An iterative workflow for mining the human intestinal metaproteome

Synergistic effect of berberine hydrochloride and dehydrocostus lactone in the treatment of ulcerative colitis: Take gut microbiota as the target

Ulcerative colitis (UC) is a difficult-to-cure and recurrent inflammatory bowel disease, and it is difficult to maintain long-term results with a single drug. Inspired by clinical medication in traditional Chinese medicine, we used berberine hydrochloride (BBH) and dehydrocostus lactone (DEH) in combination for the first time and focused on studying their mechanism of treating UC based on gut microbiota. Therefore, we evaluated the therapeutic effects of BBH and DEH on DSS-induced UC mice using ELISA, HE and AB-PAS staining, 16s rDNA amplicon sequencing technology, and fecal transplantation experiments (FMT). In this study, the combination of BBH and DEH significantly relieved symptoms, colonic inflammation, and intestinal barrier damage of DSS-induced UC mice, and they did not show antagonism. In addition, the co-administration of BBH and DEH altered the composition and function of gut microbiota, with BBH increasing the abundance of key beneficial bacterial genus Akkermansia and DEH aiming to enhance species diversity and supplying intestinal proteins to prevent overconsumption. Furthermore, our data showed that BBH and DEH improve the levels of short-chain fatty acids, which also proved the positive regulation of gut microbiota by BBH and DEH. Finally, the FMT confirmed the strong correlation between BBH, DEH, and the gut microbiota. In conclusion, the co-administration of BBH and DEH protected the intestinal barrier and reduced inflammatory damage by regulating gut microbiota, targeting the key beneficial bacterial genus Akkermansia, and maintaining a normal supply of intestinal proteins.

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.

Mode of action of Akkermansia muciniphila in the intestinal dialogue: role of extracellular proteins, metabolites and cell envelope components

Akkermansia muciniphila is a promising next-generation beneficial microbe due to its natural presence in the mucus layer of the gut, its symbiotic ability to degrade mucus, and its capacity to improve the intestinal barrier function. A. muciniphila is able to counteract weight gain and immuno-metabolic disturbances in several animal models. Many of these disorders, including obesity and auto-immune diseases, have been associated with decreased gut barrier function and consequent increased inflammation. Since A. muciniphila was found to normalize these changes and strengthen the gut barrier function, it is hypothesized that other beneficial effects of A. muciniphila might be caused by this restoration. In search for A. muciniphila's mode of action in enhancing the gut barrier function and promoting health, we reasoned that secreted components or cell envelope components of A. muciniphila are interesting candidates as they can potentially reach and interact with the epithelial barrier. In this review, we focus on the potential mechanisms through which A. muciniphila can exert its beneficial effects on the host by the production of extracellular and secreted proteins, metabolites and cell envelope components. These products have been studied in isolation for their structure, signaling capacity, and in some cases, also for their effects in preclinical models. This includes the protein known as Amuc_1100, which we here rename as pilus-associated signaling (PAS) protein , the P9 protein encoded by Amuc_1631, the short-chain fatty acids acetate and propionate, and cell envelope components, such as phosphatidylethanolamine and peptidoglycan.

The evolution and competitive strategies of Akkermansia muciniphila in gut

Akkermansia muciniphila is a commensal bacterium using mucin as its sole carbon and nitrogen source. A. muciniphila is a promising candidate for next-generation probiotics to prevent inflammatory and metabolic disorders, including diabetes and obesity, and to increase the response to cancer immunotherapy. In this study, a comparative pan-genome analysis was conducted to investigate the genomic diversity and evolutionary relationships between complete genomes of 27 A. muciniphila strains, including KGMB strains isolated from healthy Koreans. The analysis showed that A. muciniphila strains formed two clades of group A and B in a phylogenetic tree constructed using 1,219 orthologous single-copy core genes. Interestingly, group A comprised of strains from human feces in Korea, whereas most of group B comprised strains from human feces in Europe and China, and from mouse feces. As group A and B branched, mucin hydrolysis played an important role in the stability of the core genome and drove evolution in the direction of defense against invading pathogens, survival in, and colonization in the mucus layer. In addition, WapA and anSME, which function in competition and post-translational modification of sulfatase, respectively, have been a particularly important selective pressure in the evolution of group A. KGMB strains in group A with anSME gene showed sulfatase activity, but KCTC 15667^T in group B without anSME did not. Our findings revealed that KGMB strains evolved to gain an edge in the competition with other gut bacteria by increasing the utilization of sulfated mucin, which will allow it to become highly colonized in the gut environment.

Structural analysis of the sulfatase AmAS from Akkermansia muciniphila

Akkermansia muciniphila, an anaerobic Gram-negative bacterium, is a major intestinal commensal bacterium that can modulate the host immune response. It colonizes the mucosal layer and produces nutrients for the gut mucosa and other commensal bacteria. It is believed that mucin desulfation is the rate-limiting step in the mucin-degradation process, and bacterial sulfatases that carry out mucin desulfation have been well studied. However, little is known about the structural characteristics of A. muciniphila sulfatases. Here, the crystal structure of the premature form of the A. muciniphila sulfatase AmAS was determined. Structural analysis combined with docking experiments defined the critical active-site residues that are responsible for catalysis. The loop regions I–V were proposed to be essential for substrate binding. Structure-based sequence alignment and structural superposition allow further elucidation of how different subclasses of formylglycine-dependent sulfatases (FGly sulfatases) adopt the same catalytic mechanism but exhibit diverse substrate specificities. These results advance the understanding of the substrate-recognition mechanisms of A. muciniphila FGly-type sulfatases. Structural variations around the active sites account for the different substrate-binding properties. These results will enhance the understanding of the roles of bacterial sulfatases in the metabolism of glycans and host–microbe interactions in the human gut environment.

Gut microbiota signatures and clinical manifestations in celiac disease children at onset: a pilot study

BACKGROUND AND AIM

Recent researches have shown an altered gut microbiota in celiac disease (CD) patients compared with healthy controls (HCs). This study aims to evaluate the composition of the microbiota of CD children at onset and the relationship between bacterial abundances and symptoms.

METHODS

Celiac disease patients were consecutively enrolled at a pediatric unit referring for suspected CD. HCs were also included in the study. Stool and duodenal samples were collected and evaluated by a high taxonomic fingerprint microbiota array.

RESULTS

Thirty-seven subjects enrolled: 21 CD patients and 16 HCs. Fourteen subjects were male (38%). The mean age was 75 months (standard deviation 31.5) for CD patients and 71 months (standard deviation 34.9) for HCs. Duodenal microbiota of CD patients showed a dominance of Enterobacteriaceae and subdominance of Bacteroidetes/Streptococcus. Stool microbiota showed a lower abundance of Bacteroides-Prevotella (P = 0.013), Akkermansia (P = 0.002), and Staphylococcaceae (P = 0.001) in CD patients compared with HC. At symptoms level, an increased mean relative abundance of Bacillaceae and Enterobaeriaceae in patients with abdominal pain (P = 0.007 and P = 0.010) was found. CD patients with diarrhea had reduced mean relative abundance of Clostridium cluster XIVa (P = 0.044) and Akkermansia (P = 0.033) and an increase in Bacillaceae (P = 0.048) and Fusobacterium (P = 0.048).

CONCLUSIONS

Gut microbiota of CD children at disease onset is different from that of HC. Pro-inflammatory microbiota imbalances were associated with CD symptoms. Further studies are needed to assess whether dysbiosis is associated with CD early onset and symptoms.

TaxIt: An Iterative Computational Pipeline for Untargeted Strain-Level Identification Using MS/MS Spectra from Pathogenic Single-Organism Samples

Untargeted accurate strain-level classification of a priori unidentified organisms using tandem mass spectrometry is a challenging task. Reference databases often lack taxonomic depth, limiting peptide assignments to the species level. However, the extension with detailed strain information increases runtime and decreases statistical power. In addition, larger databases contain a higher number of similar proteomes. We present TaxIt, an iterative workflow to address the increasing search space required for MS/MS-based strain-level classification of samples with unknown taxonomic origin. TaxIt first applies reference sequence data for initial identification of species candidates, followed by automated acquisition of relevant strain sequences for low level classification. Furthermore, proteome similarities resulting in ambiguous taxonomic assignments are addressed with an abundance weighting strategy to increase the confidence in candidate taxa. For benchmarking the performance of our method, we apply our iterative workflow on several samples of bacterial and viral origin. In comparison to noniterative approaches using unique peptides or advanced abundance correction, TaxIt identifies microbial strains correctly in all examples presented (with one tie), thereby demonstrating the potential for untargeted and deeper taxonomic classification. TaxIt makes extensive use of public, unrestricted, and continuously growing sequence resources such as the NCBI databases and is available under open-source BSD license at https://gitlab.com/rki_bioinformatics/TaxIt.

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.

Robust Accurate Identification and Biomass Estimates of Microorganisms via Tandem Mass Spectrometry

Rapid and accurate identification of microorganisms and estimation of their biomasses are of extreme importance to public health. Mass spectrometry has become an important technique for these purposes. Previously we published a workflow named Microorganism Classification and Identification (MiCId v.12.26.2017) that was shown to perform no worse than other workflows. This manuscript presents MiCId v.12.13.2018 that, in comparison with the earlier version v.12.26.2017, allows for biomass estimates, provides more accurate microorganism identifications (better controls the number of false positives), and is robust against database size increase. This significant advance is made possible by several new ingredients introduced: first, we apply a modified expectation-maximization method to compute for each taxon considered a prior probability, which can be used for biomass estimate; second, we introduce a new concept called ownership, through which the participation ratio is computed and use it as the number of taxa to be kept within a cluster of closely related taxa; third, based on confidently identified peptides, we calculate for each taxon its degree of independence from the rest of taxa considered to determine whether or not to split this taxon off the cluster. Using 270 data files, each containing a large number of MS/MS spectra, we show that, in comparison with v.12.26.2017, version v.12.13.2018 yields superior retrieval results. We also show that MiCId v.12.13.2018 can estimate species biomass reasonably well. The new MiCId v.12.13.2018, designed to run in Linux environment, is freely available for download at https://www.ncbi.nlm.nih.gov/CBBresearch/Yu/downloads.html.

A Meta-proteogenomic Approach to Peptide Identification Incorporating Assembly Uncertainty and Genomic Variation

Matching metagenomic and/or metatranscriptomic data, currently often under-used, can be useful reference for metaproteomic tandem mass spectra (MS/MS) data analysis. Here we developed a software pipeline for identification of peptides and proteins from metaproteomic MS/MS data using proteins derived from matching metagenomic (and metatranscriptomic) data as the search database, based on two novel approaches Graph2Pro (published) and Var2Pep (new). Graph2Pro retains and uses uncertainties of metagenome assembly for reference-based MS/MS data analysis. Var2Pep considers the variations found in metagenomic/metatranscriptomic sequencing reads that are not retained in the assemblies (contigs). The new software pipeline provides one stop application of both tools, and it supports the use of metagenome assembly from commonly used assemblers including MegaHit and metaSPAdes. When tested on two collections of multi-omic microbiome data sets, our pipeline significantly improved the identification rate of the metaproteomic MS/MS spectra by about two folds, comparing to conventional contig- or read-based approaches (the Var2Pep alone identified 5.6% to 24.1% more unique peptides, depending on the data set). We also showed that identified variant peptides are important for functional profiling of microbiomes. All results suggested that it is important to take into consideration of the assembly uncertainties and genomic variants to facilitate metaproteomic MS/MS data interpretation.

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.

Role of Inflammation in the Pathogenesis of Diverticular Disease

Diverticulosis of the colon is the most common condition in Western societies and it is the most common anatomic alteration of the human colon. Recurrent abdominal pain is experienced by about 20% of patients with diverticulosis, but the pathophysiologic mechanisms of its occurrence are not completely understood. In the last years, several fine papers have showed clearly the role of low-grade inflammation both in the occurrence of symptoms in people having diverticulosis, both in symptom persistence following acute diverticulitis, even if the evidence available is not so strong. We do not know yet what the trigger of this low-grade inflammation occurrence is. However, some preliminary evidence found colonic dysbiosis linked to low-grade inflammation and therefore to symptom occurrence in those patients. The aim of this paper is to summarize current evidences about the role of inflammation in symptom occurrence in symptomatic uncomplicated diverticular disease and in symptom persistence after an episode of acute diverticulitis.

Relative abundance of Akkermansia spp. and other bacterial phylotypes correlates with anxiety- and depressive-like behavior following social defeat in mice

As discussion of stress and stress-related disorders rapidly extends beyond the brain, gut microbiota have emerged as a promising contributor to individual differences in the risk of illness, disease course, and treatment response. Here, we employed chronic mild social defeat stress and 16S rRNA gene metagenomic sequencing to investigate the role of microbial composition in mediating anxiety- and depressive-like behavior. In socially defeated animals, we found significant reductions in the overall diversity and relative abundances of numerous bacterial genera, including Akkermansia spp., that positively correlated with behavioral metrics of both anxiety and depression. Functional analyses predicted a reduced frequency of signaling molecule pathways, including G-protein-coupled receptors, in defeated animals. Collectively, our data suggest that shifts in microbial composition may play a role in the pathogenesis of anxiety and depression.

Functional metagenomics: a tool to gain knowledge for agronomic and veterinary sciences

The increased global demand for food production has motivated agroindustries to increase their own levels of production. Scientific efforts have contributed to improving these production systems, aiding to solve problems and establishing novel conceptual views and sustainable alternatives to cope with the increasing demand. Although microorganisms are key players in biological systems and may drive certain desired responses toward food production, little is known about the microbial communities that constitute the microbiomes associated with agricultural and veterinary activities. Understanding the diversity, structure and in situ interactions of microbes, together with how these interactions occur within microbial communities and with respect to their environments (including hosts), constitutes a major challenge with an enormous relevance for agriculture and biotechnology. The emergence of high-throughput sequencing technologies, together with novel and more accessible bioinformatics tools, has allowed researchers to learn more about the functional potential and functional activity of these microbial communities. These tools constitute a relevant approach for understanding the metabolic processes that can occur or are currently occurring in a given system and for implementing novel strategies focused on solving production problems or improving sustainability. Several 'omics' sciences and their applications in agriculture are discussed in this review, and the usage of functional metagenomics is proposed to achieve substantial advances for food agroindustries and veterinary sciences.

Pathophysiology of diverticular disease

Inflammation of diverticula, or outpouchings of the colonic mucosa and submucosa through the muscularis layer, leads to diverticulitis. The development of diverticular disease, encompassing both diverticulosis and diverticulitis, is a result of genetic predisposition, lifestyle, and environmental factors, including the microbiome. Areas covered: Previous reports implicated genetic predisposition, environmental factors, and colonic dysmotility in diverticular disease. Recent studies have associated specific host immune responses and the microbiome as contributors to diverticulitis. To review pertinent literature describing pathophysiological factors associated with diverticulosis or diverticulitis, we searched the PubMed database (March 2018) for articles considering the role of colonic architecture, genetic predisposition, environment, colonic motility, immune response, and the microbiome. Expert commentary: In the recent years, research into the molecular underpinnings of diverticular disease has enhanced our understanding of diverticular disease pathogenesis. Although acute uncomplicated diverticulitis is treated with broad spectrum antibiotics, evaluation of the microbiome has been limited and requires further comprehensive studies. Evidence suggests that a deregulation of the host immune response is associated with both diverticulosis and diverticulitis. Further examining these pathways may reveal proteins that can be therapeutic targets or aid in identifying biological determinants of clinical or surgical decision making.

Gut microbial functional maturation and succession during human early life

The evolutional trajectory of gut microbial colonization from birth has been shown to prime for health later in life. Here, we combined cultivation-independent 16S rRNA gene sequencing and metaproteomics to investigate the functional maturation of gut microbiota in faecal samples from full-term healthy infants collected at 6 and 18 months of age. Phylogenetic analysis of the metaproteomes showed that Bifidobacterium provided the highest number of distinct protein groups. Considerable divergences between taxa abundance and protein phylogeny were observed at all taxonomic ranks. Age had a profound effect on early microbiota where compositional and functional diversity of less dissimilar communities increased with time. Comparisons of the relative abundances of proteins revealed the transition of taxon-associated saccharolytic and fermentation strategies from milk and mucin-derived monosaccharide catabolism feeding acetate/propanoate synthesis to complex food-derived hexoses fuelling butanoate production. Furthermore, co-occurrence network analysis uncovered two anti-correlated modules of functional taxa. A low-connected Bifidobacteriaceae-centred guild of facultative anaerobes was succeeded by a rich club of obligate anaerobes densely interconnected around Lachnospiraceae, underpinning their pivotal roles in microbial ecosystem assemblies. Our findings establish a framework to visualize whole microbial community metabolism and ecosystem succession dynamics, proposing opportunities for microbiota-targeted health-promoting strategies early in life.

Studying microbial functionality within the gut ecosystem by systems biology

Humans are not autonomous entities. We are all living in a complex environment, interacting not only with our peers, but as true holobionts; we are also very much in interaction with our coexisting microbial ecosystems living on and especially within us, in the intestine. Intestinal microorganisms, often collectively referred to as intestinal microbiota, contribute significantly to our daily energy uptake by breaking down complex carbohydrates into simple sugars, which are fermented to short-chain fatty acids and subsequently absorbed by human cells. They also have an impact on our immune system, by suppressing or enhancing the growth of malevolent and beneficial microbes. Our lifestyle can have a large influence on this ecosystem. What and how much we consume can tip the ecological balance in the intestine. A "western diet" containing mainly processed food will have a different effect on our health than a balanced diet fortified with pre- and probiotics. In recent years, new technologies have emerged, which made a more detailed understanding of microbial communities and ecosystems feasible. This includes progress in the sequencing of PCR-amplified phylogenetic marker genes as well as the collective microbial metagenome and metatranscriptome, allowing us to determine with an increasing level of detail, which microbial species are in the microbiota, understand what these microorganisms do and how they respond to changes in lifestyle and diet. These new technologies also include the use of synthetic and in vitro systems, which allow us to study the impact of substrates and addition of specific microbes to microbial communities at a high level of detail, and enable us to gather quantitative data for modelling purposes. Here, we will review the current state of microbiome research, summarizing the computational methodologies in this area and highlighting possible outcomes for personalized nutrition and medicine.

Disseminating Metaproteomic Informatics Capabilities and Knowledge Using the Galaxy-P Framework

The impact of microbial communities, also known as the microbiome, on human health and the environment is receiving increased attention. Studying translated gene products (proteins) and comparing metaproteomic profiles may elucidate how microbiomes respond to specific environmental stimuli, and interact with host organisms. Characterizing proteins expressed by a complex microbiome and interpreting their functional signature requires sophisticated informatics tools and workflows tailored to metaproteomics. Additionally, there is a need to disseminate these informatics resources to researchers undertaking metaproteomic studies, who could use them to make new and important discoveries in microbiome research. The Galaxy for proteomics platform (Galaxy-P) offers an open source, web-based bioinformatics platform for disseminating metaproteomics software and workflows. Within this platform, we have developed easily-accessible and documented metaproteomic software tools and workflows aimed at training researchers in their operation and disseminating the tools for more widespread use. The modular workflows encompass the core requirements of metaproteomic informatics: (a) database generation; (b) peptide spectral matching; (c) taxonomic analysis and (d) functional analysis. Much of the software available via the Galaxy-P platform was selected, packaged and deployed through an online metaproteomics "Contribution Fest" undertaken by a unique consortium of expert software developers and users from the metaproteomics research community, who have co-authored this manuscript. These resources are documented on GitHub and freely available through the Galaxy Toolshed, as well as a publicly accessible metaproteomics gateway Galaxy instance. These documented workflows are well suited for the training of novice metaproteomics researchers, through online resources such as the Galaxy Training Network, as well as hands-on training workshops. Here, we describe the metaproteomics tools available within these Galaxy-based resources, as well as the process by which they were selected and implemented in our community-based work. We hope this description will increase access to and utilization of metaproteomics tools, as well as offer a framework for continued community-based development and dissemination of cutting edge metaproteomics software.

Action and function of Akkermansia muciniphila in microbiome ecology, health and disease

The discovery of Akkermansia muciniphila has opened new avenues for the use of this abundant intestinal symbiont in next generation therapeutic products, as well as targeting microbiota dynamics. A. muciniphila is known to colonize the mucosal layer of the human intestine where it triggers both host metabolic and immune responses. A. muciniphila is particularly effective in increasing mucus thickness and increasing gut barrier function. As a result host metabolic markers ameliorate. The mechanism of host regulation is thought to involve the outer membrane composition, including the type IV pili of A. muciniphila, that directly signal to host immune receptors. At the same time the metabolic activity of A. muciniphila leads to the production of short chain fatty acids that are beneficial to the host and microbiota members. This contributes to host-microbiota and microbe-microbe syntrophy The mucolytic activity and metabolite production make A. muciniphila a key species in the mucus layer, stimulating beneficial mucosal microbial networks. This well studied member of the microbiota has been studied in three aspects that will be further described in this review: i) A. muciniphila characteristics and mucin adaptation, ii) its role as key species in the mucosal microbiome, and iii) its role in host health.

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.

Challenges and perspectives of metaproteomic data analysis

In nature microorganisms live in complex microbial communities. Comprehensive taxonomic and functional knowledge about microbial communities supports medical and technical application such as fecal diagnostics as well as operation of biogas plants or waste water treatment plants. Furthermore, microbial communities are crucial for the global carbon and nitrogen cycle in soil and in the ocean. Among the methods available for investigation of microbial communities, metaproteomics can approximate the activity of microorganisms by investigating the protein content of a sample. Although metaproteomics is a very powerful method, issues within the bioinformatic evaluation impede its success. In particular, construction of databases for protein identification, grouping of redundant proteins as well as taxonomic and functional annotation pose big challenges. Furthermore, growing amounts of data within a metaproteomics study require dedicated algorithms and software. This review summarizes recent metaproteomics software and addresses the introduced issues in detail.

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.

Functional proteomics within the genus Lactobacillus

Lactobacillus are mainly used for the manufacture of fermented dairy, sourdough, meat, and vegetable foods or used as probiotics. Under optimal processing conditions, Lactobacillus strains contribute to food functionality through their enzyme portfolio and the release of metabolites. An extensive genomic diversity analysis was conducted to elucidate the core features of the genus Lactobacillus, and to provide a better comprehension of niche adaptation of the strains. However, proteomics is an indispensable "omics" science to elucidate the proteome diversity, and the mechanisms of regulation and adaptation of Lactobacillus strains. This review focuses on the novel and comprehensive knowledge of functional proteomics and metaproteomics of Lactobacillus species. A large list of proteomic case studies of different Lactobacillus species is provided to illustrate the adaptability of the main metabolic pathways (e.g., carbohydrate transport and metabolism, pyruvate metabolism, proteolytic system, amino acid metabolism, and protein synthesis) to various life conditions. These investigations have highlighted that lactobacilli modulate the level of a complex panel of proteins to growth/survive in different ecological niches. In addition to the general regulation and stress response, specific metabolic pathways can be switched on and off, modifying the behavior of the strains.

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.

Monitoring Perinatal Gut Microbiota in Mouse Models by Mass Spectrometry Approaches: Parental Genetic Background and Breastfeeding Effects

At birth, contact with external stimuli, such as nutrients derived from food, is necessary to modulate the symbiotic balance between commensal and pathogenic bacteria, protect against bacterial dysbiosis, and initiate the development of the mucosal immune response. Among a variety of different feeding patterns, breastfeeding represents the best modality. In fact, the capacity of breast milk to modulate the composition of infants’ gut microbiota leads to beneficial effects on their health. In this study, we used newborn mice as a model to evaluate the effect of parental genetic background (i.e., IgA-producing mice and IgA-deficient mice) and feeding modulation (i.e., maternal feeding and cross-feeding) on the onset and shaping of gut microbiota after birth. To investigate these topics, we used either a culturomic approach that employed Matrix Assisted Laser Desorption Ionization Time-of-Flight Mass Spectrometry (MS), or bottom–up Liquid Chromatography, with subsequent MSMS shotgun metaproteomic analysis that compared and assembled results of the two techniques. We found that the microbial community was enriched by lactic acid bacteria when pups were breastfed by wild-type (WT) mothers, while IgA-deficient milk led to an increase in the opportunistic bacterial pathogen (OBP) population. Cross-feeding results suggested that IgA supplementation promoted the exclusion of some OBPs and the temporary appearance of beneficial species in pups fed by WT foster mothers. Our results show that both techniques yield a picture of microbiota from different angles and with varying depths. In particular, our metaproteomic pipeline was found to be a reliable tool in the description of microbiota. Data from these studies are available via ProteomeXchange, with identifier PXD004033.

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.

The interplay between microbiota and inflammation: lessons from peritonitis and sepsis

Mammals harbor a complex gut-associated microbiota, comprising bacteria that provide immunological, metabolic and neurological benefits to the host, and contribute to their well-being. However, dysregulation of the microbiota composition, known as dysbiosis, along with the associated mucosal immune response have a key role in the pathogenesis of many inflammatory diseases, including inflammatory bowel diseases (IBDs), type 1 and type 2 diabetes, asthma, multiple sclerosis, among others. In addition, outside the gut lumen, bacteria from microbiota are the causative agent of peritoneal inflammation, abdominal sepsis and systemic sepsis. Critical care interventions during sepsis by antibiotics induce dysbiosis and present acute and long-term poor prognosis. In this review, we discuss immunomodulatory effects of the microbial molecules and products, highlighting the role of Bacteroides fragilis, a human commensal with ambiguous interactions with the host. Moreover, we also address the impact of antibiotic treatment in sepsis outcome and discuss new insights for microbiota modulation.

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.

Meta-omics in Inflammatory Bowel Disease Research: Applications, Challenges, and Guidelines

Meta-omics [metagenomics, metatranscriptomics, and metaproteomics] are rapidly expanding our knowledge of the gut microbiota in health and disease. These technologies are increasingly used in inflammatory bowel disease [IBD] research. Yet, meta-omics data analysis, interpretation, and among-study comparison remain challenging. In this review we discuss the role these techniques are playing in IBD research, highlighting their strengths and limitations. We give guidelines on proper sample collection and preparation methods, and on performing the analyses and interpreting the results, reporting available user-friendly tools and pipelines.

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.

Application of density gradient for the isolation of the fecal microbial stool component and the potential use thereof

The idea of considering the gut microbiota as a virtual human organ has led to the concept of fecal microbiota transplantation (FMT), which has recently been extremely successful in the treatment of cases of recurrent Clostridium difficile infection. Administration of safe, viable, and representative fecal microbiota is crucial for FMT. To our knowledge, suitable techniques and systematic conditions for separating the fecal microbiota from stool samples have not been thoroughly investigated. In this work we show the potential to separate stool microorganisms from the rest of fecal material using a procedure with a Nycodenz® density gradient, yielding 10¹⁰ viable bacteria per two grams of feces. This procedure did not affect the original microbiota composition in terms of viability, distribution and proportions, as assessed by a phylogenetic metagenomic approach. Obtaining the fecal microbiota by concentration and separation of the microorganisms from the rest of the stool components would allow the standardization of its recovery and its long-term preservation. FMT or similar microbiota restoration therapies could be used for the treatment of several disorders, or even for aesthetic purposes, so the method described in our work may contribute to the setting of the basis for the development of safe and standardized products.

Proteomic tools to decipher microbial community structure and functioning

Recent advances in microbial ecology allow studying microorganisms in their environment, without laboratory cultivation, in order to get access to the large uncultivable microbial community. With this aim, environmental proteomics has emerged as an appropriate complementary approach to metagenomics providing information on key players that carry out main metabolic functions and addressing the adaptation capacities of living organisms in situ. In this review, a wide range of proteomic approaches applied to investigate the structure and functioning of microbial communities as well as recent examples of such studies are presented.

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

The human gastrointestinal tract is a complex, dynamic ecosystem that consists of a carefully tuned balance of human host and microbiota membership. The microbiome is not merely a collection of opportunistic parasites, but rather provides important functions to the host that are absolutely critical to many aspects of health, including nutrient transformation and absorption, drug metabolism, pathogen defense, and immune system development. Microbial metaproteomics provides the ability to characterize the human gut microbiota functions and metabolic activities at a remarkably deep level, revealing information about microbiome development and stability as well as their interactions with their human host. Generally, microbial and human proteins can be extracted and then measured by high performance MS-based proteomics technology. Here, we review the field of human gut microbiome metaproteomics, with a focus on the experimental and informatics considerations involved in characterizing systems ranging from low-complexity model gut microbiota in gnotobiotic mice, to the emerging gut microbiome in the GI tract of newborn human infants, and finally to an established gut microbiota in human adults.

Navigating through metaproteomics data: a logbook of database searching

Metaproteomic research involves various computational challenges during the identification of fragmentation spectra acquired from the proteome of a complex microbiome. These issues are manifold and range from the construction of customized sequence databases, the optimal setting of search parameters to limitations in the identification search algorithms themselves. In order to assess the importance of these individual factors, we studied the effect of strategies to combine different search algorithms, explored the influence of chosen database search settings, and investigated the impact of the size of the protein sequence database used for identification. Furthermore, we applied de novo sequencing as a complementary approach to classic database searching. All evaluations were performed on a human intestinal metaproteome dataset. Pyrococcus furiosus proteome data were used to contrast database searching of metaproteomic data to a classic proteomic experiment. Searching against subsets of metaproteome databases and the use of multiple search engines increased the number of identifications. The integration of P. furiosus sequences in a metaproteomic sequence database showcased the limitation of the target-decoy-controlled false discovery rate approach in combination with large sequence databases. The selection of varying search engine parameters and the application of de novo sequencing represented useful methods to increase the reliability of the results. Based on our findings, we provide recommendations for the data analysis that help researchers to establish or improve analysis workflows in metaproteomics.

Enrichment or depletion? The impact of stool pretreatment on metaproteomic characterization of the human gut microbiota

To date, most metaproteomic studies of the gut microbiota employ stool sample pretreatment methods to enrich for microbial components. However, a specific investigation aimed at assessing if, how, and to what extent this may impact on the final taxonomic and functional results is still lacking. Here, stool replicates were either pretreated by differential centrifugation (DC) or not centrifuged. Protein extracts were then processed by filter-aided sample preparation, single-run LC, and high-resolution MS, and the metaproteomic data were compared by spectral counting. DC led to a higher number of identifications, a significantly richer microbial diversity, as well as to reduced information on the nonmicrobial components (host and food) when compared to not centrifuged. Nevertheless, dramatic differences in the relative abundance of several gut microbial taxa were also observed, including a significant change in the Firmicutes/Bacteroidetes ratio. Furthermore, some important microbial functional categories, including cell surface enzymes, membrane-associated proteins, extracellular proteins, and flagella, were significantly reduced after DC. In conclusion, this work underlines that a critical evaluation is needed when selecting the appropriate stool sample processing protocol in the context of a metaproteomic study, depending on the specific target to which the research is aimed. All MS data have been deposited in the ProteomeXchange with identifier PXD001573 (http://proteomecentral.proteomexchange.org/dataset/PXD001573).

Molecular ecological tools to decipher the role of our microbial mass in obesity

After birth, our gastrointestinal (GI) tract is colonised by a highly complex assemblage of microbes, collectively termed the GI microbiota, that develops intimate interactions with our body. Recent evidence indicates that the GI microbiota and its products may contribute to the development of obesity and related diseases. This, coupled with the current worldwide epidemic of obesity, has moved microbiome research into the spotlight of attention. Although the main cause of obesity and its associated metabolic complications is excess caloric intake compared with expenditure, differences in GI tract microbial ecology between individuals might be an important biomarker, mediator or new therapeutic target. This can be investigated using a diverse set of complementary so called -omics technologies, such as 16S ribosomal RNA gene-targeted composition profiling, metabolomics, metagenomics, metatranscriptomics and metaproteomics. This review aims to describe the different molecular approaches and their contributions to our understanding of the role of the GI microbiota in host energy homeostasis. Correspondingly, we highlight their respective strengths, but also try to create awareness for their specific limitations. However, it is currently still unclear which bacterial groups play a role in the development of obesity in humans. This might partly be explained by the heterogeneity in genotype, lifestyle, diet and the complex ethology of obesity and its associated metabolic disorders (OAMD). Nevertheless, recent research on this matter has shown a conceptual shift by focusing on more homogenous subpopulations, through the use of both anthropometric (weight, total body fat) as well as biochemical variables (insulin resistance, hyperlipidaemia) to define categories. Combined with technological advances, recent data suggests that an OAMD associated microbiota can be characterised by a potential pro-inflammatory composition, with less potential for the production of short chain fatty acids and butyrate in particular.

Systems-based approaches to unravel multi-species microbial community functioning

Some of the most transformative discoveries promising to enable the resolution of this century's grand societal challenges will most likely arise from environmental science and particularly environmental microbiology and biotechnology. Understanding how microbes interact in situ, and how microbial communities respond to environmental changes remains an enormous challenge for science. Systems biology offers a powerful experimental strategy to tackle the exciting task of deciphering microbial interactions. In this framework, entire microbial communities are considered as metaorganisms and each level of biological information (DNA, RNA, proteins and metabolites) is investigated along with in situ environmental characteristics. In this way, systems biology can help unravel the interactions between the different parts of an ecosystem ultimately responsible for its emergent properties. Indeed each level of biological information provides a different level of characterisation of the microbial communities. Metagenomics, metatranscriptomics, metaproteomics, metabolomics and SIP-omics can be employed to investigate collectively microbial community structure, potential, function, activity and interactions. Omics approaches are enabled by high-throughput 21st century technologies and this review will discuss how their implementation has revolutionised our understanding of microbial communities.

Pipasic: similarity and expression correction for strain-level identification and quantification in metaproteomics

MOTIVATION

Metaproteomic analysis allows studying the interplay of organisms or functional groups and has become increasingly popular also for diagnostic purposes. However, difficulties arise owing to the high sequence similarity between related organisms. Further, the state of conservation of proteins between species can be correlated with their expression level, which can lead to significant bias in results and interpretation. These challenges are similar but not identical to the challenges arising in the analysis of metagenomic samples and require specific solutions.

RESULTS

We introduce Pipasic (peptide intensity-weighted proteome abundance similarity correction) as a tool that corrects identification and spectral counting-based quantification results using peptide similarity estimation and expression level weighting within a non-negative lasso framework. Pipasic has distinct advantages over approaches only regarding unique peptides or aggregating results to the lowest common ancestor, as demonstrated on examples of viral diagnostics and an acid mine drainage dataset.

AVAILABILITY AND IMPLEMENTATION

Pipasic source code is freely available from https://sourceforge.net/projects/pipasic/.

CONTACT

RenardB@rki.de

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Bacterial protein signals are associated with Crohn's disease

OBJECTIVE

No Crohn's disease (CD) molecular maker has advanced to clinical use, and independent lines of evidence support a central role of the gut microbial community in CD. Here we explore the feasibility of extracting bacterial protein signals relevant to CD, by interrogating myriads of intestinal bacterial proteomes from a small number of patients and healthy controls.

DESIGN

We first developed and validated a workflow-including extraction of microbial communities, two-dimensional difference gel electrophoresis (2D-DIGE), and LC-MS/MS-to discover protein signals from CD-associated gut microbial communities. Then we used selected reaction monitoring (SRM) to confirm a set of candidates. In parallel, we used 16S rRNA gene sequencing for an integrated analysis of gut ecosystem structure and functions.

RESULTS

Our 2D-DIGE-based discovery approach revealed an imbalance of intestinal bacterial functions in CD. Many proteins, largely derived from Bacteroides species, were over-represented, while under-represented proteins were mostly from Firmicutes and some Prevotella members. Most overabundant proteins could be confirmed using SRM. They correspond to functions allowing opportunistic pathogens to colonise the mucus layers, breach the host barriers and invade the mucosae, which could still be aggravated by decreased host-derived pancreatic zymogen granule membrane protein GP2 in CD patients. Moreover, although the abundance of most protein groups reflected that of related bacterial populations, we found a specific independent regulation of bacteria-derived cell envelope proteins.

CONCLUSIONS

This study provides the first evidence that quantifiable bacterial protein signals are associated with CD, which can have a profound impact on future molecular diagnosis.

Graft-versus-host disease biomarkers: omics and personalized medicine

Allogeneic hematopoietic stem cell transplantation (allo-HSCT) is the most effective form of tumor immunotherapy available to date and the frequency of transplants continues to increase worldwide. However, while allo-HSCT usually induces a beneficial graft-versus leukemia effect, a major source of morbidity and mortality following allo-HSCT is graft-versus-host disease (GVHD). Currently available diagnostic and staging tools frequently fail to identify those at higher risk for GVHD morbidity, treatment unresponsiveness, and death. Furthermore, there are shortcomings in the risk stratification of patients before GVHD clinical signs develop. In parallel, recent years have been characterized by an explosive evolution of omics technologies, largely due to technological advancements in chemistry, engineering, and bioinformatics. Building on these opportunities, plasma biomarkers have been identified and validated as promising diagnostic and prognostic tools for acute GVHD. This review summarizes current information on the types of GVHD biomarkers, the omics tools used to identify them, the biomarkers currently validated as acute GVHD markers, and future recommendations for incorporating biomarkers into new grading algorithms for risk-stratifying patients and creating more personalized treatment courses. Future directions will include randomized evaluations of these biomarkers in multicenter prospective studies while extending on the need for biomarkers of chronic GVHD.

Metaproteomics: extracting and mining proteome information to characterize metabolic activities in microbial communities

Contemporary microbial ecology studies usually employ one or more "omics" approaches to investigate the structure and function of microbial communities. Among these, metaproteomics aims to characterize the metabolic activities of the microbial membership, providing a direct link between the genetic potential and functional metabolism. The successful deployment of metaproteomics research depends on the integration of high-quality experimental and bioinformatic techniques for uncovering the metabolic activities of a microbial community in a way that is complementary to other "meta-omic" approaches. The essential, quality-defining informatics steps in metaproteomics investigations are: (1) construction of the metagenome, (2) functional annotation of predicted protein-coding genes, (3) protein database searching, (4) protein inference, and (5) extraction of metabolic information. In this article, we provide an overview of current bioinformatic approaches and software implementations in metaproteome studies in order to highlight the key considerations needed for successful implementation of this powerful community-biology tool.

Meta'omic analytic techniques for studying the intestinal microbiome

Nucleotide sequencing has become increasingly common and affordable, and is now a vital tool for studies of the human microbiome. Comprehensive microbial community surveys such as MetaHit and the Human Microbiome Project have described the composition and molecular functional profile of the healthy (normal) intestinal microbiome. This knowledge will increase our ability to analyze host and microbial DNA (genome) and RNA (transcriptome) sequences. Bioinformatic and statistical tools then can be used to identify dysbioses that might cause disease, and potential treatments. Analyses that identify perturbations in specific molecules can leverage thousands of culture-based isolate genomes to contextualize culture-independent sequences, or may integrate sequence data with whole-community functional assays such as metaproteomic or metabolomic analyses. We review the state of available systems-level models for studies of the intestinal microbiome, along with analytic techniques and tools that can be used to determine its functional capabilities in healthy and unhealthy individuals.

Evaluating the impact of different sequence databases on metaproteome analysis: insights from a lab-assembled microbial mixture

Metaproteomics enables the investigation of the protein repertoire expressed by complex microbial communities. However, to unleash its full potential, refinements in bioinformatic approaches for data analysis are still needed. In this context, sequence databases selection represents a major challenge. This work assessed the impact of different databases in metaproteomic investigations by using a mock microbial mixture including nine diverse bacterial and eukaryotic species, which was subjected to shotgun metaproteomic analysis. Then, both the microbial mixture and the single microorganisms were subjected to next generation sequencing to obtain experimental metagenomic- and genomic-derived databases, which were used along with public databases (namely, NCBI, UniProtKB/SwissProt and UniProtKB/TrEMBL, parsed at different taxonomic levels) to analyze the metaproteomic dataset. First, a quantitative comparison in terms of number and overlap of peptide identifications was carried out among all databases. As a result, only 35% of peptides were common to all database classes; moreover, genus/species-specific databases provided up to 17% more identifications compared to databases with generic taxonomy, while the metagenomic database enabled a slight increment in respect to public databases. Then, database behavior in terms of false discovery rate and peptide degeneracy was critically evaluated. Public databases with generic taxonomy exhibited a markedly different trend compared to the counterparts. Finally, the reliability of taxonomic attribution according to the lowest common ancestor approach (using MEGAN and Unipept software) was assessed. The level of misassignments varied among the different databases, and specific thresholds based on the number of taxon-specific peptides were established to minimize false positives. This study confirms that database selection has a significant impact in metaproteomics, and provides critical indications for improving depth and reliability of metaproteomic results. Specifically, the use of iterative searches and of suitable filters for taxonomic assignments is proposed with the aim of increasing coverage and trustworthiness of metaproteomic data.