Metaproteomics of our microbiome - developing insight in function and activity in man and model systems

Data-independent acquisition in metaproteomics

INTRODUCTION

Metaproteomics offers insights into the function of complex microbial communities, while it is also capable of revealing microbe-microbe and host-microbe interactions. Data-independent acquisition (DIA) mass spectrometry is an emerging technology, which holds great potential to achieve deep and accurate metaproteomics with higher reproducibility yet still facing a series of challenges due to the inherent complexity of metaproteomics and DIA data.

AREAS COVERED

This review offers an overview of the DIA metaproteomics approaches, covering aspects such as database construction, search strategy, and data analysis tools. Several cases of current DIA metaproteomics studies are presented to illustrate the procedures. Important ongoing challenges are also highlighted. Future perspectives of DIA methods for metaproteomics analysis are further discussed. Cited references are searched through and collected from Google Scholar and PubMed.

EXPERT OPINION

Considering the inherent complexity of DIA metaproteomics data, data analysis strategies specifically designed for interpretation are imperative. From this point of view, we anticipate that deep learning methods and de novo sequencing methods will become more prevalent in the future, potentially improving protein coverage in metaproteomics. Moreover, the advancement of metaproteomics also depends on the development of sample preparation methods, data analysis strategies, etc. These factors are key to unlocking the full potential of metaproteomics.

Multi-omics analysis of fecal samples in colorectal cancer Egyptians patients: a pilot study

BACKGROUND

Colorectal cancer (CRC) is a public health concern and the second most common disease worldwide. This is due to genetic coding and is influenced by environmental aspects, in which the gut microbiota plays a significant role. The purpose of this study was to compare the microbiota makeup of CRC patients with that of healthy control and to identify upregulated and downregulated proteins and metabolites in CRC patients. Using a next-generation sequencing approach, fecal samples of five females (4 CRC patients and one healthy control) were analyzed by BGI DNBSEQ-T7, Hong Kong, China. Furthermore, proteomics and metabolomics analysis were performed using LC-MS/MS technique.

RESULTS

Dysbiosis of gut microbiota has been observed in patients with CRC, with an increase in microbiota diversity at all taxonomic levels relative to healthy control. Where, at the functional level the bacterial species participate in many different pathways among them de novo nucleotide synthesis and amino acids pathways were aberrantly upregulated in CRC patients. Proteomics and metabolomics profiles of CRC patients showed different proteins and metabolites, a total of 360 and 158 proteins and metabolites, respectively were highly expressed compared to healthy control with fold change ≥ 1.2. Among the highly expressed proteins were transketolase, sushi domain-containing protein, sulfide quinone oxidoreductase protein, AAA family ATPase protein, carbonic anhydrase, IgG Fc-binding protein, nucleoside diphosphate kinase protein, arylsulfatase, alkaline phosphatase protein, phosphoglycerate kinase, protein kinase domain-containing protein, non-specific serine/threonine protein kinase, Acyl-CoA synthetase and EF-hand domain-containing protein. Some of the differential metabolites, Taurine, Taurocholic acid, 7-ketodeoxycholic acid, Glycochenodeoxycholic acid, Glycocholic acid, and Taurochenodeoxycholic acid that belong to bile acids metabolites.

CONCLUSIONS

Some bacterial species, proteins, and metabolites could be used as diagnostic biomarkers for CRC. Our study paves an insight into using multi-omics technology to address the relationship between gut microbiota and CRC.

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.

Molecular characterization of gut microbiome in weaning pigs supplemented with multi-strain probiotics using metagenomic, culturomic, and metabolomic approaches

BACKGROUND

Probiotics have been reported to exhibit positive effects on host health, including improved intestinal barrier function, preventing pathogenic infection, and promoting nutrient digestion efficiency. These internal changes are reflected to the fecal microbiota composition and, bacterial metabolites production. In accordance, the application of probiotics has been broadened to industrial animals, including swine, which makes people to pursue better knowledge of the correlation between changes in the fecal microbiota and metabolites. Therefore, this study evaluated the effect of multi-strain probiotics (MSP) supplementation to piglets utilizing multiomics analytical approaches including metagenomics, culturomics, and metabolomics.

RESULTS

Six-week-old piglets were supplemented with MSP composed of Lactobacillus isolated from the feces of healthy piglets. To examine the effect of MSP supplement, piglets of the same age were selected and divided into two groups; one with MSP supplement (MSP group) and the other one without MSP supplement (Control group). MSP feeding altered the composition of the fecal microbiota, as demonstrated by metagenomics analysis. The abundance of commensal Lactobacillus was increased by 2.39%, while Clostridium was decreased, which revealed the similar pattern to the culturomic approach. Next, we investigated the microbial metabolite profiles, specifically SCFAs using HPLC-MS/MS and others using GC-MS, respectively. MSP supplement elevated the abundance of amino acids, including valine, isoleucine and proline as well as the concentration of acetic acid. According to the correlation analyses, these alterations were found out to be crucial in energy synthesizing metabolism, such as branched-chain amino acid (BCAA) metabolism and coenzyme A biosynthesis. Furthermore, we isolated commensal Lactobacillus strains enriched by MSP supplement, and analyzed the metabolites and evaluated the functional improvement, related to tight junction from intestinal porcine enterocyte cell line (IPEC-J2).

CONCLUSIONS

In conclusion, MSP administration to piglets altered their fecal microbiota, by enriching commensal Lactobacillus strains. This change contributed amino acid, acetic acid, and BCAA concentrations to be increased, and energy metabolism pathway was also increased at in vivo and in vitro. These changes produced by MSP supplement suggests the correlation between the various physiological energy metabolism functions induced by health-promoting Lactobacillus and the growth performance of piglets.

Exploring Bacterial Attributes That Underpin Symbiont Life in the Monogastric Gut

The large bowel of monogastric animals, such as that of humans, is home to a microbial community (microbiota) composed of a diversity of mostly bacterial species. Interrelationships between the microbiota as an entity and the host are complex and lifelong and are characteristic of a symbiosis. The relationships may be disrupted in association with disease, resulting in dysbiosis. Modifications to the microbiota to correct dysbiosis require knowledge of the fundamental mechanisms by which symbionts inhabit the gut. This review aims to summarize aspects of niche fitness of bacterial species that inhabit the monogastric gut, especially of humans, and to indicate the research path by which progress can be made in exploring bacterial attributes that underpin symbiont life in the gut.

Analysis methods for the gut microbiome in neuropsychiatric and neurodegenerative disorders

For a long time, the central nervous system was believed to be the only regulator of cognitive functions. However, accumulating evidence suggests that the composition of the microbiome is strongly associated with brain functions and diseases. Indeed, the gut microbiome is involved in neuropsychiatric diseases (e.g., depression, autism spectrum disorder, and anxiety) and neurodegenerative diseases (e.g., Parkinson’s disease and Alzheimer’s disease). In this review, we provide an overview of the link between the gut microbiome and neuropsychiatric or neurodegenerative disorders. We also introduce analytical methods used to assess the connection between the gut microbiome and the brain. The limitations of the methods used at present are also discussed. The accurate translation of the microbiome information to brain disorder could promote better understanding of neuronal diseases and aid in finding alternative and novel therapies.

Study on Microbial Community Succession and Functional Analysis during Biodegradation of Mushroom Residue

In this study, 16S rRNA high-throughput sequencing technology was used to analyze the composition and diversity of bacterial and fungal communities in mushroom residue samples at different composting stages. During the composting process, the maximum temperature in the center of the pile can reach 52.4°C, and the temperature above 50°C has been maintained for about 8 days. The results showed that Actinobacteria, Firmicutes, Proteobacteria, Bacteroidetes, and Chloroflexi were the main microorganisms in the composting process, accounting for 98.9%-99.7% of the total bacteria. Furthermore, in order to obtain the protein expressed in each stage of composting, the nonstandard quantitative method (label free) was used to analyze it quantitatively by mass spectrometry, anda total of 22815 proteins were identified. It indicated that the number of identified proteins related to cellulose decomposition and the number of differentially expressed proteins were significantly enriched, and the functional proteins related to cellulose decomposition had significant stage correspondence.

Gut Microbial Protein Expression in Response to Dietary Patterns in a Controlled Feeding Study: A Metaproteomic Approach

Although the gut microbiome has been associated with dietary patterns linked to health, microbial metabolism is not well characterized. This ancillary study was a proof of principle analysis for a novel application of metaproteomics to study microbial protein expression in a controlled dietary intervention. We measured the response of the microbiome to diet in a randomized crossover dietary intervention of a whole-grain, low glycemic load diet (WG) and a refined-grain, high glycemic load diet (RG). Total proteins in stools from 9 participants at the end of each diet period (n = 18) were analyzed by LC MS/MS and proteins were identified using the Human Microbiome Project (HMP) human gut microbiome database and UniProt human protein databases. T-tests, controlling for false discovery rate (FDR) <10%, were used to compare the Gene Ontology (GO) biological processes and bacterial enzymes between the two interventions. Using shotgun proteomics, more than 53,000 unique peptides were identified including microbial (89%) and human peptides (11%). Forty-eight bacterial enzymes were statistically different between the diets, including those implicated in SCFA production and degradation of fatty acids. Enzymes associated with degradation of human mucin were significantly enriched in the RG diet. These results illustrate that the metaproteomic approach is a valuable tool to study the microbial metabolism of diets that may influence host health.

Development of omics-based protocols for the microbiological characterization of multi-strain formulations marketed as probiotics: the case of VSL#3

The growing commercial interest in multi-strain formulations marketed as probiotics has not been accompanied by an equal increase in the evaluation of quality levels of these biotechnological products. The multi-strain product VSL#3 was used as a model to setup a microbiological characterization that could be extended to other formulations with high complexity. Shotgun metagenomics by deep Illumina sequencing was applied to DNA isolated from the commercial VSL#3 product to confirm strains identity safety and composition. Single-cell analysis was used to evaluate the cell viability, and β-galactosidase and urease activity have been used as marker to monitor the reproducibility of the production process. Similarly, these lots were characterized in detail by a metaproteomics approach for which a robust protein extraction protocol was combined with advanced mass spectrometry. The results identified over 1600 protein groups belonging to all strains present in the VSL#3 formulation. Of interest, only 3.2 % proteins showed significant differences mainly related to small variations in strain abundance. The protocols developed in this study addressed several quality criteria that are relevant for marketed multi-strain products and these represent the first efforts to define the quality of complex probiotic formulations such as VSL#3.

metaQuantome: An Integrated, Quantitative Metaproteomics Approach Reveals Connections Between Taxonomy and Protein Function in Complex Microbiomes

Microbiome research offers promising insights into the impact of microorganisms on biological systems. Metaproteomics, the study of microbial proteins at the community level, integrates genomic, transcriptomic, and proteomic data to determine the taxonomic and functional state of a microbiome. However, standard metaproteomics software is subject to several limitations, commonly supporting only spectral counts, emphasizing exploratory analysis rather than hypothesis testing and rarely offering the ability to analyze the interaction of function and taxonomy - that is, which taxa are responsible for different processes.Here we present metaQuantome, a novel, multifaceted software suite that analyzes the state of a microbiome by leveraging complex taxonomic and functional hierarchies to summarize peptide-level quantitative information, emphasizing label-free intensity-based methods. For experiments with multiple experimental conditions, metaQuantome offers differential abundance analysis, principal components analysis, and clustered heat map visualizations, as well as exploratory analysis for a single sample or experimental condition. We benchmark metaQuantome analysis against standard methods, using two previously published datasets: (1) an artificially assembled microbial community dataset (taxonomy benchmarking) and (2) a dataset with a range of recombinant human proteins spiked into an Escherichia coli background (functional benchmarking). Furthermore, we demonstrate the use of metaQuantome on a previously published human oral microbiome dataset.In both the taxonomic and functional benchmarking analyses, metaQuantome quantified taxonomic and functional terms more accurately than standard summarization-based methods. We use the oral microbiome dataset to demonstrate metaQuantome's ability to produce publication-quality figures and elucidate biological processes of the oral microbiome. metaQuantome enables advanced investigation of metaproteomic datasets, which should be broadly applicable to microbiome-related research. In the interest of accessible, flexible, and reproducible analysis, metaQuantome is open source and available on the command line and in Galaxy.

A Method for Comprehensive Proteomic Analysis of Human Faecal Samples to Investigate Gut Dysbiosis in Patients with Cystic Fibrosis

BACKGROUND

This chapter reports the evaluation of two shotgun metaproteomic workflows. The methods were developed to investigate gut dysbiosis via analysis of the faecal microbiota from patients with cystic fibrosis (CF). We aimed to set up an unbiased and effective method to extract the entire proteome, i.e. to extract sufficient bacterial proteins from the faecal samples in combination with a maximum of host proteins giving information on the disease state.

METHODS

Two protocols were compared; the first method involves an enrichment of the bacterial proteins while the second method is a more direct method to generate a whole faecal proteome extract. The different extracts were analysed using denaturing polyacrylamide gel electrophoresis followed by liquid chromatography-tandem mass spectrometry aiming a maximal coverage of the bacterial protein content in faecal samples.

RESULTS AND CONCLUSIONS

In all extracts, microbial proteins are detected, and in addition, nonbacterial proteins are detected in all samples providing information about the host status. Our study demonstrates the huge influence of the used protein extraction method on the obtained result and shows the need for a standardised and appropriate sample preparation for metaproteomic analysis. To address questions on the health status of the patients, a whole protein extract is preferred over a method to enrich the bacterial fraction. In addition, the method of the whole protein fraction is faster, which gives the possibility to analyse more biological replicates.

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.

Antibiotic Discovery: Where Have We Come from, Where Do We Go?

Given the increase in antibiotic-resistant bacteria, alongside the alarmingly low rate of newly approved antibiotics for clinical usage, we are on the verge of not having effective treatments for many common infectious diseases. Historically, antibiotic discovery has been crucial in outpacing resistance and success is closely related to systematic procedures—platforms—that have catalyzed the antibiotic golden age, namely the Waksman platform, followed by the platforms of semi-synthesis and fully synthetic antibiotics. Said platforms resulted in the major antibiotic classes: aminoglycosides, amphenicols, ansamycins, beta-lactams, lipopeptides, diaminopyrimidines, fosfomycins, imidazoles, macrolides, oxazolidinones, streptogramins, polymyxins, sulphonamides, glycopeptides, quinolones and tetracyclines. During the genomics era came the target-based platform, mostly considered a failure due to limitations in translating drugs to the clinic. Therefore, cell-based platforms were re-instituted, and are still of the utmost importance in the fight against infectious diseases. Although the antibiotic pipeline is still lackluster, especially of new classes and novel mechanisms of action, in the post-genomic era, there is an increasingly large set of information available on microbial metabolism. The translation of such knowledge into novel platforms will hopefully result in the discovery of new and better therapeutics, which can sway the war on infectious diseases back in our favor.

Metaproteomics of fecal samples of Crohn's disease and Ulcerative Colitis

Crohn's Disease (CD) and Ulcerative Colitis (UC) are chronic inflammatory bowel diseases (IBD) of the gastrointestinal tract. This study used non-invasive LC-MS/MS to find disease specific microbial and human proteins which might be used later for an easier diagnosis. Therefore, 17 healthy controls, 11 CD patients and 14 UC patients but also 13 Irritable Bowel Disease (IBS) patients, 8 Colon Adenoma (CA) patients, and 8 Gastric Carcinoma (GCA) patients were investigated. The proteins were extracted from the fecal samples with liquid phenol in a ball mill. Subsequently, the proteins were digested tryptically to peptides and analyzed by an Orbitrap LC-MS/MS. For protein identification and interpretation of taxonomic and functional results, the MetaProteomeAnalyzer software was used. Cluster analysis and non-parametric test (analysis of similarities) separated healthy controls from patients with CD and UC as well as from patients with GCA. Among others, CD and UC correlated with an increase of neutrophil extracellular traps and immune globulins G (IgG). In addition, a decrease of human IgA and the transcriptional regulatory protein RprY from Bacillus fragilis was found for CD and UC. A specific marker in feces for CD was an increased amount of the human enzyme sucrose-isomaltase. SIGNIFICANCE: Crohn's Disease and Ulcerative Colitis are chronic inflammatory diseases of the gastrointestinal tract, whose diagnosis required comprehensive medical examinations including colonoscopy. The impact of the microbial communities in the gut on the pathogenesis of these diseases is poorly understood. Therefore, this study investigated the impact of gut microbiome on these diseases by a metaproteome approach, revealing several disease specific marker proteins. Overall, this indicated that fecal metaproteomics has the potential to be useful as non-invasive tool for a better and easier diagnosis of both diseases.

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.

Evaluating Metagenomic Prediction of the Metaproteome in a 4.5-Year Study of a Patient with Crohn's Disease

Although genetic approaches are the standard in microbiome analysis, proteome-level information is largely absent. This discrepancy warrants a better understanding of the relationship between gene copy number and protein abundance, as this is crucial information for inferring protein-level changes from metagenomic data. As it remains unknown how metaproteomic systems evolve during dynamic disease states, we leveraged a 4.5-year fecal time series using samples from a single patient with colonic Crohn's disease. Utilizing multiplexed quantitative proteomics and shotgun metagenomic sequencing of eight time points in technical triplicate, we quantified over 29,000 protein groups and 110,000 genes and compared them to five protein biomarkers of disease activity. Broad-scale observations were consistent between data types, including overall clustering by principal-coordinate analysis and fluctuations in Gene Ontology terms related to Crohn's disease. Through linear regression, we determined genes and proteins fluctuating in conjunction with inflammatory metrics. We discovered conserved taxonomic differences relevant to Crohn's disease, including a negative association of Faecalibacterium and a positive association of Escherichia with calprotectin. Despite concordant associations of genera, the specific genes correlated with these metrics were drastically different between metagenomic and metaproteomic data sets. This resulted in the generation of unique functional interpretations dependent on the data type, with metaproteome evidence for previously investigated mechanisms of dysbiosis. An example of one such mechanism was a connection between urease enzymes, amino acid metabolism, and the local inflammation state within the patient. This proof-of-concept approach prompts further investigation of the metaproteome and its relationship with the metagenome in biologically complex systems such as the microbiome. IMPORTANCE A majority of current microbiome research relies heavily on DNA analysis. However, as the field moves toward understanding the microbial functions related to healthy and disease states, it is critical to evaluate how changes in DNA relate to changes in proteins, which are functional units of the genome. This study tracked the abundance of genes and proteins as they fluctuated during various inflammatory states in a 4.5-year study of a patient with colonic Crohn's disease. Our results indicate that despite a low level of correlation, taxonomic associations were consistent in the two data types. While there was overlap of the data types, several associations were uniquely discovered by analyzing the metaproteome component. This case study provides unique and important insights into the fundamental relationship between the genes and proteins of a single individual's fecal microbiome associated with clinical consequences.

The Human Gut Microbiome: From Association to Modulation

Our understanding of the human gut microbiome continues to evolve at a rapid pace, but practical application of thisknowledge is still in its infancy. This review discusses the type of studies that will be essential for translating microbiome research into targeted modulations with dedicated benefits for the human host.

Challenges in Clinical Metaproteomics Highlighted by the Analysis of Acute Leukemia Patients with Gut Colonization by Multidrug-Resistant Enterobacteriaceae

The microbiome has a strong impact on human health and disease and is, therefore, increasingly studied in a clinical context. Metaproteomics is also attracting considerable attention, and such data can be efficiently generated today owing to improvements in mass spectrometry-based proteomics. As we will discuss in this study, there are still major challenges notably in data analysis that need to be overcome. Here, we analyzed 212 fecal samples from 56 hospitalized acute leukemia patients with multidrug-resistant Enterobactericeae (MRE) gut colonization using metagenomics and metaproteomics. This is one of the largest clinical metaproteomic studies to date, and the first metaproteomic study addressing the gut microbiome in MRE colonized acute leukemia patients. Based on this substantial data set, we discuss major current limitations in clinical metaproteomic data analysis to provide guidance to researchers in the field. Notably, the results show that public metagenome databases are incomplete and that sample-specific metagenomes improve results. Furthermore, biological variation is tremendous which challenges clinical study designs and argues that longitudinal measurements of individual patients are a valuable future addition to the analysis of patient cohorts.

Aqueous raw and ripe Pu-erh tea extracts alleviate obesity and alter cecal microbiota composition and function in diet-induced obese rats

Pu-erh tea is attracting increased attention worldwide because of its unique flavor and health effects, but its impact on the composition and function of the gut microbiota remains unclear. The aim of this study was to investigate the effects of aqueous extracts of fermented (ripe) and non-fermented (raw) Pu-erh teas on the composition and function of the intestinal microbiota of rats with diet-induced obesity. We conducted a comparative metagenomic and meta-proteomic investigation of the microbial communities in cecal samples taken from obese rats treated with or without extracts of raw or ripe Pu-erh teas. By analyzing the composition and diversity of 16S rRNA amplicons and expression profiles of 814 distinct proteins, we found that despite differences in the chemical compositions of raw and ripe Pu-erh teas, administration of either tea at two doses (0.15- and 0.40-g/kg body weight) significantly (P < 0.05) increased microbial diversity and changed the composition of cecal microbiota by increasing the relative abundances of Firmicutes and decreasing those of Bacteroidetes. Community metabolic processes, including sucrose metabolism, glycolysis, and syntheses of proteins, rRNAs, and antibiotics were significantly (P < 0.05) promoted or had a tendency (0.10 < P < 0.05) to be promoted due to the enrichment of relevant enzymes. Furthermore, evidence at population, molecular, and metabolic levels indicated that polyphenols of raw Pu-erh tea and their metabolites potentially promote Akkermansia muciniphila growth by stimulating a type II and III secretion system protein, the elongation factor Tu, and a glyceraldehyde-3-phosphate dehydrogenase. This study provides new evidence for the prebiotic effects of Pu-erh tea.

Methods for Studying Gut Microbiota: A Primer for Physicians

Human gastrointestinal tract contains a large variety of microbes, in particular bacteria. Studies in recent years have strongly suggested a role for these microbes, collectively referred to as gut microbiota, in the maintenance of homeostasis during health. In addition, alterations in gut microbiota have been reported in several diseases, including those related to the gastrointestinal tract and several systemic conditions, and are believed to play a pathogenetic role in at least some of these. Given the close association between the human gut and liver, the association with gut microbiota appears to be particularly strong for a wide variety of liver diseases. This piece, aimed primarily at physicians, reviews in brief the methods used to study gut microbiota, with particular emphasis on those that use sequences of bacterial 16S rRNA gene or its components.

Caloric restriction promotes functional changes involving short-chain fatty acid biosynthesis in the rat gut microbiota

Caloric restriction (CR) is known to promote health and longevity, likely via modification of the gut microbiota (GM). However, functional and metabolic changes induced in the GM during CR are still unidentified. Here, we investigated the short- and long-term effects of CR on the rat GM using a metaproteogenomic approach. We show that a switch from ad libitum (AL) low fat diet to CR in young rats is able to induce rapid and deep changes in their GM metaproteomic profile, related to a reduction of the Firmicutes/Bacteroidetes ratio and an expansion of lactobacilli. Specifically, we observed a significant change in the expression of the microbial enzymes responsible for short-chain fatty acid biosynthesis, with CR boosting propionogenesis and limiting butyrogenesis and acetogenesis. Furthermore, these CR-induced effects were maintained up to adulthood and started to be reversed after a short-term diet change. We also found that CR alters the abundance of an array of host proteins released in stool, mainly related to epithelial barrier integrity and inflammation. Hence, our results provide thorough information about CR-induced modifications to GM and host functional activity, and might constitute the basis for novel GM-based approaches aimed at monitoring the effectiveness of dietary interventions.

Proteomics and the microbiome: pitfalls and potential

Introduction: Human symbiotic microbiota are now known to play important roles in human health and disease. Significant progress in our understanding of the human microbiome has been driven by recent technological advances in the fields of genomics, transcriptomics, and proteomics. As a complementary method to metagenomics, proteomics is enabling detailed protein profiling of the microbiome to decipher its structure and function and to analyze its relationship with the human body. Fecal proteomics is being increasingly applied to discover and validate potential health and disease biomarkers, and Therapeutic Goods Administration (TGA)-approved instrumentation and a range of clinical assays are being developed that will collectively play key roles in advancing personalized medicine. Areas covered: This review will introduce the complexity of the microbiome and its role in health and disease (in particular the gastrointestinal tract or gut microbiome), discuss current genomic and proteomic methods for studying this system, including the discovery of potential biomarkers, and outline the development of clinically accepted protocols leading to personalized medicine. Expert commentary: Recognition of the important role the microbiome plays in both health and disease is driving current research in this key area. A proteogenomics approach will be essential to unravel the biologies underlying this complex network.

Triflic Acid Treatment Enables LC-MS/MS Analysis of Insoluble Bacterial Biomass

The lysis and extraction of soluble bacterial proteins from cells is a common practice for proteomics analyses, but insoluble bacterial biomasses are often left behind. Here, we show that with triflic acid treatment, the insoluble bacterial biomass of Gram^- and Gram⁺ bacteria can be rendered soluble. We use LC-MS/MS shotgun proteomics to show that bacterial proteins in the soluble and insoluble postlysis fractions differ significantly. Additionally, in the case of Gram^- Pseudomonas aeruginosa, triflic acid treatment enables the enrichment of cell-envelope-associated proteins. Finally, we apply triflic acid to a human microbiome sample to show that this treatment is robust and enables the identification of a new, complementary subset of proteins from a complex microbial mixture.

Proteomics and pulse azidohomoalanine labeling of newly synthesized proteins: what are the potential applications?

INTRODUCTION

Measuring the immediate changes in cells that arise from changing environmental conditions is crucial to understanding the underlying mechanisms involved. These changes can be measured with metabolic stable isotope fully labeled proteomes, but requires looking for changes in the midst of a large background. In addition, labeling efficiency can be an issue in primary and fully differentiated cells. Area covered: Azidohomoalanine (AHA), an analog of methionine, can be accepted by cellular translational machinery and incorporated into newly synthesized proteins (NSPs). AHA-NSPs can be coupled to biotin via CuAAC-mediated click-chemistry and enriched using avidin-based affinity purification. Thus, AHA-containing proteins or peptides can be enriched and efficiently separated from the whole proteome. In this review, we describe the development of mass spectrometry (MS) based AHA strategies and discuss their potential to measure proteins involved in immune response, secretome, gut microbiome, and proteostasis as well as their potential for clinical uses. Expert commentary: AHA strategies have been used to identify synthesis activity and to compare two biological conditions in various biological model organisms. In combination with instrument development, improved sample preparation and fractionation strategies, MS-based AHA strategies have the potential for broad application, and the methods should translate into clinical use.

Rhizosphere Microbiome Modulators: Contributions of Nitrogen Fixing Bacteria towards Sustainable Agriculture

Rhizosphere microbiome which has been shown to enhance plant growth and yield are modulated or influenced by a few environmental factors such as soil type, plant cultivar, climate change and anthropogenic activities. In particular, anthropogenic activity, such as the use of nitrogen-based chemical fertilizers, is associated with environmental destruction and this calls for a more ecofriendly strategy to increase nitrogen levels in agricultural land. This feat is attainable by harnessing nitrogen-fixing endophytic and free-living rhizobacteria. Rhizobium, Pseudomonas, Azospirillum and Bacillus, have been found to have positive impacts on crops by enhancing both above and belowground biomass and could therefore play positive roles in achieving sustainable agriculture outcomes. Thus, it is necessary to study this rhizosphere microbiome with more sophisticated culture-independent techniques such as next generation sequencing (NGS) with the prospect of discovering novel bacteria with plant growth promoting traits. This review is therefore aimed at discussing factors that can modulate rhizosphere microbiome with focus on the contributions of nitrogen fixing bacteria towards sustainable agricultural development and the techniques that can be used for their study.

Proteomics and the human microbiome: where we are today and where we would like to be

What are all these hundreds of different bacterial species doing in and on us? What interactions occur between the host and the microbes, and between the microbes themselves? By studying proteins, metaproteomics tries to find preliminary answers to these questions. There is daunting complexity around this; in fact, many of these proteins have never been studied before. This article is an introduction to the field of metaproteomics in the context of the human microbiome. It summarizes where we are and what we have learnt so far. The focus will be on faecal proteomics as most metaproteomics research has been conducted on that sample type. Metaproteomics has made major advances in the past decade, but new sample preparation strategies, improved mass spectrometric analysis and, most importantly, data analysis and interpretation have the potential to pave the way for large-cohort metaproteomics.

The intestinal proteome of diabetic and control children is enriched with different microbial and host proteins

In this study, the intestinal microbial proteome of children with established type 1 diabetes (T1D) was compared with the proteome of healthy children (Control) with the aim to identify differences in the activity of the intestinal microbiota that not only will contribute to a deeper knowledge of the functionality of the gut in these children but also may provide new approaches to improve the control of the disease. Faecal protein extracts collected from three T1D children (aged 9.3±0.6 years) and three Control children (aged 9.3±1.5 years) were analysed using a combination of 2D gel electrophoresis and spectral counting. The results evidenced markedly differences between the intestinal proteome of T1D children and the Control. The T1D microbial intestinal proteome was enriched with proteins of clostridial cluster XVa and cluster IV and Bacteroides. In contrast, the Control proteome was enriched with bifidobacterial proteins. In both groups, proteins with moonlight function were observed. Human proteins also distinguished the two groups with T1D children depleted in exocrine pancreatic enzymes.

Gut microbiota, metabolites and host immunity

The microbiota - the collection of microorganisms that live within and on all mammals - provides crucial signals for the development and function of the immune system. Increased availability of technologies that profile microbial communities is facilitating the entry of many immunologists into the evolving field of host-microbiota studies. The microbial communities, their metabolites and components are not only necessary for immune homeostasis, they also influence the susceptibility of the host to many immune-mediated diseases and disorders. In this Review, we discuss technological and computational approaches for investigating the microbiome, as well as recent advances in our understanding of host immunity and microbial mutualism with a focus on specific microbial metabolites, bacterial components and the immune system.

Predicting Species-Resolved Macronutrient Acquisition during Succession in a Model Phototrophic Biofilm Using an Integrated 'Omics Approach

The principles governing acquisition and interspecies exchange of nutrients in microbial communities and how those exchanges impact community productivity are poorly understood. Here, we examine energy and macronutrient acquisition in unicyanobacterial consortia for which species-resolved genome information exists for all members, allowing us to use multi-omic approaches to predict species' abilities to acquire resources and examine expression of resource-acquisition genes during succession. Metabolic reconstruction indicated that a majority of heterotrophic community members lacked the genes required to directly acquire the inorganic nutrients provided in culture medium, suggesting high metabolic interdependency. The sole primary producer in consortium UCC-O, cyanobacterium Phormidium sp. OSCR, displayed declining expression of energy harvest, carbon fixation, and nitrate and sulfate reduction proteins but sharply increasing phosphate transporter expression over 28 days. Most heterotrophic members likewise exhibited signs of phosphorus starvation during succession. Though similar in their responses to phosphorus limitation, heterotrophs displayed species-specific expression of nitrogen acquisition genes. These results suggest niche partitioning around nitrogen sources may structure the community when organisms directly compete for limited phosphate. Such niche complementarity around nitrogen sources may increase community diversity and productivity in phosphate-limited phototrophic communities.

Metaproteomic analysis of human gut microbiota: where are we heading?

The human gut is home to complex microbial populations that change dynamically in response to various internal and external stimuli. The gut microbiota provides numerous functional benefits that are crucial for human health but in the setting of a disturbed equilibrium, the microbial community can cause deleterious outcomes such as diseases and cancers. Characterization of the functional activities of human gut microbiota is fundamental to understand their roles in human health and disease. Metaproteomics, which refers to the study of the entire protein collection of the microbial community in a given sample is an emerging area of research that provides informative details concerning functional aspects of the microbiota. In this mini review, we present a summary of the progress of metaproteomic analysis for studying the functional role of gut microbiota. This is followed by an overview of the experimental approaches focusing on fecal specimen for metaproteomics and is concluded by a discussion on the challenges and future directions of metaproteomic research.

High-throughput metaproteomics data analysis with Unipept: A tutorial

In recent years, shotgun metaproteomics has established itself as an important tool to study the composition of complex ecosystems and microbial communities. Two key steps in metaproteomics data analysis are the inference of proteins from the identified peptides, and the determination of the taxonomic origin and function of these proteins. This tutorial therefore introduces the Unipept command line interface (http://unipept.ugent.be/clidocs) as a platform-independent tool for such metaproteomics data analyses. First, a detailed overview is given of the available Unipept commands and their functions. Next, the power of the Unipept command line interface is illustrated using two case studies that analyze a single tryptic peptide, and a set of peptides retrieved from a shotgun metaproteomics experiment, respectively. Finally, the analysis results obtained using these command line tools are compared with the interactive taxonomic analysis that is available on the Unipept website.

Gut microbiota functions: metabolism of nutrients and other food components

The diverse microbial community that inhabits the human gut has an extensive metabolic repertoire that is distinct from, but complements the activity of mammalian enzymes in the liver and gut mucosa and includes functions essential for host digestion. As such, the gut microbiota is a key factor in shaping the biochemical profile of the diet and, therefore, its impact on host health and disease. The important role that the gut microbiota appears to play in human metabolism and health has stimulated research into the identification of specific microorganisms involved in different processes, and the elucidation of metabolic pathways, particularly those associated with metabolism of dietary components and some host-generated substances. In the first part of the review, we discuss the main gut microorganisms, particularly bacteria, and microbial pathways associated with the metabolism of dietary carbohydrates (to short chain fatty acids and gases), proteins, plant polyphenols, bile acids, and vitamins. The second part of the review focuses on the methodologies, existing and novel, that can be employed to explore gut microbial pathways of metabolism. These include mathematical models, omics techniques, isolated microbes, and enzyme assays.

Metaproteomic strategies and applications for gut microbial research

The human intestine hosts various complex microbial communities that are closely associated with multiple health and disease processes. Determining the composition and function of these microbial communities is critical to unveil disease mechanisms and promote human health. Recently, meta-omic strategies have been developed that use high-throughput techniques to provide a wealth of information, thus accelerating the study of gut microbes. Metaproteomics is a newly emerged analytical approach that aims to identify proteins on a large scale in complex environmental microbial communities (e.g., the gut microbiota). This review introduces the recent analytical strategies and applications of metaproteomics, with a focus on advances in gut microbiota research, including a discussion of the limitations and challenges of these approaches.

Quantitative Metaproteomics and Activity-Based Probe Enrichment Reveals Significant Alterations in Protein Expression from a Mouse Model of Inflammatory Bowel Disease

Tandem mass spectrometry based shotgun proteomics of distal gut microbiomes is exceedingly difficult due to the inherent complexity and taxonomic diversity of the samples. We introduce two new methodologies to improve metaproteomic studies of microbiome samples. These methods include the stable isotope labeling in mammals to permit protein quantitation across two mouse cohorts as well as the application of activity-based probes to enrich and analyze both host and microbial proteins with specific functionalities. We used these technologies to study the microbiota from the adoptive T cell transfer mouse model of inflammatory bowel disease (IBD) and compare these samples to an isogenic control, thereby limiting genetic and environmental variables that influence microbiome composition. The data generated highlight quantitative alterations in both host and microbial proteins due to intestinal inflammation and corroborates the observed phylogenetic changes in bacteria that accompany IBD in humans and mouse models. The combination of isotope labeling with shotgun proteomics resulted in the total identification of 4434 protein clusters expressed in the microbial proteomic environment, 276 of which demonstrated differential abundance between control and IBD mice. Notably, application of a novel cysteine-reactive probe uncovered several microbial proteases and hydrolases overrepresented in the IBD mice. Implementation of these methods demonstrated that substantial insights into the identity and dysregulation of host and microbial proteins altered in IBD can be accomplished and can be used in the interrogation of other microbiome-related diseases.

An introduction to microbiome analysis for human biology applications

Research examining the gut microbiota is currently exploding, and results are providing new perspectives on human biology. Factors such as host diet and physiology influence the composition and function of the gut microbiota, which in turn affects human nutrition, health, and behavior via interactions with metabolism, the immune system, and the brain. These findings represent an exciting new twist on familiar topics, and as a result, gut microbiome research is likely to provide insight into unresolved biological mechanisms driving human health. However, much remains to be learned about the broader ecological and evolutionary contexts within which gut microbes and humans are affecting each other. Here, I outline the procedures for generating data describing the gut microbiota with the goal of facilitating the wider integration of microbiome analyses into studies of human biology. I describe the steps involved in sample collection, DNA extraction, PCR amplification, high-throughput sequencing, and bioinformatics. While this review serves only as an introduction to these topics, it provides sufficient resources for researchers interested in launching new microbiome initiatives. As knowledge of these methods spreads, microbiome analysis should become a standard tool in the arsenal of human biology research.

The impact of sequence database choice on metaproteomic results in gut microbiota studies

BACKGROUND

Elucidating the role of gut microbiota in physiological and pathological processes has recently emerged as a key research aim in life sciences. In this respect, metaproteomics, the study of the whole protein complement of a microbial community, can provide a unique contribution by revealing which functions are actually being expressed by specific microbial taxa. However, its wide application to gut microbiota research has been hindered by challenges in data analysis, especially related to the choice of the proper sequence databases for protein identification.

RESULTS

Here, we present a systematic investigation of variables concerning database construction and annotation and evaluate their impact on human and mouse gut metaproteomic results. We found that both publicly available and experimental metagenomic databases lead to the identification of unique peptide assortments, suggesting parallel database searches as a mean to gain more complete information. In particular, the contribution of experimental metagenomic databases was revealed to be mandatory when dealing with mouse samples. Moreover, the use of a "merged" database, containing all metagenomic sequences from the population under study, was found to be generally preferable over the use of sample-matched databases. We also observed that taxonomic and functional results are strongly database-dependent, in particular when analyzing the mouse gut microbiota. As a striking example, the Firmicutes/Bacteroidetes ratio varied up to tenfold depending on the database used. Finally, assembling reads into longer contigs provided significant advantages in terms of functional annotation yields.

CONCLUSIONS

This study contributes to identify host- and database-specific biases which need to be taken into account in a metaproteomic experiment, providing meaningful insights on how to design gut microbiota studies and to perform metaproteomic data analysis. In particular, the use of multiple databases and annotation tools has to be encouraged, even though this requires appropriate bioinformatic resources.

Studying the Human Microbiota

There are a range of methodologies available to study the human microbiota, ranging from traditional approaches such as culturing through to state-of-the-art developments in next generation DNA sequencing technologies. The advent of molecular techniques in particular has opened up tremendous new avenues for research, and has galvanised interest in the study of our microbial inhabitants. Given the dazzling array of available options, however, it is important to understand the inherent advantages and limitations of each technique so that the best approach can be employed to address the particular research objective. In this chapter we cover some of the most widely used current techniques in human microbiota research and highlight the particular strengths and caveats associated with each approach.

A comprehensive and scalable database search system for metaproteomics

BACKGROUND

Mass spectrometry-based shotgun proteomics experiments rely on accurate matching of experimental spectra against a database of protein sequences. Existing computational analysis methods are limited in the size of their sequence databases, which severely restricts the proteomic sequencing depth and functional analysis of highly complex samples. The growing amount of public high-throughput sequencing data will only exacerbate this problem. We designed a broadly applicable metaproteomic analysis method (ComPIL) that addresses protein database size limitations.

RESULTS

Our approach to overcome this significant limitation in metaproteomics was to design a scalable set of sequence databases assembled for optimal library querying speeds. ComPIL was integrated with a modified version of the search engine ProLuCID (termed "Blazmass") to permit rapid matching of experimental spectra. Proof-of-principle analysis of human HEK293 lysate with a ComPIL database derived from high-quality genomic libraries was able to detect nearly all of the same peptides as a search with a human database (~500x fewer peptides in the database), with a small reduction in sensitivity. We were also able to detect proteins from the adenovirus used to immortalize these cells. We applied our method to a set of healthy human gut microbiome proteomic samples and showed a substantial increase in the number of identified peptides and proteins compared to previous metaproteomic analyses, while retaining a high degree of protein identification accuracy and allowing for a more in-depth characterization of the functional landscape of the samples.

CONCLUSIONS

The combination of ComPIL with Blazmass allows proteomic searches to be performed with database sizes much larger than previously possible. These large database searches can be applied to complex meta-samples with unknown composition or proteomic samples where unexpected proteins may be identified. The protein database, proteomic search engine, and the proteomic data files for the 5 microbiome samples characterized and discussed herein are open source and available for use and additional analysis.

Mechanistic and Technical Challenges in Studying the Human Microbiome and Cancer Epidemiology

This article reviews the significance of the microbiome in cancer epidemiology, mechanistic and technical challenges in the field, and characterization of the microbiome in different tumor types to identify biomarkers of risk, progression, and prognosis. Publications on the microbiome and cancer epidemiology were reviewed to analyze sample collection and processing, microbiome taxa characterization by 16S ribosomal RNA sequencing, and microbiome metabolite characterization (metabotyping) by nuclear magnetic resonance and mass spectrometry. The analysis identified methodology types, research design, sample types, and issues in integrating data from different platforms. Aerodigestive cancer epidemiology studies conducted by different groups demonstrated the significance of microbiome information in developing approaches to improve health. Challenges exist in sample preparation and processing (eg, standardization of methods for collection and analysis). These challenges relate to technology, data integration from "omics" studies, inherent bias in primer selection during 16S ribosomal RNA sequencing, the need for large consortia with well-characterized biospecimens, cause and effect issues, resilience of microbiota to exposure events (requires longitudinal studies), and expanding studies for fungal and viral diversity (most studies used bacterial 16S ribosomal RNA sequencing for microbiota characterization). Despite these challenges, microbiome and cancer epidemiology studies are significant and may facilitate cancer risk assessment, diagnosis, and prognosis. In the future, clinical trials likely will use microbiota modifications to improve the efficacy of existing treatments.

An integrated metagenome and -proteome analysis of the microbial community residing in a biogas production plant

To study the metaproteome of a biogas-producing microbial community, fermentation samples were taken from an agricultural biogas plant for microbial cell and protein extraction and corresponding metagenome analyses. Based on metagenome sequence data, taxonomic community profiling was performed to elucidate the composition of bacterial and archaeal sub-communities. The community's cytosolic metaproteome was represented in a 2D-PAGE approach. Metaproteome databases for protein identification were compiled based on the assembled metagenome sequence dataset for the biogas plant analyzed and non-corresponding biogas metagenomes. Protein identification results revealed that the corresponding biogas protein database facilitated the highest identification rate followed by other biogas-specific databases, whereas common public databases yielded insufficient identification rates. Proteins of the biogas microbiome identified as highly abundant were assigned to the pathways involved in methanogenesis, transport and carbon metabolism. Moreover, the integrated metagenome/-proteome approach enabled the examination of genetic-context information for genes encoding identified proteins by studying neighboring genes on the corresponding contig. Exemplarily, this approach led to the identification of a Methanoculleus sp. contig encoding 16 methanogenesis-related gene products, three of which were also detected as abundant proteins within the community's metaproteome. Thus, metagenome contigs provide additional information on the genetic environment of identified abundant proteins.

Faecal Metaproteomic Analysis Reveals a Personalized and Stable Functional Microbiome and Limited Effects of a Probiotic Intervention in Adults

Recent metagenomic studies have demonstrated that the overall functional potential of the intestinal microbiome is rather conserved between healthy individuals. Here we assessed the biological processes undertaken in-vivo by microbes and the host in the intestinal tract by conducting a metaproteome analysis from a total of 48 faecal samples of 16 healthy adults participating in a placebo-controlled probiotic intervention trial. Half of the subjects received placebo and the other half consumed Lactobacillus rhamnosus GG for three weeks (10¹⁰ cfu per day). Faecal samples were collected just before and at the end of the consumption phase as well as after a three-week follow-up period, and were processed for microbial composition and metaproteome analysis. A common core of shared microbial protein functions could be identified in all subjects. Furthermore, we observed marked differences in expressed proteins between subjects that resulted in the definition of a stable and personalized microbiome both at the mass-spectrometry-based proteome level and the functional level based on the KEGG pathway analysis. No significant changes in the metaproteome were attributable to the probiotic intervention. A detailed taxonomic assignment of peptides and comparison to phylogenetic microarray data made it possible to evaluate the activity of the main phyla as well as key species, including Faecalibacterium prausnitzii. Several correlations were identified between human and bacterial proteins. Proteins of the human host accounted for approximately 14% of the identified metaproteome and displayed variations both between and within individuals. The individually different human intestinal proteomes point to personalized host-microbiota interactions. Our findings indicate that analysis of the intestinal metaproteome can complement gene-based analysis and contributes to a thorough understanding of the activities of the microbiome and the relevant pathways in health and disease.

Enhancing metaproteomics--The value of models and defined environmental microbial systems

Metaproteomics--the large-scale characterization of the entire protein complement of environmental microbiota at a given point in time--has provided new features to study complex microbial communities in order to unravel these "black boxes." New technical challenges arose that were not an issue for classical proteome analytics before that could be tackled by the application of different model systems. Here, we review different current and future model systems for metaproteome analysis. Following a short introduction to microbial communities and metaproteomics, we introduce model systems for clinical and biotechnological research questions including acid mine drainage, anaerobic digesters, and activated sludge. Model systems are useful to evaluate the challenges encountered within (but not limited to) metaproteomics, including species complexity and coverage, biomass availability, or reliable protein extraction. The implementation of model systems can be considered as a step forward to better understand microbial community responses and ecological functions of single member organisms. In the future, improvements are necessary to fully explore complex environmental systems by metaproteomics.