Biology subjects

Cleary, S.

Publications and source records attributed to Cleary, S..

3 recordsLinked to original sources

bioRxiv2026

Environment and host infection history jointly predict disease risk in a multi-pathogen system

Forecasting disease epidemics may require considering both abiotic and biotic conditions. Abiotic conditions can influence pathogen dispersal, survival, and infection, while prior infection by one pathogen species can alter host susceptibility to subsequent pathogens, creating historical contingencies. Yet, the relative importance of environmental conditions, within-host pathogen interactions, and their interplay in predicting seasonal disease dynamics remains underexplored. We analyzed approximately 30,000 plant-level observations of three foliar fungal diseases on the grass species tall fescue in a North Carolina old field, and meteorological data, from 2017-2024. Using such datasets to make ecological predictions that are accurate and interpretable may require multiple modeling approaches. Temporally explicit random forest models predicted future disease with over 80% accuracy for two of the three diseases and revealed environmental thresholds for disease prediction in environmental variables including temperature and humidity. Survival analyses showed that pathogen-pathogen interactions rivaled environmental conditions in predicting risk of crown rust, which was strongly facilitated by prior anthracnose infection. Across all pathogens, Bayesian hierarchical models recovered evidence that facilitative interactions between coinfecting pathogens were modulated by effects of environmental conditions, particularly temperature. Together, these complementary approaches show that a host's current disease state can matter as much as its environment in predicting disease, identify key environmental factors associated with disease risk, and show that modulation of environmental drivers by pathogen coinfections can improve predictions of seasonal disease epidemics. Other disease forecasts may be improved by accounting not just for environmental drivers, but also how those drivers propagate through pathogen species interactions.

ecology↗

bioRxiv2024

Focal persistence and phylodynamics of Heartland virus in Georgia

Heartland virus (HRTV) is an emerging tick-bone virus associated with severe illness in the U.S. There are large gaps in knowledge of HRTV diversity, evolution, and transmission due to a paucity of HRTV-positive samples and genome sequences. We identified a focal site of HRTV- positive Amblyomma americanum ticks in central Georgia and developed a novel multiplex- amplicon sequencing assay to generate full HRTV genome sequences. By screening over 21,000 field-collected ticks from 2021-2023, we identified six positive pools. Five were collected from the site in central Georgia where our group first detected HRTV-positive ticks in 2019, and one from a site in western Georgia approximately 175 km away. The HRTV genome sequences from Georgia were highly related, even across this distance and over five years. Reference HRTV genome sequences from across the U.S. were also geographically clustered. Time-scaled phylogenetic analysis suggested recent spread of HRTV in the U.S., with all available sequences sharing a common ancestor within the last 300 years, and sequences from Georgia sharing a common ancestor within the last 40 years. Our observed spatial clustering of HRTV and the high degree of genetic conservation in our persistent focus suggest the importance of small spatial dynamics in HRTV transmission ecology. Author SummaryHeartland virus (HRTV) was first discovered in humans in 2009 and has since caused over 60 cases of severe and fatal disease in the United States. HRTV is transmitted by the lone star tick, Amblyomma americanum, across the Southeast, East coast, and Midwest. Little information is known about how this virus circulates and changes across time and space due to a lack of genetic data. Here, we created a new procedure to generate more genetic sequence data for HRTV and collected over 21,000 ticks to screen for HRTV across three years in Georgia. We generated 6 new HRTV sequences and compared them to existing sequences from our group in Georgia, and across the country, finding evidence of regional clustering of HRTV and highly related HRTV across time in Georgia. Our analyses additionally found that this virus was likely introduced to the U.S. in the last 300 years. Our study provides new context and information in understanding the landscape and transmission of HRTV in the U.S.

genomics↗

bioRxiv2021

No evidence that HLA genotype influences the driver mutations that occur in cancer patients

The major histocompatibility (MHC) molecules are capable of presenting neoantigens resulting from somatic mutations on cell surfaces, potentially directing immune responses against cancer. This led to the hypothesis that cancer driver mutations may occur in gaps in the capacity to present neoantigens that are dependent on MHC genotype. If this is correct, it has important implications for understanding oncogenesis and may help to predict driver mutations based on genotype data. In support of this hypothesis, it has been reported that driver mutations that occur frequently tend to be poorly presented by common MHC alleles and that the capacity of a patients MHC alleles to present the resulting neoantigens is predictive of the driver mutations that are observed in their tumour. Here we show that these reports of a strong relationship between driver mutation occurrence and patient MHC alleles are a consequence of unjustified statistical assumptions. Our reanalysis of the data provides no evidence of an effect of MHC genotype on the oncogenic mutation landscape.

cancer biology↗