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Record W3106668659 · doi:10.1101/2020.11.30.405712

Balancing positive and negative selection: <i>in vivo</i> evolution of <i>Candida lusitaniae MRR1</i>

2020· preprint· en· W3106668659 on OpenAlexfundno aff
Elora G. Demers, Jason Stajich, Alix Ashare, Patricia Occhipinti, Deborah A. Hogan

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2020
Typepreprint
Languageen
FieldMedicine
TopicAntifungal resistance and susceptibility
Canadian institutionsnot available
FundersJulius-Maximilians-Universität WürzburgDartmouth CollegeNational Institute of General Medical SciencesCanadian Institute for Advanced ResearchCystic Fibrosis FoundationNational Cancer InstituteNational Institutes of HealthNational Science Foundation
KeywordsBiologyPopulationAlleleVirulenceGeneticsDrug resistanceFluconazoleMicrobiologyGeneAntifungal

Abstract

fetched live from OpenAlex

Abstract The evolution of pathogens in response to selective pressures present during chronic infections can influence persistence, virulence, and the outcomes of antimicrobial therapy. Because subpopulations within an infection can be spatially separated and the host environment can fluctuate, an appreciation of the pathways under selection may be most easily revealed through the analysis of numerous isolates from single infections. Here, we continued our analysis of a set of clonally-derived Clavispora (Candida) lusitaniae isolates from a single chronic lung infection with a striking enrichment in the number of alleles of MRR1 . Genetic and genomic analyses found evidence for repeated acquisition of gain-of-function mutations that conferred constitutive Mrr1 activity. In the same population, there were multiple alleles with both gain-of-function mutations and secondary suppressor mutations that either attenuated or abolished the constitutive activity suggesting the presence of counteracting selective pressures. Our studies demonstrated tradeoffs between high Mrr1 activity, which confers resistance to the antifungal fluconazole, host factors, and bacterial products through its regulation of MDR1 , and resistance to hydrogen peroxide, a reactive oxygen species produced in the neutrophilic environment associated with this infection. This inverse correlation between high Mrr1 activity and hydrogen peroxide resistance was observed in multiple Candida species and in serial analysis of populations from this individual collected over three years. These data lead us to propose that dynamic or variable selective pressures can be reflected in population genomics and that these dynamics can complicate the drug resistance profile of the population. Importance Understanding microbial evolution within patients is critical for managing chronic infections and understanding host-pathogen interactions. Here, our analysis of multiple MRR1 alleles in isolates from a single Clavispora (Candida) lusitaniae infection revealed the selection for both high and low Mrr1 activity. Our studies reveal tradeoffs between high Mrr1 activity, which confers resistance to the commonly used antifungal fluconazole, host antimicrobial peptides and bacterial products, and resistance to hydrogen peroxide. This work suggests that spatial or temporal differences within chronic infections can support a large amount of dynamic and parallel evolution, and that Mrr1 activity is under both positive and negative selective pressure to balance different traits that are important for microbial survival.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.008
GPT teacher head0.222
Teacher spread0.213 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2020
Admission routes1
Has abstractyes

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