The Arabidopsis PeptideAtlas: Harnessing worldwide proteomics data to create a comprehensive community proteomics resource

Deep proteomics reveals incorporation of unedited proteins into mitochondrial protein complexes in Arabidopsis

The mitochondrial proteome consists of numerous types of proteins which either are encoded and synthesized in the mitochondria, or encoded in the cell nucleus, synthesized in the cytoplasm and imported into the mitochondria. Their synthesis in the mitochondria, but not in the nucleus, relies on the editing of the primary transcripts of their genes at defined sites. Here, we present an in-depth investigation of the mitochondrial proteome of Arabidopsis (Arabidopsis thaliana) and a public online platform for the exploration of the data. For the analysis of our shotgun proteomic data, an Arabidopsis sequence database was created comprising all available protein sequences from the TAIR10 and Araport11 databases, supplemented with sequences of proteins translated from edited and nonedited transcripts of mitochondria. Amino acid sequences derived from partially edited transcripts were also added to analyze proteins encoded by the mitochondrial genome. Proteins were digested in parallel with six different endoproteases to obtain maximum proteome coverage. The resulting peptide fractions were finally analyzed using liquid chromatography coupled to ion mobility spectrometry and tandem mass spectrometry. We generated a "deep mitochondrial proteome" of 4,692 proteins. 1,339 proteins assigned to mitochondria by the SUBA5 database (https://suba.live) accounted for >80% of the total protein mass of our fractions. The coverage of proteins by identified peptides was particularly high compared to single-protease digests, allowing the exploration of differential splicing and RNA editing events at the protein level. We show that proteins translated from nonedited transcripts can be incorporated into native mitoribosomes and the ATP synthase complex. We present a portal for the use of our data, based on "proteomaps" with directly linked protein data. The portal is available at www.proteomeexplorer.de.

Meta-Analysis of Rice Phosphoproteomics Data to Understand Variation in Cell Signaling Across the Rice Pan-Genome

Phosphorylation is the most studied post-translational modification, and has multiple biological functions. In this study, we have reanalyzed publicly available mass spectrometry proteomics data sets enriched for phosphopeptides from Asian rice (Oryza sativa). In total we identified 15,565 phosphosites on serine, threonine, and tyrosine residues on rice proteins. We identified sequence motifs for phosphosites, and link motifs to enrichment of different biological processes, indicating different downstream regulation likely caused by different kinase groups. We cross-referenced phosphosites against the rice 3,000 genomes, to identify single amino acid variations (SAAVs) within or proximal to phosphosites that could cause loss of a site in a given rice variety and clustered the data to identify groups of sites with similar patterns across rice family groups. The data has been loaded into UniProt Knowledge-Base─enabling researchers to visualize sites alongside other data on rice proteins, e.g., structural models from AlphaFold2, PeptideAtlas, and the PRIDE database─enabling visualization of source evidence, including scores and supporting mass spectra.

Plant genome information facilitates plant functional genomics

MAIN CONCLUSION

In this review, we give an overview of plant sequencing efforts and how this impacts plant functional genomics research. Plant genome sequence information greatly facilitates the studies of plant biology, functional genomics, evolution of genomes and genes, domestication processes, phylogenetic relationships, among many others. More than two decades of sequencing efforts have boosted the number of available sequenced plant genomes. The first plant genome, of Arabidopsis, was published in the year 2000 and currently, 4604 plant genomes from 1482 plant species have been published. Various large sequence initiatives are running, which are planning to produce tens of thousands of sequenced plant genomes in the near future. In this review, we give an overview on the status of sequenced plant genomes and on the use of genome information in different research areas.

Proteomic Analysis of Salivary Extracellular Vesicles from COVID-19 Patients Reveals a Specific Anti-COVID-19 Response Protein Signature

Despite the understanding of the coronavirus disease-19 (COVID-19), the role of salivary extracellular vesicles (sEVs) in COVID-19 remains unclear. Exploring the proteomic cargo of sEVs could prove valuable for diagnostic and prognostic purposes in assessing COVID-19. The proteomic cargo of sEVs from COVID-19(+) subjects and their healthy close contacts (HCC) was explored. sEVs were isolated by ultracentrifugation from unstimulated saliva samples, and subsequently characterized through nanoparticle tracking, transmission electron microscopy, and Western blot analyses. The proteomic cargo of sEVs was processed by LC-MS/MS. sEVs were morphologically compatible with EVs, with the presence of Syntenin-1 and CD81 EV markers. The sEV pellet showed 1417 proteins: 1288 in COVID-19(+) cases and 1382 in HCC. In total, 124 proteins were differentially expressed in sEVs from COVID-19(+) subjects. "Coronavirus-disease response", "complement and coagulation cascades", and "PMN extracellular trap formation" were the most enriched KEGG pathways in COVID-19(+) cases. The most represented biological processes were "Hemoglobin and haptoglobin binding" and "oxygen carrier activity", and the best-denoted molecular functions were "regulated exocytosis and secretion" and "leucocyte and PMN mediated immunity". sEV proteomic cargo in COVID-19(+) suggests activity related to immune response processes, oxygen transport, and antioxidant mechanisms. In contrast, in HCC, sEV signature profiles are mainly associated with epithelial homeostasis.

Chloroplast ion homeostasis - what do we know and where should we go?

Plant yields heavily depend on proper macro- and micronutrient supply from the soil. In the leaf cells, nutrient ions fulfill specific roles in biochemical reactions, especially photosynthesis housed in the chloroplast. Here, a well-balanced ion homeostasis is maintained by a number of ion transport proteins embedded in the envelope and thylakoid membranes. Ten years ago, the first alkali metal transporters from the K+ EFFLUX ANTIPORTER family were discovered in the model plant Arabidopsis. Since then, our knowledge about the physiological importance of these carriers and their substrates has greatly expanded. New insights into the role of alkali ions in plastid gene expression and photoprotective mechanisms, both prerequisites for plant productivity in natural environments, were gained. The discovery of a Cl- channel in the thylakoid and several additional plastid alkali and alkali metal transport proteins have advanced the field further. Nevertheless, scientists still have long ways to go before a complete systemic understanding of the chloroplast's ion transportome will emerge. In this Tansley review, we highlight and discuss the achievements of the last decade. More importantly, we make recommendations on what areas to prioritize, so the field can reach the next milestones. One area, laid bare by our similarity-based comparisons among phototrophs is our lack of knowledge what ion transporters are used by cyanobacteria to buffer photosynthesis fluctuations.

Detection and editing of the updated Arabidopsis plastid- and mitochondrial-encoded proteomes through PeptideAtlas

Arabidopsis (Arabidopsis thaliana) ecotype Col-0 has plastid and mitochondrial genomes encoding over 100 proteins. Public databases (e.g. Araport11) have redundancy and discrepancies in gene identifiers for these organelle-encoded proteins. RNA editing results in changes to specific amino acid residues or creation of start and stop codons for many of these proteins, but the impact of RNA editing at the protein level is largely unexplored due to the complexities of detection. Here, we assembled the nonredundant set of identifiers, their correct protein sequences, and 452 predicted nonsynonymous editing sites of which 56 are edited at lower frequency. We then determined accumulation of edited and/or unedited proteoforms by searching ∼259 million raw tandem MS spectra from ProteomeXchange, which is part of PeptideAtlas (www.peptideatlas.org/builds/arabidopsis/). We identified all mitochondrial proteins and all except 3 plastid-encoded proteins (NdhG/Ndh6, PsbM, and Rps16), but no proteins predicted from the 4 ORFs were identified. We suggest that Rps16 and 3 of the ORFs are pseudogenes. Detection frequencies for each edit site and type of edit (e.g. S to L/F) were determined at the protein level, cross-referenced against the metadata (e.g. tissue), and evaluated for technical detection challenges. We detected 167 predicted edit sites at the proteome level. Minor frequency sites were edited at low frequency at the protein level except for cytochrome C biogenesis 382 at residue 124 (Ccb382-124). Major frequency sites (>50% editing of RNA) only accumulated in edited form (>98% to 100% edited) at the protein level, with the exception of Rpl5-22. We conclude that RNA editing for major editing sites is required for stable protein accumulation.

Detection of the Arabidopsis Proteome and Its Post-translational Modifications and the Nature of the Unobserved (Dark) Proteome in PeptideAtlas

This study describes a new release of the Arabidopsis thaliana PeptideAtlas proteomics resource (build 2023-10) providing protein sequence coverage, matched mass spectrometry (MS) spectra, selected post-translational modifications (PTMs), and metadata. 70 million MS/MS spectra were matched to the Araport11 annotation, identifying ∼0.6 million unique peptides and 18,267 proteins at the highest confidence level and 3396 lower confidence proteins, together representing 78.6% of the predicted proteome. Additional identified proteins not predicted in Araport11 should be considered for the next Arabidopsis genome annotation. This release identified 5198 phosphorylated proteins, 668 ubiquitinated proteins, 3050 N-terminally acetylated proteins, and 864 lysine-acetylated proteins and mapped their PTM sites. MS support was lacking for 21.4% (5896 proteins) of the predicted Araport11 proteome: the "dark" proteome. This dark proteome is highly enriched for E3 ligases, transcription factors, and for certain (e.g., CLE, IDA, PSY) but not other (e.g., THIONIN, CAP) signaling peptides families. A machine learning model trained on RNA expression data and protein properties predicts the probability that proteins will be detected. The model aids in discovery of proteins with short half-life (e.g., SIG1,3 and ERF-VII TFs) and for developing strategies to identify the missing proteins. PeptideAtlas is linked to TAIR, tracks in JBrowse, and several other community proteomics resources.

The Main Functions of Plastids

Plastids are semi-autonomous organelles like mitochondria and derive from a cyanobacterial ancestor that was engulfed by a host cell. During evolution, they have recruited proteins originating from the nuclear genome, and only parts of their ancestral metabolic properties were conserved and optimized to limit functional redundancy with other cell compartments. Furthermore, large disparities in metabolic functions exist among various types of plastids, and the characterization of their various metabolic properties is far from being accomplished. In this review, we provide an overview of the main functions, known to be achieved by plastids or shared by plastids and other compartments of the cell. In short, plastids appear at the heart of all main plant functions.

The long non-coding RNA LINDA restrains cellular collapse following DNA damage in Arabidopsis thaliana

The genomic integrity of every organism is endangered by various intrinsic and extrinsic stresses. To maintain genomic integrity, a sophisticated DNA damage response (DDR) network is activated rapidly after DNA damage. Notably, the fundamental DDR mechanisms are conserved in eukaryotes. However, knowledge about many regulatory aspects of the plant DDR is still limited. Important, yet little understood, regulatory factors of the DDR are the long non-coding RNAs (lncRNAs). In humans, 13 lncRNAs functioning in DDR have been characterized to date, whereas no such lncRNAs have been characterized in plants yet. By meta-analysis, we identified the putative long intergenic non-coding RNA induced by DNA damage (LINDA) that responds strongly to various DNA double-strand break-inducing treatments, but not to replication stress induced by mitomycin C. After DNA damage, LINDA is rapidly induced in an ATM- and SOG1-dependent manner. Intriguingly, the transcriptional response of LINDA to DNA damage is similar to that of its flanking hypothetical protein-encoding gene. Phylogenetic analysis of putative Brassicales and Malvales LINDA homologs indicates that LINDA lncRNAs originate from duplication of a flanking small protein-encoding gene followed by pseudogenization. We demonstrate that LINDA is not only needed for the regulation of this flanking gene but also fine-tuning of the DDR after the occurrence of DNA double-strand breaks. Moreover, Δlinda mutant root stem cells are unable to recover from DNA damage, most likely due to hyper-induced cell death.

A meta-analysis of rice phosphoproteomics data to understand variation in cell signalling across the rice pan-genome

Phosphorylation is the most studied post-translational modification, and has multiple biological functions. In this study, we have re-analysed publicly available mass spectrometry proteomics datasets enriched for phosphopeptides from Asian rice (Oryza sativa). In total we identified 15,522 phosphosites on serine, threonine and tyrosine residues on rice proteins. We identified sequence motifs for phosphosites, and link motifs to enrichment of different biological processes, indicating different downstream regulation likely caused by different kinase groups. We cross-referenced phosphosites against the rice 3,000 genomes, to identify single amino acid variations (SAAVs) within or proximal to phosphosites that could cause loss of a site in a given rice variety. The data was clustered to identify groups of sites with similar patterns across rice family groups, for example those highly conserved in Japonica, but mostly absent in Aus type rice varieties - known to have different responses to drought. These resources can assist rice researchers to discover alleles with significantly different functional effects across rice varieties. The data has been loaded into UniProt Knowledge-Base - enabling researchers to visualise sites alongside other data on rice proteins e.g. structural models from AlphaFold2, PeptideAtlas and the PRIDE database - enabling visualisation of source evidence, including scores and supporting mass spectra.

How metabolism and development are intertwined in space and time

Developmental transitions, occurring throughout the life cycle of plants, require precise regulation of metabolic processes to generate the energy and resources necessary for the committed growth processes. In parallel, the establishment of new cells, tissues, and even organs, alongside their differentiation provoke profound changes in metabolism. It is increasingly being recognized that there is a certain degree of feedback regulation between the components and products of metabolic pathways and developmental regulators. The generation of large-scale metabolomics datasets during developmental transitions, in combination with molecular genetic approaches has helped to further our knowledge on the functional importance of metabolic regulation of development. In this perspective article, we provide insights into studies that elucidate interactions between metabolism and development at the temporal and spatial scales. We additionally discuss how this influences cell growth-related processes. We also highlight how metabolic intermediates function as signaling molecules to direct plant development in response to changing internal and external conditions.

Shining in the dark: the big world of small peptides in plants

Small peptides represent a subset of dark matter in plant proteomes. Through differential expression patterns and modes of action, small peptides act as important regulators of plant growth and development. Over the past 20 years, many small peptides have been identified due to technical advances in genome sequencing, bioinformatics, and chemical biology. In this article, we summarize the classification of plant small peptides and experimental strategies used to identify them as well as their potential use in agronomic breeding. We review the biological functions and molecular mechanisms of small peptides in plants, discuss current problems in small peptide research and highlight future research directions in this field. Our review provides crucial insight into small peptides in plants and will contribute to a better understanding of their potential roles in biotechnology and agriculture.

Analysis of state 1-state 2 transitions by genome editing and complementation reveals a quenching component independent from the formation of PSI-LHCI-LHCII supercomplex in Arabidopsis thaliana

BACKGROUND

The light-harvesting antennae of photosystem (PS) I and PSII are pigment-protein complexes responsible of the initial steps of sunlight conversion into chemical energy. In natural environments plants are constantly confronted with the variability of the photosynthetically active light spectrum. PSII and PSI operate in series but have different optimal excitation wavelengths. The prompt adjustment of light absorption by photosystems is thus crucial to ensure efficient electron flow needed to sustain downstream carbon fixing reactions. Fast structural rearrangements equilibrate the partition of excitation pressure between PSII and PSI following the enrichment in the red (PSII-favoring) or far-red (PSI-favoring) spectra. Redox imbalances trigger state transitions (ST), a photoacclimation mechanism which involves the reversible phosphorylation/dephosphorylation of light harvesting complex II (LHCII) proteins by the antagonistic activities of the State Transition 7 (STN7) kinase/TAP38 phosphatase enzyme pair. During ST, a mobile PSII antenna pool associates with PSI increasing its absorption cross section. LHCII consists of assorted trimeric assemblies of Lhcb1, Lhcb2 and Lhcb3 protein isoforms (LHCII), several being substrates of STN7. However, the precise roles of Lhcb phosphorylation during ST remain largely elusive.

RESULTS

We inactivated the complete Lhcb1 and Lhcb2 gene clades in Arabidopsis thaliana and reintroduced either wild type Lhcb1.3 and Lhcb2.1 isoforms, respectively, or versions lacking N-terminal phosphorylatable residues proposed to mediate state transitions. While the substitution of Lhcb2.1 Thr-40 prevented the formation of the PSI-LHCI-LHCII complex, replacement of Lhcb1.3 Thr-38 did not affect the formation of this supercomplex, nor did influence the amplitude or kinetics of PSII fluorescence quenching upon state 1-state 2 transition.

CONCLUSIONS

Phosphorylation of Lhcb2 Thr-40 by STN7 alone accounts for ≈ 60% of PSII fluorescence quenching during state transitions. Instead, the presence of Thr-38 phosphosite in Lhcb1.3 was not required for the formation of the PSI-LHCI-LHCII supercomplex nor for re-equilibration of the plastoquinone redox state. The Lhcb2 phosphomutant was still capable of ≈ 40% residual fluorescence quenching, implying that a yet uncharacterized, STN7-dependent, component of state transitions, which is unrelated to Lhcb2 Thr-40 phosphorylation and to the formation of the PSI-LHCI-LHCII supercomplex, contributes to the equilibration of the PSI/PSII excitation pressure upon plastoquinone over-reduction.

Mapping the Arabidopsis thaliana proteome in PeptideAtlas and the nature of the unobserved (dark) proteome; strategies towards a complete proteome

This study describes a new release of the Arabidopsis thaliana PeptideAtlas proteomics resource providing protein sequence coverage, matched mass spectrometry (MS) spectra, selected PTMs, and metadata. 70 million MS/MS spectra were matched to the Araport11 annotation, identifying ∼0.6 million unique peptides and 18267 proteins at the highest confidence level and 3396 lower confidence proteins, together representing 78.6% of the predicted proteome. Additional identified proteins not predicted in Araport11 should be considered for building the next Arabidopsis genome annotation. This release identified 5198 phosphorylated proteins, 668 ubiquitinated proteins, 3050 N-terminally acetylated proteins and 864 lysine-acetylated proteins and mapped their PTM sites. MS support was lacking for 21.4% (5896 proteins) of the predicted Araport11 proteome - the 'dark' proteome. This dark proteome is highly enriched for certain ( e.g. CLE, CEP, IDA, PSY) but not other ( e.g. THIONIN, CAP,) signaling peptides families, E3 ligases, TFs, and other proteins with unfavorable physicochemical properties. A machine learning model trained on RNA expression data and protein properties predicts the probability for proteins to be detected. The model aids in discovery of proteins with short-half life ( e.g. SIG1,3 and ERF-VII TFs) and completing the proteome. PeptideAtlas is linked to TAIR, JBrowse, PPDB, SUBA, UniProtKB and Plant PTM Viewer.

Expanding our coverage: Strategies to detect a greater range of metabolites

Whilst the study of metabolites can arguably be traced back several hundred years it began in earnest in the 20th century with studies based on single metabolites or simple metabolic pathways. The advent of metabolomics and in particular the adoption of high-resolution mass spectrometry now means we can faithfully annotate and quantify in excess of 1000 plant metabolites. Whilst this is an impressive leap it falls well short of the estimated number of metabolites in the plant kingdom. This, whilst considerable and important insights have been achieved using commonly utilized approaches, there is a need to improve the coverage of the metabolome. Here, we review three largely complementary strategies (i) methods based on using chemical libraries (ii) methods based on molecular networking and (iii) approaches that link metabolomics and genetic variance. It is our contention that using all three approaches in tandem represents the best approach to tackle this challenge.

High-throughput proteomics profiling-derived signature associated with chemotherapy response and survival for stage II/III colorectal cancer

Adjuvant chemotherapy (ACT) is usually used to reduce the risk of disease relapse and improve survival for stage II/III colorectal cancer (CRC). However, only a subset of patients could benefit from ACT. Thus, there is an urgent need to identify improved biomarkers to predict survival and stratify patients to refine the selection of ACT. We used high-throughput proteomics to analyze tumor and adjacent normal tissues of stage II/III CRC patients with /without relapse to identify potential markers for predicting prognosis and benefit from ACT. The machine learning approach was applied to identify relapse-specific markers. Then the artificial intelligence (AI)-assisted multiplex IHC was performed to validate the prognostic value of the relapse-specific markers and construct a proteomic-derived classifier for stage II/III CRC using 3 markers, including FHL3, GGA1, TGFBI. The proteomics profiling-derived signature for stage II/III CRC (PS) not only shows good accuracy to classify patients into high and low risk of relapse and mortality in all three cohorts, but also works independently of clinicopathologic features. ACT was associated with improved disease-free survival (DFS) and overall survival (OS) in stage II (pN0) patients with high PS and pN2 patients with high PS. This study demonstrated the clinical significance of proteomic features, which serve as a valuable source for potential biomarkers. The PS classifier provides prognostic value for identifying patients at high risk of relapse and mortality and optimizes individualized treatment strategy by detecting patients who may benefit from ACT for survival.

Does the Ubiquitination Degradation Pathway Really Reach inside of the Chloroplast? A Re-Evaluation of Mass Spectrometry-Based Assignments of Ubiquitination

A recent paper in Science Advances by Sun et al. claims that intra-chloroplast proteins in the model plant Arabidopsis can be polyubiquitinated and then extracted into the cytosol for subsequent degradation by the proteasome. Most of this conclusion hinges on several sets of mass spectrometry (MS) data. If the proposed results and conclusion are true, this would be a major change in the proteolysis/proteostasis field, breaking the long-standing dogma that there are no polyubiquitination mechanisms within chloroplast organelles (nor in mitochondria). Given its importance, we reanalyzed their raw MS data using both open and closed sequence database searches and encountered many issues not only with the results but also discrepancies between stated methods (e.g., use of alkylating agent iodoacetamide (IAA)) and observed mass modifications. Although there is likely enrichment of ubiquitination signatures in a subset of the data (probably from ubiquitination in the cytosol), we show that runaway alkylation with IAA caused extensive artifactual modifications of N termini and lysines to the point that a large fraction of the desired ubiquitination signatures is indistinguishable from artifactual acetamide signatures, and thus, no intra-chloroplast polyubiquitination conclusions can be drawn from these data. We provide recommendations on how to avoid such perils in future work.

PAT1-type GRAS-domain proteins control regeneration by activating DOF3.4 to drive cell proliferation in Arabidopsis roots

Plant roots possess remarkable regenerative potential owing to their ability to replenish damaged or lost stem cells. ETHYLENE RESPONSE FACTOR 115 (ERF115), one of the key molecular elements linked to this potential, plays a predominant role in the activation of regenerative cell divisions. However, the downstream operating molecular machinery driving wound-activated cell division is largely unknown. Here, we biochemically and genetically identified the GRAS-domain transcription factor SCARECROW-LIKE 5 (SCL5) as an interaction partner of ERF115 in Arabidopsis thaliana. Although nonessential under control growth conditions, SCL5 acts redundantly with the related PHYTOCHROME A SIGNAL TRANSDUCTION 1 (PAT1) and SCL21 transcription factors to activate the expression of the DNA-BINDING ONE FINGER 3.4 (DOF3.4) transcription factor gene. DOF3.4 expression is wound-inducible in an ERF115-dependent manner and, in turn, activates D3-type cyclin expression. Accordingly, ectopic DOF3.4 expression drives periclinal cell division, while its downstream D3-type cyclins are essential for the regeneration of a damaged root. Our data highlight the importance and redundant roles of the SCL5, SCL21, and PAT1 transcription factors in wound-activated regeneration processes and pinpoint DOF3.4 as a key downstream element driving regenerative cell division.

FungiProteomeDB: a database for the molecular weight and isoelectric points of the fungal proteomes

Proteins' molecular weight (MW) and isoelectric point (pI) are crucial for their subcellular localization and subsequent function. These are also useful in 2D gel electrophoresis, liquid chromatography-mass spectrometry and X-ray protein crystallography. Moreover, visualizations like a virtual 2D proteome map of pI vs. MW are worthwhile to discuss the proteome diversity among different species. Although the genome sequence data of the fungi kingdom improved enormously, the proteomic details have been poorly elaborated. Therefore, we have calculated the MW and pI of the fungi proteins and reported them in, FungiProteomeDB, an online database (DB) https://vision4research.com/fungidb/. We analyzed the proteome of 685 fungal species that contain 7 127 141 protein sequences. The DB provides an easy-to-use and efficient interface for various search options, summary statistics and virtual 2D proteome map visualizations. The MW and pI of a protein can be obtained by searching the name of a protein, a keyword or a list of accession numbers. It also allows querying protein sequences. The DB will be helpful in hypothesis formulation and in various biotechnological applications. Database URL https://vision4research.com/fungidb/.

Patpat: a public proteomics dataset search framework

SUMMARY

As the FAIR (Findable, Accessible, Interoperable, Reusable) principles have become widely accepted in the proteomics field, under the guidance of ProteomeXchange and The Human Proteome Organization Proteomics Standards Initiative, proteomics public databases have been providing Application Programming Interfaces for programmatic access. Based on generating logic from proteomics data, we present Patpat, an extensible framework for searching public datasets, merging results from multiple databases to help researchers find their proteins of interest in the vast mass spectrometry. Patpat's 2D strategy of combining results from multiple databases allows users to provide only protein identifiers to obtain metadata for relevant datasets, improving the 'Findable' of proteomics data.

AVAILABILITY AND IMPLEMENTATION

The Patpat framework is released under the Apache 2.0 license open source, and the source code is stored on GitHub (https://github.com/henry-leo/Patpat) and is freely available.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

ProteomicsML: An Online Platform for Community-Curated Data sets and Tutorials for Machine Learning in Proteomics

Data set acquisition and curation are often the most difficult and time-consuming parts of a machine learning endeavor. This is especially true for proteomics-based liquid chromatography (LC) coupled to mass spectrometry (MS) data sets, due to the high levels of data reduction that occur between raw data and machine learning-ready data. Since predictive proteomics is an emerging field, when predicting peptide behavior in LC-MS setups, each lab often uses unique and complex data processing pipelines in order to maximize performance, at the cost of accessibility and reproducibility. For this reason we introduce ProteomicsML, an online resource for proteomics-based data sets and tutorials across most of the currently explored physicochemical peptide properties. This community-driven resource makes it simple to access data in easy-to-process formats, and contains easy-to-follow tutorials that allow new users to interact with even the most advanced algorithms in the field. ProteomicsML provides data sets that are useful for comparing state-of-the-art machine learning algorithms, as well as providing introductory material for teachers and newcomers to the field alike. The platform is freely available at https://www.proteomicsml.org/, and we welcome the entire proteomics community to contribute to the project at https://github.com/ProteomicsML/ProteomicsML.

A deeply conserved protease, acylamino acid-releasing enzyme (AARE), acts in ageing in Physcomitrella and Arabidopsis

Reactive oxygen species (ROS) are constant by-products of aerobic life. In excess, ROS lead to cytotoxic protein aggregates, which are a hallmark of ageing in animals and linked to age-related pathologies in humans. Acylamino acid-releasing enzymes (AARE) are bifunctional serine proteases, acting on oxidized proteins. AARE are found in all domains of life, albeit under different names, such as acylpeptide hydrolase (APEH/ACPH), acylaminoacyl peptidase (AAP), or oxidized protein hydrolase (OPH). In humans, AARE malfunction is associated with age-related pathologies, while their function in plants is less clear. Here, we provide a detailed analysis of AARE genes in the plant lineage and an in-depth analysis of AARE localization and function in the moss Physcomitrella and the angiosperm Arabidopsis. AARE loss-of-function mutants have not been described for any organism so far. We generated and analysed such mutants and describe a connection between AARE function, aggregation of oxidized proteins and plant ageing, including accelerated developmental progression and reduced life span. Our findings complement similar findings in animals and humans, and suggest a unified concept of ageing may exist in different life forms.

The ProteomeXchange consortium at 10 years: 2023 update

Mass spectrometry (MS) is by far the most used experimental approach in high-throughput proteomics. The ProteomeXchange (PX) consortium of proteomics resources (http://www.proteomexchange.org) was originally set up to standardize data submission and dissemination of public MS proteomics data. It is now 10 years since the initial data workflow was implemented. In this manuscript, we describe the main developments in PX since the previous update manuscript in Nucleic Acids Research was published in 2020. The six members of the Consortium are PRIDE, PeptideAtlas (including PASSEL), MassIVE, jPOST, iProX and Panorama Public. We report the current data submission statistics, showcasing that the number of datasets submitted to PX resources has continued to increase every year. As of June 2022, more than 34 233 datasets had been submitted to PX resources, and from those, 20 062 (58.6%) just in the last three years. We also report the development of the Universal Spectrum Identifiers and the improvements in capturing the experimental metadata annotations. In parallel, we highlight that data re-use activities of public datasets continue to increase, enabling connections between PX resources and other popular bioinformatics resources, novel research and also new data resources. Finally, we summarise the current state-of-the-art in data management practices for sensitive human (clinical) proteomics data.

Thirty years of molecular dynamics simulations on posttranslational modifications of proteins

Posttranslational modifications (PTMs) are an integral component to how cells respond to perturbation. While experimental advances have enabled improved PTM identification capabilities, the same throughput for characterizing how structural changes caused by PTMs equate to altered physiological function has not been maintained. In this Perspective, we cover the history of computational modeling and molecular dynamics simulations which have characterized the structural implications of PTMs. We distinguish results from different molecular dynamics studies based upon the timescales simulated and analysis approaches used for PTM characterization. Lastly, we offer insights into how opportunities for modern research efforts on in silico PTM characterization may proceed given current state-of-the-art computing capabilities and methodological advancements.

Proteomic repository data submission, dissemination, and reuse: key messages

INTRODUCTION

The creation of ProteomeXchange data workflows in 2012 transformed the field of proteomics, consisting of the standardization of data submission and dissemination and enabling the widespread reanalysis of public MS proteomics data worldwide. ProteomeXchange has triggered a growing trend toward public dissemination of proteomics data, facilitating the assessment, reuse, comparative analyses, and extraction of new findings from public datasets. By 2022, the consortium is integrated by PRIDE, PeptideAtlas, MassIVE, jPOST, iProX, and Panorama Public.

AREAS COVERED

Here, we review and discuss the current ecosystem of resources, guidelines, and file formats for proteomics data dissemination and reanalysis. Special attention is drawn to new exciting quantitative and post-translational modification-oriented resources. The challenges and future directions on data depositions including the lack of metadata and cloud-based and high-performance software solutions for fast and reproducible reanalysis of the available data are discussed.

EXPERT OPINION

The success of ProteomeXchange and the amount of proteomics data available in the public domain have triggered the creation and/or growth of other protein knowledgebase resources. Data reuse is a leading, active, and evolving field; supporting the creation of new formats, tools, and workflows to rediscover and reshape the public proteomics data.

Regulation of heat shock proteins 70 and their role in plant immunity

Heat shock proteins 70 (HSP70s) are steadily gaining more attention in the field of plant biotic interactions. Though their regulation and activity in plants are much less well characterized than are those of their counterparts in mammals, accumulating evidence indicates that the role of HSP70-mediated defense mechanisms in plant cells is indispensable. In this review, we summarize current knowledge of HSP70 post-translational control in plants. We comment on the phytohormonal regulation of HSP70 expression and protein abundance, and identify a prominent role for cytokinin in HSP70 control. We outline HSP70s' subcellular localizations, chaperone activity, and chaperone-mediated protein degradation. We focus on the role of HSP70s in plant pathogen-associated molecular pattern-triggered immunity and effector-triggered immunity, and discuss the contribution of different HSP70 subfamilies to plant defense against pathogens.

A peroxisomal heterodimeric enzyme is involved in benzaldehyde synthesis in plants

Benzaldehyde, the simplest aromatic aldehyde, is one of the most wide-spread volatiles that serves as a pollinator attractant, flavor, and antifungal compound. However, the enzyme responsible for its formation in plants remains unknown. Using a combination of in vivo stable isotope labeling, classical biochemical, proteomics and genetic approaches, we show that in petunia benzaldehyde is synthesized via the β-oxidative pathway in peroxisomes by a heterodimeric enzyme consisting of α and β subunits, which belong to the NAD(P)-binding Rossmann-fold superfamily. Both subunits are alone catalytically inactive but, when mixed in equal amounts, form an active enzyme, which exhibits strict substrate specificity towards benzoyl-CoA and uses NADPH as a cofactor. Alpha subunits can form functional heterodimers with phylogenetically distant β subunits, but not all β subunits partner with α subunits, at least in Arabidopsis. Analysis of spatial, developmental and rhythmic expression of genes encoding α and β subunits revealed that expression of the gene for the α subunit likely plays a key role in regulating benzaldehyde biosynthesis.

Benzaldehyde is a simple aromatic aldehyde that attracts pollinators, has antifungal properties and contributes to flavor in many plants. Here the authors show that benzaldehyde is synthesized in petunia via the benzoic acid β-oxidative pathway by a peroxisomal heterodimeric enzyme consisting of α and β subunits.

The gene space of European mistletoe (Viscum album)

European mistletoe (Viscum album) is a hemiparasitic flowering plant that is known for its very special life cycle and extraordinary biochemical properties. Particularly, V. album has an unusual mode of cellular respiration that takes place in the absence of mitochondrial complex I. However, insights into the molecular biology of V. album so far are very limited. Since the genome of V. album is extremely large (estimated 600 times larger than the genome of the model plant Arabidopsis thaliana) it has not been sequenced up to now. We here report sequencing of the V. album gene space (defined as the space including and surrounding genic regions, encompassing coding as well as 5' and 3' non-coding regions). mRNA fractions were isolated from different V. album organs harvested in summer or winter and were analyzed via single-molecule real-time sequencing. We determined sequences of 39 092 distinct open reading frames encoding 32 064 V. album proteins (designated V. album protein space). Our data give new insights into the metabolism and molecular biology of V. album, including the biosynthesis of lectins and viscotoxins. The benefits of the V. album gene space information are demonstrated by re-evaluating mass spectrometry-based data of the V. album mitochondrial proteome, which previously had been evaluated using the A. thaliana genome sequence. Our re-examination allowed the additional identification of nearly 200 mitochondrial proteins, including four proteins related to complex I, which all have a secondary function not related to respiratory electron transport. The V. album gene space sequences are available at the NCBI.

Proteomics, phylogenetics, and co-expression analyses indicate novel interactions in the plastid CLP chaperone-protease system

The chloroplast chaperone CLPC1 unfolds and delivers substrates to the stromal CLPPRT protease complex for degradation. We previously used an in vivo trapping approach to identify interactors with CLPC1 in Arabidopsis thaliana by expressing a STREPII-tagged copy of CLPC1 mutated in its Walker B domains (CLPC1-TRAP) followed by affinity purification and mass spectrometry. To create a larger pool of candidate substrates, adaptors, or regulators, we carried out a far more sensitive and comprehensive in vivo protein trapping analysis. We identified 59 highly enriched CLPC1 protein interactors, in particular proteins belonging to families of unknown functions (DUF760, DUF179, DUF3143, UVR-DUF151, HugZ/DUF2470), as well as the UVR domain proteins EXE1 and EXE2 implicated in singlet oxygen damage and signaling. Phylogenetic and functional domain analyses identified other members of these families that appear to localize (nearly) exclusively to plastids. In addition, several of these DUF proteins are of very low abundance as determined through the Arabidopsis PeptideAtlas http://www.peptideatlas.org/builds/arabidopsis/ showing that enrichment in the CLPC1-TRAP was extremely selective. Evolutionary rate covariation indicated that the HugZ/DUF2470 family coevolved with the plastid CLP machinery suggesting functional and/or physical interactions. Finally, mRNA-based coexpression networks showed that all 12 CLP protease subunits tightly coexpressed as a single cluster with deep connections to DUF760-3. Coexpression modules for other trapped proteins suggested specific functions in biological processes, e.g., UVR2 and UVR3 were associated with extraplastidic degradation, whereas DUF760-6 is likely involved in senescence. This study provides a strong foundation for discovery of substrate selection by the chloroplast CLP protease system.

Advances and Utility of the Human Plasma Proteome

The study of proteins circulating in blood offers tremendous opportunities to diagnose, stratify, or possibly prevent diseases. With recent technological advances and the urgent need to understand the effects of COVID-19, the proteomic analysis of blood-derived serum and plasma has become even more important for studying human biology and pathophysiology. Here we provide views and perspectives about technological developments and possible clinical applications that use mass-spectrometry(MS)- or affinity-based methods. We discuss examples where plasma proteomics contributed valuable insights into SARS-CoV-2 infections, aging, and hemostasis and the opportunities offered by combining proteomics with genetic data. As a contribution to the Human Proteome Organization (HUPO) Human Plasma Proteome Project (HPPP), we present the Human Plasma PeptideAtlas build 2021-07 that comprises 4395 canonical and 1482 additional nonredundant human proteins detected in 240 MS-based experiments. In addition, we report the new Human Extracellular Vesicle PeptideAtlas 2021-06, which comprises five studies and 2757 canonical proteins detected in extracellular vesicles circulating in blood, of which 74% (2047) are in common with the plasma PeptideAtlas. Our overview summarizes the recent advances, impactful applications, and ongoing challenges for translating plasma proteomics into utility for precision medicine.