New Tools for Measuring and Analyzing Bacterial Gene-Expression Dynamics

Abstract

Messenger RNAs (mRNAs) are essential targets of gene regulation. The cell adapts and grows by changing its gene-expression profile, which it can achieve by manipulating the rates of mRNA initiation and decay and thus changing the relative abundances of transcripts. To understand the biological significance of these transcriptomic changes it is useful to observe how these changes correlate with emergent downstream behaviors and phenotypes. To manipulate and predict transcriptomic changes, it is also helpful to identify the sites of RNA regulation (transcription initiation, termination, and decay). By observing these sites of regulation, and how they change across different environmental and genetic contexts we can learn to recognize the sequence determinants of these processes and anticipate under which circumstances they will modulate gene expression changes. In order to record transcriptomic histories and facilitate the correlation of these archives with emergent cellular behaviors I have developed a molecular time capsule (MTC). An MTC is a self assembling protein capsule which captures highly reproducible snapshots of the full cellular transcriptome for delayed retrieval and analysis. These encapsulated records remain stable, even while the host transcriptome undergoes major remodeling. These records are also cleanly separable from non-encapsulated RNAs originating either from the host cell itself, or from other cells in a heterogenous population. To facilitate the identification of transcript ends across multiple conditions, I have also developed analysis tools for end-enriched RNA sequencing data (Rend-seq). Rend-seq is a variation of RNA-sequencing that aids in the interference of in vivo 5′ and 3′ ends in addition to determining their abundances. The tools I have developed for processing and identifying transcript ends from these data have been bundled into an open source Python package: rendseq. This package also powers an interactive website, rendseq.org, which increases the accessibility of published Rend-seq datasets.