Bioinformatic Approaches Including Predictive Metagenomic Profiling Reveal Characteristics of Bacterial Response to Petroleum Hydrocarbon Contamination in Diverse Environments
Abstract Microbial remediation of oil polluted habitats remains one of the foremost methods for restoration of petroleum hydrocarbon contaminated environments. The development of effective bioremediation strategies however, require an extensive understanding of the resident microbiome of these habit...
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doaj-9daf309cef0e424bb399df070f3b2dcf2020-12-08T01:38:14ZengNature Publishing GroupScientific Reports2045-23222017-04-017112210.1038/s41598-017-01126-3Bioinformatic Approaches Including Predictive Metagenomic Profiling Reveal Characteristics of Bacterial Response to Petroleum Hydrocarbon Contamination in Diverse EnvironmentsArghya Mukherjee0Bobby Chettri1James S. Langpoklakpam2Pijush Basak3Aravind Prasad4Ashis K. Mukherjee5Maitree Bhattacharyya6Arvind K. Singh7Dhrubajyoti Chattopadhyay8Department of Biotechnology, University of CalcuttaDepartment of Biochemistry, North-Eastern Hill UniversityDepartment of Biochemistry, North-Eastern Hill UniversityDepartment of Biochemistry, University of CalcuttaDr. D.Y.Patil Biotechnology and Bioinformatics InstituteDepartment of Molecular Biology and Biotechnology, Tezpur UniversityDepartment of Biochemistry, University of CalcuttaDepartment of Biochemistry, North-Eastern Hill UniversityDepartment of Biotechnology, University of CalcuttaAbstract Microbial remediation of oil polluted habitats remains one of the foremost methods for restoration of petroleum hydrocarbon contaminated environments. The development of effective bioremediation strategies however, require an extensive understanding of the resident microbiome of these habitats. Recent developments such as high-throughput sequencing has greatly facilitated the advancement of microbial ecological studies in oil polluted habitats. However, effective interpretation of biological characteristics from these large datasets remain a considerable challenge. In this study, we have implemented recently developed bioinformatic tools for analyzing 65 16S rRNA datasets from 12 diverse hydrocarbon polluted habitats to decipher metagenomic characteristics of the resident bacterial communities. Using metagenomes predicted from 16S rRNA gene sequences through PICRUSt, we have comprehensively described phylogenetic and functional compositions of these habitats and additionally inferred a multitude of metagenomic features including 255 taxa and 414 functional modules which can be used as biomarkers for effective distinction between the 12 oil polluted sites. Additionally, we show that significantly over-represented taxa often contribute to either or both, hydrocarbon degradation and additional important functions. Our findings reveal significant differences between hydrocarbon contaminated sites and establishes the importance of endemic factors in addition to petroleum hydrocarbons as driving factors for sculpting hydrocarbon contaminated bacteriomes.https://doi.org/10.1038/s41598-017-01126-3 |
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DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Arghya Mukherjee Bobby Chettri James S. Langpoklakpam Pijush Basak Aravind Prasad Ashis K. Mukherjee Maitree Bhattacharyya Arvind K. Singh Dhrubajyoti Chattopadhyay |
spellingShingle |
Arghya Mukherjee Bobby Chettri James S. Langpoklakpam Pijush Basak Aravind Prasad Ashis K. Mukherjee Maitree Bhattacharyya Arvind K. Singh Dhrubajyoti Chattopadhyay Bioinformatic Approaches Including Predictive Metagenomic Profiling Reveal Characteristics of Bacterial Response to Petroleum Hydrocarbon Contamination in Diverse Environments Scientific Reports |
author_facet |
Arghya Mukherjee Bobby Chettri James S. Langpoklakpam Pijush Basak Aravind Prasad Ashis K. Mukherjee Maitree Bhattacharyya Arvind K. Singh Dhrubajyoti Chattopadhyay |
author_sort |
Arghya Mukherjee |
title |
Bioinformatic Approaches Including Predictive Metagenomic Profiling Reveal Characteristics of Bacterial Response to Petroleum Hydrocarbon Contamination in Diverse Environments |
title_short |
Bioinformatic Approaches Including Predictive Metagenomic Profiling Reveal Characteristics of Bacterial Response to Petroleum Hydrocarbon Contamination in Diverse Environments |
title_full |
Bioinformatic Approaches Including Predictive Metagenomic Profiling Reveal Characteristics of Bacterial Response to Petroleum Hydrocarbon Contamination in Diverse Environments |
title_fullStr |
Bioinformatic Approaches Including Predictive Metagenomic Profiling Reveal Characteristics of Bacterial Response to Petroleum Hydrocarbon Contamination in Diverse Environments |
title_full_unstemmed |
Bioinformatic Approaches Including Predictive Metagenomic Profiling Reveal Characteristics of Bacterial Response to Petroleum Hydrocarbon Contamination in Diverse Environments |
title_sort |
bioinformatic approaches including predictive metagenomic profiling reveal characteristics of bacterial response to petroleum hydrocarbon contamination in diverse environments |
publisher |
Nature Publishing Group |
series |
Scientific Reports |
issn |
2045-2322 |
publishDate |
2017-04-01 |
description |
Abstract Microbial remediation of oil polluted habitats remains one of the foremost methods for restoration of petroleum hydrocarbon contaminated environments. The development of effective bioremediation strategies however, require an extensive understanding of the resident microbiome of these habitats. Recent developments such as high-throughput sequencing has greatly facilitated the advancement of microbial ecological studies in oil polluted habitats. However, effective interpretation of biological characteristics from these large datasets remain a considerable challenge. In this study, we have implemented recently developed bioinformatic tools for analyzing 65 16S rRNA datasets from 12 diverse hydrocarbon polluted habitats to decipher metagenomic characteristics of the resident bacterial communities. Using metagenomes predicted from 16S rRNA gene sequences through PICRUSt, we have comprehensively described phylogenetic and functional compositions of these habitats and additionally inferred a multitude of metagenomic features including 255 taxa and 414 functional modules which can be used as biomarkers for effective distinction between the 12 oil polluted sites. Additionally, we show that significantly over-represented taxa often contribute to either or both, hydrocarbon degradation and additional important functions. Our findings reveal significant differences between hydrocarbon contaminated sites and establishes the importance of endemic factors in addition to petroleum hydrocarbons as driving factors for sculpting hydrocarbon contaminated bacteriomes. |
url |
https://doi.org/10.1038/s41598-017-01126-3 |
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