Rapid Reverse-Engineering of Shewanella Gene Networks: Applications for Bioremediation

Michael Driscoll, Boston University

Photo of Michael Driscoll

From energy transduction and organic synthesis, to environmental sensing and signal processing, the stunning varieties of cellular behavior rival that of any engineered system. The versatility of cellular systems is based upon regulatory networks of interacting genes. Identifying the architecture and dynamics of these gene networks is an key aim of contemporary biology, requiring novel experimental and computational approaches.

Shewanella oneidensis is naturally-occurring bacterium whose unique capacity for reducing uranium (and a variety of other substrates) during respiration has made it a leading candidate for bioremediation uses in toxic waste sites. This respiratory flexibility is conferred by extensive gene networks regulating the concentrations of enzymes and other metabolic proteins.

Knowledge of the networks underlying Shewanella’s (i) aerobic to anaerobic growth transition and (ii) facultative use of alternate substrates will facilitate the optimization of these respiratory pathways for bioremediation applications.

We have developed a reverse-engineering method that enables rapid construction of a first-order differential model of a gene regulatory networks. The method, called Network Identification by multiple Regression (NIR), uses (i) steady-state perturbations to the network, (ii) measurements of the system response, and (iii) multiple linear regression to construct the first-order differential model a network (Gardner et al., Science 301: 102, 2003).

Our goal is to construct a model of the regulatory pathways controlling electron transport genes in Shewanella. We aim to identify the mechanisms that govern the oxidation and reduction of a range of electron donors and acceptors. We believe our method could improve the efficiency of existing efforts of Shewanella researchers in particular, and aid in the mapping of microbial gene networks more generally.

Abstract Author(s): Driscoll ME, Cantor CR, Collins JJ, Gardner TS