Absolute quantification of synthetic microbial communities using a simplified multiplexed ddPCR method

Synthetic microbial communities provide experimentally tractable systems for studying community assembly, stability, and function and for integrating quantitative experiments with mathematical models of community dynamics. These applications require accurate and reproducible absolute quantification of individual community members, yet commonly used methods rely on relative abundance measurements or suffer from amplification bias and limited reproducibility. Here, we present a simplified and scalable multiplexed digital droplet PCR-based workflow for absolute quantification of species abundance in synthetic microbial communities. Using a four-member community composed of Bacillus subtilis, Pseudomonas fluorescens, Rhodococcus ruber, and Enterobacter asburiae, we developed an integrated experimental workflow encompassing DNA isolation, primer and probe design, and multiplex assay configuration. A hybrid targeting strategy was adopted, substituting a single-copy gyrB gene target for Bacillus subtilis to avoid 16S rRNA gene cross-reactivity, while retaining 16S rRNA gene targets for the remaining three community members. Key assay parameters were systematically optimized to enable robust discrimination and simultaneous quantification of all community members within a single reaction. The method exhibits high linearity across a broad dynamic range, resistance to amplification bias, and tolerance to common polymerase chain reaction inhibitors. This streamlined approach, intended for experimental characterization of defined synthetic microbial communities under controlled experimental conditions rather than for microbial diagnostics or clinical detection, enables reproducible absolute quantification of defined microbial consortia and provides a quantitative foundation for systems-level analyses and model-informed studies of microbial community behavior, with species specificity being defined operationally within this community and scaling to additional targets to require manual tuning.IMPORTANCEMechanistic understanding of microbial communities increasingly depends on quantitative data that can be directly compared across experiments and used to parameterize mathematical models. However, simple methods for measuring the absolute abundance of individual species in synthetic microbial communities remain limited. We describe an accessible multiplexed digital droplet polymerase chain reaction workflow that enables direct and reproducible cell quantification in a defined microbial consortium. Unlike methods developed for microbial diagnostics or clinical testing, this approach is optimized for experimental reproducibility and quantitative modeling in well-defined microbial consortia rather than for broad-spectrum detection or regulatory validation. By supporting accurate absolute quantification, this framework strengthens integration between experimental and theoretical studies aimed at explaining how microbial communities are established and maintained.