By using samples from diseased persons, the new method makes it possible to monitor infections in human populations in real-time and to swiftly and automatically identify bugs that evade vaccination. This might help create vaccinations that are more successful at avoiding illness.
The approach will quickly show which variants of a pathogen are most worrying in terms of the potential to make people ill. This means a vaccine can be specifically targeted against these variants, to make it as effective as possible.
Henrik Salje
Additionally, the method can promptly identify new antibiotic-resistant variations. This might help determine the course of therapy for those who contract the illness and attempt to stop its spread.
It provides details on the genetic alterations that underlie the generation of novel variants using genetic sequencing data. To better understand why various variations propagate in human populations in different ways, this is crucial.
Other than the well-established COVID and influenza surveillance programs, there aren’t many mechanisms in place to monitor for new forms of infectious illnesses. The method is a significant improvement over the current strategy for treating these illnesses, which has depended on panels of specialists to determine whether a bacterium or virus in circulation has mutated sufficiently to be classified as a new variation.
Without the need to gather specialists, the new method uses “family trees” to automatically identify new variations based on how much a disease has altered genetically and how readily it spreads in the human population.
Only a few samples from sick individuals are required to identify the variations circulating in a community, and it may be used to a wide variety of bacteria and viruses. Because of this, it is especially useful in environments with limited resources.
Their findings were published in the journal Nature.
Our new method provides a way to show, surprisingly quickly, whether there are new transmissible variants of pathogens circulating in populations – and it can be used for a huge range of bacteria and viruses,
We can even use it to start predicting how new variants are going to take over, which means decisions can quickly be made about how to respond.
Dr Noémie Lefrancq
Our method provides a completely objective way of spotting new strains of disease-causing bugs, by analysing their genetics and how they’re spreading in the population. This means we can rapidly and effectively spot the emergence of new highly transmissible strains.
Julian Parkhill
Bordetella pertussis, the bacterium that causes whooping cough, was analyzed in samples using the researchers’ novel method. The present whooping cough epidemics in several nations are the worst in the past 25 years. Immediately, it recognized three previously unidentified novel variations that were circulating in the community.
The novel method proves very timely for the agent of whooping cough, which warrants reinforced surveillance given its current comeback in many countries and the worrying emergence of antimicrobial resistant lineages.
Sylvain Brisse
They examined samples of Mycobacterium tuberculosis, the bacterium that causes TB, in a second test. It revealed that two antibiotic-resistant genotypes are proliferating.
Disease-causing bacteria and viruses are always improving their ability to spread among humans. This resulted in the creation of new strains during the COVID-19 pandemic. The initial Wuhan strain spread quickly, but other varieties, such as Omicron, which improved on the original and disseminated more effectively, eventually surpassed it. Changes in the infections’ genetic composition are the basis of this evolution.
Through genetic alterations, pathogens become more adept at spreading. Genetic alterations that enable infections to elude our immune system and cause illness even when we have been vaccinated against them are of special concern to scientists.
Source: University of Cambridge News
Journal Reference: Lefrancq, Noémie, et al. “Learning the Fitness Dynamics of Pathogens from Phylogenies.” Nature, 2025, pp. 1-8, DOI: https://doi.org/10.1038/s41586-024-08309-9.
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