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.

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We report here the 4.57-Mb draft genome sequence of hydrocarbon-degrading Enterobacter cloacae strain S1:CND1 isolated from oil-contaminated soil in Guwahati, India. S1:CND1 contains 4,205 coding sequences and has a G+C content of 57.45%. This is the first report of the genome sequence of an E. cloacae adapted to an oil-contaminated environment.

18 Microbial remediation of oil polluted habitats remains one of the foremost methods for 19 restoration of petroleum hydrocarbon contaminated environments. The development of 20 effective bioremediation strategies however, require an extensive understanding of the 21 36 37 38 39 40 41 42 43 48 during production, operational use, and transportation. The development, effectiveness and 49 availability of technologies and strategies pose a significant challenge for the remediation, 50 rehabilitation and restoration of these contaminated environments. Many of the 51 technologies developed and in use for the restoration of oil contaminated environments 52 exploit the potential of biological systems, in particular microbial systems, to use these toxic 53 compounds as substrates for growth. Hence, much of the research conducted on 54 bioremediation has concentrated on the capabilities of a single or couple of microbes 55 exhibiting robust and effective growth using petroleum hydrocarbons. However, in the 56 environment, bioremediation is often a complex process involving co-metabolism, cross-57 induction, inhibition and non-interaction among microbes 1-3 , possibly as petroleum 58 hydrocarbons are a mixture of organic pollutants and therefore are used differently by 59 different microbes. These findings, along with others, established bioremediation as a 60 process mediated by a consortium of microbes rather than a few. Thus, characterization of 61 microbial communities of oil contaminated environments could potentially provide 62 guidelines for effective remediation and restoration of such environments. 63 Until recently, it was only possible to study a handful of microorganisms of interest 64 isolated from source materials (as blood, soil, water or air), given the restrictions of the 65 composition of culture media which cannot reflect and mimic the dynamic nutrient fluxes of 66 the source environment. Indeed, only 1% of microorganisms were found to be cultivable 67 4 using a set of media from the highly characterized soil rhizosphere 4 . The advent of high 68 throughput massively-parallel sequencing methods has however, allowed us to investigate 69 the entire complement of organisms inhabiting a certain environment. These next-70 generation sequencing methods (NGS) include a variety of methods to holistically study any 71 biological system such as amplicon sequencing (for variant identification and phylogenetic 72 surveys), whole genome shotgun sequencing (single organism genome and metagenomes) 73 and RNA-Seq (transcriptomes, metatranscriptomes and identification of non-regular RNAs). 74 These powerful methods have ushered in rapid advances in bioinformatics approaches 75 leading to development of software capable of handling huge amounts of data and offering 76 meaningful biological interpretations of the same. Although a technological breakthrough in 77 modern science, a number of NGS methods as metagenomic and transcriptomic/ 78 metatranscriptomic sequencing are still expensive and hence, most studies on ecologic...