Bioinformatics Analysis Reveals the Transcriptional and Post-transcriptional Regulatory Mechanisms of Pathogenic Bacteria


Student thesis: Doctoral Thesis

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Award date29 Aug 2022


Pathogenic bacteria refer to bacteria that can invade the human body, animals and plants, grow and reproduce in the host, release toxic substances and cause pathological changes and infection in varying degrees. The research of pathogenic bacteria aims to understand the molecular mechanisms of their pathogenicity and immunity from the perspectives of genome structures and functions, and interactions between pathogenic cells and host immune response. Elucidating the pathogenesis of pathogenic bacteria and regulatory mechanism set the important foundation for vaccine development and improving host disease resistance, which are key to disease prevention and control.

Transcriptional regulation is one of the key biological processes that occur in various bacteria. Transcription factors alter gene expression and construct complex regulatory networks by altering transcription rates. Post-transcriptional control refers to the regulation of gene expression at the post-transcriptional level. RNA-binding proteins are key players in post-transcriptional regulations, which regulate RNA modification, transport, localization, degradation and translation by binding to RNAs. N6-methyladenosine (m6A) is a common internal modification on mRNA and plays an important regulatory role.

Next-generation sequencing followed by computational analysis using bioinformatics and systems biology approaches provide an important unbiased, data-driven strategy to explore and elucidate the regulatory mechanism of pathogenic bacteria on a genome-wide scale. This study focused on the application of bioinformatics analysis in the field of transcriptional and post-transcriptional regulatory mechanisms of pathogenic bacteria. The studies in each chapter are described below:

Chapter 1: This chapter introduces about the transcriptional and post-transcriptional regulatory mechanisms of pathogenic bacteria. Focusing on pathogenic bacteria, we discussed important factors of virulence, and different strategies of transcriptional and post-transcriptional regulations. Based on the knowledge above, we introduced the objective of this study.

Chapter 2: This chapter introduces a genome-wide, network-based approach to dissect the crosstalk between key virulence-related transcription factors in a plant pathogen, Pseudomonas syringae. By integrating epigenomic and genomic data, we mapped a regulatory network called “PSVnet” (Pseudomonas syringae regulatory network), which contained 16 transcriptional regulator, and 238 and 153 functional genes in King’s B medium and minimal medium, respectively. This network elucidated the crosstalks between 16 virulence-associated regulators in P. syringae and, provided a database and new perspective of more in-depth understanding of the complicated signaling pathways involved in P. syringae virulence.

Chapter 3: This chapter illustrates a global RNA-binding protein YafB on the plasmids of E. coli. Using RNA immunoprecipitation sequencing, we discovered hundreds of mRNAs interacting with YafB in uropathogenic E. coli CFT073 and commensal E. coli J53. These mRNAs were functionally clustered in the metabolism processes. We also identified several YafB binding sRNAs, with GcvB being the most abundant in both strains. In vivo and in vitro experiments revealed that YafB can compete with Hfq in the interaction with GcvB, thus contribute to the virulence.

Chapter 4: In this chapter, we investigated m6A modifications in the characteristics of pathogenic bacteria. We performed methylated RNA immunoprecipitation sequencing to identify the m6A modification pattern of pathogenic bacteria. The m6A modification genes from 16 bacteria were compared, and the results showed that m6A modification was associated with several genomic features, such as gene length and GC content. We identified the conserved genes of m6A modification among different species. Further analysis showed that m6A modification may be evolutionarily conserved and positively related with a high selection pressure. In addition, we validated the prevalent m6A modification on 23S ribosomal RNA.

Chapter 5: This chapter summarizes the thesis and discusses further perspectives.