Table 1.

Summary of synthetic community design methods

Description	Requirements	Benefits	Downsides	Example usage	Design approach
Environmental conditions are modified to promote the growth of species that perform a desired function	Initial community with capacity for the desired function Selection procedure that favors growth of species that can perform the desired function	Optimizes community function without identifying individual species involved	Undefined or partially defined communities may be unsuited for therapeutics Optimization time can be extensive depending on the application and initial community	Fradinho et al., 2016 [60] Korkakaki et al., 2017 [59] Kumari et al., 2017 [63]	Enrichment
Species are isolated from an existing community, screened to keep desirable species and/or exclude undesirable species, and then reconstituted into a simplified community that recapitulates the source community’s function	Initial community with capacity for the desired function Appropriate media for culturing microbial isolates Screening procedures for isolated species	Produces a defined synthetic composition Can explicitly exclude pathogenic or otherwise undesirable species	Cannot design communities for novel functions May fail if important species cannot be cultured	Petrof et al., 2013 [68] Atarashi et al., 2015 [71] Caballero et al, 2017 [69]	Community reduction
All possible combinations of a set of candidate species are evaluated for their performance of a desired function and the best-performing composition is selected	Microbial isolates suspected to contribute to the desired function Screening procedures for candidate communities	Produces a defined synthetic composition Can explicitly exclude pathogenic or otherwise undesirable species Can combine species from distinct sources	Number of potential compositions to evaluate grows exponentially with the number of candidate species	Hu et al., 2016 [91] Hu et al., 2017 [92]	Combinatorial evaluation
Mechanistic models of microbial functional capacities and activities and/or ecological models of community dynamics are used to evaluate potential community compositions in silico, identifying one or more optimized compositions for further experimental validation	Mechanistic knowledge of individual microbial function and/or Ecological models of community dynamics	Produces a defined synthetic composition Can explicitly exclude pathogenic or otherwise undesirable species Can combine species from distinct sources Reduces time and labor required for experimental evaluation	Well-curated mechanistic information is unavailable for many species Mechanistic models of non-metabolic functions are lacking	Eng and Borenstein, 2016 [99] Julien-Laferriere et al., 2016 [100] Garcia-Jimenez et al., 2018 [109] Stein et al., 2018 [112]	Computational model-based design