We developed a method—multi-taxon INsertion Sequencing (INSeq)—for monitoring the behavior of tens of thousands of transposon (Tn) mutants of multiple bacterial species and strains simultaneously in the guts of gnotobiotic mice. We focused on four prominent human gut Bacteroides: one strain of B. cellulosilyticus, one strain of B. ovatus, and two strains of B. thetaiotaomicron. INSeq libraries, each composed of 87,000 to 167,000 isogenic Tn mutant strains, were produced (single site of Tn insertion per mutant strain; a total of 11 to 26 Tn insertions represented in the library per gene; and 82 to 92% genes covered per genome). The four mutant libraries were introduced into germ-free mice together with 11 wild-type species commonly present in the human gut microbiota. Animals were given a diet rich in fat and simple sugars but devoid of complex polysaccharides [diet 1 (D1)] or one rich in plant polysaccharides and low in fat (D2), either monotonously or in the sequence D1-D2-D1 or D2-D1-D2. Wecalculated a “fitness index” for each gene on the basis of the relative abundance of its INSeq reads in the fecal or cecal microbiota compared with the input library. In vivo INSeq data were correlated with INSeq data generated from organisms cultured under defined in vitro conditions; microbial RNA-seq profiling of the community’s metatranscriptome; and reconstructions of metabolic pathways, regulons, and polysaccharide utilization loci. On the basis of the results, we designed a prebiotic intervention.
In this study, we employed an in silico screening approach to mine potential bacteriocin clusters in genome-sequenced isolates from the gastrointestinal tract (GIT). More specifically, the bacteriocin genome-mining tool BAGEL3 was used to identify potential bacteriocin producers in the genomes of the GIT subset of the Human Microbiome Project’s reference genome database. Each of the identified gene clusters were manually annotated and potential bacteriocin-associated genes were evaluated.
we administered a second-generation cephalosporin, cefprozil, to healthy volunteers. Stool samples gathered before antibiotic exposure, at the end of the treatment and 3 months later were analysed using shotgun metagenomic sequencing.
We show that standard antibiotic treatment can alter the gut microbiome in a specific, reproducible and predictable manner.
Resistance genes that were not detectable prior to treatment were observed after a 7-day course of antibiotic administration. Specifically, point mutations in beta-lactamase blaCfxA-6 were enriched after antibiotic treatment in several participants.
Here we adopted a dynamic systems approach and found that heterogeneity in the interspecific interactions or the presence of strongly interacting species is sufficient to explain community types, independent of the topology of the underlying ecological network. By controlling the presence or absence of these strongly interacting species we can steer the microbial ecosystem to any desired community type.
We analyzed 7.2 terabases of metagenomic data from 243 Tara Oceans samples from 68 locations in epipelagic and mesopelagic waters across the globe to generate an ocean microbial reference gene catalog with >40 million nonredundant, mostly novel sequences from viruses, prokaryotes, and picoeukaryotes.
The problem is that differential abundance analysis looks at each microbe individually without considering the possible associations the microbes may have with each other. This is not favorable, since microbes rarely act individually but within intricate communities involving other microbes.
In this research paper, the proposed method AdaLassop is an augmented variable selection technique that overcomes the misgivings of Lasso and Elastic Net. It provides researchers with a holistic model that takes into account the effects of selected biomarkers in presence of other important biomarkers. For AdaLassop, variable selection on sparse ultra-high dimensional data is implemented using the Adaptive Lasso with p-values extracted from Zero Inflated Negative Binomial Regressions as augmented weights.
Animals and plants are no longer heralded as autonomous entities but rather as biomolecular networks composed of the host plus its associated microbes, i.e., "holobionts." As such, their collective genomes forge a "hologenome," and models of animal and plant biology that do not account for these intergenomic associations are incomplete. Here, we integrate these concepts into historical and contemporary visions of biology and summarize a predictive and refutable framework for their evaluation. Specifically, we present ten principles that clarify and append what these concepts are and are not, explain how they both support and extend existing theory in the life sciences, and discuss their potential ramifications for the multifaceted approaches of zoology and botany.
, the majority of AR genes were not previously classified as such, but were similar to proteins such as transport pumps, oxidoreductases, and hydrolases. Furthermore, 44% of the genes conferring antibiotic resistance were found in abundant marine taxa (e.g., Pelagibacter, Prochlorococcus, Vibrio, etc.).
Obesity, diabetes, and metabolic syndrome result from complex interactions between genetic and environmental factors, including the gut microbiota. To dissect these interactions, we utilized three commonly used inbred strains of mice—obesity/diabetes-prone C57Bl/6J mice, obesity/diabetes-resistant 129S1/SvImJ from Jackson Laboratory, and obesity-prone but diabetes-resistant 129S6/SvEvTac from Taconic—plus three derivative lines generated by breeding these strains in a new, common environment. Analysis of metabolic parameters and gut microbiota in all strains and their environmentally normalized derivatives revealed strong interactions between microbiota, diet, breeding site, and metabolic phenotype. Strain-dependent and strain-independent correlations were found between specific microbiota and phenotypes, some of which could be transferred to germ-free recipient animals by fecal transplantation. Environmental reprogramming of microbiota resulted in 129S6/SvEvTac becoming obesity resistant. Thus, development of obesity/metabolic syndrome is the result of interactions between gut microbiota, host genetics, and diet. In permissive genetic backgrounds, environmental reprograming of microbiota can ameliorate development of metabolic syndrome.
Here, we used explorative shotgun metagenomic sequencing to address the abundance of >300 antibiotic resistance genes in fecal specimens from 35 Swedish students taken before and after exchange programs on the Indian peninsula or in central Africa.
Alexander Tyakht's insight:
shotgun metagenomics for resistome. ne hodite deti v Afriku gulyat'
We applied metabolic oligosaccharide engineering and bioorthogonal click chemistry to label various commensal anaerobes, including Bacteroides fragilis, a common and immunologically important commensal. We studied the dissemination of B. fragilis after acute peritonitis and characterized the interactions of the intact microbe and its polysaccharide components in myeloid and B cell lineages. We were able to assess the distribution and colonization of labeled B. fragilis along the intestine, as well as niche competition after coadministration of multiple species of the microbiota. We also fluorescently labeled nine additional commensals (eight anaerobic and one microaerophilic) from three phyla common in the gut—Bacteroidetes, Firmicutes and Proteobacteria—as well as one aerobic pathogen (Staphylococcus aureus). This strategy permits visualization of the anaerobic microbial niche by various methods, including intravital two-photon microscopy and non-invasive whole-body imaging, and can be used to study microbial colonization and host–microbe interactions in real time.
We demonstrate via 16S rRNA gene pyrosequencing of 922 specimens from 58 subjects that the gut microbiota of premature infants residing in a tightly controlled microbial environment progresses through a choreographed succession of bacterial classes from Bacilli to Gammaproteobacteria to Clostridia, interrupted by abrupt population changes. As infants approach 33–36 wk postconceptional age (corresponding to the third to the twelfth weeks of life depending on gestational age at birth), the gut is well colonized by anaerobes. Antibiotics, vaginal vs. Caesarian birth, diet, and age of the infants when sampled influence the pace, but not the sequence, of progression.
Using a combination of genomics, enzymology and crystallography, we show that the mucin-degrader R. gnavus ATCC 29149 strain produces an intramolecular trans-sialidase (IT-sialidase) that cleaves off terminal α2-3-linked sialic acid from glycoproteins, releasing 2,7-anhydro-Neu5Ac instead of sialic acid. Evidence of IT-sialidases in human metagenomes indicates that this enzyme occurs in healthy subjects but is more prevalent in IBD metagenomes. Our results uncover a previously unrecognized enzymatic activity in the gut microbiota, which may contribute to the adaptation of intestinal bacteria to the mucosal environment in health and disease.
Alexander Tyakht's insight:
not all Ruminococci are nice - R. gnavus is mucus degrader enriched in IBD - here one of its arms is exposed - IT -sialidase
the mechanism responsible for rhythmicity has not been fully clarified. Here we report that both the host circadian system and host gender influence the rhythmicity of the total load and taxonomic abundances in the fecal microbiota, and that regulation by the host clock is dominant. Disruption of the host circadian clock by deletion of Bmal1 altered the fecal microbial composition in a gender-dependent fashion. Our analyses suggest the need to consider circadian factors and host gender in the design of microbiome studies, and highlight the importance of analyzing absolute abundance in understanding the microbiota.
This review article summarizes data published in the past 30 years that have demonstrated the signaling derived from the gut-liver axis in relation to liver injury and regeneration. Despite many correlative findings, the intricate networks of pathways involved along with a scarcity of mechanistic data urgently require nutrigenomic, metabolomics, and microbiota profiling approaches to provide a deep understanding of the interplay between nutrition, bacteria, and host response.
. Identification of specific effector genes and small molecules improves our understanding of how bacteria might interact with human cells and contribute to both health and disease. The small molecules we isolated, N-acyl-3-hydroxyglycines, resemble endogenously produced N-acyl-amide signaling molecules and were found to activate the human G-protein–coupled receptor (GPCR) GPR132/G2A. G2A has potentially important implications for autoimmune disease and atherosclerosis.
How does maternal stress during pregnancy affect postpartum development? How and when do we acquire our gastrointestinal (GI) microbiota? Does psychological stress affect our microbiota? Can changes in maternal microbiota be vertically transmitted to offspring and can those changes influence brain development? These are questions that Jasarevic et al raise and begin to answer (1).
The humble dust collecting in the average American household harbors a teeming menagerie of bacteria and fungi, and as researchers from the University of Colorado Boulder and North Carolina State University have discovered, it may be able to predict not only the geographic region of a given home, but the gender ratio of the occupants and the presence of a pet as well.
Application of our approaches to human gut-associated metatranscriptomic datasets allowed us to survey antisense transcription for a large number of bacterial species associated with human beings. The ratio of protein coding genes with antisense transcription ranges from zero to 35.8% (median = 10.0%) among 47 species. Our results show that antisense transcription is dynamic, varying between human individuals. Functional enrichment analysis revealed a preference of certain gene functions for antisense transcription, and transposase genes are among the most prominent ones (but we also observed antisense transcription in bacterial house-keeping genes).
Genetics provides a potentially powerful approach to dissect host-gut microbiota interactions. Toward this end, we profiled gut microbiota using 16s rRNA gene sequencing in a panel of 110 diverse inbred strains of mice. This panel has previously been studied for a wide range of metabolic traits and can be used for high resolution association mapping. Using a SNP-based approach with a linear mixed model we estimated the heritability of microbiota composition.
Alexander Tyakht's insight:
In mice - host genetics correlates with microbiome
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