Biology subjects

Davenport, E. R.

Publications and source records attributed to Davenport, E. R..

7 recordsLinked to original sources

bioRxiv2026

Integrative host transcriptomic and mucosal microbiome profiling reveals region-specific host-microbiome associations across the human intestine

Host genetics shapes gut microbiome composition, yet the physiological mechanisms underlying this relationship remain poorly understood. Characterizing associations between host gene expression and the mucosal microbiome offers a promising route to identifying the host pathways and microbial taxa most likely to interact physiologically. However, existing investigations have been conducted primarily in acute disease contexts and within the colon, leaving host-microbiome associations outside of acute inflammatory contexts and those in undersampled regions such as the terminal ileum poorly characterized. To address these gaps, we profiled paired host gene expression from full-thickness resections and mucosal microbiome data, both from macroscopically non-inflamed tissue from Crohns disease patients undergoing surgery across three intestinal sites: terminal ileum (n = 32), cecum (n = 35), and right colon (n = 30). Using a multi-level analytical framework including Procrustes analysis, sparse canonical correlation analysis, and elastic net regression, we identified significant associations between the mucosal transcriptome and microbiome. Intestine-wide, genes enriched in immune and intestinal barrier integrity pathways were associated with heritable taxa including Fusicatenibacter, consistent with patterns observed in microbiome genome-wide association studies. Region-specific analysis identified the terminal ileum as a distinct site of host-microbiome interaction, with associations involving metabolic and barrier-related pathways not observed in the large intestine. Notable terminal ileum-specific associations included PCDH20 with Faecalitalea and ACAT1 with Lactococcus, implicating epithelial barrier maintenance and host-microbiome metabolic interactions, respectively. These findings advance our understanding of the physiological basis of host-microbiome interactions across the intestine. ImportanceThe human gut is home to trillions of microorganisms that interact with the intestinal lining, yet we have a limited understanding of the specific biological processes involved in these interactions. Most studies characterizing the relationships between host gene expression and the gut microbiome have focused on the colon and on active disease contexts, leaving it unclear whether the associations observed reflect fundamental host-microbiome biology or disease-specific responses. By examining mucosal tissue, where host cells and microbes are in direct contact, across three sites in non-acutely inflamed tissue, we show that expression of immune defense and barrier maintenance genes is broadly associated with the microbiome across the intestine. We also identify distinct classes of associations in the terminal ileum, including host genes involved in metabolic processes. These findings provide a foundation for understanding how host biology and the gut microbiome are linked outside of acute disease.

genomics↗

bioRxiv2026

SCiMS: Sex Calling in Metagenomic Sequences

BackgroundHost sex is a critical determinant of microbial community structure across many host species, influenced by hormonal profiles, physiology, and sex-stratified behaviors. Despite its importance, sex metadata is frequently missing in microbiome studies, including for animal-associated samples. Host chromosomal sex can be inferred from the host-derived reads present in metagenomic data, but existing genomic sex prediction tools rely on fixed coverage thresholds calibrated for human XY chromosomes and require relatively high host reads, limiting their use on low host-biomass samples such as stool and on organisms with other sex-determination systems. ResultsHere, we present SCiMS (Sex Calling in Metagenomic Sequences), a bioinformatic tool that leverages host-derived DNA within shotgun metagenomic data to predict host chromosomal sex, even at low host coverage. SCiMS uses a multinomial likelihood computed from observed read counts under each sex and reports chromosomal sex calls. Because the expected read distribution is derived directly from chromosome lengths and ploidy under each candidate karyotype, SCiMS applies to any organism with a heterogametic sex-determination system. We benchmarked SCiMS against existing tools on simulated metagenomic data, human metagenomic samples spanning multiple body sites, and metagenomic samples from seven animal species. SCiMS matched or outperformed existing tools, with its noticeable advantage at low host read conditions. ConclusionsSCiMS provides an accurate, scalable, and cross-species generalizable solution for host chromosomal sex classification, even when host DNA is minimal. By enabling recovery of missing sex metadata, it serves as a quality-control tool analyses in microbiome research. SCiMS is freely available at http://github.com/davenport-lab/SCiMS.

bioinformatics↗

bioRxiv2026

Distinct trajectories of urbanization shape the human gut microbiome across South Asia

Human gut microbiomes respond to lifestyle transitions, yet the extent to which these responses are conserved across spatio-cultural contexts remains undercharacterized. We present the South Asian MicroBiome ARray (SAMBAR), a population-scale 16S gut microbiome study of 575 adults from ten geographically and socio-culturally diverse South Asian communities. Each community was sampled in ancestral villages and urban centers, enabling controlled comparisons of geography and lifestyle. Relative to global cohorts, SAMBAR microbiomes occupy a distinct compositional space with stronger correlation to geography and community membership than lifestyle. Although urbanization is consistently associated with increased abundance of disease-linked taxa, microbiome responses to lifestyle transitions are largely community-driven, including the acquisition of wheat- and dairying-associated microbial modules in some communities that may facilitate non-genetic adaptation to lactase non-persistence. Microbiome responses to urbanization are heterogeneous even at regional scales, reflecting local culture and geography and underscoring the need for community-specific investigations of health impacts.

microbiology↗

bioRxiv2024

Clade-specific long-read sequencing increases the accuracy and specificity of the gyrB phylogenetic marker gene

Phylogenetic marker gene sequencing is often used as a quick and cost-effective way of evaluating microbial composition within a community. While 16S rRNA gene sequencing (16S) is commonly used for bacteria and archaea, other marker genes are preferable in certain situations, such as when 16S sequences cannot distinguish between taxa within a group. Another situation is when researchers want to study cospeciation of host taxa that diverged much more recently than the slowly evolving 16S rRNA gene. For example, the bacterial gyrase subunit B (gyrB) gene has been used to investigate cospeciation between the microbiome and various hominid species. However, to date only primers that generate short-read Illumina MiSeq-length amplicons exist to investigate gyrB of the Bacteroidaceae, Bifidobacteriaceae, and Lachnospiraceae families. Here, we update this methodology by creating gyrB primers for the Bacteroidaceae, Bifidobacteriaceae, and Lachnospiraceae families for long-read PacBio sequencing and characterize them against established short-read gyrB primer sets. We demonstrate both bioinformatically and analytically that these longer amplicons offer more sequence space for greater taxonomic resolution, lower off-target amplification rates, and lower error rates with PacBio CCS sequencing versus established short-read sequencing. The availability of these long-read gyrB primers will prove to be integral to the continued analysis of cospeciation between bacterial members of the gut microbiome and recently diverging host species.

genomics↗

bioRxiv2024

Nepali oral microbiomes reflect a gradient of lifestyles from traditional to industrialized

BackgroundLifestyle plays an important role in shaping the gut microbiome. However, its contributions to the oral microbiome remains less clear, due to the confounding effects of geography and methodology in investigations of populations studied to date. Furthermore, while the oral microbiome seems to differ between foraging and industrialized populations, we lack insight into whether transitions to and away from agrarian lifestyles shape the oral microbiota. Given the growing interest in so-called vanishing microbiomes potentially being a risk factor for increased disease prevalence in industrialized populations, it is important that we distinguish lifestyle from geography in the study of microbiomes across populations. ResultsHere, we investigate salivary microbiomes of 63 Nepali individuals representing a spectrum of lifestyles: foraging, subsistence farming (individuals that transitioned from foraging to farming within the last 50 years), agriculturalists (individuals that have transitioned to farming for at least 300 years), and industrialists (expatriates that immigrated to the United States within the last 20 years). We characterize the role of lifestyle in microbial diversity, identify microbes that differ between lifestyles, and pinpoint specific lifestyle factors that may be contributing to differences in the microbiomes across populations. Contrary to prevailing views, when geography is controlled for, oral microbiome alpha diversity does not differ significantly across lifestyles. Microbiome composition, however, follows the gradient of lifestyles from foraging through agrarianism to industrialism, supporting the notion that lifestyle indeed plays a role in the oral microbiome. Relative abundances of several individual taxa, including Streptobacillus and an unclassified Porphyromonadaceae genus, also mirror lifestyle. Finally, we identify specific lifestyle factors associated with microbiome composition across the gradient of lifestyles, including smoking and grain source. ConclusionOur findings demonstrate that by controlling for geography, we can isolate an important role for lifestyle in determining oral microbiome composition. In doing so, we highlight the potential contributions of several lifestyle factors, underlining the importance of carefully examining the oral microbiome across lifestyles to improve our understanding of global microbiomes.

microbiology↗

bioRxiv2023

Interactions between the gut microbiome, dietary restriction, and aging in genetically diverse mice

The intestinal microbiome changes with age, but the causes and consequences of microbiome aging remain unclear. Furthermore, the gut microbiome has been proposed to mediate the benefit of lifespan- extending interventions such as dietary restriction, but this hypothesis warrants further exploration. Here, by analyzing 2997 metagenomes collected longitudinally from 913 deeply phenotyped, genetically diverse mice, we provide new insights into the interplay between the microbiome, aging, dietary restriction, host genetics, and a wide range of health parameters. First, we find that microbiome uniqueness increases with age across datasets and species. Moreover, age-associated changes are better explained by cumulative exposure to stochastic events (neutral theory) than by the influence of an aging host (selection theory). Second, we unexpectedly find that the majority of microbiome features are significantly heritable and that the amount of variation explained by host genetics is as large as that of aging and dietary restriction. Third, we find that the intensity of dietary restriction parallels the extent of microbiome changes and that dietary restriction does not rejuvenate the microbiome. Lastly, we find that the microbiome is significantly associated with multiple health parameters -- including body composition, immune parameters, and frailty -- but not with lifespan. In summary, this large and multifaceted study sheds light on the factors influencing the microbiome and aspects of host physiology modulated by the microbiome.

microbiology↗

bioRxiv2018

Gut microbiome transition across a lifestyle gradient in Himalaya

The composition of the gut microbiome in industrialized populations differs from those living traditional lifestyles. However, it has been difficult to separate the contributions of human genetic and geographic factors from lifestyle/modernization. Here, we characterize the stool bacterial composition of four Himalayan populations to investigate how the gut community changes in response to shifts in human lifestyles. These groups led seminomadic hunting-gathering lifestyles until transitioning to varying dependence upon farming. The Tharu began farming 250-300 years ago, the Raute and Raji transitioned 30-40 years ago, and the Chepang retain many aspects of a foraging lifestyle. We assess the contributions of dietary and environmental factors on their gut microbiota and find that the gut microbiome composition is significantly associated with lifestyle. The Chepang foragers harbor elevated abundance of taxa associated with foragers around the world. Conversely, the gut microbiomes of populations that have transitioned to farming are more similar to those of Americans, with agricultural dependence and several associated lifestyle and environmental factors correlating with the extent of microbiome divergence from the foraging population. For example, our results show that drinking water source and solid cooking fuel are significantly associated with the gut microbiome. Despite the pronounced differences in gut bacterial composition across populations, we found little differences in alpha diversity across populations. These findings in genetically similar populations living in the same geographical region establish the key role of lifestyle in determining human gut microbiome composition and point to the next challenging steps of isolating dietary effects from other factors that change during modernization.\n\n\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=193 SRC=\"FIGDIR/small/253450_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (108K):\norg.highwire.dtl.DTLVardef@68f595org.highwire.dtl.DTLVardef@d33792org.highwire.dtl.DTLVardef@e56314org.highwire.dtl.DTLVardef@1cbbba2_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗