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<p>In this review, we use microbial mat communities as a general model system to highlight the strengths and limitations of current computational methods for analyzing interactions between members of microbial ecosystems. We describe the factors that make this environment have such a high degree of interaction, and we explore different categories of both laboratory and computational tools for studying these interactions. For each tool, we describe efforts to apply them to microbial mats in the past and, in the process, argue that genome-scale metabolic models have breakthrough potential for modeling microbial interactions in microbial mats.</p>

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A survey of computational approaches for characterizing microbial interactions in microbial mats

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年6月16日

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  • Vanesa L. Perillo,
  • Michael Nute,
  • Nicolae Sapoval,
  • Kristen D. Curry,
  • Logan Golia,
  • Yongze Yin,
  • Huw A. Ogilvie,
  • Luay Nakhleh,
  • Santiago Segarra,
  • Devaki Bhaya,
  • Diana G. Cuadrado,
  • Todd J. Treangen

摘要

In this review, we use microbial mat communities as a general model system to highlight the strengths and limitations of current computational methods for analyzing interactions between members of microbial ecosystems. We describe the factors that make this environment have such a high degree of interaction, and we explore different categories of both laboratory and computational tools for studying these interactions. For each tool, we describe efforts to apply them to microbial mats in the past and, in the process, argue that genome-scale metabolic models have breakthrough potential for modeling microbial interactions in microbial mats.