Segmented filamentous bacterium uses secondary and tertiary lymphoid tissues to induce gut IgA and specific T helper 17 cell responses.

Segmented filamentous bacterium (SFB) is a symbiont that drives postnatal maturation of gut adaptive immune responses. In contrast to nonpathogenic E. coli, SFB stimulated vigorous development of Peyer's patches germinal centers but paradoxically induced only a low frequency of specific immunoglobulin A (IgA)-secreting cells with delayed accumulation of somatic mutations. Moreover, blocking Peyer's patch development abolished IgA responses to E. coli, but not to SFB. Indeed, SFB stimulated the postnatal development of isolated lymphoid follicles and tertiary lymphoid tissue, which substituted for Peyer's patches as inductive sites for intestinal IgA and SFB-specific T helper 17 (Th17) cell responses. Strikingly, in mice depleted of gut organized lymphoid tissue, SFB still induced a substantial but nonspecific intestinal Th17 cell response. These results demonstrate that SFB has the remarkable capacity to induce and stimulate multiple types of intestinal lymphoid tissues that cooperate to generate potent IgA and Th17 cell responses displaying only limited target specificity.

Benefits of Iterative Searches of Large Databases to Interpret Large Human Gut Metaproteomic Data Sets.

The gut microbiota are increasingly considered as a main partner of human health. Metaproteomics enables us to move from the functional potential revealed by metagenomics to the functions actually operating in the microbiome. However, metaproteome deciphering remains challenging. In particular, confident interpretation of a myriad of MS/MS spectra can only be pursued with smart database searches. Here, we compare the interpretation of MS/MS data sets from 48 individual human gut microbiomes using three interrogation strategies of the dedicated Integrated nonredundant Gene Catalog (IGC 9.9 million genes from 1267 individual fecal samples) together with the Homo sapiens database: the classical single-step interrogation strategy and two iterative strategies (in either two or three steps) aimed at preselecting a reduced-sized, more targeted search space for the final peptide spectrum matching. Both iterative searches outperformed the single-step classical search in terms of the number of peptides and protein clusters identified and the depth of taxonomic and functional knowledge, and this was the most convincing with the three-step approach. However, iterative searches do not help in reducing variability of repeated analyses, which is inherent to the traditional data-dependent acquisition mode, but this variability did not affect the hierarchical relationship between replicates and all other samples.

Synergistic convergence of microbiota-specific systemic IgG and secretory IgA.

BACKGROUND: Commensals induce local IgA responses essential to the induction of tolerance to gut microbiota, but it remains unclear whether antimicrobiota responses remain confined to the gut. OBJECTIVE: The aim of this study was to investigate systemic and intestinal responses against the whole microbiota under homeostatic conditions and in the absence of IgA. METHODS: We analyzed blood and feces from healthy donors, patients with selective IgA deficiency (SIgAd), and patients with common variable immunodeficiency (CVID). Immunoglobulin-coated bacterial repertoires were analyzed by using combined bacterial fluorescence-activated cell sorting and 16S rRNA sequencing. Bacterial lysates were probed by using Western blot analysis with healthy donor sera. RESULTS: Although absent from the healthy gut, serum antimicrobiota IgG are present in healthy subjects and increased in patients with SIgAd. IgG converges with nonoverlapping secretory IgA specificities to target the same bacteria. Each individual subject targets a diverse microbiota repertoire with a proportion that correlates inversely with systemic inflammation. Finally, intravenous immunoglobulin preparations target CVID gut microbiota much less efficiently than healthy microbiota. CONCLUSION: Secretory IgA and systemic IgG converge to target gut microbiota at the cellular level. SIgAd-associated inflammation is inversely correlated with systemic anticommensal IgG responses, which might serve as a second line of defense. We speculate that patients with SIgAd could benefit from oral IgA supplementation. Our data also suggest that intravenous immunoglobulin preparations can be supplemented with IgG from IgA-deficient patient pools to offer better protection against gut bacterial translocations in patients with CVID.

Quality control of microbiota metagenomics by k-mer analysis.

BACKGROUND: The biological and clinical consequences of the tight interactions between host and microbiota are rapidly being unraveled by next generation sequencing technologies and sophisticated bioinformatics, also referred to as microbiota metagenomics. The recent success of metagenomics has created a demand to rapidly apply the technology to large case-control cohort studies and to studies of microbiota from various habitats, including habitats relatively poor in microbes. It is therefore of foremost importance to enable a robust and rapid quality assessment of metagenomic data from samples that challenge present technological limits (sample numbers and size). Here we demonstrate that the distribution of overlapping k-mers of metagenome sequence data predicts sequence quality as defined by gene distribution and efficiency of sequence mapping to a reference gene catalogue. RESULTS: We used serial dilutions of gut microbiota metagenomic datasets to generate well-defined high to low quality metagenomes. We also analyzed a collection of 52 microbiota-derived metagenomes. We demonstrate that k-mer distributions of metagenomic sequence data identify sequence contaminations, such as sequences derived from "empty" ligation products. Of note, k-mer distributions were also able to predict the frequency of sequences mapping to a reference gene catalogue not only for the well-defined serial dilution datasets, but also for 52 human gut microbiota derived metagenomic datasets. CONCLUSIONS: We propose that k-mer analysis of raw metagenome sequence reads should be implemented as a first quality assessment prior to more extensive bioinformatics analysis, such as sequence filtering and gene mapping. With the rising demand for metagenomic analysis of microbiota it is crucial to provide tools for rapid and efficient decision making. This will eventually lead to a faster turn-around time, improved analytical quality including sample quality metrics and a significant cost reduction. Finally, improved quality assessment will have a major impact on the robustness of biological and clinical conclusions drawn from metagenomic studies.

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.

Faecalibacterium duncaniae A2-165 regulates the expression of butyrate synthesis, ferrous iron uptake, and stress-response genes based on acetate consumption.

The promising next-generation probiotic Faecalibacterium prausnitzii is one of the most abundant acetate-consuming, butyrate-producing bacteria in the healthy human gut. Yet, little is known about how acetate availability affects this bacterium's gene expression strategies. Here, we investigated the effect of acetate on temporal changes in the transcriptome of F. duncaniae A2-165 cultures using RNA sequencing. We compared gene expression patterns between two growth phases (early stationary vs. late exponential) and two acetate levels (low: 3 mM vs. high: 23 mM). Only in low-acetate conditions, a general stress response was activated. In high-acetate conditions, there was greater expression of genes related to butyrate synthesis and to the importation of B vitamins and iron. Specifically, expression was strongly activated in the case of the feoAABC operon, which encodes a FeoB ferrous iron transporter, but not in the case of the feoAB gene, which encodes a second putative FeoAB transporter. Moreover, excess ferrous iron repressed feoB expression but not feoAB. Lastly, FeoB but not FeoAB peptides from strain A2-165 were found in abundance in a healthy human fecal metaproteome. In conclusion, we characterized two early-stationary transcriptomes based on acetate consumption and this work highlights the regulation of feoB expression in F. duncaniae A2-165.

Exploring the hemicellulolytic properties and safety of Bacillus paralicheniformis as stepping stone in the use of new fibrolytic beneficial microbes.

Bacillus strains from the Moroccan Coordinated Collections of Microorganisms (CCMM) were characterised and tested for fibrolytic function and safety properties that would be beneficial for maintaining intestinal homeostasis, and recommend beneficial microbes in the field of health promotion research. Forty strains were investigated for their fibrolytic activities towards complex purified polysaccharides and natural fibres representative of dietary fibres (DFs) entering the colon for digestion. We demonstrated hemicellulolytic activities for nine strains of Bacillus aerius, re-identified as Bacillus paralicheniformis and Bacillus licheniformis, using xylan, xyloglucan or lichenan as purified polysaccharides, and orange, apple and carrot natural fibres, with strain- and substrate-dependent production of glycoside hydrolases (GHs). Our combined methods, based on enzymatic assays, secretome, and genome analyses, highlighted the hemicellulolytic activities of B. paralicheniformis and the secretion of specific glycoside hydrolases, in particular xylanases, compared to B. licheniformis. Genomic features of these strains revealed a complete set of GH genes dedicated to the degradation of various polysaccharides from DFs, including cellulose, hemicellulose and pectin, which may confer on the strains the ability to digest a variety of DFs. Preliminary experiments on the safety and immunomodulatory properties of B. paralicheniformis fibrolytic strains were evaluated in light of applications as beneficial microbes' candidates for health improvement. B. paralicheniformis CCMM B969 was therefore proposed as a new fibrolytic beneficial microbe candidate.

Modern Metaproteomics: A Unique Tool to Characterize the Active Microbiome in Health and Diseases, and Pave the Road towards New Biomarkers-Example of Crohn's Disease and Ulcerative Colitis Flare-Ups.

Thanks to the latest developments in mass spectrometry, software and standards, metaproteomics is emerging as the vital complement of metagenomics, to make headway in understanding the actual functioning of living and active microbial communities. Modern metaproteomics offers new possibilities in the area of clinical diagnosis. This is illustrated here, for the still highly challenging diagnosis of intestinal bowel diseases (IBDs). Using bottom-up proteomics, we analyzed the gut metaproteomes of the same twenty faecal specimens processed either fresh or after a two-month freezing period. We focused on metaproteomes of microbial cell envelopes since it is an outstanding way of capturing host and host-microbe interaction signals. The protein profiles of pairs of fresh and frozen-thawed samples were closely related, making feasible deferred analysis in a distant diagnosis centre. The taxonomic and functional landscape of microbes in diverse IBD phenotypes-active ulcerative colitis, or active Crohn's disease either with ileo-colonic or exclusive colonic localization-differed from each other and from the controls. Based on their specific peptides, we could identify proteins that were either strictly overrepresented or underrepresented in all samples of one clinical group compared to all samples of another group, paving the road for promising additional diagnostic tool for IBDs.

A combined test for feature selection on sparse metaproteomics data-an alternative to missing value imputation.

One of the difficulties encountered in the statistical analysis of metaproteomics data is the high proportion of missing values, which are usually treated by imputation. Nevertheless, imputation methods are based on restrictive assumptions regarding missingness mechanisms, namely "at random" or "not at random". To circumvent these limitations in the context of feature selection in a multi-class comparison, we propose a univariate selection method that combines a test of association between missingness and classes, and a test for difference of observed intensities between classes. This approach implicitly handles both missingness mechanisms. We performed a quantitative and qualitative comparison of our procedure with imputation-based feature selection methods on two experimental data sets, as well as simulated data with various scenarios regarding the missingness mechanisms and the nature of the difference of expression (differential intensity or differential presence). Whereas we observed similar performances in terms of prediction on the experimental data set, the feature ranking and selection from various imputation-based methods were strongly divergent. We showed that the combined test reaches a compromise by correlating reasonably with other methods, and remains efficient in all simulated scenarios unlike imputation-based feature selection methods.

An iterative workflow for mining the human intestinal metaproteome.

BACKGROUND: Peptide spectrum matching (PSM) is the standard method in shotgun proteomics data analysis. It relies on the availability of an accurate and complete sample proteome that is used to make interpretation of the spectra feasible. Although this procedure has proven to be effective in many proteomics studies, the approach has limitations when applied on complex samples of microbial communities, such as those found in the human intestinal tract. Metagenome studies have indicated that the human intestinal microbiome contains over 100 times more genes than the human genome and it has been estimated that this ecosystem contains over 5000 bacterial species. The genomes of the vast majority of these species have not yet been sequenced and hence their proteomes remain unknown. To enable data analysis of shotgun proteomics data using PSM, and circumvent the lack of a defined matched metaproteome, an iterative workflow was developed that is based on a synthetic metaproteome and the developing metagenomic databases that are both representative for but not necessarily originating from the sample of interest. RESULTS: Two human fecal samples for which metagenomic data had been collected, were analyzed for their metaproteome using liquid chromatography-mass spectrometry and used to benchmark the developed iterative workflow to other methods. The results show that the developed method is able to detect over 3,000 peptides per fecal sample from the spectral data by circumventing the lack of a defined proteome without naive translation of matched metagenomes and cross-species peptide identification. CONCLUSIONS: The developed iterative workflow achieved an approximate two-fold increase in the amount of identified spectra at a false discovery rate of 1% and can be applied in metaproteomic studies of the human intestinal tract or other complex ecosystems.

Cholesterol-to-Coprostanol Conversion by the Gut Microbiota: What We Know, Suspect, and Ignore.

Every day, up to 1 g of cholesterol, composed of the unabsorbed dietary cholesterol, the biliary cholesterol secretion, and cholesterol of cells sloughed from the intestinal epithelium, enters the colon. All cholesterol arriving in the large intestine can be metabolized by the colonic bacteria. Cholesterol is mainly converted into coprostanol, a non-absorbable sterol that is excreted in the feces. Interestingly, cholesterol-to-coprostanol conversion in human populations is variable, with a majority of high converters and a minority of low or inefficient converters. Two major pathways have been proposed, one involving the direct stereospecific reduction of the Δ5 double bond direct while the indirect pathway involves the intermediate formation of 4-cholelesten-3-one and coprostanone. Despite the fact that intestinal cholesterol conversion was discovered more than a century ago, only a few cholesterol-to-coprostanol-converting bacterial strains have been isolated and characterized. Moreover, the responsible genes were mainly unknown until recently. Interestingly, cholesterol-to-coprostanol conversion is highly regulated by the diet. Finally, this gut bacterial metabolism has been linked to health and disease, and recent evidence suggests it could contribute to lower blood cholesterol and cardiovascular risks.

Perturbed Microbiota/Immune Homeostasis in Multiple Sclerosis.

OBJECTIVE: Based on animal models and human studies, there is now strong suspicion that host/microbiota mutualism in the context of gut microbial dysbiosis could influence immunity and multiple sclerosis (MS) evolution. Our goal was to seek evidence of deregulated microbiota-induced systemic immune responses in patients with MS. METHODS: We investigated gut and systemic commensal-specific antibody responses in healthy controls (n = 32), patients with relapsing-remitting MS (n = 30), and individuals with clinically isolated syndromes (CISs) (n = 15). Gut microbiota composition and diversity were compared between controls and patients by analysis of 16S ribosomal ribonucleic acid (rRNA) sequencing. Autologous microbiota and cultivable bacterial strains were used in bacterial flow cytometry assays to quantify autologous serum IgG and secretory IgA responses to microbiota. IgG-bound bacteria were sorted by flow cytometry and identified using 16S rRNA sequencing. RESULTS: We show that commensal-specific gut IgA responses are drastically reduced in patients with severe MS, disease severity being correlated with the IgA-coated fecal microbiota fraction (r = -0.647, p < 0.0001). At the same time, IgA-unbound bacteria elicit qualitatively broad and quantitatively increased serum IgG responses in patients with MS and CIS compared with controls (4.1% and 2.5% vs 1.9%, respectively, p < 0.001). CONCLUSIONS: Gut and systemic microbiota/immune homeostasis are perturbed in MS. Our results argue that defective IgA responses in MS are linked to a breakdown of systemic tolerance to gut microbiota leading to an enhanced triggering of systemic IgG immunity against gut commensals occurring early in MS.

High engraftment capacity of frozen ready-to-use human fecal microbiota transplants assessed in germ-free mice.

The number of indications for fecal microbiota transplantation is expected to rise, thus increasing the needs for production of readily available frozen or freeze-dried transplants. Using shotgun metagenomics, we investigated the capacity of two novel human fecal microbiota transplants prepared in maltodextrin-trehalose solutions (abbreviated MD and TR for maltodextrin:trehalose, 3:1, w/w, and trehalose:maltodextrin 3:1, w/w, respectively), to colonize a germ-free born mouse model. Gavage with frozen-thawed MD or TR suspensions gave the taxonomic profiles of mouse feces that best resembled those obtained with the fresh inoculum (Spearman correlations based on relative abundances of metagenomic species around 0.80 and 0.75 for MD and TR respectively), while engraftment capacity of defrosted NaCl transplants most diverged (Spearman correlations around 0.63). Engraftment of members of the family Lachnospiraceae and Ruminoccocaceae was the most challenging in all groups of mice, being improved with MD and TR transplants compared to NaCl, but still lower than with the fresh preparation. Improvement of engraftment of this important group in maintaining health represents a challenge that could benefit from further research on fecal microbiota transplant manufacturing.

The Metaproteomics Initiative: a coordinated approach for propelling the functional characterization of microbiomes.

Through connecting genomic and metabolic information, metaproteomics is an essential approach for understanding how microbiomes function in space and time. The international metaproteomics community is delighted to announce the launch of the Metaproteomics Initiative (www.metaproteomics.org), the goal of which is to promote dissemination of metaproteomics fundamentals, advancements, and applications through collaborative networking in microbiome research. The Initiative aims to be the central information hub and open meeting place where newcomers and experts interact to communicate, standardize, and accelerate experimental and bioinformatic methodologies in this field. We invite the entire microbiome community to join and discuss potential synergies at the interfaces with other disciplines, and to collectively promote innovative approaches to gain deeper insights into microbiome functions and dynamics. Video Abstract.

Critical Assessment of MetaProteome Investigation (CAMPI): a multi-laboratory comparison of established workflows.

Metaproteomics has matured into a powerful tool to assess functional interactions in microbial communities. While many metaproteomic workflows are available, the impact of method choice on results remains unclear. Here, we carry out a community-driven, multi-laboratory comparison in metaproteomics: the critical assessment of metaproteome investigation study (CAMPI). Based on well-established workflows, we evaluate the effect of sample preparation, mass spectrometry, and bioinformatic analysis using two samples: a simplified, laboratory-assembled human intestinal model and a human fecal sample. We observe that variability at the peptide level is predominantly due to sample processing workflows, with a smaller contribution of bioinformatic pipelines. These peptide-level differences largely disappear at the protein group level. While differences are observed for predicted community composition, similar functional profiles are obtained across workflows. CAMPI demonstrates the robustness of present-day metaproteomics research, serves as a template for multi-laboratory studies in metaproteomics, and provides publicly available data sets for benchmarking future developments.

Human IgA binds a diverse array of commensal bacteria.

In humans, several grams of IgA are secreted every day in the intestinal lumen. While only one IgA isotype exists in mice, humans secrete IgA1 and IgA2, whose respective relations with the microbiota remain elusive. We compared the binding patterns of both polyclonal IgA subclasses to commensals and glycan arrays and determined the reactivity profile of native human monoclonal IgA antibodies. While most commensals are dually targeted by IgA1 and IgA2 in the small intestine, IgA1+IgA2+ and IgA1-IgA2+ bacteria coexist in the colon lumen, where Bacteroidetes is preferentially targeted by IgA2. We also observed that galactose-α terminated glycans are almost exclusively recognized by IgA2. Although bearing signs of affinity maturation, gut-derived IgA monoclonal antibodies are cross-reactive in the sense that they bind to multiple bacterial targets. Private anticarbohydrate-binding patterns, observed at clonal level as well, could explain these apparently opposing features of IgA, being at the same time cross-reactive and selective in its interactions with the microbiota.

Metabolite analysis of human fecal water by gas chromatography/mass spectrometry with ethyl chloroformate derivatization.

Fecal water is a complex mixture of various metabolites with a wide range of physicochemical properties and boiling points. The analytical method developed here provides a qualitative and quantitative gas chromatography/mass spectrometry (GC/MS) analysis, with high sensitivity and efficiency, coupled with derivatization of ethyl chloroformate in aqueous medium. The water/ethanol/pyridine ratio was optimized to 12:6:1, and a two-step derivatization with an initial pH regulation of 0.1M sodium bicarbonate was developed. The deionized water exhibited better extraction efficiency for fecal water compounds than did acidified and alkalized water. Furthermore, more amino acids were extracted from frozen fecal samples than from fresh samples based on multivariate statistical analysis and univariate statistical validation on GC/MS data. Method validation by 34 reference standards and fecal water samples showed a correlation coefficient higher than 0.99 for each of the standards, and the limit of detection (LOD) was from 10 to 500pg on-column for most of the standards. The analytical equipment exhibited excellent repeatability, with the relative standard deviation (RSD) lower than 4% for standards and lower than 7% for fecal water. The derivatization method also demonstrated good repeatability, with the RSD lower than 6.4% for standards (except 3,4-dihydroxyphenylacetic acid) and lower than 10% for fecal water (except dicarboxylic acids). The qualitative means by searching the electron impact (EI) mass spectral database, chemical ionization (CI) mass spectra validation, and reference standards comparison totally identified and structurally confirmed 73 compounds, and the fecal water compounds of healthy humans were also quantified. This protocol shows a promising application in metabolome analysis based on human fecal water samples.

A Guide for Ex Vivo Handling and Storage of Stool Samples Intended for Fecal Microbiota Transplantation.

Owing to the growing recognition of the gut microbiota as a main partner of human health, we are expecting that the number of indications for fecal microbiota transplantation (FMT) will increase. Thus, there is an urgent need for standardization of the entire process of fecal transplant production. This study provides a complete standardized procedure to prepare and store live and ready-to-use transplants that meet the standard requirements of good practices to applied use in pharmaceutical industry. We show that, if time before transformation to transplants would exceed 24 hours, fresh samples should not be exposed to temperatures above 20 °C, and refrigeration at 4 °C can be a safe solution. Oxygen-free atmosphere was not necessary and simply removing air above collected samples was sufficient to preserve viability. Transplants prepared in maltodextrin-trehalose solutions, stored in a -80 °C standard freezer and then rapidly thawed at 37 °C, retained the best revivification potential as  proven by 16S rRNA profiles, metabolomic fingerprints, and flow cytometry assays over a 3-month observation period. Maltodextrin-trehalose containing cryoprotectants were also efficient in preserving viability of lyophilized transplants, either in their crude or purified form, an option that can be attractive for fecal transplant biobanking and oral formulation.

A Data Integration Multi-Omics Approach to Study Calorie Restriction-Induced Changes in Insulin Sensitivity.

Background: The mechanisms responsible for calorie restriction (CR)-induced improvement in insulin sensitivity (IS) have not been fully elucidated. Greater insight can be achieved through deep biological phenotyping of subjects undergoing CR, and integration of big data. Materials and Methods: An integrative approach was applied to investigate associations between change in IS and factors from host, microbiota, and lifestyle after a 6-week CR period in 27 overweight or obese adults (ClinicalTrials.gov: NCT01314690). Partial least squares regression was used to determine associations of change (week 6 - baseline) between IS markers and lifestyle factors (diet and physical activity), subcutaneous adipose tissue (sAT) gene expression, metabolomics of serum, urine and feces, and gut microbiota composition. ScaleNet, a network learning approach based on spectral consensus strategy (SCS, developed by us) was used for reconstruction of biological networks. Results: A spectrum of variables from lifestyle factors (10 nutrients), gut microbiota (10 metagenomics species), and host multi-omics (metabolic features: 84 from serum, 73 from urine, and 131 from feces; and 257 sAT gene probes) most associated with IS were identified. Biological network reconstruction using SCS, highlighted links between changes in IS, serum branched chain amino acids, sAT genes involved in endoplasmic reticulum stress and ubiquitination, and gut metagenomic species (MGS). Linear regression analysis to model how changes of select variables over the CR period contribute to changes in IS, showed greatest contributions from gut MGS and fiber intake. Conclusion: This work has enhanced previous knowledge on links between host glucose homeostasis, lifestyle factors and the gut microbiota, and has identified potential biomarkers that may be used in future studies to predict and improve individual response to weight-loss interventions. Furthermore, this is the first study showing integration of the wide range of data presented herein, identifying 115 variables of interest with respect to IS from the initial input, consisting of 9,986 variables. Clinical Trial Registration: clinicaltrials.gov (NCT01314690).

Microbial ecology perturbation in human IgA deficiency.

Paradoxically, loss of immunoglobulin A (IgA), one of the most abundant antibodies, does not irrevocably lead to severe infections in humans but rather is associated with relatively mild respiratory infections, atopy, and autoimmunity. IgA might therefore also play covert roles, not uniquely associated with control of pathogens. We show that human IgA deficiency is not associated with massive quantitative perturbations of gut microbial ecology. Metagenomic analysis highlights an expected pathobiont expansion but a less expected depletion in some typically beneficial symbionts. Gut colonization by species usually present in the oropharynx is also reminiscent of spatial microbiota disorganization. IgM only partially rescues IgA deficiency because not all typical IgA targets are efficiently bound by IgM in the intestinal lumen. Together, IgA appears to play a nonredundant role at the forefront of the immune/microbial interface, away from the intestinal barrier, ranging from pathobiont control and regulation of systemic inflammation to preservation of commensal diversity and community networks.