Abstract
AbstractMotivationMicroorganisms thrive in large communities of diverse species, exhibiting various functionalities. The mammalian gut microbiome, for instance, has the functionality of digesting dietary fibre and producing different short-chain fatty acids. Not all microbes present in a community contribute to a given functionality; it is possible to find aminimalmicrobiome, which is a subset of the large microbiome, that is capable of performing the functionality while maintaining other community properties such as growth rate. Such a minimal microbiome will also contain keystone species for SCFA production in that community. In the wake of perturbations of the gut microbiome that result in disease conditions, cultivated minimal microbiomes can be administered to restore lost functionalities.ResultsIn this work, we present a systematic algorithm to design a minimal microbiome from a large community for a user-proposed function. We employ a top-down approach with sequential deletion followed by solving a mixed-integer linear programming problem with the objective of minimising theL1-norm of the membership vector. We demonstrate the utility of our algorithm by identifying the minimal microbiomes corresponding to model communities of the gut, and discuss their validity based on the presence of the keystone species in the community. Our approach is generic and finds application in studying a variety of microbial communities.AvailabilityThe algorithm is available fromhttps://github.com/RamanLab/minMicrobiomeAuthor SummaryMicroorganisms are ubiquitous in nature. They survive in communities by interacting with each other and influence the biosphere by carrying out specific functions. For instance, the mammalian digestive system is heavily dependent on microbial communities in the gut (known as gut microbiome) to digest dietary fibres which are otherwise indigestible. The capability of gut microbes to convert dietary fibres to short-chain fatty acids help the host by regulating the functionality of the gut epithelial barrier. Oftentimes, some members of a community have redundant functions. Hence, it is possible to find a smaller subset of organisms that is capable of a given functionality, while also maintaining the required growth rate. We call them a minimal microbiome. Knowledge of such function-specific minimal microbiomes is useful for constructing communities for laboratory study and for designing treatment strategies for medical conditions caused by microbiome disruption. We present an optimization algorithm for identifying function-specific minimal microbiomes from a large community. We also demonstrate the performance of the algorithm by analysing minimal microbiomes obtained from some known communities. Overall, our research work highlights the significance of function-specific minimal microbiomes and provides an efficient computational tool for their identification.
Publisher
Cold Spring Harbor Laboratory