Biology subjects

Crowley, D.

Publications and source records attributed to Crowley, D..

6 recordsLinked to original sources

bioRxiv2024

Jamaican fruit bats (Artibeus jamaicensis) competence for Ebola virus but not Marburg virus is driven by intrinsic differences in viral entry and IFN-I signaling antagonism.

Ebola virus (EBOV) and Marburg virus (MARV) are zoonotic filoviruses that cause hemorrhagic fever in humans. Bat species in both Chiropteran suborders host filoviruses, suggesting that bats may have coevolved with this viral family. Correlative data implicate bats as natural EBOV hosts, but neither a full-length genome nor an EBOV isolate has been found in any bats sampled. Here, we modelled filovirus infection in the Jamaican fruit bat (JFB), Artibeus jamaicensis. Bats were inoculated with either EBOV or MARV through a combination of oral, intranasal, and subcutaneous routes. EBOV-infected bats supported systemic virus replication and shed infectious virus orally. In contrast, MARV replicated only transiently and was not shed. In vitro, JFB cells replicate EBOV more efficiently than MARV, and MARV infection induced innate antiviral responses that EBOV efficiently suppressed. Experiments using VSV pseudoparticles or replicating VSV expressing the EBOV or MARV glycoprotein demonstrated an advantage for EBOV entry and replication early, respectively, in JFB cells. Overall, this study describes filovirus species-specific phenotypes for both JFB and their cells.

immunology↗

bioRxiv2024

Modeling the dietary effects on bat viral shedding and potential consequences for pathogen spillover

Changes in the quality and quantity of food resources can affect individuals health, the way they control infections and consequently the likelihood of onward transmission of pathogens. Dietary shifts have been proposed as one of the factors driving spillovers of zoonotic viruses from bats through a bridging host to humans. While there is a general understanding of the relationship between nutrition and infection in model systems, how diet affects pathogen shedding and the risk of spillover from bats is lacking. We used a data-driven mathematical modeling approach to disentangle the relation between diet, immunity, and viral shedding of Jamaican fruit bats infected with H18N11 and fed different dietary regimes. Model selection indicates that the synergistic interaction between the metabolite citrulline and the cytokine TNF controls viral shedding in a diet-dependent manner. Bats on a sub-optimal fat diet are more successful in terminating shedding than bats on an optimal or sub-optimal sugar diet. However, when bat foraging behavior is considered, bats on the optimal diet show a lower spillover hazard, probably because of a feeding behavior less conducive to transmission. This study provides novel insights into the diet-driven mechanisms of viral shedding and how they can potentially contribute to spillover events.

ecology↗

bioRxiv2023

Diet-induced changes in metabolism influence immune response and viral shedding dynamics in Jamaican fruit bats

Land-use change may drive viral spillover from bats into humans, partly through dietary shifts caused by decreased availability of native foods and increased availability of cultivated foods. We manipulated diets of Jamaican fruit bats to investigate whether diet influences shedding of a virus they naturally host. To reflect dietary changes experienced by wild bats during periods of nutritional stress, bats were fed either standard or putative suboptimal diets which were deprived of protein (suboptimal-sugar) and/or supplemented with fat (suboptimal-fat). Upon H18N11 influenza A-virus infection, bats fed the suboptimal-sugar diet shed the most viral RNA for the longest period, but bats fed the suboptimal-fat diet shed the least viral RNA for the shortest period. Unlike mice and humans, bats fed the suboptimal-fat diet displayed higher pre-infection levels of metabolic markers associated with gut health. Diet-driven heterogeneity in viral shedding may influence population-level viral dynamics in wild bats and alter risk of shedding and spillover to humans.

ecology↗

bioRxiv2023

Periodic shifts in viral load increase risk of spillover from bats

Prediction and management of zoonotic pathogen spillover requires an understanding of infection dynamics within reservoir host populations. Transmission risk is often assessed using prevalence of infected hosts, with infection status based on the presence of genomic material. However, detection of viral genomic material alone does not necessarily indicate the presence of infectious virus, which could decouple prevalence from transmission risk. We undertook a multi-faceted investigation of Hendra virus shedding in Pteropus bats, combining insights from virus isolation, viral load proxies, viral prevalence, and longitudinal patterns of shedding, from 6,151 samples. In addition to seasonal and interannual fluctuation in prevalence, we found evidence for periodic shifts in the distribution of viral loads. The proportion of bats shedding high viral loads was higher during peak prevalence periods during which spillover events were observed, and lower during non-peak periods when there were no spillovers. We suggest that prolonged periods of low viral load and low prevalence reflect prolonged shedding of non-infectious RNA, or viral loads that are insufficient or unlikely to overcome dose barriers to spillover infection. These findings show that incorporating viral load (or proxies of viral load) into longitudinal studies of virus excretion will better inform predictions of spillover risk than prevalence alone. Significance statementWe present a comprehensive analysis of a high-profile bat-virus system (Hendra virus in Australian flying-foxes) to demonstrate that both prevalence and viral loads can shift systematically over time, resulting in concentrated periods of increased spillover risk when prevalence and viral loads are high. We further suggest that prolonged periods of low-prevalence, low-load shedding may not reflect excretion of infectious virus, resolving the outstanding puzzle of why spillovers have not been observed during periods of low off-season prevalence in subtropical Australia, or more frequently in tropical Australia despite consistent low-prevalence shedding. The consideration of viral loads (or proxies of viral load) along with prevalence may improve risk inference from longitudinal surveys of zoonotic viruses across wildlife reservoir hosts.

ecology↗

bioRxiv2022

The Nanog epigenetic remodeling complex was essential to vertebrate mesoderm evolution

Pluripotency defines the unlimited potential of cells in the primitive ectoderm of vertebrate embryos, from which all adult somatic cells and germ cells are derived. Understanding how the programing of pluripotency evolved has been obscured by the study of early development in models from lower vertebrates in which pluripotency is not conserved. Here we investigated how the axolotl ortholog of the mammalian core pluripotency factor NANOG, programs pluripotency during axolotl development to model the tetrapod ancestor from which terrestrial vertebrates evolved. We show that in axolotl primitive ectoderm (animal caps; AC) NANOG synergizes with NODAL activity and the epigenetic modifying enzyme DPY30 to direct the deposition of H3K4me3 in chromatin prior to the waves of transcription required for lineage commitment and developmental progression. We show that the interaction of NANOG and NODAL with DPY30 is required to direct development downstream of pluripotency and this is conserved in axolotls and human. These data demonstrate that the interaction of NANOG and NODAL signaling represents the basal state of vertebrate pluripotency.

developmental biology↗

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↗