Feeding your good gut bacteria through fibre in diet may boost body against infections
The group of bacteria called Enterobacteriaceae, including Klebsiella pneumoniae, Shigella, E.coli and others, is present at low levels as part of a healthy human gut microbiome. But at high levels - caused for example by increased inflammation in the body, or by eating contaminated food - these bugs can cause illness and disease. In extreme cases, too much Enterobacteriaceae in the gut can be life-threatening.
Researchers have used computational approaches including AI to analyse the gut microbiome composition of over 12,000 people across 45 countries from their stool samples. They found that a person’s microbiome ‘signature’ can predict whether a person’s gut is likely to be colonised by Enterobacteriaceae. The results are consistent across different states of health and geographic locations.
The researchers identified 135 gut microbe species that are commonly found in the absence of Enterobacteriaceae, likely protecting against infection.
Notable amongst the protective gut species are a group of bacteria called Faecalibacterium, which produce beneficial compounds called short-chain fatty acids by breaking down fibre in the foods we eat. This seems to protect against infection by a range of disease-causing Enterobacteriaceae bugs.
The researchers suggest that eating more fibre in our diet will support the growth of good bacteria - and crowd out the bad ones to significantly reduce the risk of illness.
In contrast, taking probiotics - which don’t directly change the environment in the gut - is less likely to affect the likelihood of Enterobacteriaceae infection.
The results are published today in the journal Nature Microbiology.
“Our results suggest that what we eat is potentially very important in controlling the likelihood of infection with a range of bacteria, including E.coli and Klebsiella pneumoniae, because this changes our gut environment to make it more hostile to invaders,” said Dr Alexandre Almeida, a researcher at the University of Cambridge’s Department of Veterinary Medicine and senior author of the paper.
He added: “By eating fibre in foods like vegetables, beans and whole grains, we can provide the raw material for our gut bacteria to produce short chain fatty acids - compounds that can protect us from these pathogenic bugs.”
Klebsiella pneumonia can cause pneumonia, meningitis and other infections. The alarming global rise in antibiotic resistance to this bacterial pathogen has led scientists to look for new ways of keeping it, and other similar infectious bacteria, under control.
“With higher rates of antibiotic resistance there are fewer treatment options available to us. The best approach now is to prevent infections occurring in the first place, and we can do this by reducing the opportunities for these disease-causing bacteria to thrive in our gut,” said Almeida.
A new understanding of gut microbe interactions
Earlier research to understand interactions between the different bacteria in our gut has used mouse models. But some of these new results are at odds with previous findings.
The new study revealed that 172 species of gut microbe can coexist with disease-causing Enterobacteriaceae bugs. Many of these species are functionally similar to the bugs: they need the same nutrients to survive. Previously it was thought that competition for resources would stop the disease-causing bacteria from getting established in the gut.
This has important implications for treatment: taking probiotics that compete for the same nutrients with the bad bacteria to try and starve them out isn’t going to work. The researchers say that it will be more beneficial to change the environment in the gut, for instance through diet, to reduce the risk of infection with Enterobacteriaceae.
“This study highlights the importance of studying pathogens not as isolated entities, but in the context of their surrounding gut microbiome,” said Dr Qi Yin, a visiting researcher at the University of Cambridge’s Department of Veterinary Medicine and first author of the report.
The research was funded by the Medical Research Council.
Reference: Yin, Q. et al: 'Ecological dynamics of Enterobacteriaceae in the human gut microbiome across global populations.’ Jan 2025, Nature Microbiology. DOI: 10.1038/s41564-024-01912-6.
A new study has found that the composition of your gut microbiome helps predict how likely you are to succumb to potentially life-threatening infection with Klebsiella pneumoniae, E.coli and other bugs - and it may be altered by changing your diet.
Our results suggest that what we eat is potentially very important in controlling the likelihood of infection with a range of bacteria.Alexandre AlmeidaCredit Oleksandra Troian GettyIntestine with microbiome
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System to auto-detect new variants will inform better response to future infectious disease outbreaks
The new approach uses samples from infected humans to allow real-time monitoring of pathogens circulating in human populations, and enable vaccine-evading bugs to be quickly and automatically identified. This could inform the development of vaccines that are more effective in preventing disease.
The approach can also quickly detect emerging variants with resistance to antibiotics. This could inform the choice of treatment for people who become infected - and try to limit the spread of the disease.
It uses genetic sequencing data to provide information on the genetic changes underlying the emergence of new variants. This is important to help understand why different variants spread differently in human populations.
There are very few systems in place to keep watch for emerging variants of infectious diseases, apart from the established COVID and influenza surveillance programmes. The technique is a major advance on the existing approach to these diseases, which has relied on groups of experts to decide when a circulating bacteria or virus has changed enough to be designated a new variant.
By creating ‘family trees’, the new approach identifies new variants automatically based on how much a pathogen has changed genetically, and how easily it spreads in the human population – removing the need to convene experts to do this.
It can be used for a broad range of viruses and bacteria and only a small number of samples, taken from infected people, are needed to reveal the variants circulating in a population. This makes it particularly valuable for resource-poor settings.
The report is published today 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,” said Dr Noémie Lefrancq, first author of the report, who carried out the work at the University of Cambridge’s Department of Genetics.
Lefrancq, who is now based at ETH Zurich, added: “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.”
“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,” said Professor Julian Parkhill, a researcher in the University of Cambridge’s Department of Veterinary Medicine who was involved in the study.
Testing the technique
The researchers used their new technique to analyse samples of Bordetella pertussis, the bacteria that causes whooping cough. Many countries are currently experiencing their worst whooping cough outbreaks of the last 25 years. It immediately identified three new variants circulating in the population that had been previously undetected.
“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,” said Professor Sylvain Brisse, Head of the National Reference Center for whooping cough at Institut Pasteur, who provided bioresources and expertise on Bordetella pertussis genomic analyses and epidemiology.
In a second test, they analysed samples of Mycobacterium tuberculosis, the bacteria that causes Tuberculosis. It showed that two variants with resistance to antibiotics are spreading.
“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,” said Professor Henrik Salje in the University of Cambridge’s Department of Genetics, senior author of the report.
He added: “If we see a rapid expansion of an antibiotic-resistant variant, then we could change the antibiotic that’s being prescribed to people infected by it, to try and limit the spread of that variant.”
The researchers say this work is an important piece in the larger jigsaw of any public health response to infectious disease.
A constant threat
Bacteria and viruses that cause disease are constantly evolving to be better and faster at spreading between us. During the COVID pandemic, this led to the emergence of new strains: the original Wuhan strain spread rapidly but was later overtaken by other variants, including Omicron, which evolved from the original and were better at spreading. Underlying this evolution are changes in the genetic make-up of the pathogens.
Pathogens evolve through genetic changes that make them better at spreading. Scientists are particularly worried about genetic changes that allow pathogens to evade our immune system and cause disease despite us being vaccinated against them.
“This work has the potential to become an integral part of infectious disease surveillance systems around the world, and the insights it provides could completely change the way governments respond,” said Salje.
The research was primarily funded by the European Research Council.
Reference: Lefrancq, N. et al: ‘Learning the fitness dynamics of pathogens from phylogenies.’ January 2025, DOI: 10.1038/s41586-024-08309-9
Researchers have come up with a new way to identify more infectious variants of viruses or bacteria that start spreading in humans - including those causing flu, COVID, whooping cough and tuberculosis.
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 SaljeMilan Krasula on Getty
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AI algorithm accurately detects heart disease in dogs
The research team, led by the University of Cambridge, adapted an algorithm originally designed for humans and found it could automatically detect and grade heart murmurs in dogs, based on audio recordings from digital stethoscopes. In tests, the algorithm detected heart murmurs with a sensitivity of 90%, a similar accuracy to expert cardiologists.
Heart murmurs are a key indicator of mitral valve disease, the most common heart condition in adult dogs. Roughly one in 30 dogs seen by a veterinarian has a heart murmur, although the prevalence is higher in small breed dogs and older dogs.
Since mitral valve disease and other heart conditions are so common in dogs, early detection is crucial as timely medication can extend their lives. The technology developed by the Cambridge team could offer an affordable and effective screening tool for primary care veterinarians, and improve quality of life for dogs. The results are reported in the Journal of Veterinary Internal Medicine.
“Heart disease in humans is a huge health issue, but in dogs it’s an even bigger problem,” said first author Dr Andrew McDonald from Cambridge’s Department of Engineering. “Most smaller dog breeds will have heart disease when they get older, but obviously dogs can’t communicate in the same way that humans can, so it’s up to primary care vets to detect heart disease early enough so it can be treated.”
Professor Anurag Agarwal, who led the research, is a specialist in acoustics and bioengineering. “As far as we’re aware, there are no existing databases of heart sounds in dogs, which is why we started out with a database of heart sounds in humans,” he said. “Mammalian hearts are fairly similar, and when things go wrong, they tend to go wrong in similar ways.”
The researchers started with a database of heart sounds from about 1000 human patients and developed a machine learning algorithm to replicate whether a heart murmur had been detected by a cardiologist. They then adapted the algorithm so it could be used with heart sounds from dogs.
The researchers gathered data from almost 800 dogs who were undergoing routine heart examination at four veterinary specialist centres in the UK. All dogs received a full physical examination and heart scan (echocardiogram) by a cardiologist to grade any heart murmurs and identify cardiac disease, and heart sounds were recorded using an electronic stethoscope. By an order of magnitude, this is the largest dataset of dog heart sounds ever created.
“Mitral valve disease mainly affects smaller dogs, but to test and improve our algorithm, we wanted to get data from dogs of all shapes, sizes and ages,” said co-author Professor Jose Novo Matos from Cambridge’s Department of Veterinary Medicine, a specialist in small animal cardiology. “The more data we have to train it, the more useful our algorithm will be, both for vets and for dog owners.”
The researchers fine-tuned the algorithm so it could both detect and grade heart murmurs based on the audio recordings, and differentiate between murmurs associated with mild disease and those reflecting advanced heart disease that required further treatment.
“Grading a heart murmur and determining whether the heart disease needs treatment requires a lot of experience, referral to a veterinary cardiologist, and expensive specialised heart scans,” said Novo Matos. “We want to empower general practitioners to detect heart disease and assess its severity to help owners make the best decisions for their dogs.”
Analysis of the algorithm’s performance found it agreed with the cardiologist’s assessment in over half of cases, and in 90% of cases, it was within a single grade of the cardiologist’s assessment. The researchers say this is a promising result, as it is common for there to be significant variability in how different vets grade heart murmurs.
“The grade of heart murmur is a useful differentiator for determining next steps and treatments, and we’ve automated that process,” said McDonald. “For vets and nurses without as much stethoscope skill, and even those who are incredibly skilled with a stethoscope, we believe this algorithm could be a highly valuable tool.”
In humans with valve disease, the only treatment is surgery, but for dogs, effective medication is available. “Knowing when to medicate is so important, in order to give dogs the best quality of life possible for as long as possible,” said Agarwal. “We want to empower vets to help make those decisions.”
“So many people talk about AI as a threat to jobs, but for me, I see it as a tool that will make me a better cardiologist,” said Novo Matos. “We can’t perform heart scans on every dog in this country – we just don’t have enough time or specialists to screen every dog with a murmur. But tools like these could help vets and owners, so we can quickly identify those dogs who are most in need of treatment.”
The research was supported in part by the Kennel Club Charitable Trust, the Medical Research Council, and Emmanuel College Cambridge.
Reference:
Andrew McDonald et al. ‘A machine learning algorithm to grade canine heart murmurs and stage preclinical myxomatous mitral valve disease.’ Journal of Veterinary Internal Medicine (2024). DOI: 10.1111/jvim.17224
Researchers have developed a machine learning algorithm to accurately detect heart murmurs in dogs, one of the main indicators of cardiac disease, which affects a large proportion of some smaller breeds such as King Charles Spaniels.
Jacqueline GargetHuxley, a healthy volunteer Havanese, undergoes a physical examination at the Queen's Veterinary School Hospital, Cambridge.
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