Pathogens

Microbiome diversity protects against pathogens by nutrient blocking.

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Editor’s summary

The microbiota plays an important part in host defense by excluding pathogenic species in a process called colonization resistance. This property is elusive and not endowed by one or two species alone. Spragge et al. discovered that colonization resistance is a higher-order effect of a diverse community of bacteria underpinned by essential key species such as Escherichia coli (see the Perspective by Radlinski and Bäumler). In vitro and in vivo experiments showed that given the right composition, a diverse microbiota will collectively consume the nutrients that an incoming species requires to grow and establish in a host. Colonization resistance is predictable because if the symbiont community encodes many of the same (or similar) proteins as the pathogen, then it provides better colonization resistance and can potentially deliver health benefits to the host. —Caroline Ash

Structured Abstract

INTRODUCTION

The diverse bacterial species that colonize the human gut, which are collectively known as the gut microbiota, provide important health benefits. One of the key benefits is colonization resistance—the ability to restrict colonization of the gut by pathogens that can trigger disease. Multiple mechanisms have been found to influence the ability of the microbiota to provide colonization resistance, but these mechanisms are often context-specific and dependent on particular strains or species of bacteria. As a result, we lack general principles to predict which microbiota communities will be protective versus those that will allow pathogens to colonize.

RATIONALE

We used an ecological approach to study the colonization resistance provided by human gut symbionts against two important bacterial pathogens, Klebsiella pneumoniae and Salmonella enterica serovar Typhimurium. We studied colonization resistance provided by symbionts both alone and in combinations of increasing diversity to identify general patterns underlying colonization resistance, using both in vitro assays and in vivo work with gnotobiotic mice.

RESULTS

We cultured 100 human gut symbionts individually with K. pneumoniae and then S. Typhimurium and ranked the symbionts on the basis of their ability to provide colonization resistance. However, even the best-performing species provided limited protection against the pathogens in our assays. By contrast, when we combined species into diverse communities of up to 50 species, we found cases in which pathogen growth was greatly limited. The same patterns were observed when germ-free mice were colonized by a subset of these communities and challenged with a pathogen. Ecological diversity, therefore, was important for colonization resistance, but we also found that community composition was important. Both in vitro and in vivo, we found that colonization resistance rested upon certain species being present, even though these species offer little protection on their own. We were able to explain these patterns from the ability of some communities to block pathogen growth by consuming the nutrients that the pathogen needs. Nutrient blocking is thus promoted both by diversity and by the presence of certain key species that increase the overlap between the nutrient use of a community and a pathogen. As a result, the inclusion of a key species closely related to a pathogen can be central to making a community protective because it provides a higher degree of metabolic overlap. However, this alone is typically not sufficient. We found that the presence of additional, often distantly related species is also needed to ensure that nutrient blocking—and consequently, colonization resistance—occurs. Lastly, we used the nutrient-blocking principle to predict in silico more-protective and less-protective communities for a new target strain, an antimicrobial resistant Escherichia coli clinical isolate. We then tested the colonization resistance of these communities experimentally. This work revealed that we can successfully identify protective communities from a large number of possible combinations, using both phenotypic measures of metabolic overlap but also a more general measure of genomic overlap.

CONCLUSION

Our results support the idea that more-diverse microbiomes can provide health benefits, specifically that they can improve protection against pathogen colonization. We also find that colonization resistance is a collective property of microbiome communities; in other words, a single strain is protective only when in combination with others. Crucially, although increased microbiome diversity increases the probability of protection against pathogens, the overlap in nutrient-utilization profiles between the community and the pathogen is key. Our work suggests a route to optimize the composition of microbiomes for protection against pathogens.

Microbiome diversity protects against pathogens by nutrient blocking.Pathogens (red) fail to colonize when they overlap with the community (yellow and green bacteria) in nutrient-utilization profiles (nutrient niches are indicated by colored circles). As microbiome diversity increases, the probability that different nutrients are consumed increases, which helps to block pathogen growth and improve colonization resistance.

Abstract

The human gut microbiome plays an important role in resisting colonization of the host by pathogens, but we lack the ability to predict which communities will be protective. We studied how human gut bacteria influence colonization of two major bacterial pathogens, both in vitro and in gnotobiotic mice. Whereas single species alone had negligible effects, colonization resistance greatly increased with community diversity. Moreover, this community-level resistance rested critically upon certain species being present. We explained these ecological patterns through the collective ability of resistant communities to consume nutrients that overlap with those used by the pathogen. Furthermore, we applied our findings to successfully predict communities that resist a novel target strain. Our work provides a reason why microbiome diversity is beneficial and suggests a route for the rational design of pathogen-resistant communities.

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Destroy pathogens in health labs to prevent disease spread, WHO tells Ukraine

Ukraine’s laboratory capabilities have been at the forefront of a growing information war following the Russian invasion two weeks ago. (Reuters)

The World Health Organization (WHO) has advised Ukraine to destroy all high-threat pathogens housed in public health laboratories to prevent potential spills that could spread disease. Biosecurity experts have warned that Russia’s troop movement in Ukraine and the bombardment of its cities raised the risk of disease-causing pathogens escaping should any facilities be damaged, Reuters reported.

Ukraine has public health laboratories, like several other countries, researching ways to mitigate the threats posed by dangerous diseases that affect both humans and animals, including Covid-19. Its labs receive support from the US, the WHO, and the European Union.

In response to questions about its work with Ukraine prior to and during the invasion, the WHO said that it had collaborated with the country’s public health labs for years to promote security practices that prevent the deliberate or accidental release of pathogens.

As part of this work, the United Nations health agency has recommended to Ukraine’s Ministry of Health and other responsible bodies to get rid of high-threat pathogens.

While the WHO did not reveal when it made the recommendation or provide specifics about the kinds of pathogens housed in the laboratories, it also did not reveal if the recommendations were being followed.

Ukraine’s laboratory capabilities have been at the forefront of a growing information war following the Russian invasion two weeks ago. Russia Foreign Ministry Spokesperson on Wednesday Maria Zakharova reiterated a longstanding claim that the US operated a biowarfare lab in the former Soviet state. Both the US and Ukraine have previously denied the accusations.

Zakharova said documents found by Russian forces in Ukraine showed an emergency attempt to erase evidence of military-grade biological programmes by destroying laboratory samples.

A spokesperson for the Ukraine president, however, denied the allegations. Spokespeople from the US government also denied the accusations and said Russia might use these claims to deploy chemical or biological weapons.

While the WHO made no reference to biowarfare, it said it encouraged all parties to cooperate in the secure disposal of pathogens they find and reach out for technical assistance when needed.

On Friday, the United Nations Security Council will convene a meeting at Russia’s request to discuss the Kremlin’s claims about US biological activities in the war-torn country.

Your Rubber Ducky Is a Disgusting Biohazard, Loaded With Potential Pathogens

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The nightmare is real.

It’s one of the happiest-looking, most unassuming objects in your home. It exists only to float and create smiles. But behind the buoyant facade lies a dirty, dangerous secret.

main article image

New research reveals rubber ducks have a dark side that’s both figurative and literal, with scientists discovering these seemingly wholesome toys act as incubators for potentially pathogenic bacterial and fungal growths – which cling to the duck’s inner cavities in a mucky biofilm of filth.

Surprised? We probably shouldn’t be.

After all, we know we’re continually surrounded by bacteria traps in our daily lives, and items we associate with cleaning are actually the most unclean of all.

338 rubber duck bacteria trap 3(Eawag)

But it’s particularly unsettling to find out the rubber ducky is of these questionable objects, because it occupies a special place in our homes.

Unlike the rudimentary kitchen sponge – devoid of character or presence – rubber ducks are something we associate with happiness, laughter, innocence.

Children play with them, squeeze water out of them, even put them in their mouths.

In the new study, scientists led by the Swiss Federal Institute of Aquatic Science and Technology collected 19 real bath toys from Swiss households, and mimicked real-world conditions for six separate new toys, exposing them to clean and dirty bath water, mixed in with things like soap, human body fluids, and bacteria.

This cohort – rubber (actually plastic) ducks, crocodiles, and other bathtime toys – may have started out squeaky clean, but they didn’t stay that way for long.

338 rubber duck bacteria trap 3(Eawag)

After 11 weeks of simulated household use, all the toys were bisected in the lab, revealing between 5–75 million cells per square centimetre in the biofilm lining their inner surfaces.

Fungal species were detected in almost 60 percent of the real bath toys and in all the new toys exposed to dirty water, and potentially pathogenic bacteria were found in 80 percent of all the toys.

The results might sound disgusting, but in actuality, exposure to these microbial communities is kind of a mixed bag, the researchers say.

“This could strengthen the immune system, which would be positive,” explains microbiologist Frederik Hammes, “but it can also result in eye, ear, or even gastrointestinal infections.”

338 rubber duck bacteria trap 3(Eawag)

Ultimately, the team says more research needs to be done to figure out how potentially dangerous these bacterial and fungal biofilms could be – especially to children – and advise the potentials may be mitigated by cleaning toys after bathtime, by boiling and drying them, to minimise their capacity for incubation.

Or, you could look for bath toys that don’t have a squeaky hole that sucks in water, although, as the team highlights, this has its own drawbacks.

“The easiest way to prevent children from being exposed to bath toy biofilms is to simply close the hole,” they conclude, “but where is the fun in that?”

Turning Urine Into Electricity Can Also Kill Pathogens in Wastewater

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Fuel cells with microorganisms that feed on pee and generate electricity already sound like a pretty clever trick. It’s one of the emerging biotechnology solutions in a world that’s moving away from fossil fuels.

But now scientists have taken it a significant step further, showing that not only can you power mobile phones and light globes with urine, but you can also kill pathogens in the wastewater as you do so. This development makes the technology even more attractive for use in the developing world.

 

A research team from the University of the West of England (UWE)  in the UK has already demonstrated that it’s possible to rig a urinal with cheap pee-powered fuel cells to generate enough electricity for the cubicle lighting.

The trial, created in partnership with Oxfam in 2015, showed the potential of this technology for places like disaster zones and refugee camps, where power supply is often lacking and lack of outdoor lighting at night makes people more vulnerable to potential assault.

But if this biotech can also kill pathogens in wastewater, that opens up a host of other potential uses, including routine installation in off-grid areas of the world where municipal resources for cleaning waste are in short supply.

urine tricityThe urinal project from 2015 / Credit: UWE Bristol News

The technology runs on microbial fuel cells (MFC) in which microbes feed on organic material such as urine, fuelling their growth and generating a small amount of energy in the process.

“The MFC is in effect a system which taps a portion of that biochemical energy used for microbial growth, and converts that directly into electricity – what we are calling urine-tricity or pee power,” lead researcher Ioannis Ieropoulos explained back in 2015.

Studies have shown that MFCs seem to have some disinfecting properties, likely due to the generation of hydrogen peroxide during the energy generation process. This disinfection happens at a later stage in the fuel cell system, so it doesn’t kill the microbes powering the MFC.

This disinfection potential gave the UWE team an idea to systematically test how MFCs could be used to purify wastewater. For this, they picked one of the most important gastrointestinal pathogens, a strain of the Salmonella bacterium which causes typical food poisoning symptoms.

“This species was introduced into an MFC cascade system treating human urine, to determine the anodic killing efficacy when operating in continuous flow conditions,” the researchers write in the study.

When they checked the outflow at the end of the purification process to measure the remaining pathogen levels, they found just what they had hoped for – greatly reduced Salmonella counts.

“We were really excited with the results – it shows we have a stable biological system in which we can treat waste, generate electricity and stop harmful organisms making it through to the sewerage network,” says Ieropoulos.

In fact, the batteries destroyed these pathogens so effectively, they brought their levels down to what’s considered acceptable in conventional sanitation practices.

“We have reduced the number of pathogenic organisms significantly but we haven’t shown we can bring them down to zero – we will continue the work to test if we can completely eliminate them,” says one of the team, microbiologist John Greenman.

To raise awareness of this project, which is founded by the Bill & Melinda Gates Foundation, the team has also incorporated their tech into a portable toilet that will get some limelight at this year’s Glastonbury music festival in the UK.

Energy generated by the ‘Pee Power’ toilet will be used to power information displays at the festival. The plan is to process over 1,000 litres (264 gallons) of pee a day, using the electricity for a set of ten info panels.

“The festival updates are one way of showing that Pee Power and the MFC technology can be developed for a whole range of uses,” says Ieropoulos.

Source:PLOS ONE.

New Mathematics Could Neutralize Pathogens That Resist Antibiotics .

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Bacteria that make us sick are bad enough, but many of them also continually evolve in ways that help them develop resistance to common antibiotic drugs, making our medications less effective or even moot. Doctors try to reduce the evolution by cycling through various drugs over time, hoping that as resistance develops to one, the increased use of a new drug or the widespread reuse of an old drug will catch some of the bugs off guard.

Blue glowing picture of E. coli

The plans for cycling drugs are not that scientific, however, and don’t always work efficiently, allowing bacteria to continue to develop resistance. Now a new algorithm that deciphers how bacteria genes create resistance in the first place could greatly improve such a plan. The “time machine” software, developed by biologists and mathematicians, could help reverse resistant mutations and render the bacteria vulnerable to drugs again.

Miriam Barlow, a biologist from the University of California, Merced, first hit on the idea while trying to predict how antibiotic resistance would evolve several years ago. But she lacked the experimental data or the mathematics to quantify it. “We were pushing evolution forward, trying to predict how antibiotic resistance would evolve, and we saw a lot of trade-offs,” Barlow says. Introducing an antibiotic might lead to bacteria developing resistance but it might also lead to them losing resistance to some other medication. So Barlow partnered with mathematicians, including Kristina Crona from American University in Washington, D.C., and tried to figure out a series of steps to make those losses of resistance as likely as possible. Their work was published in PLoS ONE May 6.

Network of mutations with arrows leading from one to the other, labeled by drug that causes the transition

The researchers took as a starting point TEM-1, a protein stemming from an extremely common gene that confers resistance to penicillin. They considered four possible independent mutations that can occur in the gene, all of which confer resistance to new antibiotics, and they selected a range of 15 commonly used and studied antibiotics. They then measured the growth rates of Escherichia coli bacteria, as each mutation was exposed to each of the antibiotics, which let them work out the probability that the overall population of E. coli would gain or lose a mutation to adapt.

In this way the researchers could directly model possible changes to drug-resistant genes. “At every single place in the genome we can say either the mutation happened here or it did not,” Crona says. The researchers were able to sketch a network of different mutation combinations and figure out the probabilities of moving from one to the other, given certain antibiotics. They called the software for finding the path back to TEM-1, created by their collaborator, mathematician Bernd Sturmfels of the University of California, Berkeley, the “Time Machine.” Although in the real world a bacterium would not revert to its exact, prior genetic form once it had evolved, this mathematical goal revealed the best genetic targets for slowing resistance.

Network of mutations with arrows leading from one to the other, labeled by drug that causes the transition

In models of genes, researchers charted which antibiotics would encourage which of four genetic mutations in E.coli bacteria and the likelihood of each. Each mutation is represented by a “1,” so each combination is a four-digit number. Using a particular sequence of antibiotics can lead back to the wild type, 0000. Credit: Kristina Crona

The researchers were surprised to find that most mutations didn’t need a long chain of antibiotics to revert to TEM-1. They also found they could revert most mutations with about a 60 percent probability, which is more efficient than current antibiotic cycling schemes. And they found that they could reach a high level of reliability with just a few antibiotics in the cycle.

Direct network modeling like this is becoming more common in biology as researchers learn how to distill problems into the correct mathematical formats. But mathematicians are still learning the best ways to navigate and optimize networks of connections that can grow in complexity. And as with any model system, real-world work must be done. “It’s an interesting mathematical analysis based on laboratory-measured growth rates across multiple antimicrobial drugs, which is all novel,” says Joshua Plotkin, who investigates mathematical biology at the University of Pennsylvania and was not involved with this project. But he adds that researchers still need to pinpoint how long the cycles should last and the necessary dosages as well as looking into how the system adapts to more antibiotics and more complex mutations. The bacterial populations’ interactions in a clinic filled with people will be far more complex than one mutation per test tube.

To that end, Barlow’s group is currently setting up an experiment that will simulate the cross-pollination of different bacterial populations, which happens in places such as hospitals where multiple patients are exposed to one another. The same mathematical process they used can also incorporate new mutations and antibiotics found in hospitals—mutations that can apply to many different bacteria, not just E. coli. “We need more mathematicians working on this,” says Jonathan Iredell, an infectious disease physician from University of Sydney in Australia. “It indicates a way forward as we are desperate to find some positive remedies to what is basically an evolutionary and ecological problem.”

Robert Beardmore, a mathematical bioscientist at University of Exeter who, along with Iredell, did not take part in the study, describes this work as trying to find the signal in the noise of bacterial resistance development. Future lab work will reveal whether the interactions the team found are strong enough to define what happens in more complex scenarios. “At the heart of what everybody wants to know is how predictable is evolution—and if it’s predictable, can we reverse it?” he says. “It’s really hard, but you’ve got to try something.”

“We’re talking about managing evolution, trying to steer evolution,” Crona adds. “And that’s very new.”