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Record W3215310686 · doi:10.1186/s40168-021-01147-1

Accelerated discovery of novel glycoside hydrolases using targeted functional profiling and selective pressure on the rumen microbiome

2021· article· en· W3215310686 on OpenAlexafffund
A. L. A. Neves, Jiangkun Yu, Yutaka Suzuki, Marisol Báez-Magaña, Elena Arutyunova, Eóin O’Hara, Tim A. McAllister, Kim Ominski, M. Joanne Lemieux, Le Luo Guan

Bibliographic record

VenueMicrobiome · 2021
Typearticle
Languageen
FieldEngineering
TopicBiofuel production and bioconversion
Canadian institutionsUniversity of ManitobaCanadian Science Centre for Human and Animal HealthAgriculture and Agri-Food CanadaUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaEmpresa Brasileira de Pesquisa AgropecuáriaAlberta InnovatesAlberta Innovates - Technology FuturesAlberta Agriculture and Forestry
KeywordsMicrobiomeBiologyMicrobial ecologyMetagenomicsRumenComputational biologyProfiling (computer programming)Glycoside hydrolaseGlycosideBioinformaticsBiochemistryGeneticsBacteriaEnzymeBotanyGene

Abstract

fetched live from OpenAlex

BACKGROUND: Carbohydrate-active enzymes (CAZymes) form the most widespread and structurally diverse set of enzymes involved in the breakdown, biosynthesis, or modification of lignocellulose that can be found in living organisms. However, the structural diversity of CAZymes has rendered the targeted discovery of novel enzymes extremely challenging, as these proteins catalyze many different chemical reactions and are sourced by a vast array of microbes. Consequently, many uncharacterized members of CAZyme families of interest have been overlooked by current methodologies (e.g., metagenomic screening) used to discover lignocellulolytic enzymes. RESULTS: In the present study, we combined phenotype-based selective pressure on the rumen microbiota with targeted functional profiling to guide the discovery of unknown CAZymes. In this study, we found 61 families of glycoside hydrolases (GH) (out of 182 CAZymes) from protein sequences deposited in the CAZy database-currently associated with more than 20,324 microbial genomes. Phenotype-based selective pressure on the rumen microbiome showed that lignocellulolytic bacteria (e.g., Fibrobacter succinogenes, Butyrivibrio proteoclasticus) and three GH families (e.g., GH11, GH13, GH45) exhibited an increased relative abundance in the rumen of feed efficient cattle when compared to their inefficient counterparts. These results paved the way for the application of targeted functional profiling to screen members of the GH11 and GH45 families against a de novo protein reference database comprised of 1184 uncharacterized enzymes, which led to the identification of 18 putative xylanases (GH11) and three putative endoglucanases (GH45). The biochemical proof of the xylanolytic activity of the newly discovered enzyme validated the computational simulations and demonstrated the stability of the most abundant xylanase. CONCLUSIONS: These findings contribute to the discovery of novel enzymes for the breakdown, biosynthesis, or modification of lignocellulose and demonstrate that the rumen microbiome is a source of promising enzyme candidates for the biotechnology industry. The combined approaches conceptualized in this study can be adapted to any microbial environment, provided that the targeted microbiome is easy to manipulate and facilitates enrichment for the microbes of interest. Video Abstract.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.545

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 head0.026
GPT teacher head0.210
Teacher spread0.184 · 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".

Quick stats

Citations30
Published2021
Admission routes2
Has abstractyes

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