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      Metagenomic psychrohalophilic xylanase from camel rumen investigated for bioethanol production from wheat bran using Bacillus subtilis AP

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          Abstract

          Bioethanol produced from lignocellulosic biomass is regarded as a clean and sustainable energy source. The recalcitrant structure of lignocellulose is a major drawback to affordable bioethanol production from plant biomass. In this study, a novel endo-1,4-xylanase, named Xyn-2, from the camel rumen metagenome, was characterized and evaluated for hydrolysis of agricultural wastes. The enzyme was identified as a psychrohalophilic xylanase with maximum activity at 20 °C, keeping 58% of the activity at 0 °C, and exhibiting twice as much activity in 0.5–4 M NaCl concentrations. Xyn-2 was able to hydrolyze wheat bran (100%), sunflower-seed shell (70%), wheat straw (56%), rice straw (56%), and rice bran (41%), in the relative order of efficiency. Besides, the ethanologenic B. subtilis AP was evaluated without and with Xyn-2 for bioethanol production from wheat bran. The strain was able to produce 5.5 g/L ethanol with a yield of 22.6% in consolidated bioprocessing (CBP). The contribution of Xyn-2 to ethanol production of B. subtilis AP was studied in an SSF system (simultaneous saccharification and fermentation) giving rise to a significant increase in ethanol production (p ≤ 0.001) to a final concentration of 7.3 g/L with a yield of 26.8%. The results revealed that the camel rumen metagenome might be an invaluable source of novel xylanolytic enzymes with potential application in lignocellulosic biomass valorization. At the same time, the results suggest that B. subtilis with a diverse carbon-source preference and sophisticated systems for production and secretion of enzymes might be a promising candidate for strain development for bioethanol production from plant biomass. It might be assumed that the fortification of B. subtilis enzymatic arsenal with select xylanolytic enzymes from camel rumen metagenome may have a great impact on bioethanol production.

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          SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing.

          The lion's share of bacteria in various environments cannot be cloned in the laboratory and thus cannot be sequenced using existing technologies. A major goal of single-cell genomics is to complement gene-centric metagenomic data with whole-genome assemblies of uncultivated organisms. Assembly of single-cell data is challenging because of highly non-uniform read coverage as well as elevated levels of sequencing errors and chimeric reads. We describe SPAdes, a new assembler for both single-cell and standard (multicell) assembly, and demonstrate that it improves on the recently released E+V-SC assembler (specialized for single-cell data) and on popular assemblers Velvet and SoapDeNovo (for multicell data). SPAdes generates single-cell assemblies, providing information about genomes of uncultivatable bacteria that vastly exceeds what may be obtained via traditional metagenomics studies. SPAdes is available online ( http://bioinf.spbau.ru/spades ). It is distributed as open source software.
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            Pfam: The protein families database in 2021

            Abstract The Pfam database is a widely used resource for classifying protein sequences into families and domains. Since Pfam was last described in this journal, over 350 new families have been added in Pfam 33.1 and numerous improvements have been made to existing entries. To facilitate research on COVID-19, we have revised the Pfam entries that cover the SARS-CoV-2 proteome, and built new entries for regions that were not covered by Pfam. We have reintroduced Pfam-B which provides an automatically generated supplement to Pfam and contains 136 730 novel clusters of sequences that are not yet matched by a Pfam family. The new Pfam-B is based on a clustering by the MMseqs2 software. We have compared all of the regions in the RepeatsDB to those in Pfam and have started to use the results to build and refine Pfam repeat families. Pfam is freely available for browsing and download at http://pfam.xfam.org/.
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              KEGG: integrating viruses and cellular organisms

              Abstract KEGG (https://www.kegg.jp/) is a manually curated resource integrating eighteen databases categorized into systems, genomic, chemical and health information. It also provides KEGG mapping tools, which enable understanding of cellular and organism-level functions from genome sequences and other molecular datasets. KEGG mapping is a predictive method of reconstructing molecular network systems from molecular building blocks based on the concept of functional orthologs. Since the introduction of the KEGG NETWORK database, various diseases have been associated with network variants, which are perturbed molecular networks caused by human gene variants, viruses, other pathogens and environmental factors. The network variation maps are created as aligned sets of related networks showing, for example, how different viruses inhibit or activate specific cellular signaling pathways. The KEGG pathway maps are now integrated with network variation maps in the NETWORK database, as well as with conserved functional units of KEGG modules and reaction modules in the MODULE database. The KO database for functional orthologs continues to be improved and virus KOs are being expanded for better understanding of virus-cell interactions and for enabling prediction of viral perturbations.
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                Author and article information

                Contributors
                shahbani@nigeb.ac.ir
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                17 May 2022
                17 May 2022
                2022
                : 12
                : 8152
                Affiliations
                GRID grid.419420.a, ISNI 0000 0000 8676 7464, Department of Energy and Environmental Biotechnology, , National Institute of Genetic Engineering and Biotechnology (NIGEB), ; Tehran, Iran
                Article
                11412
                10.1038/s41598-022-11412-4
                9114127
                35581279
                6fec340c-9801-4e70-9c24-e5497ec85b73
                © 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
                : 11 July 2021
                : 25 April 2022
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100006485, National Institute for Genetic Engineering and Biotechnology;
                Award ID: 680
                Award ID: 762
                Award Recipient :
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                © The Author(s) 2022

                Uncategorized
                biotechnology,industrial microbiology
                Uncategorized
                biotechnology, industrial microbiology

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