Optimizing the production of useful macromolecules from transgenic microorganisms is crucial to biopharmaceutical companies. Improving bacterial growth and replication depends largely on the efficiency of translation, which is rate-limited by initiation. Among the most important interactions between the mRNA translation initiation region (TIR) and the translation machinery is the association between the Shine-Dalgarno (SD) sequence in the TIR and the complementary anti-SD (aSD) sequence which is located within a short unstructured segment that includes the 3’ terminus (3’ TAIL) of the mature 16S rRNA. However, the mature 3’ TAIL has been poorly characterized in the majority of bacteria, rendering optimal SD/aSD pairing unclear in these species.
In light of this, we established a novel strategy to characterize the mature 3’ TAILs of bacterial species that leverages the availability of publically stored RNA sequencing (RNA-Seq) data. In chapter 2, we devised a RNA-Seq-based approach to successfully recover the experimentally verified 3’ TAIL in E. coli (5’-CCUCCUUA-3’) and resolve inconsistencies surrounding the identity of the 3’ TAIL in Bacillus subtilis. In chapter 3 we improve the method introduced in chapter 2 to clearly and more reliably define the 3’ TAIL termini for 13 bacterial species with available protein abundance data.
Our results reveal considerable heterogeneity in the termini of 3’ TAILs among closely related species and that sites downstream of the canonical CCUCC aSD motif are more important to initiation than previously believed. My research contributes to advance our understanding in microbial translation efficiency in two significant ways: 1) providing an RNA-Seq-based approach to characterize rRNA transcripts, and 2) elucidating optimal recognition between protein-coding genes and the rRNA translation machinery.
Identifer | oai:union.ndltd.org:uottawa.ca/oai:ruor.uottawa.ca:10393/39044 |
Date | 08 April 2019 |
Creators | Silke, Jordan |
Contributors | Xia, Xuhua |
Publisher | Université d'Ottawa / University of Ottawa |
Source Sets | Université d’Ottawa |
Language | English |
Detected Language | English |
Type | Thesis |
Format | application/pdf |
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