New York, Jan 22 (IANS) Scientists have developed a novel computational method that reveals roles that different bacteria plays in microbiome imbalances linked to disease.
Trillions of microbes that live on and inside our bodies -- collectively forming our microbiome -- may be playing a key role in defining our health.
The method, called "Functional Shifts' Taxonomic Contributors" or FishTaco, reveals how much different bacterial species contribute to disease-associated functional imbalances in the microbiome.
It integrates taxonomic and the functional approach - the two most common approaches scientists use to profile the microbiome and to identity associations with disease.
"This method allows us to pinpoint which microbial species in our microbiome are responsible for each functional imbalance so they can be targeted for therapy," said Elhanan Borenstein, Associate Professor at the University of WashingtonAin Seattle, US.
FishTaco integrates the two approaches to assess what bacteria are doing and in which part of your body.
For the study, the team analysed the microbiomes of individuals with Type 2 diabetes and inflammatory bowel disease.
The results showed that functional shifts are often driven by diverse combinations of species.
Further, they found very similar functional imbalances observed in different diseases may in fact be driven by completely different set of species.
"Identifying the species that drive such imbalances in each disease is therefore an essential step toward targeted interventions aiming to manipulate the functional capacity of the microbiome and promote health," Borenstein added.
The study appears in the journal Cell Host & Microbe.
About VDC
Doraiah Chowdary Vundavally is a Software engineer at VTech . He is the news editor of SocialNews.XYZ and Freelance writer-contributes Telugu and English Columns on Films, Politics, and Gossips. He is the primary contributor for South Cinema Section of SocialNews.XYZ. His mission is to help to develop SocialNews.XYZ into a News website that has no bias or judgement towards any.