New Strategy Identifies Superior Pathogen Variants

A new technique known as phylowave showed potential to identify differences in fitness among viral and bacterial pathogens, based on data from a study including SARS-CoV-2, influenza A subtype H3N2, Bordetella pertussis, and Mycobacterium tuberculosis.

Understanding the genetic diversity and identifying more transmissible pathogens has implications for public health, such as opportunities for targeted vaccination and greater understanding of disease ecology, but identifying lineages with increased fitness remains a challenge, wrote corresponding author Noemie Lefrancq, PhD, of the University of Cambridge, Cambridge, United Kingdom, and colleagues in an article published in the journal Nature.

“While the population composition of some pathogens, notably SARS-CoV-2 and influenza, is widely studied, others, such as Bordetella pertussis, remain poorly characterized,” said Lefrancq in an interview.

In the article, the researchers developed a model known as phylowave that analyzes phylogenetic trees and summarizes population composition changes that signal which lineages of pathogens are likely to be more transmissible.

The researchers ran a simulation comparing one lineage expanding with a known fitness advantage vs a background population, and phylowave identified the fitter of the emerging lineages and detected specific changes in amino acids linked to changes in fitness. Phylowave consistently identified the emerging lineage in cases in which the fitness difference between strains was greater than 0.02 per year.

The researchers applied the phylowave approach to SARS-CoV-2, H3N2, B pertussis and M tuberculosis.

For each of these pathogens, phylowave showed a high level of agreement between phylowave’s identification of the most transmissible lineages and previously defined highly transmissible lineages. Notably, phylowave identified three previously unidentified B pertussis lineages with evidence of increased fitness/high transmissibility.

Clinical Potential

Phylowave provides a timely opportunity to translate the available pathogen genetic data into interpretable quantities, which can help guide public health action.

“We were surprised at how fast and general the approach is,” Lefrancq told Medscape Medical News. “Phylowave works on a vast range of pathogens from viruses to bacteria, and the index dynamics can be obtained in minutes on a laptop,” she said.

The method has important clinical implications, Lefrancq said. “Our method provides a completely objective way of spotting new strains of disease-causing bugs, by analyzing their genetics and how they are spreading in the population. This means we can rapidly and effectively spot the emergence of new highly transmissible strains,” she said.

One potential limitation: Although the method is robust to the size of the pathogen datasets, it requires that the datasets are representative of the circulating diversity, with no intrinsic bias in certain variants, Lefrancq noted. 

However, using phylowave to quantify the relative fitness advantage of new pathogen strains can help identify drivers of emerging strains, “including the role of population immunity derived from natural infection or vaccination,” the researchers concluded.

Public Health Implications: Identifying Threats, Understanding Spread

“Whole genome pathogen tracking has become the gold standard in infectious disease research, and phylogenetic approaches are at its core,” said Paul Planet, MD, assistant professor of pediatrics (Infectious Diseases) at the University of Pennsylvania, and co-director of the Center for Microbial Medicine at Children’s Hospital of Philadelphia, in an interview.

However, how to group organisms into new emerging threats from simply examining the phylogenetic trees themselves is not always clear, said Planet, who was not involved in the research. The current work provides a strategy to detect emerging threats based on the patterns in the phylogenetic tree that is not based on arbitrary decisions, he said. The phylowave research also can find genome positions that may be important for the increased fitness of emerging pathogens, which can increase understanding of the basic biology of disease spread, he added.

In terms of public health, “the technique offers a standardized method to track emerging diseases and detect replacement of pathogens with new strains as we saw during the SARS-CoV-2 pandemic and have seen for years with pathogens such as MRSA,” Planet noted.

The phylowave has its limitations, Planet told Medscape Medical News. “It still relies on the sometimes arduous and computationally intense phylogenetic and comparative genomic techniques, which may make this type of analysis difficult to use in different research and clinical environments. However, its scalability is a big plus,” he said.

“As with any tool, this approach will need to be tested as we move forward to test its ability to detect new strains and waves; in general, using and comparing multiple tools and approaches will be important going forward,” Planet said.

The study was supported by the European Research Council and the UK Research and Innovation, Medical Research Council. The researchers had no financial conflicts to disclose. Planet had no financial conflicts to disclose.