ProteomeXchange provides globally coordinated proteomics data submission and dissemination

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.

Coordinated reprogramming of renal cancer transcriptome, metabolome and secretome associates with immune tumor infiltration

BACKGROUND

Clear cell renal cell carcinoma (ccRCC) is the most common subtype of renal cancer. The molecules (proteins, metabolites) secreted by tumors affect their extracellular milieu to support cancer progression. If secreted in amounts detectable in plasma, these molecules can also serve as useful, minimal invasive biomarkers. The knowledge of ccRCC tumor microenvironment is fragmentary. In particular, the links between ccRCC transcriptome and the composition of extracellular milieu are weakly understood. In this study, we hypothesized that ccRCC transcriptome is reprogrammed to support alterations in tumor microenvironment. Therefore, we comprehensively analyzed ccRCC extracellular proteomes and metabolomes as well as transcriptomes of ccRCC cells to find molecules contributing to renal tumor microenvironment.

METHODS

Proteomic and metabolomics analysis of conditioned media isolated from normal kidney cells as well as five ccRCC cell lines was performed using mass spectrometry, with the following ELISA validation. Transcriptomic analysis was done using microarray analysis and validated using real-time PCR. Independent transcriptomic and proteomic datasets of ccRCC tumors were used for the analysis of gene and protein expression as well as the level of the immune infiltration.

RESULTS

Renal cancer secretome contained 85 proteins detectable in human plasma, consistently altered in all five tested ccRCC cell lines. The top upregulated extracellular proteins included SPARC, STC2, SERPINE1, TGFBI, while downregulated included transferrin and DPP7. The most affected extracellular metabolites were increased 4-hydroxy-proline, succinic acid, cysteine, lactic acid and downregulated glutamine. These changes were associated with altered expression of genes encoding the secreted proteins (SPARC, SERPINE1, STC2, DPP7), membrane transporters (SLC16A4, SLC6A20, ABCA12), and genes involved in protein trafficking and secretion (KIF20A, ANXA3, MIA2, PCSK5, SLC9A3R1, SYTL3, and WNTA7). Analogous expression changes were found in ccRCC tumors. The expression of SPARC predicted the infiltration of ccRCC tumors with endothelial cells. Analysis of the expression of the 85 secretome genes in > 12,000 tumors revealed that SPARC is a PanCancer indicator of cancer-associated fibroblasts' infiltration.

CONCLUSIONS

Transcriptomic reprogramming of ccRCC supports the changes in an extracellular milieu which are associated with immune infiltration. The proteins identified in our study represent valuable cancer biomarkers detectable in plasma.

Validation of MS/MS Identifications and Label-Free Quantification Using Proline

In the proteomics field, the production and publication of reliable mass spectrometry (MS)-based label-free quantitative results is a major concern. Due to the intrinsic complexity of bottom-up proteomics experiments (requiring aggregation of data relating to both precursor and fragment peptide ions into protein information, and matching this data across samples), inaccuracies and errors can occur throughout the data-processing pipeline. In a classical label-free quantification workflow, the validation of identification results is critical since errors made at this first stage of the workflow may have an impact on the following steps and therefore on the final result. Although false discovery rate (FDR) of the identification is usually controlled by using the popular target-decoy method, it has been demonstrated that this method can sometimes lead to inaccurate FDR estimates. This protocol shows how Proline can be used to validate identification results by using the method based on the Benjamini-Hochberg procedure and then quantify the identified ions and proteins in a single software environment providing data curation capabilities and computational efficiency.

Combination of Stable Isotope Labeling by Amino Acids in Cell Culture (SILAC) and Substrate Trapping for the Detection of Transient Protein Interactions

Antibody-based affinity purification is a recognized method for use in studying protein-protein interactions. There are four different classes of proteins that are typically identified with such affinity purification workflows: bait protein, proteins that specifically interact with the bait protein, proteins nonspecifically associated with the antibody, and proteins that cross-react with the antibody. Mass spectrometry can be used to differentiate these classes of proteins in affinity-purified mixtures. Here we describe the use of stable isotope labeling by amino acids in cell culture, substrate trapping, and mass spectrometry to enable the objective identification of the components of affinity-purified protein complexes.

Sialic acid-containing glycans play a role in the activity of snake venom proteases

Structural variability is a feature of snake venom proteins, and glycosylation is a post-translational modification that contributes to the diversification of venom proteomes. Studies by our group have shown that Bothrops venoms are distinctly defined by their glycoprotein content, and that most hybrid/complex N-glycans identified in these venoms contain sialic acid. Considering that metalloproteases and serine proteases are abundant components of Bothrops venoms and essential in the envenomation process, and that these enzymes contain several glycosylation sites, the role of sialic acid in venom proteolytic activity was evaluated. Here we show that removal of sialic acid by treatment of nine Bothrops venoms with neuraminidase (i) altered the pattern of gelatinolysis in zymography of most venoms and reduced the gelatinolytic activity of all venoms, (ii) decreased the proteolytic activity of some venoms on fibrinogen and the clotting activity of human plasma of all venoms, and (iii) altered the proteolysis profile of plasma proteins by B. jararaca venom, suggesting that sialic acid may play a role in the interaction of proteases with their protein substrates. In contrast, the profile of venom amidolytic activity on Bz-Arg-pNA did not change after removal of sialic acid, indicating that this monosaccharide is not essential in N-glycans of serine proteases acting on small substrates. In summary, these results expand the knowledge about the variability of the subproteomes of Bothrops venom proteases, and for the first time point to the importance of carbohydrate chains containing sialic acid in the enzymatic activities of venom proteases relevant in human envenomation.

Genetic code expansion reveals aminoacylated lysine ubiquitination mediated by UBE2W

Protein post-translational modification (PTM) regulates nearly every aspect of cellular processes in eukaryotes. However, the identification of new protein PTMs is very challenging. Here, using genetically encoded unnatural amino acids as chemical probes, we report the identification and validation of a previously unreported form of protein PTM, aminoacylated lysine ubiquitination, in which the modification occurs on the α-amine group of aminoacylated lysine. We identify more than 2,000 ubiquitination sites on all 20 aminoacylated lysines in two human cell lines. The modifications can mediate rapid protein degradation, complementing the canonical lysine ubiquitination-mediated proteome degradation. Furthermore, we demonstrate that the ubiquitin-conjugating enzyme UBE2W acts as a writer of aminoacylated lysine ubiquitination and facilitates the ubiquitination event on proteins. More broadly, the discovery and validation of aminoacylated lysine ubiquitination paves the way for the identification and verification of new protein PTMs with the genetic code expansion strategy.

Changes in the liver proteome in apoE knockout mice exposed to inhalation of silica nanoparticles indicate mitochondrial damage and impairment of ER stress responses associated with microvesicular steatosis

The adverse effects of air pollution on the cardiovascular system have been well documented. Nonalcoholic fatty liver disease (NAFLD) is an independent risk factor for cardiovascular events. However, the influence of exposure to airborne particles on the development of NAFLD is less recognised. The aim of this study was to investigate the impact of silica nanoparticles (SiNPs) on the development of liver steatosis. We used molecular and proteomic SWATH-MS methods to investigate the changes in the liver proteome of apolipoprotein E-knockout mice (apoE-/- mice) exposed to SiNPs for 4 months in a whole-body exposure chamber. Exposure to SiNPs evoked microvesicular liver steatosis in apoE-/- mice. Quantitative liver proteomics showed significant downregulation of ribosomal proteins and endoplasmic reticulum proteins. Gene expression analysis revealed a reduced level of proteins related to endoplasmic reticulum stress. Treatment with SiNPs decreased mitochondrial membrane potential and increased the production of reactive oxygen species in cultured HepG2 cells. This is the first report that inhalation exposure to SiNPs induces microvesicular steatosis and significant changes in the liver proteome in vivo. Our results highlight the important role of silica and point to the ER stress response and mitochondrial dysfunction as potential mechanisms responsible for the increase in fatty liver by SiNPs.

Data-Independent Acquisition (DIA) Is Superior for High Precision Phospho-Peptide Quantification in Magnaporthe oryzae

The dynamic interplay of signaling networks in most major cellular processes is characterized by the orchestration of reversible protein phosphorylation. Consequently, analytic methods such as quantitative phospho-peptidomics have been pushed forward from a highly specialized edge-technique to a powerful and versatile platform for comprehensively analyzing the phosphorylation profile of living organisms. Despite enormous progress in instrumentation and bioinformatics, a high number of missing values caused by the experimental procedure remains a major problem, due to either a random phospho-peptide enrichment selectivity or borderline signal intensities, which both cause the exclusion for fragmentation using the commonly applied data dependent acquisition (DDA) mode. Consequently, an incomplete dataset reduces confidence in the subsequent statistical bioinformatic processing. Here, we successfully applied data independent acquisition (DIA) by using the filamentous fungus Magnaporthe oryzae as a model organism, and could prove that while maintaining data quality (such as phosphosite and peptide sequence confidence), the data completeness increases dramatically. Since the method presented here reduces the LC-MS/MS analysis from 3 h to 1 h and increases the number of phosphosites identified up to 10-fold in contrast to published studies in Magnaporthe oryzae, we provide a refined methodology and a sophisticated resource for investigation of signaling processes in filamentous fungi.

Small molecule-induced epigenomic reprogramming of APL blasts leading to antiviral-like response and c-MYC downregulation

Acute promyelocytic leukemia (APL) is an aggressive subtype of acute myeloid leukemia (AML) in which the PML/RARα fusion protein exerts oncogenic activities by recruiting repressive complexes to the promoter of specific target genes. Other epigenetic perturbations, as alterations of histone H3 lysine 9 trimethylation (H3K9me3), have been frequently found in AMLs and are associated with leukemogenesis and leukemia progression. Here, we characterized the epigenomic effects of maltonis, a novel maltol-derived molecule, in APL cells. We demonstrate that maltonis treatments induce a profound remodulation of the histone code, reducing global H3K9me3 signal and modulating other histone post-translational modifications. Transcriptomic and epigenomic analyses revealed that maltonis exposure induces changes of genes expression associated with a genomic redistribution of histone H3 lysine 4 trimethylation (H3K4me3) and lysine 27 acetylation (H3K27ac). Upregulation of interferon alpha and gamma response and downregulation of c-MYC target genes, in function of c-MYC reduced expression (monitored in all the hematopoietic neoplasms tested), represent the most significant modulated pathways. These data demonstrate the ability of maltonis to epigenetically reprogram the gene expression profile of APL cells, inducing an intriguing antiviral-like response, concomitantly with the downregulation of c-MYC-related pathways, thus making it an attractive candidate for antileukemic therapy.

Proteomic profiling reveals mitochondrial dysfunction in the cerebellum of transgenic mice overexpressing DYRK1A, a Down syndrome candidate gene

Introduction

DYRK1A is a dual-specificity kinase that is overexpressed in Down syndrome (DS) and plays a key role in neurogenesis, neuronal differentiation and function, cognitive phenotypes, and aging. Dyrk1A has also been implicated in cerebellar abnormalities observed in association with DS, and normalization of Dyrk1A dosage rescues granular and Purkinje cell densities in a trisomic DS mouse model. However, the underlying molecular mechanisms governing these processes are unknown.

Methods

To shed light on the effects of Dyrk1A overexpression in the cerebellum, here we investigated the cerebellar proteome in transgenic Dyrk1A overexpressing mice in basal conditions and after treatment with green tea extract containing epigallocatechin-3-gallate (EGCG), a DYRK1A inhibitor.

Results and Discussion

Our results showed that Dyrk1A overexpression alters oxidative phosphorylation and mitochondrial function in the cerebellum of transgenic mice. These alterations are significantly rescued upon EGCG-containing green tea extract treatment, suggesting that its effects in DS could depend in part on targeting mitochondria, as shown by the partially restoration by the treatment of the increased mtDNA copy number in TG non-treated mice.

Engineered hydrogels for mechanobiology

Cells' local mechanical environment can be as important in guiding cellular responses as many well-characterized biochemical cues. Hydrogels that mimic the native extracellular matrix can provide these mechanical cues to encapsulated cells, allowing for the study of their impact on cellular behaviours. Moreover, by harnessing cellular responses to mechanical cues, hydrogels can be used to create tissues in vitro for regenerative medicine applications and for disease modelling. This Primer outlines the importance and challenges of creating hydrogels that mimic the mechanical and biological properties of the native extracellular matrix. The design of hydrogels for mechanobiology studies is discussed, including appropriate choice of cross-linking chemistry and strategies to tailor hydrogel mechanical cues. Techniques for characterizing hydrogels are explained, highlighting methods used to analyze cell behaviour. Example applications for studying fundamental mechanobiological processes and regenerative therapies are provided, along with a discussion of the limitations of hydrogels as mimetics of the native extracellular matrix. The article ends with an outlook for the field, focusing on emerging technologies that will enable new insights into mechanobiology and its role in tissue homeostasis and disease.

Proteomic Profiling Reveals the Molecular Control of Oocyte Maturation

Meiotic maturation is an intricate and precisely regulated process orchestrated by various pathways and numerous proteins. However, little is known about the proteome landscape during oocytes maturation. Here, we obtained the temporal proteomic profiles of mouse oocytes during in vivo maturation. We successfully quantified 4694 proteins from 4500 oocytes in three key stages (germinal vesicle, germinal vesicle breakdown, and metaphase II). In particular, we discovered the novel proteomic features during oocyte maturation, such as the active Skp1-Cullin-Fbox pathway and an increase in mRNA decay-related proteins. Using functional approaches, we further identified the key factors controlling the histone acetylation state in oocytes and the vital proteins modulating meiotic cell cycle. Taken together, our data serve as a broad resource on the dynamics occurring in oocyte proteome and provide important knowledge to better understand the molecular mechanisms during germ cell development.

Reversed-Phase Liquid Chromatography of Peptides for Bottom-Up Proteomics: A Tutorial

The performance of the current bottom-up liquid chromatography hyphenated with mass spectrometry (LC-MS) analyses has undoubtedly been fueled by spectacular progress in mass spectrometry. It is thus not surprising that the MS instrument attracts the most attention during LC-MS method development, whereas optimizing conditions for peptide separation using reversed-phase liquid chromatography (RPLC) remains somewhat in its shadow. Consequently, the wisdom of the fundaments of chromatography is slowly vanishing from some laboratories. However, the full potential of advanced MS instruments cannot be achieved without highly efficient RPLC. This is impossible to attain without understanding fundamental processes in the chromatographic system and the properties of peptides important for their chromatographic behavior. We wrote this tutorial intending to give practitioners an overview of critical aspects of peptide separation using RPLC to facilitate setting the LC parameters so that they can leverage the full capabilities of their MS instruments. After briefly introducing the gradient separation of peptides, we discuss their properties that affect the quality of LC-MS chromatograms the most. Next, we address the in-column and extra-column broadening. The last section is devoted to key parameters of LC-MS methods. We also extracted trends in practice from recent bottom-up proteomics studies and correlated them with the current knowledge on peptide RPLC separation.

Identification of Novel Kinases of Tau Using Fluorescence Complementation Mass Spectrometry (FCMS)

Hyperphosphorylation of the microtubule-associated protein Tau is a major hallmark of Alzheimer's disease and other tauopathies. Understanding the protein kinases that phosphorylate Tau is critical for the development of new drugs that target Tau phosphorylation. At present, the repertoire of the Tau kinases remains incomplete, and methods to uncover novel upstream protein kinases are still limited. Here, we apply our newly developed proteomic strategy, fluorescence complementation mass spectrometry, to identify novel kinase candidates of Tau. By constructing Tau- and kinase-fluorescent fragment library, we detected 59 Tau-associated kinases, including 23 known kinases of Tau and 36 novel candidate kinases. In the validation phase using in vitro phosphorylation, among 15 candidate kinases we attempted to purify and test, four candidate kinases, OXSR1 (oxidative-stress responsive gene 1), DAPK2 (death-associated protein kinase 2), CSK (C-terminal SRC kinase), and ZAP70 (zeta chain of T-cell receptor-associated protein kinase 70), displayed the ability to phosphorylate Tau in time-course experiments. Furthermore, coexpression of these four kinases along with Tau increased the phosphorylation of Tau in human neuroglioma H4 cells. We demonstrate that fluorescence complementation mass spectrometry is a powerful proteomic strategy to systematically identify potential kinases that can phosphorylate Tau in cells. Our discovery of new candidate kinases of Tau can present new opportunities for developing Alzheimer's disease therapeutic strategies.

The Brain Protein Atlas: A conglomerate of proteomics datasets of human neural tissue

The human brain represents one of the most complex biological structures with significant spatiotemporal molecular plasticity occurring through early development, learning, aging, and disease. While much progress has been made in mapping its transcriptional architecture, more downstream phenotypic readouts are relatively scarce due to limitations with tissue heterogeneity and accessibility, as well as an inability to amplify protein species prior to global -OMICS analysis. To address some of these barriers, our group has recently focused on using mass-spectrometry workflows compatible with small amounts of formalin-fixed paraffin-embedded tissue samples. This has enabled exploration into spatiotemporal proteomic signatures of the brain and disease across otherwise inaccessible neurodevelopmental timepoints and anatomical niches. Given the similar theme and approaches, we introduce an integrated online portal, "The Brain Protein Atlas (BPA)" (www.brainproteinatlas.org), representing a public resource that allows users to access and explore these amalgamated datasets. Specifically, this portal contains a growing set of peer-reviewed mass-spectrometry-based proteomic datasets, including spatiotemporal profiles of human cerebral development, diffuse gliomas, clinically aggressive meningiomas, and a detailed anatomic atlas of glioblastoma. One barrier to entry in mass spectrometry-based proteomics data analysis is the steep learning curve required to extract biologically relevant data. BPA, therefore, includes several built-in analytical tools to generate relevant plots (e.g., volcano plots, heatmaps, boxplots, and scatter plots) and evaluate the spatiotemporal patterns of proteins of interest. Future iterations aim to expand available datasets, including those generated by the community at large, and analytical tools for exploration. Ultimately, BPA aims to improve knowledge dissemination of proteomic information across the neuroscience community in hopes of accelerating the biological understanding of the brain and various maladies.

Integrated Transcriptomic and Proteomic Analysis Identifies Plasma Biomarkers of Hepatocellular Failure in Alcohol-Associated Hepatitis

Alcohol-associated hepatitis (AH) is a form of liver failure with high short-term mortality. Recent studies have shown that defective function of hepatocyte nuclear factor 4 alpha (HNF4a) and systemic inflammation are major disease drivers of AH. Plasma biomarkers of hepatocyte function could be useful for diagnostic and prognostic purposes. Herein, an integrative analysis of hepatic RNA sequencing and liquid chromatography-tandem mass spectrometry was performed to identify plasma protein signatures for patients with mild and severe AH. Alcohol-related liver disease cirrhosis, nonalcoholic fatty liver disease, and healthy subjects were used as comparator groups. Levels of identified proteins primarily involved in hepatocellular function were decreased in patients with AH, which included hepatokines, clotting factors, complement cascade components, and hepatocyte growth activators. A protein signature of AH disease severity was identified, including thrombin, hepatocyte growth factor α, clusterin, human serum factor H-related protein, and kallistatin, which exhibited large abundance shifts between severe and nonsevere AH. The combination of thrombin and hepatocyte growth factor α discriminated between severe and nonsevere AH with high sensitivity and specificity. These findings were correlated with the liver expression of genes encoding secreted proteins in a similar cohort, finding a highly consistent plasma protein signature reflecting HNF4A and HNF1A functions. This unbiased proteomic-transcriptome analysis identified plasma protein signatures and pathways associated with disease severity, reflecting HNF4A/1A activity useful for diagnostic assessment in AH.

Naive Pluripotent and Trophoblastic Stem Cell Lines as a Model for Detecting Missing Proteins in the Context of the Chromosome-Centric Human Proteome Project

The Chromosome-centric Human Proteome Project (C-HPP) aims at identifying the proteins as gene products encoded by the human genome, characterizing their isoforms and functions. The existence of products has now been confirmed for 93.2% of the genes at the protein level. The remaining mostly correspond to proteins of low abundance or difficult to access. Over the past years, we have significantly contributed to the identification of missing proteins in the human spermatozoa. We pursue our search in the reproductive sphere with a focus on early human embryonic development. Pluripotent cells, developing into the fetus, and trophoblast cells, giving rise to the placenta, emerge during the first weeks. This emergence is a focus of scientists working in the field of reproduction, placentation and regenerative medicine. Most knowledge has been harnessed by transcriptomic analysis. Interestingly, some genes are uniquely expressed in those cells, giving the opportunity to uncover new proteins that might play a crucial role in setting up the molecular events underlying early embryonic development. Here, we analyzed naive pluripotent and trophoblastic stem cells and discovered 4 new missing proteins, thus contributing to the C-HPP. The mass spectrometry proteomics data was deposited on ProteomeXchange under the data set identifier PXD035768.

AnnotaPipeline: An integrated tool to annotate eukaryotic proteins using multi-omics data

Assignment of gene function has been a crucial, laborious, and time-consuming step in genomics. Due to a variety of sequencing platforms that generates increasing amounts of data, manual annotation is no longer feasible. Thus, the need for an integrated, automated pipeline allowing the use of experimental data towards validation of in silico prediction of gene function is of utmost relevance. Here, we present a computational workflow named AnnotaPipeline that integrates distinct software and data types on a proteogenomic approach to annotate and validate predicted features in genomic sequences. Based on FASTA (i) nucleotide or (ii) protein sequences or (iii) structural annotation files (GFF3), users can input FASTQ RNA-seq data, MS/MS data from mzXML or similar formats, as the pipeline uses both transcriptomic and proteomic information to corroborate annotations and validate gene prediction, providing transcription and expression evidence for functional annotation. Reannotation of the available Arabidopsis thaliana, Caenorhabditis elegans, Candida albicans, Trypanosoma cruzi, and Trypanosoma rangeli genomes was performed using the AnnotaPipeline, resulting in a higher proportion of annotated proteins and a reduced proportion of hypothetical proteins when compared to the annotations publicly available for these organisms. AnnotaPipeline is a Unix-based pipeline developed using Python and is available at: https://github.com/bioinformatics-ufsc/AnnotaPipeline.

Integrative Analysis of Proteomics and Metabolism Reveals the Potential Roles of Arachidonic Acid Metabolism in Hypoxia Response in Mouse Spleen

High altitude hypoxia stress is the key cause of high-altitude pulmonary edema and spleen contraction. The molecular mechanism of immune response of various tissue systems to hypoxia stress remains lacking. In this study, we applied proteomics combined with metabolomics to explore the key molecular profilings involved in high altitude hypoxia response in the spleen of mice. The results showed that 166 proteins were significantly up-regulated, and only 39 proteins were down-regulated. Bioinformatics analysis showed that mineral absorption, neuroactive ligand-receptor interaction, arachidonic acid metabolism, IL-17 signaling pathway and NOD-like preceptor signaling pathway were significantly enriched in the list of 166 upregulated differentially expressed proteins (DEPs). Among these metabolic pathways, the former three pathways were co-identified in KEGG terms from LC-MS/MS based metabolic analysis. We further found that both arachidonate 15-lipoxygenase and hematopoietic prostaglandin D synthase were upregulated by around 30% and 80% for their protein levels and mRNA levels, respectively. Most downstream metabolites were upregulated accordingly, such as prostaglandin A2 and D2. This study provides important evidence that arachidonic acid metabolism potentially promotes spleen hypoxia response through a combined analysis of proteomics and metabolism, which could bring new insights for the spleen targeted rational design upon arachidonic acid metabolism of new therapies.

Reduced γ-glutamyl hydrolase activity likely contributes to high folate levels in Periyakulam-1 tomato

Tomato cultivars show wide variation in nutraceutical folate in ripe fruits, yet the loci regulating folate levels in fruits remain unexplored. To decipher regulatory points, we compared two contrasting tomato cultivars: Periyakulam-1 (PKM-1) with high folate and Arka Vikas (AV) with low folate. The progression of ripening in PKM-1 was nearly similar to AV but had substantially lower ethylene emission. In parallel, the levels of phytohormones salicylic acid, ABA, and jasmonic acid were substantially lower than AV. The fruits of PKM-1 were metabolically distinct from AV, with upregulation of several amino acids. Consistent with higher °Brix, the red ripe fruits also showed upregulation of sugars and sugar-derived metabolites. In parallel with higher folate, PKM-1 fruits also had higher carotenoid levels, especially lycopene and β-carotene. The proteome analysis showed upregulation of carotenoid sequestration and folate metabolism-related proteins in PKM-1. The deglutamylation pathway mediated by γ-glutamyl hydrolase (GGH) was substantially reduced in PKM-1 at the red-ripe stage. The red-ripe fruits had reduced transcript levels of GGHs and lower GGH activity than AV. Conversely, the percent polyglutamylation of folate was much higher in PKM-1. Our analysis indicates the regulation of GGH activity as a potential target to elevate folate levels in tomato fruits.

Shared and unique phosphoproteomics responses in skeletal muscle from exercise models and in hyperammonemic myotubes

Skeletal muscle generation of ammonia, an endogenous cytotoxin, is increased during exercise. Perturbations in ammonia metabolism consistently occur in chronic diseases, and may blunt beneficial skeletal muscle molecular responses and protein homeostasis with exercise. Phosphorylation of skeletal muscle proteins mediates cellular signaling responses to hyperammonemia and exercise. Comparative bioinformatics and machine learning-based analyses of published and experimentally derived phosphoproteomics data identified differentially expressed phosphoproteins that were unique and shared between hyperammonemic murine myotubes and skeletal muscle from exercise models. Enriched processes identified in both hyperammonemic myotubes and muscle from exercise models with selected experimental validation included protein kinase A (PKA), calcium signaling, mitogen-activated protein kinase (MAPK) signaling, and protein homeostasis. Our approach of feature extraction from comparative untargeted "omics" data allows for selection of preclinical models that recapitulate specific human exercise responses and potentially optimize functional capacity and skeletal muscle protein homeostasis with exercise in chronic diseases.

Protein arginine deiminase 2 (PAD2) modulates the polarization of THP-1 macrophages to the anti-inflammatory M2 phenotype

Background

Macrophages are effector cells of the innate immune system that undergo phenotypical changes in response to organ injury and repair. These cells are most often classified as proinflammatory M1 and anti-inflammatory M2 macrophages. Protein arginine deiminase (PAD), which catalyses the irreversible conversion of protein-bound arginine into citrulline, is expressed in macrophages. However, the substrates of PAD and its role in immune cells remain unclear. This study aimed to investigate the role of PAD in THP-1 macrophage polarization to the M1 and M2 phenotypes and identify the citrullinated proteins and modified arginines that are associated with this biological switch using mass spectrometry.

Results

Our study showed that PAD2 and, to a lesser extent, PAD1 and PAD4 were predominantly expressed in M1 macrophages. We showed that inhibiting PAD expression with BB-Cl-amidine decreased macrophage polarization to the M1 phenotype (TNF-α, IL-6) and increased macrophage polarization to the M2 phenotype (MRC1, ALOX15). This process was mediated by the downregulation of proteins involved in the NF-κβ pathway. Silencing PAD2 confirmed the activation of M2 macrophages by increasing the antiviral innate immune response and interferon signalling. A total of 192 novel citrullination sites associated with inflammation, cell death and DNA/RNA processing pathways were identified in M1 and M2 macrophages.

Conclusions

We showed that inhibiting PAD activity using a pharmacological inhibitor or silencing PAD2 with PAD2 siRNA shifted the activation of macrophages towards the M2 phenotype, which can be crucial for designing novel macrophage-mediated therapeutic strategies. We revealed a major citrullinated proteome and its rearrangement following macrophage polarization, which after further validation could lead to significant clinical benefits for the treatment of inflammation and autoimmune diseases.

Adaptation of a microbial community to demand-oriented biological methanation

BACKGROUND

Biological conversion of the surplus of renewable electricity and carbon dioxide (CO2) from biogas plants to biomethane (CH4) could support energy storage and strengthen the power grid. Biological methanation (BM) is linked closely to the activity of biogas-producing Bacteria and methanogenic Archaea. During reactor operations, the microbiome is often subject to various changes, e.g., substrate limitation or pH-shifts, whereby the microorganisms are challenged to adapt to the new conditions. In this study, various process parameters including pH value, CH4 production rate, conversion yields and final gas composition were monitored for a hydrogenotrophic-adapted microbial community cultivated in a laboratory-scale BM reactor. To investigate the robustness of the BM process regarding power oscillations, the biogas microbiome was exposed to five hydrogen (H2)-feeding regimes lasting several days.

RESULTS

Applying various "on-off" H2-feeding regimes, the CH4 production rate recovered quickly, demonstrating a significant resilience of the microbial community. Analyses of the taxonomic composition of the microbiome revealed a high abundance of the bacterial phyla Firmicutes, Bacteroidota and Thermotogota followed by hydrogenotrophic Archaea of the phylum Methanobacteriota. Homo-acetogenic and heterotrophic fermenting Bacteria formed a complex food web with methanogens. The abundance of the methanogenic Archaea roughly doubled during discontinuous H2-feeding, which was related mainly to an increase in acetoclastic Methanothrix species. Results also suggested that Bacteria feeding on methanogens could reduce overall CH4 production. On the other hand, using inactive biomass as a substrate could support the growth of methanogenic Archaea. During the BM process, the additional production of H2 by fermenting Bacteria seemed to support the maintenance of hydrogenotrophic methanogens at non-H2-feeding phases. Besides the elusive role of Methanothrix during the H2-feeding phases, acetate consumption and pH maintenance at the non-feeding phase can be assigned to this species.

CONCLUSIONS

Taken together, the high adaptive potential of microbial communities contributes to the robustness of BM processes during discontinuous H2-feeding and supports the commercial use of BM processes for energy storage. Discontinuous feeding strategies could be used to enrich methanogenic Archaea during the establishment of a microbial community for BM. Both findings could contribute to design and improve BM processes from lab to pilot scale.

Mitochondrial Fission Process 1 controls inner membrane integrity and protects against heart failure

Mitochondria are paramount to the metabolism and survival of cardiomyocytes. Here we show that Mitochondrial Fission Process 1 (MTFP1) is an inner mitochondrial membrane (IMM) protein that is dispensable for mitochondrial division yet essential for cardiac structure and function. Constitutive knockout of cardiomyocyte MTFP1 in mice resulted in a fatal, adult-onset dilated cardiomyopathy accompanied by extensive mitochondrial and cardiac remodeling during the transition to heart failure. Prior to the onset of disease, knockout cardiac mitochondria displayed specific IMM defects: futile proton leak dependent upon the adenine nucleotide translocase and an increased sensitivity to the opening of the mitochondrial permeability transition pore, with which MTFP1 physically and genetically interacts. Collectively, our data reveal new functions of MTFP1 in the control of bioenergetic efficiency and cell death sensitivity and define its importance in preventing pathogenic cardiac remodeling.

Alignstein: Optimal transport for improved LC-MS retention time alignment

BACKGROUND

Reproducibility of liquid chromatography separation is limited by retention time drift. As a result, measured signals lack correspondence over replicates of the liquid chromatography-mass spectrometry (LC-MS) experiments. Correction of these errors is named retention time alignment and needs to be performed before further quantitative analysis. Despite the availability of numerous alignment algorithms, their accuracy is limited (e.g., for retention time drift that swaps analytes' elution order).

RESULTS

We present the Alignstein, an algorithm for LC-MS retention time alignment. It correctly finds correspondence even for swapped signals. To achieve this, we implemented the generalization of the Wasserstein distance to compare multidimensional features without any reduction of the information or dimension of the analyzed data. Moreover, Alignstein by design requires neither a reference sample nor prior signal identification. We validate the algorithm on publicly available benchmark datasets obtaining competitive results. Finally, we show that it can detect the information contained in the tandem mass spectrum by the spatial properties of chromatograms.

CONCLUSIONS

We show that the use of optimal transport effectively overcomes the limitations of existing algorithms for statistical analysis of mass spectrometry datasets. The algorithm's source code is available at https://github.com/grzsko/Alignstein.

Machine learning-assisted elucidation of CD81-CD44 interactions in promoting cancer stemness and extracellular vesicle integrity

Tumor-initiating cells with reprogramming plasticity or stem-progenitor cell properties (stemness) are thought to be essential for cancer development and metastatic regeneration in many cancers; however, elucidation of the underlying molecular network and pathways remains demanding. Combining machine learning and experimental investigation, here we report CD81, a tetraspanin transmembrane protein known to be enriched in extracellular vesicles (EVs), as a newly identified driver of breast cancer stemness and metastasis. Using protein structure modeling and interface prediction-guided mutagenesis, we demonstrate that membrane CD81 interacts with CD44 through their extracellular regions in promoting tumor cell cluster formation and lung metastasis of triple negative breast cancer (TNBC) in human and mouse models. In-depth global and phosphoproteomic analyses of tumor cells deficient with CD81 or CD44 unveils endocytosis-related pathway alterations, leading to further identification of a quality-keeping role of CD44 and CD81 in EV secretion as well as in EV-associated stemness-promoting function. CD81 is coexpressed along with CD44 in human circulating tumor cells (CTCs) and enriched in clustered CTCs that promote cancer stemness and metastasis, supporting the clinical significance of CD81 in association with patient outcomes. Our study highlights machine learning as a powerful tool in facilitating the molecular understanding of new molecular targets in regulating stemness and metastasis of TNBC.

Nfkb2 deficiency and its impact on plasma cells and immunoglobulin expression in murine small intestinal mucosa

The alternative (noncanonical) nuclear factor-κB (NF-κB) signaling pathway predominantly regulates the function of the p52/RelB heterodimer. Germline Nfkb2 deficiency in mice leads to loss of p100/p52 protein and offers protection against a variety of gastrointestinal conditions, including azoxymethane/dextran sulfate sodium (DSS)-induced colitis-associated cancer and lipopolysaccharide (LPS)-induced small intestinal epithelial apoptosis. However, the common underlying protective mechanisms have not yet been fully elucidated. We applied high-throughput RNA-Seq and proteomic analyses to characterize the transcriptional and protein signatures of the small intestinal mucosa of naïve adult Nfkb2^-/- mice. Those data were validated by immunohistochemistry and quantitative ELISA using both small intestinal tissue lysates and serum. We identified a B-lymphocyte defect as a major transcriptional signature in the small intestinal mucosa and immunoglobulin A as the most downregulated protein by proteomic analysis in Nfkb2^-/- mice. Small intestinal immunoglobulins were dramatically dysregulated, with undetectable levels of immunoglobulin A and greatly increased amounts of immunoglobulin M being detected. The numbers of IgA-producing, cluster of differentiation (CD)138-positive plasma cells were also reduced in the lamina propria of the small intestinal villi of Nfkb2^-/- mice. This phenotype was even more striking in the small intestinal mucosa of RelB^-/- mice, although these mice were equally sensitive to LPS-induced intestinal apoptosis as their RelB^+/+ wild-type counterparts. NF-κB2/p52 deficiency confers resistance to LPS-induced small intestinal apoptosis and also appears to regulate the plasma cell population and immunoglobulin levels within the gut.NEW & NOTEWORTHY Novel transcriptomic analysis of murine proximal intestinal mucosa revealed an unexpected B cell signature in Nfkb2^-/- mice. In-depth analysis revealed a defect in the CD38+ B cell population and a gut-specific dysregulation of immunoglobulin levels.

A seed-like proteome in oil-rich tubers

There are numerous examples of plant organs or developmental stages that are desiccation-tolerant and can withstand extended periods of severe water loss. One prime example are seeds and pollen of many spermatophytes. However, in some plants, also vegetative organs can be desiccation-tolerant. One example are the tubers of yellow nutsedge (Cyperus esculentus), which also store large amounts of lipids similar to seeds. Interestingly, the closest known relative, purple nutsedge (Cyperus rotundus), generates tubers that do not accumulate oil and are not desiccation-tolerant. We generated nanoLC-MS/MS-based proteomes of yellow nutsedge in five replicates of four stages of tuber development and compared them to the proteomes of roots and leaves, yielding 2257 distinct protein groups. Our data reveal a striking upregulation of hallmark proteins of seeds in the tubers. A deeper comparison to the tuber proteome of the close relative purple nutsedge (C. rotundus) and a previously published proteome of Arabidopsis seeds and seedlings indicates that indeed a seed-like proteome was found in yellow but not purple nutsedge. This was further supported by an analysis of the proteome of a lipid droplet-enriched fraction of yellow nutsedge, which also displayed seed-like characteristics. One reason for the differences between the two nutsedge species might be the expression of certain transcription factors homologous to ABSCISIC ACID INSENSITIVE3, WRINKLED1, and LEAFY COTYLEDON1 that drive gene expression in Arabidopsis seed embryos.

Seeing the unseen: a trifoliate (MYB117) mutant allele fortifies folate and carotenoids in tomato fruits

In tomato (Solanum lycopersicum), mutations in the gene encoding the R2R3-MYB117 transcription factor elicit trifoliate leaves and initiate the formation of axillary meristems; however, their effects on fruit ripening remain unexplored. The fruits of a new trifoliate (tf) mutant (tf-5) were firmer and had higher °Brix values and higher folate and carotenoid contents. The transcriptome, proteome, and metabolome profiling of tf-5 reflected a broad-spectrum change in cellular homeostasis. The tf-5 allele enhanced the fruit firmness by suppressing cell wall softening-related proteins. tf-5 fruit displayed a substantial increase in amino acids, particularly γ-aminobutyric acid, with a parallel reduction in aminoacyl-tRNA synthases. The increased lipoxygenase protein and transcript levels seemingly elevated jasmonic acid levels. In addition, increased abscisic acid hydrolase transcript levels coupled with reduced precursor supply lowered abscisic acid levels. The upregulation of carotenoids was mediated by modulation of methylerythreitol and plastoquinone pathways and increased the levels of carotenoid isomerization proteins. The upregulation of folate in tf-5 was connoted by the increase in the precursor p-aminobenzoic acid and transcript levels of several folate biosynthesis genes. The reduction in pterin-6-carboxylate levels and γ-glutamyl hydrolase activity indicated that reduced folate degradation in tf-5 increased folate levels. Our study delineates that in addition to leaf development, MYB117 also influences fruit metabolism. The tf-5 allele can be used to increase γ-aminobutyric acid, carotenoid, and folate levels in tomato.

The rate and role of pseudogenes of the Mycobacterium tuberculosis complex

Whole-genome sequence analyses have significantly contributed to the understanding of virulence and evolution of the Mycobacterium tuberculosis complex (MTBC), the causative pathogens of tuberculosis. Most MTBC evolutionary studies are focused on single nucleotide polymorphisms and deletions, but rare studies have evaluated gene content, whereas none has comprehensively evaluated pseudogenes. Accordingly, we describe an extensive study focused on quantifying and predicting possible functions of MTBC and Mycobacterium canettii pseudogenes. Using NCBI's PGAP-detected pseudogenes, we analysed 25 837 pseudogenes from 158 MTBC and M. canetii strains and combined transcriptomics and proteomics of M. tuberculosis H37Rv to gain insights about pseudogenes' expression. Our results indicate significant variability concerning rate and conservancy of in silico predicted pseudogenes among different ecotypes and lineages of tuberculous mycobacteria and pseudogenization of important virulence factors and genes of the metabolism and antimicrobial resistance/tolerance. We show that in silico predicted pseudogenes contribute considerably to MTBC genetic diversity at the population level. Moreover, the transcription machinery of M. tuberculosis can fully transcribe most pseudogenes, indicating intact promoters and recent pseudogene evolutionary emergence. Proteomics of M. tuberculosis and close evaluation of mutational lesions driving pseudogenization suggest that few in silico predicted pseudogenes are likely capable of neofunctionalization, nonsense mutation reversal, or phase variation, contradicting the classical definition of pseudogenes. Such findings indicate that genome annotation should be accompanied by proteomics and protein function assays to improve its accuracy. While indels and insertion sequences are the main drivers of the observed mutational lesions in these species, population bottlenecks and genetic drift are likely the evolutionary processes acting on pseudogenes' emergence over time. Our findings unveil a new perspective on MTBC's evolution and genetic diversity.

Abscisic acid-controlled redox proteome of Arabidopsis and its regulation by heterotrimeric Gβ protein

The plant hormone abscisic acid (ABA) plays crucial roles in regulation of stress responses and growth modulation. Heterotrimeric G-proteins are key mediators of ABA responses. Both ABA and G-proteins have also been implicated in intracellular redox regulation; however, the extent to which reversible protein oxidation manipulates ABA and/or G-protein signaling remains uncharacterized. To probe the role of reversible protein oxidation in plant stress response and its dependence on G-proteins, we determined the ABA-dependent reversible redoxome of wild-type and Gβ-protein null mutant agb1 of Arabidopsis. We quantified 6891 uniquely oxidized cysteine-containing peptides, 923 of which show significant changes in oxidation following ABA treatment. The majority of these changes required the presence of G-proteins. Divergent pathways including primary metabolism, reactive oxygen species response, translation and photosynthesis exhibited both ABA- and G-protein-dependent redox changes, many of which occurred on proteins not previously linked to them. We report the most comprehensive ABA-dependent plant redoxome and uncover a complex network of reversible oxidations that allow ABA and G-proteins to rapidly adjust cellular signaling to adapt to changing environments. Physiological validation of a subset of these observations suggests that functional G-proteins are required to maintain intracellular redox homeostasis and fully execute plant stress responses.

Quantitative proteomics of small numbers of closely-related cells: Selection of the optimal method for a clinical setting

Mass spectrometry (MS)-based proteomics profiling has undoubtedly increased the knowledge about cellular processes and functions. However, its applicability for paucicellular sample analyses is currently limited. Although new approaches have been developed for single-cell studies, most of them have not (yet) been standardized and/or require highly specific (often home-built) devices, thereby limiting their broad implementation, particularly in non-specialized settings. To select an optimal MS-oriented proteomics approach applicable in translational research and clinical settings, we assessed 10 different sample preparation procedures in paucicellular samples of closely-related cell types. Particularly, five cell lysis protocols using different chemistries and mechanical forces were combined with two sample clean-up techniques (C18 filter- and SP3-based), followed by tandem mass tag (TMT)-based protein quantification. The evaluation was structured in three phases: first, cell lines from hematopoietic (THP-1) and non-hematopoietic (HT-29) origins were used to test the approaches showing the combination of a urea-based lysis buffer with the SP3 bead-based clean-up system as the best performer. Parameters such as reproducibility, accessibility, spatial distribution, ease of use, processing time and cost were considered. In the second phase, the performance of the method was tested on maturation-related cell populations: three different monocyte subsets from peripheral blood and, for the first time, macrophages/microglia (MAC) from glioblastoma samples, together with T cells from both tissues. The analysis of 50,000 cells down to only 2,500 cells revealed different protein expression profiles associated with the distinct cell populations. Accordingly, a closer relationship was observed between non-classical monocytes and MAC, with the latter showing the co-expression of M1 and M2 macrophage markers, although pro-tumoral and anti-inflammatory proteins were more represented. In the third phase, the results were validated by high-end spectral flow cytometry on paired monocyte/MAC samples to further determine the sensitivity of the MS approach selected. Finally, the feasibility of the method was proven in 194 additional samples corresponding to 38 different cell types, including cells from different tissue origins, cellular lineages, maturation stages and stimuli. In summary, we selected a reproducible, easy-to-implement sample preparation method for MS-based proteomic characterization of paucicellular samples, also applicable in the setting of functionally closely-related cell populations.

A multi-adenylate cyclase regulator at the flagellar tip controls African trypanosome transmission

Signaling from ciliary microdomains controls developmental processes in metazoans. Trypanosome transmission requires development and migration in the tsetse vector alimentary tract. Flagellar cAMP signaling has been linked to parasite social motility (SoMo) in vitro, yet uncovering control of directed migration in fly organs is challenging. Here we show that the composition of an adenylate cyclase (AC) complex in the flagellar tip microdomain is essential for tsetse salivary gland (SG) colonization and SoMo. Cyclic AMP response protein 3 (CARP3) binds and regulates multiple AC isoforms. CARP3 tip localization depends on the cytoskeletal protein FLAM8. Re-localization of CARP3 away from the tip microdomain is sufficient to abolish SoMo and fly SG colonization. Since intrinsic development is normal in carp3 and flam8 knock-out parasites, AC complex-mediated tip signaling specifically controls parasite migration and thereby transmission. Participation of several developmentally regulated receptor-type AC isoforms may indicate the complexity of the in vivo signals perceived.

Trypanosomes can sense signal molecules and coordinate their movement in response to such signals, a phenomenon termed social motility (SoMo). Here, Bachmaier et al show that cyclic AMP response protein 3 (CARP3) localization to the flagellar tip and its interaction with a number of different adenylate cyclases is essential for migration to tsetse fly salivary glands and for SoMo, therewith linking SoMo and cAMP signaling to trypanosome transmission.

Phosphorylation of β-catenin at Serine552 correlates with invasion and recurrence of non-functioning pituitary neuroendocrine tumours

Non-functioning pituitary tumours (NF-PitNETs) are common intracranial benign neoplasms that can exhibit aggressive behaviour by invading neighbouring structures and, in some cases, have multiple recurrences. Despite resulting in severe co-morbidities, no predictive biomarkers of recurrence have been identified for NF-PitNETs. In this study we have used high-throughput mass spectrometry-based analysis to examine the phosphorylation pattern of different subsets of NF-PitNETs. Based on histopathological, radiological, surgical and clinical features, we have grouped NF-PitNETs into non-invasive, invasive, and recurrent disease groups. Tumour recurrence was determined based on regular clinical and radiological data of patients for a mean follow-up of 10 years (SD ± 5.4 years). Phosphoproteomic analyses identified a unique phosphopeptide enrichment pattern which correlates with disease recurrence. Candidate phosphorylated proteins were validated in a large cohort of NF-PitNET patients by western blot and immunohistochemistry. We identified a cluster of 22 phosphopeptides upregulated in recurrent NF-PitNETs compared to non-invasive and invasive subgroups. We reveal significant phosphorylation of the β-catenin at Ser552 in recurrent and invasive NF-PitNETs, compared to non-invasive/non-recurrent NF-PitNET subgroup. Moreover, β-catenin pSer552 correlates with the recurrence free survival among 200 patients with NF-PitNET. Together, our results suggest that the phosphorylation status of β-catenin at Ser552 could act as potential biomarker of tumour recurrence in NF-PitNETs.

Proteomic Analysis Identifies Molecular Players and Biological Processes Specific to SARS-CoV-2 Exposure in Endothelial Cells

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been responsible for the severe pandemic of acute respiratory disease, coronavirus disease 2019 (COVID-19), experienced in the 21st century. The clinical manifestations range from mild symptoms to abnormal blood coagulation and severe respiratory failure. In severe cases, COVID-19 manifests as a thromboinflammatory disease. Damage to the vascular compartment caused by SARS-CoV-2 has been linked to thrombosis, triggered by an enhanced immune response. The molecular mechanisms underlying endothelial activation have not been fully elucidated. We aimed to identify the proteins correlated to the molecular response of human umbilical vein endothelial cells (HUVECs) after exposure to SARS-CoV-2, which might help to unravel the molecular mechanisms of endothelium activation in COVID-19. In this direction, we exposed HUVECs to SARS-CoV-2 and analyzed the expression of specific cellular receptors, and changes in the proteome of HUVECs at different time points. We identified that HUVECs exhibit non-productive infection without cytopathic effects, in addition to the lack of expression of specific cell receptors known to be essential for SARS-CoV-2 entry into cells. We highlighted the enrichment of the protein SUMOylation pathway and the increase in SUMO2, which was confirmed by orthogonal assays. In conclusion, proteomic analysis revealed that the exposure to SARS-CoV-2 induced oxidative stress and changes in protein abundance and pathways enrichment that resembled endothelial dysfunction.

Is DIA proteomics data FAIR? Current data sharing practices, available bioinformatics infrastructure and recommendations for the future

Data independent acquisition (DIA) proteomics techniques have matured enormously in recent years, thanks to multiple technical developments in e.g. instrumentation and data analysis approaches. However, there are many improvements that are still possible for DIA data in the area of the FAIR (Findability, Accessibility, Interoperability and Reusability) data principles. These include more tailored data sharing practices and open data standards, since public databases and data standards for proteomics were mostly designed with DDA data in mind. Here we first describe the current state of the art in the context of FAIR data for proteomics in general, and for DIA approaches in particular. For improving the current situation for DIA data, we make the following recommendations for the future: (i) development of an open data standard for spectral libraries; (ii) make mandatory the availability of the spectral libraries used in DIA experiments in ProteomeXchange resources; (iii) improve the support for DIA data in the data standards developed by the Proteomics Standards Initiative; and (iv) improve the support for DIA datasets in ProteomeXchange resources, including more tailored metadata requirements. This article is protected by copyright. All rights reserved.

Size-Based Proteome Fractionation through Polyacrylamide Gel Electrophoresis Combined with LC-FAIMS-MS for In-Depth Top-Down Proteomics

The combination of liquid chromatography (LC) and gas-phase separation by field-asymmetric ion mobility spectrometry (FAIMS) is a powerful proteoform separation system for top-down proteomics. Here, we present an in-depth top-down proteomics workflow, GeLC-FAIMS-MS, in which a molecular-weight-based proteome fractionation approach using SDS-polyacrylamide gel electrophoresis is performed prior to LC-FAIMS-MS. Since individual bands and their corresponding mass ranges require different compensating voltages (CVs), the MS parameters for each gel band and CV were optimized to increase the number and reliability of proteoform identifications further. We developed an easy-to-implement and inexpensive procedure combining the earlier established Passively Eluting Proteins from Polyacrylamide gels as Intact species (PEPPI) protocol with an optimized Anion-Exchange disk-assisted Sequential sample Preparation (AnExSP) method for the removal of stains and SDS. The protocol was compared with a methanol-chloroform-water (MCW)-based protein precipitation protocol. The results show that the PEPPI-AnExSP procedure is better suited for the identification of low-molecular-weight proteoforms, whereas the MCW-based protocol showed advantages for higher-molecular-weight proteoforms. Moreover, complementary results were observed with the two methods in terms of hydrophobicity and isoelectric points of the identified proteoforms. In total, 8500 proteoforms could be identified in a human proteome standard, showing the effectiveness of the gel-based sample fractionation approaches in combination with LC-FAIMS-MS.

Cryo-EM structures of prion protein filaments from Gerstmann-Sträussler-Scheinker disease

Prion protein (PrP) aggregation and formation of PrP amyloid (APrP) are central events in the pathogenesis of prion diseases. In the dominantly inherited prion protein amyloidosis known as Gerstmann-Sträussler-Scheinker (GSS) disease, plaques made of PrP amyloid are present throughout the brain. The c.593t > c mutation in the prion protein gene (PRNP) results in a phenylalanine to serine amino acid substitution at PrP residue 198 (F198S) and causes the most severe amyloidosis among GSS variants. It has been shown that neurodegeneration in this disease is associated with the presence of extracellular APrP plaques and neuronal intracytoplasmic Tau inclusions, that have been shown to contain paired helical filaments identical to those found in Alzheimer disease. Using cryogenic electron microscopy (cryo-EM), we determined for the first time the structures of filaments of human APrP, isolated post-mortem from the brain of two symptomatic PRNP F198S mutation carriers. We report that in GSS (F198S) APrP filaments are composed of dimeric, trimeric and tetrameric left-handed protofilaments with their protomers sharing a common protein fold. The protomers in the cross-β spines consist of 62 amino acids and span from glycine 80 to phenylalanine 141, adopting a previously unseen spiral fold with a thicker outer layer and a thinner inner layer. Each protomer comprises nine short β-strands, with the β1 and β8 strands, as well as the β4 and β9 strands, forming a steric zipper. The data obtained by cryo-EM provide insights into the structural complexity of the PrP filament in a dominantly inherited human PrP amyloidosis. The novel findings highlight the urgency of extending our knowledge of the filaments' structures that may underlie distinct clinical and pathologic phenotypes of human neurodegenerative diseases.

An Optimized Comparative Proteomic Approach as a Tool in Neurodegenerative Disease Research

Recent advances in proteomic technologies now allow unparalleled assessment of the molecular composition of a wide range of sample types. However, the application of such technologies and techniques should not be undertaken lightly. Here, we describe why the design of a proteomics experiment itself is only the first step in yielding high-quality, translatable results. Indeed, the effectiveness and/or impact of the majority of contemporary proteomics screens are hindered not by commonly considered technical limitations such as low proteome coverage but rather by insufficient analyses. Proteomic experimentation requires a careful methodological selection to account for variables from sample collection, through to database searches for peptide identification to standardised post-mass spectrometry options directed analysis workflow, which should be adjusted for each study, from determining when and how to filter proteomic data to choosing holistic versus trend-wise analyses for biologically relevant patterns. Finally, we highlight and discuss the difficulties inherent in the modelling and study of the majority of progressive neurodegenerative conditions. We provide evidence (in the context of neurodegenerative research) for the benefit of undertaking a comparative approach through the application of the above considerations in the alignment of publicly available pre-existing data sets to identify potential novel regulators of neuronal stability.

Validation of Top-Down Proteomics Data by Bottom-Up-Based N-Terminomics Reveals Pitfalls in Top-Down-Based Terminomics Workflows

Bottom-up proteomics (BUP)-based N-terminomics techniques have become standard to identify protein N-termini. While these methods rely on the identification of N-terminal peptides only, top-down proteomics (TDP) comes with the promise to provide additional information about post-translational modifications and the respective C-termini. To evaluate the potential of TDP for terminomics, two established TDP workflows were employed for the proteome analysis of the nematode Caenorhabditis elegans. The N-termini of the identified proteoforms were validated using a BUP-based N-terminomics approach. The TDP workflows used here identified 1658 proteoforms, the N-termini of which were verified by BUP in 25% of entities only. Caveats in both the BUP- and TDP-based workflows were shown to contribute to this low overlap. In BUP, the use of trypsin prohibits the detection of arginine-rich or arginine-deficient N-termini, while in TDP, the formation of artificially generated termini was observed in particular in a workflow encompassing sample treatment with high acid concentrations. Furthermore, we demonstrate the applicability of reductive dimethylation in TDP to confirm biological N-termini. Overall, our study shows not only the potential but also current limitations of TDP for terminomics studies and also presents suggestions for future developments, for example, for data quality control, allowing improvement of the detection of protein termini by TDP.

Metabolomic and proteomic profiling in bipolar disorder patients revealed potential molecular signatures related to hemostasis

INTRODUCTION

Bipolar disorder (BD) is a mood disorder characterized by the occurrence of depressive episodes alternating with episodes of elevated mood (known as mania). There is also an increased risk of other medical comorbidities.

OBJECTIVES

This work uses a systems biology approach to compare BD treated patients with healthy controls (HCs), integrating proteomics and metabolomics data using partial correlation analysis in order to observe the interactions between altered proteins and metabolites, as well as proposing a potential metabolic signature panel for the disease.

METHODS

Data integration between proteomics and metabolomics was performed using GC-MS data and label-free proteomics from the same individuals (N = 13; 5 BD, 8 HC) using generalized canonical correlation analysis and partial correlation analysis, and then building a correlation network between metabolites and proteins. Ridge-logistic regression models were developed to stratify between BD and HC groups using an extended metabolomics dataset (N = 28; 14 BD, 14 HC), applying a recursive feature elimination for the optimal selection of the metabolites.

RESULTS

Network analysis demonstrated links between proteins and metabolites, pointing to possible alterations in hemostasis of BD patients. Ridge-logistic regression model indicated a molecular signature comprising 9 metabolites, with an area under the receiver operating characteristic curve (AUROC) of 0.833 (95% CI 0.817-0.914).

CONCLUSION

From our results, we conclude that several metabolic processes are related to BD, which can be considered as a multi-system disorder. We also demonstrate the feasibility of partial correlation analysis for integration of proteomics and metabolomics data in a case-control study setting.

α-Synuclein molecular behavior and nigral proteomic profiling distinguish subtypes of Lewy body disorders

Lewy body disorders (LBD), characterized by the deposition of misfolded α-synuclein (α-Syn), are clinically heterogeneous. Although the distribution of α-Syn correlates with the predominant clinical features, the burden of pathology does not fully explain the observed variability in clinical presentation and rate of disease progression. We hypothesized that this heterogeneity might reflect α-Syn molecular diversity, between both patients and different brain regions. Using an ultra-sensitive assay, we evaluated α-Syn seeding in 8 brain regions from 30 LBD patients with different clinical phenotypes and disease durations. Comparing seeding across the clinical phenotypes revealed that hippocampal α-Syn from patients with a cognitive-predominant phenotype had significantly higher seeding capacity than that derived from patients with a motor-predominant phenotype, whose nigral-derived α-Syn in turn had higher seeding capacity than that from cognitive-predominant patients. Interestingly, α-Syn from patients with rapid disease progression (< 3 years to development of advanced disease) had the highest nigral seeding capacity of all the patients included. To validate these findings and explore factors underlying seeding heterogeneity, we performed in vitro toxicity assays, and detailed neuropathological and biochemical examinations. Furthermore, and for the first time, we performed a proteomic-wide profiling of the substantia nigra from 5 high seeder and 5 low seeder patients. The proteomic data suggests a significant disruption in mitochondrial function and lipid metabolism in high seeder cases compared to the low seeders. These observations suggest that distinct molecular populations of α-Syn may contribute to heterogeneity in phenotypes and progression rates in LBD and imply that effective therapeutic strategies might need to be directed at an ensemble of differently misfolded α-Syn species, with the relative contribution of their differing impacts accounting for heterogeneity in the neurodegenerative process.

Forward and reverse degradomics defines the proteolytic landscape of human knee osteoarthritic cartilage and the role of the serine protease HtrA1

OBJECTIVES

Proteolytic destruction of articular cartilage, a major pathogenic mechanism in osteoarthritis (OA), was not previously investigated by terminomics strategies. We defined the degradome of human knee OA cartilage and the contribution therein of the protease HtrA1 using Terminal Amine Isotopic Labeling of Substrates (TAILS).

DESIGN

Proteins from OA cartilage taken at knee arthroplasty (n = 6) or separately, from healthy cartilage incubated in triplicate with/without active HtrA1, were labeled at natural and proteolytically cleaved N-termini by reductive dimethylation, followed by trypsin digestion, enrichment of N-terminally labeled/blocked peptides, tandem mass spectrometry and positional peptide annotation to identify cleavage sites. Biglycan proteolysis by HtrA1 was validated biochemically and Amino-Terminal Oriented Mass Spectrometry of Substrates (ATOMS) was used to define the HtrA1 cleavage sites.

RESULTS

We identified 10,155 unique internal peptides from 2,162 proteins, suggesting at least 10,797 cleavage sites in OA cartilage. 7,635 internal peptides originated in 371 extracellular matrix/secreted components, many undergoing extensive proteolysis. Rampant ragging of protein termini suggested pervasive exopeptidase activity. HtrA1, the most abundant protease in OA cartilage, experimentally generated 323 cleavages in 109 cartilage proteins, accounting for 171 observed cleavages in the OA degradome. ATOMS identified HtrA1 cleavage sites in a selected substrate, biglycan, whose direct cleavage by HtrA1 was thus orthogonally validated.

CONCLUSIONS

OA cartilage demonstrates widespread proteolysis by endo- and exopeptidases. HtrA1 contributes broadly to cartilage proteolysis. Forward degradomics of OA cartilage together with reverse degradomics of proteases active in OA, e.g., HtrA1, can potentially fully annotate OA proteolytic pathways and provide new biomarkers.

Activity-based protein profiling identifies alternating activation of enzymes involved in the bifidobacterium shunt pathway or mucin degradation in the gut microbiome response to soluble dietary fiber

While deprivation of dietary fiber has been associated with adverse health outcomes, investigations concerning the effect of dietary fiber on the gut microbiome have been largely limited to compositional sequence-based analyses or utilize a defined microbiota not native to the host. To extend understanding of the microbiome's functional response to dietary fiber deprivation beyond correlative evidence from sequence-based analyses, approaches capable of measuring functional enzymatic activity are needed. In this study, we use an activity-based protein profiling (ABPP) approach to identify sugar metabolizing and transport proteins in native mouse gut microbiomes that respond with differential activity to the deprivation or supplementation of the soluble dietary fibers inulin and pectin. We found that the microbiome of mice subjected to a high fiber diet high in soluble fiber had increased functional activity of multiple proteins, including glycoside hydrolases, polysaccharide lyases, and sugar transport proteins from diverse taxa. The results point to an increase in activity of the Bifidobacterium shunt metabolic pathway in the microbiome of mice fed high fiber diets. In those subjected to a low fiber diet, we identified a shift from the degradation of dietary fibers to that of gut mucins, in particular by the recently isolated taxon "Musculibacterium intestinale", which experienced dramatic growth in response to fiber deprivation. When combined with metabolomics and shotgun metagenomics analyses, our findings provide a functional investigation of dietary fiber metabolism in the gut microbiome and demonstrates the power of a combined ABPP-multiomics approach for characterizing the response of the gut microbiome to perturbations.

Pulse labeling reveals the tail end of protein folding by proteome profiling

Accurate and efficient folding of nascent protein sequences into their native states requires support from the protein homeostasis network. Herein we probe which newly translated proteins are thermo-sensitive, making them susceptible to misfolding and aggregation under heat stress using pulse-SILAC mass spectrometry. We find a distinct group of proteins that is highly sensitive to this perturbation when newly synthesized but not once matured. These proteins are abundant and highly structured. Notably, they display a tendency to form β sheet secondary structures, have more complex folding topology, and are enriched for chaperone-binding motifs, suggesting a higher demand for chaperone-assisted folding. These polypeptides are also more often components of stable protein complexes in comparison with other proteins. Combining these findings suggests the existence of a specific subset of proteins in the cell that is particularly vulnerable to misfolding and aggregation following synthesis before reaching the native state.

Accelerated lysine metabolism conveys kidney protection in salt-sensitive hypertension

Hypertension and kidney disease have been repeatedly associated with genomic variants and alterations of lysine metabolism. Here, we combined stable isotope labeling with untargeted metabolomics to investigate lysine's metabolic fate in vivo. Dietary 13C6 labeled lysine was tracked to lysine metabolites across various organs. Globally, lysine reacts rapidly with molecules of the central carbon metabolism, but incorporates slowly into proteins and acylcarnitines. Lysine metabolism is accelerated in a rat model of hypertension and kidney damage, chiefly through N-alpha-mediated degradation. Lysine administration diminished development of hypertension and kidney injury. Protective mechanisms include diuresis, further acceleration of lysine conjugate formation, and inhibition of tubular albumin uptake. Lysine also conjugates with malonyl-CoA to form a novel metabolite Nε-malonyl-lysine to deplete malonyl-CoA from fatty acid synthesis. Through conjugate formation and excretion as fructoselysine, saccharopine, and Nε-acetyllysine, lysine lead to depletion of central carbon metabolites from the organism and kidney. Consistently, lysine administration to patients at risk for hypertension and kidney disease inhibited tubular albumin uptake, increased lysine conjugate formation, and reduced tricarboxylic acid (TCA) cycle metabolites, compared to kidney-healthy volunteers. In conclusion, lysine isotope tracing mapped an accelerated metabolism in hypertension, and lysine administration could protect kidneys in hypertensive kidney disease.

Bioinformatic Analysis to Investigate Metaproteome Composition Using Trans-Proteomic Pipeline

With evidence emerging that the microbiome has a role in the onset of many human diseases, including cancer, analyzing these microbial communities and their proteins (i.e., the metaproteome) has become a powerful research tool. The Trans-Proteomic Pipeline (TPP) is a free, comprehensive software suite that facilitates the analysis of mass spectrometry (MS) data. By utilizing available microbial proteomes, TPP can identify microbial proteins and species, with an acceptable peptide false-discovery rate (FDR). An application to a publicly available oral cancer dataset is presented as an example to identify the viral metaproteome on the oral cancer invasive tumor front. © 2022 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Collection of data and resources Basic Protocol 2: Analysis of MS data using TPP Basic Protocol 3: Analysis of TPP output using R in RStudio.

Profilings of subproteomes of lectin-binding proteins of nine Bothrops venoms reveal variability driven by different glycan types

Snake venom proteomes have long been investigated to explore a multitude of biologically active components that are used for prey capture and defense, and are involved in the pathological effects observed upon mammalian envenomation. Glycosylation is a major protein post-translational modification in venoms and contributes to the diversification of proteomes. We have shown that Bothrops venoms are markedly defined by their content of glycoproteins, and that most N-glycan structures of eight Bothrops venoms contain sialic acid, while bisected N-acetylglucosamine was identified in Bothrops cotiara venom. To further investigate the mechanisms involved in the generation of different venoms by related snakes, here the glycoproteomes of nine Bothrops venoms (Bothrops atrox, B. cotiara, Bothrops erythromelas, Bothrops fonsecai, B. insularis, Bothrops jararaca, Bothrops jararacussu, Bothrops moojeni and Bothrops neuwiedi) were comparatively analyzed by enrichment with three lectins of different specificities, recognizing bisecting N-acetylglucosamine- and sialic acid-containing glycoproteins, and mass spectrometry. The lectin capture strategy generated venom fractions enriched with several glycoproteins, including metalloprotease, serine protease, and L- amino acid oxidase, in addition to various types of low abundant enzymes. The different contents of lectin-enriched proteins underscore novel aspects of the variability of the glycoprotein subproteomes of Bothrops venoms and point to the role of distinct types of glycan chains in generating different venoms by closely related snake species.

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.

Digital Microfluidics Supported Microproteomics for Quantitative Proteome Analysis of Single Caenorhabditis elegans Nematodes

Miniaturization of sample preparation, including omissible manual sample handling steps, is key for reproducible nanoproteomics, as material is often restricted to only hundreds of cells or single model organisms. Here, we demonstrate a highly sensitive digital microfluidics (DMF)-based sample preparation workflow making use of single-pot solid-phase enhanced sample preparation (SP3) in combination with high-field asymmetric-waveform ion mobility spectrometry (FAIMS), and fast and sensitive ion trap detection on an Orbitrap tribrid MS system. Compared to a manual in-tube SP3-supported sample preparation, the numbers of identified peptides and proteins were markedly increased, while lower standard deviations between replicates were observed. We repeatedly identified up to 5000 proteins from single nematodes. Moreover, label-free quantification of protein changes in single Caenorhabditis elegans treated with a heat stimulus yielded 45 differentially abundant proteins when compared to the untreated control, highlighting the potential of this technology for low-input proteomics studies. LC-MS data have been deposited to the ProteomeXchange Consortium with the data set identifier PXD033143.