Metal Chelation as a Powerful Strategy to Probe Cellular Circuitry Governing Fungal Drug Resistance and Morphogenesis
Bibliographic record
Abstract
Fungal pathogens have evolved diverse strategies to sense host-relevant cues and coordinate cellular responses, which enable virulence and drug resistance. Defining circuitry controlling these traits opens new opportunities for chemical diversity in therapeutics, as the cognate inhibitors are rarely explored by conventional screening approaches. This has great potential to address the pressing need for new therapeutic strategies for invasive fungal infections, which have a staggering impact on human health. To explore this approach, we focused on a leading human fungal pathogen, Candida albicans, and screened 1,280 pharmacologically active compounds to identify those that potentiate the activity of echinocandins, which are front-line therapeutics that target fungal cell wall synthesis. We identified 19 compounds that enhance activity of the echinocandin caspofungin against an echinocandin-resistant clinical isolate, with the broad-spectrum chelator DTPA demonstrating the greatest synergistic activity. We found that DTPA increases susceptibility to echinocandins via chelation of magnesium. Whole genome sequencing of mutants resistant to the combination of DTPA and caspofungin identified mutations in the histidine kinase gene NIK1 that confer resistance to the combination. Functional analyses demonstrated that DTPA activates the mitogen-activated protein kinase Hog1, and that NIK1 mutations block Hog1 activation in response to both caspofungin and DTPA. The combination has therapeutic relevance as DTPA enhanced the efficacy of caspofungin in a mouse model of echinocandin-resistant candidiasis. We found that DTPA not only reduces drug resistance but also modulates morphogenesis, a key virulence trait that is normally regulated by environmental cues. DTPA induced filamentation via depletion of zinc, in a manner that is contingent upon Ras1-PKA signaling, as well as the transcription factors Brg1 and Rob1. Thus, we establish a new mechanism by which metal chelation modulates morphogenetic circuitry and echinocandin resistance, and illuminate a novel facet to metal homeostasis at the host-pathogen interface, with broad therapeutic potential.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".