Supplementary Materials

Supplementary Material for:

Longitudinal peripheral blood transcriptional analysis of a patient with severe Ebola virus disease

John C. Kash, Kathie-Anne Walters, Jason Kindrachuk, David Baxter, Kelsey Scherler, Krisztina B. Janosko, Rick D. Adams, Andrew S. Herbert, Rebekah M. James, Spencer W. Stonier, Matthew J. Memoli, John M. Dye, Richard T. Davey Jr., Daniel S. Chertow, Jeffery K. Taubenberger*

*Corresponding author. Email: taubenbergerj{at}niaid.nih.gov

Published 12 April 2017, Sci. Transl. Med. 9, eaai9321 (2017)
DOI: 10.1126/scitranslmed.aai9321

This PDF file includes:

  • Materials and Methods
  • Fig. S1. Heatmap showing expression of MHC class I and class II sequences.
  • Fig. S2. Graphs showing whole EBOV and Ebola GP–specific IgG titers.
  • Fig. S3. Graph showing EBOV-neutralizing IgG titers.
  • Fig. S4. Scatterplot showing comparison of expression level sequences with positive correlation to serum Ebola NP RNA on d13 relative to d28.
  • Fig. S5. Graph of type I IFN–related gene expression as determined by qRT-PCR.
  • Fig. S6. Graphs showing serum levels for TNFα, IL-12p70, IL-2, IL-4, and IL-5.
  • Fig. S7. Graphs showing serum levels for IL-1β, IL-13, IL-17a, and IFN-γ.
  • Fig. S8. Graphs showing serum levels for IL-8, IL-10, IL-6, and IL-7.
  • Fig. S9. Graphs showing serum levels for G-CSF, GM-CSF, CCL2 (MCP-1), and CCL4 (MIP-1β).
  • Fig. S10. Gene expression correlating with serum D-dimer levels during EVD.
  • Fig. S11. Gene expression correlating with platelet counts during EVD.
  • Fig. S12. Expression levels of lymphocyte-related mRNAs.
  • Fig. S13. Functional annotation of transcripts correlating with serum creatinine levels showing enriched pathways.
  • Fig. S14. Graph showing serum EBOV-specific IgM titers.
  • Fig. S15. Graph showing absence of EBOV GP RNA in outpatient samples.

[Download PDF]

Other Supplementary Material for this manuscript includes the following:

  • Table S1 (Microsoft Excel format). Gene ontology analysis of sequences positively correlated with serum EBOV GP mRNA.
  • Table S2 (Microsoft Excel format). Gene ontology analysis of sequences negatively correlated with serum EBOV GP mRNA.
  • Table S3 (Microsoft Excel format). Gene ontology analysis of sequences positively correlated with serum EBOV GP mRNA and higher expression on d13 relative to d14.
  • Table S4 (Microsoft Excel format). Gene ontology analysis of sequences positively correlated with serum EBOV GP mRNA and higher expression on d14 relative to d13.
  • Table S5 (Microsoft Excel format). Gene ontology analysis of sequences positively correlated with serum EBOV GP mRNA and higher expression on d20 relative to d21.
  • Table S6 (Microsoft Excel format). Gene ontology analysis of sequences positively correlated with serum EBOV GP mRNA and higher expression on d21 relative to d20.
  • Table S7 (Microsoft Excel format). Genes positively correlated with serum EBOV NP mRNA and higher expression on d25 relative to d28.
  • Table S8 (Microsoft Excel format). Gene ontology analysis of sequences positively correlated with serum EBOV GP mRNA and higher expression on d28 relative to d25.
  • Table S9 (Microsoft Excel format). Gene ontology analysis of sequences positively correlated with PBL EBOV NP mRNA.
  • Table S10 (Microsoft Excel format). Gene ontology analysis of inflammatory gene expression in individual K-means groups.
  • Table S11 (Microsoft Excel format). Genes with expression values showing negative correlation (≤−0.6) with serum D-dimer levels.
  • Table S12 (Microsoft Excel format). Genes with expression values showing positive correlation (≥0.6) with serum D-dimer levels.
  • Table S13 (Microsoft Excel format). Genes with expression values showing negative correlation (≥0.6) with platelet levels.
  • Table S14 (Microsoft Excel format). Genes with expression values showing positive correlation (≤−0.6) with platelet levels.
  • Table S15 (Microsoft Excel format). Gene expression correlating with clinical parameters of coagulopathy.
  • Table S16 (Microsoft Excel format). Genes with expression values showing negative correlation (≥0.6) with serum creatinine levels.
  • Table S17 (Microsoft Excel format). Genes with expression values showing positive correlation (≤−0.6) with serum creatinine levels.

[Download Tables S1 to S17]