It is now possible to investigate the entire population of a class of biomolecules in a cell or tissue simultaneously. Genomics, the study of all of the genes in an organism was the first such technology. Now, transcriptomics, proteomics, metabolomics, lipidomics, and a host of other “omics” techniques are changing the way biologists view and study cells. Data from these techniques are catalyzing fundamental changes in our understanding of biology. One such change is the view of organisms as dynamic systems composed of networks. These networks are highly interwoven and span molecular classes. Significantly, it is now clear that it is not possible to understand a biological system by only studying the parts. It is the goal of systems biology to integrate data on cellular networks into mathematical models with predictive power. While models that can predict biological responses have begun to emerge, they are still very limited. Our research focuses on model systems with the goal of developing biological models that can then be extended to more complex organisms and eventually human disease.
Archaea are philogenetic intermediates between Eukaryotes and Bacteria. The general lack of knowledge about their physiology and small genome size make them a good choice for systems biology studies. The extremophiles S. solfataricus is a member of the Archaeal domain of life and is a modle system for understanding adaptations to life in extreme environments. Using deep sequencing, proteomics, and metabolomics we are mapping metabolic pathways and building models of signaling networks in this interest organism that inhabits many of the hot springs in Yellow Stone National Park.
Few, if any, microbes live in functional or spatial isolation. The nature of the various types of inter-species interactions can be complex, ranging from competition to mutualism or syntrophy (metabolic interdependence). Such relationships can impact keystone species and play a major role in energy and element cycles at scales that extend past ecosystem boundaries. Currently, there is little understanding of the fundamental mechanisms of interspecies recognition and communication, how mutualism and syntrophy impacts microbial genome evolution and what genetic regulatory mechanisms control metabolic/energetic coupling between species in response to environmental factors. To address these questions we are studying the archaeal symbiotic system Ignicoccus hospitalis-Nanoarchaeum equitans to characterize mechanisms of interspecific recognition and communication, modulation of gene expression and metabolic processes triggered by the association. With a combined genomic complement of less than 2000 genes and an obligate chemolithoautotrophic metabolism that integrates adaptive traits and biochemical processes of interest to DOE, this system represents the simplest microbial association known in nature and allows fundamental system level investigations and modeling of symbiosis.
We have adopted this system and are using a two-level proteomics approach to elucidate pathways and proteins involved with MNV infection. At the systems level, 2D differential gel electrophoresis (2D-DIGE) is being applied to generate an overview of the global changes in the host proteome during infection. This is being complemented by activity-based screening of enzyme classes. Activity-based protein profiling (ABPP) is currently the only technique that can directly measure specific protein activity across a biological system.
Research Associate: Dr. Walid Maaty. Post Doctoral: Monika Tokmina-Lukaszewska Graduate students: Joshua Heinemann, Patricia Mathabe, and Michelle Tigges.
Proteomics, Chemical Biology, Biochemistry, Analytical