The objective of this project is to examine how bacteria coordinate production of ribosomes, which are crucial for their growth. Ribosomes are the biological machines responsible for making proteins, and in actively growing bacteria they constitute over 1/3 of the cell's contents. Thus, cells devote a large proportion of their resources to the production of ribosomes. Ribosomes require approximately 60 different components that must be produced in the correct proportions. In order to use resources most efficiently, bacteria practice just-in-time production of their ribosomal parts. This research will provide insight into this process in bacterial strains with important roles in soil bioremediation, agriculture, and the food industry, leading to increased ability to engineer the growth rate and metabolism of these strains. By understanding how this biological problem is solved in different ways by different strains of bacteria, we will better understand how such coordination can evolve and what the important performance parameters may be. This research also provides significant opportunities to young scientist trainees at the graduate, undergraduate and high school levels because it may be broken into many individual projects with limited scope and specific testable hypotheses that are accessible to novice scientists.
This project seeks to determine the role of RNA regulation on ribosomal protein synthesis in gram-positive bacteria. While the regulation of this process is well understood in the model gram-negative bacterium Escherichia coli, it remains virtually unexamined in gram-positive bacteria. By identifying and characterizing RNA structures that accomplish this task in the model gram-positive bacterium Bacillus subtilis, we will uncover numerous uncharacterized RNA regulatory structures that are alternative solutions to the same biological problem, and provide another picture of how this complex process occurs. This research will also contribute new fodder for growing RNA structural databases and biophysical analysis of RNA-protein interactions, and provide insight into the factors influencing how such systems may evolve. To accomplish these goals computationally predicted RNA structures associated with ribosomal proteins will be computationally curated to determine whether they are transcribed, resemble ribosomal RNA binding sites, or are associated with features that commonly have regulatory roles. The biological function of these RNAs will then be experimentally validated using both in vitro RNA-protein binding assays and in vivo genetic regulatory assays.
