155 research outputs found
Studying the gut virome in the metagenomic era:challenges and perspectives
The human gut harbors a complex ecosystem of microorganisms, including bacteria and viruses. With the rise of next-generation sequencing technologies, we have seen a quantum leap in the study of humangut-inhabiting bacteria, yet the viruses that infect these bacteria, known as bacteriophages, remain underexplored. In this review, we focus on what is known about the role of bacteriophages in human health and the technical challenges involved in studying the gut virome, of which they are a major component. Lastly, we discuss what can be learned from studies of bacteriophages in other ecosystems
Large-scale association analyses identify host factors influencing human gut microbiome composition
Detection of stable community structures within gut microbiota co-occurrence networks from different human populations
Microbes in the gut microbiome form sub-communities based on shared niche specialisations and specific interactions between individual taxa. The inter-microbial relationships that define these communities can be inferred from the co-occurrence of taxa across multiple samples. Here, we present an approach to identify comparable communities within different gut microbiota co-occurrence networks, and demonstrate its use by comparing the gut microbiota community structures of three geographically diverse populations. We combine gut microbiota profiles from 2,764 British, 1,023 Dutch, and 639 Israeli individuals, derive co-occurrence networks between their operational taxonomic units, and detect comparable communities within them. Comparing populations we find that community structure is significantly more similar between datasets than expected by chance. Mapping communities across the datasets, we also show that communities can have similar associations to host phenotypes in different populations. This study shows that the community structure within the gut microbiota is stable across populations, and describes a novel approach that facilitates comparative community-centric microbiome analyses
Discovery, diversity, and functional associations of crAss-like phages in human gut metagenomes from four Dutch cohorts
The crAss-like phages are a diverse group of related viruses that includes some of the most abundant viruses of the human gut. To explore their diversity and functional role in human population and clinical cohorts, we analyze gut metagenomic data collected from 1,950 individuals from the Netherlands. We identify 1,556 crAss-like phage genomes, including 125 species-level and 32 genus-level clusters absent from the reference databases used. Analysis of their genomic features shows that closely related crAss-like phages can possess strikingly divergent regions responsible for transcription, presumably acquired through recombination. Prediction of crAss-like phage hosts points primarily to bacteria of the phylum Bacteroidetes, consistent with previous reports. Finally, we explore the temporal stability of crAss-like phages over a 4-year period and identify associations between the abundance of crAss-like phages and several human phenotypes, including depletion of crAss-like phages in inflammatory bowel disease patients
Marked Changes in Gut Microbiota in Cardio-Surgical Intensive Care Patients:A Longitudinal Cohort Study
Background: Virtually no studies on the dynamics of the intestinal microbiota in patients admitted to the intensive care unit (ICU) are published, despite the increasingly recognized important role of microbiota on human physiology. Critical care patients undergo treatments that are known to influence the microbiota. However, dynamics and extent of such changes are not yet fully understood. To address this topic, we analyzed the microbiota before, during and after planned major cardio surgery that, for the first time, allowed us to follow the microbial dynamics of critical care patients. In this prospective, observational, longitudinal, single center study, we analyzed the fecal microbiota using 16S rRNA gene sequencing. Results: Samples of 97 patients admitted between April 2015 and November 2016 were included. In 32 patients, data of all three time points (before, during and after admission) were available for analysis. We found a large intra-individual variation in composition of gut microbiota. During admission, a significant change in microbial composition occurred in most patients, with a significant increase in pathobionts combined with a decrease in strictly anaerobic gut bacteria, typically beneficial for health. A lower bacterial diversity during admission was associated with longer hospitalization. In most patients analyzed at all three time points, the change in microbiota during hospital stay reverted to the original composition post-discharge. Conclusions: Our study shows that, even with a short ICU stay, patients present a significant change in microbial composition shortly after admission. The unique longitudinal setup of this study displayed a restoration of the microbiota in most patients to baseline composition post-discharge, which demonstrated its great restorative capacity. A relative decrease in benign or even beneficial bacteria and increase of pathobionts shifts the microbial balance in the gut, which could have clinical relevance. In future studies, the microbiota of ICU patients should be considered a good target for optimisation
A combination of fecal calprotectin and human beta-defensin 2 facilitates diagnosis and monitoring of inflammatory bowel disease
Inflammatory bowel disease (IBD) and irritable bowel syndrome (IBS) show a large overlap in clinical presentation, which presents diagnostic challenges. As a consequence, invasive and burdensome endoscopies are often used to distinguish between IBD and IBS. Here, we aimed to develop a noninvasive fecal test that can distinguish between IBD and IBS and reduce the number of endoscopies. We used shotgun metagenomic sequencing to analyze the composition and function of gut microbiota of 169 IBS patients, 447 IBD patients and 1044 population controls and measured fecal Calprotectin (FCal), human beta defensin 2 (HBD2), and chromogranin A (CgA) in these samples. These measurements were used to construct training sets (75% of data) for logistic regression and machine learning models to differentiate IBS from IBD and inactive from active IBD. The results were replicated on test sets (remaining 25% of the data) and microbiome data obtained using 16S sequencing. Fecal HBD2 showed high sensitivity and specificity for differentiating between IBD and IBS (sensitivity = 0.89, specificity = 0.76), while the inclusion of microbiome data with biomarkers (HBD2 and FCal) showed a potential for improvement in predictive power (optimal sensitivity = 0.87, specificity = 0.93). Shotgun sequencing-based models produced comparable results using 16S-sequencing data. HBD2 and FCal were found to have predictive power for IBD disease activity (AUC approximate to 0.7). HBD2 is a novel biomarker for IBD in patients with gastro-intestinal complaints, especially when used in combination with FCal and potentially in combination with gut microbiome data
Gut Microbiota Composition of Biliary Atresia Patients Before Kasai Portoenterostomy Associates With Long-term Outcome
BACKGROUND AND AIMS: Biliary atresia (BA) is a cholestatic, fibro-obliterative cholangiopathy of unknown etiology. BA is primarily treated by a surgical approach, i.e. the Kasai portoenterostomy (KPE), to obtain clearance of jaundice (COJ). The gut microbiota (GM) composition has been associated with the course of several cholestatic liver diseases. It is largely unknown, however, whether GM composition associates with the outcome of KPE. We compared the GM composition of BA patients and controls and assessed if GM composition before KPE was related to COJ after KPE. METHODS: We compared feces of term born BA patients before KPE and controls (patients undergoing inguinal hernia repair) by 16S rRNA sequencing. Composition and alpha diversity of the GM were compared between BA and controls before KPE and after KPE, between patients with COJ vs. without COJ (total serum bilirubin < or ≥ 20 μmol/L < 6mo post-KPE). RESULTS: Alpha diversity was comparable between BA (n = 12, age 1.6[1.3-1.8]mo) and controls (n = 6, age 2.0[1.4-2.1]mo; P = 0.22). Compared to controls, BA patients had lower abundances of Bifidobacteriaceae (β=-1.98, P < 0.001) and Lachnospiraceae (β=-1.84, P = 0.007), and higher abundances of Streptococcus (β=1.13, P = 0.003). The alpha diversity prior to KPE correlated negatively with COJ (R = -0.63, P = 0.03). Lower alpha diversity pre-KPE was associated with COJ [+] (βlogit = -0.64, P = 0.04). We observed greater abundances of genus Acinetobacter (β=1.27, P = 0.03) and family Clostridiaceae (β=1.45, P = 0.03) and lower abundances of the family Enterobacteriaceae, (genera Klebsiella (β=-1.21, P = 0.01), Salmonella (β=-1.57, P = 0.02)) in COJ [+] vs. COJ [-]. CONCLUSIONS: The gut microbiota of biliary atresia patients prior to Kasai portoenterostomy associates with outcome, clearance of jaundice, suggestive of predictive and mechanistic roles of the gut microbiota composition in bile homeostasis
Integrated fecal microbiome–metabolome signatures reflect stress and serotonin metabolism in irritable bowel syndrome
To gain insight into the complex microbiome-gut-brain axis in irritable bowel syndrome (IBS) several modalities of biological and clinical data must be combined. We aimed to identify profiles of faecal microbiota and metabolites associated with IBS and to delineate specific phenotypes of IBS that represent potential pathophysiological mechanisms. Faecal metabolites were measured using proton Nuclear Magnetic Resonance (1H-NMR) spectroscopy and gut microbiome using Shotgun Metagenomic Sequencing (MGS) in a combined dataset of 142 IBS patients and 120 healthy controls (HC) with extensive clinical, biological and phenotype information. Data were analysed using support vector classification and regression and kernel t-SNE. Microbiome and metabolome profiles could distinguish IBS and HC with an area-under-the-receiver-operator-curve (AUC) of 77.3% and 79.5%, respectively, but this could be improved by combining microbiota and metabolites to 83.6%. No significant differences in predictive ability of the microbiome-metabolome data were observed between the three classical, stool pattern-based, IBS subtypes. However, unsupervised clustering showed distinct subsets of IBS patients based on faecal microbiome-metabolome data. These clusters could be related plasma levels of serotonin and its metabolite 5-hydroxyindoleacetate, effects of psychological stress on gastrointestinal symptoms, onset of IBS after stressful events, medical history of previous abdominal surgery, dietary caloric intake and IBS symptom duration. Furthermore, pathways in metabolic reaction networks were integrated with microbiota data, that reflect the host-microbiome interactions in IBS. The identified microbiome-metabolome signatures for IBS, associated with altered serotonin metabolism and unfavourable stress-response related to gastrointestinal symptoms, support the microbiota-gut-brain link in the pathogenesis of IBS
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