Communicating regulatory high-throughput sequencing data using BioCompute Objects.

This project demonstrates the use of the IEEE 2791-2020 Standard (BioCompute Objects [BCO]) to enable the complete and concise communication of results from next generation sequencing (NGS) analysis. One arm of a clinical trial was replicated using synthetically generated data made to resemble real biological data and then two independent analyses were performed. The first simulated a pharmaceutical regulatory submission to the US Food and Drug Administration (FDA) including analysis of results and a BCO. The second simulated an FDA review that included an independent analysis of the submitted data. Of the 118 simulated patient samples generated, 117 (99.15%) were in agreement in the two analyses. This process exemplifies how a template BCO (tBCO), including a verification kit, facilitates transparency and reproducibility, thereby reinforcing confidence in the regulatory submission process.

Impact of Host DNA and Sequencing Depth on the Taxonomic Resolution of Whole Metagenome Sequencing for Microbiome Analysis.

The amount of host DNA poses a major challenge to metagenome analysis. However, there is no guidance on the levels of host DNA, nor on the depth of sequencing needed to acquire meaningful information from whole metagenome sequencing (WMS). Here, we evaluated the impact of a wide range of amounts of host DNA and sequencing depths on microbiome taxonomic profiling using WMS. Synthetic samples with increasing levels of host DNA were created by spiking DNA of a mock bacterial community, with DNA from a mouse-derived cell line. Taxonomic analysis revealed that increasing proportions of host DNA led to decreased sensitivity in detecting very low and low abundant species. Reduction of sequencing depth had major impact on the sensitivity of WMS for profiling samples with 90% host DNA, increasing the number of undetected species. Finally, analysis of simulated datasets with fixed depth of 10 million reads confirmed that microbiome profiling becomes more inaccurate as the level of host DNA increases in a sample. In conclusion, samples with high amounts of host DNA coupled with reduced sequencing depths, decrease WMS coverage for characterization of the microbiome. This study highlights the importance of carefully considering these aspects in the design of WMS experiments to maximize microbiome analyses.