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      PCB-77 biodegradation potential of biosurfactant producing bacterial isolates recovered from contaminated soil

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          Abstract

          Polychlorinated biphenyls (PCBs) are persistent organic pollutants widely distributed in the environment and possess deleterious health effects. The main objective of the study was to obtain bacterial isolates from PCB-contaminated soil for enhanced biodegradation of PCB-77. Selective enrichment resulted in the isolation of 33 strains of PCB-contaminated soil nearby Bhilai steel plant, Chhattisgarh, India. Based on the prominent growth using biphenyl as the sole carbon source and the confirmation of its degradation by GC-MS/MS analysis, four isolates were selected for further study. The isolates identified by 16S rRNA gene sequencing were Pseudomonas aeruginosa MAPB-2, Pseudomonas plecoglossicida MAPB-6, Brucella anthropi MAPB-9, and Priestia megaterium MAPB-27. The isolate MAPB-9 showed a degradation of 66.15% biphenyl, while MAPB-2, MAPB-6, and MAPB-27 showed a degradation of 62.06, 57.02, and 56.55%, respectively in 48 h. Additionally, the degradation ability of these strains was enhanced with addition of co-metabolite glucose (0.2%) in the culture medium. Addition of glucose showed 100% degradation of biphenyl by MAPB-9, in 48 h, while MAPB-6, MAPB-2, and MAPB-27 showed 97.1, 67.5, and 53.3% degradation, respectively as analyzed by GC-MS/MS. Furthermore, in the presence of inducer, PCB-77 was found to be 59.89, 30.49, 27.19, and 4.43% degraded by MAPB-6, MAPB-9, MAPB-2, and MAPB-27, respectively in 7 d. The production of biosurfactants that aid in biodegradation process were observed in all the isolates. This was confirmed by ATR-FTIR analysis that showed the presence of major functional groups (CH 2, CH 3, CH, = CH 2, C–O–C, C-O) of the biosurfactant. The biosurfactants were further identified by HPTLC and GC-MS/MS analysis. Present study is the first to report PCB-77 degradation potential of Pseudomonas aeruginosa, B. anthropi, Pseudomonas plecoglossicida, and Priestia megaterium. Similarly, this is the first report on Pseudomonas plecoglossicida and Priestia megaterium for PCB biodegradation. Our results suggest that the above isolates can be used for the biodegradation of biphenyl and PCB-77 in PCB-contaminated soil.

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          Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method.

          The two most commonly used methods to analyze data from real-time, quantitative PCR experiments are absolute quantification and relative quantification. Absolute quantification determines the input copy number, usually by relating the PCR signal to a standard curve. Relative quantification relates the PCR signal of the target transcript in a treatment group to that of another sample such as an untreated control. The 2(-Delta Delta C(T)) method is a convenient way to analyze the relative changes in gene expression from real-time quantitative PCR experiments. The purpose of this report is to present the derivation, assumptions, and applications of the 2(-Delta Delta C(T)) method. In addition, we present the derivation and applications of two variations of the 2(-Delta Delta C(T)) method that may be useful in the analysis of real-time, quantitative PCR data. Copyright 2001 Elsevier Science (USA).
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            MEGA11: Molecular Evolutionary Genetics Analysis Version 11

            The Molecular Evolutionary Genetics Analysis (MEGA) software has matured to contain a large collection of methods and tools of computational molecular evolution. Here, we describe new additions that make MEGA a more comprehensive tool for building timetrees of species, pathogens, and gene families using rapid relaxed-clock methods. Methods for estimating divergence times and confidence intervals are implemented to use probability densities for calibration constraints for node-dating and sequence sampling dates for tip-dating analyses. They are supported by new options for tagging sequences with spatiotemporal sampling information, an expanded interactive Node Calibrations Editor , and an extended Tree Explorer to display timetrees. Also added is a Bayesian method for estimating neutral evolutionary probabilities of alleles in a species using multispecies sequence alignments and a machine learning method to test for the autocorrelation of evolutionary rates in phylogenies. The computer memory requirements for the maximum likelihood analysis are reduced significantly through reprogramming, and the graphical user interface has been made more responsive and interactive for very big data sets. These enhancements will improve the user experience, quality of results, and the pace of biological discovery. Natively compiled graphical user interface and command-line versions of MEGA11 are available for Microsoft Windows, Linux, and macOS from www.megasoftware.net .
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              A simple method for estimating evolutionary rates of base substitutions through comparative studies of nucleotide sequences.

              Some simple formulae were obtained which enable us to estimate evolutionary distances in terms of the number of nucleotide substitutions (and, also, the evolutionary rates when the divergence times are known). In comparing a pair of nucleotide sequences, we distinguish two types of differences; if homologous sites are occupied by different nucleotide bases but both are purines or both pyrimidines, the difference is called type I (or "transition" type), while, if one of the two is a purine and the other is a pyrimidine, the difference is called type II (or "transversion" type). Letting P and Q be respectively the fractions of nucleotide sites showing type I and type II differences between two sequences compared, then the evolutionary distance per site is K = -(1/2) ln [(1-2P-Q) square root of 1-2Q]. The evolutionary rate per year is then given by k = K/(2T), where T is the time since the divergence of the two sequences. If only the third codon positions are compared, the synonymous component of the evolutionary base substitutions per site is estimated by K'S = -(1/2) ln (1-2P-Q). Also, formulae for standard errors were obtained. Some examples were worked out using reported globin sequences to show that synonymous substitutions occur at much higher rates than amino acid-altering substitutions in evolution.
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                Author and article information

                Contributors
                Journal
                Front Microbiol
                Front Microbiol
                Front. Microbiol.
                Frontiers in Microbiology
                Frontiers Media S.A.
                1664-302X
                26 September 2022
                2022
                : 13
                : 952374
                Affiliations
                [1] 1Department of Biological Sciences, Birla Institute of Technology and Science Pilani , Pilani, Rajasthan, India
                [2] 2Department of Pharmacy, Birla Institute of Technology and Science Pilani , Pilani, Rajasthan, India
                [3] 3Department of Plant Biology, Institute of Environmental Biology, Wrocław University of Environmental and Life Sciences , Wrocław, Poland
                [4] 4Biotecnología de Macromoléculas, Instituto de Productos Naturales y Agrobiología (IPNA-CSIC) , San Cristóbal de la Laguna, Spain
                Author notes

                Edited by: Chien Sen Liao, I-Shou University, Taiwan

                Reviewed by: Mohamed Mannaa, Cairo University, Egypt; Wen-Ching Chen, National Chung Hsing University, Taiwan

                *Correspondence: Prabhat N. Jha, prabhatjha@ 123456pilani.bits-pilani.ac.in
                José Manuel Pérez de la Lastra, jm.perezdelalastra@ 123456csic.es

                This article was submitted to Microbiotechnology, a section of the journal Frontiers in Microbiology

                Article
                10.3389/fmicb.2022.952374
                9549355
                36225351
                aee64bc0-5c4d-49f6-98fe-4cbbae1be932
                Copyright © 2022 Sandhu, Paul, Proćków, de la Lastra and Jha.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 25 May 2022
                : 18 August 2022
                Page count
                Figures: 8, Tables: 4, Equations: 2, References: 81, Pages: 18, Words: 11193
                Categories
                Microbiology
                Original Research

                Microbiology & Virology
                polychlorinated biphenyl,biodegradation,biosurfactant,pseudomonas aeruginosa,pseudomonas plecoglossicida,priestia megaterium,brucella anthropi

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