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      Methane utilization in Methylomicrobium alcaliphilum 20Z R: a systems approach

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          Abstract

          Biological methane utilization, one of the main sinks of the greenhouse gas in nature, represents an attractive platform for production of fuels and value-added chemicals. Despite the progress made in our understanding of the individual parts of methane utilization, our knowledge of how the whole-cell metabolic network is organized and coordinated is limited. Attractive growth and methane-conversion rates, a complete and expert-annotated genome sequence, as well as large enzymatic, 13C-labeling, and transcriptomic datasets make Methylomicrobium alcaliphilum 20Z R an exceptional model system for investigating methane utilization networks. Here we present a comprehensive metabolic framework of methane and methanol utilization in M. alcaliphilum 20Z R. A set of novel metabolic reactions governing carbon distribution across central pathways in methanotrophic bacteria was predicted by in-silico simulations and confirmed by global non-targeted metabolomics and enzymatic evidences. Our data highlight the importance of substitution of ATP-linked steps with PPi-dependent reactions and support the presence of a carbon shunt from acetyl-CoA to the pentose-phosphate pathway and highly branched TCA cycle. The diverged TCA reactions promote balance between anabolic reactions and redox demands. The computational framework of C 1-metabolism in methanotrophic bacteria can represent an efficient tool for metabolic engineering or ecosystem modeling.

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          Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox v2.0.

          Over the past decade, a growing community of researchers has emerged around the use of constraint-based reconstruction and analysis (COBRA) methods to simulate, analyze and predict a variety of metabolic phenotypes using genome-scale models. The COBRA Toolbox, a MATLAB package for implementing COBRA methods, was presented earlier. Here we present a substantial update of this in silico toolbox. Version 2.0 of the COBRA Toolbox expands the scope of computations by including in silico analysis methods developed since its original release. New functions include (i) network gap filling, (ii) (13)C analysis, (iii) metabolic engineering, (iv) omics-guided analysis and (v) visualization. As with the first version, the COBRA Toolbox reads and writes systems biology markup language-formatted models. In version 2.0, we improved performance, usability and the level of documentation. A suite of test scripts can now be used to learn the core functionality of the toolbox and validate results. This toolbox lowers the barrier of entry to use powerful COBRA methods.
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            Simultaneously mitigating near-term climate change and improving human health and food security.

            Tropospheric ozone and black carbon (BC) contribute to both degraded air quality and global warming. We considered ~400 emission control measures to reduce these pollutants by using current technology and experience. We identified 14 measures targeting methane and BC emissions that reduce projected global mean warming ~0.5°C by 2050. This strategy avoids 0.7 to 4.7 million annual premature deaths from outdoor air pollution and increases annual crop yields by 30 to 135 million metric tons due to ozone reductions in 2030 and beyond. Benefits of methane emissions reductions are valued at $700 to $5000 per metric ton, which is well above typical marginal abatement costs (less than $250). The selected controls target different sources and influence climate on shorter time scales than those of carbon dioxide-reduction measures. Implementing both substantially reduces the risks of crossing the 2°C threshold.
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              Whole-genome sequencing identifies common-to-rare variants associated with human blood metabolites

              Amalio Telenti, Craig Venter and colleagues report common, low-frequency and rare variants associated with blood metabolite levels using whole-genome sequencing and comprehensive metabolite profiling in 1,960 individuals. They identify 246 metabolites whose levels are associated with genetic variation at 101 loci.
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                Author and article information

                Contributors
                mkalyuzhnaya@mail.sdsu.edu
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                6 February 2018
                6 February 2018
                2018
                : 8
                : 2512
                Affiliations
                [1 ]ISNI 0000 0001 0790 1491, GRID grid.263081.e, Biology Department and Viral Information Institute, , San Diego State University, ; San Diego, USA
                [2 ]GRID grid.418953.2, Institute of Cytology and Genetics and Novosibirsk State University, ; Novosibirsk, Russia
                [3 ]GRID grid.429438.0, Metabolon, ; Inc. 617 Davis Drive, Suite 400, Durham, NC 27713 USA
                [4 ]ISNI 0000 0001 2199 3636, GRID grid.419357.d, National Bioenergy Center, , National Renewable Energy Laboratory, ; 15013 Denver West Parkway, MS 3323, Golden, CO 80401 United States
                Article
                20574
                10.1038/s41598-018-20574-z
                5802761
                29410419
                a7d6fc37-1e6f-4636-8282-0f932a6edff9
                © The Author(s) 2018

                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 September 2017
                : 22 January 2018
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