Biology subjects

Bedard, C.

Publications and source records attributed to Bedard, C..

6 recordsLinked to original sources

bioRxiv2026

Population genomics of Candida albicans reveals genetic footprints that allow the prediction of antifungal resistance

Rapid detection of drug resistance in fungi is becoming increasingly urgent. While multiple loci and mutations were linked to antifungal resistance in Candida albicans, the utility of whole genome sequencing in predicting resistance has not been tested thoroughly. We address this by integrating more than 1000 C. albicans genomes, with associated resistance phenotypes to six antifungals, a curated repository of resistance-causing mutations and variant effect predictors. We used Genome Wide Association Studies and Machine Learning approaches to associate genetic variants to resistance phenotypes. We found that well curated databases like FungAMR are able to accurately identify markers predictive antifungal resistance. Curated mutations were detected in 56 to 74% of isolates with reduced azole susceptibility and 57 to 90% of those with reduced echinocandin susceptibility, revealing incomplete coverage of resistance across both drug classes. Complementary variant- and gene-level association analyses recovered established resistance determinants and uncovered additional candidate loci, whereas copy-number changes provided limited independent explanatory power. Genomic prediction declined when genetic backgrounds were absent from training, and when leading predictive features differed among backgrounds. We also found that models trained on a curated list of mutations and variant effect predictors performed well when classifying drug-susceptible strains, but the drug-resistance trait was predicted with lower accuracy. These findings support the potential of genome-based resistance prediction while highlighting the need for broader population sampling, functional validation of candidate variants and expanded resistance catalogues to improve prediction across genetic backgrounds.

microbiology↗

bioRxiv2026

A heterologous expression system allows rapid testing and discovery of resistance-conferring mutations from multiple pathogenic fungi

To face the fungal infections that affect millions of people every year, a better understanding of resistance-conferring mutations is necessary. One obstacle is the considerable time and effort necessary to construct point mutations in pathogenic species, which is required to validate their role in resistance. To overcome this problem, we have constructed a series of heterologous expression plasmids that allow expression of the ERG3, ERG6 and ERG11 orthologs from Candida albicans, Candidozyma auris, Nakaseomyces glabratus, Candida parapsilosis, Candida tropicalis, and the CYP51A and CYP51B genes of Aspergillus fumigatus. All orthologs are codon-optimized and synthesized for expression in the budding yeast Saccharomyces cerevisiae. We also constructed host strains in which the native ERG genes are either deleted or under the control of a repressible promoter. We showed that all orthologs complement the function of the native genes when expressed from the S. cerevisiae native promoters. We recreated previously reported resistance-conferring mutations, and showed that expression in S. cerevisiae replicates known resistance phenotypes. We then used the system to test corresponding mutations across orthologs, and showed that most resistance phenotypes are conserved. The heterologous expression system allows rapid construction of mutants, by taking advantage of the abundant genetic tools available for S. cerevisiae. Screening of mutants can be done within a few experimental steps, greatly increasing the throughput compared to the introduction of mutations in pathogenic fungi. As a proof-of-concept, we used the system to discover new resistance-conferring mutations, using random mutagenesis. All plasmids are made publicly available.

microbiology↗

bioRxiv2024

FungAMR: A comprehensive portrait of antimicrobial resistance mutations in fungi

Antimicrobial resistance (AMR) is a global threat. To optimize the use of our antifungal arsenal, we need rapid detection and monitoring tools that rely on high-quality AMR mutation data. Here, we performed a thorough manual curation of published AMR mutations in fungal pathogens to produce the FungAMR reference dataset. A total of 501 papers were curated, leading to 35,792 mutation entries all classified with the degree of evidence that supports their role in resistance. FungAMR covers 95 species, 246 genes and 208 drugs. We combined variant effect predictors with FungAMR resistance mutations and showed that these tools could be used to help predict the potential impact of mutations on AMR. Additionally, a comparative analysis among species revealed a high level of convergence in the molecular basis of resistance, highlighting some potentially universal resistance mutations. The analysis also showed that a significant number of resistance mutations lead to cross-resistance within antifungals of a class, as well as between classes for certain mutated genes. The acquisition of fungal resistance in the clinic and the field is an urging concern. Finally, we provide a computational tool, ChroQueTas, that leverages FungAMR to screen fungal genomes for AMR mutations. These resources are anticipated to have great utility for researchers in the fight against antifungal resistance.

microbiology↗

bioRxiv2023

Most azole antifungal resistance mutations in the drug target provide cross-resistance and carry no intrinsic fitness cost

Azole antifungals are among the most frequently used drugs to treat fungal infections. Amino acid substitutions in and around the binding site of the azole target Erg11 (Cyp51) are a common resistance mechanism in pathogenic yeasts such as Candida albicans. How many and which mutations confer resistance, and at what cost, is however largely unknown. Here, we measure the impact of nearly 4,000 amino acid variants of the Erg11 ligand binding pocket on the susceptibility to six medical azoles. We find that a large fraction of amino acid substitutions lead to resistance (33%), most resistance mutations confer cross-resistance to two or more azoles (88%) and most importantly, only a handful of resistance mutations show a significant fitness cost in the absence of drug (9%). Our results reveal that resistance to azoles can arise through a large set of mutations and this will likely lead to azole pan-resistance, with very little evolutionary compromise. Such a resource will help inform treatment choices in clinical settings and guide the development of new drugs.

microbiology↗

bioRxiv2022

Evolutionary trajectories are contingent on mitonuclear interactions

Critical mitochondrial functions, including cellular respiration, rely on frequently interacting components expressed from both the mitochondrial and nuclear genomes. The fitness of eukaryotic organisms depends on a tight collaboration between both genomes. In the face of an elevated rate of evolution in the mitochondrial genome, current models predict that maintenance of mitonuclear compatibility relies on compensatory evolution of the nuclear genome. Mitonuclear interactions would therefore exert an influence on evolutionary trajectories. One prediction from this model is that the same nuclear genomes but evolving with different mitochondrial haplotypes would follow distinct molecular paths towards higher fitness peaks. To test this prediction, we submitted 1344 populations derived from seven mitonuclear genotypes of Saccharomyces cerevisiae to more than 300 generations of experimental evolution in conditions that either select for a mitochondrial function, or that do not strictly require respiration for survival. Performing high-throughput phenotyping and whole-genome sequencing on independently evolved individuals isolated from endpoint populations, we identified numerous examples of gene-level evolutionary convergence among populations with the same mitonuclear background. Phenotypic and genotypic data on strains derived from this evolution experiment identify the nuclear genome and the environment as the main determinants of evolutionary divergence, but also show a modulating role for the mitochondrial genome exerted both directly and via interactions with the two other components. We finally recapitulated a subset of prominent loss-of-function alleles in the ancestral backgrounds and confirmed a generalized pattern of mitonuclear-specific and highly epistatic fitness effects. Together, these results demonstrate how mitonuclear interactions can dictate evolutionary divergence of populations with identical starting nuclear genotypes.

evolutionary biology↗

bioRxiv2021

Extracellular and intracellular components of theimpedance of neural tissue

Electric phenomena in brain tissue can be measured using extracellular potentials, such as the local field potential, or the electro-encephalogram. The interpretation of these signals depend on the electric structure and properties of extracellular media, but the measurements of these electric properties are still debated. Some measurements point to a model where the extracellular medium is purely resistive, and thus parameters such as electric conductivity and permittivity should be independent of frequency. Other measurements point to a pronounced frequency dependence of these parameters, with scaling laws that are consistent with capacitive or diffusive effects. However, these experiments correspond to different preparations, and it is unclear how to correctly compare them. Here, we provide for the first time, impedance measurements (in the 1-10 KHz frequency range) using the same set-up in various preparations, from primary cell cultures to acute brain slices, with a comparison with similar measurements performed in artificial cerebrospinal fluid with no biological material. The measurements show that when the current flows across a cell membrane, the frequency dependence of the macroscopic impedance between intracellular and extracellular electrodes is significant, and cannot be captured by a model with resistive media. Fitting a mean-field model to the data shows that this frequency dependence could be explained by the ionic diffusion mainly associated to Debye layers surrounding the membranes. We conclude that neuronal membranes and their ionic environment induce strong deviations to resistivity, that should be taken into account to correctly interpret extracellular potentials generated by neurons. SignificanceThe electro-encephalogram recorded at the scalp surface and local-field potentials recorded within neural tissue are generated by electric currents in neurons, and thus depend on the impedance of neural tissue. Different measured values were proposed, and it is currently unclear what is the real impedance of neural tissue. Here, we show that the impedance depends on the measurement technique. If the measurement is exclusively extracellular, the system appears as equivalent to a simple resistor. However, if the measurement includes an intracellular electrode, a more complex impedance is observed, because the current has to flow through the membrane, as happening in the brain. Thus, we provide an explanation for apparent disagreements, and indicate in which cases each impedance should be used.

neuroscience↗