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RESEARCH

The main focus in Prof. Nagarajan’s lab is in the development of cutting-edge genome analytic tools for studying the function of diverse microbial communities and their impact on human health. His team conducts research at the interface of genetics, computer science and microbiology, in particular using a systems biology approach to understand host-microbiome-pathogen interactions in various disease conditions. His lab was one of the first to develop hybrid assembly tools for genome-resolved metagenomics and leveraging them for microbial surveillance in hospital environments. The lab has conducted several studies to understand the role of environmental and human microbiomes in antimicrobial resistance (AMR) transmission. The lab has also pioneered the use of new approaches to study Asian skin microbiomes and understand their role in various skin conditions.

RESEARCH INTEREST

Metagenomics, Human Microbiome, Antimicrobial Resistance, Bioinformatics

Selected Publications

• Ravikrishnan, A. et al. Gut metagenomes of Asian octogenarians reveal metabolic potential expansion and distinct microbial species associated with aging phenotypes. Nat Commun 15, 7751 (2024)
• Tan, C. C. S. et al. No evidence for a common blood microbiome based on a population study of 9,770 healthy humans. Nat Microbiol (2023)
• Gounot, J. S. et al. Genome-centric analysis of short and long read metagenomes reveals uncharacterized microbiome diversity in Southeast Asians. Nat Commun 13, (2022)
• Kang, J. T. L. et al. Long-term ecological and evolutionary dynamics in the gut microbiomes of carbapenemase-producing Enterobacteriaceae colonized subjects. Nat Microbiol 7, 1516–1524 (2022)
• Chng, K. R. et al. Metagenome-wide association analysis identifies microbial determinants of post-antibiotic ecological recovery in the gut. Nat Ecol Evol 4, 1256–1267 (2020)
• Chng, K. R. et al. Cartography of opportunistic pathogens and antibiotic resistance genes in a tertiary hospital environment. Nat Med 26, 941–951 (2020)
• Bertrand, D. et al. Hybrid metagenomic assembly enables high-resolution analysis of resistance determinants and mobile elements in human microbiomes. Nat Biotechnol 37, 937–944 (2019)
• Li, C. et al. An expectation-maximization algorithm enables accurate ecological modeling using longitudinal microbiome sequencing data. Microbiome 7, (2019)
• Chng, K. R. et al. Whole metagenome profiling reveals skin microbiome-dependent susceptibility to atopic dermatitis flare. Nat Microbiol (2016)
• Wilm, A. et al. LoFreq: A sequence-quality aware, ultra-sensitive variant caller for uncovering cell-population heterogeneity from high-throughput sequencing datasets. Nucleic Acids Res (2012)