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Record W4403845771 · doi:10.7717/peerj.18361

The bacterial strains JAM1<sup>T</sup> and GP59 of the species <i>Methylophaga nitratireducenticrescens</i> differ in their expression profiles of denitrification genes in oxic and anoxic cultures

2024· article· en· W4403845771 on OpenAlexafffund
Livie Lestin, Richard Villemur

Bibliographic record

VenuePeerJ · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicWastewater Treatment and Nitrogen Removal
Canadian institutionsInstitut National de la Recherche Scientifique
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsDenitrificationAnoxic watersNitrite reductaseStrain (injury)GeneNitriteBiologyTranscription (linguistics)Nitrate reductaseNitrateChemistryNitrogenBiochemistryEnzymeEcology

Abstract

fetched live from OpenAlex

Background Strain JAM1 T and strain GP59 of the methylotrophic, bacterial species Methylophaga nitratireducenticrescens were isolated from a microbial community of the biofilm that developed in a fluidized-bed, methanol-fed, marine denitrification system. Despite of their common origin, both strains showed distinct physiological characters towards the dynamics of nitrate (${\mathrm{NO}}_{3}^{-}$) reduction. Strain JAM1 T can reduce ${\mathrm{NO}}_{3}^{-}$ to nitrite (${\mathrm{NO}}_{2}^{-}$) but not ${\mathrm{NO}}_{2}^{-}$ to nitric oxide (NO) as it lacks a NO-forming ${\mathrm{NO}}_{2}^{-}$ reductase. Strain GP59 on the other hand can carry the complete reduction of ${\mathrm{NO}}_{3}^{-}$ to N 2 . Strain GP59 cultured under anoxic conditions shows a 24-48h lag phase before ${\mathrm{NO}}_{3}^{-}$ reduction occurs. In strain JAM1 T cultures, ${\mathrm{NO}}_{3}^{-}$ reduction begins immediately with accumulation of ${\mathrm{NO}}_{2}^{-}$. Furthermore, ${\mathrm{NO}}_{3}^{-}$ is reduced under oxic conditions in strain JAM1 T cultures, which does not appear in strain GP59 cultures. These distinct characters suggest differences in the regulation pathways impacting the expression of denitrification genes, and ultimately growth. Methods Both strains were cultured under oxic conditions either with or without ${\mathrm{NO}}_{3}^{-}$, or under anoxic conditions with ${\mathrm{NO}}_{3}^{-}$. Transcript levels of selected denitrification genes ( nar1 and nar2 encoding ${\mathrm{NO}}_{3}^{-}$ reductases, nirK encoding ${\mathrm{NO}}_{2}^{-}$ reductase, narK12f encoding ${\mathrm{NO}}_{3}^{-}$/${\mathrm{NO}}_{2}^{-}$transporter) and regulatory genes ( narXL and fnr ) were determined by quantitative reverse transcription polymerase chain reaction. We also derived the transcriptomes of these cultures and determined their relative gene expression profiles. Results The transcript levels of nar1 were very low in strain GP59 cultured under oxic conditions without ${\mathrm{NO}}_{3}^{-}$. These levels were 37 times higher in strain JAM1 T cultured under the same conditions, suggesting that Nar1 was expressed at sufficient levels in strain JAM1 T before the inoculation of the oxic and anoxic cultures to carry ${\mathrm{NO}}_{3}^{-}$ reduction with no lag phase. Transcriptomic analysis revealed that each strain had distinct relative gene expression profiles, and oxygen had high impact on these profiles. Among denitrification genes and regulatory genes, the nnrS3 gene encoding factor involved in NO-response function had its relative gene transcript levels 5 to 10 times higher in strain GP59 cultured under oxic conditions with ${\mathrm{NO}}_{3}^{-}$ than those in both strains cultured under oxic conditions without ${\mathrm{NO}}_{3}^{-}$. Since NnrS senses NO, these results suggest that strain GP59 reduced ${\mathrm{NO}}_{3}^{-}$ to NO under oxic conditions, but because of the oxic environment, NO is oxidized back to ${\mathrm{NO}}_{3}^{-}$ by flavohemoproteins (NO dioxygenase; Hmp), explaining why ${\mathrm{NO}}_{3}^{-}$ reduction is not observed in strain GP59 cultured under oxic conditions. Conclusions Understanding how these two strains manage the regulation of the denitrification pathway provided some clues on how they response to environmental changes in the original biofilm community, and, by extension, how this community adapts in providing efficient denitrifying activities.

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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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.247
Threshold uncertainty score0.245

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 head0.011
GPT teacher head0.216
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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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".

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Citations2
Published2024
Admission routes2
Has abstractyes

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