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      Microbial Communities Associated With Indigo Fermentation That Thrive in Anaerobic Alkaline Environments

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          Indigo fermentation, which depends on the indigo-reducing action of microorganisms, has traditionally been performed to dye textiles blue in Asia as well as in Europe. This fermentation process is carried out by naturally occurring microbial communities and occurs under alkaline, anaerobic conditions. Therefore, there is uncertainty regarding the fermentation process, and many unknown microorganisms thrive in this unique fermentation environment. Until recently, there was limited information available on bacteria associated with this fermentation process. Indigo reduction normally occurs from 4 days to 2 weeks after initiation of fermentation. However, the changes in the microbiota that occur during the transition to an indigo-reducing state have not been elucidated. Here, the structural changes in the bacterial community were estimated by PCR-based methods. On the second day of fermentation, a large change in the redox potential occurred. On the fourth day, distinct substitution of the genus Halomonas with the aerotolerant genus Amphibacillus was observed, corresponding to marked changes in indigo reduction. Under open-air conditions, indigo reduction during the fermentation process continued for 6 months on average. The microbiota, including indigo-reducing bacteria, was continuously replaced with other microbial communities that consisted of other types of indigo-reducing bacteria. A stable state consisting mainly of the genus Anaerobacillus was also observed in a long-term fermentation sample. The stability of the microbiota, proportion of indigo-reducing microorganisms, and appropriate diversity and microbiota within the fluid may play key factors in the maintenance of a reducing state during long-term indigo fermentation. Although more than 10 species of indigo-reducing bacteria were identified, the reduction mechanism of indigo particle is riddle. It can be predicted that the mechanism involves electrons, as byproducts of metabolism, being discarded by analogs mechanisms reported in bacterial extracellular solid Fe 3+ reduction under alkaline anaerobic condition.

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          MEGA7: Molecular Evolutionary Genetics Analysis Version 7.0 for Bigger Datasets.

          We present the latest version of the Molecular Evolutionary Genetics Analysis (Mega) software, which contains many sophisticated methods and tools for phylogenomics and phylomedicine. In this major upgrade, Mega has been optimized for use on 64-bit computing systems for analyzing larger datasets. Researchers can now explore and analyze tens of thousands of sequences in Mega The new version also provides an advanced wizard for building timetrees and includes a new functionality to automatically predict gene duplication events in gene family trees. The 64-bit Mega is made available in two interfaces: graphical and command line. The graphical user interface (GUI) is a native Microsoft Windows application that can also be used on Mac OS X. The command line Mega is available as native applications for Windows, Linux, and Mac OS X. They are intended for use in high-throughput and scripted analysis. Both versions are available from free of charge.
            • Record: found
            • Abstract: not found
            • Article: not found

            CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice

              • Record: found
              • Abstract: found
              • Article: not found

              A simple, fast, and accurate algorithm to estimate large phylogenies by maximum likelihood.

              The increase in the number of large data sets and the complexity of current probabilistic sequence evolution models necessitates fast and reliable phylogeny reconstruction methods. We describe a new approach, based on the maximum- likelihood principle, which clearly satisfies these requirements. The core of this method is a simple hill-climbing algorithm that adjusts tree topology and branch lengths simultaneously. This algorithm starts from an initial tree built by a fast distance-based method and modifies this tree to improve its likelihood at each iteration. Due to this simultaneous adjustment of the topology and branch lengths, only a few iterations are sufficient to reach an optimum. We used extensive and realistic computer simulations to show that the topological accuracy of this new method is at least as high as that of the existing maximum-likelihood programs and much higher than the performance of distance-based and parsimony approaches. The reduction of computing time is dramatic in comparison with other maximum-likelihood packages, while the likelihood maximization ability tends to be higher. For example, only 12 min were required on a standard personal computer to analyze a data set consisting of 500 rbcL sequences with 1,428 base pairs from plant plastids, thus reaching a speed of the same order as some popular distance-based and parsimony algorithms. This new method is implemented in the PHYML program, which is freely available on our web page:

                Author and article information

                Front Microbiol
                Front Microbiol
                Front. Microbiol.
                Frontiers in Microbiology
                Frontiers Media S.A.
                18 September 2018
                : 9
                1Bioproduction Research Institute, National Institute of Advanced Industrial Science and Technology , Sapporo, Japan
                2Department of Bioscience and Technology, School of Biological Science and Engineering, Tokai University , Hiratsuka-shi, Japan
                3Graduate School of Agriculture, Hokkaido University , Sapporo, Japan
                Author notes

                Edited by: Masahiro Ito, Toyo University, Japan

                Reviewed by: Kengo Inoue, University of Miyazaki, Japan; Masahiro Kamekura, Halophiles Research Institute, Japan

                *Correspondence: Isao Yumoto, i.yumoto@

                This article was submitted to Extreme Microbiology, a section of the journal Frontiers in Microbiology

                Copyright © 2018 Aino, Hirota, Okamoto, Tu, Matsuyama and Yumoto.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                Figures: 7, Tables: 1, Equations: 0, References: 65, Pages: 16, Words: 0
                Funded by: Japan Society for the Promotion of Science 10.13039/501100001691
                Award ID: 23570128
                Award ID: 16K07684


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