Biology subjects

Washburne, A. D.

Publications and source records attributed to Washburne, A. D..

6 recordsLinked to original sources

bioRxiv2022

Statistical challenges for inferring multiple SARS-CoV-2 spillovers with early outbreak phylodynamics

Understanding how SARS-CoV-2 entered the human population, thereby causing the COVID-19 pandemic, is one of the most urgent questions in science today. Two hypotheses are widely acknowledged as being most likely to explain the pandemics origin in late 2019: (i) the "natural origin" hypothesis that one or more cross-species transmissions from animals into humans occurred, most likely at the Huanan Seafood Market in Wuhan, China; (ii) the "laboratory origin" hypothesis, that scientific research activities led to the unintentional leak of SARS-CoV-2 from a laboratory into the general population. A recent analysis of SARS-CoV-2 genomes by Pekar et al. [Science 377:960-966 (2022)] claims to establish at least two separate spillover events from animals into humans, thus claiming to provide strong evidence for the natural origin hypothesis. However, here we use outbreak simulations to show that the findings of Pekar et al. are heavily impacted by two methodological artifacts: the dubious exclusion of informative SARS-CoV-2 genomes, and their reliance on unrealistic phylodynamic models of SARS-CoV-2. Absent models that incorporate these effects, one cannot conclude multiple SARS-CoV-2 spillovers into humans. Our results cast doubt on a primary point of evidence in favor of the natural origin hypothesis. Lay SummaryIt is not known if SARS-CoV-2 spilled over from animals into humans at the Huanan Seafood Market, or arose as a result of research activities studying bat coronaviruses. Two recent papers had claimed to answer this question, but here we show those papers are both inconclusive as they fail to account for biases in how medical managers became alerted to SARS-CoV-2 and how public health authorities sampled early cases. Additionally, key data points conflicting with the authors conclusions were improperly excluded from the analysis. The papers methods do not justify their conclusions, and the origin of SARS-CoV-2 remains an urgent, open question for science.

evolutionary biology↗

bioRxiv2022

Natural helminth infections reduce relative abundance of inflammation-inducing Prevotella in wild primates

Microbes living within the mammalian gastrointestinal tract affect the metabolization and extraction of dietary nutrients, immune function, colonization by pathogens, and risk of autoimmune disease. While most microbiome studies focus on sequences of the 16S gene shared by Bacteria and Archaea, these are not the only regular inhabitants of mammalian guts. Macroparasites such as helminths are nearly ubiquitous in wildlife, and a quarter of the worlds human population harbors helminths; these worms affect host physiology as they compete with microbiota over host resources while also affecting host immunity, and changing the host microbiome. Little is understood about how helminths interact with microbiomes to affect host disease states, and few studies have examined these interactions in natural systems in genetically diverse hosts experiencing coinfections and other stressors. We surveyed the microbiomes and helminth parasites of wild primates and found strong associations between helminths and microbes in the bacterial microbiome. Notably, we find that the presence of a strongyle we hypothesize to be hookworm is correlated strongly with decreased relative abundance of Prevotella species, a lineage associated with inflammatory bowel disease humans. This observed decline in Prevotella relative abundance, a genus implicated in several host autoimmune and inflammatory disorders, motivates future research on whether the mixed results of helminthic therapy (i.e., "infecting" patients with gastrointestinal nematodes to treat various diseases) stem from the mixed causes of inflammation, and whether inflammation specifically correlated with Prevotella-driven dysbiosis can be mediated through mechanisms mimicking how hookworms and other nematodes behave in the gastrointestinal ecosystem of their hosts. Our findings lend ground-truthed support to previous lab-based studies and limited/restricted human trials showing potential benefits, via microbial modulation, of nematode therapy in treating inflammatory bowel disease. Our study adds statistical weight to a link between helminths and a specific lineage of microbes associated with inflammation.

ecology↗

bioRxiv2020

Homogeneous selection promotes microdiversity in the glacier-fed stream microbiome

Microdiversity, the organization of microorganisms into groups with closely related but ecologically different sub-types, is widespread and represents an important linchpin between microbial ecology and evolution. However, the drivers of microdiversification remain largely unknown. Here we show that selection promotes microdiversity in the microbiome associated with sediments in glacier-fed streams (GFS). Applying a novel phylogenetic framework, we identify several clades that are under homogeneous selection and that contain genera with higher levels of microdiversity than the rest of the genera. Overall these clades constituted [~]44% and [~]64% of community -diversity and abundance, and both percentages increased further in GFS that were largely devoid of primary producers. Our findings show that strong homogeneous selection drives the microdiversification of specialized microbial groups putatively underlying their success in the extreme environment of GFS. This microdiversity could be threatened as glaciers shrink, with unknown consequences for microbial diversity and functionality in these ecosystems.

ecology↗

bioRxiv2019

A phylogenetic model for the arrival of species into microbial communities and application to studies of thehuman microbiome

Understanding when and why new species are recruited into microbial communities is a formidable problem with implications for managing microbial systems, for instance by helping us better understand whether a probiotic or pathogen would be expected to colonize a human microbiome. Much theory in microbial temporal dynamics is focused on how phylogenetic relationships between microbes impact the order in which those microbes are recruited; for example species that are closely related may competitively exclude each other. However, several recent human microbiome studies have observed closely-related bacteria being recruited into microbial communities in short succession, suggesting that microbial community assembly is historically contingent, but competitive exclusion of close relatives may not be important. To address this, we developed a mathematical model that describes the order in which new species are detected in microbial communities over time within a phylogenetic framework. We use our model to test three hypothetical assembly modes: underdispersion (species recruitment is more likely if a close relative was previously detected), overdispersion (recruitment is more likely if a close relative has not been previously detected), and the neutral model (recruitment likelihood is not related to phylogenetic relationships among species). We applied our model to longitudinal human microbiome data, and found that for the individuals we analyzed, the human microbiome generally follows the underdispersion (i.e. nepotism) hypothesis. Exceptions were oral communities and the fecal communities of two infants that had undergone heavy antibiotic treatment. None of the data sets we analyzed showed statistically significant phylogenetic overdispersion.

microbiology↗

bioRxiv2019

Temporal and spatial limitations in global surveillance for bat filoviruses and henipaviruses

Sampling reservoir hosts over time and space is critical to detect epizootics, predict spillover, and design interventions. However, because sampling is logistically difficult and expensive, researchers rarely perform spatiotemporal sampling of many reservoir hosts. Bats are reservoirs of many virulent zoonotic pathogens such as filoviruses and henipaviruses, yet the highly mobile nature of these animals has limited optimal sampling of bat populations. To quantify the frequency of temporal sampling and to characterize the geographic scope of bat virus research, we here collated data on filovirus and henipavirus prevalence and seroprevalence in wild bats. We used a phylogenetically controlled meta-analysis to next assess temporal and spatial variation in bat virus detection estimates. Our analysis shows that only one in four bat virus studies report data longitudinally, that sampling efforts cluster geographically (e.g., filovirus data are available across much of Africa and Asia but are absent from Latin America and Oceania), and that sampling designs and reporting practices may affect some viral detection estimates (e.g., filovirus seroprevalence). Within the limited number of longitudinal bat virus studies, we observed high heterogeneity in viral detection estimates that in turn reflected both spatial and temporal variation. This suggests that spatiotemporal sampling designs are essential to understand how zoonotic viruses are maintained and spread within and across wild bat populations, which in turn could help predict and preempt risks of zoonotic viral spillover.

epidemiology↗

bioRxiv2017

Phylofactorization - a graph partitioning algorithm to identify phylogenetic scales of ecological data

The problem of pattern and scale is a central challenge in ecology. The problem of scale is central to community ecology, where functional ecological groups are aggregated and treated as a unit underlying an ecological pattern, such as aggregation of \"nitrogen fixing trees\" into a total abundance of a trait underlying ecosystem physiology. With the emergence of massive community ecological datasets, from microbiomes to breeding bird surveys, there is a need to objectively identify the scales of organization pertaining to well-defined patterns in community ecological data.\n\nThe phylogeny is a scaffold for identifying key phylogenetic scales associated with macroscopic patterns. Phylofactorization was developed to objectively identify phylogenetic scales underlying patterns in relative abundance data. However, many ecological data, such as presence-absences and counts, are not relative abundances, yet it is still desireable and informative to identify phylogenetic scales underlying a pattern of interest. Here, we generalize phylofactorization beyond relative abundances to a graph-partitioning algorithm for any community ecological data.\n\nGeneralizing phylofactorization connects many tools from data analysis to phylogenetically-informe analysis of community ecological data. Two-sample tests identify three phylogenetic factors of mammalian body mass which arose during the K-Pg extinction event, consistent with other analyses of mammalian body mass evolution. Projection of data onto coordinates defined by the phylogeny yield a phylogenetic principal components analysis which refines our understanding of the major sources of variation in the human gut microbiome. These same coordinates allow generalized additive modeling of microbes in Central Park soils and confirm that a large clade of Acidobacteria thrive in neutral soils. Generalized linear and additive modeling of exponential family random variables can be performed by phylogenetically-constrained reduced-rank regression or stepwise factor contrasts. We finish with a discussion of how phylofac-torization produces an ecological species concept with a phylogenetic constraint. All of these tools can be implemented with a new R package available online.

ecology↗