PNNL

Abstract

Modulation of interspecies interactions in the presence of neighbor species is a key ecological factor that governs dynamics and function of microbial communities, yet the development of theoretical frameworks explicit for understanding context-dependent interactions are still nascent. In a recent study, we proposed a novel rule-based inference method that enables predicting the effect of new species on pairwise interactions among existing members and termed it the Minimal Interspecies Interaction Adjustment (MIIA). The theoretical basis for MIIA has been validated in the condition where all member species can grow solely as well as with partners. While useful, this development becomes highly constrained in cases that species have not been mono-cultured (e.g., due to their inability to grow in the absence of specific partnerships) because binary interaction coefficients – basic parameters required for implementing the MIIA – are inestimable without axenic and binary population data. Thus, here we present an alternative formulation based on the following two central ideas. First, in the case where only axenic data are unavailable, we remove axenic populations from governing equations through appropriate scaling. This allows us to predict neighbor-dependent interactions in a relative sense (i.e., fractional change of interactions between with versus without neighbors). Second, in the case where both axenic and binary populations are missing, we parameterize binary interaction coefficients to determine their values through a sensitivity analysis. In the case study of a four-member, multispecies community that provides data with respect to each case mentioned, we were able to successfully predict interspecies interactions that are consistent with experimentally derived results. Therefore, this technical advancement enhances our ability to predict context-dependent interspecies interactions in a broad range of microbial systems without being limited to specific growth conditions as a pre-requisite.