Table 1.

Summary of the principles of microbiome engineering derived from studies of synthetic consortia.

Consortium composition	Ecological factor	Proposed principle	Possible application	References
Natural strains	Pairwise coexistence	In a multispecies community, species that all coexist with each other in pairs will survive, whereas species that are excluded by any of the surviving species will become extinct	Maintain strain coexistence	[32]
Engineered strains	Growth rate	Controlling the growth of different members could maintain their coexistence and stabilize the community		[33, 34, 35]
Engineered strains	Cooperative interdependence	Cooperative interdependence contributes to the maintenance of the long‐term coexistence of multiple species		[36]
Natural strains	Temperature	Higher temperatures favor slower‐growing bacterial species in multispecies communities	Control the environmental factors	[37]
Natural strains	Nutrient availability	High nutrient concentrations often cause more negative than positive interactions between species, which exclude more species from the community, resulting in a loss of biodiversity		[38]
Natural strains	Nutrient complexity	The assembly of microbial communities in the presence of multiple nutrients is consistent with the behavior of consumer‐resource models		[39]
Natural strains	pH	Description of a set of interactions can be simplified using one simple environmental parameter, pH		[40]
Natural strains	Stochastic process	A rare successful colonist in the gut dominates the individual community and resists invasion by new colonists	Control the stochastic factors	[41, 42, 43]
Model derived	Pairwise interactions	Positive interactions enhance the diversity and productivity of the community but decrease its stability	Design interactions within the engineered microbiome	[44, 45, 46]
Engineered strains	Pairwise interactions	The dynamics of communities could be predicted using Lotka–Volterra pairwise Model parameterized by two‐strain coculture experiments	Develop quantitative modeling	[47, 48]
Engineered strains	Cooperative interdependence	Cooperative interdependence shapes intermixing the spatial pattern of the community, which helps to prevent cheaters from invasion	Design the spatial structure of the engineered microbiome	[49, 50]
Natural strains/Engineered strains	Cell–cell distance	Maintaining a suitable distance among the interacting strains could benefit community performance		[51, 52]
Engineered strains	Metabolic burden	Metabolic division of labor (MDOL) reduces the metabolic burden, giving higher metabolic efficiency	(1) Judge whether an MDOL strategy should be adopted. (2) Engineer a stable MDOL community with a defined structure	[8, 53]
Model derived	Metabolic burden; transfer efficiency	An MDOL community outperforms a single population only when the benefit derived from reduced metabolic burden overcomes the inefficiency of intermediate transport		[54]
Engineered strains	Parameters involved in a metabolic pathway	To maintain the stability of an MDOL community, the populations responsible for the initial steps in a linear metabolic pathway should hold a growth advantage (m) over the “private benefit” (n) of the population responsible for the last step. The steady‐state frequency of the last population is then determined by the quotient of n and m		[33]
Engineered strains	Substrate concentration and toxicity	The proportion of the population executing the first metabolic step in an MDOL community can be estimated by Monod‐like formulas governed by substrate concentration and toxicity		[55]