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

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.

Driving gut microbiota enterotypes through host genetics

BACKGROUND

Population stratification based on interindividual variability in gut microbiota composition has revealed the existence of several ecotypes named enterotypes in humans and various animal species. Enterotypes are often associated with environmental factors including diet, but knowledge of the role of host genetics remains scarce. Moreover, enterotypes harbor functionalities likely associated with varying abilities and susceptibilities of their host. Previously, we showed that under controlled conditions, 60-day-old pig populations consistently split into two enterotypes with either Prevotella and Mitsuokella (PM enterotype) or Ruminococcus and Treponema (RT enterotype) as keystone taxa. Here, our aim was to rely on pig as a model to study the influence of host genetics to assemble enterotypes, and to provide clues on enterotype functional differences and their links with growth traits.

RESULTS

We established two pig lines contrasted for abundances of the genera pairs specifying each enterotype at 60 days of age and assessed them for fecal microbiota composition and growth throughout three consecutive generations. Response to selection across three generations revealed, per line, an increase in the prevalence of the selected enterotype and in the average relative abundances of directly and indirectly selected bacterial genera. The PM enterotype was found less diverse than the RT enterotype but more efficient for piglet growth during the post-weaning period. Shotgun metagenomics revealed differentially abundant bacterial species between the two enterotypes. By using the KEGG Orthology database, we show that functions related to starch degradation and polysaccharide metabolism are enriched in the PM enterotype, whereas functions related to general nucleoside transport and peptide/nickel transport are enriched in the RT enterotype. Our results also suggest that the PM and RT enterotypes might differ in the metabolism of valine, leucin, and isoleucine, favoring their biosynthesis and degradation, respectively.

CONCLUSION

We experimentally demonstrated that enterotypes are functional ecosystems that can be selected as a whole by exerting pressure on the host genetics. We also highlight that holobionts should be considered as units of selection in breeding programs. These results pave the way for a holistic use of host genetics, microbiota diversity, and enterotype functionalities to understand holobiont shaping and adaptation. Video Abstract.

Gut microbiome and metabolome profiling in Framingham heart study reveals cholesterol-metabolizing bacteria

Accumulating evidence suggests that cardiovascular disease (CVD) is associated with an altered gut microbiome. Our understanding of the underlying mechanisms has been hindered by lack of matched multi-omic data with diagnostic biomarkers. To comprehensively profile gut microbiome contributions to CVD, we generated stool metagenomics and metabolomics from 1,429 Framingham Heart Study participants. We identified blood lipids and cardiovascular health measurements associated with microbiome and metabolome composition. Integrated analysis revealed microbial pathways implicated in CVD, including flavonoid, γ-butyrobetaine, and cholesterol metabolism. Species from the Oscillibacter genus were associated with decreased fecal and plasma cholesterol levels. Using functional prediction and in vitro characterization of multiple representative human gut Oscillibacter isolates, we uncovered conserved cholesterol-metabolizing capabilities, including glycosylation and dehydrogenation. These findings suggest that cholesterol metabolism is a broad property of phylogenetically diverse Oscillibacter spp., with potential benefits for lipid homeostasis and cardiovascular health.

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.

Micro(nano)plastics and Their Potential Impact on Human Gut Health: A Narrative Review

Microplastics and nanoplastics (MNPs) are becoming an increasingly severe global problem due to their widespread distribution and complex impact on living organisms. Apart from their environmental impact, the effects of MNPs on living organisms have also continued to attract attention. The harmful impact of MNPs has been extensively documented in marine invertebrates and larger marine vertebrates like fish. However, the research on the toxicity of these particles on mammals is still limited, and their possible effects on humans are poorly understood. Considering that MNPs are commonly found in food or food packaging, humans are primarily exposed to them through ingestion. It would be valuable to investigate the potential harmful effects of these particles on gut health. This review focuses on recent research exploring the toxicological impacts of micro- and nanoplastics on the gut, as observed in human cell lines and mammalian models. Available data from various studies indicate that the accumulation of MNPs in mammalian models and human cells may result in adverse consequences, in terms of epithelial toxicity, immune toxicity, and the disruption of the gut microbiota. The paper also discusses the current research limitations and prospects in this field, aiming to provide a scientific basis and reference for further studies on the toxic mechanisms of micro- and nanoplastics.

Perturbation and resilience of the gut microbiome up to 3 months after β-lactams exposure in healthy volunteers suggest an important role of microbial β-lactamases

BACKGROUND

Antibiotics notoriously perturb the gut microbiota. We treated healthy volunteers either with cefotaxime or ceftriaxone for 3 days, and collected in each subject 12 faecal samples up to day 90. Using untargeted and targeted phenotypic and genotypic approaches, we studied the changes in the bacterial, phage and fungal components of the microbiota as well as the metabolome and the β-lactamase activity of the stools. This allowed assessing their degrees of perturbation and resilience.

RESULTS

While only two subjects had detectable concentrations of antibiotics in their faeces, suggesting important antibiotic degradation in the gut, the intravenous treatment perturbed very significantly the bacterial and phage microbiota, as well as the composition of the metabolome. In contrast, treatment impact was relatively low on the fungal microbiota. At the end of the surveillance period, we found evidence of resilience across the gut system since most components returned to a state like the initial one, even if the structure of the bacterial microbiota changed and the dynamics of the different components over time were rarely correlated. The observed richness of the antibiotic resistance genes repertoire was significantly reduced up to day 30, while a significant increase in the relative abundance of β-lactamase encoding genes was observed up to day 10, consistent with a concomitant increase in the β-lactamase activity of the microbiota. The level of β-lactamase activity at baseline was positively associated with the resilience of the metabolome content of the stools.

CONCLUSIONS

In healthy adults, antibiotics perturb many components of the microbiota, which return close to the baseline state within 30 days. These data suggest an important role of endogenous β-lactamase-producing anaerobes in protecting the functions of the microbiota by de-activating the antibiotics reaching the colon. Video Abstract.

Linking microbial genes to plasma and stool metabolites uncovers host-microbial interactions underlying ulcerative colitis disease course

Understanding the role of the microbiome in inflammatory diseases requires the identification of microbial effector molecules. We established an approach to link disease-associated microbes to microbial metabolites by integrating paired metagenomics, stool and plasma metabolomics, and culturomics. We identified host-microbial interactions correlated with disease activity, inflammation, and the clinical course of ulcerative colitis (UC) in the Predicting Response to Standardized Colitis Therapy (PROTECT) pediatric inception cohort. In severe disease, metabolite changes included increased dipeptides and tauro-conjugated bile acids (BAs) and decreased amino-acid-conjugated BAs in stool, whereas in plasma polyamines (N-acetylputrescine and N1-acetylspermidine) increased. Using patient samples and Veillonella parvula as a model, we uncovered nitrate- and lactate-dependent metabolic pathways, experimentally linking V. parvula expansion to immunomodulatory tryptophan metabolite production. Additionally, V. parvula metabolizes immunosuppressive thiopurine drugs through xdhA xanthine dehydrogenase, potentially impairing the therapeutic response. Our findings demonstrate that the microbiome contributes to disease-associated metabolite changes, underscoring the importance of these interactions in disease pathology and treatment.

Multicenter evaluation of gut microbiome profiling by next-generation sequencing reveals major biases in partial-length metabarcoding approach

Next-generation sequencing workflows, using either metabarcoding or metagenomic approaches, have massively contributed to expanding knowledge of the human gut microbiota, but methodological bias compromises reproducibility across studies. Where these biases have been quantified within several comparative analyses on their own, none have measured inter-laboratory reproducibility using similar DNA material. Here, we designed a multicenter study involving seven participating laboratories dedicated to partial- (P1 to P5), full-length (P6) metabarcoding, or metagenomic profiling (MGP) using DNA from a mock microbial community or extracted from 10 fecal samples collected at two time points from five donors. Fecal material was collected, and the DNA was extracted according to the IHMS protocols. The mock and isolated DNA were then provided to the participating laboratories for sequencing. Following sequencing analysis according to the laboratories' routine pipelines, relative taxonomic-count tables defined at the genus level were provided and analyzed. Large variations in alpha-diversity between laboratories, uncorrelated with sequencing depth, were detected among the profiles. Half of the genera identified by P1 were unique to this partner and two-thirds of the genera identified by MGP were not detected by P3. Analysis of beta-diversity revealed lower inter-individual variance than inter-laboratory variances. The taxonomic profiles of P5 and P6 were more similar to those of MGP than those obtained by P1, P2, P3, and P4. Reanalysis of the raw sequences obtained by partial-length metabarcoding profiling, using a single bioinformatic pipeline, harmonized the description of the bacterial profiles, which were more similar to each other, except for P3, and closer to the profiles obtained by MGP. This study highlights the major impact of the bioinformatics pipeline, and primarily the database used for taxonomic annotation. Laboratories need to benchmark and optimize their bioinformatic pipelines using standards to monitor their effectiveness in accurately detecting taxa present in gut microbiota.

Unveiling Candida albicans intestinal carriage in healthy volunteers: the role of micro- and mycobiota, diet, host genetics and immune response

Candida albicans is a commensal yeast present in the gut of most healthy individuals but with highly variable concentrations. However, little is known about the host factors that influence colonization densities. We investigated how microbiota, host lifestyle factors, and genetics could shape C. albicans intestinal carriage in 695 healthy individuals from the Milieu Intérieur cohort. C. albicans intestinal carriage was detected in 82.9% of the subjects using quantitative PCR. Using linear mixed models and multiway-ANOVA, we explored C. albicans intestinal levels with regard to gut microbiota composition and lifestyle factors including diet. By analyzing shotgun metagenomics data and C. albicans qPCR data, we showed that Intestinimonas butyriciproducens was the only gut microbiota species whose relative abundance was negatively correlated with C. albicans concentration. Diet is also linked to C. albicans growth, with eating between meals and a low-sodium diet being associated with higher C. albicans levels. Furthermore, by Genome-Wide Association Study, we identified 26 single nucleotide polymorphisms suggestively associated with C. albicans colonization. In addition, we found that the intestinal levels of C. albicans might influence the host immune response, specifically in response to fungal challenge. We analyzed the transcriptional levels of 546 immune genes and the concentration of 13 cytokines after whole blood stimulation with C. albicans cells and showed positive associations between the extent of C. albicans intestinal levels and NLRP3 expression, as well as secreted IL-2 and CXCL5 concentrations. Taken together, these findings open the way for potential new interventional strategies to curb C. albicans intestinal overgrowth.

The bacterial species profiles of the lingual and salivary microbiota differ with basic tastes sensitivity in human

Taste perception is crucial and impairments, which can be linked to pathologies, can lead to eating disorders. It is triggered by taste compounds stimulating receptors located on the tongue. However, the tongue is covered by a film containing saliva and microorganisms suspected to modulate the taste receptor environment. The present study aimed to elucidate the links between taste sensitivity (sweetness, sourness, bitterness, saltiness, umami) and the salivary as well as the tongue microbiota using shotgun metagenomics. 109 bacterial species were correlated with at least one taste. Interestingly, when a species was correlated with at least two tastes, the correlations were unidirectional, indicating a putative global implication. Some Streptococcus, SR1 and Rickenellaceae species correlated with five tastes. When comparing both ecosystems, saliva appears to be a better taste predictor than tongue. This work shows the implication of the oral microbiota in taste and exhibits specificities depending on the ecosystem considered.

Rationally-defined microbial consortia suppress multidrug-resistant proinflammatory Enterobacteriaceae via ecological control

Persistent colonization and outgrowth of pathogenic organisms in the intestine may occur due to long-term antibiotic usage or inflammatory conditions, which perpetuate dysregulated immunity and tissue damage1,2. Gram-negative Enterobacteriaceae gut pathobionts are particularly recalcitrant to conventional antibiotic treatment3,4, though an emerging body of evidence suggests that manipulation of the commensal microbiota may be a practical alternative therapeutic strategy5-7. In this study, we rationally isolated and down-selected commensal bacterial consortia from healthy human stool samples capable of strongly and specifically suppressing intestinal Enterobacteriaceae. One of the elaborated consortia, consisting of 18 commensal strains, effectively controlled ecological niches by regulating gluconate availability, thereby reestablishing colonization resistance and alleviating antibiotic-resistant Klebsiella-driven intestinal inflammation in mice. Harnessing these microbial activities in the form of live bacterial therapeutics may represent a promising solution to combat the growing threat of proinflammatory, antimicrobial-resistant bacterial infection.

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.

Machine learning approaches in microbiome research: challenges and best practices

Microbiome data predictive analysis within a machine learning (ML) workflow presents numerous domain-specific challenges involving preprocessing, feature selection, predictive modeling, performance estimation, model interpretation, and the extraction of biological information from the results. To assist decision-making, we offer a set of recommendations on algorithm selection, pipeline creation and evaluation, stemming from the COST Action ML4Microbiome. We compared the suggested approaches on a multi-cohort shotgun metagenomics dataset of colorectal cancer patients, focusing on their performance in disease diagnosis and biomarker discovery. It is demonstrated that the use of compositional transformations and filtering methods as part of data preprocessing does not always improve the predictive performance of a model. In contrast, the multivariate feature selection, such as the Statistically Equivalent Signatures algorithm, was effective in reducing the classification error. When validated on a separate test dataset, this algorithm in combination with random forest modeling, provided the most accurate performance estimates. Lastly, we showed how linear modeling by logistic regression coupled with visualization techniques such as Individual Conditional Expectation (ICE) plots can yield interpretable results and offer biological insights. These findings are significant for clinicians and non-experts alike in translational applications.

Unraveling the Gut Microbiome-Diet Connection: Exploring the Impact of Digital Precision and Personalized Nutrition on Microbiota Composition and Host Physiology

The human gut microbiome, an intricate ecosystem housing trillions of microorganisms within the gastrointestinal tract, holds significant importance in human health and the development of diseases. Recent advances in technology have allowed for an in-depth exploration of the gut microbiome, shedding light on its composition and functions. Of particular interest is the role of diet in shaping the gut microbiome, influencing its diversity, population size, and metabolic functions. Precision nutrition, a personalized approach based on individual characteristics, has shown promise in directly impacting the composition of the gut microbiome. However, to fully understand the long-term effects of specific diets and food components on the gut microbiome and to identify the variations between individuals, longitudinal studies are crucial. Additionally, precise methods for collecting dietary data, alongside the application of machine learning techniques, hold immense potential in comprehending the gut microbiome's response to diet and providing tailored lifestyle recommendations. In this study, we investigated the complex mechanisms that govern the diverse impacts of nutrients and specific foods on the equilibrium and functioning of the individual gut microbiome of seven volunteers (four females and three males) with an average age of 40.9 ± 10.3 years, aiming at identifying potential therapeutic targets, thus making valuable contributions to the field of personalized nutrition. These findings have the potential to revolutionize the development of highly effective strategies that are tailored to individual requirements for the management and treatment of various diseases.

Centenarians have a diverse gut virome with the potential to modulate metabolism and promote healthy lifespan

Distinct gut microbiome ecology may be implicated in the prevention of aging-related diseases as it influences systemic immune function and resistance to infections. Yet, the viral component of the microbiome throughout different stages in life remains unexplored. Here we present a characterization of the centenarian gut virome using previously published metagenomes from 195 individuals from Japan and Sardinia. Compared with gut viromes of younger adults (>18 yr) and older individuals (>60 yr), centenarians had a more diverse virome including previously undescribed viral genera, such as viruses associated with Clostridia. A population shift towards higher lytic activity was also observed. Finally, we investigated phage-encoded auxiliary functions that influence bacterial physiology, which revealed an enrichment of genes supporting key steps in sulfate metabolic pathways. Phage and bacterial members of the centenarian microbiome displayed an increased potential for converting methionine to homocysteine, sulfate to sulfide and taurine to sulfide. A greater metabolic output of microbial hydrogen sulfide in centenarians may in turn support mucosal integrity and resistance to pathobionts.

The gut microbiota contributes to the pathogenesis of anorexia nervosa in humans and mice

Anorexia nervosa (AN) is an eating disorder with a high mortality. About 95% of cases are women and it has a population prevalence of about 1%, but evidence-based treatment is lacking. The pathogenesis of AN probably involves genetics and various environmental factors, and an altered gut microbiota has been observed in individuals with AN using amplicon sequencing and relatively small cohorts. Here we investigated whether a disrupted gut microbiota contributes to AN pathogenesis. Shotgun metagenomics and metabolomics were performed on faecal and serum samples, respectively, from a cohort of 77 females with AN and 70 healthy females. Multiple bacterial taxa (for example, Clostridium species) were altered in AN and correlated with estimates of eating behaviour and mental health. The gut virome was also altered in AN including a reduction in viral-bacterial interactions. Bacterial functional modules associated with the degradation of neurotransmitters were enriched in AN and various structural variants in bacteria were linked to metabolic features of AN. Serum metabolomics revealed an increase in metabolites associated with reduced food intake (for example, indole-3-propionic acid). Causal inference analyses implied that serum bacterial metabolites are potentially mediating the impact of an altered gut microbiota on AN behaviour. Further, we performed faecal microbiota transplantation from AN cases to germ-free mice under energy-restricted feeding to mirror AN eating behaviour. We found that the reduced weight gain and induced hypothalamic and adipose tissue gene expression were related to aberrant energy metabolism and eating behaviour. Our 'omics' and mechanistic studies imply that a disruptive gut microbiome may contribute to AN pathogenesis.

An Integrated Approach to Skeletal Muscle Health in Aging

A decline in muscle mass and function represents one of the most problematic changes associated with aging, and has dramatic effects on autonomy and quality of life. Several factors contribute to the inexorable process of sarcopenia, such as mitochondrial and autophagy dysfunction, and the lack of regeneration capacity of satellite cells. The physiologic decline in muscle mass and in motoneuron functionality associated with aging is exacerbated by the sedentary lifestyle that accompanies elderly people. Regular physical activity is beneficial to most people, but the elderly need well-designed and carefully administered training programs that improve muscle mass and, consequently, both functional ability and quality of life. Aging also causes alteration in the gut microbiota composition associated with sarcopenia, and some advances in research have elucidated that interventions via the gut microbiota-muscle axis have the potential to ameliorate the sarcopenic phenotype. Several mechanisms are involved in vitamin D muscle atrophy protection, as demonstrated by the decreased muscular function related to vitamin D deficiency. Malnutrition, chronic inflammation, vitamin deficiencies, and an imbalance in the muscle-gut axis are just a few of the factors that can lead to sarcopenia. Supplementing the diet with antioxidants, polyunsaturated fatty acids, vitamins, probiotics, prebiotics, proteins, kefir, and short-chain fatty acids could be potential nutritional therapies against sarcopenia. Finally, a personalized integrated strategy to counteract sarcopenia and maintain the health of skeletal muscles is suggested in this review.

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.

The gut microbiota in multiple sclerosis varies with disease activity

BACKGROUND

Multiple sclerosis is a chronic immune-mediated disease of the brain and spinal cord resulting in physical and cognitive impairment in young adults. It is hypothesized that a disrupted bacterial and viral gut microbiota is a part of the pathogenesis mediating disease impact through an altered gut microbiota-brain axis. The aim of this study is to explore the characteristics of gut microbiota in multiple sclerosis and to associate it with disease variables, as the etiology of the disease remains only partially known.

METHODS

Here, in a case-control setting involving 148 Danish cases with multiple sclerosis and 148 matched healthy control subjects, we performed shotgun sequencing of fecal microbial DNA and associated bacterial and viral microbiota findings with plasma cytokines, blood cell gene expression profiles, and disease activity.

RESULTS

We found 61 bacterial species that were differentially abundant when comparing all multiple sclerosis cases with healthy controls, among which 31 species were enriched in cases. A cluster of inflammation markers composed of blood leukocytes, CRP, and blood cell gene expression of IL17A and IL6 was positively associated with a cluster of multiple sclerosis-related species. Bacterial species that were more abundant in cases with disease-active treatment-naïve multiple sclerosis were positively linked to a group of plasma cytokines including IL-22, IL-17A, IFN-β, IL-33, and TNF-α. The bacterial species richness of treatment-naïve multiple sclerosis cases was associated with number of relapses over a follow-up period of 2 years. However, in non-disease-active cases, we identified two bacterial species, Faecalibacterium prausnitzii and Gordonibacter urolithinfaciens, whose absolute abundance was enriched. These bacteria are known to produce anti-inflammatory metabolites including butyrate and urolithin. In addition, cases with multiple sclerosis had a higher viral species diversity and a higher abundance of Caudovirales bacteriophages.

CONCLUSIONS

Considerable aberrations are present in the gut microbiota of patients with multiple sclerosis that are directly associated with blood biomarkers of inflammation, and in treatment-naïve cases bacterial richness is positively associated with disease activity. Yet, the finding of two symbiotic bacterial species in non-disease-active cases that produce favorable immune-modulating compounds provides a rationale for testing these bacteria as adjunct therapeutics in future clinical trials.

Identification of representative species-specific genes for abundance measurements

Motivation

Metagenomic binning facilitates the reconstruction of genomes and identification of Metagenomic Species Pan-genomes or Metagenomic Assembled Genomes. We propose a method for identifying a set of de novo representative genes, termed signature genes, which can be used to measure the relative abundance and used as markers of each metagenomic species with high accuracy.

Results

An initial set of the 100 genes that correlate with the median gene abundance profile of the entity is selected. A variant of the coupon collector's problem was utilized to evaluate the probability of identifying a certain number of unique genes in a sample. This allows us to reject the abundance measurements of strains exhibiting a significantly skewed gene representation. A rank-based negative binomial model is employed to assess the performance of different gene sets across a large set of samples, facilitating identification of an optimal signature gene set for the entity. When benchmarked the method on a synthetic gene catalog, our optimized signature gene sets estimate relative abundance significantly closer to the true relative abundance compared to the starting gene sets extracted from the metagenomic species. The method was able to replicate results from a study with real data and identify around three times as many metagenomic entities.

Availability and implementation

The code used for the analysis is available on GitHub: https://github.com/trinezac/SG_optimization.

Supplementary information

Supplementary data are available at Bioinformatics Advances online.

Both Disease Activity and HLA-B27 Status Are Associated With Gut Microbiome Dysbiosis in Spondyloarthritis Patients

OBJECTIVE

Gut microbiome dysbiosis has previously been reported in spondyloarthritis (SpA) patients and could be critically involved in the pathogenesis of this disorder. The objectives of this study were to further characterize the microbiota structure in SpA patients and to investigate the relationship between dysbiosis and disease activity in light of the putative influence of the genetic background.

METHODS

Shotgun sequencing was performed on fecal DNA isolated from stool samples from 2 groups of adult volunteers: SpA patients (n = 102) and healthy controls (n = 63). A subset of the healthy controls comprised the age-matched siblings of patients whose HLA-B27 status was known. Changes in gut microbiota composition were assessed based on species diversity, enterotypes, and taxonomic and functional differences.

RESULTS

Dysbiosis was confirmed in SpA patients as compared to healthy controls. The restriction of microbiota diversity was detected in patients with the most active disease, and the abundance of several bacterial species was correlated with Bath Ankylosing Spondylitis Disease Activity Index score. Among healthy controls, significant differences in microbiota composition were also detected between the HLA-B27-positive and the HLA-B27-negative siblings of SpA patients. We highlighted a decreased abundance of several species of bacteria in SpA patients, especially those bacteria belonging to the Clostridiales order. Among the few species of bacteria showing increased abundance, Ruminococcus gnavus was one of the top differentiating species.

CONCLUSION

These findings reveal that genetic background and level of disease activity are likely to influence the composition of the gut microbiota of patients with SpA. It may be appropriate for further research on chronic arthritis to focus on these key parameters.

The gut microbiota, a key to understanding the health implications of micro(nano)plastics and their biodegradation

The effects of plastic debris on the environment and plant, animal, and human health are a global challenge, with micro(nano)plastics (MNPs) being the main focus. MNPs are found so often in the food chain that they are provoking an increase in human intake. They have been detected in most categories of consumed foods, drinking water, and even human feces. Therefore, oral ingestion becomes the main source of exposure to MNPs, and the gastrointestinal tract, primarily the gut, constantly interacts with these small particles. The consequences of human exposure to MNPs remain unclear. However, current in vivo studies and in vitro gastrointestinal tract models have shown that MNPs of several types and sizes impact gut intestinal bacteria, affecting gut homeostasis. The typical microbiome signature of MNP ingestion is often associated with dysbiosis and loss of resilience, leads to frequent pathogen outbreaks, and local and systemic metabolic disorders. Moreover, the small micro- and nano-plastic particles found in animal tissues with accumulated evidence of microbial degradation of plastics/MNPs by bacteria and insect gut microbiota raise the issue of whether human gut bacteria make key contributions to the bio-transformation of ingested MNPs. Here, we discuss these issues and unveil the complex interplay between MNPs and the human gut microbiome. Therefore, the elucidation of the biological consequences of this interaction on both host and microbiota is undoubtedly challenging. It is expected that microbial biotechnology and microbiome research could help decipher the extent to which gut microorganisms diversify and MNP-determinant species, mechanisms, and enzymatic systems, as well as become important to understand our response to MNP exposure and provide background information to inspire future holistic studies.

Seasonal microbial dynamics in the ocean inferred from assembled and unassembled data: a view on the unknown biosphere

In environmental metagenomic experiments, a very high proportion of the microbial sequencing data (> 70%) remains largely unexploited because rare and closely related genomes are missed in short-read assemblies. The identity and the potential metabolisms of a large fraction of natural microbial communities thus remain inaccessible to researchers. The purpose of this study was to explore the genomic content of unassembled metagenomic data and test their level of novelty. We used data from a three-year microbial metagenomic time series of the NW Mediterranean Sea, and conducted reference-free and database-guided analysis. The results revealed a significant genomic difference between the assembled and unassembled reads. The unassembled reads had a lower mean identity against public databases, and fewer metabolic pathways could be reconstructed. In addition, the unassembled fraction presented a clear temporal pattern, unlike the assembled ones, and a specific community composition that was similar to the rare communities defined by metabarcoding using the 16S rRNA gene. The rare gene pool was characterised by keystone bacterial taxa, and the presence of viruses, suggesting that viral lysis could maintain some taxa in a state of rarity. Our study demonstrates that unassembled metagenomic data can provide important information on the structure and functioning of microbial communities.

Identification of trypsin-degrading commensals in the large intestine

Increased levels of proteases, such as trypsin, in the distal intestine have been implicated in intestinal pathological conditions^1–3. However, the players and mechanisms that underlie protease regulation in the intestinal lumen have remained unclear. Here we show that Paraprevotella strains isolated from the faecal microbiome of healthy human donors are potent trypsin-degrading commensals. Mechanistically, Paraprevotella recruit trypsin to the bacterial surface through type IX secretion system-dependent polysaccharide-anchoring proteins to promote trypsin autolysis. Paraprevotella colonization protects IgA from trypsin degradation and enhances the effectiveness of oral vaccines against Citrobacter rodentium. Moreover, Paraprevotella colonization inhibits lethal infection with murine hepatitis virus-2, a mouse coronavirus that is dependent on trypsin and trypsin-like proteases for entry into host cells^4,5. Consistently, carriage of putative genes involved in trypsin degradation in the gut microbiome was associated with reduced severity of diarrhoea in patients with SARS-CoV-2 infection. Thus, trypsin-degrading commensal colonization may contribute to the maintenance of intestinal homeostasis and protection from pathogen infection.

Colonization of trypsin-degrading commensal bacteria may contribute to the maintenance of intestinal homeostasis and protection against pathogen infection in humans and mice.

MAGNETO: An Automated Workflow for Genome-Resolved Metagenomics

Metagenome-assembled genomes (MAGs) represent individual genomes recovered from metagenomic data. MAGs are extremely useful to analyze uncultured microbial genomic diversity, as well as to characterize associated functional and metabolic potential in natural environments. Recent computational developments have considerably improved MAG reconstruction but also emphasized several limitations, such as the nonbinning of sequence regions with repetitions or distinct nucleotidic composition. Different assembly and binning strategies are often used; however, it still remains unclear which assembly strategy, in combination with which binning approach, offers the best performance for MAG recovery. Several workflows have been proposed in order to reconstruct MAGs, but users are usually limited to single-metagenome assembly or need to manually define sets of metagenomes to coassemble prior to genome binning. Here, we present MAGNETO, an automated workflow dedicated to MAG reconstruction, which includes a fully-automated coassembly step informed by optimal clustering of metagenomic distances, and implements complementary genome binning strategies, for improving MAG recovery. MAGNETO is implemented as a Snakemake workflow and is available at: https://gitlab.univ-nantes.fr/bird_pipeline_registry/magneto. IMPORTANCE Genome-resolved metagenomics has led to the discovery of previously untapped biodiversity within the microbial world. As the development of computational methods for the recovery of genomes from metagenomes continues, existing strategies need to be evaluated and compared to eventually lead to standardized computational workflows. In this study, we compared commonly used assembly and binning strategies and assessed their performance using both simulated and real metagenomic data sets. We propose a novel approach to automate coassembly, avoiding the requirement for a priori knowledge to combine metagenomic information. The comparison against a previous coassembly approach demonstrates a strong impact of this step on genome binning results, but also the benefits of informing coassembly for improving the quality of recovered genomes. MAGNETO integrates complementary assembly-binning strategies to optimize genome reconstruction and provides a complete reads-to-genomes workflow for the growing microbiome research community.

Functional characterization of prokaryotic dark matter: the road so far and what lies ahead

Eight-hundred thousand to one trillion prokaryotic species may inhabit our planet. Yet, fewer than two-hundred thousand prokaryotic species have been described. This uncharted fraction of microbial diversity, and its undisclosed coding potential, is known as the "microbial dark matter" (MDM). Next-generation sequencing has allowed to collect a massive amount of genome sequence data, leading to unprecedented advances in the field of genomics. Still, harnessing new functional information from the genomes of uncultured prokaryotes is often limited by standard classification methods. These methods often rely on sequence similarity searches against reference genomes from cultured species. This hinders the discovery of unique genetic elements that are missing from the cultivated realm. It also contributes to the accumulation of prokaryotic gene products of unknown function among public sequence data repositories, highlighting the need for new approaches for sequencing data analysis and classification. Increasing evidence indicates that these proteins of unknown function might be a treasure trove of biotechnological potential. Here, we outline the challenges, opportunities, and the potential hidden within the functional dark matter (FDM) of prokaryotes. We also discuss the pitfalls surrounding molecular and computational approaches currently used to probe these uncharted waters, and discuss future opportunities for research and applications.

Low-dose interleukin-2 shapes a tolerogenic gut microbiota that improves autoimmunity and gut inflammation

Gut microbiota dysbiosis is associated with inflammatory bowel diseases and with cardiometabolic, neurological, and autoimmune diseases. Gut microbiota composition has a direct effect on the immune system, and vice versa, and it has a particular effect on Treg homeostasis. Low-dose IL-2 (IL-2_LD) stimulates Tregs and is a promising treatment for autoimmune and inflammatory diseases. We aimed to evaluate the impact of IL-2_LD on gut microbiota and correlatively on the immune system. We used 16S ribosomal RNA profiling and metagenomics to characterize gut microbiota of mice and humans treated or not with IL-2_LD. We performed fecal microbiota transplantation (FMT) from IL-2_LD–treated to naive recipient mice and evaluated its effects in models of gut inflammation and diabetes. IL-2_LD markedly affected gut microbiota composition in mice and humans. Transfer of an IL-2–tuned microbiota by FMT protected C57BL/6J mice from dextran sulfate sodium–induced colitis and prevented diabetes in NOD mice. Metagenomic analyses highlighted a role for several species affected by IL-2_LD and for microbial pathways involved in the biosynthesis of amino acids, short-chain fatty acids, and L-arginine. Our results demonstrate that IL-2_LD induced changes in gut microbiota that are involved in the immunoregulatory effects of IL-2_LD and suggest a crosstalk between Tregs and gut microbiota. These results provide potentially novel insight for understanding the mode of action of Treg-directed therapies.

Discovery of bioactive microbial gene products in inflammatory bowel disease

Microbial communities and their associated bioactive compounds^1-3 are often disrupted in conditions such as the inflammatory bowel diseases (IBD)⁴. However, even in well-characterized environments (for example, the human gastrointestinal tract), more than one-third of microbial proteins are uncharacterized and often expected to be bioactive^5-7. Here we systematically identified more than 340,000 protein families as potentially bioactive with respect to gut inflammation during IBD, about half of which have not to our knowledge been functionally characterized previously on the basis of homology or experiment. To validate prioritized microbial proteins, we used a combination of metagenomics, metatranscriptomics and metaproteomics to provide evidence of bioactivity for a subset of proteins that are involved in host and microbial cell-cell communication in the microbiome; for example, proteins associated with adherence or invasion processes, and extracellular von Willebrand-like factors. Predictions from high-throughput data were validated using targeted experiments that revealed the differential immunogenicity of prioritized Enterobacteriaceae pilins and the contribution of homologues of von Willebrand factors to the formation of Bacteroides biofilms in a manner dependent on mucin levels. This methodology, which we term MetaWIBELE (workflow to identify novel bioactive elements in the microbiome), is generalizable to other environmental communities and human phenotypes. The prioritized results provide thousands of candidate microbial proteins that are likely to interact with the host immune system in IBD, thus expanding our understanding of potentially bioactive gene products in chronic disease states and offering a rational compendium of possible therapeutic compounds and targets.

Diet Supplementation with NUTRIOSE, a Resistant Dextrin, Increases the Abundance of Parabacteroides distasonis in the Human Gut

SCOPE

An imbalance of the gut microbiota ("dysbiosis") is associated with numerous chronic diseases, and its modulation is a promising novel therapeutic approach. Dietary supplementation with soluble fiber is one of several proposed modulation strategies. This study aims at confirming the impact of the resistant dextrin NUTRIOSE (RD), a soluble fiber with demonstrated beneficial health effects, on the gut microbiota of healthy individuals.

METHODS AND RESULTS

Fifty healthy women are enrolled and supplemented daily with either RD (n = 24) or a control product (n = 26) during 6 weeks. Characterization of the fecal metagenome with shotgun sequencing reveals that RD intake dramatically increases the abundance of the commensal bacterium Parabacteroides distasonis. Furthermore, presence in metagenomes of accessory genes from P. distasonis, coding for susCD (a starch-binding membrane protein complex) is associated with a greater increase of the species. This suggests that response to RD might be strain-dependent.

CONCLUSION

Supplementation with RD can be used to specifically increase P. distasonis in gut microbiota of healthy women. The magnitude of the response may be associated with fiber-metabolizing capabilities of strains carried by subjects. Further research will seek to confirm that P. distasonis directly modulates the clinical effects observed in other studies.

Genome-scale metabolic modelling of the human gut microbiome reveals changes of the glyoxylate and dicarboxylate metabolism in metabolic disorders

The human gut microbiome has been associated with metabolic disorders including obesity, type 2 diabetes, and atherosclerosis. Understanding the contribution of microbiome metabolic changes is important for elucidating the role of gut bacteria in regulating metabolism. We used available metagenomics data from these metabolic disorders, together with genome-scale metabolic modeling of key bacteria in the individual and community-level to investigate the mechanistic role of the gut microbiome in metabolic diseases. Modeling predicted increased levels of glutamate consumption along with the production of ammonia, arginine, and proline in gut bacteria common across the disorders. Abundance profiles and network-dependent analysis identified the enrichment of tartrate dehydrogenase in the disorders. Moreover, independent plasma metabolite levels showed associations between metabolites including proline and tyrosine and an increased tartrate metabolism in healthy obese individuals. We, therefore, propose that an increased tartrate metabolism could be a significant mediator of the microbiome metabolic changes in metabolic disorders.

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Metagenomic analysis highlights key common bacterial species across metabolic diseases

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Metabolic models showed higher levels of acetate produced by disease enriched bacteria

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Reaction analysis revealed increases in the glyoxylate and dicarboxylate pathway

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Metabolomics and modeling analysis showed the potential role of tartrate metabolism

A deep siamese neural network improves metagenome-assembled genomes in microbiome datasets across different environments

Metagenomic binning is the step in building metagenome-assembled genomes (MAGs) when sequences predicted to originate from the same genome are automatically grouped together. The most widely-used methods for binning are reference-independent, operating de novo and enable the recovery of genomes from previously unsampled clades. However, they do not leverage the knowledge in existing databases. Here, we introduce SemiBin, an open source tool that uses deep siamese neural networks to implement a semi-supervised approach, i.e. SemiBin exploits the information in reference genomes, while retaining the capability of reconstructing high-quality bins that are outside the reference dataset. Using simulated and real microbiome datasets from several different habitats from GMGCv1 (Global Microbial Gene Catalog), including the human gut, non-human guts, and environmental habitats (ocean and soil), we show that SemiBin outperforms existing state-of-the-art binning methods. In particular, compared to other methods, SemiBin returns more high-quality bins with larger taxonomic diversity, including more distinct genera and species.

Human gut metatranscriptome changes induced by a fermented milk product are associated with improved tolerance to a flatulogenic diet

Healthy plant-based diets rich in fermentable residues may induce gas-related symptoms, possibly mediated by the gut microbiota. We previously showed that consumption of a fermented milk product (FMP) containing Bifidobacterium animalis subsp. lactis CNCM I-2494 and lactic acid bacteria improved gastrointestinal (GI) comfort in response to a flatulogenic dietary challenge in healthy individuals. To study the effects of the FMP on gut microbiota activity from those participants, we conducted a metatranscriptomic analysis of fecal samples (n = 262), which were collected during the ingestion of a habitual diet and two series of a 3-day high-residue challenge diet, before and following 28-days of FMP consumption.

Most of the FMP species were detected or found enriched upon consumption of the product. FMP mitigated the effect of a flatulogenic diet on gas-related symptoms in several ways. First, FMP consumption was associated with the depletion of gas-producing bacteria and increased hydrogen to methane conversion. It also led to the upregulation of activities such as replication and downregulation of functions related to motility and chemotaxis. Furthermore, upon FMP intake, metabolic activities such as carbohydrate metabolism, attributed to B. animalis and S. thermophilus, were enriched; these activities were coincidentally found to be negatively associated with several GI symptoms. Finally, a more connected microbial ecosystem or mutualistic relationship among microbes was found in responders to the FMP intervention.

Taken together, these findings suggest that consumption of the FMP improved the tolerance of a flatulogenic diet through active interactions with the resident gut microbiota.

Deciphering mechanisms and implications of bacterial translocation in human health and disease

Significant increases in potential microbial translocation, especially along the oral-gut axis, have been identified in many immune-related and inflammatory diseases, such as inflammatory bowel disease, colorectal cancer, rheumatoid arthritis, and liver cirrhosis, for which we currently have no cure or long-term treatment options. Recent advances in computational and experimental omics approaches now enable strain tracking, functional profiling, and strain isolation in unprecedented detail, which has the potential to elucidate the causes and consequences of microbial translocation. In this review, we discuss current evidence for the detection of bacterial translocation, examine different translocation axes with a primary focus on the oral-gut axis, and outline currently known translocation mechanisms and how they adversely affect the host in disease. Finally, we conclude with an overview of state-of-the-art computational and experimental tools for strain tracking and highlight the required next steps to elucidate the role of bacterial translocation in human health.

Changes in Gut Microbiota of Patients with Atopic Dermatitis During Balneotherapy

Introduction

Balneotherapy (BT) is the treatment of disease through the use of thermal spring water (TSW). It has been used for centuries and remains a popular form of treatment for dermatologic diseases such as atopic dermatitis (AD). Recent findings highlighted the role of the gut microbiota in AD and the possible crosstalk between gut and skin microbiomes in this pathology. Nevertheless, changes in the composition of the gut microbiota after balneotherapy remain to be elucidated.

Methods

A total of 96 patients, with moderate to severe AD according to the SCORAD, were enrolled. Stool samples were collected prior and post a 3-week balneotherapy at the thermal care center of La Roche-Posay (France). Composition of the gut microbiota was assessed by shotgun metagenomic sequencing.

Results

Species associated with high gut microbiota richness tended to correlate negatively with disease severity (SCORAD) and positively with SCORAD reduction, while species associated with low richness displayed the opposite pattern. Relative abundance of 23 species was significantly altered during BT, these changes being significantly associated with SCORAD reduction during BT, suggesting that gut microbiota composition and AD progression were associated through the treatment. Microbial functions related to gut-brain axis such as GABA and tryptophan metabolism were also altered by the treatment. Long-standing AD patients exhibited a better gut microbial profile than recently diagnosed patients, with higher MSP richness and species associated with SCORAD reduction.

Conclusion

In patients with AD, clinical disease parameters such as SCORAD or disease duration are intricately linked to the gut microbiota composition. SCORAD reduction occurring during BT was also associated with gut microbiota. The gut-brain-skin axis via neurotransmitter such as GABA should be further studied in diseases such as AD.

Toward accurate diagnosis and surveillance of bacterial infections using enhanced strain-level metagenomic next-generation sequencing of infected body fluids

Metagenomic next-generation sequencing (mNGS) enables comprehensive pathogen detection and has become increasingly popular in clinical diagnosis. The distinct pathogenic traits between strains require mNGS to achieve a strain-level resolution, but an equivocal concept of 'strain' as well as the low pathogen loads in most clinical specimens hinders such strain awareness. Here we introduce a metagenomic intra-species typing (MIST) tool (https://github.com/pandafengye/MIST), which hierarchically organizes reference genomes based on average nucleotide identity (ANI) and performs maximum likelihood estimation to infer the strain-level compositional abundance. In silico analysis using synthetic datasets showed that MIST accurately predicted the strain composition at a 99.9% average nucleotide identity (ANI) resolution with a merely 0.001× sequencing depth. When applying MIST on 359 culture-positive and 359 culture-negative real-world specimens of infected body fluids, we found the presence of multiple-strain reached considerable frequencies (30.39%-93.22%), which were otherwise underestimated by current diagnostic techniques due to their limited resolution. Several high-risk clones were identified to be prevalent across samples, including Acinetobacter baumannii sequence type (ST)208/ST195, Staphylococcus aureus ST22/ST398 and Klebsiella pneumoniae ST11/ST15, indicating potential outbreak events occurring in the clinical settings. Interestingly, contaminations caused by the engineered Escherichia coli strain K-12 and BL21 throughout the mNGS datasets were also identified by MIST instead of the statistical decontamination approach. Our study systemically characterized the infected body fluids at the strain level for the first time. Extension of mNGS testing to the strain level can greatly benefit clinical diagnosis of bacterial infections, including the identification of multi-strain infection, decontamination and infection control surveillance.

The influence of the gut microbiome on BCG-induced trained immunity

BACKGROUND

The bacillus Calmette-Guérin (BCG) vaccine protects against tuberculosis and heterologous infections but elicits high inter-individual variation in specific and nonspecific, or trained, immune responses. While the gut microbiome is increasingly recognized as an important modulator of vaccine responses and immunity in general, its potential role in BCG-induced protection is largely unknown.

RESULTS

Stool and blood were collected from 321 healthy adults before BCG vaccination, followed by blood sampling after 2 weeks and 3 months. Metagenomics based on de novo genome assembly reveals 43 immunomodulatory taxa. The nonspecific, trained immune response is detected by altered production of cytokines IL-6, IL-1β, and TNF-α upon ex vivo blood restimulation with Staphylococcus aureus and negatively correlates with abundance of Roseburia. The specific response, measured by IFN-γ production upon Mycobacterium tuberculosis stimulation, is associated positively with Ruminococcus and Eggerthella lenta. The identified immunomodulatory taxa also have the strongest effects on circulating metabolites, with Roseburia affecting phenylalanine metabolism. This is corroborated by abundances of relevant enzymes, suggesting alternate phenylalanine metabolism modules are activated in a Roseburia species-dependent manner.

CONCLUSIONS

Variability in cytokine production after BCG vaccination is associated with the abundance of microbial genomes, which in turn affect or produce metabolites in circulation. Roseburia is found to alter both trained immune responses and phenylalanine metabolism, revealing microbes and microbial products that may alter BCG-induced immunity. Together, our findings contribute to the understanding of specific and trained immune responses after BCG vaccination.

Microplastics in the human digestive environment: A focus on the potential and challenges facing in vitro gut model development

Plastic pollution is a major issue worldwide, generating massive amounts of smaller plastic particles, including microplastics (MPs). Their ubiquitous nature in the environment but also in foodstuff and consumer packaged goods has revealed potential threats to humans who can be contaminated mainly through air, food and water consumption. In this review, the current literature on human exposure to MPs is summarized with a focus on the gastrointestinal tract as portal of entry. Then, we discuss the vector effect of MPs, in their pristine versus weathered forms, with well-known contaminants as heavy metals and chemicals, or more emerging ones as antibiotics or microbial pathogens, like Pseudomonas spp., Vibrio spp., Campylobacter spp. and Escherichia coli. Comprehensive knowledge on MP fate in the gastrointestinal tract and their potential impact on gut homeostasis disruption, including gut microbiota, mucus and epithelial barrier, is reported in vitro and in vivo in mammals. Special emphasis is given on the crucial need of developing robust in vitro gut models to adequately simulate human digestive physiology and absorption processes. Finally, this review points out future research directions on MPs in human intestinal health.

Novel bile acid biosynthetic pathways are enriched in the microbiome of centenarians

Centenarians have a decreased susceptibility to ageing-associated illnesses, chronic inflammation and infectious diseases^1-3. Here we show that centenarians have a distinct gut microbiome that is enriched in microorganisms that are capable of generating unique secondary bile acids, including various isoforms of lithocholic acid (LCA): iso-, 3-oxo-, allo-, 3-oxoallo- and isoallolithocholic acid. Among these bile acids, the biosynthetic pathway for isoalloLCA had not been described previously. By screening 68 bacterial isolates from the faecal microbiota of a centenarian, we identified Odoribacteraceae strains as effective producers of isoalloLCA both in vitro and in vivo. Furthermore, we found that the enzymes 5α-reductase (5AR) and 3β-hydroxysteroid dehydrogenase (3β-HSDH) were responsible for the production of isoalloLCA. IsoalloLCA exerted potent antimicrobial effects against Gram-positive (but not Gram-negative) multidrug-resistant pathogens, including Clostridioides difficile and Enterococcus faecium. These findings suggest that the metabolism of specific bile acids may be involved in reducing the risk of infection with pathobionts, thereby potentially contributing to the maintenance of intestinal homeostasis.

Multi-omics reveal microbial determinants impacting responses to biologic therapies in inflammatory bowel disease

The intestinal microbiome is a key determinant of responses to biologic therapy in inflammatory bowel disease (IBD). However, diverse therapeutics and variable responses among IBD patients have posed challenges in predicting clinical therapeutic success. In this prospective study, we profiled baseline stool and blood in patients with moderate-to-severe Crohn's disease or ulcerative colitis initiating anti-cytokine therapy (anti-TNF or -IL12/23) or anti-integrin therapy. Patients were assessed at 14 weeks for clinical remission and 52 weeks for clinical and endoscopic remission. Baseline microbial richness indicated preferential responses to anti-cytokine therapy and correlated with the abundance of microbial species capable of 7α/β-dehydroxylation of primary to secondary bile acids. Serum signatures of immune proteins reflecting microbial diversity identified patients more likely to achieve remission with anti-cytokine therapy. Remission-associated multi-omic profiles were unique to each therapeutic class. These profiles may facilitate a priori determination of optimal therapeutics for patients and serve as targets for newer therapies.

Alterations in bile acid metabolizing gut microbiota and specific bile acid genes as a precision medicine to subclassify NAFLD

Multiple mechanisms for the gut microbiome contributing to the pathogenesis of nonalcoholic fatty liver disease (NAFLD) have been implicated. Here, we aim to investigate the contribution and potential application for altered bile acids (BA) metabolizing microbes in NAFLD by post hoc analysis of whole metagenome sequencing (WMS) data. The discovery cohort consisted of 86 well-characterized patients with biopsy-proven NAFLD and 38 healthy controls. Assembly-based analysis was performed to identify BA-metabolizing microbes. Statistical tests, feature selection, and microbial coabundance analysis were integrated to identify microbial alterations and markers in NAFLD. An independent validation cohort was subjected to similar analyses. NAFLD microbiota exhibited decreased diversity and microbial associations. We established a classifier model with 53 differential species exhibiting a robust diagnostic accuracy [area under the receiver-operator curve (AUC) = 0.97] for detecting NAFLD. Next, eight important differential pathway markers including secondary BA biosynthesis were identified. Specifically, increased abundance of 7α-hydroxysteroid dehydrogenase (7α-HSDH), 3α-hydroxysteroid dehydrogenase (baiA), and bile acid-coenzyme A ligase (baiB) was detected in NAFLD. Furthermore, 10 of 50 BA-metabolizing metagenome-assembled genomes (MAGs) from Bacteroides ovatus and Eubacterium biforme were dominant in NAFLD and interplayed as a synergetic ecological guild. Importantly, two subtypes of patients with NAFLD were observed according to secondary BA metabolism potentials. Elevated capability for secondary BA biosynthesis was also observed in the validation cohort. These bacterial BA-metabolizing genes and microbes identified in this study may serve as disease markers. Microbial differences in BA-metabolism and strain-specific differences among patients highlight the potential for precision medicine in NAFLD treatment.

Antibiotic resistance: Time of synthesis in a post-genomic age

Antibiotic resistance has been highlighted by international organizations, including World Health Organization, World Bank and United Nations, as one of the most relevant global health problems. Classical approaches to study this problem have focused in infected humans, mainly at hospitals. Nevertheless, antibiotic resistance can expand through different ecosystems and geographical allocations, hence constituting a One-Health, Global-Health problem, requiring specific integrative analytic tools. Antibiotic resistance evolution and transmission are multilayer, hierarchically organized processes with several elements (from genes to the whole microbiome) involved. However, their study has been traditionally gene-centric, each element independently studied. The development of robust-economically affordable whole genome sequencing approaches, as well as other -omic techniques as transcriptomics and proteomics, is changing this panorama. These technologies allow the description of a system, either a cell or a microbiome as a whole, overcoming the problems associated with gene-centric approaches. We are currently at the time of combining the information derived from -omic studies to have a more holistic view of the evolution and spread of antibiotic resistance. This synthesis process requires the accurate integration of -omic information into computational models that serve to analyse the causes and the consequences of acquiring AR, fed by curated databases capable of identifying the elements involved in the acquisition of resistance. In this review, we analyse the capacities and drawbacks of the tools that are currently in use for the global analysis of AR, aiming to identify the more useful targets for effective corrective interventions.

Improved metagenome binning and assembly using deep variational autoencoders

Despite recent advances in metagenomic binning, reconstruction of microbial species from metagenomics data remains challenging. Here we develop variational autoencoders for metagenomic binning (VAMB), a program that uses deep variational autoencoders to encode sequence coabundance and k-mer distribution information before clustering. We show that a variational autoencoder is able to integrate these two distinct data types without any previous knowledge of the datasets. VAMB outperforms existing state-of-the-art binners, reconstructing 29-98% and 45% more near-complete (NC) genomes on simulated and real data, respectively. Furthermore, VAMB is able to separate closely related strains up to 99.5% average nucleotide identity (ANI), and reconstructed 255 and 91 NC Bacteroides vulgatus and Bacteroides dorei sample-specific genomes as two distinct clusters from a dataset of 1,000 human gut microbiome samples. We use 2,606 NC bins from this dataset to show that species of the human gut microbiome have different geographical distribution patterns. VAMB can be run on standard hardware and is freely available at https://github.com/RasmussenLab/vamb .

Diet and gut microbiome interactions of relevance for symptoms in irritable bowel syndrome

BACKGROUND

While several studies have documented associations between dietary habits and microbiota composition and function in healthy individuals, no study explored these associations in patients with irritable bowel syndrome (IBS), and especially with symptoms.

METHODS

Here, we used a novel approach that combined data from a 4-day food diary, integrated into a food tree, together with gut microbiota (shotgun metagenomic) for individuals with IBS (N = 149) and healthy controls (N = 52). Paired microbiota and food-based trees allowed us to detect new associations between subspecies and diet. Combining co-inertia analysis and linear regression models, exhaled gas levels and symptom severity could be predicted from metagenomic and dietary data.

RESULTS

We showed that individuals with severe IBS are characterized by a higher intake of poorer-quality food items during their main meals. Our analysis suggested that covariations between gut microbiota at subspecies level and diet could be explained with IBS symptom severity, exhaled gas, glycan metabolism, and meat/plant ratio. We provided evidence that IBS severity is associated with altered gut microbiota hydrogen function in correlation with microbiota enzymes involved in animal carbohydrate metabolism.

CONCLUSIONS

Our study provides an unprecedented resolution of diet-microbiota-symptom interactions and ultimately guides new interventional studies that aim to identify gut microbiome-based nutritional recommendations for the management of gastrointestinal symptoms.

TRIAL REGISTRATION

This trial was registered on the ClinicalTrials.gov, with the registration number NCT01252550 , on 3rd December 2010. Video abstract.

Mediterranean diet consumption affects the endocannabinoid system in overweight and obese subjects: possible links with gut microbiome, insulin resistance and inflammation

Purpose

To investigate whether a Mediterranean diet (MD) affected the plasma concentrations of endocannabinoids (ECs), N-acylethanolamines (NAEs) and their specific ratios in subjects with lifestyle risk factors for metabolic diseases. To identify the relationship between circulating levels of these compounds and gut microbiome, insulin resistance and systemic inflammation.

Methods

A parallel 8-week randomised controlled trial was performed involving 82 overweight and obese subjects aged (mean ± SEM) 43 ± 1.4 years with a BMI of 31.1 ± 0.5 kg/m², habitual Western diet (CT) and sedentary lifestyle. Subjects were randomised to consume an MD tailored to their habitual energy and macronutrient intake (n = 43) or to maintain their habitual diet (n = 39). Endocannabinoids and endocannabinoid-like molecules, metabolic and inflammatory markers and gut microbiome were monitored over the study period.

Results

The MD intervention lowered plasma arachidonoylethanolamide (AEA, p = 0.02), increased plasma oleoylethanolamide/palmitoylethanolamide (OEA/PEA, p = 0.009) and OEA/AEA (p = 0.006) and increased faecal Akkermansia muciniphila (p = 0.026) independent of body weight changes. OEA/PEA positively correlated with abundance of key microbial players in diet–gut–health interplay and MD adherence. Following an MD, individuals with low-plasma OEA/PEA at baseline decreased homeostatic model assessment of insulin resistance index (p = 0.01), while individuals with high-plasma OEA/PEA decreased serum high-sensitive C-reactive protein (p = 0.02).

Conclusions

We demonstrated that a switch from a CT to an isocaloric MD affects the endocannabinoid system and increases A. muciniphila abundance in the gut independently of body weight changes. Endocannabinoid tone and microbiome functionality at baseline drives an individualised response to an MD in ameliorating insulin sensitivity and inflammation.

Clinical Trial Registry number and website NCT03071718; www.clinicaltrials.gov

Supplementary Information

The online version contains supplementary material available at 10.1007/s00394-021-02538-8.

Integrating pan-genome with metagenome for microbial community profiling

Advances in sequencing technology have led to the increased availability of genomes and metagenomes, which has greatly facilitated microbial pan-genome and metagenome analysis in the community. In line with this trend, studies on microbial genomes and phenotypes have gradually shifted from individuals to environmental communities.

Pan-genomics and metagenomics are powerful strategies for in-depth profiling study of microbial communities. Pan-genomics focuses on genetic diversity, dynamics, and phylogeny at the multi-genome level, while metagenomics profiles the distribution and function of culture-free microbial communities in special environments. Combining pan-genome and metagenome analysis can reveal the microbial complicated connections from an individual complete genome to a mixture of genomes, thereby extending the catalog of traditional individual genomic profile to community microbial profile. Therefore, the combination of pan-genome and metagenome approaches has become a promising method to track the sources of various microbes and decipher the population-level evolution and ecosystem functions.

This review summarized the pan-genome and metagenome approaches, the combined strategies of pan-genome and metagenome, and applications of these combined strategies in studies of microbial dynamics, evolution, and function in communities. We discussed emerging strategies for the study of microbial communities that integrate information in both pan-genome and metagenome. We emphasized studies in which the integrating pan-genome with metagenome approach improved the understanding of models of microbial community profiles, both structural and functional. Finally, we illustrated future perspectives of microbial community profile: more advanced analytical techniques, including big-data based artificial intelligence, will lead to an even better understanding of the patterns of microbial communities.

A comprehensive evaluation of binning methods to recover human gut microbial species from a non-redundant reference gene catalog

The human gut microbiota performs functions that are essential for the maintenance of the host physiology. However, characterizing the functioning of microbial communities in relation to the host remains challenging in reference-based metagenomic analyses. Indeed, as taxonomic and functional analyses are performed independently, the link between genes and species remains unclear. Although a first set of species-level bins was built by clustering co-abundant genes, no reference bin set is established on the most used gut microbiota catalog, the Integrated Gene Catalog (IGC). With the aim to identify the best suitable method to group the IGC genes, we benchmarked nine taxonomy-independent binners implementing abundance-based, hybrid and integrative approaches. To this purpose, we designed a simulated non-redundant gene catalog (SGC) and computed adapted assessment metrics. Overall, the best trade-off between the main metrics is reached by an integrative binner. For each approach, we then compared the results of the best-performing binner with our expected community structures and applied the method to the IGC. The three approaches are distinguished by specific advantages, and by inherent or scalability limitations. Hybrid and integrative binners show promising and potentially complementary results but require improvements to be used on the IGC to recover human gut microbial species.

Congruent microbiome signatures in fibrosis-prone autoimmune diseases: IgG4-related disease and systemic sclerosis

BACKGROUND

Immunoglobulin G4-related disease (IgG4-RD) and systemic sclerosis (SSc) are rare autoimmune diseases characterized by the presence of CD4+ cytotoxic T cells in the blood as well as inflammation and fibrosis in various organs, but they have no established etiologies. Similar to other autoimmune diseases, the gut microbiome might encode disease-triggering or disease-sustaining factors.

METHODS

The gut microbiomes from IgG4-RD and SSc patients as well as healthy individuals with no recent antibiotic treatment were studied by metagenomic sequencing of stool DNA. De novo assembly-based taxonomic and functional characterization, followed by association and accessory gene set enrichment analysis, were applied to describe microbiome changes associated with both diseases.

RESULTS

Microbiomes of IgG4-RD and SSc patients distinctly separated from those of healthy controls: numerous opportunistic pathogenic Clostridium and typically oral Streptococcus species were significantly overabundant, while Alistipes, Bacteroides, and butyrate-producing species were depleted in the two diseases compared to healthy controls. Accessory gene content analysis in these species revealed an enrichment of Th17-activating Eggerthella lenta strains in IgG4-RD and SSc and a preferential colonization of a homocysteine-producing strain of Clostridium bolteae in SSc. Overabundance of the classical mevalonate pathway, hydroxyproline dehydratase, and fibronectin-binding protein in disease microbiomes reflects potential functional differences in host immune recognition and extracellular matrix utilization associated with fibrosis. Strikingly, the majority of species that were differentially abundant in IgG4-RD and SSc compared to controls showed the same directionality in both diseases. Compared with multiple sclerosis and rheumatoid arthritis, the gut microbiomes of IgG4-RD and SSc showed similar signatures; in contrast, the most differentially abundant taxa were not the facultative anaerobes consistently identified in inflammatory bowel diseases, suggesting the microbial signatures of IgG4-RD and SSc do not result from mucosal inflammation and decreased anaerobism.

CONCLUSIONS

These results provide an initial characterization of gut microbiome ecology in fibrosis-prone IgG4-RD and SSc and reveal microbial functions that offer insights into the pathophysiology of these rare diseases.

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.