Transcriptional changes in macaques exposed to Sudan virus and treated with a vehicle controls or obeldesivir for 5 or 10 days

Normalized Nanostring transcriptomic data (fold2-change- and Benjamini–Hochberg adjusted p-values) were exported as an .xlsx file. Groups include vehicle control (N=3), treated fatal (N=2), and treated survivor subjects administered ODV for 5 (N=3) or 10 days (N=5) compared against a pre-challenge baseline (0 DPI) at each collection timepoint. Any differentially expressed transcripts with a Benjamini-Hochberg false discovery rate (FDR) corrected p-value less than 0.05 were deemed significant. ODV, obeldesivir; DPI, days post infection., NHPV2_Immunology reporter and capture probe sets (NanoString Technologies) were hybridized with 3 µL of each RNA sample for ~24 hours at 65°C. The RNA:probe set complexes were subsequently loaded onto an nCounter microfluidics cartridge and assayed using a NanoString nCounter SPRINT Profiler.  Samples with an image binding density greater than 2.0 were re-analyzed with 1 µL of RNA to meet quality control criteria.
Briefly, nCounter .RCC files were imported into NanoString nSolver 4.0 software. To compensate for varying RNA inputs and reaction efficiency, an array of 10 housekeeping genes and spiked-in positive and negative controls were used to normalize the raw read counts. The array and number of housekeeping mRNAs are selected by default within the Nanostring nSolver Advanced Analysis module. As both sample input and reaction efficiency are expected to affect all probes uniformly, normalization for run-to-run and sample-to-sample variability is performed by dividing counts within a l..., , # Data S1-S3

To determine immune correlates associated with obeldesivir-mediated protection, we performed targeted transcriptomics on whole blood RNA samples from Sudan virus-exposed macaques using a Nanostring nCounter® SPRINT Profiler and Nanostring NHPV2_Immunology reporter and capture probe sets. Normalized data (fold2-change- and Benjamini–Hochberg adjusted p-values) were exported as an .xlsx file (**Data S1**).

To capture shifts in circulating immune cell populations for each vehicle control (N=3), treated fatal (N=2), and treated survivor (N=3 for 5-day treatment; N=5 for 10-day treatment) group, we performed digital cell quantitation (DCQ) via transcriptional profiling. Predicted cell-type scores were exported as an .xlsx file (**Data S2**).

Pathway analysis was conducted to compare z-scores from canonical pathway, upstream analysis, disease and function, and tox function analyses among groups. Z-scores were exported as an .xlsx file (**Data S3**).

## Description of the da...