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Biology subjects

Dai, C. L.

Publications and source records attributed to Dai, C. L..

5 recordsLinked to original sources

Genome-microbiome interplay provides insight into the determinants of the human blood metabolome

Variation in the blood metabolome is intimately related to human health. Prior work has shown that host genetics and gut microbiome composition, combined, explain sizable, but orthogonal, components of the overall variance in blood metabolomic profiles. However, few details are known about the interplay between genetics and the microbiome in explaining variation on a metabolite-by-metabolite level. Here, we performed analyses of variance for each of the 945 blood metabolites that were robustly detected across a cohort of 2,049 individuals, while controlling for a number of relevant covariates, like sex, age, and genetic ancestry. Over 60% of the detected blood metabolites were significantly associated with either host genetics or the gut microbiome, with more than half of these associations driven solely by the microbiome and around 30% under hybrid genetic-microbiome control. The variances explained by genetics and the microbiome for each metabolite were indeed largely additive, although subtle, but significant, non-additivity was detected. We found that interaction effects, where a metabolitemicrobe association was specific to a particular genetic background, were quite common, albeit with modest effect sizes. The outputs of our integrated genetic-microbiome regression models provide novel biological insights into the processes governing the composition of the blood metabolome. For example, we found that unconjugated secondary bile acids were solely associated with the microbiome, while their conjugated forms were under strong host genetic control. Overall, our results reveal which components of the blood metabolome are under strong genetic control, which are more dependent on gut microbiome composition, and which are dependent upon both. This knowledge will help to guide targeted interventions designed to alter the composition of the blood metabolome.

systems biology↗

Microbe-seq: high-throughput, single-microbe genomics with strain resolution, applied to a human gut microbiome

We present Microbe-seq, a high-throughput single-microbe method that yields strain-resolved genomes from complex microbial communities. We encapsulate individual microbes into droplets with microfluidics and liberate their DNA, which we amplify, tag with droplet-specific barcodes, and sequence. We use Microbe-seq to explore the human gut microbiome; we collect stool samples from a single individual, sequence over 20,000 microbes, and reconstruct nearly-complete genomes of almost 100 bacterial species, including several with multiple subspecies strains. We use these genomes to probe genomic signatures of microbial interactions: we reconstruct the horizontal gene transfer (HGT) network within the individual and observe far greater exchange within the same bacterial phylum than between different phyla. We probe bacteria-virus interactions; unexpectedly, we identify a significant in vivo association between crAssphage, an abundant bacteriophage, and a single strain of Bacteroides vulgatus. Microbe-seq contributes high-throughput culture-free capabilities to investigate genomic blueprints of complex microbial communities with single-microbe resolution.

microbiology↗

Tracking strains predicts personal microbiomes and reveals recent adaptive evolution

An individuals microbiome consists of a diverse set of bacterial strains that encode rich information on its colonization and evolutionary history. Here, we introduce a versatile and straightforward reference-based strain tracking approach (StrainTrack) that determines whether distinct metagenomes carry closely-related strains based on gene presence and absence profiles. We show that StrainTrack can predict whether two metagenomes originate from the same donor via counting the number of species sharing closely-related strains, achieving >96% specificity, and [~]100% sensitivity. When applied to the metagenomes of adult twins in the TwinsUK registry, we identify six cases of closely-related strains carried by both twins, potentially over decades of colonization.

bioinformatics↗

Choosing Your Battles: Which Resistance Genes Warrant Global Action?

The increasing accumulation of antibiotic resistance genes (ARGs) in pathogens poses a severe threat to the treatment of bacterial infections. However, not all ARGs do not pose the same threats to human health. Here, we present a framework to rank the risk of ARGs based on three factors: \"anthropogenic enrichment\", \"mobility\", and \"host pathogenicity\". The framework is informed by all available bacterial genomes (55,000), plasmids (16,000), integrons (3,000), and 850 metagenomes covering diverse global eco-habitats. The framework prioritizes 3% of all known ARGs in Rank I (the most at risk of dissemination amongst pathogens) and 0.3% of ARGs in Rank II (high potential emergence of new resistance in pathogens). We further validated the framework using a list of 38 ARG families previously identified as high risk by the World Health Organization and published literature, and found that 36 of them were properly identified as top risk (Rank I) in our approach. Furthermore, we identified 43 unreported Rank I ARG families that should be prioritized for public health interventions. Within the same gene family, homologous genes pose different risks, host range, and ecological distributions, indicating the need for high resolution surveillance into their sequence variants. Finally, to help strategize the policy interventions, we studied the impact of industrialization on high risk ARGs in 1,120 human gut microbiome metagenomes of 36 diverse global populations. Our findings suggest that current policies on controlling the clinical antimicrobial consumptions could effectively control Rank I, while greater antibiotic stewardship in veterinary settings could help control Rank II. Overall, our framework offered a straightforward evaluation of the risk posed by ARGs, and prioritized a shortlist of current and emerging threats for global action to fight ARGs.

microbiology↗

Population histories of the United States revealed through fine-scale migration and haplotype analysis

The population of the United States is shaped by centuries of migration, isolation, growth, and admixture between ancestors of global origins. Here, we assemble a comprehensive view of recent population history by studying the ancestry and population structure of over 32,000 individuals in the US using genetic, ancestral birth origin, and geographic data from the National Geographic Genographic Project. We identify migration routes and barriers that reflect historical demographic events. We also uncover the spatial patterns of relatedness in subpopulations through the combination of haplotype clustering, ancestral birth origin analysis, and local ancestry inference. Examples of these patterns include substantial substructure and heterogeneity in Hispanics/Latinos, isolation-by-distance in African Americans, elevated levels of relatedness and homozygosity in Asian immigrants, and fine-scale structure in European descents. Taken together, our results provide detailed insights into the genetic structure and demographic history of the diverse US population.

genetics↗