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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 of Paracoccidioides propagules from the environment. The main agents include members of the P. brasiliensis complex (phylogenetically-defined species S1, PS2, PS3, and PS4) and P. lutzii . DNA-sequencing of protein-coding loci (e.g., GP43 , ARF , and TUB1 ) is the reference method for recognizing Paracoccidioides species 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 within Paracoccidioides . We report using new amplified fragment length polymorphism (AFLP) markers and mating-type analysis for genotyping Paracoccidioides species. The bioinformatic analysis generated 144 in silico AFLP profiles, highlighting two discriminatory primer pairs combinations (#1 EcoRI-AC/MseI-CT and #2 EcoRI-AT/MseI-CT). The combinations #1 and #2 were used in vitro to genotype 165 Paracoccidioides isolates recovered from across a vast area of South America. Considering the overall scored AFLP markers in 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 ( H &lt;inf&gt; avp &lt;/inf&gt; = 0.00002-0.00004), demonstrated the utility of AFLP markers to speciate Paracoccidioides and 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 among P. brasiliensis complex and P. lutzii (PhiPT = 0.651-0.658, P &lt; 0.0001), supporting a highly structured population. Heterothallism was the exclusive mating strategy, and the distributions of MAT1-1 or MAT1-2 idiomorphs were not significantly skewed (1:1 ratio) for P. brasiliensis s. str. (χ 2 = 1.025; P = 0.3113), P. venezuelensis (χ 2 = 0.692; P = 0.4054), and P. lutzii (χ 2 = 0.027; P = 0.8694), supporting random mating within each species. In contrast, skewed distributions were found for P. americana (χ 2 = 8.909; P = 0.0028) and P. restrepiensis (χ 2 = 4.571; P = 0.0325) with a preponderance of MAT1-1 . Geographical distributions confirmed that P. americana , P. restrepiensis , and P. lutzii are 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 of Paracoccidioides species, 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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.044
Threshold uncertainty score0.246

Codex and Gemma teacher scores by category

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

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 teacher head, 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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