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Record W2940246800 · doi:10.1098/rsif.2019.0129

Increasing sulfate levels show a differential impact on synthetic communities comprising different methanogens and a sulfate reducer

2019· article· en· W2940246800 on OpenAlexaff
Jing Chen, Matthew J. Wade, Jan Dolfing, Orkun S. Soyer

Bibliographic record

VenueJournal of The Royal Society Interface · 2019
Typearticle
Languageen
FieldEngineering
TopicAnaerobic Digestion and Biogas Production
Canadian institutionsMcMaster University
FundersBiotechnology and Biological Sciences Research Council
KeywordsSulfateMethanogenesisReducerMethaneEcologyBiologyChemistryEnvironmental chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Methane-producing microbial communities are of ecological and biotechnological interest. Syntrophic interactions among sulfate reducers and aceto/hydrogenotrophic and obligate hydrogenotrophic methanogens form a key component of these communities, yet, the impact of these different syntrophic routes on methane production and their stability against sulfate availability are not well understood. Here, we construct model synthetic communities using a sulfate reducer and two types of methanogens representing different methanogenesis routes. We find that tri-cultures with both routes increase methane production by almost twofold compared to co-cultures and are stable in the absence of sulfate. With increasing sulfate, system stability and productivity decreases and does so faster in communities with aceto/hydrogenotrophic methanogens despite the continued presence of acetate. We show that this is due to a shift in the metabolism of these methanogens towards co-utilization of hydrogen with acetate. These findings indicate the important role of hydrogen dynamics in the stability and productivity of syntrophic communities.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.342
Threshold uncertainty score0.505

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 integrity0.0000.001
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 head0.014
GPT teacher head0.241
Teacher spread0.227 · 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 designSimulation or modeling
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

Citations42
Published2019
Admission routes1
Has abstractyes

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