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Record W4366490375 · doi:10.1016/j.heliyon.2023.e15639

Tolerance, taxonomic and phylogenetic studies of some bacterial isolates involved in bioremediation of crude oil polluted soil in the southern region of Nigeria

2023· article· en· W4366490375 on OpenAlexfundno aff
Emmanuel Chukwuma Omenna, Kingsley Omage, Emmanuel Ezaka, Marshall Arebojie Azeke

Bibliographic record

VenueHeliyon · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicMicrobial bioremediation and biosurfactants
Canadian institutionsnot available
FundersProvidence Health Care
KeywordsBioremediationBiologySoil contaminationBenin cityBacteriaVeterinary medicineSoil waterMicrobiologyContaminationEcology

Abstract

fetched live from OpenAlex

Indigenous bacteria play vital roles in the bioremediation of crude oil polluted soils. The effectiveness of the bioremediation process depends on the tolerance, characteristics and biodiversity of the bacteria isolates. Bacteria strains were isolated from crude-oil polluted sites in different locations in the southern region of Nigeria namely: Azikoro and Otukpoti (Bayelsa state); Ologbo and Benin (Edo State) and non-polluted soil was collected from Ibadan (Oyo state). Tolerance study was conducted for 96 h s. Isolation and characterization of the most effective isolate from each location was done using cultural, physico-chemical and molecular methods. The tolerance level of the isolates from the different oil-polluted soils and their comparative growth performance on crude oil supplemented media decreases in the order: Azikoro - Ologbo - Otukpoti - Benin. MATS analysis showed that cell surfaces of Azikoro, Ologbo and Otukpoti strains exhibited 58–63 % adhesion to n-hexadecane and are hydrophobic strains while Benin strain possess 38% adhesion to n-hexadecane and are hydrophilic. The cell surfaces of isolates from Azikoro, Ologbo and Otukpoti are highly Lewis-acidic while that from Benin is highly Lewis-basic. Isolates from Benin-3, Ologbo-1, and Otukpoti-1 were shown to be gram positive while that from Azikoro was gram negative. 16S rDNA fingerprinting confirmed the identities of the isolates as follows: Paenalcaligenes suwonesis with accession numbers NR-133804.1 from Azikoro spillage site (93.77%); Lactobacillus nagelii with accession number NR-158108.1 (91.30%) from Benin spillage site; Lactobacillus fermentum with accession number NR-104927.1 (96.70%) from Ologbo and Otukpoti spillage sites. Phylogenetic analysis putatively categorized the isolates from Otukpoti and Ologbo in close association belonging to same homology while Benin isolate is a subgroup. The characteristics and biodiversity of all the isolated bacteria from the regions possibly justifies their involvement in the bioremediation of petroleum hydrocarbons.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
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 head0.231
Teacher spread0.207 · 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 designObservational
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
Published2023
Admission routes1
Has abstractyes

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