Biology subjects

Bahl, J.

Publications and source records attributed to Bahl, J..

8 recordsLinked to original sources

bioRxiv2026

Dairy cattle movement networks govern the spread and persistence of H5N1 B3.13 in the United States

Avian influenza virus H5N1 is predominantly found in wild and domestic birds. H5N1 genotype B3.13 was first detected in United States dairy cattle in March 2024 and spread through much of the country during 2024 and 2025, resulting in the largest known H5N1 outbreak in domestic mammals. By analysing viral genomic data jointly with historical cattle movement patterns, we find that live cattle movement is the predominant contributor to H5N1 spatial spread, rather than wild or domestic birds. Using phylogeographic methods we estimate that >40% of interstate viral transmissions occurred before B3.13's first detection and >70% occurred before interstate dairy cattle movement restrictions were implemented in April 2024. After this implementation, interstate transmission slowed but within-state spread persisted, driven by local cattle network density and movement volume. Our epidemic simulations demonstrate that the connectivity of counties within and around the Texas Panhandle - where the earliest cases were documented - predisposed the region to become an outbreak epicentre. Counterfactual simulations indicate that interstate restrictions needed to have begun 2-3 months earlier in order to limit the epizootic substantively, given the extent of cryptic spread before detection. Network-informed interventions outperformed geographically-defined containment, but response speed (rather than intervention strength) was the limiting factor in our epidemic models, underscoring the need for surveillance systems capable of detecting pathogen emergence before widespread dissemination.

evolutionary biology↗

bioRxiv2024

Pandemic Risk Assessment for a Swine Influenza A Virus in Comparative Human Substrates

Swine influenza A viruses pose a public health concern as novel and circulating strains occasionally spill over into human hosts, with the potential to cause disease. Crucial to preempting these events is the use of a threat assessment framework for human populations. However, established guidelines do not specify what animal models or in vitro substrates should be used. We completed an assessment of a contemporary swine influenza isolate, A/swine/GA/A27480/2019, using animal models and human cell substrates. Infection studies in vivo revealed high replicative ability and a pathogenic phenotype in the swine host with replication corresponding to a complementary study performed in swine primary respiratory epithelial cells. However, replication was limited in human primary cell substrates. This contrasted with our findings in the Calu-3 cell line, which demonstrated a replication profile on par with the 2009 pandemic H1N1 virus. These data suggest selection of models is important for meaningful risk assessment. Article Summary LineA novel swine influenza A virus was rigorously assessed for pandemic potential in animal models and human surrogate culture models, illustrating a wide range in potential public health risk dependent on the model utilized.

microbiology↗

bioRxiv2022

Diversity and Evolution of Computationally Predicted T Cell Epitopes against Human Respiratory Syncytial Virus

Human respiratory syncytial virus (RSV) is a major cause of lower respiratory infection. Despite more than 60 years of research, there is no licensed vaccine. While B cell response is a major focus for vaccine design, the T cell epitope profile of RSV is also important for vaccine development. Here, we computationally predicted putative T cell epitopes in the Fusion protein (F) and Glycoprotein (G) of RSV wild circulating strains by predicting Major Histocompatibility Complex (MHC) class I and class II binding affinity. We limited our inferences to conserved epitopes in both F and G proteins that have been experimentally validated. We applied multidimensional scaling (MDS) to construct T cell epitope landscapes to investigate the diversity and evolution of T cell profiles across different RSV strains. We find the RSV strains are clustered into three RSV-A groups and two RSV-B groups on this T epitope landscape. These clusters represent divergent RSV strains with potentially different immunogenic profiles. In addition, our results show a greater proportion of F protein T cell epitope content conservation among recent epidemic strains, whereas the G protein T cell epitope content was decreased. Importantly, our results suggest that RSV-A and RSV-B have different patterns of epitope drift and replacement and that RSV-B vaccines may need more frequent updates. Our study provides a novel framework to study RSV T cell epitope evolution. Understanding the patterns of T cell epitope conservation and change may be valuable for vaccine design and assessment. Author SummaryLower respiratory infections caused by human respiratory syncytial virus (RSV) is a global health challenge. B cell epitope immune response has been the major focus of RSV vaccine and therapeutic development. However, T cell epitope induced immunity plays an important role in the resolution of RSV infection. While RSV genetic diversity has been widely reported, few studies focus on RSV T epitope diversity, which can influence vaccine effectiveness. Here, we use computationally predicted T cell epitope profiles of circulating strains to characterize the diversity and evolution of the T cell epitope of RSV A and B. We systematically evaluate the T epitope profile of RSV F and G proteins. We provide a T cell epitope landscape visualization that shows co-circulation of three RSV-A groups and two RSV-B groups, suggesting potentially distinct T cell immunity. Furthermore, our study shows different levels of F and G protein T cell epitope content conservation, which may be important to correlate with duration of vaccine protection. This study provides a novel framework to study RSV T cell epitope evolution, infer RSV T cell immunity at population levels and monitor RSV vaccine effectiveness.

evolutionary biology↗

bioRxiv2022

Phylogeny and Metadata Network Database for Epidemiologic Surveillance

AO_SCPLOWBSTRACTC_SCPLOWThe ongoing SARS-CoV-2 pandemic has highlighted the difficulty in integrating disparate data sources for epidemiologic surveillance. To address this challenge, we have created a graph database to integrate phylogenetic trees, associated metadata, and community surveillance data for phylodynamic inference. As an example use case, we divided 22,713 SARS-CoV-2 samples into 5 groups, generated maximum likelihood trees, and inferred a potential transmission network from a forest of minimum spanning trees built on patristic distances between samples. We then used Cytoscape to visualize the resultant graphs.

evolutionary biology↗

bioRxiv2021

Host diversity and behavior determine patterns of interspecies transmission and geographic diffusion of avian Influenza A subtypes among North American wild reservoir species

Wild birds can carry avian influenza viruses (AIV), including those with pandemic or panzootic potential, long distances. Even though AIV has a broad host range, few studies account for host diversity when estimating AIV spread. We analyzed AIV genomic sequences from North American wild birds, including 303 newly sequenced isolates, to estimate interspecies transmission and geographic diffusion patterns among multiple co-circulating subtypes. Our results show high transition rates within Anseriformes and Charadriiformes, but limited transitions between these orders. Patterns of interspecies transmission were positively associated with breeding habitat range overlap, and negatively associated with host genetic distance. Distance between regions (negative correlation) and summer temperature at origin (positive correlation) were strong predictors of diffusion. Taken together, this study demonstrates that host diversity and ecology can determine evolutionary processes that underlie AIV natural history and spread. Understanding these processes can provide important insights for effective control of AIV.

evolutionary biology↗

bioRxiv2019

Agricultural and geographic factors shaped the North American 2015 highly pathogenic avian influenza H5N2 outbreak

The 2014 - 2015 highly pathogenic avian influenza (HPAI) H5NX outbreak represents the largest and most expensive HPAI outbreak in the United States to date. Despite extensive traditional and molecular epidemiological studies, factors associated with the spread of HPAI among midwestern poultry premises remain unclear. To better understand the dynamics of this outbreak, 182 full genome HPAI H5N2 sequences isolated from commercial layer chicken and turkey production premises were analyzed using evolutionary models modified to incorporate epidemiological and geographic information. Epidemiological compartmental models constructed in a phylogenetic framework provided evidence that poultry type acted as a barrier to the transmission of virus among midwestern poultry farms. Furthermore, after initial introduction, a continuous external source of virus was not needed to explain the propagation of HPAI cases within the commercial poultry industries. Discrete trait diffusion models indicated that within state viral transitions occurred more frequently than inter-state transitions. Distance, road density and proportion of water coverage were all supported as associated with viral transition between county groups (Bayes Factor > 3.0). Together these findings indicate that the midwestern poultry industries were not a single homogenous population, but rather, the outbreak was shaped by poultry sectors and geographic factors.\n\nAUTHOR SUMMARYThe highly pathogenic avian influenza outbreak among poultry farms in the midwestern United States appears to be influenced by agricultural and geographic factors. After initial introduction of the virus into the poultry industries, no further introductions (such as from a wild bird reservoir) were necessary to explain the continuation of the outbreak from March to June 2015. Additionally, evidence suggests that proximity increases the chances of viral movement between two locations. While many hypotheses have been proposed to explain the transmission of virus among poultry farms, the support for road density as an important driver of viral movement suggests human-mediated viral transportation played a key role in the spread of the highly pathogenic H5N2 outbreak in North America.

epidemiology↗

bioRxiv2019

Genotype-dependent and non-gradient patterns of RSV gene expression

Respiratory syncytial virus (RSV) is a nonsegmented negative-strand (NNS) RNA virus and a leading cause of severe lower respiratory tract illness in infants and the elderly. Transcription of the ten RSV genes proceeds sequentially from the 3 promoter and requires conserved gene start (GS) and gene end (GE) signals. Previous studies using the prototypical GA1 genotype Long and A2 strains have indicated a gradient of gene transcription. However, recent reports show data that appear inconsistent with a gradient. To better understand RSV transcriptional regulation, mRNA abundances from five RSV genes were measured by quantitative real-time PCR (qPCR) in three cell lines and cotton rats infected with virus isolates belonging to four different genotypes (GA1, ON, GB1, BA). Relative mRNA levels reached steady-state between four and 24 hours post-infection. Steady-state patterns were genotype-specific and non-gradient, where mRNA levels from the G (attachment) gene exceeded those from the more promoter-proximal N (nucleocapsid) gene across isolates. Transcript stabilities could not account for the non-gradient patterns observed, indicating that relative mRNA levels more strongly reflect transcription than decay. While the GS signal sequences were highly conserved, their alignment with N protein in the helical ribonucleocapsid, i.e., N-phase, was variable, suggesting polymerase recognition of GS signal conformation affects transcription initiation. The effect of GS N-phase on transcription efficiency was tested using dicistronic minigenomes. Ratios of minigenome gene expression showed a switch-like dependence on N-phase with a period of seven nucleotides. Our results indicate that RSV gene expression is in part sculpted by polymerases that initiate transcription with a probability dependent on GS signal N-phase.\n\nAuthor SummaryRSV is a major viral pathogen that causes significant morbidity and mortality, especially in young children. Shortly after RSV enters a host cell, transcription from its nonsegmented negative-strand (NNS) RNA genome starts at the 3 promoter and proceeds sequentially. Transcriptional attenuation is thought to occur at each gene junction, resulting in a gradient of gene expression. However, recent studies showing non-gradient levels of RSV mRNA suggest that transcriptional regulation may have additional mechanisms. We show using RSV isolates belonging to four different genotypes that gene expression is genotype-dependent and one gene (the G or attachment gene) is consistently more highly expressed than an upstream neighbor. We hypothesize that variable alignment of highly conserved gene start (GS) signals with nucleoprotein (i.e., variable GS N-phase) can affect transcription and give rise to non-gradient patterns of gene expression. We show using dicistronic RSV minigenomes wherein the reporter genes differ only in the N-phase of one GS signal that GS N-phase affects gene expression. Our results suggest the existence of a novel mechanism of transcriptional regulation that might play a role in other NNS RNA viruses.

molecular biology↗

bioRxiv2017

Structurally informed evolutionary models improve phylogenetic reconstruction for emerging, seasonal, and pandemic influenza viruses

Precise estimation of genetic substitution patterns is critical for accurate reconstruction of pathogen phylogenies. Few studies of viral evolution account for variations of mutation rate across a single gene. This is especially true when considering evolution of segmented viruses where individual segments are short, encoding for few proteins. However, the structural and functional partitions of these proteins could provide valuable information for more accurate inference of viral evolution, due to the disparate immune selection pressure on different functional domains. Accurately reconstructed evolutionary features on specific functional domains can in turn provide biological information on viral protein and immune targets for vaccine design. In this study we developed and evaluated a structurally informed partitioning scheme that accounts for rate variation among immunogenic head and stalk domains of the surface protein hemagglutinin (HA) of influenza viruses. We evaluated the model fit and performance of four different models - HKY, SRD06 codon, HKY with a structurally informed partitioning scheme, SRD06 with a structurally informed partitioning scheme on pandemic A/H1N1pdm09, seasonal A/H1N1postpdm, A/H3N2, B-Yamagata-like and Victoria-like lineages, and two highly pathogenic avian influenza A viruses H5Nx and H7N9. Results showed that structurally informed partitioning with SRD06 performed better for all datasets with decisively statistical support. Significantly faster nucleotide substitution rates for head domain, compared to stalk domain was observed and may provide insight for stalk derived broadly-reactive vaccine design. Taken together, integrating a functionally informed partitioning scheme based on protein structures of immune targets allows for significant improvement of phylogenetic analysis and providing important biological insights.

evolutionary biology↗