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Record W4306834506 · doi:10.3389/fceng.2022.1036084

Biological funneling of phenolics from transgenic plants engineered to express the bacterial 3-dehydroshikimate dehydratase (qsuB) gene

2022· article· en· W4306834506 on OpenAlexaff
German E. Umana, Jose M. Perez, Faride Unda, Chien-Yuan Lin, Canan Sener, Steven D. Karlen, Shawn D. Mansfield, Aymerick Eudes, John Ralph, Timothy J. Donohue, Daniel R. Noguera

Bibliographic record

VenueFrontiers in Chemical Engineering · 2022
Typearticle
Languageen
FieldEngineering
TopicBiofuel production and bioconversion
Canadian institutionsUniversity of British Columbia
FundersGreat Lakes Bioenergy Research CenterLawrence Berkeley National LaboratoryBiological and Environmental ResearchOffice of ScienceU.S. Department of Energy
KeywordsLignocellulosic biomassProtocatechuic acidArabidopsisBioproductsGenetically modified cropsBiologyBotanyTransgeneLigninBiochemistryFood scienceBiotechnologyBiofuelGeneMutant

Abstract

fetched live from OpenAlex

The economic and environmental sustainability of lignocellulosic biomass biorefineries is predicated on generating biofuels and bioproducts from cell-wall polysaccharide and lignin polymers. Historical efforts in plant genetic engineering have focused on the development of strategies that facilitate biomass deconstruction, with more recently efforts including the synthesis of high-value chemicals in planta. One such genetic modification is the expression of the bacterial quinate and shikimate utilization B (qsuB) gene that increases the accumulation of protocatechuic acid in lignocellulosic biomass. Herein, we evaluated the effectiveness of an alkaline pretreatment process to extract phenolics directly from wild-type and QsuB-transgenic lines of Arabidopsis, poplar, and sorghum, and then upgrade them to the polyester precursor 2-pyrone-4,6-dicarboxylic acid (PDC) with an engineered strain of Novosphingobium aromaticivorans. Protocatechuic acid extracted from all QsuB transgenic lines was found to be mostly in the glycosylated form. Glycosylated protocatechuic acid and other plant-derived phenolics were effectively metabolized by N. aromaticivorans, and PDC production was greatest using extracts from an Arabidopsis QsuB transgenic line (∼5% w/w), followed by QsuB sorghum (∼1.1% w/w), and QsuB poplar (∼0.4% w/w) lines. The comparison of PDC production from wild-type and QsuB transgenic lines of Arabidopsis, poplar, and sorghum demonstrates the utility of a mild alkaline pretreatment to liberate phenolics from plant biomass that are either naturally present or that accumulate as a consequence of genetic engineering strategies. All QsuB transgenic lines outperformed their wild-type counterparts with respect to observed PDC yields. In addition, microbial funneling to PDC was effective even when most of the protocatechuic acid extracted was in glycosylated form, clearly demonstrating that this bacterium can metabolize these aromatic conjugates. These findings illustrate the benefits of combining plant and microbial engineering for bioproduct formation from phenolics in lignocellulosic biorefineries.

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
Bibliometrics0.0000.000
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 head0.011
GPT teacher head0.176
Teacher spread0.165 · 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

Citations16
Published2022
Admission routes1
Has abstractyes

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