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Record W2064987038 · doi:10.1186/1471-2180-12-214

Proteomic analysis of Clostridium thermocellum core metabolism: relative protein expression profiles and growth phase-dependent changes in protein expression

2012· article· en· W2064987038 on OpenAlexafffund
Thomas Rydzak, Peter McQueen, Oleg V. Krokhin, Vic Spicer, Peyman Ezzati, Ravi C. Dwivedi, Dmitry Shamshurin, David B. Levin, John A. Wilkins, Richard Sparling

Bibliographic record

VenueBMC Microbiology · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicrobial Metabolic Engineering and Bioproduction
Canadian institutionsUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of CanadaBIOCAP CanadaGenome Canada
KeywordsFerredoxinClostridium thermocellumBiochemistryBiologyMetabolic engineeringOxidoreductaseMetabolismCellobioseFormate dehydrogenaseProteomeCofactorEnzyme

Abstract

fetched live from OpenAlex

BACKGROUND: Clostridium thermocellum produces H2 and ethanol, as well as CO2, acetate, formate, and lactate, directly from cellulosic biomass. It is therefore an attractive model for biofuel production via consolidated bioprocessing. Optimization of end-product yields and titres is crucial for making biofuel production economically feasible. Relative protein expression profiles may provide targets for metabolic engineering, while understanding changes in protein expression and metabolism in response to carbon limitation, pH, and growth phase may aid in reactor optimization. We performed shotgun 2D-HPLC-MS/MS on closed-batch cellobiose-grown exponential phase C. thermocellum cell-free extracts to determine relative protein expression profiles of core metabolic proteins involved carbohydrate utilization, energy conservation, and end-product synthesis. iTRAQ (isobaric tag for relative and absolute quantitation) based protein quantitation was used to determine changes in core metabolic proteins in response to growth phase. RESULTS: Relative abundance profiles revealed differential levels of putative enzymes capable of catalyzing parallel pathways. The majority of proteins involved in pyruvate catabolism and end-product synthesis were detected with high abundance, with the exception of aldehyde dehydrogenase, ferredoxin-dependent Ech-type [NiFe]-hydrogenase, and RNF-type NADH:ferredoxin oxidoreductase. Using 4-plex 2D-HPLC-MS/MS, 24% of the 144 core metabolism proteins detected demonstrated moderate changes in expression during transition from exponential to stationary phase. Notably, proteins involved in pyruvate synthesis decreased in stationary phase, whereas proteins involved in glycogen metabolism, pyruvate catabolism, and end-product synthesis increased in stationary phase. Several proteins that may directly dictate end-product synthesis patterns, including pyruvate:ferredoxin oxidoreductases, alcohol dehydrogenases, and a putative bifurcating hydrogenase, demonstrated differential expression during transition from exponential to stationary phase. CONCLUSIONS: Relative expression profiles demonstrate which proteins are likely utilized in carbohydrate utilization and end-product synthesis and suggest that H2 synthesis occurs via bifurcating hydrogenases while ethanol synthesis is predominantly catalyzed by a bifunctional aldehyde/alcohol dehydrogenase. Differences in expression profiles of core metabolic proteins in response to growth phase may dictate carbon and electron flux towards energy storage compounds and end-products. Combined knowledge of relative protein expression levels and their changes in response to physiological conditions may aid in targeted metabolic engineering strategies and optimization of fermentation conditions for improvement of biofuels production.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.014
GPT teacher head0.243
Teacher spread0.229 · 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 source (direct Gemma or distilled Codex), 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".

Quick stats

Citations129
Published2012
Admission routes2
Has abstractyes

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