Bacterial nitrilases and their regulation

Chhiba-Govindjee, Varsha P; Westhuyzen, Christiaan W. van der; Bode, Moira L.; Brady, Dean

doi:10.1007/s00253-019-09776-1

Cited by 18 publications

(15 citation statements)

References 118 publications

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“…This Nit4 expression profile is unusual because the 3-CNA nitrilase from Pseudomonas sp. 13 is induced by 3-CNA ( 18 ), and most bacterial nitrilases are induced by nitriles ( 33 ). Expression of the P. pseudoalcaligenes CECT5344 nit4 gene could be related to its location in the cio gene cluster, which is specifically induced by cyanide and not by 3-CNA ( Fig.…”

Section: Discussionmentioning

confidence: 99%

Alternative Pathway for 3-Cyanoalanine Assimilation in Pseudomonas pseudoalcaligenes CECT5344 under Noncyanotrophic Conditions

et al. 2021

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Nitriles are organic cyanides with important industrial applications, but they are also found in nature. 3-Cyanoalanine is synthesized by plants and some bacteria to detoxify cyanide from endogenous or exogenous sources, but this nitrile may be also involved in other processes such as stress tolerance, nitrogen and sulfur metabolism, and signaling. The cyanide-degrading bacterium Pseudomonas pseudoalcaligenes CECT5344 grows with 3-cyanoalanine as the sole nitrogen source, but it does not use this nitrile as an intermediate in the cyanide assimilation pathway.

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Section: Discussionmentioning

confidence: 99%

Alternative Pathway for 3-Cyanoalanine Assimilation in Pseudomonas pseudoalcaligenes CECT5344 under Noncyanotrophic Conditions

et al. 2021

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“…Only strain R-39594 T shows the potential to use nitrile as a nitrogen source by converting it into ammonia using nitrilase. The presence of nitrilases in bacteria is rare, with only 6.8% of bacteria expressing nitrilases [22].…”

Section: Nitrogen Sulfur Phosphor and Potassium Metabolismmentioning

confidence: 99%

“…Little is known about these enzymes in bacteria, except for their role in supplying a nitrogen source for growth [22]. As predicted by the annotations, ammonia is the main nitrogen source of the strains.…”

Section: Nitrogen Sulfur Phosphor and Potassium Metabolismmentioning

confidence: 99%

Description and functional testing of four species of the novel phototrophic genus Chioneia gen. nov., isolated from different East Antarctic environments

Tahon

Gök

Lebbe

et al. 2021

Systematic and Applied Microbiology

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“…They are an example of an enzyme family with broad scope and are found in a range of eukaryotic and prokaryotic organisms. Nitrilases play an important role in many biological processes, such as the degradation of toxic nitrile compounds, metabolism, and generation of hormones, and synthesis of signaling molecules 16 . In the context of plant‐microbe interactions, they are believed to play a role in hormone synthesis, nutrient assimilation, detoxification, and modulation of plant development and physiology, making them attractive for improved food crop production 17 .…”

Section: Introductionmentioning

confidence: 99%

“…Nitrilases play an important role in many biological processes, such as the degradation of toxic nitrile compounds, metabolism, and generation of hormones, and synthesis of signaling molecules. 16 In the context of plant-microbe interactions, they are believed to play a role in hormone synthesis, nutrient assimilation, detoxification, and modulation of plant development and physiology, making them attractive for improved food crop production. 17 In addition, nitriles are desirable for their use in efficient chemo-and enantioselective synthesis of carboxylic acids, making them attractive for drug design.…”

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confidence: 99%

Machine learning‐based prediction of enzyme substrate scope: Application to bacterial nitrilases

et al. 2020

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Predicting the range of substrates accepted by an enzyme from its amino acid sequence is challenging. Although sequence‐ and structure‐based annotation approaches are often accurate for predicting broad categories of substrate specificity, they generally cannot predict which specific molecules will be accepted as substrates for a given enzyme, particularly within a class of closely related molecules. Combining targeted experimental activity data with structural modeling, ligand docking, and physicochemical properties of proteins and ligands with various machine learning models provides complementary information that can lead to accurate predictions of substrate scope for related enzymes. Here we describe such an approach that can predict the substrate scope of bacterial nitrilases, which catalyze the hydrolysis of nitrile compounds to the corresponding carboxylic acids and ammonia. Each of the four machine learning models (logistic regression, random forest, gradient‐boosted decision trees, and support vector machines) performed similarly (average ROC = 0.9, average accuracy = ~82%) for predicting substrate scope for this dataset, although random forest offers some advantages. This approach is intended to be highly modular with respect to physicochemical property calculations and software used for structural modeling and docking.

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Bacterial nitrilases and their regulation

Cited by 18 publications

References 118 publications

Alternative Pathway for 3-Cyanoalanine Assimilation in Pseudomonas pseudoalcaligenes CECT5344 under Noncyanotrophic Conditions

Alternative Pathway for 3-Cyanoalanine Assimilation in Pseudomonas pseudoalcaligenes CECT5344 under Noncyanotrophic Conditions

Description and functional testing of four species of the novel phototrophic genus Chioneia gen. nov., isolated from different East Antarctic environments

Machine learning‐based prediction of enzyme substrate scope: Application to bacterial nitrilases

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