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Genome and transcriptome analysis of rock-dissolving Pseudomonas sp. NLX-4 strain

2022· other· en· W6958999590 on OpenAlexaff

Bibliographic record

VenueFigshare · 2022
Typeother
Languageen
FieldAgricultural and Biological Sciences
TopicBotanical Research and Chemistry
Canadian institutionsLakehead University
Fundersnot available
KeywordsTranscriptomeStrain (injury)GenomePseudomonasGeneBacteriaSilicateWeathering

Abstract

fetched live from OpenAlex

Abstract Microbial weathering processes can significantly promote soil properties and reduce rock-to-soil ratio. Some soil-inhabiting bacteria exhibit efficient rock-dissolution abilities by releasing organic acids and other chemical elements from the silicate rocks. However, our understanding of the molecular mechanisms involved during bacterial rock-dissolution is still limited. In this study, we performed silicate rock-dissolution experiments on a Pseudomonas sp. NLX-4 strain isolated from an over-exploited mining site. The results revealed that Pseudomonas sp. NLX-4 strain efficiently accelerates the dissolution of silicate rocks by secreting amino acids, exopolysaccharides, and organic acids. Through employing genome and transcriptome sequencing (RNA-seq), we identified the major regulatory genes. Specifically, 15 differentially expressed genes (DEGs) encoding for siderophore transport, EPS and amino acids synthesis, organic acids metabolism, and bacterial resistance to adverse environmental conditions were highly up-regulated in silicate rock cultures of NLX-4 strain. Our study reports a potential bacterial based approach for improving the ecological restoration of over-exploited rock mining sites. Graphical 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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.906
Threshold uncertainty score0.294

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.9060.000

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 head0.031
GPT teacher head0.247
Teacher spread0.216 · 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.

Study designNot applicable
Domainnot available
GenreDataset

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

Citations0
Published2022
Admission routes1
Has abstractyes

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