Biology subjects

Han, B. A.

Publications and source records attributed to Han, B. A..

3 recordsLinked to original sources

bioRxiv2020

The evolutionary history of ACE2 usage within the coronavirus subgenus Sarbecovirus

SARS-CoV-1 and SARS-CoV-2 are not phylogenetically closely related; however, both use the ACE2 receptor in humans for cell entry. This is not a universal sarbecovirus trait; for example, many known sarbecoviruses related to SARS-CoV-1 have two deletions in the receptor binding domain of the spike protein that render them incapable of using human ACE2. Here, we report three sequences of a novel sarbecovirus from Rwanda and Uganda which are phylogenetically intermediate to SARS-CoV-1 and SARS-CoV-2 and demonstrate via in vitro studies that they are also unable to utilize human ACE2. Furthermore, we show that the observed pattern of ACE2 usage among sarbecoviruses is best explained by recombination not of SARS-CoV-2, but of SARS-CoV-1 and its relatives. We show that the lineage that includes SARS-CoV-2 is most likely the ancestral ACE2-using lineage, and that recombination with at least one virus from this group conferred ACE2 usage to the lineage including SARS-CoV-1 at some time in the past. We argue that alternative scenarios such as convergent evolution are much less parsimonious; we show that biogeography and patterns of host tropism support the plausibility of a recombination scenario; and we propose a competitive release hypothesis to explain how this recombination event could have occurred and why it is evolutionarily advantageous. The findings provide important insights into the natural history of ACE2 usage for both SARS-CoV-1 and SARS-CoV-2, and a greater understanding of the evolutionary mechanisms that shape zoonotic potential of coronaviruses. This study also underscores the need for increased surveillance for sarbecoviruses in southwestern China, where most ACE2-using viruses have been found to date, as well as other regions such as Africa, where these viruses have only recently been discovered.

evolutionary biology↗

bioRxiv2020

Predicting wildlife hosts of betacoronaviruses for SARS-CoV-2 sampling prioritization

Despite global investment in One Health disease surveillance, it remains difficult--and often very costly--to identify and monitor the wildlife reservoirs of novel zoonotic viruses. Statistical models can be used to guide sampling prioritization, but predictions from any given model may be highly uncertain; moreover, systematic model validation is rare, and the drivers of model performance are consequently under-documented. Here, we use bat hosts of betacoronaviruses as a case study for the data-driven process of comparing and validating predictive models of likely reservoir hosts. In the first quarter of 2020, we generated an ensemble of eight statistical models that predict host-virus associations and developed priority sampling recommendations for potential bat reservoirs and potential bridge hosts for SARS-CoV-2. Over more than a year, we tracked the discovery of 40 new bat hosts of betacoronaviruses, validated initial predictions, and dynamically updated our analytic pipeline. We find that ecological trait-based models perform extremely well at predicting these novel hosts, whereas network methods consistently perform roughly as well or worse than expected at random. These findings illustrate the importance of ensembling as a buffer against variation in model quality and highlight the value of including host ecology in predictive models. Our revised models show improved performance and predict over 400 bat species globally that could be undetected hosts of betacoronaviruses. Although 20 species of horseshoe bats (Rhinolophus spp.) are known to be the primary reservoir of SARS-like viruses, we find at least three-fourths of plausible betacoronavirus reservoirs in this bat genus might still be undetected. Our study is the first to demonstrate through systematic validation that machine learning models can help optimize wildlife sampling for undiscovered viruses and illustrates how such approaches are best implemented through a dynamic process of prediction, data collection, validation, and updating.

ecology↗

bioRxiv2020

The macroecology and evolution of avian competence for Borrelia burgdorferi

AimPredicting novel reservoirs of zoonotic pathogens would be improved by identifying inter-specific drivers of host competence, the ability to transmit pathogens to new hosts or vectors. Tick-borne pathogens can provide a useful model system, as larvae become infected only when feeding on a competent host during their first bloodmeal. For tick-borne diseases, competence has been best studied for Borrelia burgdorferi sensu lato (Bbsl), which causes Lyme borreliosis. Major reservoirs include several small mammal species, but birds may play an underrecognized role in human risk given their ability to disperse infected ticks across large spatial scales. Here, we provide a global synthesis of the ecological and evolutionary factors that determine the ability of bird species to infect larval ticks with Bbsl. LocationGlobal Time period1983 to 2019 Major taxa studiedBirds MethodsWe compiled a dataset of Bbsl competence across 183 bird species and applied meta-analysis, phylogenetic factorization, and boosted regression trees to describe spatial and temporal patterns in competence, characterize its phylogenetic distribution across birds, reconstruct its evolution, and evaluate the trait profiles associated with competent avian species. ResultsHalf of sampled bird species show evidence of competence for Bbsl. Competence displays moderate phylogenetic signal, has evolved multiple times across bird species, and is pronounced in the genus Turdus. Trait-based analyses distinguished competent birds with 80% accuracy and show that such species have low baseline corticosterone, exist on both ends of the pace-of-life continuum, breed and winter at high latitudes, and have broad migratory movements into their breeding range. We use these trait profiles to predict various likely but unsampled competent species, including novel concentrations of avian reservoirs within the Neotropics. Main conclusionOur results can generate new hypotheses for how birds contribute to the dynamics of tick-borne pathogens and help prioritize surveillance of likely but unsampled competent birds. Our findings further emphasize that birds display underrecognized variation in their contributions to enzootic cycles of Bbsl and the broader need to better consider competence in ecological and predictive studies of multi-host pathogens.

ecology↗