DOI QR코드

DOI QR Code

Biphasic Study to Characterize Agricultural Biogas Plants by High-Throughput 16S rRNA Gene Amplicon Sequencing and Microscopic Analysis

  • Maus, Irena (Bielefeld University, Center for Biotechnology (CeBiTec), Genome Research and Systems Biology) ;
  • Kim, Yong Sung (Hamburg University of Applied Sciences (HAW), Faculty Life Sciences / Research Center "Biomass Utilization Hamburg", Laboratory for Applied Microbiology) ;
  • Wibberg, Daniel (Bielefeld University, Center for Biotechnology (CeBiTec), Genome Research and Systems Biology) ;
  • Stolze, Yvonne (Bielefeld University, Center for Biotechnology (CeBiTec), Genome Research and Systems Biology) ;
  • Off, Sandra (Hamburg University of Applied Sciences (HAW), Faculty Life Sciences / Research Center "Biomass Utilization Hamburg", Laboratory for Applied Microbiology) ;
  • Antonczyk, Sebastian (Hamburg University of Applied Sciences (HAW), Faculty Life Sciences / Research Center "Biomass Utilization Hamburg", Laboratory for Applied Microbiology) ;
  • Puhler, Alfred (Bielefeld University, Center for Biotechnology (CeBiTec), Genome Research and Systems Biology) ;
  • Scherer, Paul (Hamburg University of Applied Sciences (HAW), Faculty Life Sciences / Research Center "Biomass Utilization Hamburg", Laboratory for Applied Microbiology) ;
  • Schluter, Andreas (Bielefeld University, Center for Biotechnology (CeBiTec), Genome Research and Systems Biology)
  • Received : 2016.05.31
  • Accepted : 2016.10.09
  • Published : 2017.02.28

Abstract

Process surveillance within agricultural biogas plants (BGPs) was concurrently studied by high-throughput 16S rRNA gene amplicon sequencing and an optimized quantitative microscopic fingerprinting (QMF) technique. In contrast to 16S rRNA gene amplicons, digitalized microscopy is a rapid and cost-effective method that facilitates enumeration and morphological differentiation of the most significant groups of methanogens regarding their shape and characteristic autofluorescent factor 420. Moreover, the fluorescence signal mirrors cell vitality. In this study, four different BGPs were investigated. The results indicated stable process performance in the mesophilic BGPs and in the thermophilic reactor. Bacterial subcommunity characterization revealed significant differences between the four BGPs. Most remarkably, the genera Defluviitoga and Halocella dominated the thermophilic bacterial subcommunity, whereas members of another taxon, Syntrophaceticus, were found to be abundant in the mesophilic BGP. The domain Archaea was dominated by the genus Methanoculleus in all four BGPs, followed by Methanosaeta in BGP1 and BGP3. In contrast, Methanothermobacter members were highly abundant in the thermophilic BGP4. Furthermore, a high consistency between the sequencing approach and the QMF method was shown, especially for the thermophilic BGP. The differences elucidated that using this biphasic approach for mesophilic BGPs provided novel insights regarding disaggregated single cells of Methanosarcina and Methanosaeta species. Both dominated the archaeal subcommunity and replaced coccoid Methanoculleus members belonging to the same group of Methanomicrobiales that have been frequently observed in similar BGPs. This work demonstrates that combining QMF and 16S rRNA gene amplicon sequencing is a complementary strategy to describe archaeal community structures within biogas processes.

Keywords

References

  1. Lebuhn M, Munk B, Effenberger M. 2014. Agricultural biogas production in Germany - from practice to microbiology basics. Energy Sustain. Soc. 4: 10. https://doi.org/10.1186/2192-0567-4-10
  2. Ridley CE, Clark CM, Leduc SD, Bierwagen BG, Lin BB, Mehl A, Tobias DA. 2012. Biofuels: network analysis of the literature reveals key environmental and economic unknowns. Environ. Sci. Technol. 46: 1309-1315. https://doi.org/10.1021/es2023253
  3. Weiland P. 2010. Biogas production: current state and perspectives. Appl. Microbiol. Biotechnol. 85: 849-860. https://doi.org/10.1007/s00253-009-2246-7
  4. Ali Shah F, Mahmood Q, Maroof Shah M, Pervez A, Ahmad Asad S. 2014. Microbial ecology of anaerobic digesters: the key players of anaerobiosis. Sci. World J. 2014: e183752.
  5. Demirel B, Scherer PA. 2008. The roles of acetotrophic and hydrogenotrophic methanogens during anaerobic conversion of biomass to methane: a review. Rev. Environ. Sci. Biotechnol. 7: 173-190. https://doi.org/10.1007/s11157-008-9131-1
  6. Stolze Y, Zakrzewski M, Maus I, Eikmeyer F, Jaenicke S, Rottmann N, et al. 2015. Comparative metagenomics of biogas-producing microbial communities from productionscale biogas plants operating under wet or dry fermentation conditions. Biotechnol. Biofuels 8: 8-14. https://doi.org/10.1186/s13068-014-0191-x
  7. Krakat N, Schmidt S, Scherer PA. 2010. The mesophilic fermentation of renew able biomass - does hydraulic retention time regulate diversity of methanogens? Appl. Environ. Microbiol. 76: 6322-6326. https://doi.org/10.1128/AEM.00927-10
  8. Jaenicke S, Ander C, Bekel T, Bisdorf R, Droge M, Gartemann KH, et al. 2011. Comparative and joint analysis of two metagenomic datasets from a biogas fermenter obtained by 454-pyrosequencing. PLoS One 6: e14519. https://doi.org/10.1371/journal.pone.0014519
  9. Krober M, Bekel T, Diaz NN, Goesmann A, Jaenicke S, Krause L, et al. 2009. Phylogenetic characterization of a biogas plant microbial community integrating clone library 16S-rDNA sequences and metagenome sequence data obtained by 454-pyrosequencing. J. Biotechnol. 142: 38-49. https://doi.org/10.1016/j.jbiotec.2009.02.010
  10. Theuerl S, Kohrs F, Benndorf D, Maus I, Wibberg D, Schluter A, et al. 2015. Community shifts in a well-operating agricultural biogas plant: how process variations are handled by the microbiome. Appl. Microbiol. Biotechnol. 18: 7791-7803.
  11. Eikmeyer FG, Rademacher A, Hanreich A, Hennig M, Jaenicke S, Maus I, et al. 2013. Detailed analysis of metagenome datasets obtained from biogas-producing microbial communities residing in biogas reactors does not indicate the presence of putative pathogenic microorganisms. Biotechnol. Biofuels 6: 49. https://doi.org/10.1186/1754-6834-6-49
  12. Zakrzewski M, Goesmann A, Jaenicke S, Junemann S, Eikmeyer F, Szczepanowski R, et al. 2012. Profiling of the metabolically active community from a production-scale biogas plant by means of high-throughput metatranscriptome sequencing. J. Biotechnol. 158: 248-258. https://doi.org/10.1016/j.jbiotec.2012.01.020
  13. Schluter A, Bekel T, Diaz NN, Dondrup M, Eichenlaub R, Gartemann KH, et al. 2008. The metagenome of a biogasproducing microbial community of a production-scale biogas plant fermenter analysed by the 454-pyrosequencing technology. J. Biotechnol. 136: 77-90. https://doi.org/10.1016/j.jbiotec.2008.05.008
  14. Kim YS, Westerholm M, Scherer P. 2014. Dual investigation of methanogenic processes by quantitative PCR and quantitative microscopic fingerprinting (QMF). FEMS Microbiol. 360: 76-84. https://doi.org/10.1111/1574-6968.12592
  15. Scherer PA, Neumann L, Kim Y. 2012. Schnellmethode zur biologischen Aktivitatsbestimmung in Biogasanlagen - Quantitativer mikroskopischer Fingerabdruck (QMF), pp. 124-137. In IHK (ed.). Biogas Potenziale: Erkennen, Erforschen, Erwirtschaften. Bornimer Agrartechnische Berichte, Potsdam-Bornim, Germany.
  16. Maus I, Cibis KG, Bremges A, Stolze Y, Wibberg D, Tomazetto D, et al. 2016. Genomic characterization of Defluviitoga tunisiensis L3, a key hydrolytic bacterium in a thermophilic biogas plant and its abundance as determined by metagenome fragment recruitment. J. Biotechnol. 232: 50-60. https://doi.org/10.1016/j.jbiotec.2016.05.001
  17. Stolze Y, Bremges A, Rumming M, Henke C, Maus I, Pühler A, et al. 2016. Identification and genome reconstruction of distinct taxa in microbiomes from four different productionscale biogas plants. Biotechnol. Biofuels 9: 156. https://doi.org/10.1186/s13068-016-0565-3
  18. Raposo F, Borja R, Mumme J, Orupold K, Esteves S, Noguerol-Arias J, et al. 2013. First international comparative study of volatile fatty acids in aqueous samples by chromatographic techniques: evaluating sources of error. Trends Anal. Chem. 51: 127-144. https://doi.org/10.1016/j.trac.2013.07.007
  19. VDI4630. 2006. Fermentation of organic materials: characterization of the substrate, sampling, collection of material data, fermentation tests. Verein Deutscher Ingenieure, Dusseldorf, ICS13.030.30;27.190. Available from http://www.vdi.eu/uploads/tx_vdirili/pdf/9703240.pdf. Accessed March 10, 2016.
  20. Hansen KH, Angelidaki I, Ahring BK. 1998. Anaerobic digestion of swine manure: inhibition by ammonia. Water Res. 32: 5-12. https://doi.org/10.1016/S0043-1354(97)00201-7
  21. Scherer PA. 2007. Operational analytics of biogas plants to improve efficiency and to ensure process stability, pp. 77-84. In IBBK (ed.). Progress in Biogas. Kirchberg, Germany.
  22. KTBL. 2013. Faustzahlen Biogas. 3. Auflage. Kuratorium fur Technik und Bauwesen in der Landwirtschaft eV (KTBL) & Fachagentur Nachwachsender Rohstoffe (FNR), Darmstadt, Germany.
  23. Takahashi S, Tomita J, Nishioka K, Hisada T, Nishijima M. 2014. Development of a prokaryotic universal primer for simultaneous analysis of Bacteria and Archaea using nextgeneration sequencing. PLoS One 9: e105592. https://doi.org/10.1371/journal.pone.0105592
  24. Magoc T, Salzberg SL. 2011. FLASH: fast length adjustment of short reads to improve genome assemblies. Bioinformatics 27: 2957-2963. https://doi.org/10.1093/bioinformatics/btr507
  25. Edgar RC. 2010. Search and clustering of magnitude faster than BLAST. Bioinformatics 26: 2460-2461. https://doi.org/10.1093/bioinformatics/btq461
  26. Edgar RC. 2013. UPARSE: highly accurate OTU sequences from microbial amplicon reads. Nat. Methods 10: 996-998. https://doi.org/10.1038/nmeth.2604
  27. Wang Q, Garrity GM, Tiedje JM, Cole JR. 2007. Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Appl. Environ. Microbiol. 73: 5261-5267. https://doi.org/10.1128/AEM.00062-07
  28. Liebe S, Wibberg D, Winkler A, Puhler A, Schluter A, Varrelmann M. 2016. Taxonomic analysis of the microbial community in stored sugar beets using high-throughput sequencing of different marker genes. FEMS Microbiol Ecol. 92. DOI: 10.1093/femsec/fiw004.
  29. Maus I, Cibis KG, Wibberg D, Winkler A, Stolze Y, König H, et al. 2015. Complete genome sequence of the strain Defluviitoga tunisiensis L3, isolated from a thermophilic, production-scale biogas plant. J. Biotechnol. 203: 17-18. https://doi.org/10.1016/j.jbiotec.2015.03.006
  30. Metsalu T, Vilo J. 2015. ClustVis: a web tool for visualizing clustering of multivariate data using principal component analysis and heatmap. Nucleic Acids Res. 43: W566-W570. https://doi.org/10.1093/nar/gkv468
  31. Paulson JN, Stine OC, Bravo HC, Pop M. 2013. Differential abundance analysis for microbial marker-gene surveys. Nat. Methods 10: 1200-1202. https://doi.org/10.1038/nmeth.2658
  32. Nielsen HB, Uellendahlm H, Ahring BK. 2007. Regulation and optimization of the biogas process: propionate as a key parameter. Biomass Bioenerg. 31: 820-830. https://doi.org/10.1016/j.biombioe.2007.04.004
  33. Li H. 2015. GitHub Repository. Toolkit for processing sequences in FASTA/Q formats. Available from https://github.com/lh3/seqtk. Accessed August 28, 2016.
  34. Itoh T, Iino T. 2013. Phylogeny and biotechnological features of thermophiles, pp. 249-270. In Satyanarayana T, Littlechild J, Kawarabayasi Y. (eds.). Thermophilic Microbes in Environmental and Industrial Biotechnology. Springer, Netherlands.
  35. Mirmohammadsadeghi H, Abedi D, Mohmoudpour HR, Akbari V. 2013. Comparison of five methods for extraction of genomic DNA from a marine Archaea, Pyrococcus furiosus. Pak. J. Med. Sci. 29: 390-394.
  36. Visweswaran GR, Dijkstra BW, Kok J. 2010. Two major archaeal pseudomurein endoisopeptidases: PeiW and PeiP. Archaea 2010: 480492.
  37. Krakat N, Westphal A, Schmidt S, Scherer P. 2010. Anaerobic digestion of renewable biomass - thermophilic temperature governs population dynamics of methanogens. Appl. Environ. Microbiol. 76: 1842-1850. https://doi.org/10.1128/AEM.02397-09
  38. Nettmann E, Bergmann I, Pramschüfer S, Mundt K, Plogsties V, Herrmann C, Klocke M. 2010. Polyphasic analyses of methanogenic archaeal communities in agricultural biogas plants. Appl. Environ. Microbiol. 76: 2540-2548. https://doi.org/10.1128/AEM.01423-09
  39. Wirth R, Kovacs E, Maroti G, Bagi Z, Rakhely G, Kovacs KL. 2012. Characterization of a biogas-producing microbial community by short-read next generation DNA sequencing. Biotechnol. Biofuels 5: 41-57. https://doi.org/10.1186/1754-6834-5-41
  40. Ziembinska-Buczynska A, Banach A, Bacza T, Pieczykolan M. 2014. Diversity and variability of methanogens during the shift from mesophilic to thermophilic conditions while biogas production. World J. Microbiol. Biotechnol. 30: 3047-3053. https://doi.org/10.1007/s11274-014-1731-z
  41. Lee SH, Kang HJ, Lee YH, Lee TJ, Han K, Choi Y, Park HD. 2012. Monitoring bacterial community structure and variability in time scale in full-scale anaerobic digesters. J. Environ. Monit. 14: 1893-1905. https://doi.org/10.1039/c2em10958a
  42. Leven L, Eriksson AR, Schnurer A. 2007. Effect of process temperature on bacterial and archaeal communities in two methanogenic bioreactors treating organic household waste. FEMS Microbiol. Ecol. 59: 683-693. https://doi.org/10.1111/j.1574-6941.2006.00263.x
  43. Ritari J, Koskinen K, Hultman J, Kurola JM, Kymäläinen M, Romantschuk M, et al. 2012. Molecular analysis of mesoand thermophilic microbiota associated with anaerobic biowaste degradation. BMC Microbiol. 12: 121. https://doi.org/10.1186/1471-2180-12-121
  44. Maus I, Koeck DE, Cibis KG, Hahnke S, Kim YS, Langer T, et al. 2016. Unraveling the microbiome of a thermophilic biogas plant by metagenome and metatranscriptome analysis complemented by characterization of bacterial and archaeal isolates. Biotechnol. Biofuels 9: 171. https://doi.org/10.1186/s13068-016-0581-3
  45. Simankova MV, Chernych NA, Osipov GA, Zavarzin GA. 1993. Halocella cellulolytica gen. nov., sp. nov., a new obligately anaerobic, halophilic, cellulolytic bacterium. Syst. Appl. Microbiol. 16: 385-389. https://doi.org/10.1016/S0723-2020(11)80270-5
  46. Ben Hania W, Godbane R, Postec A, Hamdi M, Ollivier B, Fardeau ML. 2012. Defluviitoga tunisiensis gen. nov., sp. nov., a thermophilic bacterium isolated from a mesothermic and anaerobic whey digester. Int. J. Syst. Evol. Microbiol. 62: 1377-1382. https://doi.org/10.1099/ijs.0.033720-0
  47. Whitman WB, Boone DR, Koga Y, Keswani J. 2001. Euryarchaeota phy. nov., pp. 211-294. In Boone DR, Castenholz RW, Garrity GM (eds.). Bergey's Manual of Systematic Bacteriology. Springer, New York.
  48. Westerholm M, Roos S, Schnurer A. 2010. Syntrophaceticus schinkii gen. nov., sp. nov., an anaerobic, syntrophic acetateoxidizing bacterium isolated from a mesophilic anaerobic filter. FEMS Microbiol. Lett. 309: 100-104.
  49. Ahring BK, Alatriste-Mondragon F, Westermann P, Mah RA. 1991. Effects of cations on Methanosarcina thermophile TM-1 growing on moderate concentration of acetate: production of single cells. Appl. Microbiol. Biotechnol. 35: 686-689.
  50. Sowers KR, Boone J, Gunsalus RP. 1993. Disaggregation of Methanosarcina spp. and growth as single cells at elevated osmolarity. Appl. Environ. Microbiol. 59: 3832-3839.
  51. Sowers K, Gunsalus RP. 1988. Adaption for growth at various saline concentrations by the archaebacterium Methanosarcina thermophile. J. Bacteriol 170: 998-1002. https://doi.org/10.1128/jb.170.2.998-1002.1988
  52. Liu Y, Boone DR, Sleat R, Mah RA. 1985. Methanosarcina mazei LYC, a new methanogenic isolate which produces a disaggregating enzyme. Appl. Environ. Microbiol. 49: 608-613.
  53. Boone DR, Whitman WB, Rouviere P. 1993. Diversity and taxonomy of methanogens, pp. 35-80. In Ferry JG (ed.). Methanogenesis. Chapman & Hall Inc., New York.
  54. Ho DP, Jensen PD, Batstone DJ. 2013. Methanosarcinaceae and acetate-oxidizing pathways dominate in high-rate thermophilic anaerobic digestion of waste-activated sludge. Appl. Environ. Microbiol. 79: 6491-6500. https://doi.org/10.1128/AEM.01730-13
  55. Zhou L, Yu H, Ai G, Zhang B, Hu S, Dong X. 2014. Transcriptomic and physiological insights into the robustness of long filamentous cells of Methanosaeta harundinacea, prevalent in upflow anaerobic sludge blanket granules. Appl. Environ. Microbiol. 81: 831-839.

Cited by

  1. Metagenome, metatranscriptome, and metaproteome approaches unraveled compositions and functional relationships of microbial communities residing in biogas plants vol.102, pp.12, 2017, https://doi.org/10.1007/s00253-018-8976-7
  2. Harvest of the Oleaginous Microalgae Scenedesmus obtusiusculus by Flocculation From Culture Based on Natural Water Sources vol.6, pp.None, 2017, https://doi.org/10.3389/fbioe.2018.00200
  3. Bio-Hydrogen Production From Buffalo Waste With Rumen Inoculum and Metagenomic Characterization of Bacterial and Archaeal Community vol.2, pp.None, 2017, https://doi.org/10.3389/fsufs.2018.00013
  4. Effect of pH and temperature on microbial community structure and carboxylic acid yield during the acidogenic digestion of duckweed vol.11, pp.None, 2017, https://doi.org/10.1186/s13068-018-1278-6
  5. Dynamics of a Perturbed Microbial Community during Thermophilic Anaerobic Digestion of Chemically Defined Soluble Organic Compounds vol.6, pp.4, 2017, https://doi.org/10.3390/microorganisms6040105
  6. Performance and microbial analysis during long‐term anaerobic digestion of olive mill wastewater in a packed‐bed biofilm reactor vol.95, pp.3, 2020, https://doi.org/10.1002/jctb.6275
  7. Microbiome Diversity and Community-Level Change Points within Manure-based small Biogas Plants vol.8, pp.8, 2020, https://doi.org/10.3390/microorganisms8081169
  8. Impact of process temperature and organic loading rate on cellulolytic / hydrolytic biofilm microbiomes during biomethanation of ryegrass silage revealed by genome-centered metagenomics and metatransc vol.15, pp.1, 2020, https://doi.org/10.1186/s40793-020-00354-x
  9. Indicative Marker Microbiome Structures Deduced from the Taxonomic Inventory of 67 Full-Scale Anaerobic Digesters of 49 Agricultural Biogas Plants vol.9, pp.7, 2017, https://doi.org/10.3390/microorganisms9071457
  10. Phytoplankton consortia as a blueprint for mutually beneficial eukaryote-bacteria ecosystems based on the biocoenosis of Botryococcus consortia vol.11, pp.1, 2017, https://doi.org/10.1038/s41598-021-81082-1