https://www.quantamagazine.org/simpler-m...-20180119/
EXCERPT: Over the past century, scientists have become adept at plotting the ecological interactions of the diverse organisms that populate the planet’s forests, plains and seas. They have established powerful mathematical techniques to describe systems ranging from the carbon cycles driven by plants to the predator-prey dynamics that dictate the behavior of lions and gazelles. Understanding the inner workings of microbial communities that can involve hundreds or thousands of microscopic species, however, poses a far greater challenge.
Microbes nourish each other and engage in chemical warfare; their behavior shifts with their spatial arrangements and with the identities of their neighbors; they function as populations of separate species but also as a cohesive whole that can at times resemble a single organism. Data collected from these communities reveal incredible diversity but also hint at an underlying, unifying structure.
Scientists want to tease out what that structure might be — not least because they hope one day to be able to manipulate it. Microbial communities help to define ecosystems of all shapes and sizes: in oceans and soil, in plants and animals. Some health conditions correlate with the balance of microbes in a person’s gut, and for a few conditions, such as Crohn’s disease, there are known causal links to onset and severity. Controlling the balance of microbes in different settings might provide new ways to treat or prevent various illnesses, improve crop productivity or make biofuels.
But to reach that level of control, scientists first have to work out all the ways in which the members of any microbial community interact — a challenge that can become incredibly complicated. In a paper published in Nature Communications last month, a team of researchers led by Yang-Yu Liu, a statistical physicist at Harvard Medical School, presented an approach that gets around some of the formidable obstacles and could enable scientists to analyze a lot of data they haven’t been able to work with.
The paper joins a growing body of work seeking to make sense of how microbes interact, and to illuminate one of the field’s biggest unknowns: whether the main drivers of change in a microbial community are the microbes themselves or the environment around them....
MORE: https://www.quantamagazine.org/simpler-m...-20180119/
EXCERPT: Over the past century, scientists have become adept at plotting the ecological interactions of the diverse organisms that populate the planet’s forests, plains and seas. They have established powerful mathematical techniques to describe systems ranging from the carbon cycles driven by plants to the predator-prey dynamics that dictate the behavior of lions and gazelles. Understanding the inner workings of microbial communities that can involve hundreds or thousands of microscopic species, however, poses a far greater challenge.
Microbes nourish each other and engage in chemical warfare; their behavior shifts with their spatial arrangements and with the identities of their neighbors; they function as populations of separate species but also as a cohesive whole that can at times resemble a single organism. Data collected from these communities reveal incredible diversity but also hint at an underlying, unifying structure.
Scientists want to tease out what that structure might be — not least because they hope one day to be able to manipulate it. Microbial communities help to define ecosystems of all shapes and sizes: in oceans and soil, in plants and animals. Some health conditions correlate with the balance of microbes in a person’s gut, and for a few conditions, such as Crohn’s disease, there are known causal links to onset and severity. Controlling the balance of microbes in different settings might provide new ways to treat or prevent various illnesses, improve crop productivity or make biofuels.
But to reach that level of control, scientists first have to work out all the ways in which the members of any microbial community interact — a challenge that can become incredibly complicated. In a paper published in Nature Communications last month, a team of researchers led by Yang-Yu Liu, a statistical physicist at Harvard Medical School, presented an approach that gets around some of the formidable obstacles and could enable scientists to analyze a lot of data they haven’t been able to work with.
The paper joins a growing body of work seeking to make sense of how microbes interact, and to illuminate one of the field’s biggest unknowns: whether the main drivers of change in a microbial community are the microbes themselves or the environment around them....
MORE: https://www.quantamagazine.org/simpler-m...-20180119/