Associating Growth Conditions with Cellular Composition in Gram-negative Bacteria
Abstract
The overarching goal of this project is to develop an understanding of how bacterial growth conditions relate to bacterial physiology, and more importantly, how we may predict growth conditions from physiology. The association between growth conditions and physiology (as measured by cellular composition) has important applications both in bacterial forensics (e.g., identifying the source of a pathogen used in a deliberate attack) and in engineering applications. We are carrying out theoretical and experimental work to address this question. First, we are developing general statistical theory for Multiple-Input-Multiple-Output data sets. Second, we are developing theoretical and computational models that link bacterial physiology back to growth conditions. Third, we are collecting a comprehensive experimental data set of E. coli grown under a variety of different conditions. In this data set, we obtain a variety of cellular composition measurements for our samples, include RNA expression data, protein expression data, lipid abundance data, and metabolic flux data. Fourth, we are applying the statistical and computational methods to the experimental data set we are compiling, with the ultimate goal to be able to predict the specific conditions under which a sample was grown from the measured cellular composition.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jun 21, 2018
- Accession Number
- AD1062635
Entities
People
- Bart Smith
- Claus O. Wilke
Organizations
- University of Texas at Austin