Khaledi, A. | Search bioRxiv

bioRxiv2022

Constitutive production of flagellar proteins is required for proper flagellation in Shewanella putrefaciens

Flagella are multiprotein complexes whose assembly and positioning requires complex spatiotemporal control. Flagellar assembly is thought to be controlled by several transcriptional tiers, which is mediated through various master regulators. Here, we revisited the regulation of flagellar genes in polarly flagellated gammaproteobacteria by the regulators FlrA, RpoN ({sigma}54) and FliA ({sigma}28) in Shewanella putrefaciens CN-32 at the transcript and protein level. As expected, strict control at both levels occurred for for highly abundant flagellar proteins, including the building blocks for the outer rings, rod, hook and filament. In contrast, a number of regulatory and structural proteins were always present also in the absence of the main regulators. Initiation of flagella assembly and motor activation likely relies on the abundance control of only few structural key components required for formation of the MS- and C-ring and the flagellar type III secrection system. We identified {sigma}70-dependent promoters driving constitutive expression of some flagellar genes including the regulators of flagellar number and positioning, FlhF and FlhG. Reduction of the constitutive expression levels resulted in emergence of hyperflagellation. Thus, basal expression and presence of flagellar proteins is required for proper flagellation, which adds a deeper layer to the regulation of flagellar synthesis and assembly. SignificanceThe tier-based transcriptional regulation underlying bacterial flagella synthesis is - with certain variations - well-established in various species. Here we show that initiation and proceeding of flagellar synthesis can be simply based on the control of some key components and highly abundant building blocks. We further identified a 'tier zero, a set of constitutively produced flagellar regulators and building blocks, which is required, for example, to maintain the flagellar counter. We expect this not only to apply to our model species Shewanella, but also to other flagella regulation systems in bacteria.

microbiology↗

bioRxiv2019

Fighting antimicrobial resistance in Pseudomonas aeruginosa with machine learning-enabled molecular diagnostics

The growing importance of antibiotic resistance on clinical outcomes and cost of care underscores the need for optimization of current diagnostics. For a number of bacterial species antimicrobial resistance can be unambiguously predicted based on their genome sequence. In this study, we sequenced the genomes and transcriptomes of 414 drug-resistant clinical Pseudomonas aeruginosa isolates. By training machine learning classifiers on information about the presence or absence of genes, their sequence variation, and gene expression profiles, we generated predictive models and identified biomarkers of susceptibility or resistance to four commonly administered antimicrobial drugs. Using these data types alone or in combination resulted in high (0.8-0.9) or very high (>0.9) sensitivity and predictive values, where the relative contribution of the different categories of biomarkers strongly depended on the antibiotic. For all drugs except for ciprofloxacin, gene expression information substantially improved diagnostic performance. Our results pave the way for the development of a molecular resistance profiling tool that reliably predicts antimicrobial susceptibility based on genomic and transcriptomic markers. The implementation of a molecular susceptibility test system in routine clinical microbiology diagnostics holds promise to provide earlier and more detailed information on antibiotic resistance profiles of bacterial pathogens and thus could change how physicians treat bacterial infections.

microbiology↗