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Record W4404851854 · doi:10.1128/spectrum.01891-24

Exploration of urease-aided calcium carbonate mineralization by enzyme analyses of <i>Neobacillus mesonae</i> strain NS-6

2024· article· en· W4404851854 on OpenAlexaff
Zhiwei Ma, Juncheng Lu, Shichuang Liu, Yanling Ma

Bibliographic record

VenueMicrobiology Spectrum · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicMicrobial Applications in Construction Materials
Canadian institutionsScience North
FundersNational Natural Science Foundation of China
KeywordsUreaseChemistryUreaEnzymeHydrolysisBiochemistry

Abstract

fetched live from OpenAlex

ABSTRACT Urease containing nickel cofactor is crucial for urea-hydrolytic induced calcium carbonate (CaCO 3 ) precipitation (UICP). However, limited information exists regarding the influence of amino acid residues interacting with nickel ions in its structure on induced CaCO 3 mineralization. Herein, RT-qPCR was used to demonstrate that the addition of NiCl 2 dramatically upregulated the expression of urease structural gene ureC that was correlated with nickel binding in Neobacillus mesonae strain NS-6. Homology modeling and molecular docking were employed to construct the three-dimensional structure of urease and seek the key residues involved in nickel binding process, and virtual mutation technology was adopted to inform three key residues coordinated with nickel ions and urea, His249, His275, and Asp363. Four metrics, including root mean square deviation values for mutations of those key residues in urease-urea complexes severally and wild-type, were calculated by molecular dynamics simulations when they were mutated into alanine, respectively. Subsequently, the mutations of H249A, H275A, and D363A were characterized using western blotting to reveal a decrease in the relative expression and activity of urease, along with a corresponding reduction in CaCO 3 precipitation. Ultimately, the mutations also exhibited that they had lower substrate affinity and catalytic efficiency for urea through enzymatic properties analysis. The findings suggested that those residues played a pivotal role in UICP of strain NS-6, which would expand the theoretical basis for modulating urease activity. IMPORTANCE Urease-producing bacterium is of great importance in diverse application fields, such as environmental remediation, due to its key driving characteristics in catalyzing urea hydrolysis via urea-hydrolytic induced CaCO 3 precipitation (UICP). As essential cofactors of urease, nickel ions play a crucial role in regulating urease catalysis and maintaining structural stability. Numerous investigations have emphasized the impact of nickel ions on urease activity in recent years, to our best knowledge, only a few literatures have studied the molecular-level regulation of nickel-ligand residues. This study focused on the highly urease-producing bacterial Neobacillus mesonae NS-6 to explore the effects of specific nickel-ligand residues on the urease-aided CaCO 3 mineralization process using molecular simulation predictions and targeted mutation experiments. The aim was to provide a molecular-level understanding of the interactive effects between urea and critical residues associated with the urease active center, as well as propose an effective modification strategy to enhance the application of UICP in future environmental areas.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.035
Threshold uncertainty score0.998

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)0.0020.000

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 head0.030
GPT teacher head0.291
Teacher spread0.260 · 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 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

Citations3
Published2024
Admission routes1
Has abstractyes

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