Bacteria and viruses constantly evolve to outpace our defenses, creating new challenges in public health. A research team led by Dr. Noémie Lefrancq at the University of Cambridge has developed a novel method to identify these emerging threats.
This innovative system promises faster detection of infectious disease variants, including those resistant to antibiotics or capable of evading vaccines.
Dr. Lefrancq collaborated with Professor Julian Parkhill, a renowned expert in microbial genomics, to design a cutting-edge approach that could revolutionize global disease surveillance.
The new method uses genetic sequencing to monitor the evolution of pathogens in real time.
Unlike traditional systems that rely on expert panels to identify variants, the algorithm automatically maps genetic changes, creating “family trees” of pathogens. These trees reveal how rapidly variants spread in human populations, providing a clear and objective way to spot troubling trends.
“Our method provides a completely objective way of spotting new strains of disease-causing bugs by analyzing their genetics and spread in the population,” said Parkhill.
This automatic detection is not only quicker but also scalable across various pathogens, making it invaluable in resource-limited settings.
To demonstrate its utility, the researchers tested the system on Bordetella pertussis, the bacteria behind whooping cough.
Recent outbreaks of this disease, some of the worst in decades, highlight the need for improved surveillance. The technique immediately identified three new variants, previously undetected, circulating among populations.
“This method is timely for whooping cough, given its resurgence in many countries and the emergence of antimicrobial-resistant strains,” said Professor Sylvain Brisse of Institut Pasteur.
The team also applied the technique to Mycobacterium tuberculosis, which causes tuberculosis (TB). The analysis uncovered two antibiotic-resistant variants currently spreading, highlighting the method’s potential to guide treatment choices.
“If we see a rapid expansion of an antibiotic-resistant variant, we can adapt the prescribed antibiotics to limit its spread,” explained Professor Henrik Salje, senior author of the report. This adaptability could transform the fight against TB, a disease that still claims millions of lives annually.
The real-time insights this method provides have far-reaching implications.
During the COVID-19 pandemic, new variants such as Omicron emerged, each making the disease more transmissible than before. Understanding these evolutionary changes helps scientists and public health officials stay one step ahead.
“Our new method shows surprisingly quickly whether new transmissible variants of pathogens are circulating, and it can be applied to a huge range of bacteria and viruses,” said Dr. Lefrancq.
The researchers envision this technique as part of a comprehensive infectious disease monitoring system. By identifying variants capable of spreading more easily or resisting treatments, governments can adjust their responses, from vaccine development to antibiotic recommendations.
The relentless evolution of pathogens highlights the urgent need for advanced surveillance tools.
Genetic mutations allow viruses and bacteria to evade vaccines or treatments, posing a constant threat. Without robust monitoring systems, these changes could lead to outbreaks that catch health systems unprepared.
“This work could completely change how governments respond to infectious diseases,” said Salje. By integrating this approach into existing systems, public health agencies can take proactive steps to contain threats before they spiral out of control.
One of the method’s most significant advantages is its accessibility. It requires only a small number of samples from infected individuals, making it especially useful in low-resource settings.
These regions often lack the infrastructure for extensive surveillance but face the highest burden of infectious diseases.
Incorporating this technique into global health strategies could help level the playing field, ensuring all nations benefit from cutting-edge technology. The insights gained about disease variants could save countless lives by enabling timely and targeted interventions.
The team plans to refine the technique further and explore its applications in more pathogens.
By expanding its scope, they hope to address gaps in existing surveillance programs, which are currently limited to diseases like COVID-19 and influenza.
“This work is an important piece in the larger jigsaw of any public health response to infectious disease,” said Salje. As the system evolves, it could become a cornerstone of global health strategies, providing the data needed to combat emerging threats.
This remarkable system for variant detection represents a major leap forward in infectious disease surveillance.
By automating the identification of variants, it offers a faster, more objective, and widely applicable tool for monitoring pathogens.
The challenges posed by evolving pathogens demand a proactive, data-driven approach, and this research offers a powerful blueprint for success.
The study is published in the journal Nature.
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