Exploring the yeast acetylome using functional genomics.

Lysine acetylation is a dynamic posttranslational modification with a well-defined role in regulating histones. The impact of acetylation on other cellular functions remains relatively uncharacterized. We explored the budding yeast acetylome with a functional genomics approach, assessing the effects of gene overexpression in the absence of lysine deacetylases (KDACs). We generated a network of 463 synthetic dosage lethal (SDL) interactions involving class I and II KDACs, revealing many cellular pathways regulated by different KDACs. A biochemical survey of genes interacting with the KDAC RPD3 identified 72 proteins acetylated in vivo. In-depth analysis of one of these proteins, Swi4, revealed a role for acetylation in G1-specific gene expression. Acetylation of Swi4 regulates interaction with its partner Swi6, both components of the SBF transcription factor. This study expands our view of the yeast acetylome, demonstrates the utility of functional genomic screens for exploring enzymatic pathways, and provides functional information that can be mined for future studies.

The Landscape and Perspectives of the Human Gut Metaproteomics.

The human gut microbiome is closely associated with human health and diseases. Metaproteomics has emerged as a valuable tool for studying the functionality of the gut microbiome by analyzing the entire proteins present in microbial communities. Recent advancements in liquid chromatography and tandem mass spectrometry (LC-MS/MS) techniques have expanded the detection range of metaproteomics. However, the overall coverage of the proteome in metaproteomics is still limited. While metagenomics studies have revealed substantial microbial diversity and functional potential of the human gut microbiome, few studies have summarized and studied the human gut microbiome landscape revealed with metaproteomics. In this article, we present the current landscape of human gut metaproteomics studies by re-analyzing the identification results from 15 published studies. We quantified the limited proteome coverage in metaproteomics and revealed a high proportion of annotation coverage of metaproteomics-identified proteins. We conducted a preliminary comparison between the metaproteomics view and the metagenomics view of the human gut microbiome, identifying key areas of consistency and divergence. Based on the current landscape of human gut metaproteomics, we discuss the feasibility of using metaproteomics to study functionally unknown proteins and propose a whole workflow peptide-centric analysis. Additionally, we suggest enhancing metaproteomics analysis by refining taxonomic classification and calculating confidence scores, as well as developing tools for analyzing the interaction between taxonomy and function.

Retinal proteome profiling of inherited retinal degeneration across three different mouse models suggests common drug targets in retinitis pigmentosa.

Inherited retinal degenerations (IRDs) are a leading cause of blindness among the population of young people in the developed world. Approximately half of IRDs initially manifest as gradual loss of night vision and visual fields, characteristic of retinitis pigmentosa (RP). Due to challenges in genetic testing, and the large heterogeneity of mutations underlying RP, targeted gene therapies are an impractical largescale solution in the foreseeable future. For this reason, identifying key pathophysiological pathways in IRDs that could be targets for mutation-agnostic and disease-modifying therapies (DMTs) is warranted. In this study, we investigated the retinal proteome of three distinct IRD mouse models, in comparison to sex- and age-matched wild-type mice. Specifically, we used the Pde6ßRd10 (rd10) and RhoP23H/WT (P23H) mouse models of autosomal recessive and autosomal dominant RP, respectively, as well as the Rpe65-/- mouse model of Leber´s congenital amaurosis type 2 (LCA2). The mice were housed at two distinct institutions and analyzed using LC-MS in three separate facilities/instruments following data-dependent and data-independent acquisition modes. This cross-institutional and multi-methodological approach signifies the reliability and reproducibility of the results. The largescale profiling of the retinal proteome, coupled with in vivo electroretinography recordings, provided us with a reliable basis for comparing the disease phenotypes and severity. Despite evident inflammation, cellular stress, and downscaled phototransduction observed consistently across all three models, the underlying pathologies of RP and LCA2 displayed many differences, sharing only four general KEGG pathways. The opposite is true for the two RP models in which we identify remarkable convergence in proteomic phenotype even though the mechanism of primary rod death in rd10 and P23H mice is different. Our data highlights the cAMP and cGMP second-messenger signaling pathways as potential targets for therapeutic intervention. The proteomic data is curated and made publicly available, facilitating the discovery of universal therapeutic targets for RP.

Spectral entropy as a measure of the metaproteome complexity.

The diversity and complexity of the microbiome's genomic landscape are not always mirrored in its proteomic profile. Despite the anticipated proteomic diversity, observed complexities of microbiome samples are often lower than expected. Two main factors contribute to this discrepancy: limitations in mass spectrometry's detection sensitivity and bioinformatics challenges in metaproteomics identification. This study introduces a novel approach to evaluating sample complexity directly at the full mass spectrum (MS1) level rather than relying on peptide identifications. When analyzing under identical mass spectrometry conditions, microbiome samples displayed significantly higher complexity, as evidenced by the spectral entropy and peptide candidate entropy, compared to single-species samples. The research provides solid evidence for the complexity of microbiome in proteomics indicating the optimization potential of the bioinformatics workflow.

A complementary metaproteomic approach to interrogate microbiome cultivated from clinical colon biopsies.

The human gut microbiome plays a vital role in preserving individual health and is intricately involved in essential functions. Imbalances or dysbiosis within the microbiome can significantly impact human health and are associated with many diseases. Several metaproteomics platforms are currently available to study microbial proteins within complex microbial communities. In this study, we attempted to develop an integrated pipeline to provide deeper insights into both the taxonomic and functional aspects of the cultivated human gut microbiomes derived from clinical colon biopsies. We combined a rapid peptide search by MSFragger against the Unified Human Gastrointestinal Protein database and the taxonomic and functional analyses with Unipept Desktop and MetaLab-MAG. Across seven samples, we identified and matched nearly 36,000 unique peptides to approximately 300 species and 11 phyla. Unipept Desktop provided gene ontology, InterPro entries, and enzyme commission number annotations, facilitating the identification of relevant metabolic pathways. MetaLab-MAG contributed functional annotations through Clusters of Orthologous Genes and Non-supervised Orthologous Groups categories. These results unveiled functional similarities and differences among the samples. This integrated pipeline holds the potential to provide deeper insights into the taxonomy and functions of the human gut microbiome for interrogating the intricate connections between microbiome balance and diseases.

Multilevel Proteomic Profiling of Colorectal Adenocarcinoma Caco-2 Cell Differentiation to Characterize an Intestinal Epithelial Model.

Emergent advancements on the role of the intestinal microbiome for human health and disease necessitate well-defined intestinal cellular models to study and rapidly assess host, microbiome, and drug interactions. Differentiated Caco-2 cell line is commonly utilized as an epithelial model for drug permeability studies and has more recently been utilized for investigating host-microbiome interactions. However, its suitability to study such interactions remains to be characterized. Here, we employed multilevel proteomics to demonstrate that both spontaneous and butyrate-induced Caco-2 differentiations displayed similar protein and pathway changes, including the downregulation of proteins related to translation and proliferation and upregulation of functions implicated in host-microbiome interactions, such as cell adhesion, tight junction, extracellular vesicles, and responses to stimuli. Lysine acetylomics revealed that histone protein acetylation levels were decreased along with cell differentiation, while the acetylation in proteins associated with mitochondrial functions was increased. This study also demonstrates that, compared to spontaneous differentiation methods, butyrate-containing medium accelerates Caco-2 differentiation, with earlier upregulation of proteins related to host-microbiome interactions, suggesting its superiority for assay development using this intestinal model. Altogether, this multiomics study emphasizes the controlled progression of Caco-2 differentiation toward a specialized intestinal epithelial-like cell and establishes its suitability for investigating the host-microbiome interactions.

Staufen1 controls mitochondrial metabolism via HIF2α in embryonal rhabdomyosarcoma and promotes tumorigenesis.

Elevated mitochondrial metabolism promotes tumorigenesis of Embryonal Rhabdomyosarcomas (ERMS). Accordingly, targeting oxidative phosphorylation (OXPHOS) could represent a therapeutic strategy for ERMS. We previously demonstrated that genetic reduction of Staufen1 (STAU1) levels results in the inhibition of ERMS tumorigenicity. Here, we examined STAU1-mediated mechanisms in ERMS and focused on its potential involvement in regulating OXPHOS. We report the novel and differential role of STAU1 in mitochondrial metabolism in cancerous versus non-malignant skeletal muscle cells (NMSkMCs). Specifically, our data show that STAU1 depletion reduces OXPHOS and inhibits proliferation of ERMS cells. Our findings further reveal the binding of STAU1 to several OXPHOS mRNAs which affects their stability. Indeed, STAU1 depletion reduced the stability of OXPHOS mRNAs, causing inhibition of mitochondrial metabolism. In parallel, STAU1 depletion impacted negatively the HIF2α pathway which further modulates mitochondrial metabolism. Exogenous expression of HIF2α in STAU1-depleted cells reversed the mitochondrial inhibition and induced cell proliferation. However, opposite effects were observed in NMSkMCs. Altogether, these findings revealed the impact of STAU1 in the regulation of mitochondrial OXPHOS in cancer cells as well as its differential role in NMSkMCs. Overall, our results highlight the therapeutic potential of targeting STAU1 as a novel approach for inhibiting mitochondrial metabolism in ERMS.

The LDL receptor is regulated by membrane cholesterol as revealed by fluorescence fluctuation analysis.

Membrane cholesterol-rich domains have been shown to be important for regulating a range of membrane protein activities. Low-density lipoprotein receptor (LDLR)-mediated internalization of cholesterol-rich LDL particles is tightly regulated by feedback mechanisms involving intracellular sterol sensors. Since LDLR plays a role in maintaining cellular cholesterol homeostasis, we explore the role that membrane domains may have in regulating LDLR activity. We expressed a fluorescent LDLR-mEGFP construct in HEK293T cells and imaged the unligated receptor or bound to an LDL/DiI fluorescent ligand using total internal reflection fluorescence microscopy. We studied the receptor's spatiotemporal dynamics using fluorescence fluctuation analysis methods. Image cross correlation spectroscopy reveals a lower LDL-to-LDLR binding fraction when membrane cholesterol concentrations are augmented using cholesterol esterase, and a higher binding fraction when the cells are treated with methyl-ß-cyclodextrin) to lower membrane cholesterol. This suggests that LDLR's ability to metabolize LDL particles is negatively correlated to membrane cholesterol concentrations. We then tested if a change in activity is accompanied by a change in membrane localization. Image mean-square displacement analysis reveals that unligated LDLR-mEGFP and ligated LDLR-mEGFP/LDL-DiI constructs are transiently confined on the cell membrane, and the size of their confinement domains increases with augmented cholesterol concentrations. Receptor diffusion within the domains and their domain-escape probabilities decrease upon treatment with methyl-ß-cyclodextrin, consistent with a change in receptor populations to more confined domains, likely clathrin-coated pits. We propose a feedback model to account for regulation of LDLR within the cell membrane: when membrane cholesterol concentrations are high, LDLR is sequestered in cholesterol-rich domains. These LDLR populations are attenuated in their efficacy to bind and internalize LDL. However, when membrane cholesterol levels drop, LDL has a higher binding affinity to its receptor and the LDLR transits to nascent clathrin-coated domains, where it diffuses at a slower rate while awaiting internalization.

An emerging field: Post-translational modification in microbiome.

Post-translational modifications (PTMs) play an essential role in most biological processes. PTMs on human proteins have been extensively studied. Studies on bacterial PTMs are emerging, which demonstrate that bacterial PTMs are different from human PTMs in their types, mechanisms and functions. Few PTM studies have been done on the microbiome. Here, we reviewed several studied PTMs in bacteria including phosphorylation, acetylation, succinylation, glycosylation, and proteases. We discussed the enzymes responsible for each PTM and their functions. We also summarized the current methods used to study microbiome PTMs and the observations demonstrating the roles of PTM in the microbe-microbe interactions within the microbiome and their interactions with the environment or host. Although new methods and tools for PTM studies are still needed, the existing technologies have made great progress enabling a deeper understanding of the functional regulation of the microbiome. Large-scale application of these microbiome-wide PTM studies will provide a better understanding of the microbiome and its roles in the development of human diseases.

An economic and robust TMT labeling approach for high throughput proteomic and metaproteomic analysis.

Multiplexed quantitative proteomics using tandem mass tag (TMT) is increasingly used in -omic study of complex samples. While TMT-based proteomics has the advantages of the higher quantitative accuracy, fewer missing values, and reduced instrument analysis time, it is limited by the additional reagent cost. In addition, current TMT labeling workflows involve repeated small volume pipetting of reagents in volatile solvents, which may increase the sample-to-sample variations and is not readily suitable for high throughput applications. In this study, we demonstrated that the TMT labeling procedures could be streamlined by using pre-aliquoted dry TMT reagents in a 96 well plate or 12-tube strip. As little as 50 µg dry TMT per channel was used to label 6-12 µg peptides, yielding high TMT labeling efficiency (∼99%) in both microbiome and mammalian cell line samples. We applied this workflow to analyze 97 samples in a study to evaluate whether ice recrystallization inhibitors improve the cultivability and activity of frozen microbiota. The results demonstrated tight sample clustering corresponding to groups and consistent microbiome responses to prebiotic treatments. This study supports the use of TMT reagents that are pre-aliquoted, dried, and stored for robust quantitative proteomics and metaproteomics in high throughput applications.

MetaLab-MAG: A Metaproteomic Data Analysis Platform for Genome-Level Characterization of Microbiomes from the Metagenome-Assembled Genomes Database.

The studies of microbial communities have drawn increased attention in various research fields such as agriculture, environment, and human health. Recently, metaproteomics has become a powerful tool to interpret the roles of the community members by investigating the expressed proteins of the microbes. However, analyzing the metaproteomic data sets at genome resolution is still challenging because of the lack of efficient bioinformatics tools. Here we develop MetaLab-MAG, a specially designed tool for the characterization of microbiomes from metagenome-assembled genomes databases. MetaLab-MAG was evaluated by analyzing various human gut microbiota data sets and performed comparably or better than searching the gene catalog protein database directly. MetaLab-MAG can quantify the genome-level microbiota compositions and supports both label-free and isobaric labeling-based quantification strategies. MetaLab-MAG removes the obstacles of metaproteomic data analysis and provides the researchers with in-depth and comprehensive information from the microbiomes.

Assessing the Dark Field of Metaproteome.

The human gut microbiome is a complex system composed of hundreds of species, and metaproteomics can be used to explore their expressed functions. However, many lower abundance species are not detected by current metaproteomic techniques and represent the dark field of metaproteomics. We do not know the minimal abundance of a bacterium in a microbiome(depth) that can be detected by shotgun metaproteomics. In this study, we spiked 15N-labeled E. coli peptides at different percentages into peptides mixture derived from the human gut microbiome to evaluate the depth that can be achieved by shotgun metaproteomics. We observed that the number of identified peptides and peptide intensity from 15N-labeled E. coli were linearly correlated with the spike-in levels even when 15N-labeled E. coli was down to 0.5% of the biomass. Below that level, it was not detected. Interestingly, the match-between-run strategy significantly increased the number of quantified peptides even when 15N-labeled E. coli peptides were at low abundance. This is indicative that in metaproteomics of complex gut microbiomes many peptides from low abundant species are likely observable in MS1 but are not selected for MS2 by standard shotgun strategies.

Proteomics and Metaproteomics Add Functional, Taxonomic and Biomass Dimensions to Modeling the Ecosystem at the Mucosal-luminal Interface.

Recent efforts in gut microbiome studies have highlighted the importance of explicitly describing the ecological processes beyond correlative analysis. However, we are still at the early stage of understanding the organizational principles of the gut ecosystem, partially because of the limited information provided by currently used analytical tools in ecological modeling practices. Proteomics and metaproteomics can provide a number of insights for ecological studies, including biomass, matter and energy flow, and functional diversity. In this Mini Review, we discuss proteomics and metaproteomics-based experimental strategies that can contribute to studying the ecology, in particular at the mucosal-luminal interface (MLI) where the direct host-microbiome interaction happens. These strategies include isolation protocols for different MLI components, enrichment methods to obtain designated array of proteins, probing for specific pathways, and isotopic labeling for tracking nutrient flow. Integration of these technologies can generate spatiotemporal and site-specific biological information that supports mathematical modeling of the ecosystem at the MLI.

A non-canonical monovalent zinc finger stabilizes the integration of Cfp1 into the H3K4 methyltransferase complex COMPASS.

COMPlex ASsociating with SET1 (COMPASS) is a histone H3 Lys-4 methyltransferase that typically marks the promoter region of actively transcribed genes. COMPASS is a multi-subunit complex in which the catalytic unit, SET1, is required for H3K4 methylation. An important subunit known to regulate SET1 methyltransferase activity is the CxxC zinc finger protein 1 (Cfp1). Cfp1 binds to COMPASS and is critical to maintain high level of H3K4me3 in cells but the mechanisms underlying its stimulatory activity is poorly understood. In this study, we show that Cfp1 only modestly activates COMPASS methyltransferase activity in vitro. Binding of Cfp1 to COMPASS is in part mediated by a new type of monovalent zinc finger (ZnF). This ZnF interacts with the COMPASS's subunits RbBP5 and disruption of this interaction blunts its methyltransferase activity in cells and in vivo. Collectively, our studies reveal that a novel form of ZnF on Cfp1 enables its integration into COMPASS and contributes to epigenetic signaling.

The Functional Characteristics of Goat Cheese Microbiota from a One-Health Perspective.

Goat cheese is an important element of the Mediterranean diet, appreciated for its health-promoting features and unique taste. A pivotal role in the development of these characteristics is attributed to the microbiota and its continuous remodeling over space and time. Nevertheless, no thorough study of the cheese-associated microbiota using two metaomics approaches has previously been conducted. Here, we employed 16S rRNA gene sequencing and metaproteomics to explore the microbiota of a typical raw goat milk cheese at various ripening timepoints and depths of the cheese wheel. The 16S rRNA gene-sequencing and metaproteomics results described a stable microbiota ecology across the selected ripening timepoints, providing evidence for the microbiologically driven fermentation of goat milk products. The important features of the microbiota harbored on the surface and in the core of the cheese mass were highlighted in both compositional and functional terms. We observed the rind microbiota struggling to maintain the biosafety of the cheese through competition mechanisms and/or by preventing the colonization of the cheese by pathobionts of animal or environmental origin. The core microbiota was focused on other biochemical processes, supporting its role in the development of both the health benefits and the pleasant gustatory nuances of goat cheese.

Associations between Cellular Energy and Pediatric Inflammatory Bowel Disease Patient Response to Treatment.

Inflammatory bowel diseases (IBDs), including Crohn's disease (CD) and ulcerative colitis, are chronic diseases of the gastrointestinal tract, with an unknown etiology, that affect over 6.8 million people worldwide. To characterize disease pathogenesis, proteomic and bioinformatic analyses were performed on colon biopsies collected during diagnostic endoscopy from 119 treatment-naïve pediatric patients, including from 78 IBD patients and 41 non-IBD patients who served as controls. Due to the presence of noninflamed and/or inflamed regions in IBD patients, up to two biopsies were obtained from IBD patients as compared to a single noninflamed biopsy from non-IBD pediatric control patients. Additional biopsies were obtained and analyzed from 33 of the IBD patients after IBD-directed therapeutic intervention for comparison of pre- and post-treatment proteomes. SuperSILAC was utilized to perform quantitative analysis of homogenized tissues, which were processed by filter-aided sample preparation. Hierarchical clustering and principal component analyses revealed proteomic patterns that distinguished inflamed from noninflamed tissues independent of therapy. Gene ontology revealed that proteins downregulated in inflammation are associated with metabolism, whereas upregulated proteins contribute to protein processing. A comparison of pre- and post-treatment proteomes from CD patients identified over 100 proteins that are significantly different between patients who responded and those who did not respond to therapy, including creatine kinase B and basigin.

Exploring the Microbiome-Wide Lysine Acetylation, Succinylation, and Propionylation in Human Gut Microbiota.

Lysine acylations are important post-translational modifications that are present in both eukaryotes and prokaryotes and regulate diverse cellular functions. Our knowledge of the microbiome lysine acylation remains limited due to the lack of efficient analytical and bioinformatics methods for complex microbial communities. Here, we show that the serial enrichment using motif antibodies successfully captures peptides containing lysine acetylation, propionylation, and succinylation from human gut microbiome samples. A new bioinformatic workflow consisting of an unrestricted database search confidently identified >60,000 acetylated, and ∼20,000 propionylated and succinylated gut microbial peptides. The characterization of these identified modification-specific metaproteomes, i.e., meta-PTMomes, demonstrates that lysine acylations are differentially distributed in microbial species with different metabolic capabilities. This study provides an analytical framework for the study of lysine acylations in the microbiome, which enables functional microbiome studies at the post-translational level.

pepFunk: a tool for peptide-centric functional analysis of metaproteomic human gut microbiome studies.

MOTIVATION: Enzymatic digestion of proteins before mass spectrometry analysis is a key process in metaproteomic workflows. Canonical metaproteomic data processing pipelines typically involve matching spectra produced by the mass spectrometer to a theoretical spectra database, followed by matching the identified peptides back to parent-proteins. However, the nature of enzymatic digestion produces peptides that can be found in multiple proteins due to conservation or chance, presenting difficulties with protein and functional assignment. RESULTS: To combat this challenge, we developed pepFunk, a peptide-centric metaproteomic workflow focused on the analysis of human gut microbiome samples. Our workflow includes a curated peptide database annotated with Kyoto Encyclopedia of Genes and Genomes (KEGG) terms and a gene set variation analysis-inspired pathway enrichment adapted for peptide-level data. Analysis using our peptide-centric workflow is fast and highly correlated to a protein-centric analysis, and can identify more enriched KEGG pathways than analysis using protein-level data. Our workflow is open source and available as a web application or source code to be run locally. AVAILABILITY AND IMPLEMENTATION: pepFunk is available online as a web application at https://shiny.imetalab.ca/pepFunk/ with open-source code available from https://github.com/northomics/pepFunk. CONTACT: dfigeys@uottawa.ca. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Chemoenzymatic Method for Glycoproteomic N-Glycan Type Quantitation.

Glycosylation is one of the most important post-translational modifications in biological systems. Current glycoproteome methods mainly focus on qualitative identification of glycosylation sites or intact glycopeptides. However, the systematic quantitation of glycoproteins has remained largely unexplored. Here, we developed a chemoenzymatic method to quantitatively investigate N-glycoproteome based on the N-glycan types. Taking advantage of the specificity of different endoglycosidases and isotope dimethyl labeling, six N-glycan types of structures linked on each glycopeptide, including high-mannose/hybrid, biantennary, and triantennary with/without core fucose, were quantified. As a proof of principle, the glycoproteomic N-glycan type quantitative (glyco-TQ) method was first used to determine the N-glycan type composition of the immunoglobulin G1 (IgG1) Fc fragment. Then we applied the method to analyze the glycan type profile of proteins from the breast cancer cell line MCF7, and we quantitatively revealed the N-glycan type microheterogeneity at the glycopeptide and glycoprotein level. The novel quantitative strategy to evaluate the relative intensity of the six states of N-glycan type glycosylation on each site provides a new avenue to investigate the function of glycoproteins in broad areas, such as cancer biomarker research, pharmaceuticals characterization, and antiglycan vaccine development.

Studying the Temporal Dynamics of the Gut Microbiota Using Metabolic Stable Isotope Labeling and Metaproteomics.

The gut microbiome and its metabolic processes are dynamic systems. Surprisingly, our understanding of gut microbiome dynamics is limited. Here, we report a metaproteomic workflow that involves protein stable isotope probing (protein-SIP) and identification/quantification of partially labeled peptides. We also developed a package, which we call MetaProfiler, that corrects for false identifications and performs phylogenetic and time series analysis for the study of microbiome dynamics. From the stool sample of five mice that were fed with 15N hydrolysate from Ralstonia eutropha, we identified 12 326 nonredundant unlabeled peptides, of which 8256 of their heavy counterparts were quantified. These peptides revealed incorporation profiles over time that were different between and within taxa, as well as between and within clusters of orthologous groups (COGs). Our study helps unravel the complex dynamics of protein synthesis and bacterial dynamics in the mouse microbiome. MetaProfiler and the bioinformatic pipeline are available at https://github.com/northomics/MetaProfiler.git.