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.

Microbial functional diversity across biogeochemical provinces in the central Pacific Ocean.

Enzymes catalyze key reactions within Earth's life-sustaining biogeochemical cycles. Here, we use metaproteomics to examine the enzymatic capabilities of the microbial community (0.2 to 3 µm) along a 5,000-km-long, 1-km-deep transect in the central Pacific Ocean. Eighty-five percent of total protein abundance was of bacterial origin, with Archaea contributing 1.6%. Over 2,000 functional KEGG Ontology (KO) groups were identified, yet only 25 KO groups contributed over half of the protein abundance, simultaneously indicating abundant key functions and a long tail of diverse functions. Vertical attenuation of individual proteins displayed stratification of nutrient transport, carbon utilization, and environmental stress. The microbial community also varied along horizontal scales, shaped by environmental features specific to the oligotrophic North Pacific Subtropical Gyre, the oxygen-depleted Eastern Tropical North Pacific, and nutrient-rich equatorial upwelling. Some of the most abundant proteins were associated with nitrification and C1 metabolisms, with observed interactions between these pathways. The oxidoreductases nitrite oxidoreductase (NxrAB), nitrite reductase (NirK), ammonia monooxygenase (AmoABC), manganese oxidase (MnxG), formate dehydrogenase (FdoGH and FDH), and carbon monoxide dehydrogenase (CoxLM) displayed distributions indicative of biogeochemical status such as oxidative or nutritional stress, with the potential to be more sensitive than chemical sensors. Enzymes that mediate transformations of atmospheric gases like CO, CO2, NO, methanethiol, and methylamines were most abundant in the upwelling region. We identified hot spots of biochemical transformation in the central Pacific Ocean, highlighted previously understudied metabolic pathways in the environment, and provided rich empirical data for biogeochemical models critical for forecasting ecosystem response to climate change.

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.

Metaproteomic analysis of King Ghezo tomb wall (Abomey, Benin) confirms 19th century voodoo sacrifices.

The palace of King Ghezo in Abomey, capital of the ancient kingdom of Dahomey (present-day Benin), houses two sacred huts which are specific funerary structures. It is claimed that the binder in their walls is made of human blood. In the study presented here, we conceived an original strategy to analyze the proteins present on minute amounts of the cladding sampled from the inner facade of the cenotaph wall and establish their origin. The extracted proteins were proteolyzed and the resulting peptides were characterized by high-resolution tandem mass spectrometry. Over 6397 distinct molecular entities were identified using cascading searches. Starting from without a priori searches of an extended generic database, the peptide repertoire was narrowed down to the most representative organisms-identified by means of taxon-specific peptides. A wide diversity of bacteria, fungi, plants, and animals were detected through the available protein material. This inventory was used to archaeologically reconstruct the voodoo rituals of consecration and maintenance of vitality. Several indicators attested to the presence of traces of human and poultry blood in the material taken. This study shows the essential advantages of paleoproteomics and metaproteomics for the study of ancient residues from archaeological excavations or historical monuments.

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.

Proteomic scrutiny of nasal microbiomes: implications for the clinic.

INTRODUCTION: The nasal cavity is the initial site of the human respiratory tract and is one of the habitats where microorganisms colonize. The findings from a growing number of studies have shown that the nasal microbiome is an important factor for human disease and health. 16S rRNA sequencing and metagenomic next-generation sequencing (mNGS) are the most commonly used means of microbiome evaluation. Among them, 16S rRNA sequencing is the primary method used in previous studies of nasal microbiomes. However, neither 16S rRNA sequencing nor mNGS can be used to analyze the genes specifically expressed by nasal microorganisms and their functions. This problem can be addressed by proteomic analysis of the nasal microbiome. AREAS COVERED: In this review, we summarize current advances in research on the nasal microbiome, introduce the methods for proteomic evaluation of the nasal microbiome, and focus on the important roles of proteomic evaluation of the nasal microbiome in the diagnosis and treatment of related diseases. EXPERT OPINION: The detection method for microbiome-expressed proteins is known as metaproteomics. Metaproteomic analysis can help us dig deeper into the nasal microbiomes and provide new targets and ideas for clinical diagnosis and treatment of many nasal dysbiosis-related diseases.

Metaproteomics analysis of anaerobic digestion of food waste by the addition of calcium peroxide and magnetite.

Adding trace calcium peroxide and magnetite into a semi-continuous digester is a new method to effectively improve the anaerobic digestion of food waste. However, the microbial mechanism in this system has not been fully explored. Metaproteomics further revealed that the most active and significantly regulated genus u_p_Chloroflexi had formed a good cooperative relationship with Methanomicrobiales and Methanothrix in the system. u_p_Chloroflexi decomposed more organic compounds into CO2, acetate, amino acids, and other substances by alternating between short aerobic-anaerobic respiration. It perceived and adapted to the surrounding environment by producing biofilm, extracellular enzymes, and accelerating substrate transport, formed a respiratory barrier, and enhanced iron transport capacity by using highly expressed cytochrome C. The methanogens formed reactive oxygen species scavengers and reduced iron transport to prevent oxidative damage. This study provides new insight for improving the efficiency of anaerobic digestion of food waste and identifying key microorganisms and their regulated functional proteins in the calcium peroxide-magnetite digestion system.IMPORTANCEPrevious study has found that the combination of calcium peroxide and magnetite has a good promoting effect on the anaerobic digestion process of food waste. Through multiple omics approaches, information such as microbial population structure and changes in metabolites can be further analyzed. This study can help researchers gain a deeper understanding of the digestion pathway of food waste under the combined action of calcium peroxide and magnetite, further elucidate the impact mechanisms of calcium peroxide and magnetite at the microbial level, and provide theoretical guidance to improve the efficiency and stability of anaerobic digestion of food waste, as well as reduce operational costs. This research contributes to improving energy recovery efficiency, promoting sustainable management and development of food waste, and is of great significance to environmental protection.

Consistency across multi-omics layers in a drug-perturbed gut microbial community.

Multi-omics analyses are used in microbiome studies to understand molecular changes in microbial communities exposed to different conditions. However, it is not always clear how much each omics data type contributes to our understanding and whether they are concordant with each other. Here, we map the molecular response of a synthetic community of 32 human gut bacteria to three non-antibiotic drugs by using five omics layers (16S rRNA gene profiling, metagenomics, metatranscriptomics, metaproteomics and metabolomics). We find that all the omics methods with species resolution are highly consistent in estimating relative species abundances. Furthermore, different omics methods complement each other for capturing functional changes. For example, while nearly all the omics data types captured that the antipsychotic drug chlorpromazine selectively inhibits Bacteroidota representatives in the community, the metatranscriptome and metaproteome suggested that the drug induces stress responses related to protein quality control. Metabolomics revealed a decrease in oligosaccharide uptake, likely caused by Bacteroidota depletion. Our study highlights how multi-omics datasets can be utilized to reveal complex molecular responses to external perturbations in microbial communities.

Microbial diagnostics in periodontal diseases.

Microbial analytical methods have been instrumental in elucidating the complex microbial etiology of periodontal diseases, by shaping our understanding of subgingival community dynamics. Certain pathobionts can orchestrate the establishment of dysbiotic communities that can subvert the host immune system, triggering inflammation and tissue destruction. Yet, diagnosis and management of periodontal conditions still rely on clinical and radiographic examinations, overlooking the well-established microbial etiology. This review summarizes the chronological emergence of periodontal etiological models and the co-evolution with technological advances in microbial detection. We additionally review the microbial analytical approaches currently accessible to clinicians, highlighting their value in broadening the periodontal assessment. The epidemiological importance of obtaining culture-based antimicrobial susceptibility profiles of periodontal taxa for antibiotic resistance surveillance is also underscored, together with clinically relevant analytical approaches to guide antibiotherapy choices, when necessary. Furthermore, the importance of 16S-based community and shotgun metagenomic profiling is discussed in outlining dysbiotic microbial signatures. Because dysbiosis precedes periodontal damage, biomarker identification offers early diagnostic possibilities to forestall disease relapses during maintenance. Altogether, this review highlights the underutilized potential of clinical microbiology in periodontology, spotlighting the clinical areas most conductive to its diagnostic implementation for enhancing prevention, treatment predictability, and addressing global antibiotic resistance.

The Selenoproteome as a Dynamic Response Mechanism to Oxidative Stress in Hydrogenotrophic Methanogenic Communities.

Methanogenesis is a critical process in the carbon cycle that is applied industrially in anaerobic digestion and biogas production. While naturally occurring in diverse environments, methanogenesis requires anaerobic and reduced conditions, although varying degrees of oxygen tolerance have been described. Microaeration is suggested as the next step to increase methane production and improve hydrolysis in digestion processes; therefore, a deeper understanding of the methanogenic response to oxygen stress is needed. To explore the drivers of oxygen tolerance in methanogenesis, two parallel enrichments were performed under the addition of H2/CO2 in an environment without reducing agents and in a redox-buffered environment by adding redox mediator 9,10-anthraquinone-2,7-disulfonate disodium. The cellular response to oxidative conditions is mapped using proteomic analysis. The resulting community showed remarkable tolerance to high-redox environments and was unperturbed in its methane production. Next to the expression of pathways to mitigate reactive oxygen species, the higher redox potential environment showed an increased presence of selenocysteine and selenium-associated pathways. By including sulfur-to-selenium mass shifts in a proteomic database search, we provide the first evidence of the dynamic and large-scale incorporation of selenocysteine as a response to oxidative stress in hydrogenotrophic methanogenesis and the presence of a dynamic selenoproteome.

Quantitative Metaproteomics and Activity-based Protein Profiling of Patient Fecal Microbiome Identifies Host and Microbial Serine-type Endopeptidase Activity Associated With Ulcerative Colitis.

The gut microbiota plays an important yet incompletely understood role in the induction and propagation of ulcerative colitis (UC). Organism-level efforts to identify UC-associated microbes have revealed the importance of community structure, but less is known about the molecular effectors of disease. We performed 16S rRNA gene sequencing in parallel with label-free data-dependent LC-MS/MS proteomics to characterize the stool microbiomes of healthy (n = 8) and UC (n = 10) patients. Comparisons of taxonomic composition between techniques revealed major differences in community structure partially attributable to the additional detection of host, fungal, viral, and food peptides by metaproteomics. Differential expression analysis of metaproteomic data identified 176 significantly enriched protein groups between healthy and UC patients. Gene ontology analysis revealed several enriched functions with serine-type endopeptidase activity overrepresented in UC patients. Using a biotinylated fluorophosphonate probe and streptavidin-based enrichment, we show that serine endopeptidases are active in patient fecal samples and that additional putative serine hydrolases are detectable by this approach compared with unenriched profiling. Finally, as metaproteomic databases expand, they are expected to asymptotically approach completeness. Using ComPIL and de novo peptide sequencing, we estimate the size of the probable peptide space unidentified ("dark peptidome") by our large database approach to establish a rough benchmark for database sufficiency. Despite high variability inherent in patient samples, our analysis yielded a catalog of differentially enriched proteins between healthy and UC fecal proteomes. This catalog provides a clinically relevant jumping-off point for further molecular-level studies aimed at identifying the microbial underpinnings of UC.

The Bee Gut Microbiota: Bridging Infective Agents Potential in the One Health Context.

The bee gut microbiota plays an important role in the services the bees pay to the environment, humans and animals. Alongside, gut-associated microorganisms are vehiculated between apparently remote habitats, promoting microbial heterogeneity of the visited microcosms and the transfer of the microbial genetic elements. To date, no metaproteomics studies dealing with the functional bee microbiota are available. Here, we employ a metaproteomics approach to explore a fraction of the bacterial, fungal, and unicellular parasites inhabiting the bee gut. The bacterial community portrays a dynamic composition, accounting for specimens of human and animal concern. Their functional features highlight the vehiculation of virulence and antimicrobial resistance traits. The fungal and unicellular parasite fractions include environment- and animal-related specimens, whose metabolic activities support the spatial spreading of functional features. Host proteome depicts the major bee physiological activities, supporting the metaproteomics strategy for the simultaneous study of multiple microbial specimens and their host-crosstalks. Altogether, the present study provides a better definition of the structure and function of the bee gut microbiota, highlighting its impact in a variety of strategies aimed at improving/overcoming several current hot topic issues such as antimicrobial resistance, environmental pollution and the promotion of environmental health.

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.

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.

Metaproteomic Analysis of Nasopharyngeal Swab Samples to Identify Microbial Peptides in COVID-19 Patients.

During the COVID-19 pandemic, impaired immunity and medical interventions resulted in cases of secondary infections. The clinical difficulties and dangers associated with secondary infections in patients necessitate the exploration of their microbiome. Metaproteomics is a powerful approach to study the taxonomic composition and functional status of the microbiome under study. In this study, the mass spectrometry (MS)-based data of nasopharyngeal swab samples from COVID-19 patients was used to investigate the metaproteome. We have established a robust bioinformatics workflow within the Galaxy platform, which includes (a) generation of a tailored database of the common respiratory tract pathogens, (b) database search using multiple search algorithms, and (c) verification of the detected microbial peptides. The microbial peptides detected in this study, belong to several opportunistic pathogens such as Streptococcus pneumoniae, Klebsiella pneumoniae, Rhizopus microsporus, and Syncephalastrum racemosum. Microbial proteins with a role in stress response, gene expression, and DNA repair were found to be upregulated in severe patients compared to negative patients. Using parallel reaction monitoring (PRM), we confirmed some of the microbial peptides in fresh clinical samples. MS-based clinical metaproteomics can serve as a powerful tool for detection and characterization of potential pathogens, which can significantly impact the diagnosis and treatment of patients.

Metaproteogenomic Profile of a Mesopelagic Adenylylsulfate Reductase: Course-Based Discovery Using the Ocean Protein Portal.

Adenylylsulfate reductase (Apr) is a flavoprotein with a dissimilatory sulfate reductase function. Its ability to catalyze the reverse reaction in sulfur oxidizers has propelled a complex phylogenetic history of transfers with sulfate reducers and made this enzyme an important protein in ocean sulfur cycling. As part of a graduate course, we analyzed metaproteomic data from the Ocean Protein Portal and observed evidence of Apr alpha (AprA) and beta (AprB) subunits in the Central Pacific Ocean. The protein was originally taxonomically attributed toChlorobium tepidum TLS, a green sulfur bacterium. However, our phylogenomic and oceanographic contextual analysis contradicted this label, instead showing that this protein is consistent with the genomic material from the newly discovered Candidatus Lambdaproteobacteriaclass, implying that the ecological role of this lineage in oxygen minimum twilight zones is underappreciated. This study illustrates how metaproteogenomic analysis can contribute to more accurate metagenomic/proteomic annotations and comprehensive ocean biogeochemical processes conducive to course-based research experiences.

Unipept Desktop 2.0: Construction of Targeted Reference Protein Databases for Metaproteogenomics Analyses.

Unipept Desktop 2.0 is the most recent iteration of the Unipept Desktop tool that adds support for the analysis of metaproteogenomics datasets. Unipept Desktop now supports the automatic construction of targeted protein reference databases that only contain proteins (originating from the UniProtKB resource) associated with a predetermined list of taxa. This improves both the taxonomic and functional resolution of a metaproteomic analysis and yields several technical advantages. By limiting the proteins present in a reference database, it is also possible to perform (meta)proteogenomics analyses. Since the protein reference database resides on the user's local machine, they have complete control over the database used during an analysis. Data no longer need to be transmitted over the Internet, decreasing the time required for an analysis and better safeguarding privacy-sensitive data. As a proof of concept, we present a case study in which a human gut metaproteome dataset is analyzed with Unipept Desktop 2.0 using different targeted databases based on matched 16S rRNA gene sequencing data.

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.

Meta4P: A User-Friendly Tool to Parse Label-Free Quantitative Metaproteomic Data and Taxonomic/Functional Annotations.

We present Meta4P (MetaProteins-Peptides-PSMs Parser), an easy-to-use bioinformatic application designed to integrate label-free quantitative metaproteomic data with taxonomic and functional annotations. Meta4P can retrieve, filter, and process identification and quantification data from three levels of inputs (proteins, peptides, PSMs) in different file formats. Abundance data can be combined with taxonomic and functional information and aggregated at different and customizable levels, including taxon-specific functions and pathways. Meta4P output tables, available in various formats, are ready to be used as inputs for downstream statistical analyses. This user-friendly tool is expected to provide a useful contribution to the field of metaproteomic data analysis, helping make it more manageable and straightforward.

MetaProD: A Highly-Configurable Mass Spectrometry Analyzer for Multiplexed Proteomic and Metaproteomic Data.

The microbiome has been shown to be important for human health because of its influence on disease and the immune response. Mass spectrometry is an important tool for evaluating protein expression and species composition in the microbiome but is technically challenging and time-consuming. Multiplexing has emerged as a way to make spectrometry workflows faster while improving results. Here, we present MetaProD (MetaProteomics in Django) as a highly configurable metaproteomic data analysis pipeline supporting label-free and multiplexed mass spectrometry. The pipeline is open-source, uses fully open-source tools, and is integrated with Django to offer a web-based interface for configuration and data access. Benchmarking of MetaProD using multiple metaproteomics data sets showed that MetaProD achieved fast and efficient identification of peptides and proteins. Application of MetaProD to a multiplexed cancer data set resulted in identification of more differentially expressed human proteins in cancer tissues versus healthy tissues as compared to previous studies; in addition, MetaProD identified bacterial proteins in those samples, some of which are differentially abundant.