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      Antibiotic Resistome Biomarkers associated to the Pelagic Sediments of the Gulfs of Kathiawar Peninsula and Arabian Sea

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          Abstract

          Antibiotic resistance has been one of the most persistent global issue. Specifically, marine microbiomes have served as complex reservoirs of antibiotic resistant genes. Molecular advancements have enabled exploration of the uncultured microbial portion from hitherto difficult to sample niches such as deeper oceans. The Gulfs of Kathiawar Peninsula have been known for their unique properties like extreme tidal variations, different sediment textures and physicochemical variations. Pelagic sediment cores across four coordinates each of the Gulf of Kutch, Gulf of Khambhat and an open Arabian Sea were collected, processed for metagenomic sequencing and assessed for antibiotic and metal resistome. The dominant genes were mostly resistant to macrolides, glycopeptides and tetracycline drugs. Studied samples divided into three clusters based on their resistome with carA, macB, bcrA, taeA, srmB, tetA, oleC and sav1866 among the abundant genes. Samples from creek of Gulf of Kutch and mouth of Gulf of Khambhat were most diverse in resistance gene profile. Biomarkers observed include gyrA mutation conferring resistance gene in the Arabian Sea; Proteobacteria species in Gulf of Kutch and Arabian sea; while Aquificae, Acidobacteria and Firmicutes species in the Gulf of Khambhat. Region-wise differentially abundant 23 genes and 3 taxonomic biomarkers were proposed for antibiotic resistance monitoring.

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          Metagenomic and network analysis reveal wide distribution and co-occurrence of environmental antibiotic resistance genes.

          A metagenomic approach and network analysis was used to investigate the wide-spectrum profiles of antibiotic resistance genes (ARGs) and their co-occurrence patterns in 50 samples from 10 typical environments. In total, 260 ARG subtypes belonging to 18 ARG types were detected with an abundance range of 5.4 × 10(-6)-2.2 × 10(-1) copy of ARG per copy of 16S-rRNA gene. The trend of the total ARG abundances in environments matched well with the levels of anthropogenic impacts on these environments. From the less impacted environments to the seriously impacted environments, the total ARG abundances increased up to three orders of magnitude, that is, from 3.2 × 10(-3) to 3.1 × 10(0) copy of ARG per copy of 16S-rRNA gene. The abundant ARGs were associated with aminoglycoside, bacitracin, β-lactam, chloramphenicol, macrolide-lincosamide-streptogramin, quinolone, sulphonamide and tetracycline, in agreement with the antibiotics extensively used in human medicine or veterinary medicine/promoters. The widespread occurrences and abundance variation trend of vancomycin resistance genes in different environments might imply the spread of vancomycin resistance genes because of the selective pressure resulting from vancomycin use. The simultaneous enrichment of 12 ARG types in adult chicken faeces suggests the coselection of multiple ARGs in this production system. Non-metric multidimensional scaling analysis revealed that samples belonging to the same environment generally possessed similar ARG compositions. Based on the co-occurrence pattern revealed by network analysis, tetM and aminoglycoside resistance protein, the hubs of the ARG network, are proposed to be indicators to quantitatively estimate the abundance of 23 other co-occurring ARG subtypes by power functions.
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            FQC Dashboard: integrates FastQC results into a web-based, interactive, and extensible FASTQ quality control tool

            Abstract Summary FQC is software that facilitates quality control of FASTQ files by carrying out a QC protocol using FastQC, parsing results, and aggregating quality metrics into an interactive dashboard designed to richly summarize individual sequencing runs. The dashboard groups samples in dropdowns for navigation among the data sets, utilizes human-readable configuration files to manipulate the pages and tabs, and is extensible with CSV data. Availability and implementation FQC is implemented in Python 3 and Javascript, and is maintained under an MIT license. Documentation and source code is available at: https://github.com/pnnl/fqc. Contact joseph.brown@pnnl.gov
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              Bacteria subsisting on antibiotics.

              Antibiotics are a crucial line of defense against bacterial infections. Nevertheless, several antibiotics are natural products of microorganisms that have as yet poorly appreciated ecological roles in the wider environment. We isolated hundreds of soil bacteria with the capacity to grow on antibiotics as a sole carbon source. Of 18 antibiotics tested, representing eight major classes of natural and synthetic origin, 13 to 17 supported the growth of clonal bacteria from each of 11 diverse soils. Bacteria subsisting on antibiotics are surprisingly phylogenetically diverse, and many are closely related to human pathogens. Furthermore, each antibiotic-consuming isolate was resistant to multiple antibiotics at clinically relevant concentrations. This phenomenon suggests that this unappreciated reservoir of antibiotic-resistance determinants can contribute to the increasing levels of multiple antibiotic resistance in pathogenic bacteria.
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                Author and article information

                Contributors
                chandu.avi@gmail.com
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                21 November 2019
                21 November 2019
                2019
                : 9
                : 17281
                Affiliations
                [1 ]ISNI 0000 0000 9818 9921, GRID grid.411684.e, Department of Marine Science, , Maharaja Krishnakumarsinhji Bhavnagar University, ; Bhavnagar, 364-001 Gujarat India
                [2 ]ISNI 0000 0000 9818 9921, GRID grid.411684.e, Department of Life Sciences, , Maharaja Krishnakumarsinhji Bhavnagar University, ; Bhavnagar, 364-001 Gujarat India
                [3 ]Government Science College, Bhakta Kavi Narsinh Mehta University, Veraval, 362-265 Gujarat India
                [4 ]ISNI 0000 0004 1794 2950, GRID grid.411373.3, Department of Animal Biotechnology, College of Veterinary & Animal Husbandry, , Anand Agricultural University, ; Anand, 388-001 Gujarat India
                [5 ]ISNI 0000 0001 0658 0454, GRID grid.464868.0, Gujarat Biotechnology Research Centre (GBRC), , Department of Science & Technology, Government of Gujarat, ; Gandhinagar, 382-011 Gujarat India
                Article
                53832
                10.1038/s41598-019-53832-9
                6872816
                31754151
                161f1921-2c9f-49a3-b892-a96e8dc6d521
                © The Author(s) 2019

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 8 March 2019
                : 4 November 2019
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100001843, DST | Science and Engineering Research Board (SERB);
                Award ID: PDF/2016/001239
                Award Recipient :
                Categories
                Article
                Custom metadata
                © The Author(s) 2019

                Uncategorized
                marine biology,high-throughput screening
                Uncategorized
                marine biology, high-throughput screening

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