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      Schrödinger’s microbes: Tools for distinguishing the living from the dead in microbial ecosystems

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          Abstract

          While often obvious for macroscopic organisms, determining whether a microbe is dead or alive is fraught with complications. Fields such as microbial ecology, environmental health, and medical microbiology each determine how best to assess which members of the microbial community are alive, according to their respective scientific and/or regulatory needs. Many of these fields have gone from studying communities on a bulk level to the fine-scale resolution of microbial populations within consortia. For example, advances in nucleic acid sequencing technologies and downstream bioinformatic analyses have allowed for high-resolution insight into microbial community composition and metabolic potential, yet we know very little about whether such community DNA sequences represent viable microorganisms. In this review, we describe a number of techniques, from microscopy- to molecular-based, that have been used to test for viability (live/dead determination) and/or activity in various contexts, including newer techniques that are compatible with or complementary to downstream nucleic acid sequencing. We describe the compatibility of these viability assessments with high-throughput quantification techniques, including flow cytometry and quantitative PCR (qPCR). Although bacterial viability-linked community characterizations are now feasible in many environments and thus are the focus of this critical review, further methods development is needed for complex environmental samples and to more fully capture the diversity of microbes (e.g., eukaryotic microbes and viruses) and metabolic states (e.g., spores) of microbes in natural environments.

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          Standard Methods for the Examination of Water and Wastewater

          "The Twenty-First Edition has continued the trend to revise methods as issues are identified and contains further refined quality assurance requirements in a number of Parts [sic] and new data on precision and bias. New methods have been added in Parts 2000, 4000, 5000, 6000, 7000, 8000, and 9000, and numerous methods have been revised. Details of these changes appear on the reverse of the title page for each part."--Pref. p. iv.
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            Exposure to environmental microorganisms and childhood asthma.

            Children who grow up in environments that afford them a wide range of microbial exposures, such as traditional farms, are protected from childhood asthma and atopy. In previous studies, markers of microbial exposure have been inversely related to these conditions. In two cross-sectional studies, we compared children living on farms with those in a reference group with respect to the prevalence of asthma and atopy and to the diversity of microbial exposure. In one study--PARSIFAL (Prevention of Allergy-Risk Factors for Sensitization in Children Related to Farming and Anthroposophic Lifestyle)--samples of mattress dust were screened for bacterial DNA with the use of single-strand conformation polymorphism (SSCP) analyses to detect environmental bacteria that cannot be measured by means of culture techniques. In the other study--GABRIELA (Multidisciplinary Study to Identify the Genetic and Environmental Causes of Asthma in the European Community [GABRIEL] Advanced Study)--samples of settled dust from children's rooms were evaluated for bacterial and fungal taxa with the use of culture techniques. In both studies, children who lived on farms had lower prevalences of asthma and atopy and were exposed to a greater variety of environmental microorganisms than the children in the reference group. In turn, diversity of microbial exposure was inversely related to the risk of asthma (odds ratio for PARSIFAL, 0.62; 95% confidence interval [CI], 0.44 to 0.89; odds ratio for GABRIELA, 0.86; 95% CI, 0.75 to 0.99). In addition, the presence of certain more circumscribed exposures was also inversely related to the risk of asthma; this included exposure to species in the fungal taxon eurotium (adjusted odds ratio, 0.37; 95% CI, 0.18 to 0.76) and to a variety of bacterial species, including Listeria monocytogenes, bacillus species, corynebacterium species, and others (adjusted odds ratio, 0.57; 95% CI, 0.38 to 0.86). Children living on farms were exposed to a wider range of microbes than were children in the reference group, and this exposure explains a substantial fraction of the inverse relation between asthma and growing up on a farm. (Funded by the Deutsche Forschungsgemeinschaft and the European Commission.).
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              Twenty-five years of quantitative PCR for gene expression analysis.

              Following its invention 25 years ago, PCR has been adapted for numerous molecular biology applications. Gene expression analysis by reverse-transcription quantitative PCR (RT-qPCR) has been a key enabling technology of the post-genome era. Since the founding of BioTechniques, this journal has been a resource for the improvements in qPCR technology, experimental design, and data analysis. qPCR and, more specifically, real-time qPCR has become a routine and robust approach for measuring the expression of genes of interest, validating microarray experiments, and monitoring biomarkers. The use of real-time qPCR has nearly supplanted other approaches (e.g., Northern blotting, RNase protection assays). This review examines the current state of qPCR for gene expression analysis now that the method has reached a mature stage of development and implementation. Specifically, the different fluorescent reporter technologies of real-time qPCR are discussed as well as the selection of endogenous controls. The conceptual framework for data analysis methods is also presented to demystify these analysis techniques. The future of qPCR remains bright as the technology becomes more rapid, cost-effective, easier to use, and capable of higher throughput.
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                Author and article information

                Contributors
                571-643-1667 , jbemerson@ucdavis.edu
                510-643-5483 , adamsri@berkeley.edu
                787-307-3290 , clarissebetancourt@gmail.com
                510-643-2225 , bbrooks@berkeley.edu
                970-261-0850 , coil.david@gmail.com
                216-374-2537 , katdah@ucdavis.edu
                510-207-4408 , holly.h.ganz@gmail.com
                847-467-4528 , erica.hartmann@northwestern.edu
                949-373-6752 , thsu@fas.harvard.edu , thsu@broadinstitute.org
                (510) 643-3722 , nicholas.justice@wholebiome.com
                650-604-5441 , ivan.g.paulinolima@nasa.gov
                303-847-5155 , jluongo1@gmail.com
                510-643-6498 , dlympero@berkeley.edu
                510-486-6901 , cgomezsilvan@lbl.gov
                b.rothschild-mancinelli16@imperial.ac.uk
                m.balk@uu.nl
                chuttenh@hsph.harvard.edu
                +49-208-40303383 , andreas.nocker@gmail.com
                818-393-7025 , vaishamp@jpl.nasa.gov
                650-604-6525 , Lynn.J.Rothschild@nasa.gov
                Journal
                Microbiome
                Microbiome
                Microbiome
                BioMed Central (London )
                2049-2618
                16 August 2017
                16 August 2017
                2017
                : 5
                : 86
                Affiliations
                [1 ]ISNI 0000 0001 2285 7943, GRID grid.261331.4, Department of Microbiology, , The Ohio State University, ; 484 West 12th Avenue, Columbus, OH 43210 USA
                [2 ]ISNI 0000 0001 2181 7878, GRID grid.47840.3f, Department of Plant & Microbial Biology, , University of California, Berkeley, ; 111 Koshland Hall, Berkeley, CA 94720 USA
                [3 ]ISNI 0000 0004 1936 8008, GRID grid.170202.6, Biology and the Built Environment Center, Institute of Ecology and Evolution, , University of Oregon, ; Eugene, OR 97403 USA
                [4 ]ISNI 0000 0004 1936 8008, GRID grid.170202.6, Institute of Ecology and Evolution, , University of Oregon, ; Eugene, OR 97403 USA
                [5 ]ISNI 0000 0001 2181 7878, GRID grid.47840.3f, Department of Earth and Planetary Sciences, , University of California, Berkeley, ; Berkeley, CA 94720 USA
                [6 ]ISNI 0000 0004 1936 9684, GRID grid.27860.3b, Genome Center, , University of California Davis, ; 451 Health Sciences Drive, Davis, CA 95616 USA
                [7 ]ISNI 0000 0001 2299 3507, GRID grid.16753.36, Department of Civil and Environmental Engineering, , Northwestern University, ; 2145 Sheridan Road, Evanston, IL 60208 USA
                [8 ]ISNI 000000041936754X, GRID grid.38142.3c, Department of Biostatistics, , Harvard T.H. Chan School of Public Health, ; 665 Huntington Avenue, Boston, MA 02115 USA
                [9 ]GRID grid.66859.34, , The Broad Institute of MIT and Harvard, ; 415 Main Street, Cambridge, MA 02142 USA
                [10 ]ISNI 0000 0001 2231 4551, GRID grid.184769.5, , Lawrence Berkeley National Lab, ; 1 Cyclotron Road, 955-512L, Berkeley, CA 94720 USA
                [11 ]ISNI 0000 0001 1955 7990, GRID grid.419075.e, Universities Space Research Association, , NASA Ames Research Center, ; Mail Stop 239-20, Building 239, room 377, Moffett Field, CA 94035-1000 USA
                [12 ]ISNI 0000000096214564, GRID grid.266190.a, Department of Mechanical Engineering, , University of Colorado at Boulder, ; 1111 Engineering Drive, 427 UCB, Boulder, CO 80309 USA
                [13 ]ISNI 0000 0001 2181 7878, GRID grid.47840.3f, Department of Environmental Science, Policy, and Management, , University of California, ; Berkeley, CA 94702 USA
                [14 ]ISNI 0000 0004 1936 7988, GRID grid.4305.2, Division of Biological Sciences, , The University of Edinburgh, ; Mayfield Road, Edinburgh, EH9 3JH UK
                [15 ]ISNI 0000000120346234, GRID grid.5477.1, Department of Earth Sciences – Petrology, Faculty of Geosciences, , Utrecht University, ; P.O. Box 80.021, 3508 TA Utrecht, The Netherlands
                [16 ]IWW Water Centre, Moritzstrasse 26, 45476 Mülheim an der Ruhr, Germany
                [17 ]ISNI 0000000107068890, GRID grid.20861.3d, Biotechnology and Planetary Protection Group, Jet Propulsion Laboratory, , California Institute of Technology, ; Pasadena, CA USA
                [18 ]ISNI 0000 0001 1955 7990, GRID grid.419075.e, Planetary Sciences and Astrobiology, , NASA Ames Research Center, ; Mail Stop 239-20, Building 239, room 361, Moffett Field, CA 94035-1000 USA
                [19 ]ISNI 0000 0004 1936 9684, GRID grid.27860.3b, Current Address: Department of Plant Pathology, , University of California, ; Davis, CA USA
                Article
                285
                10.1186/s40168-017-0285-3
                5558654
                28810907
                0a6d217c-af08-4cca-b7ac-8645ca5ac9b8
                © The Author(s). 2017

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided 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 Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 2 November 2016
                : 5 June 2017
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100000879, Alfred P. Sloan Foundation;
                Categories
                Review
                Custom metadata
                © The Author(s) 2017

                dna sequencing,flow cytometry,infectivity,live/dead,low biomass,metagenomics,microbial ecology,pma,rna,qpcr,viability

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