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Record W3138796413 · doi:10.21203/rs.3.rs-267999/v1

Genetic and chemical methods of ascertaining aflatoxigenicity give discordant results: A Case of Aspergillus species from Eastern Kenya

2021· preprint· en· W3138796413 on OpenAlexfundno aff
Micah Kipkemboi Lagat, Faith Jebet Toroitich, Huxley Mae Makonde, Meshack Amos Obonyo

Bibliographic record

VenueResearch Square · 2021
Typepreprint
Languageen
FieldAgricultural and Biological Sciences
TopicMycotoxins in Agriculture and Food
Canadian institutionsnot available
FundersGrand Challenges Canada
KeywordsAflatoxinAspergillus flavusBiologyAspergillus parasiticusGeneInternal transcribed spacerAspergillusMycotoxinChemotypeGeneticsMicrobiologyBotanyBiotechnologyRibosomal RNA

Abstract

fetched live from OpenAlex

Abstract Background: Aflatoxins (AFs) are poisonous compounds produced by species of fungi belonging to the genus Aspergillus mainly A. flavus and A. parasiticus. However, there are some members of these species that do not produce toxins and have since become of interest for use in Biological Control programs. The species that produce AFs are believed to have clusters of aflatoxin-associated genes that confer aflatoxigenicity. However, recent findings suggest that the presence of aflatoxin genes may not imply aflatoxin production capability. We therefore examined the extent to which the presence or absence of aflatoxin-associated genes (genetic) infers aflatoxigenicity using the Dichlorvos-Ammonia (chemical) method as reference.Results: We report a dissonance between the genetic and chemical methods of ascertaining aflatoxigenicity. Fungi (n = 314) that were morphologically identified as A. flavus and A. parasiticus were isolated from maize kernels and soil from Eastern Kenya. The fungi were further characterized to confirm their identities using a PCR-sequence analysis of the internal transcribed spacer (ITS) region of rDNA which confirmed them to be Aspergillus species. We selected and induced 16 isolates in YES media amended with Dichlorvos to produce AFs. Seven of the sixteen isolates were DM-AM positive (aflatoxigenic) but lacked at least one of the key aflatoxin-associated genes. Even more confounding, A. flavus isolate (1EM2606) had all aflatoxin-associated genes but was non-aflatoxigenic (DV-AM negative) while A. flavus (1EM1901) having all genes was aflatoxigenic (DV-AM positive). The genetic abundance of the AF-asscociated genes among the isolates was as follows: aflQ (100%), aflD (62.5%) followed by aflR (37.5%) and aflP (25%). Conclusion: We report that either method alone is limited in ascertaining aflatoxigenicity among Aspergillus section Flavi. The discordance between presence of aflatoxin-associated genes and aflatoxigenicity may be due to epigenetic factors that affect secondary metabolism, or even other signaling processes that alter toxin production that still remain poorly understood.

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)0.004
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 score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.089
GPT teacher head0.374
Teacher spread0.285 · 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

Citations1
Published2021
Admission routes1
Has abstractyes

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