Phylowave, a novel computational tool, shows promise in identifying more transmissible pathogen lineages by analyzing phylogenetic trees and population composition changes. This advancement has significant implications for public health, enabling targeted vaccination strategies and a deeper understanding of disease ecology.
A new technique, called phylowave, has shown promise in identifying differences in fitness among viral and bacterial pathogens. This breakthrough, based on a study that included SARS-CoV-2, influenza A subtype H3N2, and other pathogens, offers potential implications for public health . Understanding the genetic diversity and pinpointing more transmissible pathogens can lead to targeted vaccination strategies and a deeper understanding of disease ecology.
However, identifying lineages with increased fitness remains a significant challenge. Researchers at the University of Cambridge, led by Dr. Noemie Lefrancq, developed phylowave, a model that analyzes phylogenetic trees and summarizes population composition changes. These changes act as signals, indicating which pathogen lineages are likely to be more transmissible. The team ran simulations comparing a lineage expanding with a known fitness advantage to a background population. Phylowave accurately identified the fitter lineage and detected specific amino acid changes linked to fitness variations. This method consistently identified the emerging lineage when the fitness difference between strains exceeded 0.02 per year.For each pathogen studied, phylowave demonstrated a high level of agreement between its identification of the most transmissible lineages and previously defined highly transmissible lineages. Notably, it identified three previously unidentified highly transmissible lineages. Phylowave offers a valuable opportunity to translate available pathogen genetic data into interpretable quantities, guiding public health action. The method is applicable to a wide range of pathogens, from viruses to bacteria, and can be executed quickly on a standard laptop. Dr. Lefrancq highlights the clinical implications, stating that phylowave provides an entirely objective way to detect new strains of disease-causing organisms by analyzing their genetics and spread within the population. This enables rapid and effective identification of emerging, highly transmissible strains. Although the method is robust to the size of pathogen datasets, it requires representative datasets reflecting circulating diversity, without any inherent bias towards specific variants. However, using phylowave to quantify the relative fitness advantage of new pathogen strains can help identify the drivers of emerging strains, including the role of population immunity acquired through natural infection or vaccination. The study's findings have been lauded by experts in the field. Dr. Paul Planet, assistant professor of pediatrics (Infectious Diseases) at the University of Pennsylvania, acknowledges the significance of whole genome pathogen tracking in infectious disease research, with phylogenetic approaches at its core. He emphasizes that phylowave offers a standardized strategy to detect emerging threats based on patterns in phylogenetic trees, moving beyond arbitrary decisions. Moreover, the method can pinpoint genome positions potentially important for the increased fitness of emerging pathogens, enhancing our understanding of disease spread. Dr. Planet also notes the public health implications, stating that the technique offers a way to track emerging diseases and detect pathogen replacement with new strains, as observed during the SARS-CoV-2 pandemic and with pathogens like MRSA. While acknowledging the potential limitations, Dr. Planet emphasizes the scalability of phylowave as a major advantage. He encourages further testing to validate its ability to detect new strains and waves, emphasizing the importance of using and comparing multiple tools and approaches for comprehensive analysis. The study was supported by the European Research Council and the UK Research and Innovation, Medical Research Council
Phylowave Pathogen Fitness Transmissibility Public Health Phylogenetics
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