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      Functional gene surveys from ocean drilling expeditions - a review and perspective

      1
      FEMS Microbiology Ecology
      Wiley

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          Abstract

          The vast majority of microbes inhabiting the subseafloor remain uncultivated and their energy sources unknown. Thus, a focus of ocean drilling expeditions over the past decade has been to characterize the distribution of microbes associated with specific metabolic reactions. An important question has been whether microbes involved in key microbial processes, such as sulfate reduction and methanogenesis, differ fundamentally from their counterparts in surface environments. To this end, functional genes of anaerobic methane cycling (mcrA), sulfate reduction (dsrAB), acetogenesis (fhs), and dehalorespiration (rdhA) have been examined. A compilation of existing functional gene data suggests that subseafloor microbes involved in anaerobic methane cycling, sulfate reduction, acetogenesis, and dehalorespiration are not fundamentally different from their counterparts in the surface world. Moreover, quantifications of mcrA and dsrAB suggest that, unless the majority of subseafloor microbes involved in methane cycling and sulfate reduction are too genetically divergent to be detected with conventional methods, these processes only support a small fraction (< 1%) of total microbial biomass in the deep biosphere. Ecological explanations for the observed trends, target processes and methods for future investigations, and strategies for tackling the unresolved issue of microbial contamination in samples obtained by ocean drilling are discussed. © 2012 Federation of European Microbiological Societies. Published by Blackwell Publishing Ltd. All rights reserved.

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          Most cited references204

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          Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy.

          The Ribosomal Database Project (RDP) Classifier, a naïve Bayesian classifier, can rapidly and accurately classify bacterial 16S rRNA sequences into the new higher-order taxonomy proposed in Bergey's Taxonomic Outline of the Prokaryotes (2nd ed., release 5.0, Springer-Verlag, New York, NY, 2004). It provides taxonomic assignments from domain to genus, with confidence estimates for each assignment. The majority of classifications (98%) were of high estimated confidence (> or = 95%) and high accuracy (98%). In addition to being tested with the corpus of 5,014 type strain sequences from Bergey's outline, the RDP Classifier was tested with a corpus of 23,095 rRNA sequences as assigned by the NCBI into their alternative higher-order taxonomy. The results from leave-one-out testing on both corpora show that the overall accuracies at all levels of confidence for near-full-length and 400-base segments were 89% or above down to the genus level, and the majority of the classification errors appear to be due to anomalies in the current taxonomies. For shorter rRNA segments, such as those that might be generated by pyrosequencing, the error rate varied greatly over the length of the 16S rRNA gene, with segments around the V2 and V4 variable regions giving the lowest error rates. The RDP Classifier is suitable both for the analysis of single rRNA sequences and for the analysis of libraries of thousands of sequences. Another related tool, RDP Library Compare, was developed to facilitate microbial-community comparison based on 16S rRNA gene sequence libraries. It combines the RDP Classifier with a statistical test to flag taxa differentially represented between samples. The RDP Classifier and RDP Library Compare are available online at http://rdp.cme.msu.edu/.
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            Real-time DNA sequencing from single polymerase molecules.

            We present single-molecule, real-time sequencing data obtained from a DNA polymerase performing uninterrupted template-directed synthesis using four distinguishable fluorescently labeled deoxyribonucleoside triphosphates (dNTPs). We detected the temporal order of their enzymatic incorporation into a growing DNA strand with zero-mode waveguide nanostructure arrays, which provide optical observation volume confinement and enable parallel, simultaneous detection of thousands of single-molecule sequencing reactions. Conjugation of fluorophores to the terminal phosphate moiety of the dNTPs allows continuous observation of DNA synthesis over thousands of bases without steric hindrance. The data report directly on polymerase dynamics, revealing distinct polymerization states and pause sites corresponding to DNA secondary structure. Sequence data were aligned with the known reference sequence to assay biophysical parameters of polymerization for each template position. Consensus sequences were generated from the single-molecule reads at 15-fold coverage, showing a median accuracy of 99.3%, with no systematic error beyond fluorophore-dependent error rates.
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              Continuous base identification for single-molecule nanopore DNA sequencing.

              A single-molecule method for sequencing DNA that does not require fluorescent labelling could reduce costs and increase sequencing speeds. An exonuclease enzyme might be used to cleave individual nucleotide molecules from the DNA, and when coupled to an appropriate detection system, these nucleotides could be identified in the correct order. Here, we show that a protein nanopore with a covalently attached adapter molecule can continuously identify unlabelled nucleoside 5'-monophosphate molecules with accuracies averaging 99.8%. Methylated cytosine can also be distinguished from the four standard DNA bases: guanine, adenine, thymine and cytosine. The operating conditions are compatible with the exonuclease, and the kinetic data show that the nucleotides have a high probability of translocation through the nanopore and, therefore, of not being registered twice. This highly accurate tool is suitable for integration into a system for sequencing nucleic acids and for analysing epigenetic modifications.
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                Author and article information

                Journal
                FEMS Microbiology Ecology
                FEMS Microbiol Ecol
                Wiley
                01686496
                April 2013
                April 2013
                January 07 2013
                : 84
                : 1
                : 1-23
                Affiliations
                [1 ]Center for Geomicrobiology; Institute of BioScience; Aarhus University; Aarhus; Denmark
                Article
                10.1111/1574-6941.12051
                23228016
                33c59cd4-30a6-4a07-a259-027f8266147a
                © 2013
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