Advanced methods to delineate complex microbial communities towards clinical application
The cost-effective massive and parallel sequencing methods based on bacterial 16S rRNA gene amplicons have been crucial in uncovering the enormous diversity of microorganisms inhabiting the human body. They have been applied for years in hundreds of human cohorts to seek associations between microbiota and health states. Despite the broad application, these methods reached their full flourish years ago. Nowadays, they cannot describe the species present in complex microbial communities associated with human samples in a detailed manner. Consequently, it is necessary to implement a new generation of molecular methods and data analysis to fill the gap in establishing specific associations between species and disease conditions, reducing the ambiguity and uncertainty of such predicted links. We present a novel, cost-effective molecular method to discriminate species and strain level variation in human-associated microbial communities. The rigorous control of significant covariates recognized to impact the human microbiota is imperative to ascertain the biomarkers pursuit for clinical application accurately.
Dr Alfonso Benítez-Páez is a biologist and biochemist with a PhD in Molecular Biology from the University Autonomous of Madrid. He is the Principal Investigator of the Host-Microbe Interactions in Metabolic Health laboratory at the Principe Felipe Research Center in Valencia, Spain. Appointed Tenure Scientist for the Spanish National Research Council. His investigation is based on establishing interactions among diet, human microbiota and health and disease states. He has multidisciplinary expertise in microbiology, molecular biology, computational biology, and data analysis. Currently, he is part of the Editorial Boards of Frontiers in Nutrition, Frontiers in microbiology, and Microbiome journal.