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Emerging methods for genome-scale metabolic modeling of microbial communities
Chaimaa Tarzi1, Guido Zampieri2, Neil Sullivan3
1School of Computing, Engineering and Digital Technologies, Teesside University, Southfield Rd, Middlesbrough, TS1 3BX, North Yorkshire, UK.
Trends in Endocrinology and Metabolism: TEM
|April 4, 2024
Summary
This study offers a guide to building and evaluating genome-scale metabolic models (GEMs) for microbial communities. It addresses challenges in computational tool selection and model limitations for researchers.
Area of Science:
- Microbial Ecology
- Systems Biology
- Computational Biology
Background:
- Genome-scale metabolic models (GEMs) are increasingly used for studying microbial communities.
- Challenges exist in tool selection, standardization, and inherent limitations when applying GEMs.
Purpose of the Study:
- To provide a comprehensive overview of foundational concepts for building and evaluating microbial community GEMs.
- To compare available computational tools for GEM analysis.
- To highlight current challenges and future directions in microbial community modeling.
Main Methods:
- Review and synthesis of existing knowledge on GEMs for microbial communities.
- Comparative analysis of computational tools based on requirements, capabilities, and applications.
- Identification of pitfalls and open challenges in the field.
Main Results:
- A structured overview of essential concepts for microbial community GEM development and evaluation.
- A comparative assessment of computational tools, aiding in selection.
- An outline of current limitations and future research needs.
Conclusions:
- This compendium serves as a valuable resource for both novice and experienced modelers in the field of microbial community GEMs.
- Addressing the identified challenges will facilitate more robust and reliable microbial community modeling.
- Standardization and development of new tools are crucial for advancing the application of GEMs.
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