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Microbial interactions in natural environments are intricately complex. High numbers and rich diversity of microorganisms, along with compositional heterogeneities complicate the cause. It is essential to simplify these complex communities to understand the microbial interactions. We proposed a concept of “ simple state community ,” which represents a subset of microbes and/or microbial functions of the original population that is necessary to build a stable community. By combining microbial culturing and high-throughput sequencing, we can better understand microbe-microbe and microbe-host interactions. To support our proposed model, we used carbon-based and nitrogen-based media to capture the simple state communities. We used 16S rRNA amplicon sequencing and assigned taxonomic identity to the bacterial populations before and after simple state communities. We showed that simple state communities were a subset of the original microbial communities at both phyla and genera level. We further used shotgun metagenomics to gain insights into the functional potential of the assembled simple state communities. Our proposed model supported the goal of simplifying the complex communities across diverse systems to provide opportunity to facilitate comprehension of both the structure and function of the subset communities. Further applications of the concept include the high-throughput screening of simple state communities using the BIOLOG ® system and continuous culturing (Chemostat). This concept has the potential to test diverse experimental hypotheses in simplified microbial communities, and further extend that knowledge to answer the overarching questions at a more holistic level.