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Record W3126512465 · doi:10.7717/peerj.12424

Co-culturing <i>Hyphomicrobium nitrativorans</i> strain NL23 and <i>Methylophaga nitratireducenticrescens</i> strain JAM1 allows sustainable denitrifying activities under marine conditions

2021· article· en· W3126512465 on OpenAlexafffund
Alexandra Cucaita, Marianne Piochon, Richard Villemur

Bibliographic record

VenuePeerJ · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicWastewater Treatment and Nitrogen Removal
Canadian institutionsInstitut National de la Recherche Scientifique
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsDenitrifying bacteriaBiofilmAnoxic watersDenitrificationStrain (injury)MicrobiologyBacteriaBiologyBioreactorFood scienceNitrite reductaseNitrateChemistryNitriteBotanyNitrogenEcology

Abstract

fetched live from OpenAlex

Background Hyphomicrobium nitrativorans strain NL23 and Methylophaga nitratireducenticrescens strain JAM1 are the principal bacteria involved in the denitrifying activities of a methanol-fed, fluidized-bed marine denitrification system. Strain NL23 possesses the complete denitrification pathway, but cannot grow under marine conditions in pure cultures. Strain JAM1 is a marine bacterium that lacks genes encoding a dissimilatory nitrite (NO 2 − ) reductase and therefore cannot reduce NO 2 − . Here, we report the characterization of some of their physiological traits that could influence their co-habitation. We also perform co-cultures to assess the potential synergy between the two strains under marine and denitrifying conditions. Methodology Anoxic planktonic pure cultures of both strains were grown with different concentrations of nitrate (NO 3 − ). Anoxic planktonic co-cultures could only be cultured on low NaCl concentrations for strain NL23 to grow. Biofilm co-cultures were achieved in a 500-mL bioreactor, and operated under denitrifying conditions with increasing concentrations of NaCl. NO 3 − and NO 2 − concentrations and the protein content were measured to derive the denitrification rates. The concentrations of both strains in co-cultures were determined by quantitative PCR (qPCR). Ectoine concentration was measured by mass spectrometry in the biofilm co-culture. The biofilm was visualized by fluorescence in situ hybridization. Reverse-transcription-qPCR and RNA-seq approaches were used to assess changes in the expression profiles of genes involved in the nitrogen pathways in the biofilm cultures. Results Planktonic pure cultures of strain JAM1 had a readiness to reduce NO 3 − with no lag phase for growth in contrast to pure cultures of strain NL23, which had a 2-3 days lag phase before NO 3 − starts to be consumed and growth to occur. Compared to strain NL23, strain JAM1 has a higher µmax for growth and higher specific NO 3 − reduction rates. Denitrification rates were twice higher in the planktonic co-cultures than those measured in strain NL23 pure cultures. The biofilm co-cultures showed sustained denitrifying activities and surface colonization by both strains under marine conditions. Increase in ectoine concentrations was observed in the biofilm co-culture with the increase of NaCl concentrations. Changes in the relative transcript levels were observed in the biofilm culture with genes encoding NapA and NapGH in strain NL23. The type of medium had a great impact on the expression of genes involved in the N-assimilation pathways in both strains. Conclusions These results illustrate the capacity of both strains to act together in performing sustainable denitrifying activities under marine conditions. Although strain JAM1 did not contribute in better specific denitrifying activities in the biofilm co-cultures, its presence helped strain NL23 to acclimate to medium with NaCl concentrations &gt;1.0%.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient 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 score0.023
Threshold uncertainty score1.000

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 studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.010
GPT teacher head0.236
Teacher spread0.226 · 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

Citations7
Published2021
Admission routes2
Has abstractyes

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