A Reproducible and Tunable Synthetic Soil Microbial Community Provides New Insights into Microbial Ecology.

Microbial soil communities form commensal relationships with plants to promote the growth of both parties. The optimization of plant-microbe interactions to advance sustainable agriculture is an important field in agricultural research. However, investigation in this field is hindered by a lack of model microbial community systems and efficient approaches for building these communities. Two key challenges in developing standardized model communities are maintaining community diversity over time and storing/resuscitating these communities after cryopreservation, especially considering the different growth rates of organisms. Here, a model synthetic community (SynCom) of 16 soil microorganisms commonly found in the rhizosphere of diverse plant species, isolated from soil surrounding a single switchgrass plant, has been developed and optimized for in vitro experiments. The model soil community grows reproducibly between replicates and experiments, with a high community α-diversity being achieved through growth in low-nutrient media and through the adjustment of the starting composition ratios for the growth of individual organisms. The community can additionally be cryopreserved with glycerol, allowing for easy replication and dissemination of this in vitro system. Furthermore, the SynCom also grows reproducibly in fabricated ecosystem devices (EcoFABs), demonstrating the application of this community to an existing in vitro plant-microbe system. EcoFABs allow reproducible research in model plant systems, offering the precise control of environmental conditions and the easy measurement of plant microbe metrics. Our results demonstrate the generation of a stable and diverse microbial SynCom for the rhizosphere that can be used with EcoFAB devices and can be shared between research groups for maximum reproducibility. IMPORTANCE Microbes associate with plants in distinct soil communities to the benefit of both the soil microbes and the plants. Interactions between plants and these microbes can improve plant growth and health and are therefore a field of study in sustainable agricultural research. In this study, a model community of 16 soil bacteria has been developed to further the reproducible study of plant-soil microbe interactions. The preservation of the microbial community has been optimized for dissemination to other research settings. Overall, this work will advance soil microbe research through the optimization of a robust, reproducible model community.

synDNA-a Synthetic DNA Spike-in Method for Absolute Quantification of Shotgun Metagenomic Sequencing.

Microbiome studies have the common goal of determining which microbial taxa are present, respond to specific conditions, or promote phenotypic changes in the host. Most of these studies rely on relative abundance measurements to drive conclusions. Inherent limitations of relative values are the inability to determine whether an individual taxon is more or less abundant and the magnitude of this change between the two samples. These limitations can be overcome by using absolute abundance quantifications, which can allow for a more complete understanding of community dynamics by measuring variations in total microbial loads. Obtaining absolute abundance measurements is still technically challenging. Here, we developed synthetic DNA (synDNA) spike-ins that enable precise and cost-effective absolute quantification of microbiome data by adding defined amounts of synDNAs to the samples. We designed 10 synDNAs with the following features: 2,000-bp length, variable GC content (26, 36, 46, 56, or 66% GC), and negligible identity to sequences found in the NCBI database. Dilution pools were generated by mixing the 10 synDNAs at different concentrations. Shotgun metagenomic sequencing showed that the pools of synDNAs with different percentages of GC efficiently reproduced the serial dilution, showing high correlation (r = 0.96; R2 ≥ 0.94) and significance (P < 0.01). Furthermore, we demonstrated that the synDNAs can be used as DNA spike-ins to generate linear models and predict with high accuracy the absolute number of bacterial cells in complex microbial communities. IMPORTANCE The synDNAs designed in this study enable accurate and reproducible measurements of absolute amount and fold changes of bacterial species in complex microbial communities. The method proposed here is versatile and promising as it can be applied to bacterial communities or genomic features like genes and operons, in addition to being easily adaptable by other research groups at a low cost. We also made the synDNAs' sequences and the plasmids available to encourage future application of the proposed method in the study of microbial communities.