Caboche, S. | bioRxiv Science

bioRxiv2023

The panC-encoded pantothenate synthetase to tackle carbapenem-resistant OprD Pseudomonas aeruginosa mutant revealed through Tn-Seq

For the World Health Organization, carbapenem-resistant Pseudomonas aeruginosa is a critical priority for which new antimicrobial drugs are needed. Consequently, understanding the underlying mechanisms of resistant bacteria infection will enable the identification of new therapeutic targets. Loss of the OprD porin is the main determinant of resistance to the last resort carbapenem antibiotics and has been described to enhance fitness in vivo and virulence. Transposon sequencing is a high-throughput sequencing technique that makes it possible to identify essential genes (EGs) that may turn out to be therapeutic targets. However, such a strategy has not yet been used for OprD-deficient P. aeruginosa. In this study, we identified the EGs specific to PA14 OprD mutant for LB growth and we established a list of 30 EGs among these, we highlighted the panC gene encoding pantothenate synthetase as a promising target. Using CRISPRi, we confirmed that silencing panC reduced LB growth, and decreased sigX expression, whose overexpression is associated with membrane fluidity, as well as the expression of genes involved in the fatty acid synthesis (FAS). Taking into account the weakness of PA14 OprD mutant due to an altered membrane consecutive to a decrease in unsaturated FAS in the absence of panC, we showed that silencing panC extended the destruction time of 16HBE airway cells. Overall, our findings highlighted the anti-virulence potential of panC inhibition and shed new light on its inhibition as a target for treating carbapenem-resistant OprD-defective PA lung infections.

microbiology↗

bioRxiv2018

Comparative assessment of long-read error-correction software applied to RNA-sequencing data

MotivationLong-read sequencing technologies offer promising alternatives to high-throughput short read sequencing, especially in the context of RNA-sequencing. However these technologies are currently hindered by high error rates that affect analyses such as the identification of isoforms, exon boundaries, open reading frames, and the creation of gene catalogues. Due to the novelty of such data, computational methods are still actively being developed and options for the error-correction of RNA-sequencing long reads remain limited.\n\nResultsIn this article, we evaluate the extent to which existing long-read DNA error correction methods are capable of correcting cDNA Nanopore reads. We provide an automatic and extensive benchmark tool that not only reports classical error-correction metrics but also the effect of correction on gene families, isoform diversity, bias toward the major isoform, and splice site detection. We find that long read error-correction tools that were originally developed for DNA are also suitable for the correction of RNA-sequencing data, especially in terms of increasing base-pair accuracy. Yet investigators should be warned that the correction process perturbs gene family sizes and isoform diversity. This work provides guidelines on which (or whether) error-correction tools should be used, depending on the application type.\n\nBenchmarking softwarehttps://gitlab.com/leoisl/LR_EC_analyser

bioinformatics↗