDC, the abundance of FDH was significantly reduced in the mutant, whereas its activity was unaltered compared with tagged Col-0 (Table 1; Fig. 5B). Previously, FDH was identified in a Lys acetylome study of Arabidopsis mitochondria from 10-d-old Col-0 seedlings (König et al., 2014). This might indicate that FDH activity is more likely regulated by posttranslational modifications than by protein abundance. The BOU protein was recently assigned the function of a Glu transporter (Porcelli et al., 2018). Glu is indirectly linked to photorespiration, as it is needed for the polyglutamylation of THF, which increases its stability and promotes the activity of THF-dependent enzymes (Hanson and Gregory, 2011). However, in addition to BOU, mitochondria-localized uncoupling proteins 1 and 2 show Glu uptake activity in Arabidopsis (Monné et al., 2018). This raises the question why knockout of the BOU gene leads to a photorespiratory phenotype in young tissues, if BOU is not the only Glu transporter of mitochondria. Additionally, polyglutamylation is not restricted to mitochondria, as Arabidopsis contains three isoforms of FGPS localized to mitochondria, plastids, and the cytosol (Hanson and Gregory, 2011). Folate transporters prefer monoglutamylated forms of THF, whereas enzymes generally prefer polyglutamylated forms (Suh et al., 2001). These data indicate that BOU performs other functions, in addition to Glu transport in vivo. We exclude its function as a mitochondrial Glu/Gln shuttle, as BOU shows no Gln uptake activity (Porcelli et al., 2018). However, it is possible that BOU is involved in folate metabolism, as folate biosynthesis occurs only in mitochondria (Hanson and Gregory, 2011). This possibility, however, needs to be investigated in future studies. CONCLUSION Our experiments show that, in addition to the analysis of protein-protein interactions, affinity tagging is a powerful tool for the isolation of functional organelles from Arabidopsis. The mitochondria isolated using this method showed high purity and integrity. Future studies will be required to efficiently elute mitochondria from magnetic beads and to determine the applicability of this method for metabolite analyses. To conduct metabolite analyses, it is encouraging that the LC/MS-compatible buffer system developed previously for mammalian mitochondria (Chen et al., 2016) can also be used for the isolation of mitochondria from plant tissues. Expressing the affinity tag under the control of cell-specific promoters will allow the isolation of mitochondria from specific cell types, such as meristems or guard cells (Yang et al., 2008; Schürholz et al., 2018). The use of cell-specific promoters in our construct will help unravel the complex role of mitochondria in various cell types. We expect that similar tagging strategies will be applicable to other plant cell organelles, such as plastids and peroxisomes. Moreover, simultaneous expression of several different affinity tags will facilitate the affinity purification of different organelles from a single extract. MATERIALS AND METHODS Plant Growth Conditions Arabidopsis (Arabidopsis thaliana) ecotype Col-0 and bou-2 mutant (GABI-Kat line number 079D12; http://www.gabi-kat.de/db/lineid.php; Kleinboelting et al., 2012; Eisenhut et al., 2013) were used in this study. Seeds were sterilized by washing with 70% (v/v) ethanol supplemented with 1% (v/v) Triton X-100 twice for 10 min each, followed by washing with 100% ethanol twice for 10 min each. Seeds were grown on half-strength Murashige and Skoog medium (pH 5.7) supplemented with 0.8% (w/v) agar. Seeds were subjected to cold stratification for 2 d at 4°C. After germination, seedlings were grown for 10 d under a 12-h light/12-h dark photoperiod under 100 µmol m−2 s−1 light intensity and a CO2-enriched atmosphere (0.3% CO2), unless otherwise stated. Measurement of Dry Weight Ten-day-old Arabidopsis Col-0, tagged Col-0, bou-2, and tagged bou-2 were collected in 1.5-mL microcentrifuge tubes, dried for 3 d at 70°C, and then weighed. Four-week-old Arabidopsis Col-0 and tagged Col-0 rosettes grown at ambient CO2 conditions were collected in paper bags, dried for 5 d at 70°C, and then weighed. Construction of Transgenic Lines The HA epitope-tag was amplified with a start codon from the Gateway binary vector pGWB15 (GenBank accession AB289778). The coding sequence of sGFP, minus the start and stop codons but including a linker peptide (GGSG) at the 5′ and 3′ ends, was amplified from the Gateway binary vector pGWB4 (GenBank accession AB289767). The coding sequence of TOM5 (At5g08040; minus the start codon) was amplified from Arabidopsis cDNA. Starting from the 5′ end to the 3′ end, the amplified 3×HA-tag, sGFP, and TOM5 were cloned into the pUTKan vector (Krebs et al., 2012) under the control of the Arabidopsis UB10p using restriction endonucleases. The construct was introduced into Agrobacterium tumefaciens, strain GV3101::pMP90 (Koncz and Schell, 1986), which was then introduced into Col-0 and bou-2 plants via Agrobacterium-mediated transformation using the floral-dip method, as described previously (Clough and Bent, 1998). Homozygotes of the T3 generation were used for analyses. The generated vector pUTKan-3×HA-sGFP-TOM5 has been deposited on Addgene (ID 130674). Confocal Laser Scanning Microscopy The expression of 3×HA-sGFP-TOM5 was verified via confocal laser scanning microscopy using the Zeiss LSM 78 Confocal Microscope and Zeiss ZEN software. The Col-0 and bou-2 seedlings regenerated from independent transformation events were incubated with 200 nm MitoTracker red CMXRos (Molecular Probes) in half-strength Murashige and Skoog supplemented with 3% (w/v) Suc for 15 min. Images were captured using the following excitation/emission wavelengths: sGFP (488 nm/490–550 nm) and MitoTracker red CMXRos (561 nm/580–625 nm). Pictures were processed using the ImageJ software (https://imagej.nih.gov/ij/). Rapid Isolation of Mitochondria Using co-IP Epitope-tagged mitochondria were rapidly isolated using co-IP, as described previously (Chen et al., 2016). In brief, 1 to 10 g of Arabidopsis seedlings were harvested and homogenized in 40 mL KPBS (10 mm KH2PO4 [pH 7.25] and 136 mm KCl) twice for 5 s at low speed and 15 s at high speed in a Warren blender. The resulting homogenate was filtered through three layers of miracloth supported by a nylon mesh (pore size 40 µm) and centrifuged at 2500g for 5 min. The pellet containing cell debris and chloroplasts was discarded. The supernatant was subsequently centrifuged at 20,000g for 9 min. The pellet representing the crude mitochondrial fraction was resuspended in 1 mL KPBS using a fine paintbrush and homogenized with three strokes using a Potter-Elvehjem (B. Braun, Melsungen). Crude mitochondria were incubated with 50 to 250 µL prewashed magnetic anti-HA beads (Thermo Fisher Scientific) on an end-over-end rotator for 5 min in 1.5-mL microcentrifuge tubes. Magnetic beads were prewashed according to the manufacturer’s instructions using phosphate-buffered saline supplemented with 0.5% (v/v) Triton X-114. Magnetic beads were separated using a magnetic stand (DYNAL, DynaMag-2 Magnet, Invitrogen) and washed at least three times with each 1 mL KPBS. The purified mitochondria were lysed using 50 to 250 µL mitochondria lysis buffer (50 mm TES/KOH [pH 7.5], 2 mm EDTA, 5 mm MgCl2, 10% [v/v] glycerol, and 0.1% [v/v] Triton X-100) for enzyme activity assays and immunoblot analysis or directly frozen in liquid nitrogen for proteome analyses. All steps were carried out at 4°C. The amount of protein recovered after lysis was determined using the Quick Start Bradford Protein Assay Kit (Bio-Rad), with bovine serum albumin as the standard. Chlorophyll content of rapidly enriched mitochondria was measured as previously described (Porra, 2002). Isolation of Mitochondria Using the Traditional Approach Mitochondria were isolated from 10-d-old Col-0 seedlings via differential centrifugation and Percoll gradient purification, as described previously (Kühn et al., 2015). Immunoblot Analysis 25 µg of total leaf extract and 6.45 µg of isolated mitochondria fractions were heated at 96°C in SDS-PAGE loading buffer for 10 min and separated on 12% SDS-polyacrylamide gels (Laemmli, 1970). Proteins were transferred to 0.2-µm polyvinylidene difluoride membranes (Bio-Rad) or 0.45-µm nitrocellulose membranes (Thermo Scientific) using standard protocols. Protein transfer was verified by staining the membranes with Ponceau S red (Sigma Aldrich). Membranes were blocked according to the manufacturer’s instructions for 1 h, washed with Tris-buffered saline containing 0.1% (v/v) Tween 20 (TBST), and subsequently incubated with either a primary antibody or a single-step antibody overnight at 4°C. Antibodies against marker proteins were diluted as follows: anti-AOX (1:1000), anti-IDH (1:5000), anti-VDAC1 (1:5000), anti-HA-horseradish peroxidase (HRP; 1:5000; Miltenyi Biotec), anti-RbcL (1:7500), anti-Cat (1:1000), anti-BiP2 (1:2000), anti-Histone H3 (1:5000), and anti-HSC70 (1:3000). Membranes were washed with TBST twice for 10 min each and incubated with the secondary goat anti-rabbit-HRP antibody (1:5000; Merck Millipore) at room temperature for 1 h or at 4°C overnight. Subsequently, membranes were washed with TBST five times for 5 min each and visualized using a chemiluminescence detection system (Immobilon Western HRP Substrate, Merck Millipore). All steps were carried out with phosphate-buffered saline when using anti-Cat antibody. Antibodies were purchased from Agrisera if not stated otherwise. Seahorse XFe96 Extracellular Flux Analyzer Mitochondria were isolated from 10-d-old tagged Col-0 as described above. Purified mitochondria bound to magnetic anti-HA beads were resuspended in mitochondria assay buffer for Seahorse Analyzer measurement (70 mm Suc, 220 mm mannitol, 10 mm KH2PO4, 5 mm MgCl2, 2 mm HEPES, 1 mm EGTA, 0.2% [w/v] fatty acid-free bovine serum albumin, pH 7.2 at 37°C) to a concentration of 0.2 µg/µL. Each 20-µL mitochondria suspension (4 µg total mitochondrial protein) per well was analyzed in a cell culture plate for Seahorse Analyzer using an Agilent Seahorse XFe96 Extracellular Flux Analyzer (Agilent Technologies). Mitochondria were attached to the bottom of the plate using a magnetic stand. Subsequently, mitochondria assay buffer for Seahorse Analyzer measurement including succinate as substrate (final concentration 10 mm) was carefully added. Assay protocol was adapted from the Agilent Seahorse XF Cell Mito Stress Test manual. First basal respiration with succinate as substrate was measured in the presence or absence of antimycin A (final concentration 4 µm; Sigma Aldrich), following injection of antimycin A (to a final concentration of 4 µm) to inhibit the respiratory chain. Cartridge hydration overnight was performed according to the manufacturer’s instruction. Control isolations were performed on 10-d-old Col-0 seedlings. Recovery Mitochondrial recovery was determined based on cytochrome c oxidase activity in homogenized extract and isolated mitochondria via co-IP, as described previously (Lai et al., 2019). Cytochrome c oxidase activity was measured by following the oxidation of cytochrome c at 550 nm (Spinazzi et al., 2012). The assay mixture contained 50 mm potassium phosphate buffer (pH 7.0), 40 µm fully reduced cytochrome c, and 0.1 to 0.5 µg total mitochondrial protein or 5 to 10 µg total extract protein. Staining of Intact Mitochondria In mitochondria, staining experiments purified mitochondria bound to 100 µL magnetic anti-HA beads were incubated for 15 min in 1 mL KPBS supplemented with 200 nm MitoTracker red CMXRos in the dark on an end-over-end rotator. Magnetic beads were washed three times with KPBS. Mitochondria were lysed using 1 mL mitochondria lysis buffer. Released fluorescence was measured using a fluorescence spectrophotometer (SynergyH1, BioTek) with the following excitation/emission settings: 570 nm/600 to 650 nm. Latency of MDH Activity To assess latency of MDH activity, purified mitochondria bound to 100 µL magnetic anti-HA beads were first eluted in 100 µL KPBS followed by elution in 100 µL KPBS with 0.1% (v/v) Triton X-114. MDH activity in both elution fractions was measured as described previously (Tomaz et al., 2010). Enzyme Assays Activities of mitochondrial enzymes were measured using a plate-reader spectrophotometer (SynergyH1, BioTek) based on the A340. Mitochondria were enriched using 150-µL magnetic anti-HA beads and lysed in 200 to 250 µL mitochondrial lysis buffer. The activity of MDH was measured based on the oxidation of NADH to NAD+ at 340 nm, as described previously (Tomaz et al., 2010). The reaction mixture contained 50 mm KH2PO4 (pH 7.5), 0.2 mm NADH, 5 mm EDTA, 10 mm MgCl2, 2 mm OAA (Tomaz et al., 2010), and 0.1 to 0.4 µg total mitochondrial protein. AspAT activity was measured in a reaction coupled with MDH, as described previously (Wilkie and Warren, 1998), with 0.3 to 1 µg total mitochondrial protein per assay. No external pyridoxal-5′-phosphate was added to the reaction mixture. GluDH activity was measured as described previously (Turano et al., 1996), based on the reduction of NAD+ to NADH at 340 nm. To determine the amination activity, 0.5 to 2 µg total mitochondrial protein was used per assay. GABA-T activity was measured in a reaction coupled with succinate-semialdehyde dehydrogenase (SSADH), as described previously (Clark et al., 2009). The assay buffer contained 50 mm 3-{[2-hydroxy-1,1-bis(hydroxymethyl)ethyl]amino}-1-propanesulfonic acid (pH 9), 0.2 mm NAD+, 0.625 mm EDTA, 8 mm GABA, 2 mm pyruvate, 1 U/mL SSADH, and 2 to 5 µg total mitochondrial protein. The NAD+-dependent SSADH was purified from Escherichia coli, as described previously (Clark et al., 2009). The recombinant purified protein catalyzed the production of NADH with a specific activity of 1.6 U/mg protein. AlaAT activity was measured in reaction coupled with lactate dehydrogenase, as described previously (Miyashita et al., 2007), with 1 to 5 µg total mitochondrial protein. FDH activity was measured based on the reduction of NAD+ to NADH at 340 nm and 30°C, with 1 to 5 µg total mitochondrial protein. The assay buffer contained 100 mm potassium phosphate buffer (pH 7.5), 1 mm NAD+, and 50 mm sodium formate. Sample Preparation for LC/MS Analysis To elute proteins from magnetic beads, 30 µL of Laemmli buffer was added to the reaction mixture, and samples were incubated at 95°C for 10 min. Subsequently, 20 µL of protein sample was loaded on an SDS-polyacrylamide gel for in-gel digestion. The isolated gel pieces were reduced using 50 µL of 10 mm dithiothreitol, then alkylated using 50 µL of 50 mm iodoacetamide, and finally digested using 6 µL of trypsin (200 ng) in 100 mm ammonium bicarbonate. The peptides were resolved in 15 µL of 0.1% (v/v) trifluoracetic acid and subjected to LC/MS analysis. LC/MS Analysis The LC/MS analysis was performed on a Q Exactive Plus mass spectrometer (Thermo Scientific) connected to an Ultimate 3000 Rapid Separation LC system (Dionex; Thermo Scientific) and equipped with an Acclaim PepMap 100 C18 column (75 µm inner diameter × 25 cm length × 2 mm particle size; Thermo Scientific). The length of the isocratic LC gradient was 120 min. The mass spectrometer was operated in positive mode and coupled with a nano electrospray ionization source. Capillary temperature was set at 250°C, and source voltage was set at 1.4 kV. The survey scans were conducted at a mass to charge (m/z) of 200 to 2000 and a resolution of 70,000. The automatic gain control was set at 3,000,000, and the maximum fill time was set at 50 ms. The 10 most intensive peptide ions were isolated and fragmented by high-energy collision dissociation. Computational MS Data Analysis Peptide and protein identification and quantification was performed using MaxQuant version 1.5.5.1 (MPI for Biochemistry) with default parameters. The identified Arabidopsis peptides and proteins were queried against a specific proteome database (UP0000006548, downloaded 12/11/17) from UniProt. The oxidation and acetylation of Met residues at the N termini of proteins were set as variable modifications, whereas carbamidomethylations at Cys residues were considered as fixed modification. Peptides and proteins were accepted with a false discovery rate of 1%. Unique and razor peptides were used for label-free quantification, and peptides with variable modifications were included in the quantification. The minimal ratio count was set to two, and the “matched between runs” option was enabled. Normalized intensities, as provided by MaxQuant, were analyzed using the Perseus framework (version 1.5.0.15; MPI for Biochemistry; Tyanova et al., 2016). Only proteins containing at least two unique peptides and a minimum of three valid values in at least one group were quantified. Proteins that were identified only by site or marked as a contaminant (from the MaxQuant contaminant list) were excluded from the analysis. Differential enrichment of proteins in the two groups (Col-0; bou-2) was assessed using Student’s t test. Significance analysis was applied on log2-transformed values using an S0 constant of 0 and a false discovery rate of 5% as threshold cutoffs (Benjamini and Hochberg, 1995). The MS proteomics data has been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the data set identifier PXD014137. Accession Numbers Sequence data from this article can be found in the GenBank/EMBL data libraries under accession numbers AAF82782 (AlaAT1), AAF82781 (AlaAT2), AEC08469 (AspAT), OAO95225 (BOU), AED92076 (FDH), AEE76603 (GABA-T), AED92515 (GluDH1), AED91158 (GluDH2), AEE74011 (GluDH3), BAF44962 (sGFP), Q9ZP06 (mMDH1), Q9LKA3 (mMDH2), and OAO94076 (TOM5). Supplemental Data The following supplemental materials are available. Supplemental Figure S1. Schematic representation of the vector used to label mitochondria with triple HA-tag. Supplemental Figure S2. Phenotypic analysis of transgenic lines. Supplemental Figure S3. Original images of all immunoblots related to Figure 3. Supplemental Figure S4. Activity of MDH in mitochondria rapidly isolated from 4-week-old Col-0 and bou-2 leaves expressing the UB10p-3×HA-sGFP-TOM5 construct. Supplemental Table S1. List of proteins identified and quantified in 10-d-old Col-0 and bou-2 plants expressing the 3×HA-sGFP-TOM5 protein. Supplemental Table S2. List of raw intensities and reliability of all quantified peptides. LITERATURE CITED Benjamini Y , Hochberg Y ( 1995 ) Controlling the false discovery rate: A practical and powerful approach to multiple testing . J R Stat Soc Series B Stat Methodol 57 : 289 – 300 Google Scholar OpenURL Placeholder Text WorldCat Chen WW , Freinkman E, Wang T, Birsoy K, Sabatini DM ( 2016 ) Absolute quantification of matrix metabolites reveals the dynamics of mitochondrial metabolism . Cell 166 : 1324 – 1337.e11 Google Scholar Crossref Search ADS PubMed WorldCat Clark SM , Di Leo R, Dhanoa PK, Van Cauwenberghe OR, Mullen RT, Shelp BJ ( 2009 ) Biochemical characterization, mitochondrial localization, expression, and potential functions for an Arabidopsis gamma-aminobutyrate transaminase that utilizes both pyruvate and glyoxylate . J Exp Bot 60 : 1743 – 1757 Google Scholar Crossref Search ADS PubMed WorldCat Clough SJ , Bent AF ( 1998 ) Floral dip: A simplified method for Agrobacterium-mediated transformation of Arabidopsis thaliana . Plant J 16 : 735 – 743 Google Scholar Crossref Search ADS PubMed WorldCat De Col V , Fuchs P, Nietzel T, Elsässer M, Voon CP, Candeo A, Seeliger I, Fricker MD, Grefen C, Møller IM, et al. ( 2017 ) ATP sensing in living plant cells reveals tissue gradients and stress dynamics of energy physiology . eLife 6 : 1 – 29 Google Scholar Crossref Search ADS WorldCat Collakova E , Goyer A, Naponelli V, Krassovskaya I, Gregory JF III , Hanson AD, Shachar-Hill Y ( 2008 ) Arabidopsis 10-formyl tetrahydrofolate deformylases are essential for photorespiration . Plant Cell 20 : 1818 – 1832 Google Scholar Crossref Search ADS PubMed WorldCat Dietmeier K , Hönlinger A, Bömer U, Dekker PJ, Eckerskorn C, Lottspeich F, Kübrich M, Pfanner N ( 1997 ) Tom5 functionally links mitochondrial preprotein receptors to the general import pore . Nature 388 : 195 – 200 Google Scholar Crossref Search ADS PubMed WorldCat Eisenhut M , Planchais S, Cabassa C, Guivarc’h A, Justin AM, Taconnat L, Renou JP, Linka M, Gagneul D, Timm S, et al. ( 2013 ) Arabidopsis A BOUT DE SOUFFLE is a putative mitochondrial transporter involved in photorespiratory metabolism and is required for meristem growth at ambient CO2 levels . Plant J 73 : 836 – 849 Google Scholar Crossref Search ADS PubMed WorldCat Eisenhut M , Roell MS, Weber APM ( 2019 ) Mechanistic understanding of photorespiration paves the way to a new green revolution . New Phytol 223 : 1762 – 1769 Google Scholar Crossref Search ADS PubMed WorldCat Engel N , van den Daele K, Kolukisaoglu U, Morgenthal K, Weckwerth W, Pärnik T, Keerberg O, Bauwe H ( 2007 ) Deletion of glycine decarboxylase in Arabidopsis is lethal under nonphotorespiratory conditions . Plant Physiol 144 : 1328 – 1335 Google Scholar Crossref Search ADS PubMed WorldCat Fromm S , Senkler J, Eubel H, Peterhänsel C, Braun H-P ( 2016 ) Life without complex I: Proteome analyses of an Arabidopsis mutant lacking the mitochondrial NADH dehydrogenase complex . J Exp Bot 67 : 3079 – 3093 Google Scholar Crossref Search ADS PubMed WorldCat Hanson AD , Gregory JF III ( 2011 ) Folate biosynthesis, turnover, and transport in plants . Annu Rev Plant Biol 62 : 105 – 125 Google Scholar Crossref Search ADS PubMed WorldCat Hooper CM , Castleden IR, Tanz SK, Aryamanesh N, Millar AH ( 2017 ) SUBA4: The interactive data analysis centre for Arabidopsis subcellular protein locations . Nucleic Acids Res 45 ( D1 ): D1064 – D1074 Google Scholar Crossref Search ADS PubMed WorldCat Horie C , Suzuki H, Sakaguchi M, Mihara K ( 2003 ) Targeting and assembly of mitochondrial tail-anchored protein Tom5 to the TOM complex depend on a signal distinct from that of tail-anchored proteins dispersed in the membrane . J Biol Chem 278 : 41462 – 41471 Google Scholar Crossref Search ADS PubMed WorldCat Hu Y , Zou W, Wang Z, Zhang Y, Hu Y, Qian J, Wu X, Ren Y, Zhao J ( 2019 ) Translocase of the outer mitochondrial membrane 40 is required for mitochondrial biogenesis and embryo development in Arabidopsis . Front Plant Sci 10 : 389 Google Scholar Crossref Search ADS PubMed WorldCat Husic DW , Husic HD, Tolbert NE, Black CC ( 1987 ) The oxidative photosynthetic carbon cycle or C2 cycle . CRC Crit Rev Plant Sci 5 : 45 – 100 Google Scholar Crossref Search ADS WorldCat Keech O , Dizengremel P, Gardeström P ( 2005 ) Preparation of leaf mitochondria from Arabidopsis thaliana . Physiol Plant 124 : 403 – 409 Google Scholar Crossref Search ADS WorldCat Kelly GJ , Latzko E ( 1976 ) Inhibition of spinach-leaf phosphofructokinase by 2-phosphoglycollate . FEBS Lett 68 : 55 – 58 Google Scholar Crossref Search ADS PubMed WorldCat Kleinboelting N , Huep G, Kloetgen A, Viehoever P, Weisshaar B ( 2012 ) GABI-Kat SimpleSearch: New features of the Arabidopsis thaliana T-DNA mutant database . Nucleic Acids Res 40 : D1211 – D1215 Google Scholar Crossref Search ADS PubMed WorldCat Klodmann J , Senkler M, Rode C, Braun H-P ( 2011 ) Defining the protein complex proteome of plant mitochondria . Plant Physiol 157 : 587 – 598 Google Scholar Crossref Search ADS PubMed WorldCat Kolli R , Soll J, Carrie C ( 2019 ) OXA2b is crucial for proper membrane insertion of COX2 during biogenesis of complex IV in plant mitochondria . Plant Physiol 179 : 601 – 615 Google Scholar Crossref Search ADS PubMed WorldCat Koncz C , Schell J ( 1986 ) The promoter of TL-DNA gene 5 controls the tissue-specific expression of chimaeric genes carried by a novel type of Agrobacterium binary vector . Mol Gen Genet 204 : 383 – 396 Google Scholar Crossref Search ADS WorldCat König AC , Hartl M, Boersema PJ, Mann M, Finkemeier I ( 2014 ) The mitochondrial lysine acetylome of Arabidopsis . Mitochondrion 19 ( Pt B ): 252 – 260 Google Scholar Crossref Search ADS PubMed WorldCat Krebs M , Held K, Binder A, Hashimoto K, Den Herder G, Parniske M, Kudla J, Schumacher K ( 2012 ) FRET-based genetically encoded sensors allow high-resolution live cell imaging of Ca2+ dynamics . Plant J 69 : 181 – 192 Google Scholar Crossref Search ADS PubMed WorldCat Kühn K , Obata T, Feher K, Bock R, Fernie AR, Meyer EH ( 2015 ) Complete mitochondrial complex I deficiency induces an up-regulation of respiratory fluxes that is abolished by traces of functional complex I . Plant Physiol 168 : 1537 – 1549 Google Scholar Crossref Search ADS PubMed WorldCat van der Laan M , Horvath SE, Pfanner N ( 2016 ) Mitochondrial contact site and cristae organizing system . Curr Opin Cell Biol 41 : 33 – 42 Google Scholar Crossref Search ADS PubMed WorldCat Laemmli UK ( 1970 ) Cleavage of structural proteins during the assembly of the head of bacteriophage T4 . Nature 227 : 680 – 685 Google Scholar Crossref Search ADS PubMed WorldCat Lai N , M Kummitha C, Rosca MG, Fujioka H, Tandler B, Hoppel CL ( 2019 ) Isolation of mitochondrial subpopulations from skeletal muscle: Optimizing recovery and preserving integrity . Acta Physiol (Oxf) 225 : e13182 Google Scholar Crossref Search ADS PubMed WorldCat Linka M , Weber APM ( 2005 ) Shuffling ammonia between mitochondria and plastids during photorespiration . Trends Plant Sci 10 : 461 – 465 Google Scholar Crossref Search ADS PubMed WorldCat Mansilla N , Racca S, Gras DE, Gonzalez DH, Welchen E ( 2018 ) The complexity of mitochondrial complex IV: An update of cytochrome c oxidase biogenesis in plants . Int J Mol Sci 19 : 1 – 34 Google Scholar OpenURL Placeholder Text WorldCat Meyer EH , Welchen E, Carrie C ( 2019 ) Assembly of the complexes of the oxidative phosphorylation system in land plant mitochondria . Annu Rev Plant Biol 70 : 23 – 50 Google Scholar Crossref Search ADS PubMed WorldCat Millar AH , Eubel H, Jänsch L, Kruft V, Heazlewood JL, Braun H-P ( 2004 ) Mitochondrial cytochrome c oxidase and succinate dehydrogenase complexes contain plant specific subunits . Plant Mol Biol 56 : 77 – 90 Google Scholar Crossref Search ADS PubMed WorldCat Millar AH , Sweetlove LJ, Giegé P, Leaver CJ ( 2001 ) Analysis of the Arabidopsis mitochondrial proteome . Plant Physiol 127 : 1711 – 1727 Google Scholar Crossref Search ADS PubMed WorldCat Miyashita Y , Dolferus R, Ismond KP, Good AG ( 2007 ) Alanine aminotransferase catalyses the breakdown of alanine after hypoxia in Arabidopsis thaliana . Plant J 49 : 1108 – 1121 Google Scholar Crossref Search ADS PubMed WorldCat Monné M , Daddabbo L, Gagneul D, Obata T, Hielscher B, Palmieri L, Miniero DV, Fernie AR, Weber APM, Palmieri F ( 2018 ) Uncoupling proteins 1 and 2 (UCP1 and UCP2) from Arabidopsis thaliana are mitochondrial transporters of aspartate, glutamate, and dicarboxylates . J Biol Chem 293 : 4213 – 4227 Google Scholar Crossref Search ADS PubMed WorldCat Murcha MW , Kmiec B, Kubiszewski-Jakubiak S, Teixeira PF, Glaser E, Whelan J ( 2014 ) Protein import into plant mitochondria: Signals, machinery, processing, and regulation . J Exp Bot 65 : 6301 – 6335 Google Scholar Crossref Search ADS PubMed WorldCat Murcha MW , Narsai R, Devenish J, Kubiszewski-Jakubiak S, Whelan J ( 2015 ) MPIC: A mitochondrial protein import components database for plant and non-plant species . Plant Cell Physiol 56 : e10 Google Scholar Crossref Search ADS PubMed WorldCat Nickel C , Horneff R, Heermann R, Neumann B, Jung K, Soll J, Schwenkert S ( 2019 ) Phosphorylation of the outer membrane mitochondrial protein OM64 influences protein import into mitochondria . Mitochondrion 44 : 93 – 102 Google Scholar Crossref Search ADS PubMed WorldCat Ogren WL , Bowes G ( 1971 ) Ribulose diphosphate carboxylase regulates soybean photorespiration . Nat New Biol 230 : 159 – 160 Google Scholar Crossref Search ADS PubMed WorldCat Oliver DJ , Neuburger M, Bourguignon J, Douce R ( 1990 ) Interaction between the component enzymes of the glycine decarboxylase multienzyme complex . Plant Physiol 94 : 833 – 839 Google Scholar Crossref Search ADS PubMed WorldCat Pendergrass W , Wolf N, Poot M ( 2004 ) Efficacy of MitoTracker green and CMXrosamine to measure changes in mitochondrial membrane potentials in living cells and tissues . Cytometry A 61 : 162 – 169 Google Scholar PubMed OpenURL Placeholder Text WorldCat Peterhansel C , Horst I, Niessen M, Blume C, Kebeish R, Kürkcüoglu S, Kreuzaler F ( 2010 ) Photorespiration . Arabidopsis Book 8 : e0130 Google Scholar Crossref Search ADS PubMed WorldCat Peters K , Belt K, Braun H-P ( 2013 ) 3D gel map of Arabidopsis complex I . Front Plant Sci 4 : 153 Google Scholar Crossref Search ADS PubMed WorldCat Porcelli V , Vozza A, Calcagnile V, Gorgoglione R, Arrigoni R, Fontanesi F, Marobbio CMT, Castegna A, Palmieri F, Palmieri L ( 2018 ) Molecular identification and functional characterization of a novel glutamate transporter in yeast and plant mitochondria . Biochim Biophys Acta Bioenerg 1859 : 1249 – 1258 Google Scholar Crossref Search ADS PubMed WorldCat Porra RJ ( 2002 ) The chequered history of the development and use of simultaneous equations for the accurate determination of chlorophylls a and b . Photosynth Res 73 : 149 – 156 Google Scholar Crossref Search ADS PubMed WorldCat Rao RSP , Salvato F, Thal B, Eubel H, Thelen JJ, Møller IM ( 2017 ) The proteome of higher plant mitochondria . Mitochondrion 33 : 22 – 37 Google Scholar Crossref Search ADS PubMed WorldCat Schneider M , Knuesting J, Birkholz O, Heinisch JJ, Scheibe R ( 2018 ) Cytosolic GAPDH as a redox-dependent regulator of energy metabolism . BMC Plant Biol 18 : 184 Google Scholar Crossref Search ADS PubMed WorldCat Schürholz A-K , López-Salmerón V, Li Z, Forner J, Wenzl C, Gaillochet C, Augustin S, Barro AV, Fuchs M, Gebert M, et al. ( 2018 ) A comprehensive toolkit for inducible, cell type-specific gene expression in Arabidopsis . Plant Physiol 178 : 40 – 53 Google Scholar Crossref Search ADS PubMed WorldCat Senkler J , Senkler M, Eubel H, Hildebrandt T, Lengwenus C, Schertl P, Schwarzländer M, Wagner S, Wittig I, Braun HP ( 2017 ) The mitochondrial complexome of Arabidopsis thaliana . Plant J 89 : 1079 – 1092 Google Scholar Crossref Search ADS PubMed WorldCat Spinazzi M , Casarin A, Pertegato V, Salviati L, Angelini C ( 2012 ) Assessment of mitochondrial respiratory chain enzymatic activities on tissues and cultured cells . Nat Protoc 7 : 1235 – 1246 Google Scholar Crossref Search ADS PubMed WorldCat Suh JR , Herbig AK, Stover PJ ( 2001 ) New perspectives on folate catabolism . Annu Rev Nutr 21 : 255 – 282 Google Scholar Crossref Search ADS PubMed WorldCat Sunderhaus S , Dudkina NV, Jänsch L, Klodmann J, Heinemeyer J, Perales M, Zabaleta E, Boekema EJ, Braun HP ( 2006 ) Carbonic anhydrase subunits form a matrix-exposed domain attached to the membrane arm of mitochondrial complex I in plants . J Biol Chem 281 : 6482 – 6488 Google Scholar Crossref Search ADS PubMed WorldCat Tomaz T , Bagard M, Pracharoenwattana I, Lindén P, Lee CP, Carroll AJ, Ströher E, Smith SM, Gardeström P, Millar AH ( 2010 ) Mitochondrial malate dehydrogenase lowers leaf respiration and alters photorespiration and plant growth in Arabidopsis . Plant Physiol 154 : 1143 – 1157 Google Scholar Crossref Search ADS PubMed WorldCat Turano FJ , Dashner R, Upadhyaya A, Caldwell CR ( 1996 ) Purfication of mitochondrial glutamate dehydrogenase from dark-grown soybean seedlings . Plant Physiol 112 : 1357 – 1364 Google Scholar Crossref Search ADS PubMed WorldCat Tyanova S , Temu T, Sinitcyn P, Carlson A, Hein MY, Geiger T, Mann M, Cox J ( 2016 ) The Perseus computational platform for comprehensive analysis of (prote)omics data . Nat Methods 13 : 731 – 740 Google Scholar Crossref Search ADS PubMed WorldCat Voll LM , Jamai A, Renné P, Voll H, McClung CR, Weber APM ( 2006 ) The photorespiratory Arabidopsis shm1 mutant is deficient in SHM1 . Plant Physiol 140 : 59 – 66 Google Scholar Crossref Search ADS PubMed WorldCat Werhahn W , Jänsch L, Braun HP ( 2003 ) Identification of novel subunits of the TOM complex from Arabidopsis thaliana . Plant Physiol Biochem 41 : 407 – 416 Google Scholar Crossref Search ADS WorldCat Werhahn W , Niemeyer A, Jänsch L, Kruft V, Schmitz UK, Braun H ( 2001 ) Purification and characterization of the preprotein translocase of the outer mitochondrial membrane from Arabidopsis. Identification of multiple forms of TOM20 . Plant Physiol 125 : 943 – 954 Google Scholar Crossref Search ADS PubMed WorldCat Wiedemann N , Frazier AE, Pfanner N ( 2004 ) The protein import machinery of mitochondria . J Biol Chem 279 : 14473 – 14476 Google Scholar Crossref Search ADS PubMed WorldCat Wilkie SE , Warren MJ ( 1998 ) Recombinant expression, purification, and characterization of three isoenzymes of aspartate aminotransferase from Arabidopsis thaliana . Protein Expr Purif 12 : 381 – 389 Google Scholar Crossref Search ADS PubMed WorldCat Yang Y , Costa A, Leonhardt N, Siegel RS, Schroeder JI ( 2008 ) Isolation of a strong Arabidopsis guard cell promoter and its potential as a research tool . Plant Methods 4 : 6 Google Scholar Crossref Search ADS PubMed WorldCat Author notes 1 This work was supported by the Deutsche Forschungsgemeinschaft (CRC 1208; and funding under Germany’s Excellence Strategy [EXC-2048/1 - project ID 390686111]). [OPEN] Articles can be viewed without a subscription. 3 Senior author. The author responsible for distribution of materials integral to the findings presented in this article in accordance with the policy described in the Instructions for Authors (www.plantphysiol.org) is: Andreas P.M. Weber ([email protected]). F.K. generated transgenic lines harboring affinity-tagged mitochondria, isolated mitochondria, analyzed the data, and drafted the manuscript; A.S., N.O., and K.S. performed the proteomics analysis and analyzed the data; L.D. and A.S.R. assisted with the Seahorse Analyzer measurements; A.P.M.W. conceived and supervised the experiments and contributed to the writing of the manuscript. www.plantphysiol.org/cgi/doi/10.1104/pp.19.00732 © 2020 American Society of Plant Biologists. All Rights Reserved. © The Author(s) 2020. Published by Oxford University Press on behalf of American Society of Plant Biologists. 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