Xia Lab @ McGill

Metabolomics & Microbiomics

Metabolomics is the systematic study of all small molecules in a biological system. The metabolome consists of both endogenous metabolites and exogenous compounds derived from diet, gut microbes and environmental exposures. The increased application and availability of accurate, high-resolution LC-MS systems has significantly advanced progress in metabolomics. The long-term goal of my reseaarch is to develop a system metabolomics platform to bridge targeted and untargeted metabolomics, while maximizing throughput and information gain for systems-level understanding.

The microbes living in our gut (microbiome) interact extensively with their host through metabolic exchanges and co-metabolism of foods, drugs, and chemical pollutants. Given their high relevance to human and animal health, growing number of large-scale projects have been carried out to study microbiome. However, data analysis and functional interpretation have become the major challenges. We are currently developing algorithms, tools and databases, with particular interests to integrate metabolomics with other omics to obtain functional insights.

Web & Cloud-based Visual Analytics

The current biomedical big data challenges are characterized by both size and complexity. A long-term interest in my laboratory is to develop new-generation computational frameworks integrating high-performance computing, statistics and data visualization techniques, coupled with comprehensive domain knowledge to facilitate novel discovery, hypothesis generation, and systems understanding. We use both local supercomputers and public cloud to enable high-performance data analysis. To date, we have developed multiple popular software tools for metabolomics, transcriptomics and microbiomics. These tools are used by 1000s of researchers worldwide in their omics data analysis and interpretation.

We are currently developing two complementary approaches (biological networks and multivariate statistics) for multi-omics integration - the former is based mainly on known molecular interactions (suitable for model organisms), while the latter can be used to identify coherent patterns for any organisms.

C. elegans model for Gene-Environment-Microbiome (GEM) Interactions

Recent studies have shown the that natural populations of C. elegans harbor distinct microbiome, which can be easily established and maintained in the laboratory. We are developing this model to study the effects of different microbiome compositions on worm fitness as well as response to chemical exposures. Distinct phenotypes are further investigated using deep sequencing and metabolomics for mechanistic understandings.

We are developing a high-throughput platform consisting of a powerful microscope, a worm ScreenChip system, and a cutting-edge Orbitrap LC-MS for investigating GEM interactions.