+1 Recommend
0 collections
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Coupled laboratory and field investigations resolve microbial interactions that underpin persistence in hydraulically fractured shales

      Read this article at

          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.


          Microorganisms persisting in hydraulically fractured shales must maintain osmotic balance in hypersaline fluids, gain energy in the absence of electron acceptors, and acquire carbon and nitrogen to synthesize cell building blocks. We provide evidence that that cofermentation of amino acids (Stickland reaction) meets all of these organismal needs, thus functioning as a keystone metabolism in enriched and natural microbial communities from hydraulically fractured shales. This amino acid-based metabolic network can be rationally designed to optimize biogenic methane yields and minimize undesirable chemistries in this engineered ecosystem. Our proposed ecological framework extends to the human gut and other protein-rich ecosystems, where the role of Stickland fermentations and their derived syntrophies play unrecognized roles in carbon and nitrogen turnover.


          Hydraulic fracturing is one of the industrial processes behind the surging natural gas output in the United States. This technology inadvertently creates an engineered microbial ecosystem thousands of meters below Earth’s surface. Here, we used laboratory reactors to perform manipulations of persisting shale microbial communities that are currently not feasible in field scenarios. Metaproteomic and metabolite findings from the laboratory were then corroborated using regression-based modeling performed on metagenomic and metabolite data from more than 40 produced fluids from five hydraulically fractured shale wells. Collectively, our findings show that Halanaerobium, Geotoga, and Methanohalophilus strain abundances predict a significant fraction of nitrogen and carbon metabolites in the field. Our laboratory findings also exposed cryptic predatory, cooperative, and competitive interactions that impact microorganisms across fractured shales. Scaling these results from the laboratory to the field identified mechanisms underpinning biogeochemical reactions, yielding knowledge that can be harnessed to potentially increase energy yields and inform management practices in hydraulically fractured shales.

          Related collections

          Most cited references 41

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

          Fermentation, hydrogen, and sulfur metabolism in multiple uncultivated bacterial phyla.

          BD1-5, OP11, and OD1 bacteria have been widely detected in anaerobic environments, but their metabolisms remain unclear owing to lack of cultivated representatives and minimal genomic sampling. We uncovered metabolic characteristics for members of these phyla, and a new lineage, PER, via cultivation-independent recovery of 49 partial to near-complete genomes from an acetate-amended aquifer. All organisms were nonrespiring anaerobes predicted to ferment. Three augment fermentation with archaeal-like hybrid type II/III ribulose-1,5-bisphosphate carboxylase-oxygenase (RuBisCO) that couples adenosine monophosphate salvage with CO(2) fixation, a pathway not previously described in Bacteria. Members of OD1 reduce sulfur and may pump protons using archaeal-type hydrogenases. For six organisms, the UGA stop codon is translated as tryptophan. All bacteria studied here may play previously unrecognized roles in hydrogen production, sulfur cycling, and fermentation of refractory sedimentary carbon.
            • Record: found
            • Abstract: not found
            • Article: not found

            Performance of some variable selection methods when multicollinearity is present

              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              EMIRGE: reconstruction of full-length ribosomal genes from microbial community short read sequencing data

              Recovery of ribosomal small subunit genes by assembly of short read community DNA sequence data generally fails, making taxonomic characterization difficult. Here, we solve this problem with a novel iterative method, based on the expectation maximization algorithm, that reconstructs full-length small subunit gene sequences and provides estimates of relative taxon abundances. We apply the method to natural and simulated microbial communities, and correctly recover community structure from known and previously unreported rRNA gene sequences. An implementation of the method is freely available at

                Author and article information

                Proc Natl Acad Sci U S A
                Proc. Natl. Acad. Sci. U.S.A
                Proceedings of the National Academy of Sciences of the United States of America
                National Academy of Sciences
                10 July 2018
                25 June 2018
                25 June 2018
                : 115
                : 28
                : E6585-E6594
                aDepartment of Microbiology, The Ohio State University , Columbus, OH 43210;
                bEnvironmental Molecular Science Laboratory, Pacific Northwest National Laboratory , Richland, WA 99352;
                cDepartment of Energy, Joint Genome Institute , Walnut Creek, CA 94589;
                dThe School of Earth Sciences, The Ohio State University , Columbus, OH 43210;
                eDepartment of Civil and Environmental Engineering, University of New Hampshire , Durham, NH 03824;
                fDepartment of Geology and Geography, West Virginia University , Morgantown, WV 26501
                Author notes
                1To whom correspondence should be addressed. Email: kwrighton@ .

                Edited by Edward F. DeLong, University of Hawaii at Manoa, Honolulu, HI, and approved May 15, 2018 (received for review January 8, 2018)

                Author contributions: M.A.B., S.S., T.R.C., D.R.C., P.J.M., M.S.L., M.J.W., and K.C.W. designed research; M.A.B., D.W.H., S.R., R.A.D., S.A.W., C.D.N., S.P., E.K.E., A.J.H., J.M.S., D.M.M., and K.C.W. performed research; M.A.B., D.W.H., S.R., C.D.N., S.P., E.K.E., and K.C.W. contributed new reagents/analytic tools; M.A.B., D.W.H., S.R., R.A.D., R.A.W., and K.C.W. analyzed data; and M.A.B., M.J.W., and K.C.W. wrote the paper.

                Copyright © 2018 the Author(s). Published by PNAS.

                This open access article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND).

                Page count
                Pages: 10
                PNAS Plus
                Biological Sciences
                PNAS Plus


                Comment on this article