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Record W3189362170 · doi:10.1038/s41467-021-24396-y

Timing the evolution of antioxidant enzymes in cyanobacteria

2021· article· en· W3189362170 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueNature Communications · 2021
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeochemistry and Elemental Analysis
Canadian institutionsUniversity of ReginaUniversity of Alberta
FundersRoyal Society
KeywordsCyanobacteriaPhototrophSuperoxide dismutaseBiologyReactive oxygen speciesPhotosynthesisOxidative stressBotanyBiochemistryGeneticsBacteria

Abstract

fetched live from OpenAlex

The ancestors of cyanobacteria generated Earth's first biogenic molecular oxygen, but how they dealt with oxidative stress remains unconstrained. Here we investigate when superoxide dismutase enzymes (SODs) capable of removing superoxide free radicals evolved and estimate when Cyanobacteria originated. Our Bayesian molecular clocks, calibrated with microfossils, predict that stem Cyanobacteria arose 3300-3600 million years ago. Shortly afterwards, we find phylogenetic evidence that ancestral cyanobacteria used SODs with copper and zinc cofactors (CuZnSOD) during the Archaean. By the Paleoproterozoic, they became genetically capable of using iron, nickel, and manganese as cofactors (FeSOD, NiSOD, and MnSOD respectively). The evolution of NiSOD is particularly intriguing because it corresponds with cyanobacteria's invasion of the open ocean. Our analyses of metalloenzymes dealing with reactive oxygen species (ROS) now demonstrate that marine geochemical records alone may not predict patterns of metal usage by phototrophs from freshwater and terrestrial habitats.

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.

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)0.000
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 score0.039
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.015
GPT teacher head0.247
Teacher spread0.232 · 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