MétaCan
Menu
Back to cohort
Record W2147497134 · doi:10.1186/1754-6834-4-36

The enhancement of enzymatic hydrolysis of lignocellulosic substrates by the addition of accessory enzymes such as xylanase: is it an additive or synergistic effect?

2011· article· en· W2147497134 on OpenAlexafffund
Jinguang Hu, Valdeir Arantes, J. N. Saddler

Bibliographic record

VenueBiotechnology for Biofuels · 2011
Typearticle
Languageen
FieldEngineering
TopicBiofuel production and bioconversion
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaNatural Resources CanadaChina Scholarship CouncilMinistry of Education of the People's Republic of ChinaGenome British Columbia
KeywordsXylanaseCellulaseCorn stoverChemistryHydrolysisLignocellulosic biomassXylanCelluloseHemicelluloseEnzymatic hydrolysisFood scienceBiochemistryLigninPulp and paper industryEnzymeOrganic chemistry

Abstract

fetched live from OpenAlex

BACKGROUND: We and other workers have shown that accessory enzymes, such as β-glucosidase, xylanase, and cellulase cofactors, such as GH61, can considerably enhance the hydrolysis effectiveness of cellulase cocktails when added to pretreated lignocellulosic substrates. It is generally acknowledged that, among the several factors that hamper our current ability to attain efficient lignocellulosic biomass conversion yields at low enzyme loadings, a major problem lies in our incomplete understanding of the cooperative action of the different enzymes acting on pretreated lignocellulosic substrates. RESULTS: The reported work assessed the interaction between cellulase and xylanase enzymes and their potential to improve the hydrolysis efficiency of various pretreated lignocellulosic substrates when added at low protein loadings. When xylanases were added to the minimum amount of cellulase enzymes required to achieve 70% cellulose hydrolysis of steam pretreated corn stover (SPCS), or used to partially replace the equivalent cellulase dose, both approaches resulted in enhanced enzymatic hydrolysis. However, the xylanase supplementation approach increased the total protein loading required to achieve significant improvements in hydrolysis (an additive effect), whereas the partial replacement of cellulases with xylanase resulted in similar improvements in hydrolysis without increasing enzyme loading (a synergistic effect). The enhancement resulting from xylanase-aided synergism was higher when enzymes were added simultaneously at the beginning of hydrolysis. This co-hydrolysis of the xylan also influenced the gross fiber characteristics (for example, fiber swelling) resulting in increased accessibility of the cellulose to the cellulase enzymes. These apparent increases in accessibility enhanced the steam pretreated corn stover digestibility, resulting in three times faster cellulose and xylan hydrolysis, a seven-fold decrease in cellulase loading and a significant increase in the hydrolysis performance of the optimized enzyme mixture. When a similar xylanase-aided enhancement strategy was assessed on other pretreated lignocellulosic substrates, equivalent increases in hydrolysis efficiency were also observed. CONCLUSIONS: It was apparent that the 'blocking effect' of xylan was one of the major mechanisms that limited the accessibility of the cellulase enzymes to the cellulose. However, the synergistic interaction of the xylanase and cellulase enzymes was also shown to significantly improve cellulose accessibility through increasing fiber swelling and fiber porosity and also plays a major role in enhancing enzyme accessibility.

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)0.001
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 score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.021
GPT teacher head0.245
Teacher spread0.224 · 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

Citations463
Published2011
Admission routes2
Has abstractyes

Explore more

Same venueBiotechnology for BiofuelsSame topicBiofuel production and bioconversionFrench-language works237,207