Unveiling The Regulation of Secondary Metabolism in Steptomyces
Sarika Mehra1, Karthik Jayapal2, Salim Charaniya3, Marlene Castro2, Doraiswami Ramkrishna4, and Wei-Shou Hu3. (1) 1Department of Chemical Engineering, Indian Institute of Technology, 421 Washington Ave SE, 151 Amundson Hall, MailBox No. 70, Bombay, India, (2) University of Minnesota, 421 Washington Ave SE, 151 Amundson Hall, MailBox No. 70, Minneapolis, MN 55455, (3) Chemical Engineering and Materials Science, University of Minnesota, 151 Amundson Hall, 421 Washington Avenue SE, Minneapolis, MN 55455-0132, (4) Chemical Engineering, Purdue University, 1283 Forney Hall, West Lafayette, IN 47907
Streptomyces produces many antibiotics that help them compete with other organisms in their natural habitat. The production of those arsenals is highly coordinated in a population to expedite its accumulation to an effective concentration. Furthermore, as antibiotics are often toxic to even their producers, a coordinated production allows microbes first to arm themselves with a defense mechanism to resist their own antibiotics before production commences. The signals which indicate impending adverse conditions, and thus antibiotic production, are likely to be riddled with noise. Differentiating between these signals and noise is critical for a coordinate response and thereby the survival of the population. One possible mechanism of coordination is through the production of signaling molecules. If a large number of surrounding neighbors are positively responding to the signal and the signaling molecule is accumulating, then the signal must be true, hence the laggard will respond too. Conversely, if that number is small, then the signal is probably false; and those which have responded will eventually return to the original non-antibiotic producing state. Downstream of the signaling pathways, the antibiotic biosynthesis is regulated by a dynamic network involving multiple overlapping circuits and many layers of cellular control. To facilitate the elucidation of the regulatory network we have constructed a series of disruption mutants for known and putative regulatory genes in Streptomyces coelicolor and employed genomic proteomic and modeling tools to probe their gene expression dynamics. This integrated approach combining computational tools and experimentation with bioinformatic analysis has facilitated the deciphering and unlocking the regulation of secondary metabolism. However, those data alone are insufficient for reconstructing even some local regulatory network. The missing links and the possible approaches to further our understanding of the regulation of secondary metabolism will be discussed.