misosoup: a metabolic modeling tool for identifying minimal microbial communities, facilitates the exploration of microbial ecology and biotechnological applications.

Microbial survival and function often depend on metabolic interactions within communities. Therefore, a central question in disentangling microbial organization is determining which minimal groups of strains are able to thrive in a given medium-referred to as "minimal communities." Answering this question is essential for understanding microbial distribution, enhancing laboratory cultivation, and designing synthetic communities (SynComs). Here, we introduce misosoup, a Python package for identifying minimal communities ( IMPORTANCE: Microbes often rely on each other to survive, especially in environments where they cannot live alone. Understanding which small groups of microbes can thrive together-called minimal communities-is key to improving laboratory research, designing synthetic ecosystems, and exploring how microbes spread in nature. To support this, we developed misosoup, a Python tool that identifies these communities using advanced metabolic modeling. misosoup helps scientists discover how microbes cooperate by sharing nutrients, a process known as metabolic cross-feeding. When tested on sets of species from different origins, the tool showed that species could thrive in more environments when part of a group. This finding highlights the importance of cooperation in microbial life. misosoup not only predicts these interactions but also provides detailed insights that can guide ecological studies and biotechnological innovation. By revealing how microbes support each other, misosoup contributes to a deeper understanding of life's interconnectedness and offers tools for solving real-world challenges.