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Modeling de novo granulation of anaerobic sludge

  • Anna Doloman
  • , Honey Varghese
  • , Charles D. Miller
  • , Nicholas S. Flann*
  • *Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Background: A unique combination of mechanical, physiochemical and biological forces influences granulation during processes of anaerobic digestion. Understanding this process requires a systems biology approach due to the need to consider not just single-cell metabolic processes, but also the multicellular organization and development of the granule. Results: In this computational experiment, we address the role that physiochemical and biological processes play in granulation and provide a literature-validated working model of anaerobic granule de novo formation. The agent-based model developed in a cDynoMiCs simulation environment successfully demonstrated a de novo granulation in a glucose fed system, with the average specific methanogenic activity of 1.11 ml C H 4/g biomass and formation of a 0.5 mm mature granule in 33 days. The simulated granules exhibit experimental observations of radial stratification: a central dead core surrounded by methanogens then encased in acidogens. Practical application of the granulation model was assessed on the anaerobic digestion of low-strength wastewater by measuring the changes in methane yield as experimental configuration parameters were systematically searched. Conclusions: In the model, the emergence of multicellular organization of anaerobic granules from randomly mixed population of methanogens and acidogens was observed and validated. The model of anaerobic de novo granulation can be used to predict the morphology of the anaerobic granules in a alternative substrates of interest and to estimate methane potential of the resulting microbial consortia. The study demonstrates a successful integration of a systems biology approach to model multicellular systems with the engineering of an efficient anaerobic digestion system.

Original languageEnglish
Article number69
JournalBMC Systems Biology
Volume11
Issue number1
DOIs
Publication statusPublished - 17 Jul 2017
Externally publishedYes

Keywords

  • Agent-based modeling
  • Anaerobic granulation
  • Multicellular modeling
  • Wastewater treatment

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