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Record W4399021528 · doi:10.1186/s12866-024-03331-3

Uncovering the lignin-degrading potential of Serratia quinivorans AORB19: insights from genomic analyses and alkaline lignin degradation

2024· article· en· W4399021528 on OpenAlexafffund
Nadia Sufdar Ali, Subarna Thakur, Mengwei Ye, Fanny Monteil‐Rivera, Youlian Pan, Wensheng Qin, Trent Chunzhong Yang

Bibliographic record

VenueBMC Microbiology · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicEnzyme-mediated dye degradation
Canadian institutionsLakehead UniversityNational Research Council Canada
FundersNational Research Council CanadaLakehead University
KeywordsLigninLaccaseBiologyContext (archaeology)BiorefineryBiochemistryStrain (injury)CellulaseExtremophileFood scienceMicrobiologyBiotechnologyEnzymeBotanyBiofuel

Abstract

fetched live from OpenAlex

BACKGROUND: Lignin is an intricate phenolic polymer found in plant cell walls that has tremendous potential for being converted into value-added products with the possibility of significantly increasing the economics of bio-refineries. Although lignin in nature is bio-degradable, its biocatalytic conversion is challenging due to its stable complex structure and recalcitrance. In this context, an understanding of strain's genomics, enzymes, and degradation pathways can provide a solution for breaking down lignin to unlock the full potential of lignin as a dominant valuable bioresource. A gammaproteobacterial strain AORB19 has been isolated previously from decomposed wood based on its high laccase production. This work then focused on the detailed genomic and functional characterization of this strain based on whole genome sequencing, the identification of lignin degradation products, and the strain's laccase production capabilities on various agro-industrial residues. RESULTS: Lignin degrading bacterial strain AORB19 was identified as Serratia quinivorans based on whole genome sequencing and core genome phylogeny. The strain comprised a total of 123 annotated CAZyme genes, including ten cellulases, four hemicellulases, five predicted carbohydrate esterase genes, and eight lignin-degrading enzyme genes. Strain AORB19 was also found to possess genes associated with metabolic pathways such as the β-ketoadipate, gentisate, anthranilate, homogentisic, and phenylacetate CoA pathways. LC-UV analysis demonstrated the presence of p-hydroxybenzaldehyde and vanillin in the culture media which constitutes potent biosignatures indicating the strain's capability to degrade lignin. Finally, the study evaluated the laccase production of Serratia AORB19 grown with various industrial raw materials, with the highest activity detected on flax seed meal (257.71 U/L), followed by pea hull (230.11 U/L), canola meal (209.56 U/L), okara (187.67 U/L), and barley malt sprouts (169.27 U/L). CONCLUSIONS: The whole genome analysis of Serratia quinivorans AORB19, elucidated a repertoire of genes, pathways and enzymes vital for lignin degradation that widens the understanding of ligninolytic metabolism among bacterial lignin degraders. The LC-UV analysis of the lignin degradation products coupled with the ability of S. quinivorans AORB19 to produce laccase on diverse agro-industrial residues underscores its versatility and its potential to contribute to the economic viability of bio-refineries.

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 score0.058
Threshold uncertainty score0.283

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 head0.025
GPT teacher head0.247
Teacher spread0.222 · 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

Citations11
Published2024
Admission routes2
Has abstractyes

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