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Record W4206962549 · doi:10.1021/acs.est.1c05279

<i>In Vivo</i> Temperature Dependency of Molybdenum and Vanadium Nitrogenase Activity in the Heterocystous Cyanobacteria <i>Anabaena variabilis</i>

2022· article· en· W4206962549 on OpenAlexafffund
Romain Darnajoux, Robert L. Bradley, Jean‐Philippe Bellenger

Bibliographic record

VenueEnvironmental Science & Technology · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicMicrobial Fuel Cells and Bioremediation
Canadian institutionsUniversité de Sherbrooke
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsNitrogenaseAnabaena variabilisCyanobacteriaVanadiumChemistryHeterocystNitrogen fixationMolybdenumEnvironmental chemistryBiologyNitrogenInorganic chemistryBacteria

Abstract

fetched live from OpenAlex

The reduction of atmospheric dinitrogen by nitrogenase is a key component of terrestrial nitrogen cycling. Nitrogenases exist in several isoforms named after the metal present within their active center: the molybdenum (Mo), the vanadium (V), and the iron (Fe)-only nitrogenase. While earlier in vitro studies hint that the relative contribution of V nitrogenase to total BNF could be temperature-dependent, the effect of temperature on in vivo activity remains to be investigated. In this study, we characterize the in vivo effect of temperature (3–42 °C) on the activities of Mo nitrogenase and V nitrogenase in the heterocystous cyanobacteria Anabaena variabilis ATTC 29413 using the acetylene reduction assay by cavity ring-down absorption spectroscopy. We demonstrate that V nitrogenase becomes as efficient as Mo nitrogenase at temperatures below 10–15 °C. At temperatures above 22 °C, BNF seems to be limited by O2 availability to respiration in both enzymes. Furthermore, Anabaena variabilis cultures grown in Mo or V media achieved similar growth rates at temperatures below 20 °C. Considering the average temperature on earth is 15 °C, our findings further support the role of V nitrogenase as a viable backup enzymatic system for BNF in natural ecosystems.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.002
GPT teacher head0.173
Teacher spread0.171 · 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.

Study designBench or experimental
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

Citations23
Published2022
Admission routes2
Has abstractyes

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