Global compositional and functional states of the human gut microbiome in health and disease.

The human gut microbiota is of increasing interest, with metagenomics a key tool for analyzing bacterial diversity and functionality in health and disease. Despite increasing efforts to expand microbial gene catalogs and an increasing number of metagenome-assembled genomes, there have been few pan-metagenomic association studies and in-depth functional analyses across different geographies and diseases. Here, we explored 6014 human gut metagenome samples across 19 countries and 23 diseases by performing compositional, functional cluster, and integrative analyses. Using interpreted machine learning classification models and statistical methods, we identified Fusobacterium nucleatum and Anaerostipes hadrus with the highest frequencies, enriched and depleted, respectively, across different disease cohorts. Distinct functional distributions were observed in the gut microbiomes of both westernized and nonwesternized populations. These compositional and functional analyses are presented in the open-access Human Gut Microbiome Atlas, allowing for the exploration of the richness, disease, and regional signatures of the gut microbiota across different cohorts.

Cross talk between Paneth and tuft cells drives dysbiosis and inflammation in the gut mucosa.

Gut microbiota imbalance (dysbiosis) is increasingly associated with pathological conditions, both within and outside the gastrointestinal tract. Intestinal Paneth cells are considered to be guardians of the gut microbiota, but the events linking Paneth cell dysfunction with dysbiosis remain unclear. We report a three-step mechanism for dysbiosis initiation. Initial alterations in Paneth cells, as frequently observed in obese and inflammatorybowel diseases patients, cause a mild remodeling of microbiota, with amplification of succinate-producing species. SucnR1-dependent activation of epithelial tuft cells triggers a type 2 immune response that, in turn, aggravates the Paneth cell defaults, promoting dysbiosis and chronic inflammation. We thus reveal a function of tuft cells in promoting dysbiosis following Paneth cell deficiency and an unappreciated essential role of Paneth cells in maintaining a balanced microbiota to prevent inappropriate activation of tuft cells and deleterious dysbiosis. This succinate-tuft cell inflammation circuit may also contribute to the chronic dysbiosis observed in patients.

Three transmission events of Vibrio cholerae O1 into Lusaka, Zambia.

BACKGROUND: Cholera has been present and recurring in Zambia since 1977. However, there is a paucity of data on genetic relatedness and diversity of the Vibrio cholerae isolates responsible for these outbreaks. Understanding whether the outbreaks are seeded from existing local isolates or if the outbreaks represent separate transmission events can inform public health decisions. RESULTS: Seventy-two V. cholerae isolates from outbreaks in 2009/2010, 2016, and 2017/2018 in Zambia were characterized using multilocus variable number tandem repeat analysis (MLVA) and whole genome sequencing (WGS). The isolates had eight distinct MLVA genotypes that clustered into three MLVA clonal complexes (CCs). Each CC contained isolates from only one outbreak. The results from WGS revealed both clustered and dispersed single nucleotide variants. The genetic relatedness of isolates based on WGS was consistent with the MLVA, each CC was a distinct genetic lineage and had nearest neighbors from other East African countries. In Lusaka, isolates from the same outbreak were more closely related to themselves and isolates from other countries than to isolates from other outbreaks in other years. CONCLUSIONS: Our observations are consistent with i) the presence of random mutation and alternative mechanisms of nucleotide variation, and ii) three separate transmission events of V. cholerae into Lusaka, Zambia. We suggest that locally, case-area targeted invention strategies and regionally, well-coordinated plans be in place to effectively control future cholera outbreaks.

MSPminer: abundance-based reconstitution of microbial pan-genomes from shotgun metagenomic data.

MOTIVATION: Analysis toolkits for shotgun metagenomic data achieve strain-level characterization of complex microbial communities by capturing intra-species gene content variation. Yet, these tools are hampered by the extent of reference genomes that are far from covering all microbial variability, as many species are still not sequenced or have only few strains available. Binning co-abundant genes obtained from de novo assembly is a powerful reference-free technique to discover and reconstitute gene repertoire of microbial species. While current methods accurately identify species core parts, they miss many accessory genes or split them into small gene groups that remain unassociated to core clusters. RESULTS: We introduce MSPminer, a computationally efficient software tool that reconstitutes Metagenomic Species Pan-genomes (MSPs) by binning co-abundant genes across metagenomic samples. MSPminer relies on a new robust measure of proportionality coupled with an empirical classifier to group and distinguish not only species core genes but accessory genes also. Applied to a large scale metagenomic dataset, MSPminer successfully delineates in a few hours the gene repertoires of 1661 microbial species with similar specificity and higher sensitivity than existing tools. The taxonomic annotation of MSPs reveals microorganisms hitherto unknown and brings coherence in the nomenclature of the species of the human gut microbiota. The provided MSPs can be readily used for taxonomic profiling and biomarkers discovery in human gut metagenomic samples. In addition, MSPminer can be applied on gene count tables from other ecosystems to perform similar analyses. AVAILABILITY AND IMPLEMENTATION: The binary is freely available for non-commercial users at www.enterome.com/downloads. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Comparative methods for fecal sample storage to preserve gut microbial structure and function in an in vitro model of the human colon.

In vitro gut models, such as the mucosal artificial colon (M-ARCOL), provide timely and cost-efficient alternatives to in vivo assays allowing mechanistic studies to better understand the role of human microbiome in health and disease. Using such models inoculated with human fecal samples may require a critical step of stool storage. The effects of preservation methods on microbial structure and function in in vitro gut models have been poorly investigated. This study aimed to assess the impact of three commonly used preserving methods, compared with fresh fecal samples used as a control, on the kinetics of lumen and mucus-associated microbiota colonization in the M-ARCOL model. Feces from two healthy donors were frozen 48 h at - 80 °C with or without cryoprotectant (10% glycerol) or lyophilized with maltodextrin and trehalose prior to inoculation of four parallel bioreactors (e.g., fresh stool, raw stool stored at - 80 °C, stool stored at - 80 °C with glycerol and lyophilized stool). Microbiota composition and diversity (qPCR and 16S metabarcoding) as well as metabolic activity (gases and short chain fatty acids) were monitored throughout the fermentation process (9 days). All the preservative treatments allowed the maintaining inside the M-ARCOL of a complex and functional microbiota, but considering stabilization time of microbial profiles and activities (and not technical constraints associated with the supply of frozen material), our results highlighted 48 h freezing at - 80 °C without cryoprotectant as the most efficient method. These results will help scientists to determine the most accurate method for fecal storage prior to inoculation of in vitro gut microbiome models. KEY POINTS: • In vitro ARCOL model reproduces luminal and mucosal human microbiome. • Short-term storage of fecal sample influences microbial stabilization and activity. • 48 h freezing at - 80°C: most efficient method to preserve microbial ecosystem. • Scientific and technical requirements: influencers of preservation method.

Dietary intervention impact on gut microbial gene richness.

Complex gene-environment interactions are considered important in the development of obesity. The composition of the gut microbiota can determine the efficacy of energy harvest from food and changes in dietary composition have been associated with changes in the composition of gut microbial populations. The capacity to explore microbiota composition was markedly improved by the development of metagenomic approaches, which have already allowed production of the first human gut microbial gene catalogue and stratifying individuals by their gut genomic profile into different enterotypes, but the analyses were carried out mainly in non-intervention settings. To investigate the temporal relationships between food intake, gut microbiota and metabolic and inflammatory phenotypes, we conducted diet-induced weight-loss and weight-stabilization interventions in a study sample of 38 obese and 11 overweight individuals. Here we report that individuals with reduced microbial gene richness (40%) present more pronounced dys-metabolism and low-grade inflammation, as observed concomitantly in the accompanying paper. Dietary intervention improves low gene richness and clinical phenotypes, but seems to be less efficient for inflammation variables in individuals with lower gene richness. Low gene richness may therefore have predictive potential for the efficacy of intervention.

Richness of human gut microbiome correlates with metabolic markers.

We are facing a global metabolic health crisis provoked by an obesity epidemic. Here we report the human gut microbial composition in a population sample of 123 non-obese and 169 obese Danish individuals. We find two groups of individuals that differ by the number of gut microbial genes and thus gut bacterial richness. They contain known and previously unknown bacterial species at different proportions; individuals with a low bacterial richness (23% of the population) are characterized by more marked overall adiposity, insulin resistance and dyslipidaemia and a more pronounced inflammatory phenotype when compared with high bacterial richness individuals. The obese individuals among the lower bacterial richness group also gain more weight over time. Only a few bacterial species are sufficient to distinguish between individuals with high and low bacterial richness, and even between lean and obese participants. Our classifications based on variation in the gut microbiome identify subsets of individuals in the general white adult population who may be at increased risk of progressing to adiposity-associated co-morbidities.

Direct Detection of Shigella in Stool Specimens by Use of a Metagenomic Approach.

The underestimation of Shigella species as a cause of childhood diarrhea disease has become increasingly apparent with quantitative PCR (qPCR)-based diagnostic methods versus culture. We sought to confirm qPCR-based detection of Shigella via a metagenomics approach. Three groups of samples were selected from diarrheal cases from the Global Enteric Multicenter Study: nine Shigella culture-positive and qPCR-positive (culture+ qPCR+) samples, nine culture-negative but qPCR-positive (culture- qPCR+) samples, and nine culture-negative and qPCR-negative (culture- qPCR-) samples. Fecal DNA was sequenced using paired-end Illumina HiSeq, whereby 3.26 × 108 ± 5.6 × 107 high-quality reads were generated for each sample. We used Kraken software to compare the read counts specific to "Shigella" among the three groups. The proportions of Shigella-specific nonhuman sequence reads between culture+ qPCR+ (0.65 ± 0.42%) and culture- qPCR+ (0.55 ± 0.31%) samples were similar (Mann-Whitney U test, P = 0.627) and distinct from the culture- qPCR- group (0.17 ± 0.15%, P < 0.05). The read counts of sequences previously targeted by Shigella/enteroinvasive Escherichia coli (EIEC) qPCR assays, namely, ipaH, virA, virG, ial, ShET2, and ipaH3, were also similar between the culture+ qPCR+ and culture- qPCR+ groups and distinct from the culture- qPCR- groups (P < 0.001). Kraken performed well versus other methods: its precision and recall of Shigella were excellent at the genus level but variable at the species level. In summary, metagenomic sequencing indicates that Shigella/EIEC qPCR-positive samples are similar to those of Shigella culture-positive samples in Shigella sequence composition, thus supporting qPCR as an accurate method for detecting Shigella.

A metagenome-wide association study of gut microbiota in type 2 diabetes.

Assessment and characterization of gut microbiota has become a major research area in human disease, including type 2 diabetes, the most prevalent endocrine disease worldwide. To carry out analysis on gut microbial content in patients with type 2 diabetes, we developed a protocol for a metagenome-wide association study (MGWAS) and undertook a two-stage MGWAS based on deep shotgun sequencing of the gut microbial DNA from 345 Chinese individuals. We identified and validated approximately 60,000 type-2-diabetes-associated markers and established the concept of a metagenomic linkage group, enabling taxonomic species-level analyses. MGWAS analysis showed that patients with type 2 diabetes were characterized by a moderate degree of gut microbial dysbiosis, a decrease in the abundance of some universal butyrate-producing bacteria and an increase in various opportunistic pathogens, as well as an enrichment of other microbial functions conferring sulphate reduction and oxidative stress resistance. An analysis of 23 additional individuals demonstrated that these gut microbial markers might be useful for classifying type 2 diabetes.

Genetic relatedness of Vibrio cholerae isolates within and between households during outbreaks in Dhaka, Bangladesh.

BACKGROUND: Household contacts of cholera patients have a 100 times higher risk of developing a cholera infection than the general population. To compare the genetic relatedness of clinical and water source Vibrio cholerae isolates from cholera patients' households across three outbreaks, we analyzed these isolates using whole-genome-sequencing (WGS) and multilocus variable-number tandem-repeat analysis (MLVA). RESULTS: The WGS analyses revealed that 80% of households had source water isolates that were more closely related to clinical isolates from the same household than to any other isolates. While in another 20% of households an isolate from a person was more closely related to clinical isolates from another household than to source water isolates from their own household. The mean pairwise differences in single nucleotide-variant (SNV) counts for isolates from the same household were significantly lower than those for different households (2.4 vs. 7.7 p < 0.0001), and isolates from the same outbreak had significantly fewer mean pairwise differences compared to isolates from different outbreaks (mean: 6.2 vs. 8.0, p < 0.0001). Based on MLVA in outbreak 1, we observed that the majority of households had clinical isolates with MLVA genotypes related to other clinical isolates and unrelated to water source isolates from the same household. While in outbreak 3, there were different MLVA genotypes between households, however within the majority of households, the clinical and water source isolates had the same MLVA genotypes. The beginning of outbreak 2 resembled outbreak 1 and the latter part resembled outbreak 3. We validated our use of MLVA by comparing it to WGS. Isolates with the identical MLVA genotype had significantly fewer mean pairwise SNV differences than those isolates with different MLVA genotypes (mean: 4.8 vs. 7.7, p < 0.0001). Furthermore, consistent with WGS results, the number of pairwise differences in the five MLVA loci for isolates within the same household was significantly lower than isolates from different households (mean: 1.6 vs. 3.0, p < 0.0001). CONCLUSION: These results suggest that transmission patterns for cholera are a combination of person-to-person and water-to-person cholera transmission with the proportions of the two modes varying within and between outbreaks.

Enterotypes of the human gut microbiome.

Our knowledge of species and functional composition of the human gut microbiome is rapidly increasing, but it is still based on very few cohorts and little is known about variation across the world. By combining 22 newly sequenced faecal metagenomes of individuals from four countries with previously published data sets, here we identify three robust clusters (referred to as enterotypes hereafter) that are not nation or continent specific. We also confirmed the enterotypes in two published, larger cohorts, indicating that intestinal microbiota variation is generally stratified, not continuous. This indicates further the existence of a limited number of well-balanced host-microbial symbiotic states that might respond differently to diet and drug intake. The enterotypes are mostly driven by species composition, but abundant molecular functions are not necessarily provided by abundant species, highlighting the importance of a functional analysis to understand microbial communities. Although individual host properties such as body mass index, age, or gender cannot explain the observed enterotypes, data-driven marker genes or functional modules can be identified for each of these host properties. For example, twelve genes significantly correlate with age and three functional modules with the body mass index, hinting at a diagnostic potential of microbial markers.

Construction of a dairy microbial genome catalog opens new perspectives for the metagenomic analysis of dairy fermented products.

BACKGROUND: Microbial communities of traditional cheeses are complex and insufficiently characterized. The origin, safety and functional role in cheese making of these microbial communities are still not well understood. Metagenomic analysis of these communities by high throughput shotgun sequencing is a promising approach to characterize their genomic and functional profiles. Such analyses, however, critically depend on the availability of appropriate reference genome databases against which the sequencing reads can be aligned. RESULTS: We built a reference genome catalog suitable for short read metagenomic analysis using a low-cost sequencing strategy. We selected 142 bacteria isolated from dairy products belonging to 137 different species and 67 genera, and succeeded to reconstruct the draft genome of 117 of them at a standard or high quality level, including isolates from the genera Kluyvera, Luteococcus and Marinilactibacillus, still missing from public database. To demonstrate the potential of this catalog, we analysed the microbial composition of the surface of two smear cheeses and one blue-veined cheese, and showed that a significant part of the microbiota of these traditional cheeses was composed of microorganisms newly sequenced in our study. CONCLUSIONS: Our study provides data, which combined with publicly available genome references, represents the most expansive catalog to date of cheese-associated bacteria. Using this extended dairy catalog, we revealed the presence in traditional cheese of dominant microorganisms not deliberately inoculated, mainly Gram-negative genera such as Pseudoalteromonas haloplanktis or Psychrobacter immobilis, that may contribute to the characteristics of cheese produced through traditional methods.

MetaCompass: Reference-guided Assembly of Metagenomes.

Metagenomic studies have primarily relied on de novo assembly for reconstructing genes and genomes from microbial mixtures. While reference-guided approaches have been employed in the assembly of single organisms, they have not been used in a metagenomic context. Here we describe the first effective approach for reference-guided metagenomic assembly that can complement and improve upon de novo metagenomic assembly methods for certain organisms. Such approaches will be increasingly useful as more genomes are sequenced and made publicly available.

Privacy-Preserving Federated Survival Support Vector Machines for Cross-Institutional Time-To-Event Analysis: Algorithm Development and Validation.

BACKGROUND: Central collection of distributed medical patient data is problematic due to strict privacy regulations. Especially in clinical environments, such as clinical time-to-event studies, large sample sizes are critical but usually not available at a single institution. It has been shown recently that federated learning, combined with privacy-enhancing technologies, is an excellent and privacy-preserving alternative to data sharing. OBJECTIVE: This study aims to develop and validate a privacy-preserving, federated survival support vector machine (SVM) and make it accessible for researchers to perform cross-institutional time-to-event analyses. METHODS: We extended the survival SVM algorithm to be applicable in federated environments. We further implemented it as a FeatureCloud app, enabling it to run in the federated infrastructure provided by the FeatureCloud platform. Finally, we evaluated our algorithm on 3 benchmark data sets, a large sample size synthetic data set, and a real-world microbiome data set and compared the results to the corresponding central method. RESULTS: Our federated survival SVM produces highly similar results to the centralized model on all data sets. The maximal difference between the model weights of the central model and the federated model was only 0.001, and the mean difference over all data sets was 0.0002. We further show that by including more data in the analysis through federated learning, predictions are more accurate even in the presence of site-dependent batch effects. CONCLUSIONS: The federated survival SVM extends the palette of federated time-to-event analysis methods by a robust machine learning approach. To our knowledge, the implemented FeatureCloud app is the first publicly available implementation of a federated survival SVM, is freely accessible for all kinds of researchers, and can be directly used within the FeatureCloud platform.

Transient colonizing microbes promote gut dysbiosis and functional impairment.

Species composition of the healthy adult gut microbiota tends to be stable over time. Destabilization of the gut microbiome under the influence of different factors is the main driver of the microbial dysbiosis and subsequent impacts on host physiology. Here, we used metagenomics data from a Swedish longitudinal cohort, to determine the stability of the gut microbiome and uncovered two distinct microbial species groups; persistent colonizing species (PCS) and transient colonizing species (TCS). We validated the continuation of this grouping, generating gut metagenomics data for additional time points from the same Swedish cohort. We evaluated the existence of PCS/TCS across different geographical regions and observed they are globally conserved features. To characterize PCS/TCS phenotypes, we performed bioreactor fermentation with faecal samples and metabolic modeling. Finally, using chronic disease gut metagenome and other multi-omics data, we identified roles of TCS in microbial dysbiosis and link with abnormal changes to host physiology.

In Vitro Modelling of Oral Microbial Invasion in the Human Colon.

Recent advances in the human microbiome characterization have revealed significant oral microbial detection in stools of dysbiotic patients. However, little is known about the potential interactions of these invasive oral microorganisms with commensal intestinal microbiota and the host. In this proof-of-concept study, we proposed a new model of oral-to-gut invasion by the combined use of an in vitro model simulating both the physicochemical and microbial (lumen- and mucus-associated microbes) parameters of the human colon (M-ARCOL), a salivary enrichment protocol, and whole-metagenome shotgun sequencing. Oral invasion of the intestinal microbiota was simulated by injection of enriched saliva in the in vitro colon model inoculated with a fecal sample from the same healthy adult donor. The mucosal compartment of M-ARCOL was able to retain the highest species richness levels over time, while species richness levels decreased in the luminal compartment. This study also showed that oral microorganisms preferably colonized the mucosal microenvironment, suggesting potential oral-to-intestinal mucosal competitions. This new model of oral-to-gut invasion can provide useful mechanistic insights into the role of oral microbiome in various disease processes. IMPORTANCE Here, we propose a new model of oral-to-gut invasion by the combined use of an in vitro model simulating both the physicochemical and microbial (lumen- and mucus-associated microbes) parameters of the human colon (M-ARCOL), a salivary enrichment protocol, and whole-metagenome shotgun sequencing. Our study revealed the importance of integrating the mucus compartment, which retained higher microbial richness during fermentation, showed the preference of oral microbial invaders for the mucosal resources, and indicated potential oral-to-intestinal mucosal competitions. It also underlined promising opportunities to further understand mechanisms of oral invasion into the human gut microbiome, define microbe-microbe and mucus-microbe interactions in a compartmentalized fashion, and help to better characterize the potential of oral microbial invasion and their persistence in the gut.

Evaluation of an Adapted Semi-Automated DNA Extraction for Human Salivary Shotgun Metagenomics.

Recent attention has highlighted the importance of oral microbiota in human health and disease, e.g., in Parkinson's disease, notably using shotgun metagenomics. One key aspect for efficient shotgun metagenomic analysis relies on optimal microbial sampling and DNA extraction, generally implementing commercial solutions developed to improve sample collection and preservation, and provide high DNA quality and quantity for downstream analysis. As metagenomic studies are today performed on a large number of samples, the next evolution to increase study throughput is with DNA extraction automation. In this study, we proposed a semi-automated DNA extraction protocol for human salivary samples collected with a commercial kit, and compared the outcomes with the DNA extraction recommended by the manufacturer. While similar DNA yields were observed between the protocols, our semi-automated DNA protocol generated significantly higher DNA fragment sizes. Moreover, we showed that the oral microbiome composition was equivalent between DNA extraction methods, even at the species level. This study demonstrates that our semi-automated protocol is suitable for shotgun metagenomic analysis, while allowing for improved sample treatment logistics with reduced technical variability and without compromising the structure of the oral microbiome.

Recovery of Metagenome-Assembled Genomes from a Human Fecal Sample with Pacific Biosciences High-Fidelity Sequencing.

Here, we report the recovery of 89 metagenome-assembled genomes (MAGs) derived from a human fecal sample subjected to Pacific Biosciences (PacBio) high-fidelity (HiFi) sequencing. A total of 9 MAGs consisted of complete circular contigs, and 45 MAGs were high-quality draft genomes according to the minimum information about a metagenome-assembled genome (MIMAG) standards.

Benchmarking second and third-generation sequencing platforms for microbial metagenomics.

Shotgun metagenomic sequencing is a common approach for studying the taxonomic diversity and metabolic potential of complex microbial communities. Current methods primarily use second generation short read sequencing, yet advances in third generation long read technologies provide opportunities to overcome some of the limitations of short read sequencing. Here, we compared seven platforms, encompassing second generation sequencers (Illumina HiSeq 300, MGI DNBSEQ-G400 and DNBSEQ-T7, ThermoFisher Ion GeneStudio S5 and Ion Proton P1) and third generation sequencers (Oxford Nanopore Technologies MinION R9 and Pacific Biosciences Sequel II). We constructed three uneven synthetic microbial communities composed of up to 87 genomic microbial strains DNAs per mock, spanning 29 bacterial and archaeal phyla, and representing the most complex and diverse synthetic communities used for sequencing technology comparisons. Our results demonstrate that third generation sequencing have advantages over second generation platforms in analyzing complex microbial communities, but require careful sequencing library preparation for optimal quantitative metagenomic analysis. Our sequencing data also provides a valuable resource for testing and benchmarking bioinformatics software for metagenomics.

Complete genome sequence of the pigmented Streptococcus thermophilus strain JIM8232.

Streptococcus thermophilus is a dairy species commonly used in the manufacture of cheese and yogurt. Here, we report the complete sequence of S. thermophilus strain JIM8232, isolated from milk and which produces a yellow pigment, an atypical trait for this bacterium.