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Record W3216633520 · doi:10.1016/j.simyco.2021.100131

Trends in the molecular epidemiology and population genetics of emerging<i>Sporothrix</i>species

2021· article· en· W3216633520 on OpenAlexfundno aff
Thiago Nunes Roberto, Jamile Ambrósio de Carvalho, Mathew A. Beale, Ferry Hagen, Matthew C. Fisher, Rosane Christine Hahn, Zoilo Pires dè Camargo, Anderson Messias Rodrigues

Bibliographic record

VenueStudies in Mycology · 2021
Typearticle
Languageen
FieldMedicine
TopicFungal Infections and Studies
Canadian institutionsnot available
FundersConselho Nacional de Desenvolvimento Científico e TecnológicoFundação de Amparo à Pesquisa do Estado de São PauloCoordenação de Aperfeiçoamento de Pessoal de Nível SuperiorWellcome TrustMedical Research CouncilCanadian Institute for Advanced Research
KeywordsBiologyAmplified fragment length polymorphismParacoccidioidomycosisGeneticsPopulationParacoccidioidesGenetic diversityMicrobiology

Abstract

fetched live from OpenAlex

Paracoccidioidomycosis (PCM) is a life-threatening systemic fungal infection acquired after inhalation ofParacoccidioidespropagules from the environment. The main agents include members of theP. brasiliensiscomplex (phylogenetically-defined species S1, PS2, PS3, and PS4) andP. lutzii. DNA-sequencing of protein-coding loci (e.g.,GP43,ARF, andTUB1) is the reference method for recognizingParacoccidioidesspecies due to a lack of robust phenotypic markers. Thus, developing new molecular markers that are informative and cost-effective is key to providing quality information to explore genetic diversity withinParacoccidioides. We report using new amplified fragment length polymorphism (AFLP) markers and mating-type analysis for genotypingParacoccidioidesspecies. The bioinformatic analysis generated 144in silicoAFLP profiles, highlighting two discriminatory primer pairs combinations (#1 EcoRI-AC/MseI-CT and #2 EcoRI-AT/MseI-CT). The combinations #1 and #2 were usedin vitroto genotype 165Paracoccidioidesisolates recovered from across a vast area of South America. Considering the overall scored AFLP markersin vitro(67-87 fragments), the values of polymorphism information content (PIC= 0.3345-0.3456), marker index (MI= 0.0018), effective multiplex ratio (E= 44.6788-60.3818), resolving power (Rp= 22.3152-34.3152), discriminating power (D= 0.5183-0.5553), expected heterozygosity (H= 0.4247-0.4443), and mean heterozygosity (Havp = 0.00002-0.00004), demonstrated the utility of AFLP markers to speciateParacoccidioidesand to dissect both deep and fine-scale genetic structures. Analysis of molecular variance (AMOVA) revealed that the total genetic variance (65-66 %) was due to variability amongP. brasiliensiscomplex andP. lutzii(PhiPT = 0.651-0.658,P < 0.0001), supporting a highly structured population. Heterothallism was the exclusive mating strategy, and the distributions ofMAT1-1orMAT1-2idiomorphs were not significantly skewed (1:1 ratio) forP. brasiliensis s. str.(χ2= 1.025;P= 0.3113),P. venezuelensis(χ2= 0.692;P= 0.4054), andP. lutzii(χ2= 0.027;P= 0.8694), supporting random mating within each species. In contrast, skewed distributions were found forP. americana(χ2= 8.909;P= 0.0028) andP. restrepiensis(χ2= 4.571;P= 0.0325) with a preponderance ofMAT1-1. Geographical distributions confirmed thatP. americana,P. restrepiensis, andP. lutziiare more widespread than previously thought.P. brasiliensis s. str.is by far the most widely occurring lineage in Latin America countries, occurring in all regions of Brazil. Our new DNA fingerprint assay proved to be rapid, reproducible, and highly discriminatory, to give insights into the taxonomy, ecology, and epidemiology ofParacoccidioidesspecies, guiding disease-control strategies to mitigate PCM.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.089
GPT teacher head0.411
Teacher spread0.321 · 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 designObservational
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

Citations27
Published2021
Admission routes1
Has abstractyes

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