Biology subjects

Caro, E. A.

Publications and source records attributed to Caro, E. A..

4 recordsLinked to original sources

bioRxiv2026

Mitochondrial cardiolipin sequestration of caspofungin underlies Cryptococcus neoformans inherent resistance and may contribute to cardiotoxicity

Cryptococcus exhibits inherent resistance to the echinocandin, caspofungin, which inhibits the synthesis of (1,3)-{beta}-D-glucan, a key component of the polysaccharide cell wall. The essential FKS1 gene encodes the catalytic subunit of (1,3)-{beta}-D-glucan synthase and caspofungin effectively inhibits its activity in vitro, yet the drug remains ineffective against Cryptococcus, suggesting mechanisms beyond target insensitivity. The underlying mechanisms of caspofungin resistance remain unknown, although altered regulation of cell-wall remodeling genes, plasma membrane modifications, drug efflux pathways, and melanin biosynthesis have been suggested. Using boron dipyrromethene (BD-) and fluorescein (F-) labelled caspofungin, we demonstrate that caspofungin enters the cryptococcal cell and primarily accumulates in the mitochondrial inner membrane rather than the plasma membrane. We further establish that this mitochondrial accumulation is driven by a specific interaction between caspofungin and cardiolipin, a phospholipid found in mitochondrial membranes. We demonstrate that this unforeseen localization indicates that mitochondrial sequestration diminishes the effective drug concentrations at the intended target. Notably, the interaction between caspofungin and cardiolipin also takes place in human cells, establishing a mechanistic connection to caspofungin-related cardiotoxicity. Our findings reveal a previously unrecognized mechanism of echinocandin resistance in Cryptococcus and emphasize cardiolipin as an important factor in caspofungin effectiveness.

microbiology↗

bioRxiv2025

A Deep Learning Framework for Quantifying Dynamic Self-Organization in Myxococcus xanthus

Under starvation, Myxococcus xanthus bacteria initiate a multicellular developmental program in which cells move to form fruiting bodies and differentiate into distinct cell types. Many genes affecting this process have been identified, and it is assumed that perturbing genes within the same pathway induces similar changes in the phenotype, although those changes may be subtle or obscured by pleiotropic effects. However, these pathways cannot be systematically mapped, as there are no systematic methods for quantifying phenotype similarity. Here, we applied deep learning techniques to quantify the phenotype patterns and self-organization dynamics of 292 genetically distinct strains. By integrating ResNet and StyleGAN2 to construct a Variational AutoEncoder (VAE) and utilizing a Siamese network for phenotypic similarity metrics, we efficiently encoded high-resolution microscopy images into 13-dimensional feature vectors, capturing phenotypic variability in aggregation patterns across time and strains. Human evaluation confirmed that our models reconstructions were visually indistinguishable from real images and closely aligned with input phenotypes. Importantly, the feature space is interpretable: individual dimensions correlate with biological features such as aggregate number and size, and extrapolation along these dimensions produces predictable morphological changes. Remarkably, our model revealed that developmental phenotypes are predictable from the earliest stages before visible aggregate formation begins. This predictability held across both genetic and environmental sources of variation, suggesting fundamental constraints on developmental trajectories and indicating that subtle phenotypic variations carry important information. These results demonstrate how machine learning can reveal hidden structure in complex multicellular dynamics and provide scalable methods for phenotypic analysis without manual annotation.

systems biology↗

bioRxiv2023

Stochastic bounds of aggregation dynamics distinguish near-wild-type from wild-type strains in social bacteria

The genotype-to-phenotype problem (G2P) for multicellular development asks how genetic inputs control collective phenotypic outputs. It is a difficult problem even to observe. On the genotype side, the phenotypic impact of mutation is often subtle due at least partly to gene redundancy and myriad other factors. On the phenotype side, biological and even technical developmental replicates can display significant phenotypic variation due at least in part to stochasticity, again with other factors. We attempt to partially resolve the G2P inputs and outputs from the obfuscating effects of factors like redundancy and stochasticity. As a model organism, we selected the biofilm-forming species Myxococcus xanthus, a motile self-organizing bacterium that forms three-dimensional cell aggregates that grow and mature into spore-filled fruiting bodies when under starvation stress. We developed data acquisition tools and analysis and visualization methods that can produce a topological map of M. xanthus development. We demonstrate that even subtle effects on developmental dynamics caused by mutation can be identified, discriminated, characterized, and given statistical significance.

biophysics↗

bioRxiv2021

Unraveling a Bacterial Starvation Response Through the Direct Targets of a Starvation-Induced Transcriptional Activator

Organisms frequently encounter environments with nutrient shortages and their survival depends on changes in physiology and the ability to conserve resources. In bacteria, many physiological changes associated with starvation have been identified, but the underlying genetic components and regulatory networks that direct these physiological changes are often poorly defined. Here, we aimed to better define the gene regulatory networks that mediate the starvation response in Myxococcus xanthus, a bacterium that copes with starvation by producing fruiting bodies filled with dormant and stress-resistant spores. We focused on the direct promoter/gene targets of Nla28, a transcriptional activator/enhancer binding protein (EBP) that is important for early rounds of gene expression following starvation. Using expression profiling to identify genes that are downregulated in nla28 mutant cells and bioinformatics to identify the putative promoters of these genes, 12 potential promoter targets (37 genes) of Nla28 were identified. The results of in vitro promoter binding assays, coupled with in vitro and in vivo mutational analyses, suggested that the 12 promoters are in vivo targets of Nla28 and that Nla28 dimers use tandem, imperfect repeats of an 8-bp sequence for binding. Interestingly, nine of the Nla28 target promoters are intragenic, located in the protein coding sequence of an upstream gene or in the protein coding sequence of one gene within an operon (internal promoters). Based on mutational analyses, we concluded that the 12 Nla28 target loci contain at least one gene important for production of stress-resistant spores following starvation. Most of these loci contain genes predicted to be involved in regulatory or defense-related functions. Using the consensus Nla28 binding sequence, followed by bioinformatics and expression profiling, 58 additional promoters and 102 genes were tagged as potential Nla28 targets. Among these putative Nla28 targets, functions such as regulatory, metabolic and cell envelope biogenesis were commonly assigned to genes.

microbiology↗