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      Lake microbiome and trophy fluctuations of the ancient hemp rettery

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          Abstract

          Lake sediments not only store the long-term ecological information including pollen and microfossils but are also a source of sedimentary DNA ( sedDNA). Here, by the combination of traditional multi-proxy paleolimnological methods with the whole-metagenome shotgun-sequencing of sedDNA we were able to paint a comprehensive picture of the fluctuations in trophy and bacterial diversity and metabolism of a small temperate lake in response to hemp retting, across the past 2000 years. Hemp retting (HR), a key step in hemp fibre production, was historically carried out in freshwater reservoirs and had a negative impact on the lake ecosystems. In Lake Slone, we identified two HR events, during the late stage of the Roman and Early Medieval periods and correlated these to the increased trophy and imbalanced lake microbiome. The metagenomic analyses showed a higher abundance of Chloroflexi, Planctomycetes and Bacteroidetes and a functional shift towards anaerobic metabolism, including degradation of complex biopolymers such as pectin and cellulose, during HR episodes. The lake eutrophication during HR was linked to the allochthonous, rather than autochthonous carbon supply—hemp straws. We also showed that the identification of HR based on the palynological analysis of hemp pollen may be inconclusive and we suggest the employment of the fibre count analysis as an additional and independent proxy.

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          KEGG: kyoto encyclopedia of genes and genomes.

          M Kanehisa (2000)
          KEGG (Kyoto Encyclopedia of Genes and Genomes) is a knowledge base for systematic analysis of gene functions, linking genomic information with higher order functional information. The genomic information is stored in the GENES database, which is a collection of gene catalogs for all the completely sequenced genomes and some partial genomes with up-to-date annotation of gene functions. The higher order functional information is stored in the PATHWAY database, which contains graphical representations of cellular processes, such as metabolism, membrane transport, signal transduction and cell cycle. The PATHWAY database is supplemented by a set of ortholog group tables for the information about conserved subpathways (pathway motifs), which are often encoded by positionally coupled genes on the chromosome and which are especially useful in predicting gene functions. A third database in KEGG is LIGAND for the information about chemical compounds, enzyme molecules and enzymatic reactions. KEGG provides Java graphics tools for browsing genome maps, comparing two genome maps and manipulating expression maps, as well as computational tools for sequence comparison, graph comparison and path computation. The KEGG databases are daily updated and made freely available (http://www. genome.ad.jp/kegg/).
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            Prodigal: prokaryotic gene recognition and translation initiation site identification

            Background The quality of automated gene prediction in microbial organisms has improved steadily over the past decade, but there is still room for improvement. Increasing the number of correct identifications, both of genes and of the translation initiation sites for each gene, and reducing the overall number of false positives, are all desirable goals. Results With our years of experience in manually curating genomes for the Joint Genome Institute, we developed a new gene prediction algorithm called Prodigal (PROkaryotic DYnamic programming Gene-finding ALgorithm). With Prodigal, we focused specifically on the three goals of improved gene structure prediction, improved translation initiation site recognition, and reduced false positives. We compared the results of Prodigal to existing gene-finding methods to demonstrate that it met each of these objectives. Conclusion We built a fast, lightweight, open source gene prediction program called Prodigal http://compbio.ornl.gov/prodigal/. Prodigal achieved good results compared to existing methods, and we believe it will be a valuable asset to automated microbial annotation pipelines.
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              MEGAHIT: an ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph.

              MEGAHIT is a NGS de novo assembler for assembling large and complex metagenomics data in a time- and cost-efficient manner. It finished assembling a soil metagenomics dataset with 252 Gbps in 44.1 and 99.6 h on a single computing node with and without a graphics processing unit, respectively. MEGAHIT assembles the data as a whole, i.e. no pre-processing like partitioning and normalization was needed. When compared with previous methods on assembling the soil data, MEGAHIT generated a three-time larger assembly, with longer contig N50 and average contig length; furthermore, 55.8% of the reads were aligned to the assembly, giving a fourfold improvement. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
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                Author and article information

                Contributors
                agata.starosta@gmail.com
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                25 May 2022
                25 May 2022
                2022
                : 12
                : 8846
                Affiliations
                [1 ]GRID grid.29328.32, ISNI 0000 0004 1937 1303, ECOTECH-Complex and Institute of Biological Sciences, , Maria Curie-Sklodowska University, ; Lublin, Poland
                [2 ]GRID grid.413454.3, ISNI 0000 0001 1958 0162, Institute of Biochemistry and Biophysics, , Polish Academy of Science, ; Warsaw, Poland
                [3 ]GRID grid.445493.b, Polish-Japanese Academy of Information Technology, ; Warsaw, Poland
                [4 ]GRID grid.29328.32, ISNI 0000 0004 1937 1303, Institute of Earth and Environmental Sciences, , Maria Curie-Sklodowska University, ; Lublin, Poland
                [5 ]GRID grid.29328.32, ISNI 0000 0004 1937 1303, ECOTECH-Complex, , Maria Curie-Sklodowska University, ; Lublin, Poland
                [6 ]GRID grid.8585.0, ISNI 0000 0001 2370 4076, Department of Hydrology, Institute of Geography, , University of Gdansk, ; Gdansk, Poland
                [7 ]GRID grid.435463.3, ISNI 0000 0004 4677 2444, Institute of Geological Sciences Polish Academy of Sciences, ; Warsaw, Poland
                [8 ]GRID grid.29857.31, ISNI 0000 0001 2097 4281, Department of Biochemistry and Molecular Biology and the Huck Institutes of Life Sciences, , Pennsylvania State University, ; University Park, PA USA
                Article
                12761
                10.1038/s41598-022-12761-w
                9132974
                35614182
                8b8afbe2-6153-4c81-acac-45c1b0a13450
                © The Author(s) 2022

                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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 29 November 2021
                : 16 May 2022
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100001870, Fundacja na rzecz Nauki Polskiej;
                Award ID: POIR. 04.04.00-00-3E9C/17-00
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100004410, European Molecular Biology Organization;
                Award ID: Installation Grants (IG project 3914)
                Award Recipient :
                Categories
                Article
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                © The Author(s) 2022

                Uncategorized
                limnology,metagenomics
                Uncategorized
                limnology, metagenomics

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