Every day, the billions of bacteria that inhabit your digestive system change; the food you eat, the medications you take, and the germs you are exposed to make some bacteria thrive more than others. Scientists know this ever-changing balance of gut microbes is linked to your health and disease, but they’ve had a hard time figuring out what makes one microbial balance better than another.
Over the past decade, scientists have generally described a person’s microbiome – the collection of microbes found in the human gut – by characterizing which species of bacteria are present and in what amounts. Today, a group of researchers led by Katie Pollard, PhD, at the Gladstone Institutes, published two new studies that suggest monitoring strains of bacteria – not just species – may provide better information about the microbiome.
Bacterial strains are much like dog breeds or tomato varieties, being part of the same species, but distinct from each other.
“I think researchers missed a lot of information by focusing only on species of microbes,” says Pollard, director of the Gladstone Institute of Data Science and Biotechnology and lead author of both studies. “When we take a more sophisticated approach and look at the strains of bacteria, I predict that we will start to find causal links between the microbiome and disease. “
In a study published in the journal Natural biotechnology, Pollard’s lab worked with Stephen Nayfach, PhD, a researcher at the US Department of Energy Joint Genome Institute, to develop a new computational method to analyze bacterial strains in a microbiome sample much faster and more cheaply than existing technologies. The new approach, Pollard says, will allow researchers to perform larger and more precise analyzes of the microbiome than ever before.
In a separate article published online in Genome research, Pollard collaborated with the labs of Benjamin Good, PhD, and Michael Snyder, PhD, at Stanford University to track the strains of bacteria present in a person’s microbiome at 19 different times over a 5-month period, including before and after a course of antibiotics. They found that in some cases the abundance of a species of bacteria remained constant from moment to moment, but the strains within that species changed dramatically.
Giving meaning to microbiomes
Inside your gut, bacteria are probably doing more than just digesting your food. This is because studies have shown that people with conditions as diverse as inflammatory bowel disease, asthma, autism, diabetes and cancer have different bacteria in their digestive system than people with good health. But few treatments targeting the microbiome have emerged from these observations so far.
Since each bacteria has its own genetic code, scientists rely on DNA sequencing to find out which bacteria inhabit a particular person’s microbiome. But analysis of DNA sequences is difficult due to the size and complexity of the data. While researchers can use existing methods to determine which species are present, these only provide part of the picture of the diversity and function of the microbiome. Indeed, the different strains of the same species of bacteria can harbor important genetic differences, which are often large enough to induce different behaviors.
Until now, identifying genetic differences in a microbiome sample has required high-performance computing power and cloud storage, which is not available to most labs. The researchers had to compare millions of DNA fragments from the genomes of thousands of bacteria found in the microbiome to a database with the sequences of every known microorganism, using a technique known as alignment. sequences.
“The algorithms for analyzing genetic sequences have been developed for human genomes,” says Pollard, who is also a professor at UC San Francisco and a researcher at Chan Zuckerberg Biohub. “They work very well for the challenge of sequencing the genome of a single organism, but not for our needs of sequencing the genomes of thousands of unknown organisms at once.”
Pollard and his colleagues knew that long sequences of genomes are common in many species or strains of bacteria. Thus, these sequences cannot be used to help locate a specific bacterial strain. Inspired by approaches that analyze only the most variable regions of the human genome, the team set out to find the minimum amount of sequence information it would need to remove data from the microbiome to identify the strains it needs. it contained.
The researchers analyzed more than 100,000 publicly available, high-quality genomes from around 900 bacterial species commonly found in the human gut. They discovered 104 million short chains of DNA in bacterial genomes that most often vary between strains of bacteria. Then, they used that information to design a new algorithm, dubbed GenoTyper for Prokaryotes (GT-Pro), which searches microbiome sequence data for exact matches with key strings that serve as identifiers for bacterial strains. Unlike previous sequence alignment methods, GT-Pro fits in laptop memory and does not require high performance computing or cloud credits.
“With the explosion of newly sequenced genomes from the gut microbiome and other environments, we can now create detailed genetic maps for thousands of bacterial species,” says Nayfach. “Our approach takes advantage of this prior information to quickly and comprehensively identify genetic variants in a microbiome sample without performing tedious sequence alignments. “
The field of research was previously limited by the fact that only a few labs around the world have the money or computer equipment to analyze microbiome data at strain resolution.
“Our new algorithm opens the door for everyone to be able to achieve this level of resolution on a personal computer,” says Pollard.
Before and after antibiotics
One of the questions microbiome researchers have struggled to answer in recent years is how much the microbiome changes in a person’s body over time. This issue has been addressed at the species level; scientists have followed the evolution of the species composition of human microbiomes along with diet, disease or environmental changes. But the results did not explain how the microbiome acquires new functions, such as resistance to antibiotics or the ability to inactivate chemotherapy drugs, when species composition remains stable from month to month.
Pollard and his colleagues wanted to explore this question further by analyzing how strains of bacteria, rather than just species, change over time. They reused a method designed for sequencing single human cells and used it to barcode bacterial DNA molecules. This allowed the group to follow individual strains of bacteria in one person during a 5-month study.
The team sequenced a healthy individual’s microbiome about once a week for 5 months. During this time, the subject was surprisingly diagnosed with Lyme disease and received a 2-week course of antibiotics, known to kill many species of bacteria, including those that live in the human gut.
“What we assumed was that a lot of microbes would become less abundant with the antibiotics and then recover, but the microbiome in the end would look more or less like the microbiome in the beginning,” says Good, assistant professor of applied physics at Stanford.
In some cases this was true – some species and strains of microbes were remarkably resistant, present with almost unchanged genomes at the start and end of the 5 month period. But in other cases, the strains present after the antibiotics were genetically different from those at the start even though the abundance of the species did not change. Importantly, these differences would have been missed if the team had only analyzed the species present in each microbiome sample.
Although the GT-Pro algorithm was not yet available for use in this study, Pollard says it would make similar future studies much easier and cheaper to conduct.
Charting a New Path for Microbiome Studies
The bacteria in your body are like a jungle – a living, changing ecosystem with organisms coexisting in a delicate balance. By viewing satellite images from above, conservationists can monitor a jungle’s deepest and most drastic changes, but they’ll miss out on the finer subtleties that shape the environment.
Likewise, those who study the microbiome by observing the evolution of species have gotten a high-level view of the network and only see the most obvious links to health and disease. But with GT-Pro and a new view of microbial strains, Pollard says, new links will become apparent.
“There is still a lot of work to be done to understand the functional consequences of differences in the microbiome,” says Pollard. “But until now, we haven’t had the right measurement tools to ask these questions, and now we do. “
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