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Turcotte, B.

Publications and source records attributed to Turcotte, B..

3 recordsLinked to original sources

Mitochondrial defects result in decreased susceptibility to echinocandins via the transcriptional regulator Pdr1 in Candida glabrata.

In the human fungal pathogen Candida glabrata, the transcription factor Pdr1 controls the expression of genes encoding drug efflux pumps such as Cdr1. Pdr1 also controls its own expression by binding to pleiotropic drug responsive elements (PDREs) located in its promoter. Increased resistance to the antifungal drugs azoles (e.g. fluconazole) is often due to gain-of-function mutations in PDR1 that render the factor hyperactive. Mitochondrial defects also result in increased resistance to azoles via Pdr1. Resistance to another class of antifungals, the echinocandins (e.g. micafungin), is generally due to mutations in the FKS1 and FKS2 genes that encode the catalytic subunit of 1,3-beta-D-glucan synthase, the echinocandin target. We have observed that mitochondrial defects also result in increased resistance to echinocandins and we have shown that this process is mediated by Pdr1. Mitochondrial defects result in increased levels of PDR1 mRNA. Overexpression of PDR1 by replacing its native promoter by the strong ADH1 promoter resulted in increased resistance to micafungin. However, mutations in PDR1 that decrease susceptibility to azoles generally have modest effects on echinocandin resistance. We randomly mutagenized the PDR1 gene and screened for mutants with altered resistance to micafungin. Single amino acid changes downstream of the DNA binding domain result in preferential resistance to micafungin as compared to fluconazole. We also show that auto-regulation of PDR1 expression is necessary for resistance to micafungin. One PDR1 mutant showed over 15-fold increased promoter activity in a PDRE-dependent manner. In summary, we have identified a novel role for the transcriptional regulator Pdr1.

microbiology↗

Development of AI-assisted microscopy frameworks through realistic simulation in pySTED

The integration of artificial intelligence (AI) into microscopy systems significantly enhances performance, optimizing both the image acquisition and analysis phases. Development of AI-assisted super-resolution microscopy is often limited by the access to large biological datasets, as well as by the difficulties to benchmark and compare approaches on heterogeneous samples. We demonstrate the benefits of a realistic STED simulation platform, pySTED, for the development and deployment of AI-strategies for super-resolution microscopy. The simulation environment provided by pySTED allows the augmentation of data for the training of deep neural networks, the development of online optimization strategies, and the training of reinforcement learning models, that can be deployed successfully on a real microscope.

bioinformatics↗

A SKI subcomplex specifically required for the degradation of ribosome-free RNA regions

The Ski2-Ski3-Ski8 (SKI) complex assists the RNA exosome during the 3-5 degradation of cytoplasmic transcripts. Previous reports showed that the SKI complex is involved in the 3-5 degradation of mRNA, including 3 untranslated regions (UTRs), devoid of ribosomes. Paradoxically, we recently showed that the SKI complex directly interacts with ribosomes during the co-translational mRNA decay and that this interaction is necessary for its RNA degradation promoting activity. Here, we characterized a new SKI-associated factor, Ska1, which antagonizes the SKI-ribosome interaction. We showed that the SKI-Ska1-subcomplex is specifically involved in the degradation of ribosome-free RNA regions such as long mRNA 3UTRs and cytoplasmic lncRNAs. We propose a model in which the SKI-exosome complex first targets ribosome-free RNA 3ends in its Ska1-associated form. When the complex reaches the mRNA coding sequence, the Ska1-SKI-exosome complex is exchanged for the SKI-exosome, which interacts directly with ribosomes in order to resume the degradation process.

molecular biology↗