A new computational tool developed by UGA statistics researchers shows promise for further understanding and identifying the complicated makeup of the microbiome:
Microbes, found everywhere—in our environment, on our skin and in human bodies and consisting of bacteria, archaea, fungi, protozoans and viruses—form microbiomes that have both good and harmful implications for human health.
With the creation of this new big data tool, researchers will help identify differences in patterns of microbes that may lead to a better understanding of chronic diseases such as diabetes and obesity.
“Accumulating evidence suggests that the microbial ecosystems play a crucial role in human health. However, compared to the huge amounts of medical research on human cells, our understanding of the microbial ecosystems is very limited; the biodiversity of them is not completely understood, not to mention their interactions with the human host,” said Wenxuan Zhong, professor of statistics and director of the UGA Big Data Analytics Lab.”
Zhong and her team have created a new computational tool called MetaGen that can simultaneously identify microbial species and estimate their abundance in multiple samples.
“MetaGen is able to quantify their distributions in large microbial communities,” Zhong said. “With the growing number of the samples being sequenced, our effort will greatly help both the computational biologist and the experimental biologist in studying the changes of the microbial ecosystems, detecting pathogens and reducing the diagnostic error in microbial-related human diseases.”
Zhong and her team tested metagenomics data of chronic diseases such as inflammatory bowel disease, Type 2 diabetes and obesity. They were able to test 378 billion base pairs, which is the equivalent of testing over a hundred human genomes at once.
The microbiome is a kind of unified theory-grail that is neither theory nor fiction but a construct that
will is helping scientists in every imaginable environment, from the human gut to the oceans. The sheer scale of it all can be difficult to comprehend - and extraordinarily difficult to work with. But that is where these efforts really show promise. New tools will facilitate breakthroughs in basic research, therapies and solutions. Great work and great news for scientists in practically every discipline.
Image: public domain Big Data world illustration/graphic