Inferring relationships between Genotype, Phenotype and Environment

A central problem in biology is to uncover the links between the genetic makeup of an organism (genotype) and its observable physical or biochemical characteristics (phenotype). This is very important as, for example, it would increase our ability to rapidly characterize an unknown microorganism, which is critical in both responding to infectious disease and biodefense. To do this, we need some way of anticipating an organism’s phenotype based on the molecules encoded by its genome.

Approaches have been developed to sample the genetic content of heterogeneous environments (metagenomics). We investigated how metagenomic sequences link distinct environmental conditions with specific biological processes. We focused on how the usage of particular pathways and subnetworks reflects the adaptation of microbial communities across environments and habitats. We introduced a novel approach to relate multiple, continuously varying factors defining an environment to the extent of particular microbial pathways present in a geographic site. This allowed us to develop a method to identify ensembles of weighted pathways, which we called metabolic footprints, that are predictive of their environment and could be used as biosensors.

We have also developed a method to predict essential genes in pathogens that could be used for directed drug development.

At the same time, by what means specific sequences link distinct environmental conditions with specific biological processes is also not well understood. Thus, another important challenge is how the usage of particular pathways and subnetworks reflects the adaptation of microbial communities across environments and habitats – i.e., how network dynamics relates to environmental features.

• Quantifying environmental adaptation of metabolic pathways in metagenomics 
  Proc Natl Acad Sci USA (2009) Feb 3;106(5):1374-9. This paper was highlighted in Science 2009; 323 (5918) and Nature Genetics 2009; 41 (275).
  
  
• Predicting essential genes in fungal genomes
  Genome Research, 16, 1126 (2006).
  
  
• Integrating curated databases to identify genotype-phenotype associations 
  BMC Genomics, vol. 7, p. 257, 2006.