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.

Improving the safety of outpatient parenteral antimicrobial therapy for patients with solid tumors.

BACKGROUND AND OBJECTIVES: Outpatient parenteral antimicrobial therapy (OPAT) for infections has been in use for nearly 40 years, and although it has been found safe and efficacious, its use has been studied primarily among otherwise healthy patients. We aimed to develop and evaluate an OPAT program for patients with cancer, particularly solid tumors. METHODS: We implemented multiple quality improvement interventions between June 2018 and January 2020. We retrospectively and prospectively collected data on demographics, the completeness of infectious diseases (ID) physician consultation notes, rates of laboratory test result monitoring, ID clinic follow-up, and 30-day outcomes, including unplanned OPAT-related readmissions, OPAT-related emergency center visits, and deaths. RESULTS: Completeness of ID provider notes improved from a baseline of 77 to 100% (p < .0001) for antimicrobial recommendations, 75 to 97% (p < .0001) for follow-up recommendations, and 19 to 98% (p < .0001) for laboratory test result monitoring recommendations. Completion of laboratory tests increased from a baseline rate of 24 to 56% (p = .027). Thirty-day unplanned OPAT-related readmission, ID clinic follow-up, 30-day emergency center visit, and death rates improved without reaching statistical significance. CONCLUSIONS: Sustained efforts, multiple interventions, and multidisciplinary engagement can improve laboratory test result monitoring among solid tumor patients discharged with OPAT. Although demonstrating a decrease in unplanned readmissions through institution of a formal OPAT program among patients with solid malignancies may be more difficult compared with the general population, the program may still result in improved safety.

Applications and Challenges of Machine Learning to Enable Realistic Cellular Simulations.

In this perspective, we examine three key aspects of an end-to-end pipeline for realistic cellular simulations: reconstruction and segmentation of cellular structures; generation of cellular structures; and mesh generation, simulation, and data analysis. We highlight some of the relevant prior work in these distinct but overlapping areas, with a particular emphasis on current use of machine learning technologies, as well as on future opportunities.