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Bettauer, V.

Publications and source records attributed to Bettauer, V..

4 recordsLinked to original sources

Candida albicans exhibits heterogeneous and adaptive cytoprotective responses to anti-fungal compounds

Candida albicans is an opportunistic human pathogen which represents a significant threat to human health and is associated with substantial socio-economic burden. Current antifungal treatments fail at least in part because C. albicans can initiate a strong drug tolerance response, allowing cells to grow at concentrations above their minimal inhibitory concentration. Our goal is to better characterize this cytoprotective tolerance program at the molecular single cell level. We present here a nano-liter droplet-based fungal single cell transcriptomics platform capable of profiling thousands of individual C. albicans SC5314 cells in an efficient manner. Profiles of untreated cells partition into three transcriptional clusters with each highlighting a cell cycle checkpoint coupled with specific metabolic and stress responses, as perhaps expected. After just two days post-treatment with fluconazole, surviving cells bifurcate into two distinct subpopulations: the so-called response involving upregulation of protein translation, rRNA processing and mitochondrial cellular respiration, and the {beta} response involving processes and stress responses that assist damaged cells. By extending our time series to six days and profiling with other antifungals and bioactive compounds, we provide evidence that surviving cells transition from the to {beta} responses mediated by the Ribosome Assembly Stress Response (RASTR).

microbiology↗

A deep learning approach to capture the essence of Candida albicans morphologies

We present deep learning-based approaches for exploring the complex array of morphologies exhibited by the opportunistic human pathogen C. albicans. Our system entitled Candescence automatically detects C. albicans cells from Differential Image Contrast microscopy, and labels each detected cell with one of nine vegetative, mating-competent or filamentous morphologies. The software is based upon a fully convolutional one-stage object detector and exploits a novel cumulative curriculum-based learning strategy that stratifies our images by difficulty from simple vegetative forms to more complex filamentous architectures. Candescence achieves very good performance on this difficult learning set which has substantial intermixing between the predicted classes. To capture the essence of each C. albicans morphology, we develop models using generative adversarial networks and identify subcomponents of the latent space which control technical variables, developmental trajectories or morphological switches. We envision Candescence as a community meeting point for quantitative explorations of C. albicans morphology.

microbiology↗

A metagenomic-based stufy of two sites from the Barbadian reef system

We study the microbiome of sea water collected from two locations of the Barbadian coral reefs. The two sites differ in several environmental and ecological variables including their endogenous benthic community in addition to their proximity to urban development and runoffs from inland watersheds. The composition of the microbial community was estimated using whole genome DNA shotgun sequencing. Although both sites exhibit a similar degree of richness, the less urbanized site (Maycocks reef at Hangmans Bay) is strongly concentrated with phototrophs. In comparison, the more urbanized location (Bellairs Research Institute) is enriched for copiotrophs, macroalgal symbionts and marine-related disease-bearing organisms from taxa scattered across the tree of life. Overall, our samples and associated measurements of chemical and environmental qualities of the water are in line with previous marine microbiome profiles of warm ocean surface waters. This suggests our approach captures salient information regarding the state of each coral reef site and sets the stage for larger longitudinal studies of coral reef dynamics in Barbados.

microbiology↗

Candida albicans exhibits distinct cytoprotective responses to anti-fungal drugs that facilitate the evolution of drug resistance

We developed a modified protocol for nanolitre droplet-based single cell sequencing appropriate for fungal settings, and used it to transcriptionally profiled several thousands cells from a prototrophic Candida albicans population and several drug exposed colonies (incl. fluconazole, caspofungin and nystatin). Thousands of cells from each colony were profiled both at early and late time points post-treatment in order to infer survival trajectories from initial drug tolerance to drug resistance. We find that prototrophic C. albicans populations differentially and stochastically express cytoprotective epigenetic programs. For all drugs, there is evidence that tolerant individuals partition into distinct subpopulations, each with a unique survival strategy involving different regulatory programs. These responses are weakly related to changes in morphology (shift from white to opaque forms, or shift from yeast to filamentous forms). In turn, those subpopulations that successfully reach resistance each have a distinct multivariate epigenetic response that coordinates the expression of efflux pumps, chaperones, transport mechanisms, and cell wall maintenance. Live cell fluorescent imaging was used to validate predictions of which molecular responses most often led to survival after drug exposure. Together our findings provide evidence that C. albicans has a robust toolkit of short-term epigenetic cytoprotective responses designed to "buy time" and increase the chance of acquiring long-term resistance.

genomics↗