bioRxivBiochemistry
Pathogenic bacteria experience pervasive RNA polymerase backtracking during infection
Abstract
Pathogenic bacteria and their eukaryotic hosts are in a constant arms race. Hosts have numerous defense mechanisms at their disposal that not only challenge the bacterial invaders, but have the potential to disrupt molecular transactions along the bacterial chromosome. However, it is unclear how the host impacts association of proteins with the bacterial chromosome at the molecular level during infection. This is partially due to the lack of a method that could detect these events in pathogens while they are within host cells. We developed and optimized a system capable of mapping and measuring levels of bacterial proteins associated with the chromosome while they are actively infecting the host (referred to as PIC-seq). Here, we focused on the dynamics of RNA polymerase (RNAP) movement and association with the chromosome in the pathogenic bacterium Salmonella enterica as a model system during infection. Using PIC-seq, we found that RNAP association patterns with the chromosome change during infection genome-wide, including at regions that encode for key virulence genes. Importantly, we found that infection of a host significantly increases RNAP backtracking on the bacterial chromosome. RNAP backtracking is the most common form of disruption to RNAP progress on the chromosome. Interestingly, we found that the resolution of backtracked RNAPs via the anti-backtracking factors GreA and GreB is critical for pathogenesis, revealing a new class of virulence genes. Altogether, our results strongly suggest that infection of a host significantly impacts transcription by disrupting RNAP movement on the chromosome within the bacterial pathogen. The increased backtracking events have important implications not only for efficient transcription, but also for mutation rates as stalled RNAPs increase the levels of mutagenesis.
- organism: bacteria (other)
- assay: DNA methylation
- research focus: chromatin & epigenetic regulation
- research focus: cell type annotation
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: experimental assay
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