Microbial metaproteomics for characterizing the range of metabolic functions and activities of human gut microbiota

Faecal metaproteomics analysis reveals a high cardiovascular risk profile across healthy individuals and heart failure patients

The gut microbiota is a crucial link between diet and cardiovascular disease (CVD). Using fecal metaproteomics, a method that concurrently captures human gut and microbiome proteins, we determined the crosstalk between gut microbiome, diet, gut health, and CVD. Traditional CVD risk factors (age, BMI, sex, blood pressure) explained < 10% of the proteome variance. However, unsupervised human protein-based clustering analysis revealed two distinct CVD risk clusters (low-risk and high-risk) with different blood pressure (by 9 mmHg) and sex-dependent dietary potassium and fiber intake. In the human proteome, the low-risk group had lower angiotensin-converting enzymes, inflammatory proteins associated with neutrophil extracellular trap formation and auto-immune diseases. In the microbial proteome, the low-risk group had higher expression of phosphate acetyltransferase that produces SCFAs, particularly in fiber-fermenting bacteria. This model identified severity across phenotypes in heart failure patients and long-term risk of cardiovascular events in a large population-based cohort. These findings underscore multifactorial gut-to-host mechanisms that may underlie risk factors for CVD.

Insights on Wet and Dry Workflows for Human Gut Metaproteomics

The human gut microbiota (GM) is a community of microorganisms that resides in the gastrointestinal (GI) tract. Recognized as a critical element of human health, the functions of the GM extend beyond GI well-being to influence overall systemic health and susceptibility to disease. Among the other omic sciences, metaproteomics highlights additional facets that make it a highly valuable discipline in the study of GM. Indeed, it allows the protein inventory of complex microbial communities. Proteins with associated taxonomic membership and function are identified and quantified from their constituent peptides by liquid chromatography coupled to mass spectrometry analyses and by querying specific databases (DBs). The aim of this review was to compile comprehensive information on metaproteomic studies of the human GM, with a focus on the bacterial component, to assist newcomers in understanding the methods and types of research conducted in this field. The review outlines key steps in a metaproteomic-based study, such as protein extraction, DB selection, and bioinformatic workflow. The importance of standardization is emphasized. In addition, a list of previously published studies is provided as hints for researchers interested in investigating the role of GM in health and disease states.

Mass spectrometry-based proteomic applications in dental implants research

Dental implants have been established as successful treatment options for missing teeth with steadily increasing demands. Today, the primary areas of research in dental implantology revolve around osseointegration, soft and hard tissue grafting as well as peri-implantitis diagnostics, prevention, and treatment. This review provides a comprehensive overview of the current literature on the application of MS-based proteomics in dental implant research, highlights how explorative proteomics provided insights into the biology of peri-implant soft and hard tissues and how proteomics facilitated the stratification between healthy and diseased implants, enabling the identification of potential new diagnostic markers. Additionally, this review illuminates technical aspects, and provides recommendations for future study designs based on the current evidence.

The role of insect gut microbiota in host fitness, detoxification and nutrient supplementation

Insects are incredibly diverse, ubiquitous and have successfully flourished out of the dynamic and often unpredictable nature of evolutionary processes. The resident microbiome has accompanied the physical and biological adaptations that enable their continued survival and proliferation in a wide array of environments. The host insect and microbiome's bidirectional relationship exhibits their capability to influence each other's physiology, behavior and characteristics. Insects are reported to rely directly on the microbial community to break down complex food, adapt to nutrient-deficit environments, protect themselves from natural adversaries and control the expression of social behavior. High-throughput metagenomic approaches have enhanced the potential for determining the abundance, composition, diversity and functional activities of microbial fauna associated with insect hosts, enabling in-depth investigation into insect-microbe interactions. We undertook a review of some of the major advances in the field of metagenomics, focusing on insect-microbe interaction, diversity and composition of resident microbiota, the functional capability of endosymbionts and discussions on different symbiotic relationships. The review aims to be a valuable resource on insect gut symbiotic microbiota by providing a comprehensive understanding of how insect gut symbionts systematically perform a range of functions, viz., insecticide degradation, nutritional support and immune fitness. A thorough understanding of manipulating specific gut symbionts may aid in developing advanced insect-associated research to attain health and design strategies for pest management.

A comprehensive overview of microbiome data in the light of machine learning applications: categorization, accessibility, and future directions

Metagenomics, Metabolomics, and Metaproteomics have significantly advanced our knowledge of microbial communities by providing culture-independent insights into their composition and functional potential. However, a critical challenge in this field is the lack of standard and comprehensive metadata associated with raw data, hindering the ability to perform robust data stratifications and consider confounding factors. In this comprehensive review, we categorize publicly available microbiome data into five types: shotgun sequencing, amplicon sequencing, metatranscriptomic, metabolomic, and metaproteomic data. We explore the importance of metadata for data reuse and address the challenges in collecting standardized metadata. We also, assess the limitations in metadata collection of existing public repositories collecting metagenomic data. This review emphasizes the vital role of metadata in interpreting and comparing datasets and highlights the need for standardized metadata protocols to fully leverage metagenomic data's potential. Furthermore, we explore future directions of implementation of Machine Learning (ML) in metadata retrieval, offering promising avenues for a deeper understanding of microbial communities and their ecological roles. Leveraging these tools will enhance our insights into microbial functional capabilities and ecological dynamics in diverse ecosystems. Finally, we emphasize the crucial metadata role in ML models development.

Techniques, procedures, and applications in microbiome analysis

Microbiota is a complex community of microorganisms living in a defined environment. Until the 20th century, knowledge of microbiota was partial, as the techniques available for their characterization were primarily based on bacteriological culture. In the last twenty years, the development of DNA sequencing technologies, multi-omics, and bioinformatics has expanded our understanding of microorganisms. We have moved from mainly considering them isolated disease-causing agents to recognizing the microbiota as an essential component of host biology. These techniques have shown that the microbiome plays essential roles in various host phenotypes, influencing development, physiology, reproduction, and evolution. This chapter provides researchers with a summary of the primary concepts, sample collection, experimental techniques, and bioinformatics analysis commonly used in microbiome research. The main features, applications in microbiome studies, and their advantages and limitations are included in each section.

Aromatic amino acid metabolism and active transport regulation are implicated in microbial persistence in fractured shale reservoirs

Hydraulic fracturing has unlocked vast amounts of hydrocarbons trapped within unconventional shale formations. This large-scale engineering approach inadvertently introduces microorganisms into the hydrocarbon reservoir, allowing them to inhabit a new physical space and thrive in the unique biogeochemical resources present in the environment. Advancing our fundamental understanding of microbial growth and physiology in this extreme subsurface environment is critical to improving biofouling control efficacy and maximizing opportunities for beneficial natural resource exploitation. Here, we used metaproteomics and exometabolomics to investigate the biochemical mechanisms underpinning the adaptation of model bacterium Halanaerobium congolense WG10 and mixed microbial consortia enriched from shale-produced fluids to hypersalinity and very low reservoir flow rates (metabolic stress). We also queried the metabolic foundation for biofilm formation in this system, a major impediment to subsurface energy exploration. For the first time, we report that H. congolense WG10 accumulates tyrosine for osmoprotection, an indication of the flexible robustness of stress tolerance that enables its long-term persistence in fractured shale environments. We also identified aromatic amino acid synthesis and cell wall maintenance as critical to biofilm formation. Finally, regulation of transmembrane transport is key to metabolic stress adaptation in shale bacteria under very low well flow rates. These results provide unique insights that enable better management of hydraulically fractured shale systems, for more efficient and sustainable energy extraction.

Infant gut microbiota contributes to cognitive performance in mice

Gut microbiota has been linked to infant neurodevelopment. Here, an association between infant composite cognition and gut microbiota composition is established as soon as 6 months. Higher diversity and evenness characterize microbial communities of infants with composite cognition above (Inf-aboveCC) versus below (Inf-belowCC) median values. Metaproteomic and metabolomic analyses establish an association between microbial histidine ammonia lyase and infant histidine metabolome with cognition. Fecal transplantation from Inf-aboveCC versus Inf-belowCC donors into germ-free mice shows that memory, assessed by a novel object recognition test, is a transmissible trait. Furthermore, Inf-aboveCC mice are enriched in species belonging to Phocaeicola, as well as Bacteroides and Bifidobacterium, previously linked to cognition. Finally, Inf-aboveCC mice show lower fecal histidine and urocanate:histidine and urocanate:glutamate ratios in the perirhinal cortex compared to Inf-belowCC mice. Overall, these findings reveal a causative role of gut microbiota on infant cognition, pointing at the modulation of histidine metabolite levels as a potential underlying mechanism.

Integrated multi-omics reveals the beneficial role of chlorogenic acid in improving the growth performance and immune function of immunologically stressed broilers

Intensive production can cause immunological stress in commercial broilers. Chlorogenic acid (CGA) regulates the intestinal microbiota, barrier function, and immune function in chickens. As complex interrelations regulate the dynamic interplay between gut microbiota, the host, and diverse health outcomes, the aim of this study was to elucidate the immunoregulatory mechanisms of CGA using multi-omics approaches. A total of 240 one-day-old male broilers were assigned to a 2 × 2 factorial design with 2 CGA levels (0 or 500 mg/kg) either with or without dexamethasone (DEX) injection for a 21-day experimental period. Therefore, there were 4 dietary treatments: control, DEX, CGA, and DEX + CGA, with 6 replicates per treatment. CGA supplementation improved (P < 0.05) growth performance, jejunal morphology, jejunal barrier function, and immune function in DEX-treated broilers. Moreover, in DEX + CGA-treated broilers, the increase in gut microbiome diversity (P < 0.05) was consistent with a change in taxonomic composition, especially in the Clostridiales vadin BB60_group. Additionally, the levels of short-chain fatty acids increased remarkably (P < 0.01) after CGA supplementation. This was consistent with the Kyoto Encyclopedia of Genes and Genomes analysis results that the "pyruvate fermentation to butanoate" pathway was more enriched (P < 0.01) in the DEX + CGA group than in the DEX group. Proteomics revealed that CGA treatment increased the expression of several health-promoting proteins, thymosin beta (TMSB4X) and legumain (LGMN), which were verified by multiple reaction monitoring. Metabolomics revealed that CGA treatment increased the expression of health-promoting metabolites (2,4-dihydroxy benzoic acid and homogentisic acid). Proteomic and metabolic analyses showed that CGA treatment regulated the peroxisome proliferator-activated receptor (PPAR) and mitogen-activated protein kinase (MAPK) pathways. Western blotting results support these findings. Pearson's correlation analyses showed correlations (P < 0.01) between altered immune function, jejunal barrier function, different microbiota, proteins, and metabolites parameters. Overall, our data indicate that CGA treatment increased growth performance and improved the immunological functions of DEX-treated broilers by regulating gut microbiota and the PPAR and MAPK pathways. The results offer novel insights into a CGA-mediated improvement in immune function and intestinal health.

Effects of microbial-derived biotics (meta/pharma/post-biotics) on the modulation of gut microbiome and metabolome; general aspects and emerging trends

Potential effects of metabiotics (probiotics effector molecules or signaling factors), pharmabiotics (pro-functional metabolites produced by gut microbiota (GMB)) and postbiotics (multifunctional metabolites and structural compounds of food-grade microorganisms) on GMB have been rarely reviewed. These multifunctional components have several promising capabilities for prevention, alleviation and treatment of some diseases or disorders. Correlations between these essential biotics and GMB are also very interesting and important in human health and nutrition. Furthermore, these natural bioactives are involved in modulation of the immune function, control of metabolic dysbiosis and regulation of the signaling pathways. This review discusses the potential of meta/pharma/post-biotics as new classes of pharmaceutical agents and their effective mechanisms associated with GMB-host cell to cell communications with therapeutic benefits which are important in balance and the integrity of the host microbiome. In addition, cutting-edge findings about bioinformatics /metabolomics analyses related to GMB and these essential biotics are reviewed.

Chronic Strongyloides stercoralis infection increases presence of the Ruminococcus torques group in the gut and alters the microbial proteome

We explored the impact of chronic Strongyloides stercoralis infection on the gut microbiome and microbial activity in a longitudinal study. At baseline (time-point T0), 42 fecal samples from matched individuals (21 positive for strongyloidiasis and 21 negative) were subjected to microbiome 16S-rRNA sequencing. Those positive at T0 (untreated then because of COVID19 lockdowns) were retested one year later (T1). Persistent infection in these individuals indicated chronic strongyloidiasis: they were treated with ivermectin and retested four months later (T2). Fecal samples at T1 and T2 were subjected to 16S-rRNA sequencing and LC-MS/MS to determine microbial diversity and proteomes. No significant alteration of indices of gut microbial diversity was found in chronic strongyloidiasis. However, the Ruminococcus torques group was highly over-represented in chronic infection. Metaproteome data revealed enrichment of Ruminococcus torques mucin-degrader enzymes in infection, possibly influencing the ability of the host to expel parasites. Metaproteomics indicated an increase in carbohydrate metabolism and Bacteroidaceae accounted for this change in chronic infection. STITCH interaction networks explored highly expressed microbial proteins before treatment and short-chain fatty acids involved in the synthesis of acetate. In conclusion, our data indicate that chronic S. stercoralis infection increases Ruminococcus torques group and alters the microbial proteome.

The need for an integrated multi-OMICs approach in microbiome science in the food system

Microbiome science as an interdisciplinary research field has evolved rapidly over the past two decades, becoming a popular topic not only in the scientific community and among the general public, but also in the food industry due to the growing demand for microbiome-based technologies that provide added-value solutions. Microbiome research has expanded in the context of food systems, strongly driven by methodological advances in different -omics fields that leverage our understanding of microbial diversity and function. However, managing and integrating different complex -omics layers are still challenging. Within the Coordinated Support Action MicrobiomeSupport (https://www.microbiomesupport.eu/), a project supported by the European Commission, the workshop "Metagenomics, Metaproteomics and Metabolomics: the need for data integration in microbiome research" gathered 70 participants from different microbiome research fields relevant to food systems, to discuss challenges in microbiome research and to promote a switch from microbiome-based descriptive studies to functional studies, elucidating the biology and interactive roles of microbiomes in food systems. A combination of technologies is proposed. This will reduce the biases resulting from each individual technology and result in a more comprehensive view of the biological system as a whole. Although combinations of different datasets are still rare, advanced bioinformatics tools and artificial intelligence approaches can contribute to understanding, prediction, and management of the microbiome, thereby providing the basis for the improvement of food quality and safety.

Petroleum Hydrocarbon Catabolic Pathways as Targets for Metabolic Engineering Strategies for Enhanced Bioremediation of Crude-Oil-Contaminated Environments

Anthropogenic activities and industrial effluents are the major sources of petroleum hydrocarbon contamination in different environments. Microbe-based remediation techniques are known to be effective, inexpensive, and environmentally safe. In this review, the metabolic-target-specific pathway engineering processes used for improving the bioremediation of hydrocarbon-contaminated environments have been described. The microbiomes are characterised using environmental genomics approaches that can provide a means to determine the unique structural, functional, and metabolic pathways used by the microbial community for the degradation of contaminants. The bacterial metabolism of aromatic hydrocarbons has been explained via peripheral pathways by the catabolic actions of enzymes, such as dehydrogenases, hydrolases, oxygenases, and isomerases. We proposed that by using microbiome engineering techniques, specific pathways in an environment can be detected and manipulated as targets. Using the combination of metabolic engineering with synthetic biology, systemic biology, and evolutionary engineering approaches, highly efficient microbial strains may be utilised to facilitate the target-dependent bioprocessing and degradation of petroleum hydrocarbons. Moreover, the use of CRISPR-cas and genetic engineering methods for editing metabolic genes and modifying degradation pathways leads to the selection of recombinants that have improved degradation abilities. The idea of growing metabolically engineered microbial communities, which play a crucial role in breaking down a range of pollutants, has also been explained. However, the limitations of the in-situ implementation of genetically modified organisms pose a challenge that needs to be addressed in future research.

Characterization and Spatial Mapping of the Human Gut Metasecretome

Bacterially secreted proteins play an important role in microbial physiology and ecology in many environments, including the mammalian gut. While gut microbes have been extensively studied over the past decades, little is known about the proteins that they secrete into the gastrointestinal tract. In this study, we developed and applied a computational pipeline to a comprehensive catalog of human-associated metagenome-assembled genomes in order to predict and analyze the bacterial metasecretome of the human gut, i.e., the collection of proteins secreted out of the cytoplasm by human gut bacteria. We identified the presence of large and diverse families of secreted carbohydrate-active enzymes and assessed their phylogenetic distributions across different taxonomic groups, which revealed an enrichment in Bacteroidetes and Verrucomicrobia. By mapping secreted proteins to available metagenomic data from endoscopic sampling of the human gastrointestinal tract, we specifically pinpointed regions in the upper and lower intestinal tract along the lumen and mucosa where specific glycosidases are secreted by resident microbes. The metasecretome analyzed in this study constitutes the most comprehensive list of secreted proteins produced by human gut bacteria reported to date and serves as a useful resource for the microbiome research community. IMPORTANCE Bacterially secreted proteins are necessary for the proper functioning of bacterial cells and communities. Secreted proteins provide bacterial cells with the ability to harvest resources from the exterior, import these resources into the cell, and signal to other bacteria. In the human gut microbiome, these actions impact host health and allow the maintenance of a healthy gut bacterial community. We utilized computational tools to identify the major components of human gut bacterially secreted proteins and determined their spatial distribution in the gastrointestinal tract. Our analysis of human gut bacterial secreted proteins will allow a better understanding of the impact of gut bacteria on human health and represents a step toward identifying new protein functions with interesting applications in biomedicine and industry.

The Promises, Challenges, and Opportunities of Omics for Studying the Plant Holobiont

Microorganisms are critical drivers of biological processes that contribute significantly to plant sustainability and productivity. In recent years, emerging research on plant holobiont theory and microbial invasion ecology has radically transformed how we study plant–microbe interactions. Over the last few years, we have witnessed an accelerating pace of advancements and breadth of questions answered using omic technologies. Herein, we discuss how current state-of-the-art genomics, transcriptomics, proteomics, and metabolomics techniques reliably transcend the task of studying plant–microbe interactions while acknowledging existing limitations impeding our understanding of plant holobionts.

MetaLP: An integrative linear programming method for protein inference in metaproteomics

Metaproteomics based on high-throughput tandem mass spectrometry (MS/MS) plays a crucial role in characterizing microbiome functions. The acquired MS/MS data is searched against a protein sequence database to identify peptides, which are then used to infer a list of proteins present in a metaproteome sample. While the problem of protein inference has been well-studied for proteomics of single organisms, it remains a major challenge for metaproteomics of complex microbial communities because of the large number of degenerate peptides shared among homologous proteins in different organisms. This challenge calls for improved discrimination of true protein identifications from false protein identifications given a set of unique and degenerate peptides identified in metaproteomics. MetaLP was developed here for protein inference in metaproteomics using an integrative linear programming method. Taxonomic abundance information extracted from metagenomics shotgun sequencing or 16s rRNA gene amplicon sequencing, was incorporated as prior information in MetaLP. Benchmarking with mock, human gut, soil, and marine microbial communities demonstrated significantly higher numbers of protein identifications by MetaLP than ProteinLP, PeptideProphet, DeepPep, PIPQ, and Sipros Ensemble. In conclusion, MetaLP could substantially improve protein inference for complex metaproteomes by incorporating taxonomic abundance information in a linear programming model.

Morphine and high-fat diet differentially alter the gut microbiota composition and metabolic function in lean versus obese mice

There are known associations between opioids, obesity, and the gut microbiome, but the molecular connection/mediation of these relationships is not understood. To better clarify the interplay of physiological, genetic, and microbial factors, this study investigated the microbiome and host inflammatory responses to chronic opioid administration in genetically obese, diet-induced obese, and lean mice. Samples of feces, urine, colon tissue, and plasma were analyzed using targeted LC-MS/MS quantification of metabolites, immunoassays of inflammatory cytokine levels, genome-resolved metagenomics, and metaproteomics. Genetic obesity, diet-induced obesity, and morphine treatment in lean mice each showed increases in distinct inflammatory cytokines. Metagenomic assembly and binning uncovered over 400 novel gut bacterial genomes and species. Morphine administration impacted the microbiome's composition and function, with the strongest effect observed in lean mice. This microbiome effect was less pronounced than either diet or genetically driven obesity. Based on inferred microbial physiology from the metaproteome datasets, a high-fat diet transitioned constituent microbes away from harvesting diet-derived nutrients and towards nutrients present in the host mucosal layer. Considered together, these results identified novel host-dependent phenotypes, differentiated the effects of genetic obesity versus diet induced obesity on gut microbiome composition and function, and showed that chronic morphine administration altered the gut microbiome.

Exploring Drug Metabolism by the Gut Microbiota: Modes of Metabolism and Experimental Approaches

Increasing evidence uncovers the involvement of gut microbiota in the metabolism of numerous pharmaceutical drugs. The human gut microbiome harbors 10-100 trillion symbiotic gut microbial bacteria that use drugs as substrates for enzymatic processes to alter host metabolism. Thus, microbiota-mediated drug metabolism can change the conventional drug action course and cause inter-individual differences in efficacy and toxicity, making it vital for drug discovery and development. This review focuses on drug biotransformation pathways and discusses different models for evaluating the role of gut microbiota in drug metabolism. SIGNIFICANCE STATEMENT: This review emphasizes the importance of gut microbiota and different modes of drug metabolism mediated by them. It provides information on in vivo, in vitro, ex vivo, in silico and multi-omics approaches for identifying the role of gut microbiota in metabolism. Further, it highlights the significance of gut microbiota-mediated metabolism in the process of new drug discovery and development as a rationale for safe and efficacious drug therapy.

Considerations for Constructing a Protein Sequence Database for Metaproteomics

Mass spectrometry-based metaproteomics has emerged as a prominent technique for interrogating the functions of specific organisms in microbial communities, in addition to total community function. Identifying proteins by mass spectrometry requires matching mass spectra of fragmented peptide ions to a database of protein sequences corresponding to the proteins in the sample. This sequence database determines which protein sequences can be identified from the measurement, and as such the taxonomic and functional information that can be inferred from a metaproteomics measurement. Thus, the construction of the protein sequence database directly impacts the outcome of any metaproteomics study. Several factors, such as source of sequence information and database curation, need to be considered during database construction to maximize accurate protein identifications traceable to the species of origin. In this review, we provide an overview of existing strategies for database construction and the relevant studies that have sought to test and validate these strategies. Based on this review of the literature and our experience we provide a decision tree and best practices for choosing and implementing database construction strategies.

Metaproteomics Approach and Pathway Modulation in Obesity and Diabetes: A Narrative Review

Low-grade inflammatory diseases revealed metabolic perturbations that have been linked to various phenotypes, including gut microbiota dysbiosis. In the last decade, metaproteomics has been used to investigate protein composition profiles at specific steps and in specific healthy/pathologic conditions. We applied a rigorous protocol that relied on PRISMA guidelines and filtering criteria to obtain an exhaustive study selection that finally resulted in a group of 10 studies, based on metaproteomics and that aim at investigating obesity and diabetes. This batch of studies was used to discuss specific microbial and human metaproteome alterations and metabolic patterns in subjects affected by diabetes (T1D and T2D) and obesity. We provided the main up- and down-regulated protein patterns in the inspected pathologies. Despite the available results, the evident paucity of metaproteomic data is to be considered as a limiting factor in drawing objective considerations. To date, ad hoc prepared metaproteomic databases collecting pathologic data and related metadata, together with standardized analysis protocols, are required to increase our knowledge on these widespread pathologies.

Evaluation of Sample Preservation and Storage Methods for Metaproteomics Analysis of Intestinal Microbiomes

A critical step in studies of the intestinal microbiome using meta-omics approaches is the preservation of samples before analysis. Preservation is essential for approaches that measure gene expression, such as metaproteomics, which is used to identify and quantify proteins in microbiomes. Intestinal microbiome samples are typically stored by flash-freezing and storage at -80°C, but some experimental setups do not allow for immediate freezing of samples. In this study, we evaluated methods to preserve fecal microbiome samples for metaproteomics analyses when flash-freezing is not possible. We collected fecal samples from C57BL/6 mice and stored them for 1 and 4 weeks using the following methods: flash-freezing in liquid nitrogen, immersion in RNAlater, immersion in 95% ethanol, immersion in a RNAlater-like buffer, and combinations of these methods. After storage, we extracted protein and prepared peptides for liquid chromatography with tandem mass spectrometry (LC-MS/MS) analysis to identify and quantify peptides and proteins. All samples produced highly similar metaproteomes, except for ethanol-preserved samples that were distinct from all other samples in terms of protein identifications and protein abundance profiles. Flash-freezing and RNAlater (or RNAlater-like treatments) produced metaproteomes that differed only slightly, with less than 0.7% of identified proteins differing in abundance. In contrast, ethanol preservation resulted in an average of 9.5% of the identified proteins differing in abundance between ethanol and the other treatments. Our results suggest that preservation at room temperature in RNAlater or an RNAlater-like solution performs as well as freezing for the preservation of intestinal microbiome samples before metaproteomics analyses. IMPORTANCE Metaproteomics is a powerful tool to study the intestinal microbiome. By identifying and quantifying a large number of microbial, dietary, and host proteins in microbiome samples, metaproteomics provides direct evidence of the activities and functions of microbial community members. A critical step for metaproteomics workflows is preserving samples before analysis because protein profiles are susceptible to fast changes in response to changes in environmental conditions (air exposure, temperature changes, etc.). This study evaluated the effects of different preservation treatments on the metaproteomes of intestinal microbiome samples. In contrast to prior work on preservation of fecal samples for metaproteomics analyses, we ensured that all steps of sample preservation were identical so that all differences could be attributed to the preservation method.

MPA_Pathway_Tool: User-Friendly, Automatic Assignment of Microbial Community Data on Metabolic Pathways

Taxonomic and functional characterization of microbial communities from diverse environments such as the human gut or biogas plants by multi-omics methods plays an ever more important role. Researchers assign all identified genes, transcripts, or proteins to biological pathways to better understand the function of single species and microbial communities. However, due to the versality of microbial metabolism and a still-increasing number of newly biological pathways, linkage to standard pathway maps such as the KEGG central carbon metabolism is often problematic. We successfully implemented and validated a new user-friendly, stand-alone web application, the MPA_Pathway_Tool. It consists of two parts, called 'Pathway-Creator' and 'Pathway-Calculator'. The 'Pathway-Creator' enables an easy set-up of user-defined pathways with specific taxonomic constraints. The 'Pathway-Calculator' automatically maps microbial community data from multiple measurements on selected pathways and visualizes the results. The MPA_Pathway_Tool is implemented in Java and ReactJS.

Palaeoproteomic analyses of dog palaeofaeces reveal a preserved dietary and host digestive proteome

The domestic dog has inhabited the anthropogenic niche for at least 15 000 years, but despite their impact on human strategies, the lives of dogs and their interactions with humans have only recently become a subject of interest to archaeologists. In the Arctic, dogs rely exclusively on humans for food during the winter, and while stable isotope analyses have revealed dietary similarities at some sites, deciphering the details of provisioning strategies have been challenging. In this study, we apply zooarchaeology by mass spectrometry (ZooMS) and liquid chromatography tandem mass spectrometry to dog palaeofaeces to investigate protein preservation in this highly degradable material and obtain information about the diet of domestic dogs at the Nunalleq site, Alaska. We identify a suite of digestive and metabolic proteins from the host species, demonstrating the utility of this material as a novel and viable substrate for the recovery of gastrointestinal proteomes. The recovered proteins revealed that the Nunalleq dogs consumed a range of Pacific salmon species (coho, chum, chinook and sockeye) and that the consumed tissues derived from muscle and bone tissues as well as roe and guts. Overall, the study demonstrated the viability of permafrost-preserved palaeofaeces as a unique source of host and dietary proteomes.

Omic methodologies for assessing metal(-loid)s-host-microbiota interplay: A review

Omic methodologies have become key analytical tools in a wide number of research topics such as systems biology, environmental analysis, biomedicine or food analysis. They are especially useful when they are combined providing a new perspective and a holistic view of the analytical problem. Methodologies for microbiota analysis have been mostly focused on genome sequencing. However, information provided by these metagenomic studies is limited to the identification of the presence of genes, taxa and their inferred functionality. To achieve a deeper knowledge of microbial functionality in health and disease, especially in dysbiosis conditions related to metal and metalloid exposure, the introduction of additional meta-omic approaches including metabolomics, metallomics, metatranscriptomics and metaproteomics results essential. The possible impact of metals and metalloids on the gut microbiota and their effects on gut-brain axis (GBA) only begin to be figured out. To this end new analytical workflows combining powerful tools are claimed such as high resolution mass spectrometry and heteroatom-tagged proteomics for the absolute quantification of metal-containing biomolecules using the metal as a "tag" in a sensitive and selective detector (e.g. ICP-MS). This review focus on current analytical methodologies related with the analytical techniques and procedures available for metallomics and microbiota analysis with a special attention on their advantages and drawbacks.

MAPLE: A Microbiome Analysis Pipeline Enabling Optimal Peptide Search and Comparative Taxonomic and Functional Analysis

Metaproteomics by mass spectrometry (MS) is a powerful approach to profile a large number of proteins expressed by all organisms in a highly complex biological or ecological sample, which is able to provide a direct and quantitative assessment of the functional makeup of a microbiota. The human gastrointestinal microbiota has been found playing important roles in human physiology and health, and metaproteomics has been shown to shed light on multiple novel associations between microbiota and diseases. MS-powered proteomics generally relies on genome data to define search space. However, metaproteomics, which simultaneously analyzes all proteins from hundreds to thousands of species, faces significant challenges regarding database search and interpretation of results. To overcome these obstacles, we have developed a user-friendly microbiome analysis pipeline (MAPLE, freely downloadable at http://maple.rx.umaryland.edu/), which is able to define an optimal search space by inferring proteomes specific to samples following the principle of parsimony. MAPLE facilitates highly comparable or better peptide identification compared to a sample-specific metagenome-guided search. In addition, we implemented an automated peptide-centric enrichment analysis function in MAPLE to address issues of traditional protein-centric comparison, enabling straightforward and comprehensive comparison of taxonomic and functional makeup between microbiota.

Microbial function and genital inflammation in young South African women at high risk of HIV infection

BACKGROUND

Female genital tract (FGT) inflammation is an important risk factor for HIV acquisition. The FGT microbiome is closely associated with inflammatory profile; however, the relative importance of microbial activities has not been established. Since proteins are key elements representing actual microbial functions, this study utilized metaproteomics to evaluate the relationship between FGT microbial function and inflammation in 113 young and adolescent South African women at high risk of HIV infection. Women were grouped as having low, medium, or high FGT inflammation by K-means clustering according to pro-inflammatory cytokine concentrations.

RESULTS

A total of 3186 microbial and human proteins were identified in lateral vaginal wall swabs using liquid chromatography-tandem mass spectrometry, while 94 microbial taxa were included in the taxonomic analysis. Both metaproteomics and 16S rRNA gene sequencing analyses showed increased non-optimal bacteria and decreased lactobacilli in women with FGT inflammatory profiles. However, differences in the predicted relative abundance of most bacteria were observed between 16S rRNA gene sequencing and metaproteomics analyses. Bacterial protein functional annotations (gene ontology) predicted inflammatory cytokine profiles more accurately than bacterial relative abundance determined by 16S rRNA gene sequence analysis, as well as functional predictions based on 16S rRNA gene sequence data (p < 0.0001). The majority of microbial biological processes were underrepresented in women with high inflammation compared to those with low inflammation, including a Lactobacillus-associated signature of reduced cell wall organization and peptidoglycan biosynthesis. This signature remained associated with high FGT inflammation in a subset of 74 women 9 weeks later, was upheld after adjusting for Lactobacillus relative abundance, and was associated with in vitro inflammatory cytokine responses to Lactobacillus isolates from the same women. Reduced cell wall organization and peptidoglycan biosynthesis were also associated with high FGT inflammation in an independent sample of ten women.

CONCLUSIONS

Both the presence of specific microbial taxa in the FGT and their properties and activities are critical determinants of FGT inflammation. Our findings support those of previous studies suggesting that peptidoglycan is directly immunosuppressive, and identify a possible avenue for biotherapeutic development to reduce inflammation in the FGT. To facilitate further investigations of microbial activities, we have developed the FGT-DB application that is available at http://fgtdb.org/ . Video Abstract.

Gut-Brain Axis and Neurodegeneration: State-of-the-Art of Meta-Omics Sciences for Microbiota Characterization

Recent advances in the field of meta-omics sciences and related bioinformatics tools have allowed a comprehensive investigation of human-associated microbiota and its contribution to achieving and maintaining the homeostatic balance. Bioactive compounds from the microbial community harboring the human gut are involved in a finely tuned network of interconnections with the host, orchestrating a wide variety of physiological processes. These includes the bi-directional crosstalk between the central nervous system, the enteric nervous system, and the gastrointestinal tract (i.e., gut-brain axis). The increasing accumulation of evidence suggest a pivotal role of the composition and activity of the gut microbiota in neurodegeneration. In the present review we aim to provide an overview of the state-of-the-art of meta-omics sciences including metagenomics for the study of microbial genomes and taxa strains, metatranscriptomics for gene expression, metaproteomics and metabolomics to identify and/or quantify microbial proteins and metabolites, respectively. The potential and limitations of each discipline were highlighted, as well as the advantages of an integrated approach (multi-omics) to predict microbial functions and molecular mechanisms related to human diseases. Particular emphasis is given to the latest results obtained with these approaches in an attempt to elucidate the link between the gut microbiota and the most common neurodegenerative diseases, such as multiple sclerosis (MS), Alzheimer's disease (AD), Parkinson's disease (PD), and amyotrophic lateral sclerosis (ALS).

Resources and tools for the high-throughput, multi-omic study of intestinal microbiota

The human gut microbiome impacts several aspects of human health and disease, including digestion, drug metabolism and the propensity to develop various inflammatory, autoimmune and metabolic diseases. Many of the molecular processes that play a role in the activity and dynamics of the microbiota go beyond species and genic composition and thus, their understanding requires advanced bioinformatics support. This article aims to provide an up-to-date view of the resources and software tools that are being developed and used in human gut microbiome research, in particular data integration and systems-level analysis efforts. These efforts demonstrate the power of standardized and reproducible computational workflows for integrating and analysing varied omics data and gaining deeper insights into microbe community structure and function as well as host-microbe interactions.

Most dominant roles of insect gut bacteria: digestion, detoxification, or essential nutrient provision?

BACKGROUND

The insect gut microbiota has been shown to contribute to the host's digestion, detoxification, development, pathogen resistance, and physiology. However, there is poor information about the ranking of these roles. Most of these results were obtained with cultivable bacteria, whereas the bacterial physiology may be different between free-living and midgut-colonizing bacteria. In this study, we provided both proteomic and genomic evidence on the ranking of the roles of gut bacteria by investigating the anal droplets from a weevil, Cryptorhynchus lapathi.

RESULTS

The gut lumen and the anal droplets showed qualitatively and quantitatively different subsets of bacterial communities. The results of 16S rRNA sequencing showed that the gut lumen is dominated by Proteobacteria and Bacteroidetes, whereas the anal droplets are dominated by Proteobacteria. From the anal droplets, enzymes involved in 31 basic roles that belong to 7 super roles were identified by Q-TOF MS. The cooperation between the weevil and its gut bacteria was determined by reconstructing community pathway maps, which are defined in this study. A score was used to rank the gut bacterial roles. The results from the proteomic data indicate that the most dominant role of gut bacteria is amino acid biosynthesis, followed by protein digestion, energy metabolism, vitamin biosynthesis, lipid digestion, plant secondary metabolite (PSM) degradation, and carbohydrate digestion, while the order from the genomic data is amino acid biosynthesis, vitamin biosynthesis, lipid digestion, energy metabolism, protein digestion, PSM degradation, and carbohydrate digestion. The PCA results showed that the gut bacteria form functional groups from the point of view of either the basic role or super role, and the MFA results showed that there are functional variations among gut bacteria. In addition, the variations between the proteomic and genomic data, analyzed with the HMFA method from the point of view of either the bacterial community or individual bacterial species, are presented.

CONCLUSION

The most dominant role of gut bacteria is essential nutrient provisioning, followed by digestion and detoxification. The weevil plays a pioneering role in diet digestion and mainly digests macromolecules into smaller molecules which are then mainly digested by gut bacteria.

Function is what counts: how microbial community complexity affects species, proteome and pathway coverage in metaproteomics

Introduction: Metaproteomics is an established method to obtain a comprehensive taxonomic and functional view of microbial communities. After more than a decade, we are now able to describe the promise, reality, and perspectives of metaproteomics and provide useful information about the choice of method, applications, and potential improvement strategies.Areas covered: In this article, we will discuss current challenges of species and proteome coverage, and also highlight functional aspects of metaproteomics analysis of microbial communities with different levels of complexity. To do this, we re-analyzed data from microbial communities with low to high complexity (8, 72, 200 and >300 species). High species diversity leads to a reduced number of protein group identifications in a complex community, and thus the number of species resolved is underestimated. Ultimately, low abundance species remain undiscovered in complex communities. However, we observed that the main functional categories were better represented within complex microbiomes when compared to species coverage.Expert opinion: Our findings showed that even with low species coverage, metaproteomics has the potential to reveal habitat-specific functional features. Finally, we exploit this information to highlight future research avenues that are urgently needed to enhance our understanding of taxonomic composition and functions of complex microbiomes.

Differential Lysis Approach Enables Selective Extraction of Taxon-Specific Proteins for Gut Metaproteomics

Changes in microbiome composition and function have been linked to human health and diseases. Metaproteomics provides invaluable functional information on the state of a microbiome. However, lower-abundance bacteria in complex microbiomes are difficult to observe by metaproteomics. In this study, stepwise differential lysis protocols were developed for human stool microbiomes to separate different microbial species and to increase the depth of metaproteomic measurements. We achieved differential lysis of Gram-positive (G⁺) and Gram-negative (G^-) bacteria, selective enrichment of specific bacteria, and functional enrichment by our stepwise differential lysis protocols. Therefore, differential lysis can serve as a fractionation method to reduce sample complexity and selectively extract proteins from specific taxa for deep metaproteomic studies.

Systems biology perspective for studying the gut microbiota in human physiology and liver diseases

The advancement in high-throughput sequencing technologies and systems biology approaches have revolutionized our understanding of biological systems and opened a new path to investigate unacknowledged biological phenomena. In parallel, the field of human microbiome research has greatly evolved and the relative contribution of the gut microbiome to health and disease have been systematically explored. This review provides an overview of the network-based and translational systems biology-based studies focusing on the function and composition of gut microbiota. We also discussed the association between the gut microbiome and the overall human physiology, as well as hepatic diseases and other metabolic disorders.

Microcins in Enterobacteriaceae: Peptide Antimicrobials in the Eco-Active Intestinal Chemosphere

Microcins are low-molecular-weight, ribosomally produced, highly stable, bacterial-inhibitory molecules involved in competitive, and amensalistic interactions between Enterobacteriaceae in the intestine. These interactions take place in a highly complex chemical landscape, the intestinal eco-active chemosphere, composed of chemical substances that positively or negatively influence bacterial growth, including those originated from nutrient uptake, and those produced by the action of the human or animal host and the intestinal microbiome. The contribution of bacteria results from their effect on the host generated molecules, on food and digested food, and organic substances from microbial origin, including from bacterial degradation. Here, we comprehensively review the main chemical substances present in the human intestinal chemosphere, particularly of those having inhibitory effects on microorganisms. With this background, and focusing on Enterobacteriaceae, the most relevant human pathogens from the intestinal microbiota, the microcin’s history and classification, mechanisms of action, and mechanisms involved in microcin’s immunity (in microcin producers) and resistance (non-producers) are reviewed. Products from the chemosphere likely modulate the ecological effects of microcin activity. Several cross-resistance mechanisms are shared by microcins, colicins, bacteriophages, and some conventional antibiotics, which are expected to produce cross-effects. Double-microcin-producing strains (such as microcins MccM and MccH47) have been successfully used for decades in the control of pathogenic gut organisms. Microcins are associated with successful gut colonization, facilitating translocation and invasion, leading to bacteremia, and urinary tract infections. In fact, Escherichia coli strains from the more invasive phylogroups (e.g., B2) are frequently microcinogenic. A publicly accessible APD3 database http://aps.unmc.edu/AP/ shows particular genes encoding microcins in 34.1% of E. coli strains (mostly MccV, MccM, MccH47, and MccI47), and much less in Shigella and Salmonella (<2%). Some 4.65% of Klebsiella pneumoniae are microcinogenic (mostly with MccE492), and even less in Enterobacter or Citrobacter (mostly MccS). The high frequency and variety of microcins in some Enterobacteriaceae indicate key ecological functions, a notion supported by their dominance in the intestinal microbiota of biosynthetic gene clusters involved in the synthesis of post-translationally modified peptide microcins.

A glycal-based photoaffinity probe that enriches sialic acid binding proteins

To identify sialic acid binding proteins from complex proteomes, three photocrosslinking affinity-based probes were constructed using Neu5Ac (5 and 6) and Neu5Ac2en (7) scaffolds. Kinetic inhibition assays and Western blotting revealed the Neu5Ac2en-based 7 to be an effective probe for the labeling of a purified gut microbial sialidase (BDI_2946) and a purified human sialic acid binding protein (hCD33). Additionally, LC-MS/MS affinity-based protein profiling verified the ability of 7 to enrich a low-abundance sialic acid binding protein (complement factor H) from human serum thus validating the utility of this probe in a complex context.

A Robust and Universal Metaproteomics Workflow for Research Studies and Routine Diagnostics Within 24 h Using Phenol Extraction, FASP Digest, and the MetaProteomeAnalyzer

The investigation of microbial proteins by mass spectrometry (metaproteomics) is a key technology for simultaneously assessing the taxonomic composition and the functionality of microbial communities in medical, environmental, and biotechnological applications. We present an improved metaproteomics workflow using an updated sample preparation and a new version of the MetaProteomeAnalyzer software for data analysis. High resolution by multidimensional separation (GeLC, MudPIT) was sacrificed to aim at fast analysis of a broad range of different samples in less than 24 h. The improved workflow generated at least two times as many protein identifications than our previous workflow, and a drastic increase of taxonomic and functional annotations. Improvements of all aspects of the workflow, particularly the speed, are first steps toward potential routine clinical diagnostics (i.e., fecal samples) and analysis of technical and environmental samples. The MetaProteomeAnalyzer is provided to the scientific community as a central remote server solution at www.mpa.ovgu.de.

Metaproteomic investigation to assess gut microbiota shaping in newborn mice: A combined taxonomic, functional and quantitative approach

Breastfeeding is nowadays known to be one of the most critical factors contributing to the development of an efficient immune system. In the last decade, a consistent number of pieces of evidence demonstrated the relationship between a healthy organism and its gut microbiota. However, this link is still not fully understood and requires further investigation. We recently adopted a murine model to describe the impact of either maternal milk or parental genetic background, on the composition of the gut microbial population in the first weeks of life. A metaproteomic approach to such complex environments is a big challenge that requires a strong effort in both data production and analysis, including the set-up of dedicated multitasking bioinformatics pipelines. Herein we present an LC-MS/MS based investigation to monitor mouse gut microbiota in the early life, aiming at characterizing its functions and metabolic activities together with a taxonomic description in terms of operational taxonomic units. We provided a quantitative evaluation of bacterial metaproteins, taking into account differential expression results in relation to the functional and taxonomic classification, particularly with proteins from orthologues groups. This allowed the reduction of the bias arising from the presence of a high number of shared peptides, and proteins, among different bacterial species. We also focused on host mucosal proteome and its modulation, according to different microbiota composition. SIGNIFICANCE: This paper would represent a reference work for investigations on gut microbiota in early life, from both a microbiological and a functional proteomic point of view. We focused on the shaping of the mouse gut microbiota in dependence on the feeding modality, defining a reliable taxonomic description, highlighting some functional characteristics of the microbial community, and performing a first quantitative evaluation by data independent analysis in metaproteomics.

Metaproteomic and 16S rRNA Gene Sequencing Analysis of the Infant Fecal Microbiome

A metaproteomic analysis was conducted on the fecal microbiome of eight infants to characterize global protein and pathway expression. Although mass spectrometry-based proteomics is now a routine tool, analysis of the microbiome presents specific technical challenges, including the complexity and dynamic range of member taxa, the need for well-annotated metagenomic databases, and high inter-protein sequence redundancy and similarity. In this study, an approach was developed for assessment of biological phenotype and metabolic status, as a functional complement to DNA sequence analysis. Fecal samples were prepared and analysed by tandem mass spectrometry and a homology-based meta-clustering strategy was used to combine peptides from multiple species into representative proteins. In total, 15,250 unique peptides were sequenced and assigned to 2154 metaclusters, which were then assigned to pathways and functional groups. Differences were noted in several pathways, consistent with the dominant genera observed in different subjects. Although this study was not powered to draw conclusions from the comparisons, the results obtained demonstrate the applicability of this approach and provide the methods needed for performing semi-quantitative comparisons of human fecal microbiome composition, physiology and metabolism, as well as a more detailed assessment of microbial composition in comparison to 16S rRNA gene sequencing.

Identification and function of extracellular protein in wastewater treatment using proteomic approaches: A minireview

Microbial extracellular proteins serve as important functions in wastewater treatment process. Analysis of their compositions and properties is crucial to probe their specific functions. However, conventional analytical techniques cannot obtain interest protein information from complex proteins. Recently, the extracellular proteomics method has been applied to resolve the composition of extracellular proteins. In order to better understand the roles of extracellular protein in wastewater treatment process, this review provides the information on the proteomics methods and their application in investigating extracellular proteins involved in microbial attachment/aggregation, biodegradation of pollutants, and response to environmental stresses. Future work needs to exploit the full capability of the proteome.

More Is Not Always Better: Evaluation of 1D and 2D-LC-MS/MS Methods for Metaproteomics

Metaproteomics, the study of protein expression in microbial communities, is a versatile tool for environmental microbiology. Achieving sufficiently high metaproteome coverage to obtain a comprehensive picture of the activities and interactions in microbial communities is one of the current challenges in metaproteomics. An essential step to maximize the number of identified proteins is peptide separation via liquid chromatography (LC) prior to mass spectrometry (MS). Thorough optimization and comparison of LC methods for metaproteomics are, however, currently lacking. Here, we present an extensive development and test of different 1D and 2D-LC approaches for metaproteomic peptide separations. We used fully characterized mock community samples to evaluate metaproteomic approaches with very long analytical columns (50 and 75 cm) and long gradients (up to 12 h). We assessed a total of over 20 different 1D and 2D-LC approaches in terms of number of protein groups and unique peptides identified, peptide spectrum matches (PSMs) generated, the ability to detect proteins of low-abundance species, the effect of technical replicate runs on protein identifications and method reproducibility. We show here that, while 1D-LC approaches are faster and easier to set up and lead to more identifications per minute of runtime, 2D-LC approaches allow for a higher overall number of identifications with up to >10,000 protein groups identified. We also compared the 1D and 2D-LC approaches to a standard GeLC workflow, in which proteins are pre-fractionated via gel electrophoresis. This method yielded results comparable to the 2D-LC approaches, however with the drawback of a much increased sample preparation time. Based on our results, we provide recommendations on how to choose the best LC approach for metaproteomics experiments, depending on the study aims.

Metaproteomics reveals persistent and phylum-redundant metabolic functional stability in adult human gut microbiomes of Crohn's remission patients despite temporal variations in microbial taxa, genomes, and proteomes

BACKGROUND

The gut microbiome plays a fundamental role in the human host's overall health by contributing key biological functions such as expanded metabolism and pathogen defense/immune control. In a healthy individual, the gut microbiome co-exists within the human host in a symbiotic, non-inflammatory relationship that enables mutual benefits, such as microbial degradation of indigestible food products into small molecules that the host can utilize, and enhanced pathogen defense. In abnormal conditions, such as Crohn's disease, this favorable metabolic relationship breaks down and a variety of undesirable activities result, including chronic inflammation and other health-related issues. It has been difficult, however, to elucidate the overall functional characteristics of this relationship because the microbiota can vary substantially in composition for healthy humans and possibly even more in individuals with gut disease conditions such as Crohn's disease. Overall, this suggests that microbial membership composition may not be the best way to characterize a phenotype. Alternatively, it seems to be more informative to examine and characterize the functional composition of a gut microbiome. Towards that end, this study examines 25 metaproteomes measured in several Crohn's disease patients' post-resection surgery across the course of 1 year, in order to examine persistence of microbial taxa, genes, proteins, and metabolic functional distributions across time in individuals whose microbiome might be more variable due to the gut disease condition.

RESULTS

The measured metaproteomes were highly personalized, with all the temporally-related metaproteomes clustering most closely by individual. In general, the metaproteomes were remarkably distinct between individuals and to a lesser extent within individuals. This prompted a need to characterize the metaproteome at a higher functional level, which was achieved by annotating identified protein groups with KEGG orthologous groups to infer metabolic modules. At this level, similar and redundant metabolic functions across multiple phyla were observed across time and between individuals. Tracking through these various metabolic modules revealed a clear path from carbohydrate, lipid, and amino acid degradation to central metabolism and finally the production of fermentation products.

CONCLUSIONS

The human gut metaproteome can vary quite substantially across time and individuals. However, despite substantial intra-individual variation in the metaproteomes, there is a clear persistence of conserved metabolic functions across time and individuals. Additionally, the persistence of these core functions is redundant across multiple phyla but is not always observable in the same sample. Finally, the gut microbiome's metabolism is not driven by a set of discrete linear pathways but a web of interconnected reactions facilitated by a network of enzymes that connect multiple molecules across multiple pathways.

Unipept 4.0: Functional Analysis of Metaproteome Data

Unipept ( https://unipept.ugent.be ) is a web application for metaproteome data analysis, with an initial focus on tryptic-peptide-based biodiversity analysis of MS/MS samples. Because the true potential of metaproteomics lies in gaining insight into the expressed functions of complex environmental samples, the 4.0 release of Unipept introduces complementary functional analysis based on GO terms and EC numbers. Integration of this new functional analysis with the existing biodiversity analysis is an important asset of the extended pipeline. As a proof of concept, a human faecal metaproteome data set from 15 healthy subjects was reanalyzed with Unipept 4.0, yielding fast, detailed, and straightforward characterization of taxon-specific catalytic functions that is shown to be consistent with previous results from a BLAST-based functional analysis of the same data.

Recent Advancements in Intestinal Microbiota Analyses: A Review for Non-Microbiologists

Microbial constituents naturally inhabiting the gastrointestinal tract may influence the homeostasis of the gut environment. The presence or overabundance of some bacterial taxa has been reported to be associated with complex diseases, and the metabolites of certain bacteria may contribute to diverse disorders by influencing signaling pathways. Therefore, the study of gut microbial population has emerged as a crucial field and a new potential area of clinical significance. Advances in the methods of microbiota analysis have shed light upon the details including species diversity, microfloral activities as well as the entire gut microbiota. Nevertheless, comprehensive reviews on this subject are still limited. For elucidating the appropriate selection strategy of the methods to address a particular research question, we comprehensively reviewed the continuously improving technologies, classical to newly developed, and dissected their relative advantages and drawbacks. In addition, aiming at the rapidly advancing next-generation sequencing, we enumerated the improvements in mainstream platforms and made the horizontal and vertical comparison among them. Additionally, we demonstrated the four main -omics methods, which may provide further mechanistic insights into the role of microbiota, to propel phylotyping analysis to functional analysis.

Sipros Ensemble improves database searching and filtering for complex metaproteomics

Motivation

Complex microbial communities can be characterized by metagenomics and metaproteomics. However, metagenome assemblies often generate enormous, and yet incomplete, protein databases, which undermines the identification of peptides and proteins in metaproteomics. This challenge calls for increased discrimination of true identifications from false identifications by database searching and filtering algorithms in metaproteomics.

Results

Sipros Ensemble was developed here for metaproteomics using an ensemble approach. Three diverse scoring functions from MyriMatch, Comet and the original Sipros were incorporated within a single database searching engine. Supervised classification with logistic regression was used to filter database searching results. Benchmarking with soil and marine microbial communities demonstrated a higher number of peptide and protein identifications by Sipros Ensemble than MyriMatch/Percolator, Comet/Percolator, MS-GF+/Percolator, Comet & MyriMatch/iProphet and Comet & MyriMatch & MS-GF+/iProphet. Sipros Ensemble was computationally efficient and scalable on supercomputers.

Availability and implementation

Freely available under the GNU GPL license at http://sipros.omicsbio.org.

Supplementary information

Supplementary data are available at Bioinformatics online.

Association Between Gut Microbiota and CD4 Recovery in HIV-1 Infected Patients

Composition of the gut microbiota has been linked with human immunedeficiency virus (HIV)-infected patients on antiretroviral therapy (ART). Evidence suggests that ART-treated patients with poor CD4⁺ T-cell recovery have higher levels of microbial translocation and immune activation. However, the association of the gut microbiota and immune recovery remains unclear. We performed a cross-sectional study on 30 healthy controls (HC) and 61 HIV-infected individuals, including 15 immunological ART responders (IRs), 20 immunological ART non-responders (INRs) and 26 untreated individuals (VU). IR and INR groups were classified by CD4⁺ T-cell counts of ≥350 cells/mm³ and <350 cells/mm³ after 2 years of ART, respectively. Each subject’s gut microbiota composition was analyzed by metagenomics sequencing. Levels of CD4⁺ T cells, CD8⁺HLA-DR⁺ T cells and CD8⁺CD38⁺ T cells were measured by flow cytometry. We identified more Prevotella and fewer Bacteroides in HIV-infected individuals than in HC. Patients in INR group were enriched with Faecalibacterium prausnitzii, unclassified Subdoligranulum sp. and Coprococcus comes when compared with those in IR group. F. prausnitzii and unclassified Subdoligranulum sp. were overrepresented in individuals in VU group with CD4⁺ T-cell counts <350 cells/mm³. Moreover, we found that the relative abundance of unclassified Subdoligranulum sp. and C. comes were positively correlated with CD8⁺HLA-DR⁺ T-cell count and CD8⁺HLA-DR⁺/CD8⁺ percentage. Our study has shown that gut microbiota changes were associated with CD4⁺ T-cell counts and immune activation in HIV-infected subjects. Interventions to reverse gut dysbiosis and inhibit immune activation could be a new strategy for improving immune reconstitution of HIV-1-infected individuals.

Characterization of microbial mixtures by mass spectrometry

MS applications in microbiology have increased significantly in the past 10 years, due in part to the proliferation of regulator-approved commercial MALDI MS platforms for rapid identification of clinical infections. In parallel, with the expansion of MS technologies in the "omics" fields, novel MS-based research efforts to characterize organismal as well as environmental microbiomes have emerged. Successful characterization of microorganisms found in complex mixtures of other organisms remains a major challenge for researchers and clinicians alike. Here, we review recent MS advances toward addressing that challenge. These include sample preparation methods and protocols, and established, for example, MALDI, as well as newer, for example, atmospheric pressure ionization (API) techniques. MALDI mass spectra of intact cells contain predominantly information on the highly expressed house-keeping proteins used as biomarkers. The API methods are applicable for small biomolecule analysis, for example, phospholipids and lipopeptides, and facilitate species differentiation. MS hardware and techniques, for example, tandem MS, including diverse ion source/mass analyzer combinations are discussed. Relevant examples for microbial mixture characterization utilizing these combinations are provided. Chemometrics and bioinformatics methods and algorithms, including those applied to large scale MS data acquisition in microbial metaproteomics and MS imaging of biofilms, are highlighted. Select MS applications for polymicrobial culture analysis in environmental and clinical microbiology are reviewed as well.

Hospitalized Premature Infants Are Colonized by Related Bacterial Strains with Distinct Proteomic Profiles

During the first weeks of life, microbial colonization of the gut impacts human immune system maturation and other developmental processes. In premature infants, aberrant colonization has been implicated in the onset of necrotizing enterocolitis (NEC), a life-threatening intestinal disease. To study the premature infant gut colonization process, genome-resolved metagenomics was conducted on 343 fecal samples collected during the first 3 months of life from 35 premature infants housed in a neonatal intensive care unit, 14 of whom developed NEC, and metaproteomic measurements were made on 87 samples. Microbial community composition and proteomic profiles remained relatively stable on the time scale of a week, but the proteome was more variable. Although genetically similar organisms colonized many infants, most infants were colonized by distinct strains with metabolic profiles that could be distinguished using metaproteomics. Microbiome composition correlated with infant, antibiotics administration, and NEC diagnosis. Communities were found to cluster into seven primary types, and community type switched within infants, sometimes multiple times. Interestingly, some communities sampled from the same infant at subsequent time points clustered with those of other infants. In some cases, switches preceded onset of NEC; however, no species or community type could account for NEC across the majority of infants. In addition to a correlation of protein abundances with organism replication rates, we found that organism proteomes correlated with overall community composition. Thus, this genome-resolved proteomics study demonstrated that the contributions of individual organisms to microbiome development depend on microbial community context.IMPORTANCE Humans are colonized by microbes at birth, a process that is important to health and development. However, much remains to be known about the fine-scale microbial dynamics that occur during the colonization period. We conducted a genome-resolved study of microbial community composition, replication rates, and proteomes during the first 3 months of life of both healthy and sick premature infants. Infants were found to be colonized by similar microbes, but each underwent a distinct colonization trajectory. Interestingly, related microbes colonizing different infants were found to have distinct proteomes, indicating that microbiome function is not only driven by which organisms are present, but also largely depends on microbial responses to the unique set of physiological conditions in the infant gut.