A unique neural network tool is making it possible to accurately infer the interactions between the microbes that are present in a community and the metabolites they produce – a capability that will greatly advance research into the microbiomes in the environment and inside our bodies.
The gut microbiome undergoes rapid and dramatic changes in species composition and gene expression when the host switches between eating cooked or raw vegetables, according to a new study published in Nature Microbiology.
An international team of scientists led by the Joint Genome Institute has developed a genetic engineering tool that makes producing and analyzing microbial secondary metabolites – the basis for many important agricultural, industrial, and medical products – much easier than before, and could even lead to breakthroughs in biomanufacturing.
Every year, hydraulic fracturing of oil and gas wells generates billions of gallons of contaminated water. Scientists at Berkeley Lab and the CO School of Mines believe microbes could be the key to turning this waste into a resource.
Long ago, during the European Renaissance, Leonardo da Vinci wrote that we humans “know more about the movement of celestial bodies than about the soil underfoot.” Five hundred years and innumerable technological and scientific advances later, his sentiment still holds true. But that could soon change. A new study in Nature Communications details how an improved method for studying microbes in the soil will help scientists understand both fine-grained details and large-scale cycles of the environment.
A human’s health is shaped both by environmental factors and the body’s interactions with the microbiome, particularly in the gut. Genome sequences are critical for characterizing individual microbes and understanding their functional roles. However, previous studies have estimated that only 50 percent of species in the gut microbiome have a sequenced genome, in part because many species have not yet been cultivated for study.