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Sheth, R. U.

Publications and source records attributed to Sheth, R. U..

5 recordsLinked to original sources

SAMPL-seq reveals micron-scale spatial hubs in the human gut microbiome

The local arrangement of microbes can profoundly impact community assembly, function, and stability. To date, little is known about the spatial organization of the human gut microbiome. Here, we describe a high-throughput and streamlined method, dubbed SAMPL-seq, that samples microbial composition of micron-scale sub-communities with split-and-pool barcoding to capture spatial colocalization in a complex consortium. SAMPL-seq analysis of the gut microbiome of healthy humans identified bacterial taxa pairs that consistently co-occurred both over time and across multiple individuals. These colocalized microbes organize into spatially distinct groups or "spatial hubs" dominated by Bacteroideceae, Ruminococceae, and Lachnospiraceae families. From a dietary perturbation using inulin, we observed reversible spatial rearrangement of the gut microbiome, where specific taxa form new local partnerships. Spatial metagenomics using SAMPL-seq can unlock new insights to improve the study of microbial communities. One Sentence SummaryHigh throughput micron-scale subcommunity sampling and sequencing identifies distinct spatial associations of gut bacteria within and across individuals.

systems biology↗

Spatiotemporal dynamics during niche remodeling by super-colonizing microbiota in the mammalian gut

While fecal microbiota transplantation (FMT) has been shown to be effective in reversing gut dysbiosis, we lack an understanding for the fundamental processes underlying microbial engraftment in the mammalian gut. Here, we explored a murine gut colonization model leveraging natural inter-individual variations in gut microbiomes to elucidate the spatiotemporal dynamics of FMT. We identified a natural super-donor consortium that universally engrafts into diverse recipients and resists reciprocal colonization. Temporal profiling of the gut microbiome showed an ordered succession of rapid engraftment by early colonizers within 72 hours followed by a slower emergence of late colonizers over 15-30 days. Moreover, engraftment was localized to distinct compartments of the gastrointestinal tract in a species-specific manner. Spatial metagenomic characterization suggested engraftment was mediated by simultaneous transfer of spatially co-localizing species from the super-donor consortia. These results offer a mechanism of super-donor colonization by which nutritional niches are expanded in a spatiotemporally- dependent manner.

microbiology↗

Real-time capture of horizontal gene transfers from gut microbiota by engineered CRISPR-Cas acquisition

Horizontal gene transfer (HGT) is central to the adaptation and evolution of bacteria. However, our knowledge about the flow of genetic material within complex microbiomes is lacking; most studies of HGT rely on bioinformatic analyses of genetic elements maintained on evolutionary timescales or experimental measurements of phenotypically trackable markers (e.g. antibiotic resistance). Consequently, our knowledge of the capacity and dynamics of HGT in complex communities is limited. Here, we utilize the CRISPR-Cas spacer acquisition process to detect HGT events from complex microbiota in real-time and at nucleotide resolution. In this system, a recording strain is exposed to a microbial sample, spacers are acquired from foreign transferred elements and permanently stored in genomic CRISPR arrays. Subsequently, sequencing and analysis of these spacers enables identification of the transferred elements. This approach allowed us to quantify transfer frequencies of individual mobile elements without the need for phenotypic markers or post-transfer replication. We show that HGT in human clinical fecal samples can be extensive and rapid, often involving multiple different plasmid types, with the IncX type being the most actively transferred. Importantly, the vast majority of transferred elements did not carry readily selectable phenotypic markers, highlighting the utility of our approach to reveal previously hidden real-time dynamics of mobile gene pools within complex microbiomes.

microbiology↗

Macroecological relationships in the dynamics of gut microbiota

The gut microbiome is now widely recognized as a dynamic ecosystem that plays an important role in health and disease1. While current sequencing technologies make it possible to estimate relative abundances of host-associated bacteria over time2, 3, the biological processes governing their dynamics remain poorly understood. Therefore, as in other ecological systems4, 5, it is important to identify quantitative relationships describing global aspects of gut microbiota dynamics. Here we use multiple high-resolution time series data obtained from humans and mice6-8 to demonstrate that despite their inherent complexity, gut microbiota dynamics can be characterized by several robust scaling relationships. Interestingly, these patterns are highly similar to those previously observed across diverse ecological communities and economic systems, including the temporal fluctuations of animal and plant populations9-12 and the performance of publicly traded companies13. Specifically, we find power law relationships describing short- and long-term changes in gut microbiota abundances, species residence and return times, and the connection between the mean and variance of species abundances. The observed scaling relationships are altered in mice receiving different diets and affected by context-specific perturbations in humans. We use these macroecological relationships to reveal specific bacterial taxa whose dynamics are significantly affected by dietary and environmental changes. Overall, our results suggest that a quantitative macroecological framework will be important for characterizing and understanding complex dynamics of microbial communities.

microbiology↗

Quantification of human gut microbiota variability using replicate sampling and spike-in sequencing

Metagenomic sequencing has enabled detailed investigation of diverse microbial communities, but understanding their spatiotemporal dynamics remains an important challenge. Here we present DIVERS, a widely applicable method based on replicate sampling and spike-in sequencing that quantifies the contributions of temporal dynamics, spatial sampling variability and technical noise to the variances and covariances of absolute bacterial abundances. Using high resolution time series profiling, we apply DIVERS to the human gut microbiome. Our method reveals complex spatiotemporal dynamics of individual gut bacteria and unmasks key features of their behavior hidden from previous analyses.

microbiology↗