Meta'omics for hacking the human microbiome
As healthy adults, we harbour ~100 trillion microbes which outnumber our own cells by a factor of ten. This microbial diversity (the "microbiome") and its functions are still largely uncharachterized but we can now try to mine it using cultivation-free metagenomic tools.
We employ experimental meta'omic tools and novel computational approaches to study the diversity of the microbiome and its role in human dysbiosis and infections. Our projects bring together computer scientists, microbiologists, statisticians, and clinicians.
Main research directions
Next generation computational metagenomic tools. The potential of shotgun metagenomics (several GBs/sample) is only partially expressed due to computational challenges. We are working on novel computational tools to profile microbiomes at increased resolution. This involves processing thousands of microbial genomes and is also resulting in new tools for microbiology, phylogenomics, and pathogen identification.
Integrative and machine learning meta'omic approaches. Microbiomes are complex biological entities that require ad-hoc statistical approaches. We develop new machine learning tools to cope with the variability and dimensionality of microbiomes to provide robust and clinically relevant analyses and biomarkers also integrating complementary meta'omic approaches (e.g. metatrasncriptomics or metaproteomics).
Microbiome-pathogen interaction in human infections. Despite intriguing results in mice, the role of microbiome-pathogen interactions in the acquisition and development of infections is unclear. By coupling longitudinal pathogen and microbiome sequencing we aim understand how the microbiome can modulate the virulence profile and antibiotic resistance of human infections, with specific focus on Cystic Fibrosis infections.
Microbiome transmission and infant probiotics. We study how microbes can be transmitted between different environments and become stable colonizers in the new environment. Specifically, we investigate the sources of variability for the early colonization of the infant gut, considering environmental factors as well as vertical mother-to-infant transmission of potentially probiotic strains .