Biology subjects

Dhanasekaran, V.

Publications and source records attributed to Dhanasekaran, V..

5 recordsLinked to original sources

bioRxiv2026

Epistasis facilitates the long-term antigenic evolution of the influenza B virus hemagglutinin

The antigenic drift of viral glycoproteins must be balanced by purifying selection pressure to maintain functionality. Understanding these evolutionary processes is key to predicting and combating viral evolution but is primarily based on influenza A(H3N2), which may limit generalisability. By characterising the influenza B virus haemagglutinin (HA) over 8 decades of circulation in humans, we found continuous genetic diversification, punctuated with antigenic changes that did not follow a linear path in antigenic space. Antigenic change is primarily underpinned by re-occurring mutations and deletions at positions 136, 150, 162-165, 197 and 203. These residues form complex epistatic networks that modulate the antigenic impact of mutation recycling. They also generate permissive backbones on which immune escape can emerge with limited replicative fitness cost. Our study identifies critical similarities and differences with A(H3N2) evolution and demonstrates the role of epistasis in balancing antigenic novelty with viral fitness. Our findings and genetic, antigenic and phenotypic datasets support the development of genotype-to-phenotype prediction tools, but such predictions need to capture the complex outcomes of epistasis.

microbiology↗

bioRxiv2023

Long-term epidemiology and evolution of swine influenza viruses in Vietnam

Swine influenza virus (SwIV) surveillance in Hanoi, Vietnam from 2013-2019 found gene pool enrichment from imported swine from Asia and North America. Long-term maintenance, persistence and reassortment of SwIV lineages was observed. Co-circulation of H1-{delta}1a viruses with other SwIV genotypes raises concern due to its zoonotic potential.

microbiology↗

bioRxiv2022

The episodic resurgence of highly pathogenic avian influenza H5 virus

Highly pathogenic avian influenza (HPAI) H5N1 activity has intensified globally since 2021, replacing the dominant clade 2.3.4.4 H5N8 virus. H5N1 viruses have spread rapidly to four continents, causing increasing reports of mass mortality in wild birds and poultry. The ecological and virological properties required for future mitigation strategies are unclear. Using epidemiological, spatial and genomic approaches, we demonstrate changes in the source of resurgent H5 HPAI and reveal significant shifts in virus ecology and evolution. Outbreak data indicates key resurgent events in 2016/17 and 2020/21 that contributed to the panzootic spread of H5N1 in 2021/22, including an increase in virus diffusion velocity and persistence in wild birds. Genomic analysis reveals that the 2016/17 epizootics originated in Asia, where HPAI H5 reservoirs are documented as persistent. However, in 2020/21, 2.3.4.4b H5N8 viruses emerged in domestic poultry in Africa, featuring several novel mutations altering the HA structure, receptor binding, and antigenicity. The new H5N1 virus emerged from H5N8 through reassortment in wild birds along the Adriatic flyway around the Mediterranean Sea. It was characterized by extensive reassortment with low pathogenic avian influenza in domestic and wild birds as it spread globally. In contrast, earlier outbreaks of H5N8 were caused by a more stable genetic constellation, highlighting dynamic changes in HPAI H5 genomic evolution. These results suggest a shift in the epicenter of HPAI H5 beyond Asia to new regions in Africa, the Middle East, Europe, and North and South America. The persistence of HPAI H5 with resurgence potential in domestic birds indicates that elimination strategies remain a high priority.

microbiology↗

bioRxiv2020

Saturation of influenza virus neutralization and antibody consumption can both lead to bistable growth kinetics

Influenza virus is a major human health threat. Neutralizing antibodies elicited through prior infection or vaccination play an irreplaceable role in protection from subsequent infection. The efficacy of antibody-dependent vaccines relies on both virus replication and neutralization, but their quantitative relationship was unknown. Here we use mathematical models to quantitatively investigate viral survivability determined by antibody concentration and inocula size. We performed focus reduction assays for 49 seasonal influenza A/H3N2 viruses circulating during 2017-2019 against influenza antisera raised in ferrets, and find that the antibody consumption rates of individual reactions were either small or large, and this was strongly positively correlated with virus saturation. Regardless of antibody consumption rate, virus-antibody interactions always lead to antibody-induced bistable viral kinetics. As a result, at a specific interval of antibody concentration, small viral inocula are eliminated but not large virus inocula, which is triggered by saturated virus neutralization or antibody consumption. Our finding highlights virus-antibody interaction with different antigenic properties, thereby explaining commonly observed influenza re-infection and enhancing vaccine efficiency.

microbiology↗

bioRxiv2019

Bayesian Evaluation of Temporal Signal in Measurably Evolving Populations

Phylogenetic methods can use the sampling times of molecular sequence data to calibrate the molecular clock, enabling the estimation of evolutionary rates and timescales for rapidly evolving pathogens and data sets containing ancient DNA samples. A key aspect of such calibrations is whether a sufficient amount of molecular evolution has occurred over the sampling time window, that is, whether the data can be treated as having come from a measurably evolving population. Here we investigate the performance of a fully Bayesian evaluation of temporal signal (BETS) in sequence data. The method involves comparing the fit to the data of two models: a model in which the data are accompanied by the actual (heterochronous) sampling times, and a model in which the samples are constrained to be contemporaneous (isochronous). We conducted simulations under a wide range of conditions to demonstrate that BETS accurately classifies data sets according to whether they contain temporal signal or not, even when there is substantial among-lineage rate variation. We explore the behaviour of this classification in analyses of five empirical data sets: modern samples of A/H1N1 influenza virus, the bacterium Bordetella pertussis, coronaviruses from mammalian hosts, ancient DNA from Hepatitis B virus and mitochondrial genomes of dog species. Our results indicate that BETS is an effective alternative to other tests of temporal signal. In particular, this method has the key advantage of allowing a coherent assessment of the entire model, including the molecular clock and tree prior which are essential aspects of Bayesian phylodynamic analyses.

bioinformatics↗