• Candida
• FMT introduction
• intestinal fungi
• ulcerative colitis

• Bowel preparation
• Colonoscopy
• Inflammatory bowel disease
• Microbiota
• Probiotics

• Humans
• Dysbiosis/microbiology
• Dysbiosis/therapy
• Dysbiosis/prevention & control
• Dysbiosis/etiology
• Gastrointestinal Microbiome/drug effects
• Colonoscopy/adverse effects
• Colonoscopy/methods
• Probiotics/therapeutic use
• Probiotics/administration & dosage
• Cathartics/adverse effects
• Cathartics/administration & dosage
• Inflammatory Bowel Diseases/microbiology

• MGWAS
• host genome
• intestinal microbiota
• metabolome
• multi-omics integrated analysis

• Mus musculus
• dietary intervention
• gut microbiome
• metagenomics
• metaproteomics
• mice

• Animals
• Dietary Proteins/metabolism
• Dietary Proteins/administration & dosage
• Mice
• Gastrointestinal Microbiome/drug effects
• Metagenomics
• Bacteria/classification
• Bacteria/genetics
• Mice, Inbred C57BL
• Proteomics
• Diet
• Male
• Amino Acids/metabolism

• R35 GM138362 NIGMS NIH HHS
• 7002782 USDA National Institute of Food and Agriculture
• P30 DK034987 NIDDK NIH HHS
• P30 DK034987 NIH HHS
• T32 DK007737 NIDDK NIH HHS
• 7002782 USDA National Institute of Food and Agriculture, Hatch
• National Institutes of Health

• human gut microbiota
• mass spectrometry
• metaproteomics
• standardization

• The Italian Ministry of Health provided "Current Research funds" to L.P. to support this work

• Crohn’s disease
• IBD
• Mycobacterium paratuberculosis
• antibiotics
• bacteria
• microbiome
• mycobacteria
• surgery

• Crohn’s disease
• Inflammatory bowel disease
• immunosuppressive therapy
• metabolome
• microbiome
• treatment response
• ulcerative colitis

• Humans
• Gastrointestinal Microbiome
• Inflammatory Bowel Diseases/microbiology
• Feces/microbiology
• Fecal Microbiota Transplantation
• Biomarkers/analysis

• 16S rRNA amplicon sequencing
• Aerobic granular sludge
• Metaproteomics
• Wastewater treatment
• metagenomics

• Sewage/chemistry
• RNA, Ribosomal, 16S/genetics
• Bioreactors
• Microbiota
• Metagenome
• Metagenomics/methods

• Flammulina velutipes
• dietary fiber
• flavomycin
• laying hens
• microbiota

• 16S rRNA gene sequencing
• Fusobacterium nucleatum
• Leptotrichia
• Porphyromonas gingivalis
• Prevotella
• Streptococcus mutans
• oral cancer
• oral disease
• oral microbiome

• P30 CA168524 NCI NIH HHS

• endosphere
• metaproteomics
• microbiome
• microbiota
• phytobiome
• plant-microbe interactions
• rhizoplane

• Arabidopsis
• Microbiota
• Chromatography, Liquid
• Proteome
• Mass Spectrometry
• Plants

The complex gut bacterial communities may facilitate the function, distribution, and diversity of birds. For migratory birds, long-distance traveling poses selection pressures on their gut microbiota, ultimately affecting the birds’ health, fitness, ecology, and evolution. However, our understanding of mechanisms that underlie the assembly of the gut microbiome of migratory birds is limited. In this study, the gut microbiota of winter migratory birds in the Poyang Lake wetland was characterized using MiSeq sequencing of 16S rRNA genes. The sampled bird included herbivorous, carnivorous, and omnivorous birds from a total of 17 species of 8 families. Our results showed that the gut microbiota of migratory birds was dominated by four major bacterial phyla: Firmicutes (47.8%), Proteobacteria (18.2%), Fusobacteria (12.6%), and Bacteroidetes (9.1%). Dietary specialization outweighed the phylogeny of birds as an important factor governing the gut microbiome, mainly through regulating the deterministic processes of homogeneous selection and stochastic processes of homogeneous dispersal balance. Moreover, the omnivorous had more bacterial diversity than the herbivorous and carnivorous. Microbial networks for the gut microbiome of the herbivorous and carnivorous were less integrated, i.e., had lower average node degree and greater decreased network stability upon node attack removal than those of the omnivorous birds. Our findings advance the understanding of host-microbiota interactions and the evolution of migratory bird dietary flexibility and diversification.

• microbiome
• symbiosis

• T32 DK007737 NIDDK NIH HHS

(-)-Epicatechin (EC) is one of the most popular polyphenols present in various food products in daily life. Upon intake, it is intensively metabolized by microbiota in the large intestine. In the present study, intra- and inter-individual variations in this gut microbial conversion of EC and the concomitant formation of its major metabolites, including 5-(3′,4′-dihydroxy phenyl)-γ-valerolactone (3,4-diHPV), were identified and quantified via liquid chromatography triple quadrupole mass spectrometry (LC-TQ-MS) in anaerobic fecal incubations. In addition, the bioactivity of EC and 3,4-diHPV in activating Nrf2-mediated gene expression was tested quantifying their effects in the U2OS Nrf2 CALUX assay (a reporter gene assay that is used to test the potency of chemicals in activation of Nrf2 signaling), and on the expression levels of Nrf2-related proteins in Hepa1c1c7 and Caco-2 cells via nanoLC-MSMS. A quantitative real-time polymerase chain reaction (RT-qPCR) was carried out to confirm selected Nrf2-regulated gene expressions at the mRNA level. Results obtained show that both intra- and inter-individual differences exist in human gut microbial EC degradation and 3,4-diHPV formation, with inter-individual differences being more distinct than intra-individual differences. The metabolite, 3,4-diHPV, showed higher potency in the U2OS Nrf2 CALUX assay than EC itself. Among the obviously altered Nrf2-related proteins, 14 and 10 Nrf2-associated proteins were upregulated to a higher extent upon 3,4-diHPV treatment than in the EC treated group for Hepa1c1c7 and Caco-2 cells, respectively. While only three and four of these Nrf2-associated proteins were induced at a higher level upon EC than upon 3,4-diHPV treatment for Hepa1c1c7 and Caco-2 cells, respectively. RT-qPCR results showed that indeed Nrf2-mediated genes (e.g., Nqo1 and Ugt1a) were only induced significantly in 3,4-diHPV treated and not in EC treated Hepa1c1c7 cells. Taken together, the results suggest that the major colonic EC metabolite, 3,4-diHPV, was more capable of inducing Nrf2-mediated gene expression than its parent compound EC. This implies that the evident inter- and intra-individual differences in the microbial conversion of EC to this major metabolite 3,4-diHPV may affect the overall health-promoting effects of EC consumption related to the Nrf2 pathway activation.

Host-microbiome interactions and the microbial community have broad impact in human health and diseases. Most microbiome based studies are performed at the genome level based on next-generation sequencing techniques, but metaproteomics is emerging as a powerful technique to study microbiome functional activity by characterizing the complex and dynamic composition of microbial proteins. We conducted a large-scale survey of human gut microbiome metaproteomic data to identify generalist species that are ubiquitously expressed across all samples and specialists that are highly expressed in a small subset of samples associated with a certain phenotype. We were able to utilize the metaproteomic mass spectrometry data to reveal the protein landscapes of these species, which enables the characterization of the expression levels of proteins of different functions and underlying regulatory mechanisms, such as operons. Finally, we were able to recover a large number of open reading frames (ORFs) with spectral support, which were missed by de novo protein-coding gene predictors. We showed that a majority of the rescued ORFs overlapped with de novo predicted protein-coding genes, but on opposite strands or in different frames. Together, these demonstrate applications of metaproteomics for the characterization of important gut bacterial species.

Many reference genomes for studying human gut microbiome are available, but knowledge about how microbial organisms work is limited. Identification of proteins at individual species or community level provides direct insight into the functionality of microbial organisms. By analyzing more than a thousand metaproteomics datasets, we examined protein landscapes of more than two thousands of microbial species that may be important to human health and diseases. This work demonstrated new applications of metaproteomic datasets for studying individual genomes. We made the analysis results available through a website (called GutBac), which we believe will become a resource for studying microbial species important for human health and diseases.

• Bacteria/genetics
• Gastrointestinal Microbiome/genetics
• Humans
• Microbiota/genetics
• Proteome/analysis
• Proteomics/methods

• R01 AI108888 NIAID NIH HHS
• R01 AI143254 NIAID NIH HHS
• National Institute of Allergy and Infectious Diseases
• National Science Foundation

• k-means
• individual variability
• iterative clustering
• longitudinal sampling
• microbiota stability

• Metaproteomics
• Mus musculus
• mass spectrometry
• microbiome
• proteogenomics

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.

•

Identified 176 significantly altered protein groups between healthy and UC patients.

• Irritable bowel syndrome
• fecal metabolome
• gut metabolome
• gut microbiota
• gut-brain
• host-microbiome interaction
• microbiome
• serotonin
• stress

• Bioinformatics
• Computational biology
• Mass spectrometry
• Metaproteomics
• Microbiome
• Proteomics
• Quantification
• Software
• Statistics

• Computational Biology/methods
• Gastrointestinal Microbiome
• Microbiota
• Proteomics/methods
• Software

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.

• R35 GM138362 NIGMS NIH HHS
• T32 DK007737 NIDDK NIH HHS

• LC-MS/MS
• gut microbes
• intestinal microbiome
• metaproteomics
• microbiota
• sample preservation
• storage

• Animals
• Bacteria/chemistry
• Bacteria/genetics
• Bacteria/isolation & purification
• Bacterial Proteins/chemistry
• Chromatography, Liquid
• Feces/chemistry
• Feces/microbiology
• Female
• Gastrointestinal Microbiome
• Male
• Mice
• Mice, Inbred C57BL
• Peptides/chemistry
• Preservation, Biological/methods
• Proteomics/methods
• Tandem Mass Spectrometry

• R35 GM138362 NIGMS NIH HHS
• HHS | NIH | National Institute of General Medical Sciences (NIGMS)
• Foundation for Food and Agriculture Research (FFAR)

• Early life human microbiome
• Metabolomics
• Metagenomics
• Metaproteomics
• Microbial colonisation

• gut microbiota (GM)
• human health
• interplay
• nutrition
• plant miRNAs

• Gastrointestinal Microbiome
• Gene Expression Regulation, Plant
• Humans
• MicroRNAs/genetics
• Plant Development
• Plants/genetics
• RNA, Plant/genetics

• 1D-LC-MS/MS
• environmental microbiology
• field sampling
• mass spectrometry
• microbial communities
• microbiome
• preservation methods

• B-cell epitope
• Burkholderia
• Francisella
• antigen
• immunoproteome
• peptide vaccine

• hidradenitis suppurativa
• microbiome

• comprehensive active modulation
• environmental
• metaproteomics
• microbiome
• nano 2D LC MS/MS
• proteomics

• Core/periphery network
• Inflammatory bowel disease
• Mucosal microbiome
• Species co-occurrence network
• Species diversity
• Ulcerative colitis

• circadian
• gastrointestinal tract
• gut microbiota
• gut microflora

• Energy Metabolism/genetics
• Gastrointestinal Microbiome/physiology
• Gene Expression/genetics
• Gene Expression Regulation/genetics
• Humans
• RNA, Ribosomal, 16S/genetics

• R01 DK093595 NIDDK NIH HHS
• Pennsylvania State University

• bead-based metabolic biosensors
• bioconjugate chemistry
• food science
• human gut microbiome
• infectious disease
• microbiology
• polysaccharide structure
• prebiotic discovery
• utilization

• Animals
• Biosensing Techniques/methods
• Gastrointestinal Microbiome/physiology
• Germ-Free Life
• Male
• Mice
• Mice, Inbred C57BL
• Polysaccharides/analysis
• Polysaccharides/metabolism
• Prebiotics

• F30 DK123838 NIDDK NIH HHS
• P01 DK078669 NIDDK NIH HHS
• P30 DK056341 NIDDK NIH HHS
• R01 DK070977 NIDDK NIH HHS
• National Institutes of Health
• Damon Runyon Cancer Research Foundation
• Agilent Technologies

• antibiotic therapy
• bacterial interactions
• diet
• intestinal microbiology

• Gut microbial proteolysis
• Inflammatory bowel disease
• Metaproteomics

• Adolescent
• Adult
• Child
• Escherichia coli/metabolism
• Gastrointestinal Microbiome
• Humans
• Middle Aged
• Peptide Fragments/analysis
• Peptide Fragments/chemistry
• Peptide Fragments/metabolism
• Proteolysis
• Proteomics
• Trypsin/metabolism
• Young Adult

• National Natural Science Foundation of China
• Guangdong Basic and Applied Basic Research Foundation
• Science and Technology Development Fund of Macau SAR

• Biomarkers
• Diet
• Ethnicity
• Industrialized
• Nonindustrialized

The infant gut microbiome consists of a complex and diverse microbial community. Comprehensive taxonomic and metabolic functional knowledge about microbial communities supports medical and biological applications, such as fecal diagnostics. Among the omics approaches available for the investigation of microbial communities, metaproteomics-based analysis is a very powerful approach; under this method, the activity of microbial communities is explored by investigating protein expression within a sample. Through use of metaproteomics, this study aimed to investigate the microbial community composition of the infant gut to identify different key proteins playing metabolic functional roles in the microbiome of healthy infants and infants with atopic dermatitis in a Thai population-based birth cohort. Here, 18 fecal samples were analyzed by liquid chromatography-tandem mass spectrometry to conduct taxonomic, functional, and pathway-based protein annotation. Accordingly, 49,973 annotated proteins out of 68,232 total proteins were investigated in gut microbiome samples and compared between the healthy and atopic dermatitis groups. Through differentially expressed proteins (DEPs) analysis, 130 significant DEPs were identified between the healthy and atopic dermatitis groups. Among these DEPs, eight significant proteins were uniquely expressed in the atopic dermatitis group. For instance, triosephosphate isomerase (TPI) in Bifidobacteriaceae in the genus Alloscardovia and demethylmenaquinone methyltransferase (DMM) in Bacteroides were shown to potentially play metabolic functional roles related to disease. PPI network analysis revealed seven reporter proteins showing metabolic alterations between the healthy and disease groups associated with the biosynthesis of ubiquinone and other quinones as well as the energy supply. This study serves as a scaffold for microbial community-wide metabolic functional studies of the infant gut microbiome in relation to allergic disease.

• Atopic dermatitis
• Bioinformatics
• Gut microbiome
• Infants
• Metabolic function
• Metaproteomics

• Functional database
• Gene function annotation
• Gut microbiota
• Metagenomics
• Sable (Martes zibellina)

Purpose: To analyze human and bacteria proteomic profiles in bile, exposed to a tumor vs. non-tumor microenvironment, in order to identify differences between these conditions, which may contribute to a better understanding of pancreatic carcinogenesis.

Patients and Methods: Using liquid chromatography and mass spectrometry, human and bacterial proteomic profiles of a total of 20 bile samples (7 from gallstone (GS) patients, and 13 from pancreatic head ductal adenocarcinoma (PDAC) patients) that were collected during surgery and taken directly from the gallbladder, were compared. g:Profiler and KEGG (Kyoto Encyclopedia of Genes and Genomes) Mapper Reconstruct Pathway were used as the main comparative platform focusing on over-represented biological pathways among human proteins and interaction pathways among bacterial proteins.

Results: Three bacterial infection pathways were over-represented in the human PDAC group of proteins. IL-8 is the only human protein that coincides in the three pathways and this protein is only present in the PDAC group. Quantitative and qualitative differences in bacterial proteins suggest a dysbiotic microenvironment in the PDAC group, supported by significant participation of antibiotic biosynthesis enzymes. Prokaryotes interaction signaling pathways highlight the presence of zeatin in the GS group and surfactin in the PDAC group, the former in the metabolism of terpenoids and polyketides, and the latter in both metabolisms of terpenoids, polyketides and quorum sensing. Based on our findings, we propose a bacterial-induced carcinogenesis model for the biliary tract.

Conclusion: To the best of our knowledge this is the first study with the aim of comparing human and bacterial bile proteins in a tumor vs. non-tumor microenvironment. We proposed a new carcinogenesis model for the biliary tract based on bile metaproteomic findings. Our results suggest that bacteria may be key players in biliary tract carcinogenesis, in a long-lasting dysbiotic and epithelially harmful microenvironment, in which specific bacterial species' biofilm formation is of utmost importance. Our finding should be further explored in future using in vitro and in vivo investigations.

• IL-8
• bile
• carcinogenesis model
• metaproteomic
• pancreatic cancer
• proteomic
• surfactin
• zeatin

Gut microbiota participates in diverse metabolic and homeostatic functions related to health and well-being. Its composition varies between individuals, and depends on factors related to host and microbial communities, which need to adapt to utilize various nutrients present in gut environment. We profiled fecal microbiota in 63 healthy adult individuals using metaproteomics, and focused on microbial CAZy (carbohydrate-active) enzymes involved in glycan foraging. We identified two distinct CAZy profiles, one with many Bacteroides-derived CAZy in more than one-third of subjects (n = 25), and it associated with high abundance of Bacteroides in most subjects. In a smaller subset of donors (n = 8) with dietary parameters similar to others, microbiota showed intense expression of Prevotella-derived CAZy including exo-beta-(1,4)-xylanase, xylan-1,4-beta-xylosidase, alpha-l-arabinofuranosidase and several other CAZy belonging to glycosyl hydrolase families involved in digestion of complex plant-derived polysaccharides. This associated invariably with high abundance of Prevotella in gut microbiota, while in subjects with lower abundance of Prevotella, microbiota showed no Prevotella-derived CAZy. Identification of Bacteroides- and Prevotella-derived CAZy in microbiota proteome and their association with differences in microbiota composition are in evidence of individual variation in metabolic specialization of gut microbes affecting their colonizing competence.

Metaproteomics of gut microbiomes from animal hosts lacking a reference genome is challenging. Here we describe a strategy combining high-resolution metaproteomics and host RNA sequencing (RNA-seq) with generalist database searching to survey the digestive tract of Gammarus fossarum, a small crustacean used as a sentinel species in ecotoxicology. This approach provides a deep insight into the full range of biomasses and metabolic activities of the holobiont components, and differentiates between the intestine and hepatopancreatic caecum.

• Data analysis
• Metagenomics
• Microbiome
• Visualization

• Crohn’s disease
• amino acids
• autologous
• biomarkers
• fecal microbiota transplantation
• remission

• Chronic gastritis
• Colorectal cancer
• Dysbiosis
• Gastric cancer
• Inflammatory bowel disease
• Irritable bowel syndrome
• Microbiome
• Microbiota

• Animals
• Colorectal Neoplasms/microbiology
• Colorectal Neoplasms/pathology
• Dysbiosis/microbiology
• Dysbiosis/pathology
• Gastrointestinal Microbiome
• Helicobacter pylori/pathogenicity
• Humans
• Inflammatory Bowel Diseases/microbiology
• Inflammatory Bowel Diseases/pathology
• Irritable Bowel Syndrome/microbiology
• Irritable Bowel Syndrome/pathology

• mass spectrometry
• metabolomics
• metaproteomics
• microbiome
• multi-omics

• Crohn's Disease
• Fecal samples
• Gastrointestinal tract
• Inflammatory Bowel Disease
• Metaproteomics
• Non-invasive diagnosis
• Ulcerative Colitis

• Adult
• Aged
• Aged, 80 and over
• Biomarkers/metabolism
• Colitis, Ulcerative/metabolism
• Colitis, Ulcerative/microbiology
• Crohn Disease/metabolism
• Crohn Disease/microbiology
• Feces/microbiology
• Female
• Gastrointestinal Microbiome
• Humans
• Male
• Middle Aged