Skip to main content
SpringerLink
Log in

Effects of the Antibiotics Chlortetracycline and Enrofloxacin on the Anaerobic Digestion in Continuous Experiments

  • Published:
BioEnergy Research Aims and scope Submit manuscript

An Erratum to this article was published on 28 December 2015

Abstract

Significant quantities of antibiotics are used in modern livestock husbandry and are found in livestock waste. Such waste has been reported to exert inhibitory effects if used as a substrate in biogas facilities. The goal of this study is to analyze the inhibitory effect of the antibiotics chlortetracycline (CTC) and enrofloxacin (EFX) on biogas production with pig slurry. Antibiotic concentrations up to 8,000 mg kg−1 dry matter (DM) pig slurry were added in continuous fermentation tests. Impacts on methane production and on the microbial community structure were analyzed. The results clearly show that chlortetracycline and enrofloxacin negatively affect biogas production. Higher concentrations of antibiotics led to lower methane production. The addition of 200 mg kg−1 DM of CTC or EFX reduced the specific methane yields up to 49 and 44 %, respectively. The microbial community did not show any changes at this concentration. When chlortetracycline was added at a concentration of 8,000 mg kg−1 DM, the biodiversity changed slightly compared to the control without antibiotics.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1

Similar content being viewed by others

References

  1. Weiland P (2006) Biomass digestion in agriculture: a successful pathway for the energy production and waste treatment in Germany. Eng Life Sci 6(3):302–309

    Article  CAS  Google Scholar 

  2. Appels L, Lauwers J, Degrve J, Helsen L, Lievens B, Willems K, Van Impe J, Dewil R (2011) Anaerobic digestion in global bio-energy production: potential and research challenges. Renew Sust Energ Rev 15(9):4295–4301. doi:10.1016/j.rser.2011.07.121

    Article  CAS  Google Scholar 

  3. Weiland P, Verstraete W, Van Haandel A (2009) Biomass digestion to methane in agriculture: a successful pathway for the energy production and waste treatment worldwide. In: Vandamme WSa EJ (ed) Biofuels. Wiley, Belgium, pp 171–195

    Chapter  Google Scholar 

  4. Sommer SG, Petersen SO, Møller HB (2004) Algorithms for calculating methane and nitrous oxide emissions from manure management. Nutr Cycl Agroecosyst 69(2):143–154. doi:10.1023/B:FRES.0000029678.25083.fa

    Article  CAS  Google Scholar 

  5. Holm-Nielsen JB, Al Seadi T, Oleskowicz-Popiel P (2009) The future of anaerobic digestion and biogas utilization. Bioresour Technol 100(22):5478–5484

    Article  PubMed  CAS  Google Scholar 

  6. Winckler C, Grafe A (2000) Characterization and recycling of waste from intensive farming considering different soils (Original title: Charakterisierung und Verwertung von Abfällen aus der Massentierhaltung unter Berücksichtigung verschiedener Böden); Forschungsbericht 29733911. Deutschland//Umweltbundesamt: Texte, vol 2000,44. Umweltbundesamt, Berlin

  7. Mellon M, Benbrook C, Benbrook KL (2001) Hogging it: estimates of antimicrobial abuse in livestock. Union of Concerned Scientists (UCS) Publications, Cambridge

    Google Scholar 

  8. Apley MD, Bush EJ, Morrison RB, Singer RS, Snelson H (2012) Use estimates of in-feed antimicrobials in swine production in the United States. Foodborne Pathog Dis 9(3):272–279. doi:10.1089/fpd.2011.0983

    Article  PubMed  CAS  Google Scholar 

  9. Arikan OA, Sikora LJ, Mulbry W, Khan SU, Rice C, Foster GD (2006) The fate and effect of oxytetracycline during the anaerobic digestion of manure from therapeutically treated calves. Process Biochem 41(7):1637–1643. doi:10.1016/j.procbio.2006.03.010

    Article  CAS  Google Scholar 

  10. Gans O, Pfundtner E, Winckler C, Bauer A (2010) Reduction of veterinary antibiotics in agricultural soils by collocated biogas plants? (Original title: Reduktion des Antibiotikaeintrages in landwirtschaftlich genützten Böden durch Biogasanlagen?). Umweltbundesamt, Vienna

    Google Scholar 

  11. Gans O, Weiss S, Sitka A, Pfundtner E, Scheffknecht C, Scharf S (2008) Determination of selected veterinary antibiotics and quaternary ammonium compounds in digestates of biogas plants in Austria. In: Fuchs G, Kupper T, Tamm L, Schenk K (eds) Compost and digestate: sustainability, benefits, impacts for the environment and for the plant production. CODIS 2008, Solothurn

  12. Lindsey ME, Meyer M, Thurman EM (2001) Analysis of trace levels of sulfonamide and tetracycline antimicrobials, in groundwater and surface water using solid-phase extraction and liquid chromatography/mass spectrometry. Anal Chem 73(19):4640–4646

    Article  PubMed  CAS  Google Scholar 

  13. Martínez-Carballo E, González-Barreiro C, Scharf S, Gans O (2007) Environmental monitoring study of selected veterinary antibiotics in animal manure and soils in Austria. Environ Pollut 148(2):570–579. doi:10.1016/j.envpol.2006.11.035

    Article  PubMed  Google Scholar 

  14. Choi E (2007) Piggery waste management: towards a sustainable future. IWA Publishing, London

    Google Scholar 

  15. Shimada T, Zilles JL, Morgenroth E, Raskin L (2008) Inhibitory effects of the macrolide antimicrobial tylosin on anaerobic treatment. Biotechnol Bioeng 101(1):73–82. doi:10.1002/bit.21864

    Article  PubMed  CAS  Google Scholar 

  16. Sanz JL, Rodriguez N, Amils R (1996) The action of antibiotics on the anaerobic digestion process. Appl Microbiol Biotechnol 46(5–6):587–592

    Article  PubMed  CAS  Google Scholar 

  17. Masse DI, Lu D, Masse L, Droste RL (2000) Effect of antibiotics on psychrophilic anaerobic digestion of swine manure slurry in sequencing batch reactors. Bioresour Technol 75(3):205–211

    Article  CAS  Google Scholar 

  18. Lallai A, Mura G, Onnis N (2002) The effects of certain antibiotics on biogas production in the anaerobic digestion of pig waste slurry. Bioresour Technol 82(2):205–208. doi:10.1016/S0960-8524(01)00162-6

    Article  PubMed  CAS  Google Scholar 

  19. VDI (2006) VDI 4630—fermentation of organic materials. Characterisation of substrate, sampling, collection of material data, fermentation tests. VDI Gesellschaft Energietechnik

  20. Hopfner-Sixt K, Amon T, Walla C, Pötsch E, Amon B, Milovanovic D, Mayr H, Weichselbaum W (2007) Analysis and optimization of new biogas plants (Original title: Analyse und Optimierung neuer Biogasanlagen). Österreichische Forschungsfürderungsgesellschaft (FFG)

  21. D.I.N (2001) Characterization of sludges—determination of dry residue and water content (Original title: Charakterisierung von Schlämmen—Bestimmung des Trockenrückstandes und des Wassergehalts); Deutsche Fassung EN 12880:2000

  22. Sluiter A, Ruiz R, Scarlata C, Sluiter J, Templeton D (2008) Determination of extractives in biomass. Laboratory Analytical Procedure (LAP)

  23. Naumann C, Bassler R (1993) The chemical analysis of animal feed (Original title: Die chemische Untersuchung von Futtermittel), 3rd edn. VDLUFA, Darmstadt

    Google Scholar 

  24. Daims H, Stoecker K, Wagner M (2005) Fluorescence in situ hybridisation for the detection of prokaryotes. In: Science G (ed) Advanced methods in molecular microbial ecology. BIOS Scientific Publishers, Abingdon, pp 213–239

    Google Scholar 

  25. Nettmann E, Bergmann I, Mundt K, Linke B, Klocke M (2008) Archaea diversity within a commercial biogas plant utilizing herbal biomass determined by 16S rDNA and mcrA analysis. J Appl Microbiol 105(6):1835–1850. doi:10.1111/j.1365-2672.2008.03949.x

    Article  PubMed  CAS  Google Scholar 

  26. Bergmann I, Mundt K, Sontag M, Baumstark I, Nettmann E, Klocke M (2010) Influence of DNA isolation on Q-PCR-based quantification of methanogenic Archaea in biogas fermenters. Syst Appl Microbiol 33(2):78–84. doi:10.1016/j.syapm.2009.11.004

    Article  PubMed  CAS  Google Scholar 

  27. Klocke M, Nettmann E, Bergmann I, Mundt K, Souidi K, Mumme J, Linke B (2008) Characterization of the methanogenic Archaea within two-phase biogas reactor systems operated with plant biomass. Syst Appl Microbiol 31(3):190–205. doi:10.1016/j.syapm.2008.02.003

    Article  PubMed  CAS  Google Scholar 

  28. Yu Y, Lee C, Kim J, Hwang S (2005) Group-specific primer and probe sets to detect methanogenic communities using quantitative real-time polymerase chain reaction. Biotechnol Bioeng 89(6):670–679. doi:10.1002/bit.20347

    Article  PubMed  CAS  Google Scholar 

  29. 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(8):2540–2548. doi:10.1128/AEM.01423-09

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  30. Amann RI, Binder BJ, Olson RJ, Chisholm SW, Devereux R, Stahl DA (1990) Combination of 16S rRNA-targeted oligonucleotide probes with flow cytometry for analyzing mixed microbial populations. Appl Environ Microbiol 56(6):1919–1925

    PubMed  CAS  PubMed Central  Google Scholar 

  31. Stahl D, Amann R (1991) Development and application of nucleic acid probes. In: Stackebrandt E, Goodfellow M (eds) Nucleic acid techniques in bacterial systematics. Wiley, Chichester, pp 205–248

    Google Scholar 

  32. Deublein D, Steinhauser A (2008) Biogas from waste and renewable resources—an introduction. Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim

    Book  Google Scholar 

  33. Stone JJ, Clay SA, Spellman GM (2010) Tylosin and chlortetracycline effects during swine manure digestion: Influence of sodium azide. Bioresour Technol 101(24):9515–9520. doi:10.1016/j.biortech.2010.07.116

    Article  PubMed  CAS  Google Scholar 

  34. Gujer WA, Zehnder AJB (1983) Conversion processes in anaerobic digestion. Water Sci Technol 15:127–167

    CAS  Google Scholar 

  35. Schnürer A, Houwen FP, Svensson BH (1994) Mesophilic syntrophic acetate oxidation during methane formation by a triculture at high ammonium concentration. Arch Microbiol 162(1–2):70–74. doi:10.1007/s002030050103

    Article  Google Scholar 

  36. Tamura K, Peterson D, Peterson N, Stecher G, Nei M, Kumar S (2011) MEGA5: molecular evolutionary genetics analysis using maximum likelihood, evolutionary distance, and maximum parsimony methods. Mol Biol Evol 28:2731–2739

    Article  PubMed  CAS  PubMed Central  Google Scholar 

Download references

Acknowledgments

The authors would like to thank Dr. M. Casler for his valuable suggestions to improve the quality of the paper. This project was financed by the Federal Ministry of Agriculture, Forestry, Environment and Water Management (BMLFUW) and the nine Austrian provinces and Austrian Research Promotion Agency (FFG), who promote this project. E. N. and I. B. gratefully acknowledge the grant provided by the German Federal Ministry of Food and Agriculture (grant no. FNR 22011804).

Author information

Authors and Affiliations

  1. Division of Agricultural Engineering, University of Natural Resources and Applied Life Sciences, Konrad Lorenz Strasse 24, 3430, Tulln, Austria

    A. Bauer, J. Lizasoain, M. Rincón & G. Piringer

  2. AlpS-Gmbh, Centre for Climate Change Adaptation Technologies, Grabenweg 68, 6020, Innsbruck, Austria

    A. Bauer & J. Lizasoain

  3. Lehrstuhl für Siedlungswasserwirtschaft und Umwelttechnik, Ruhr-Universität Bochum, Universitätstrasse 150, 44801, Bochum, Germany

    E. Nettmann

  4. Abt. Bioverfahrenstechnik, Leibniz-Institut für Agrartechnik Potsdam-Bornim e.V. (ATB), Max-Eyth-Allee 100, 14469, Potsdam, Germany

    I. Bergmann, K. Mundt & M. Klocke

  5. Abt. Technik in der Tierhaltung, Leibniz-Institut für Agrartechnik Potsdam-Bornim e.V. (ATB), Max-Eyth-Allee 100, 14469, Potsdam, Germany

    T. Amon

Authors
  1. A. Bauer
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. J. Lizasoain
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. E. Nettmann
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. I. Bergmann
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. K. Mundt
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. M. Klocke
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. M. Rincón
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. T. Amon
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. G. Piringer
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to A. Bauer.

Electronic supplementary material

Below is the link to the electronic supplementary material.

ESM 1

Distribution of operational taxonomic units (OTUs) as represented by individual ARDRA fingerprint patterns and the contributing clone numbers as detected in the two 16S rRNA gene libraries constructed out of samples derived from fermentations with and without addition of 8,000 mg kg−1 DM enrofloxacin (EFX). The taxonomic classification was according to Bergey’s Manual and NCBI taxonomy. ND = not detected. (PDF 34 kb)

ESM 2

Phylogenetic tree of the operational taxonomic units (OTUs) among the phylum Euryarchaeota of the domain Archaea as determined in clone libraries constructed from PCR-amplified sequences of microbial 16S rRNA genes out of microbial gDNA purified from samples with and without enrofloxacin (8,000 mg kg−1 DM; experiment 1, variant 11). Numbers in round brackets indicate contributing clone numbers in the respective clone library (with/without enrofloxacin; further details as given in Tab. S1). The tree based on neighbor-joining analysis of 616 nucleotide positions. The evolutionary distances were computed using the Jukes-Cantor method and are in the units of the number of base substitutions per site. Numbers at nodes represent bootstrap values for the nodes in percent (1,000 times resampling analysis). Only bootstrap values above 50 % were displayed. Numbers in brackets indicate the NCBI genbank accession number of 16S rRNA gene sequences of reference strains. Halobacterium salinarium was used as the outgroup (marked by an asterisk). For phylogenetic analysis and tree construction the software MEGA5 developed by Tamura et al. (2011) was used. All further details as described in Klocke et al. [25]. (PDF 70 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Bauer, A., Lizasoain, J., Nettmann, E. et al. Effects of the Antibiotics Chlortetracycline and Enrofloxacin on the Anaerobic Digestion in Continuous Experiments. Bioenerg. Res. 7, 1244–1252 (2014). https://doi.org/10.1007/s12155-014-9458-0

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12155-014-9458-0

Keywords

Search

Navigation