Xiaofang Jiang, Ph.D.

The overarching goal of this Dr Jiang's group is to develop computational tools and approaches to advance microbiome-based diagnostic, therapeutic and preventive practices in biomedical and clinical health sciences. Currently her key research areas are:

1. Functional profiling of health-relevant features of the microbiome data via comparative genomics. Most health-relevant features of microbial genomes are only studied in only one or a few species. Dr Jiang's group is developing a functional profiling framework to identify these functions across a broad range of gut microbial species using ortholog detection, phylogenetic inference and structural modeling.
2. Explore the genomic basis of the adaptation of gut bacteria taxa to specific ecological niches. Leveraging the ever-growing volume of multi-omics data in microbiome research, Dr Jiang's group is working to pinpoint the genetic components of gut bacteria species that confer interaction with diet and host‐derived metabolites using genomics, metabolomics, statistical inference, and machine learning approaches.

In response to the COVID-19 pandemic, Dr Jiang's group investigates genome evolution in coronaviruses, particularly, the factors and mechanisms that contribute to and underlie coronavirus genome recombination. Dr Jiang's group is involved in a collaborative project to build metagenomic analysis infrastructure for wastewater-derived SARS-CoV-2 sequences to determine the active circulating variants within a community.

Dr. Jiang started her research program at the National Library of Medicine in August 2019. Prior to joining the NLM, she performed postdoctoral research at MIT and the Broad Institute. During her postdoctoral training, she developed tools to annotate mobile genetic elements from the gut microbiome and identify phase variable regions in bacterial genomes. Her findings on invertible promoter mediate bacterial phase variation, antibiotic resistance, and host adaptation in the gut were published in Science (2019). Dr. Jiang earned her Ph.D. in Genetics, Bioinformatics, and Computational Biology from Virginia Tech in 2016.