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      Microbial ecology‐based engineering of Microbial Electrochemical Technologies

      review-article
      1 , , 1 , 1
      Microbial Biotechnology
      John Wiley and Sons Inc.

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          Summary

          Microbial ecology is devoted to the understanding of dynamics, activity and interaction of microorganisms in natural and technical ecosystems. Bioelectrochemical systems represent important technical ecosystems, where microbial ecology is of highest importance for their function. However, whereas aspects of, for example, materials and reactor engineering are commonly perceived as highly relevant, the study and engineering of microbial ecology are significantly underrepresented in bioelectrochemical systems. This shortfall may be assigned to a deficit on knowledge and power of these methods as well as the prerequisites for their thorough application. This article discusses not only the importance of microbial ecology for microbial electrochemical technologies but also shows which information can be derived for a knowledge‐driven engineering. Instead of providing a comprehensive list of techniques from which it is hard to judge the applicability and value of information for a respective one, this review illustrates the suitability of selected techniques on a case study. Thereby, best practice for different research questions is provided and a set of key questions for experimental design, data acquisition and analysis is suggested.

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          Most cited references66

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          Experimental and analytical tools for studying the human microbiome.

          The human microbiome substantially affects many aspects of human physiology, including metabolism, drug interactions and numerous diseases. This realization, coupled with ever-improving nucleotide sequencing technology, has precipitated the collection of diverse data sets that profile the microbiome. In the past 2 years, studies have begun to include sufficient numbers of subjects to provide the power to associate these microbiome features with clinical states using advanced algorithms, increasing the use of microbiome studies both individually and collectively. Here we discuss tools and strategies for microbiome studies, from primer selection to bioinformatics analysis.
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            Single cell activity reveals direct electron transfer in methanotrophic consortia.

            Multicellular assemblages of microorganisms are ubiquitous in nature, and the proximity afforded by aggregation is thought to permit intercellular metabolic coupling that can accommodate otherwise unfavourable reactions. Consortia of methane-oxidizing archaea and sulphate-reducing bacteria are a well-known environmental example of microbial co-aggregation; however, the coupling mechanisms between these paired organisms is not well understood, despite the attention given them because of the global significance of anaerobic methane oxidation. Here we examined the influence of interspecies spatial positioning as it relates to biosynthetic activity within structurally diverse uncultured methane-oxidizing consortia by measuring stable isotope incorporation for individual archaeal and bacterial cells to constrain their potential metabolic interactions. In contrast to conventional models of syntrophy based on the passage of molecular intermediates, cellular activities were found to be independent of both species intermixing and distance between syntrophic partners within consortia. A generalized model of electric conductivity between co-associated archaea and bacteria best fit the empirical data. Combined with the detection of large multi-haem cytochromes in the genomes of methanotrophic archaea and the demonstration of redox-dependent staining of the matrix between cells in consortia, these results provide evidence for syntrophic coupling through direct electron transfer.
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              Error bars in experimental biology

              Error bars commonly appear in figures in publications, but experimental biologists are often unsure how they should be used and interpreted. In this article we illustrate some basic features of error bars and explain how they can help communicate data and assist correct interpretation. Error bars may show confidence intervals, standard errors, standard deviations, or other quantities. Different types of error bars give quite different information, and so figure legends must make clear what error bars represent. We suggest eight simple rules to assist with effective use and interpretation of error bars.
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                Author and article information

                Contributors
                christin.koch@ufz.de
                Journal
                Microb Biotechnol
                Microb Biotechnol
                10.1111/(ISSN)1751-7915
                MBT2
                Microbial Biotechnology
                John Wiley and Sons Inc. (Hoboken )
                1751-7915
                14 August 2017
                January 2018
                : 11
                : 1 , Thematic Issue: Microbial Electrochemical technologies come of age ( doiID: 10.1111/mbt2.2018.11.issue-1 )
                : 22-38
                Affiliations
                [ 1 ] Department of Environmental Microbiology Helmholtz Centre for Environmental Research GmbH ‐ UFZ Permoserstraße 15 04318 Leipzig Germany
                Author notes
                [*] [* ]For correspondence. E‐mail christin.koch@ 123456ufz.de ; Tel. 0049 341 235 1363; Fax 0049 341 235 451363.
                Article
                MBT212802
                10.1111/1751-7915.12802
                5743830
                28805354
                231792b5-e575-4033-852f-03f2ce9f0c8b
                © 2017 The Authors. Microbial Biotechnology published by John Wiley & Sons Ltd and Society for Applied Microbiology.

                This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 30 April 2017
                : 11 July 2017
                : 12 July 2017
                Page count
                Figures: 3, Tables: 1, Pages: 17, Words: 11909
                Funding
                Funded by: BMBF
                Funded by: Helmholtz‐Association within the Research Renewable Energies
                Categories
                Minireview
                Minireview
                Custom metadata
                2.0
                mbt212802
                January 2018
                Converter:WILEY_ML3GV2_TO_NLMPMC version:5.2.8 mode:remove_FC converted:26.12.2017

                Biotechnology
                Biotechnology

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