CosR (Campylobacter oxidative stress regulator; Cj0355c) is an OmpR-type response regulator essential for the viability of Campylobacter jejuni, a leading foodborne pathogen causing human gastroenteritis worldwide. Despite importance, the function of CosR remains completely unknown mainly because of cell death caused by its knockout mutation. To overcome this technical limitation, in this study, antisense technology was used to investigate the regulatory function of CosR by modulating the level of CosR expression. Two-dimensional gel electrophoresis (2DGE) was performed to identify the CosR regulon either by suppressing CosR expression with antisense peptide nucleic acid (PNA) or by overexpressing CosR in C. jejuni. According to the results of 2DGE, CosR regulated 32 proteins involved in various cellular processes. Notably, CosR negatively regulated a few key proteins of the oxidative stress response of C. jejuni, such as SodB, Dps, Rrc and LuxS, whereas CosR positively controlled AhpC. Electrophoretic mobility shift assay showed that CosR directly bound to the promoter region of the oxidative stress genes. DNase I footprinting assays identified 21-bp CosR binding sequences in the sodB and ahpC promoters, suggesting CosR specifically recognizes and binds to the regulated genes. Interestingly, the level of CosR protein was significantly reduced by paraquat (a superoxide generator) but not by hydrogen peroxide. Consistent with the overall negative regulation of oxidative stress defense proteins by CosR, the CosR knockdown by antisense rendered C. jejuni more resistant to oxidative stress compared to the wild type. Overall, this study reveals the important role played by the essential response regulator CosR in the oxidative stress defense of C. jejuni.

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Campylobacter jejuni is a leading food-borne pathogen causing gastroenteritis in humans. Although OxyR is a widespread oxidative stress regulator in many Gram-negative bacteria, C. jejuni lacks OxyR and instead possesses the metalloregulator PerR. Despite the important role played by PerR in oxidative stress defense, little is known about the factors influencing perR expression in C. jejuni. In this study, a perR promoter-lacZ fusion assay demonstrated that iron significantly reduced the level of perR transcription, whereas other metal ions, such as copper, cobalt, manganese, and zinc, did not affect perR transcription. Notably, a perR mutation substantially increased the level of perR transcription and in trans complementation restored the transcriptional changes, suggesting perR is transcriptionally autoregulated in C. jejuni. In the perR mutant, iron did not repress perR transcription, indicating the iron dependence of perR expression results from perR autoregulation. Electrophoretic mobility shift assays showed that PerR binds to the perR promoter, and DNase I footprinting assays identified a PerR binding site overlapping the ؊35 region of the two perR promoters, further supporting perR autoregulation at the transcriptional level. Alignment of the PerR binding sequence in the perR promoter with the regulatory region of other PerR regulon genes of C. jejuni revealed a 16-bp consensus PerR binding sequence, which shares high similarities to the Bacillus subtilis PerR box. The results of this study demonstrated that PerR directly interacts with the perR promoter and regulates perR transcription and that perR autoregulation is responsible for the repression of perR transcription by iron in C. jejuni.

Clinically differentiating multiple system atrophy cerebellar (MSA-C) phenotype and spinocerebellar ataxias (SCAs) is challenging especially in the early stage. We assessed diagnostic value of brain magnetic resonance imaging (MRI) in differentiating MSA-C and SCAs based at different disease stages (<3, 3–7, and >7 years of disease duration). Overall, 186 patients with probable MSA-C and 117 with genetically confirmed SCAs were included. Hot cross bun (HCB) signs and middle cerebellar peduncle (MCP) hyperintensities were exclusively prevalent in MSA-C compared to SCAs at <3 years (HCB, 44.6% versus 0.9%; MCP hyperintensities, 38.3% versus 0.9%, respectively). Sensitivity, specificity, and positive predictive value (PPV) for HCB signs to differentiate MSA-C from SCAs were 45%, 99%, and 99% and those for MCP hyperintensities were 68%, 99%, and 99%, respectively; considering both HCB signs and MCP hyperintensities, specificity and PPV were 100%. However, the differential value of MRI signs decreased over time. MCP widths were smaller and showed more significant decrease in MSA-C than in SCAs. In conclusion, pontine and MCP changes were exclusively prominent in early stage MSA-C rather than in SCAs. Therefore, we should consider disease duration when interpreting pontine and MCP changes in brain MRIs, which will help better differentiate MSA-C and SCAs.