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Metagenomic insights into cyanotoxin dynamics in a Mexican subtropical lake

2025· article· en· W4408253443 on OpenAlexafffund
Nicolas Tromas, Dana F. Simon, Nathalie Fortin, Miriam Hernández‐Zamora, Autumn Pereira, Alberto Mazza, Marie-Josée Levesque, Laura Martínez-Jerónimo, Paloma Antuna-González, Gabriel Munoz, B. Jesse Shapiro, Sébastien Sauvé, Fernando Martı́nez-Jerónimo

Bibliographic record

VenueChemosphere · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicAquatic Ecosystems and Phytoplankton Dynamics
Canadian institutionsMcGill UniversityNational Research Council CanadaUniversité de Montréal
FundersFonds de recherche du QuébecConsejo Nacional de Ciencia y TecnologíaGenome Canada
KeywordsCyanotoxinSubtropicsMetagenomicsEnvironmental scienceBiologyEcologyCyanobacteriaGeneticsBacteria

Abstract

fetched live from OpenAlex

Valle de Bravo is a vital water supply for part of the metropolitan area of the Valle de Mexico megacity, providing 30% of Mexico City's water demand. This water body has experienced an acceleration in its trophic status, going from oligotrophic to eutrophic in just a few years. This temperate lake (at a tropical latitude) is in a persistent bloom dominated by a variety of co-occurring cyanobacteria, many of which have toxigenic potential based on microscopic identification, that makes it difficult or even impractical to identify the cyanotoxin producers. To unravel this complexity and directly identify the toxigenic genera, we showed that integrating classical approaches with metagenomic is required. We first characterized, from genes to metagenomes assembled genomes, the toxigenic Cyanobacteria. We found that Microcystis was the most dominant cyanobacterial genus and the sole carrier of the mcy operon, making it the only microcystin producer. We then quantified twenty-one different cyanopeptides, including twelve microcystin congeners using a high-performance liquid chromatography-high-resolution. Nine microcystins (MCs) and the emerging cyanotoxin anabaenopeptin-A and -B were found at varying concentrations throughout the year, with MC-LA being the most common and abundant. Our findings, constrained by our sampling strategy, indicate that conventional cyanotoxin biomarkers ( e.g. , toxin mcy genes) were not consistently reliable indicators of cyanotoxin concentrations in this freshwater system. In this study, we followed the dynamics of the cyanobacterial community and the associated cyanopeptides with unprecedented resolution. Our results have implications for better management of toxic blooms in this freshwater system, which supplies drinking water to more than 7 million people in the megalopolis of Valle de México. • Identifications of cyanotoxins producers using metagenomic and genes information is key when multiple toxigenic Cyanobacteria co-occur. • Microcystis was the only mcy genes carrier among the cyanobacterial community. • The microcystin variant MC-LA dominated spatially and temporarily. • Anabaenopeptins and microcystin were the most abundant cyanotoxins. • Planktothrix was one of the best candidates associated with the synthesis of anabaenopeptins.

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)0.000
metaresearch head score (Gemma)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.004
GPT teacher head0.208
Teacher spread0.205 · 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
Published2025
Admission routes2
Has abstractyes

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