DOI: 10.5061/dryad.wdbrv15vn
title: Transcriptional changes in macaques exposed to Sudan virus and treated with a vehicle controls or obeldesivir for 5 or 10 days

description: 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.
description: 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 lane by the geometric mean of the reference/normalizer probes from the same lane (i.e., all probes/count levels within a lane are adjusted by the same factor). The ideal normalization genes are automatically determined by selecting those that minimize the pairwise variation statistic and are selected using the widely used geNorm algorithm as implemented in the Bioconductor package NormqPCR. The data was analyzed with NanoString nSolver Advanced Analysis 2.0 package for differential expression. Normalized data (fold2-change- and Benjamini–Hochberg adjusted p-values) were exported as an .xlsx file (<strong>Data S1</strong>). 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. Human annotations were added for each respective mRNA to perform immune cell profiling within nSolver (<strong>Data S2</strong>). For the heatmaps, groups of vehicle control (N=3), treated fatal (N=2), and treated survivor subjects administered ODV for 5 (N=3) or 10 days (N=5) were compared against their pre-challenge baseline (0 DPI) at each collection timepoint. For enrichment analysis, differentially expressed transcripts and adjusted p-values from the Data S1 file were imported into Ingenuity Pathway Analysis (IPA; Qiagen) for canonical pathway, upstream analysis, disease and function, and tox function analyses with respect to a pre-challenge baseline (<strong>Data S3</strong>). The topmost significant pathways based on z-scores were imported into GraphPad Prism version 10.0.1 to produce heatmaps.
description: # 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 data and file structure **Data
 S1.** **Normalized fold2-change- and Benjamini–Hochberg adjusted p-values
 in vehicle control and obeldesivir-treated groups.** Values were derived
 from macaque blood samples in vehicle control (N=3), treated fatal (N=2),
 and treated survivor (N=3 for 5-day treatment; N=5 for 10-day treatment)
 groups at each timepoint. (e.g., Control : 01 vs. Control : 00 means a
 comparison was made between the control group at 1 day post infection
 versus the day 0 pre-challenge baseline). Comparisons were made at each
 collection timepoint among vehicle control (N=3), treated fatal (N=2 for
 5-day treatment), and treated survivor (N=3 for 5-day treatment; N=5 for
 10-day treatment) groups. The Treated 1-5 groups (fatal, survivor)
 indicate that subjects were treated with obeldesivir for 5 consecutive
 days. The Treated 1-10 group (all survivors) indicates subjects were
 treated with obeldesivir for 10 consecutive days. Any differentially
 expressed transcripts with a Benjamini-Hochberg false discovery rate (FDR)
 corrected p-value less than 0.05 were deemed significant. Empty columns
 denote a group size n &lt; 3 for that particular time point (i.e., the
 vehicle control group at days 1, 3, 5, and 9 days post infection versus a
 day 0 post infection pre-challenge baseline) due to inconsistent sampling
 at that timepoint for the control group. Other empty cells denote that
 statistics could not be calculated due to the lack of detectable
 transcripts for that particular probe. Please also note that annotations
 are not provided for non-human primate probe sets and so that column is
 empty. Abbreviations: mRNA, messenger RNA. **Data S2.** **Cell-type trend
 scores in individual vehicle control and obeldesivir-treated subjects.**
 Raw abundance values of cell types were derived from blood samples from
 individual macaque subjects treated with a vehicle control (N=3) or
 obeldesivir (N=10) (continuous data). Human annotations were added for
 each respective mRNA to perform immune cell profiling within nSolver.
 Categorial data variables include cytotoxic cells, T-cells, exhausted CD8
 T-cells, B-cells, NK CD56dim, macrophages, neutrophils, CD8 T cells, NK
 cells, mast cells, and Th1 cells. The continuous variable includes
 cell-type trend scores. Empty cells denote a cell-type score could not be
 derived due to the lack of detectable transcripts for that particular
 probe (score of 0). Note that our methods do not support the conclusion
 that one cell type is more abundant than another. Rather, they support the
 claim that a given cell type is more abundant in one sample than in
 another. Abbreviations: C, control subject; T, treated subject; D, day
 post infection; NK, natural killer; Th1, T helper 1. **Data S3.**
 **Enrichment** **Z-scores in vehicle control and obeldesivir-treated
 groups.** Z-scores were derived using Ingenuity Pathway Analysis (Qiagen)
 for canonical pathway, upstream analysis, disease and function, and tox
 function analyses. Comparisons were made at each collection timepoint
 among vehicle control (N=3), treated fatal (N=2), and treated survivor
 (N=3 for 5-day treatment; N=5 for 10-day treatment) groups. For example,
 "Control : 04 vs. Control : 00" means a comparison was made
 between the control group at 4 days post infection versus the day 0
 pre-challenge baseline. The Treated 1-5 groups (fatal, survivor) indicate
 that subjects were treated with obeldesivir for 5 consecutive days. The
 Treated 1-10 group (all survivors) indicates subjects were treated with
 obeldesivir for 10 consecutive days. A cell with N/A indicates that an
 insufficient number of transcripts mapped to that term and so z-scores
 could not be calculated. ## Sharing/Access information All data are
 provided as .xlsx files. ## Code/Software The data was analyzed with
 NanoString nSolver and the Advanced Analysis 2.0 package for differential
 expression.