Collaborative Research: Deciphering complex phenotypes in bacteria aided by continuous genome shuffling and high throughput analytical technologies

San Jose State University Foundation, San Jose CA

Investigators

Abstract

A defining trait of living systems is that they adapt and evolve. This trait can be used in biotechnology to produce microbes with desired properties and functions. However, adaptation of microbial systems can cause instability and loss of performance. Maximizing the performance of microbial systems in biotechnology rests on understanding the mechanisms of adaptation and evolution. This is far from being a trivial task; it requires new knowledge and methods to investigate the “gap” between an organism's genes (genotype) and characteristics (phenotype). The research supported by this NSF award focuses on the development of a knowledge base of cellular properties associated with desired complex phenotypes. Such a base could be used to study the relationship between genotype and the observed phenotype, to narrow the gap between these two properties of a microbial system, and to enable microbial engineering for applications in biotechnology as well as in biomedicine. The researchers will recruit high school and undergraduate students, with a focus on underrepresented students, to conduct research in the area of biotechnology. The central hypothesis of this project is that there exist cellular properties that are correlated with phenotypes-of-interest. The hypothesis is formed based on preliminary data that show correlations between certain cellular properties and microbial fitness in specific environments. The proposed objectives are: 1) to develop and characterize a recombination-proficient genderless strain of E. coli with increased recombination frequency, 2) to apply the genderless strain to identify cellular properties associated with complex phenotypes, and 3) to generate strains with tolerance to multiple environmental stressors. Results from this work will shed light on how cellular properties identified correlate with phenotypes (e.g. tolerance to stressors), genotype, and on the underlying molecular mechanisms that connect the genotype to the phenotype. This knowledge may be used to modify in a rational manner cellular properties to enhance tolerance to industrially-relevant environmental stressors. The knowledge base will provide an important resource for the biotechnology community to facilitate rational strain engineering. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.