Development of a Novel Biosensor to Accelerate Investigations of the Gut Microbiome - The human gut microbiome is a promising avenue of precision medicine that has been linked to immunology, metabolism, neurodegenerative disease, cancer, and infectious disease. However, clinical translation of these findings has been limited. A key barrier to translation is that existing data generation tools cannot support the creation of the large, time-longitudinal datasets needed for effective discovery & reproduction of clinically actionable microbiome biomarkers. Without strong data, investigators today have reduced ability to advance the microbiome's precision medicine potential. BiomeSense is developing the first dedicated tools for large-scale, standardized, and low-cost microbiome data generation to eliminate the barriers to large, longitudinal microbiome datasets. These consist of the GutLab, a novel hardware technology for continuous, standardized data generation; and MetaBiome, a novel bioinformatics software platform to standardize and streamline metanalyses. At the time of the grant period, GutLab prototypes will have undergone laboratory validation and preliminary at-home testing. In this Phase II project, BiomeSense will validate the real-world functionality of the GutLab prototypes in a large observational study. User-testing of GutLab prototypes in the home environment will allow for technical stress-testing and user feedback, while data generated by these tests can be fed into MetaBiome for improved algorithm development and validation. This approach will simultaneously benefit hardware and software development pathways. Aim 1 describes the execution of the observational GutLab study, while Aim 2 describes the use of this dataset to develop a novel analytical component for Metabiome to forecast microbial communities. At the end of Aim 1, BiomeSense will have created one of the highest-quality, largest, and densest metagenomic datasets in existence. The data from this study will be available through BiomeSense's reference cohort database for use in future metanalyses, and for the continued development of proprietary analytical techniques. In the long term, the forecasting models generated in Aim 2 can be applied in the clinic to monitor disease progression or detect anomalies and critical transition points days or even weeks before the events occur. In the short term, this project will support the field-wide adoption of BiomeSense's technology, which will routinely enable the discovery of microbiome-based biomarkers and translation into consumer facing diagnostics & therapeutics.