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Related Concept Videos

Biofilms01:29

Biofilms

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Biofilms are complex communities of microorganisms encased in a self-produced extracellular polysaccharide matrix attached to surfaces. These microbial consortia can include single or multiple species, providing enhanced survival benefits by forming organized, multilayered structures.The formation of biofilms occurs through four key stages: attachment, colonization, development, and dispersal.During attachment, free-swimming planktonic cells adhere to a surface, often facilitated by...
682

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Agent Based Models of Polymicrobial Biofilms and the Microbiome-A Review.

Sherli Koshy-Chenthittayil1, Linda Archambault1,2, Dhananjai Senthilkumar3

  • 1Center for Quantitative Medicine, University of Connecticut Health Center, Farmington, CT 06030, USA.

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Agent-based modeling, combined with experiments, offers a powerful way to understand the complex interactions within microbial communities and biofilms. This approach enhances our comprehension of the human microbiome and its role in health and disease.

Keywords:
agent-based modelingbiofilmindividual-based modelingmicrobiomereview

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Area of Science:

  • Microbiology
  • Computational Biology
  • Bioinformatics

Background:

  • The human microbiome, comprising diverse microbial communities, plays a crucial role in health and disease.
  • Microbes often exist as biofilms on mucosal surfaces, influencing physiological processes and disease states.
  • Disturbances in microbial communities can lead to infections and other health issues.

Purpose of the Study:

  • To review recent innovations (past five years) in agent-based modeling (ABM) for studying biofilms and the microbiome.
  • To explore both biological and mathematical advancements in ABM for microbial communities.
  • To highlight the potential of ABM to deepen our understanding of polymicrobial biofilms and the microbiome.

Main Methods:

  • Review of recent literature on agent-based modeling in microbiology.
  • Analysis of biological and mathematical innovations in ABM for biofilms and the microbiome.
  • Discussion of the integration of ABM with experimental approaches.

Main Results:

  • Agent-based modeling has emerged as a key computational tool for simulating complex microbial interactions.
  • Recent advancements have improved the biological realism and mathematical sophistication of ABMs for biofilms.
  • ABMs, when coupled with experimental data, provide powerful insights into microbial community dynamics.

Conclusions:

  • Agent-based modeling is crucial for understanding the intricate dynamics of polymicrobial biofilms and the human microbiome.
  • Continued development in ABM, integrating biological and mathematical perspectives, will enhance our predictive capabilities.
  • This approach holds significant promise for advancing microbiome research and developing novel therapeutic strategies.