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Applied Microbiology and Biotechnology

, Volume 56, Issue 3–4, pp 531–538 | Cite as

The impact of fermentative organisms on carbon flow in methanogenic systems under constant low-substrate conditions

  •  S. Dollhopf
  •  S. Hashsham
  •  F. Dazzo
  •  R. Hickey
  •  C. Criddle
  •  J. Tiedje
original paper

Abstract.

We compared carbon flow under constant low-substrate conditions (below 20 µM glucose in situ) in laboratory-scale glucose-fed methanogenic bioreactors containing two very different microbial communities that removed chemical oxygen demand at similar rates. One community contained approximately equal proportions of spiral and cocci morphologies, while the other community was dominated by cocci. In the former bioreactor, over 50% of the cloned SSU rRNA genes and the most common SSU rDNA terminal restriction fragment corresponded to Spirochaetaceae-related sequences, while in the latter bioreactor over 50% of the cloned SSU rRNA genes and the most common SSU rDNA terminal restriction fragment corresponded to Streptococcus-related sequences. Carbon flow was assessed by measuring 14C-labeled metabolites derived from a feeding of [U-14C]glucose that did not alter the concentration of glucose in the bioreactors. Acetate and ethanol were detected in the Spirochaetaceae-dominated reactor, whereas acetate and propionate were detected in the Streptococcus-dominated reactor. A spirochete isolated from a Spirochaetaceae-dominated reactor fermented glucose to acetate, ethanol, and small amounts of lactate. Maximum substrate utilization assays carried out on fluid from the same reactor indicated that acetate and ethanol were rapidly utilized by this community. These data indicate that an acetate- and ethanol-based food chain was present in the Spirochaetaceae-dominated bioreactor, while the typical acetate- and propionate-based food chain was prevalent in the Streptococcus-dominated bioreactor.

Keywords

Glucose Microbial Community Chemical Oxygen Demand Food Chain Equal Proportion 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag 2001

Authors and Affiliations

  •  S. Dollhopf
    • 1
  •  S. Hashsham
    • 1
  •  F. Dazzo
    • 1
  •  R. Hickey
    • 2
  •  C. Criddle
    • 1
  •  J. Tiedje
    • 1
  1. 1.Center for Microbial Ecology, 545 Plant and Soil Sciences Building, Michigan State University, E. Lansing, MI 48824, USA
  2. 2.Department of Civil and Environmental Engineering, Michigan State University, E. Lansing, MI 48824

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