Dataset Information

Modeling, Mutagenesis and In-silico Structural Stability Assay of the Model of Superoxide Dismutase of Lactococcus Lactis Subsp. Cremoris MG1363.

ABSTRACT: Background:Characterizing the structure and function of superoxide dismutase (SOD), as an antioxidant enzyme providing opportunities for its application in food supplements. Objectives:In this study, the features of the Manganese-SOD of Lactococcus Lactis (SDLL), subsp. Cremoris MG1363, as probiotic bacteria, were determined on the basis of the computational methods. Materials and Methods:The protein's physicochemical properties and the prediction of its secondary structure were determined via the ProtParam server and the GOR program respectively. Moreover, the 3D structures of the proteins were constructed via the MODELLER on the basis of the homology method and the threading algorithm MUSTER. On the other hand, the structural stability of the models was assayed under the quasi-physiological conditions by the GROMACS program via the GROMOS96 43a1 force field in Linux system. Finally, using the Molecular Docking Studies, the functionality features of the models were predicted through their affinity with the corresponding substrates. Results:The results revealed the physicochemical properties of the SDLL and a 3D model of a chain of the enzyme being similar to the SOD from the Bacillus Subtilis (SDBS). The model of the SDLL was checked for quality control purposes including the Ramachandran plot, the ERRAT and the Verifiy3D. The model was suggestive of the structural stability in quasi-physiological conditions; yet, less than that of the SDBS. Assessing the cause of the instability in the SDLL model was indicative of two unstable regions in the area far from the enzyme's active position, they were considered suitable for mutagenesis. Accordingly, the loop substitution for the corresponding region of SDBS and the deletion of the loop positioned at the C terminal of SDLL resulted in a mutant of SDLL with more stability and appropriate affinity with the corresponding substrate. Conclusion:In general, the study provides a new model of SDLL with certain thermostable features, and a new mutant with suitable stability and functionality on the basis of the direct mutagenesis being used in different applications.

SUBMITTER: Gholampour-Faroji N

PROVIDER: S-EPMC7461707 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

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Publications

Modeling, Mutagenesis and <i>In-silico</i> Structural Stability Assay of the Model of Superoxide Dismutase of <i>Lactococcus Lactis</i> Subsp. <i>Cremoris</i> MG1363.

Gholampour-Faroji Nazanin N Shakeri Monir-Sadat MS Hemmat Jafar J Rastegar-Moghadam Mohammad M Haddad-Mashadrizeh Aliakbar A

Iranian journal of biotechnology 20200101 1

<h4>Background</h4>Characterizing the structure and function of superoxide dismutase (SOD), as an antioxidant enzyme providing opportunities for its application in food supplements.<h4>Objectives</h4>In this study, the features of the Manganese-SOD of <i>Lactococcus Lactis</i> (SDLL), subsp. <i>Cremoris</i> MG1363, as probiotic bacteria, were determined on the basis of the computational methods.<h4>Materials and methods</h4>The protein's physicochemical properties and the prediction of its secon ...[more]

PMID: 32884954

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Project description:Lactococcus lactis is one of the most commonly used lactic acid bacteria in the dairy industry. Activation of competence for natural DNA transformation in this species would greatly improve the selection of novel strains with desired genetic traits. Here, we investigated the activation of natural transformation in L. lactis subsp. cremoris KW2, a strain of plant origin whose genome encodes the master competence regulator ComX and the complete set of proteins usually required for natural transformation. In the absence of knowledge about competence regulation in this species, we constitutively overproduced ComX in a reporter strain of late competence phase activation and showed, by transcriptomic analyses, a ComX-dependent induction of all key competence genes. We further demonstrated that natural DNA transformation is functional in this strain and requires the competence DNA uptake machinery. Since constitutive ComX overproduction is unstable, we alternatively expressed comX under the control of an endogenous xylose-inducible promoter. This regulated system was used to successfully inactivate the adaptor protein MecA and subunits of the Clp proteolytic complex, which were previously shown to be involved in ComX degradation in streptococci. In the presence of a small amount of ComX, the deletion of mecA, clpC, or clpP genes markedly increased the activation of the late competence phase and transformability. Altogether, our results report the functionality of natural DNA transformation in L. lactis and pave the way for the identification of signaling mechanisms that trigger the competence state in this species.IMPORTANCELactococcus lactis is a lactic acid bacterium of major importance, which is used as a starter species for milk fermentation, a host for heterologous protein production, and a delivery platform for therapeutic molecules. Here, we report the functionality of natural transformation in L. lactis subsp. cremoris KW2 by the overproduction of the master competence regulator ComX. The developed procedure enables a flexible approach to modify the chromosome with single point mutation, sequence insertion, or sequence replacement. These results represent an important step for the genetic engineering of L. lactis that will facilitate the design of strains optimized for industrial applications. This will also help to discover natural regulatory mechanisms controlling competence in the genus Lactococcus.

Dataset Information

Modeling, Mutagenesis and In-silico Structural Stability Assay of the Model of Superoxide Dismutase of Lactococcus Lactis Subsp. Cremoris MG1363.

Publications

Modeling, Mutagenesis and <i>In-silico</i> Structural Stability Assay of the Model of Superoxide Dismutase of <i>Lactococcus Lactis</i> Subsp. <i>Cremoris</i> MG1363.

Similar Datasets

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