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 and their proximity to urban development and runoffs from inland watersheds. The composition of the microbial communities was estimated using whole genome DNA shotgun sequencing with adjuvant measurements of chemical and environmental qualities. Although both sites exhibit a similar degree of richness, the less urbanized site (Maycocks reef at Hangman’s Bay) has a strong concentration of phototrophs whereas the more urbanized location (Bellairs reef at Folkstone) is enriched for copiotrophs, macroalgal symbionts and marine-related disease-bearing organisms from taxa scattered across the tree of life. Our results are concordant with previous profiles of warm ocean surface waters, suggesting our approach captures the state of each coral reef site, setting the stage for longitudinal studies of marine microbiome dynamics in Barbados.

Candida albicans, an opportunistic human pathogen, poses a significant threat to human health and is associated with significant socio-economic burden. Current antifungal treatments fail, at least in part, because C. albicans can initiate a strong drug tolerance response that allows some cells to grow at drug concentrations above their minimal inhibitory concentration. To better characterize this cytoprotective tolerance program at the molecular single-cell level, we used a nanoliter droplet-based transcriptomics platform to profile thousands of individual fungal cells and establish their subpopulation characteristics in the absence and presence of antifungal drugs. Profiles of untreated cells exhibit heterogeneous expression that correlates with cell cycle stage with distinct metabolic and stress responses. At 2 days post-fluconazole exposure (a time when tolerance is measurable), surviving cells bifurcate into two major subpopulations: one characterized by the upregulation of genes encoding ribosomal proteins, rRNA processing machinery, and mitochondrial cellular respiration capacity, termed the Ribo-dominant (Rd) state; and the other enriched for genes encoding stress responses and related processes, termed the Stress-dominant (Sd) state. This bifurcation persists at 3 and 6 days post-treatment. We provide evidence that the ribosome assembly stress response (RASTR) is activated in these subpopulations and may facilitate cell survival.

We present deep learning-based approaches for exploring the complex array of morphologies exhibited by the opportunistic human pathogen Candida albicans. Our system, entitled Candescence, automatically detects C. albicans cells from differential image contrast microscopy and labels each detected cell with one of nine morphologies. This ranges from yeast white and opaque forms to hyphal and pseudohyphal filamentous morphologies. The software is based upon a fully convolutional one-stage (FCOS) object detector, a deep learning technique that uses an extensive set of images that we manually annotated with the location and morphology of each cell. We developed a novel cumulative curriculum-based learning strategy that stratifies our images by difficulty from simple yeast forms to complex filamentous architectures. Candescence achieves very good performance (~85% recall; 81% precision) on this difficult learning set, where some images contain hundreds of cells with substantial intermixing between the predicted classes. To capture the essence of each C. albicans morphology and how they intermix, we used a second technique from deep learning entitled generative adversarial networks. The resultant models allow us to identify and explore technical variables, developmental trajectories, and morphological switches. Importantly, the model allows us to quantitatively capture morphological plasticity observed with genetically modified strains or strains grown in different media and environments. We envision Candescence as a community meeting point for quantitative explorations of C. albicans morphology. IMPORTANCE The fungus Candida albicans can "shape shift" between 12 morphologies in response to environmental variables. The cytoprotective capacity provided by this polymorphism makes C. albicans a formidable pathogen to treat clinically. Microscopy images of C. albicans colonies can contain hundreds of cells in different morphological states. Manual annotation of images can be difficult, especially as a result of densely packed and filamentous colonies and of technical artifacts from the microscopy itself. Manual annotation is inherently subjective, depending on the experience and opinion of annotators. Here, we built a deep learning approach entitled Candescence to parse images in an automated, quantitative, and objective fashion: each cell in an image is located and labeled with its morphology. Candescence effectively replaces simple rules based on visual phenotypes (size, shape, and shading) with neural circuitry capable of capturing subtle but salient features in images that may be too complex for human annotators.

Background For Candida albicans and Candidiasis, drug resistance is sometimes due to the pre-existence of genetic polymorphisms that bypass the mode of action of the drug, thus conferring a long-term survival benefit. In other cases, resistance is acquired via the evolution of de novo genetic polymorphisms. There is evidence that C. albicans possess a drug tolerance response which “buys time” for individuals to evolve beneficial mutations. Our goal here is to characterize this poorly understood epigenetic cytoprotective program at the single cell molecular level. Methods We developed a nano-litre droplet based Candida single cell sequencing platform capable of transcriptionally profiling several thousand individual cells in an efficient manner. We exploit this platform to profile both untreated and drug exposed (incl. fluconazole, caspofungin and nystatin) populations at early time points post-treatment (tolerance) and late time points (resistance) in order to understand survival trajectories. The profile are compared with the matched sequenced genomes. Results We show that untreated Candida populations exhibit “bet hedging”, stochastically expressing cytoprotective transcriptional programs, and drug tolerant individuals partition into distinct subpopulations, each with a unique survival strategy involving different transcriptional programs. We observe a burst of chromosomal aberrations at two days post-treatment that differ between survivor subpopulation. Discussion Our single cell approach highlights that survivor subpopulations pass through a tolerance phase that involves a multivariate transcriptional response including upregulation of efflux pumps, chaperones and transport mechanisms, and cell wall maintenance. Together this suggests that targeting the tolerance response concomitantly with standard therapies could represent an efficient approach to ablating clinical persistence.

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.