̽��ֱ�� of Cambridge - Cambridge Infectious Diseases

Cambridge initiative to address risks of future engineered pandemics

cjb250 — Thu, 27 Feb 2025 08:00:39 +0000

These are some of the questions being addressed by a new initiative launched today at the ̽��ֱ�� of Cambridge, which seeks to address the urgent challenge of managing the risks of future engineered pandemics.

̽��ֱ��Engineered Pandemics Risk Management Programme aims to understand the social and biological factors that might drive an engineered pandemic and to make a major contribution to building the UK’s capability for managing these risks. It will build a network of experts from academia, government, and industry to tackle the problem.

Increased security threats from state and non-state actors, combined with increased urbanisation and global mobility, means the threat of deliberate pathogen release must be taken seriously as must other intertwined aspects of pandemic risk such as mis- and disinformation, the erosion of trust in a number of institutions and an increasingly volatile geopolitical context. Further potential risks are posed by recent developments in gene-editing tools and artificial intelligence, which have rapidly advanced technological capability that may make it easier to engineer potential pandemic pathogens.

Professor Clare Bryant from the Department of Medicine at the ̽��ֱ�� of Cambridge said: “There is a great opportunity to take a joined-up approach to managing the risks posed by engineered pandemics. We need experts and agencies across the spectrum to work together to develop a better understanding of who or what might drive such events and what their likely impact would be. And we need evidence-informed policies and networks in place that would help us respond to – or better still, prevent – such an eventuality.”

̽��ֱ��aims of the Engineered Pandemics Risk Management Programme are:
To develop the conceptual underpinnings for the risk management of engineered pandemics based on interdisciplinary research
To support the capability of the UK’s engineered pandemic risk policy and practice, including building and maintaining networks that connect government, academia and industry.
To strengthen the international networks that will support this work globally

There are four main strands of work:

Social determinants of engineered pandemic threat

This strand will look at the actors who have the potential to engineer harmful pathogens, either deliberately or accidentally. It will ask questions such as: What could motivate bioterrorism in the coming decades? Who might the relevant actors be? What are the kinds of engineered pandemic that someone might want to create?

Dr Rob Doubleday, Executive Director of the Centre for Science and Policy at the ̽��ֱ�� of Cambridge, said: “ ̽��ֱ��common narrative is that there’s a wide range of potential actors out there who want to create bioweapons but don’t yet have the technical means. But in fact, there’s been very little work to really understand who these people might be, and their relationship to emerging technology. To explore these questions, we need a broad network including social scientists, biosecurity researchers, criminologists, experts in geopolitics and counterterrorism.”

̽��ֱ��strand will also look at the governance of scientific research in areas that may facilitate an engineered pandemic, whether unwittingly or maliciously, aiming to deliver a policy framework that enables freedom of intellectual research while managing real and apparent risk in infectious disease research.

Professor Bryant said: “As scientists, we’re largely responsible for policing our own work and ensuring integrity, trustworthiness and transparency, and for considering the consequences of new knowledge and how it might be used. But with the rapid progress of genomic technologies and AI, self-regulation becomes more difficult to manage. We need to find governance frameworks that balance essential scientific progress with its potential misapplication.”

Biological determinants of engineered pandemic threat

Recognising that the most likely cause of an engineered pandemic would be the deliberate release of a naturally-occurring pathogen – viral or bacterial, for example – rather than a man-made pathogen, this strand aims to understand what might make a particular pathogen infectious and how our immune systems respond to infection. This knowledge will allow researchers to screen currently available drugs to prevent or treat infection and to design vaccines quickly should a pandemic occur.

Modelling threats and risk management of engineered pandemics

̽��ֱ��Covid-19 pandemic highlighted practical problems of dealing with pandemic infections, from the provision of personal protective equipment (PPE) to ensuring a sufficient supply of vaccine doses and availability of key medications. Modelling the potential requirements of a pandemic, how they could be delivered, how ventilation systems could be modiﬁed, what biosafety measures could be taken, for example, are all key challenges for managing any form of pandemic. This strand will address how existing modelling approaches would need to be adapted for a range of plausible engineered pandemics.

Policy innovation challenges

Working with the policy community, the Cambridge team will co-create research that directly addresses policy needs and involves policy makers. It will support policy makers in experimenting with more joined-up approaches through testing, learning and adapting solutions developed in partnership.

̽��ֱ��Engineered Pandemics Risk Management Programme is supported by a £5.25 million donation to the Centre for Research in the Arts, Humanities and Social Sciences (CRASSH) at the ̽��ֱ�� of Cambridge. ̽��ֱ��team intends it to form a central component of a future Pandemic Risk Management Centre, for which it is now fundraising.

Professor Joanna Page, Director of CRASSH, said: “Cambridge has strengths across a broad range of disciplines – from genetics and immunology to mathematical modelling to existential risk and policy engagement – that can make a much-needed initiative such as this a success.”

To find out more, visit the Engineered Pandemic Risk Management website.

Covid-19 showed us how vulnerable the world is to pandemics – but what if the next pandemic were somehow engineered? How would the world respond – and could we stop it happening in the first place?

There is a great opportunity to take a joined-up approach to managing the risks posed by engineered pandemics

Clare Bryant

Martin Sanchez

Illustration showing global pandemic spread

̽��ֱ��text in this work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. Images, including our videos, are Copyright © ̽��ֱ�� of Cambridge and licensors/contributors as identified. All rights reserved. We make our image and video content available in a number of ways – on our main website under its Terms and conditions, and on a range of channels including social media that permit your use and sharing of our content under their respective Terms.

Yes

Licence type:

Public Domain

Feeding your good gut bacteria through fibre in diet may boost body against infections

jg533 — Fri, 10 Jan 2025 10:21:10 +0000

̽��ֱ��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. ̽��ֱ��results are consistent across different states of health and geographic locations.

̽��ֱ��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.

̽��ֱ��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.

̽��ֱ��results were published on 10 January in the journal 'Nature Microbiology' – read the results in full on Nature's website.

“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 ̽��ֱ�� 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. ̽��ֱ��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. ̽��ֱ��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.

̽��ֱ��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. ̽��ֱ��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 ̽��ֱ�� of Cambridge’s Department of Veterinary Medicine and first author of the report.

̽��ֱ��research was funded by the Medical Research Council.

System to auto-detect new variants will inform better response to future infectious disease outbreaks

jg533 — Wed, 01 Jan 2025 16:00:35 +0000

̽��ֱ��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.

̽��ֱ��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. ̽��ֱ��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.

̽��ֱ��report was 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,” said Dr Noémie Lefrancq, first author of the report, who carried out the work at the ̽��ֱ�� 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 ̽��ֱ�� of Cambridge’s Department of Veterinary Medicine who was involved in the study.

Testing the technique

̽��ֱ��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 3 new variants circulating in the population that had been previously undetected.

“ ̽��ֱ��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 2 variants with resistance to antibiotics are spreading.

“ ̽��ֱ��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 ̽��ֱ�� 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.”

̽��ֱ��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.

̽��ֱ��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.

̽��ֱ��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

Milan Krasula on Getty

Yes

Licence type:

Attribution

AI able to identify drug-resistant typhoid-like infection from microscopy images in matter of hours

cjb250 — Mon, 08 Jul 2024 07:00:00 +0000

Antimicrobial resistance is an increasing global health issue that means many infections are becoming difficult to treat, with fewer treatment options available. It even raises the spectre of some infections becoming untreatable in the near future.

One of the challenges facing healthcare workers is the ability to distinguish rapidly between organisms that can be treated with first-line drugs and those that are resistant to treatment. Conventional testing can take several days, requiring bacteria to be cultured, tested against various antimicrobial treatments, and analysed by a laboratory technician or by machine. This delay often results in patients being treated with an inappropriate drug, which can lead to more serious outcomes and, potentially, further drive drug resistance.

In research published in Nature Communications, a team led by researchers in Professor Stephen Baker’s Lab at the ̽��ֱ�� of Cambridge developed a machine-learning tool capable of identifying from microscopy images Salmonella typhimurium bacteria that are resistant to the first-line antibiotic ciprofloxacin – even without testing the bacteria against the drug.

S. Typhimurium causes gastrointestinal illness and typhoid-like illness in severe cases, whose symptoms include fever, fatigue, headache, nausea, abdominal pain, and constipation or diarrhoea. In severe cases, it can be life threatening. While infections can be treated with antibiotics, the bacteria are becoming increasingly resistant to a number of antibiotics, making treatment more complicated.

̽��ֱ��team used high-resolution microscopy to examine S. Typhimurium isolates exposed to increasing concentrations of ciprofloxacin and identified the five most important imaging features for distinguishing between resistant and susceptible isolates.

They then trained and tested machine-learning algorithm to recognise these features using imaging data from 16 samples.

̽��ֱ��algorithm was able to correctly predict in each case whether or not bacteria were susceptible or resistant to ciprofloxacin without the need for the bacteria to be exposed to the drug. This was the case for isolates cultured for just six hours, compared to the usual 24 hours to culture a sample in the presence of antibiotic.

Dr Tuan-Anh Tran, who worked on this research while a PhD student at the ̽��ֱ�� of Oxford and is now based at the ̽��ֱ�� of Cambridge, said: “S. Typhimurium bacteria that are resistant to ciprofloxacin have several notable differences to those still susceptible to the antibiotic. While an expert human operator might be able to identify some of these, on their own they wouldn't be enough to confidently distinguish resistant and susceptible bacteria.

“ ̽��ֱ��beauty of the machine learning model is that it can identify resistant bacteria based on a few subtle features on microscopy images that human eyes cannot detect.”

In order for a sample to be analysed using this approach, it would still be necessary to isolate the bacteria from a sample – for example a blood, urine or stool sample. However, because the bacteria do not need to be tested against ciprofloxacin, this means the whole process could be reduced from several days to a matter of hours.

While there are limitations to how practical and cost effective this particular approach would be, the team says it demonstrates in principle how powerful artificial intelligence could be in helping the fight against antimicrobial resistance.

Dr Sushmita Sridhar, who initiated this project while a PhD student in the Department of Medicine at the ̽��ֱ�� of Cambridge and is now a postdoc at the ̽��ֱ�� of New Mexico and Harvard School of Public Health, said: “Given that this approach uses single cell resolution imaging, it isn’t yet a solution that could be readily deployed everywhere. But it shows real promise that by capturing just a few parameters about the shape and structure of the bacteria, it can give us enough information to predict drug resistance with relative ease.”

̽��ֱ��team now aims to work on larger collections of bacteria to create a more robust experimental set that could speed up the identification process even more and allow them to identify resistance to ciprofloxacin and other antibiotics in a number of different species of bacteria.

Sridhar added: “What would be really important, particularly for a clinical context, would be to be able to take a complex sample – for example blood or urine or sputum – and identify susceptibility and resistance directly from that. That's a much more complicated problem and one that really hasn't been solved at all, even in clinical diagnostics in a hospital. If we could find a way of doing this, we could reduce the time taken to identify drug resistance and at a much lower cost. That could be truly transformative.”

̽��ֱ��research was funded by Wellcome.

Reference
Tran, TA & Sridhar, S et al. Combining machine learning with high-content imaging to infer ciprofloxacin susceptibility in isolates of Salmonella Typhimurium. Nat Comms; 13 June 2024; DOI: 10.1038/s41467-024-49433-4

Artificial intelligence (AI) could be used to identify drug resistant infections, significantly reducing the time taken for a correct diagnosis, Cambridge researchers have shown. ̽��ֱ��team showed that an algorithm could be trained to identify drug-resistant bacteria correctly from microscopy images alone.

̽��ֱ��beauty of the machine learning model is that it can identify resistant bacteria based on a few subtle features on microscopy images that human eyes cannot detect

Tuan-Anh Tran

Rocky Mountain Laboratories, NIAID, NIH

Colour-enhanced scanning electron micrograph showing Salmonella Typhimurium (red) invading cultured human cells

Yes

Licence type:

Public Domain

Scientists map how deadly bacteria evolved to become epidemic

cjb250 — Thu, 04 Jul 2024 18:00:53 +0000

P. aeruginosa is responsible for over 500,000 deaths per year around the world, of which over 300,000 are associated with antimicrobial resistance (AMR). People with conditions such as COPD (smoking-related lung damage), cystic fibrosis (CF), and non-CF bronchiectasis, are particularly susceptible.

How P. aeruginosa evolved from an environmental organism into a specialised human pathogen was not previously known. To investigate this, an international team led by scientists at the ̽��ֱ�� of Cambridge examined DNA data from almost 10,000 samples taken from infected individuals, animals, and environments around the world. Their results are published today in Science

By mapping the data, the team was able to create phylogenetic trees – ‘family trees’ – that show how the bacteria from the samples are related to each other. Remarkably, they found that almost seven in ten infections are caused by just 21 genetic clones, or ‘branches’ of the family tree, that have rapidly evolved (by acquiring new genes from neighbouring bacteria) and then spread globally over the last 200 years. This spread occurred most likely as a result of people beginning to live in densely-populated areas, where air pollution made our lungs more susceptible to infection and where there were more opportunities for infections to spread.

These epidemic clones have an intrinsic preference for infecting particular types of patients, with some favouring CF patients and other non-CF individuals. It turns out that the bacteria can exploit a previously unknown immune defect in people with CF, allowing them to survive within macrophages. Macrophages are cells that ‘eat’ invading organisms, breaking them down and preventing the infection from spreading. But a previously-unknown flaw in the immune systems of CF patients means that once the macrophage ‘swallows’ P. aeruginosa, it is unable to get rid of it.

Having infected the lungs, these bacteria then evolve in different ways to become even more specialised for a particular lung environment. ̽��ֱ��result is that certain clones can be transmitted within CF patients and other clones within non-CF patients, but almost never between CF and non-CF patient groups.

Professor Andres Floto, Director of the UK Cystic Fibrosis Innovation Hub at the ̽��ֱ�� of Cambridge and Royal Papworth Hospital NHS Foundation Trust, and senior author of the study said: “Our research on Pseudomonas has taught us new things about the biology of cystic fibrosis and revealed important ways we might be able to improve immunity against invading bacteria in this and potentially other conditions.

“From a clinical perspective, this study has revealed important information about Pseudomonas. ̽��ֱ��focus has always been on how easily this infection can spread between CF patients, but we’ve shown that it can spread with worrying ease between other patients, too. This has very important consequences for infection control in hospitals, where it’s not uncommon for an infected individual to be on an open ward with someone potentially very vulnerable.

“We are incredibly lucky at Royal Papworth Hospital where we have single rooms and have developed and evaluated a new air-handling system to reduce the amount of airborne bacteria and protect all patients.”

Dr Aaron Weimann from the Victor Phillip Dahdaleh Heart & Lung Research Institute at the ̽��ֱ�� of Cambridge, and first author on the study, said: “It’s remarkable to see the speed with which these bacteria evolve and can become epidemic and how they can specialise for a particular lung environment. We really need systematic, pro-active screening of all at risk patient groups to detect and hopefully prevent the emergence of more epidemic clones.”

̽��ֱ��research was funded by Wellcome and the UK Cystic Fibrosis Trust.

Reference
Weimann, A et al. Evolution and host-specific adaptation of Pseudomonas aeruginosa. Science; 4 July 2024; DOI: 10.1126/science.adi0908

Pseudomonas aeruginosa – an environmental bacteria that can cause devastating multidrug-resistant infections, particularly in people with underlying lung conditions – evolved rapidly and then spread globally over the last 200 years, probably driven by changes in human behaviour, a new study has found.

It’s remarkable to see the speed with which these bacteria evolve and can become epidemic and how they can specialise for a particular lung environment

Aaron Weimann

engin akyurt

A man with a respirator on his face

Yes

Licence type:

Public Domain

New vaccine effective against coronaviruses that haven’t even emerged yet

jg533 — Mon, 06 May 2024 09:00:25 +0000

This is a new approach to vaccine development called ‘proactive vaccinology’, where scientists build a vaccine before the disease-causing pathogen even emerges.

̽��ֱ��new vaccine works by training the body’s immune system to recognise specific regions of eight different coronaviruses, including SARS-CoV-1, SARS-CoV-2, and several that are currently circulating in bats and have potential to jump to humans and cause a pandemic.

Key to its effectiveness is that the specific virus regions the vaccine targets also appear in many related coronaviruses. By training the immune system to attack these regions, it gives protection against other coronaviruses not represented in the vaccine – including ones that haven’t even been identified yet.

For example, the new vaccine does not include the SARS-CoV-1 coronavirus, which caused the 2003 SARS outbreak, yet it still induces an immune response to that virus.

“Our focus is to create a vaccine that will protect us against the next coronavirus pandemic, and have it ready before the pandemic has even started,” said Rory Hills, a graduate researcher in the ̽��ֱ�� of Cambridge’s Department of Pharmacology and first author of the report.

He added: “We’ve created a vaccine that provides protection against a broad range of different coronaviruses – including ones we don’t even know about yet.”

̽��ֱ��results are published today in the journal Nature Nanotechnology.

“We don’t have to wait for new coronaviruses to emerge. We know enough about coronaviruses, and different immune responses to them, that we can get going with building protective vaccines against unknown coronaviruses now,” said Professor Mark Howarth in the ̽��ֱ�� of Cambridge’s Department of Pharmacology, senior author of the report.

He added: “Scientists did a great job in quickly producing an extremely effective COVID vaccine during the last pandemic, but the world still had a massive crisis with a huge number of deaths. We need to work out how we can do even better than that in the future, and a powerful component of that is starting to build the vaccines in advance.”

̽��ֱ��new ‘Quartet Nanocage’ vaccine is based on a structure called a nanoparticle – a ball of proteins held together by incredibly strong interactions. Chains of different viral antigens are attached to this nanoparticle using a novel ‘protein superglue’. Multiple antigens are included in these chains, which trains the immune system to target specific regions shared across a broad range of coronaviruses.

This study demonstrated that the new vaccine raises a broad immune response, even in mice that were pre-immunised with SARS-CoV-2.

̽��ֱ��new vaccine is much simpler in design than other broadly protective vaccines currently in development, which the researchers say should accelerate its route into clinical trials.

̽��ֱ��underlying technology they have developed also has potential for use in vaccine development to protect against many other health challenges.

̽��ֱ��work involved a collaboration between scientists at the ̽��ֱ�� of Cambridge, the ̽��ֱ�� of Oxford, and Caltech. It improves on previous work, by the Oxford and Caltech groups, to develop a novel all-in-one vaccine against coronavirus threats. ̽��ֱ��vaccine developed by Oxford and Caltech should enter Phase 1 clinical trials in early 2025, but its complex nature makes it challenging to manufacture which could limit large-scale production.

Conventional vaccines include a single antigen to train the immune system to target a single specific virus. This may not protect against a diverse range of existing coronaviruses, or against pathogens that are newly emerging.

̽��ֱ��research was funded by the Biotechnology and Biological Sciences Research Council.

Reference: Hills, R A et al: ‘Proactive vaccination using multiviral Quartet Nanocages to elicit broad anti-coronavirus responses.’ Nature Nanotechnology, May 2024. DOI: 10.1038/s41565-024-01655-9

Researchers have developed a new vaccine technology that has been shown in mice to provide protection against a broad range of coronaviruses with potential for future disease outbreaks - including ones we don’t even know about

Our focus is to create a vaccine that will protect us against the next coronavirus pandemic, and have it ready before the pandemic has even started.

Rory Hills

Stefan Cristian Cioata on Getty

Syringe and vaccine bottle

Yes

Licence type:

Attribution-Noncommerical

TB vaccine may enable elimination of the disease in cattle by reducing its spread

jg533 — Thu, 28 Mar 2024 18:00:16 +0000

̽��ֱ��research, led by the ̽��ֱ�� of Cambridge and Penn State ̽��ֱ��, improves prospects for the elimination and control of bovine tuberculosis (TB), an infectious disease of cattle that results in large economic costs and health impacts across the world.

This is the first study to show that BCG-vaccinated cattle infected with TB are substantially less infectious to other cattle. This remarkable indirect effect of the vaccine beyond its direct protective effect has not been measured before.

̽��ֱ��spillover of infection from livestock has been estimated to account for about 10% of human tuberculosis cases. While such zoonotic TB (zTB) infections are most commonly associated with gastro-intestinal infections related to drinking contaminated milk, zTB can also cause chronic lung infections in humans. Lung disease caused by zTB can be indistinguishable from regular tuberculosis, but is more difficult to treat due to natural antibiotic resistance in the cattle bacteria.

TB remains endemic in many countries around the world, including in Europe and the Americas, where its control costs farmers and taxpayers hundreds of millions of dollars each year.

̽��ֱ��study is published today in the journal Science.

In the study, carried out in Ethiopia, researchers examined the ability of the vaccine, Bacillus Calmette-Guérin (BCG), to directly protect cattle that receive it, as well as to indirectly protect both vaccinated and unvaccinated cattle by reducing TB transmission. Vaccinated and unvaccinated animals were put into enclosures with naturally infected animals, in a novel crossover design performed over two years.

“Our study found that BCG vaccination reduces TB transmission in cattle by almost 90%. Vaccinated cows also developed significantly fewer visible signs of TB than unvaccinated ones. This suggests that the vaccination not only reduces the progression of the disease, but that if vaccinated animals become infected, they are substantially less infectious to others,” said Andrew Conlan, Associate Professor of Epidemiology at the ̽��ֱ�� of Cambridge’s Department of Veterinary Medicine and a corresponding author of the study.

Using livestock census and movement data from Ethiopia, the team developed a transmission model to explore the potential for routine vaccination to control bovine tuberculosis.

“Results of the model suggest that vaccinating calves within the dairy sector of Ethiopia could reduce the reproduction number of the bacterium — the R0 — to below 1, arresting the projected increase in the burden of disease and putting herds on a pathway towards elimination of TB,” Conlan said.

̽��ֱ��team focused their studies in Ethiopia, a country with the largest cattle herd in Africa and a rapidly growing dairy sector that has a growing burden of bovine tuberculosis and no current control program, as a representative of similarly situated transitional economies.

“Bovine tuberculosis is largely uncontrolled in low- and middle-income countries, including Ethiopia,” said Abebe Fromsa, associate professor of agriculture and veterinary medicine at Addis Ababa ̽��ֱ�� in Ethiopia and the study’s co-lead author. “Vaccination of cattle has the potential to provide significant benefits in these regions.”

“For over a hundred years, programs to eliminate bovine tuberculosis have relied on intensive testing and slaughtering of infected animals,” said Vivek Kapur, professor of microbiology and infectious diseases and Huck Distinguished Chair in Global Health at Penn State and a corresponding author of the study.

He added: “This approach is unimplementable in many parts of the world for economic and social reasons, resulting in considerable animal suffering and economic losses from lost productivity, alongside an increased risk of spillover of infection to humans. By vaccinating cattle, we hope to be able to protect both cattle and humans from the consequences of this devastating disease.”

Professor James Wood, Alborada Professor of Equine and Farm Animal Science in the ̽��ֱ�� of Cambridge’s Department of Veterinary Medicine, noted that despite TB being more prevalent in lower-income countries, the United Kingdom, Ireland and New Zealand also experience considerable economic pressures from the disease which continues to persist despite intensive and costly control programs.

Wood said: “For over twenty-years the UK government has pinned hopes on cattle vaccination for bovine tuberculosis as a solution to reduce the disease and the consequent costs of the controls. These results provide important support for the epidemiological benefit that cattle vaccination could have to reduce rates of transmission to and within herds.”

This research was supported by ̽��ֱ��Bill & Melinda Gates Foundation, as well as the Biotechnology and Biological Sciences Research Council; Foreign, Commonwealth and Development Office; Economic & Social Research Council; Medical Research Council; Natural Environment Research Council; and Defence Science & Technology.

Reference: Fromsa, A. et al: ‘BCG vaccination of cattle reduces transmission of bovine tuberculosis, improving the prospects for elimination.’ Science, March 2024. DOI: 10.1126/science.adl3962

Vaccination not only reduces the severity of TB in infected cattle, but reduces its spread in dairy herds by 89%, research finds.

Our study suggests that vaccination not only reduces the progression of the disease, but that if vaccinated animals become infected, they are substantially less infectious to others.

Andrew Conlan

Getty/ kamisoka

Herd of cows in a grassy field

Yes

Licence type:

Attribution-Noncommerical

Vulnerability to different COVID-19 mutations depends on previous infections and vaccination, study suggests

jg533 — Fri, 06 Oct 2023 08:00:00 +0000

A new study has found that people differ in how vulnerable they are to different mutations in emerging variants of SARS-CoV-2.

This is because the variant of SARS-CoV-2 a person was first exposed to determines how well their immune system responds to different parts of the virus, and how protected they are against other variants.

It also means that the same COVID-19 vaccine might work differently for different people, depending on which variants of SARS-CoV-2 they have previously been exposed to and where their immune response has focused.

̽��ֱ��discovery underlies the importance of continuing surveillance programmes to detect the emergence of new variants, and to understand differences in immunity to SARS-CoV-2 across the population.

It will also be important for future vaccination strategies, which must consider both the virus variant a vaccine contains and how immune responses of the population may differ in their response to it.

“It was a surprise how much of a difference we saw in the focus of immune responses of different people to SARS-CoV-2. Their immune responses appear to target different specific regions of the virus, depending on which variant their body had encountered first,” said Dr Samuel Wilks at the ̽��ֱ�� of Cambridge’s Centre for Pathogen Evolution in the Department of Zoology, first author of the report.

He added: “Our results mean that if the virus mutates in a specific region, some people’s immune system will not recognize the virus as well - so it could make them ill, while others may still have good protection against it.”

̽��ֱ��research, published today in the journal Science, involved a large-scale collaboration across ten research institutes including the ̽��ֱ�� of Cambridge and produced a comprehensive snapshot of early global population immunity to COVID-19.

Researchers collected 207 serum samples - extracted from blood samples - from people who had either been infected naturally with one of the many previously circulating SARS-CoV-2 variants, or who had been vaccinated against SARS-CoV-2 with different numbers of doses of the Moderna vaccine.

They then analysed the immunity these people had developed, and found significant differences between immune responses depending on which variant a person had been infected with first.

“These results give us a deep understanding of how we might optimise the design of COVID-19 booster vaccines in the future,” said Professor Derek Smith, Director of the ̽��ֱ�� of Cambridge’s Centre for Pathogen Evolution in the Department of Zoology, senior author of the report.

He added: “We want to know the key virus variants to use in vaccines to best protect people in the future.”

̽��ֱ��research used a technique called ‘antigenic cartography’ to compare the similarity of different variants of the SARS-CoV-2 virus. This measures how well human antibodies, formed in response to infection with one virus, respond to infection with a variant of that virus. It shows whether the virus has changed enough to escape the human immune response and cause disease.

̽��ֱ��resulting ‘antigenic map’ shows the relationship between a wide selection of SARS-CoV-2 variants that have previously circulated. Omicron variants are noticeably different from the others – which helps to explain why many people still succumbed to infection with Omicron despite vaccination or previous infection with a different variant.

Immunity to COVID-19 can be acquired by having been infected with SARS-CoV-2 or by vaccination. Vaccines provide immunity without the risk from the disease or its complications. They work by activating the immune system so it will recognise and respond rapidly to exposure to SARS-CoV-2 and prevent it causing illness. But, like other viruses, the SARS-CoV-2 virus keeps mutating to try and escape human immunity.

During the first year of the pandemic, the main SARS-CoV-2 virus in circulation was the B.1 variant. Since then, multiple variants emerged that escaped pre-existing immunity, causing reinfections in people who had already had COVID.

“ ̽��ֱ��study was an opportunity to really see - from the first exposure to SARS-CoV-2 onwards - what the basis of people’s immunity is, and how this differs across the population,” said Wilks.

This research was funded by the National Institute of Allergy and Infectious Diseases and National Institutes of Health.

Reference

Wilks, S H et al: ‘Mapping SARS-CoV-2 antigenic relationships and serological responses.’ Science, October 2023. DOI: 10.1126/science.adj0070

10 October 2023: New projects to kickstart future vaccine development awarded UKRI funding

̽��ֱ�� ̽��ֱ�� has been awarded £3.46 million by the UKRI as part of a consortium project, PROVAC: Evolutionarily smart vaccine strain selection for proactive vaccinology.

This project aims to enhance the SARS-CoV-2 vaccine strain selection process to provide the best possible protection for the UK population. It will predict which variants may emerge in the future and measure immune responses against this potential future evolution. This will enable researchers to choose the variant of the virus to use in the next vaccine.

Continual monitoring and updating of the variant is necessary to protect those at high-risk of complications from COVID-19, who will require further vaccinations against the evolving virus.

Professor Derek Smith at the ̽��ֱ�� of Cambridge’s Centre for Pathogen Evolution/ Department of Zoology will lead the consortium, which also involves researchers at Imperial College London, Francis Crick Institute, ̽��ֱ�� College London Hospitals, and the ̽��ֱ�� of Glasgow. ̽��ֱ��consortium is the direct result of the researchers’ substantial involvement in multiple aspects of the UK COVID-19 response.

̽��ֱ��award is made as part of UKRI’s five-year strategy Transforming Tomorrow Together 2022 to 2027 to harness the full power of the UK’s research and innovation system to tackle large-scale, complex challenges. In total £25m has been awarded to new projects to tackle epidemics and disease mutation.

Read UKRI's full award announcement here.

This page was originally published on 6 October 2023 and last updated: 10 October 2023.

A person’s immune response to variants of SARS-CoV-2, the virus that causes COVID-19, depends on their previous exposure – and differences in the focus of immune responses will help scientists understand how to optimise vaccines in the future to provide broad protection.

It was a surprise how much of a difference we saw in the focus of immune responses of different people to SARS-CoV-2.

Sam Wilks

Alexandra Koch on Pixabay

Virus variants

̽��ֱ��text in this work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. Images, including our videos, are Copyright © ̽��ֱ�� of Cambridge and licensors/contributors as identified. All rights reserved. We make our image and video content available in a number of ways – as here, on our main website under its Terms and conditions, and on a range of channels including social media that permit your use and sharing of our content under their respective Terms.

Yes

Licence type:

Attribution-Noncommerical

̽��ֱ�� of Cambridge - Cambridge Infectious Diseases

Cambridge initiative to address risks of future engineered pandemics

Social determinants of engineered pandemic threat

Biological determinants of engineered pandemic threat

Modelling threats and risk management of engineered pandemics

Policy innovation challenges

Feeding your good gut bacteria through fibre in diet may boost body against infections

A new understanding of gut microbe interactions

More about this topic

System to auto-detect new variants will inform better response to future infectious disease outbreaks

Testing the technique

A constant threat

AI able to identify drug-resistant typhoid-like infection from microscopy images in matter of hours

Scientists map how deadly bacteria evolved to become epidemic

New vaccine effective against coronaviruses that haven’t even emerged yet

TB vaccine may enable elimination of the disease in cattle by reducing its spread

Vulnerability to different COVID-19 mutations depends on previous infections and vaccination, study suggests

Reference

10 October 2023: New projects to kickstart future vaccine development awarded UKRI funding

̽��ֱ�� ̽��ֱ�� has been awarded £3.46 million by the UKRI as part of a consortium project, PROVAC: Evolutionarily smart vaccine strain selection for proactive vaccinology.