Coupling growth kinetics modeling with machine learning reveals microbial immigration impacts and identifies key environmental parameters in a biological wastewater treatment process.

Journal: Microbiome
PMID: 30995941

Abstract

BACKGROUND: Ubiquitous in natural and engineered ecosystems, microbial immigration is one of the mechanisms shaping community assemblage. However, quantifying immigration impact remains challenging especially at individual population level. The activities of immigrants in the receiving community are often inadequately considered, leading to potential bias in identifying the relationship between community composition and environmental parameters.

Authors

  • Ran Mei
    Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, 3207 Newmark Civil Engineering Laboratory, 205 North Mathews Ave, Urbana, IL, 61801, USA.
  • Jinha Kim
    Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, 3207 Newmark Civil Engineering Laboratory, 205 North Mathews Ave, Urbana, IL, 61801, USA.
  • Fernanda P Wilson
    Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, 3207 Newmark Civil Engineering Laboratory, 205 North Mathews Ave, Urbana, IL, 61801, USA.
  • Benjamin T W Bocher
    Petrochemicals Technology, BP America, Naperville, IL, 60563, USA.
  • Wen-Tso Liu
    Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, 3207 Newmark Civil Engineering Laboratory, 205 North Mathews Ave, Urbana, IL, 61801, USA. wtliu@illinois.edu.

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