Study the phases and progression of infection across the five major components of the host response with the pathogen-agnostic content of the nCounter Host Response Panel. Rapidly advance knowledge of emerging infectious disease with experiments that take minutes to set-up and get results in less than 24 hours.
- Profile 785 human genes across 50+ pathways optimized for blood but suitable for all sample types
- Study the five elements of the host response
- Host Susceptibility
- Interferon Response
- Innate Immune Cell Activation
- Adaptive Immune Response
- Detect the presence of a pathogen and evaluate organ-specific tissue damage with a Panel Plus spike-in
- Develop signatures of host response dynamics
- Identify and validate biomarkers for disease severity
- Evaluate the effect of vaccines & therapies
Get off-the-shelf data analysis and publication-ready figures with the nSolver™ Analysis Software.
Biological Framework of the Host Response Panel
|Innate Immune Cell Activation
|Adaptive Immune Response
|Angiotensin System||ALPK1 Signaling||Chemokine Signaling||BCR Signaling||Angiotensin System|
|Virus-Host Interaction||DNA Sensing||Cytoxicity||Complement System||Apoptosis|
|Glycan Sensing||Host Defense Peptides||Immune Exhaustion||Autophagy|
|Inflammasomes||IL-1 Signaling||Immune Memory||Coagulation|
|Interferon Response Genes||IL-2 Signaling||Lymphocyte Trafficking||HIF1A Signaling|
|JAK/STAT Signaling||IL-6 Signaling||MHC Class I Antigen Presentation||Leukotriene and Prostaglandin Inflammation|
|MAPK Signaling||IL-17 Signaling||MHC Class II Antigen Presentation||Lysosomes|
|NLR Signaling||Mononuclear Cell Migration||Mononuclear Cell Migration||Oxidative Stress Response|
|RNA Sensing||Myeloid Activation||T cell Costimulation||Proteotoxic Stress|
|TLR Signaling||Myeloid Inflammation||TCR Signaling||Tissue Stress|
|TNF Signaling||NK Activity||TH1 Differentiation||TNF Signaling|
|Type I Interferon Signaling||NF-kappaB Signaling||TH2 Differentiation|
|Type II Interferon Signaling||NO Signaling||TH9 Differentiation|
|Type III Interferon Signaling||Other Interleukin Signaling||TH17 Differentiation|
|Oxidative Stress Response||Treg Differentiation|
Customize your research project by adding tissue or pathogen-specific probes to the Host Response Panel with a 55-gene Panel Plus. Add the off-the-shelf 20-gene Coronavirus Panel Plus to study SARS-CoV-2 and other coronaviruses or build your own Panel Plus gene list with transcripts specific for different tissue types. Mix and match transcripts from the pathogen of your choice and additional host tissue markers to add a Panel Plus to the Host Response Panel for studying the pathogenesis of various infectious diseases.
Study organ damage wrought by COVID-19 by adding up to 55 genes to the Host Response Panel as a Panel Plus or by adding custom targets to a GeoMx Digital Spatial Profiling RNA assay. Download the COVID-19 Tissue Reference Gene List to get ideas on which genes to add for studying the effect of COVID-19 on the kidney, GI tract, heart, liver, endothelium, lung, and brain. Check back often for updates as the NanoString Bioinformatics team continually adds to and refines these reference gene lists.
The content is mined from publications and represents genes associated multiple times in the literature as related to a tissue in the context of COVID-19, as well as the top ten genes associated with that tissue. The rationale for each gene’s inclusion and its presence or absence in the Host Response Panel and the GeoMx COVID-19 Immune Response Atlas is noted. Listed genes can be used alongside any nCounter gene expression panel or GeoMx RNA assay; please contact Bioinformatics for more information on which genes may already be present in a given panel or GeoMx RNA assay of interest.
Take advantage of comprehensive coverage of the most relevant immune checkpoints to study modulation of the host immune response and subsequent inflammatory cascade.
|ADORA2A (A2aR)||CD70||HAVCR2 (TIM3)||CD274 (PD-L1)||TNFRSF9 (4-1BB)|
|CD27||CD80||ICOS||PDCD1LG2 (PD-L2)||TNFSF9 (4-1BBL)|
|CD28||CD86||ICOSLG (B7-H2)||TIGIT||TNFRSF18 (GITR)|
|CD40||CD276 (B7-H3)||LAG3||TNFRSF4 (OX40)||TNFSF18 (GITRL)|
|CD40LG||CTLA-4||PDCD1 (PD-1)||TNFSF4 (OX40L)||VSIR (VISTA)|
Probes included in the Host Response Panel have high homology to non-human primates, allowing for seamless comparative infectious disease research as well as preclinical studies. Percent identity is used to estimate likelihood of the probe functioning on non-human primate targets. Additional comparisons with other NHP species are available upon request.
|Number of Genes|
|% Identity||Cynomologus Macaque||Rhesus Macaque|
Genes included in the Host Response Panel provide unique cell profiling data to measure the relative abundance of 14 different immune cell types. The table below summarizes the genes included in each cell type signature, as qualified through biostatistical approaches and selected literature in the field
|Cell Type||Associated Human Genes|
|B cells||BLK, CD19, FAM30A, FCRL2, MS4A1, PNOC, SPIB, TCL1A, TNFRSF17|
|CD8 T cells||CD8A, CD8B|
|Cytotoxic cells||CTSW, GNLY, GZMA, GZMB, GZMH, KLRB1, KLRD1, KLRK1, NKG7, PRF1|
|Dendritic cells||CCL13, CD209, HSD11B1|
|Exhausted CD8 cells||CD244, EOMES, LAG3, PTGER4|
|Macrophages||CD163, CD68, CD84, MS4A4A|
|Mast cells||CPA3, HDC, MS4A2, TPSAB1/B2|
|NK CD56dim cells||IL21R, KIR2DL3, KIR3DL1/2|
|NK cells||NCR1, XCL1/2|
|Neutrophils||CEACAM3, CSF3R, FCAR, FCGR3A/B, FPR1, S100A12, SIGLEC5|
|T cells||CD3D, CD3E, CD3G, CD6, SH2D1A, TRAT1|
|Number of Targets||785 (Human), including 12 internal reference genes|
|Sample Input - Standard (No amplification required)||25-300 ng|
|Sample Input - Low Input||As little as 1 ng with nCounter Low Input Kit and Primer Pools (sold separately)|
|Sample Type(s)||Cultured cells/cell lysates, sorted cells, FFPE-derived RNA, total RNA, fragmented RNA, PBMCs, and whole blood/plasma|
|Customizable||Add up to 55 unique genes with Panel-Plus and/or up to 10 custom protein targets|
|Time to Results||Approximately 24 hours|
|Data Analysis||nSolver™ Analysis Software (RUO)|
- Altman, MC et al. Development and Characterization of a Fixed Repertoire of Blood Transcriptome Modules Based on Co-expression Patterns Across Immunological States. (2020) doi:10.1101/525709.
- Azouz F et al. Integrated MicroRNA and mRNA Profiling in Zika Virus-Infected Neurons. Viruses. 2019;11(2):162.
- Borchers, AT et al. Respiratory Syncytial Virus—A Comprehensive Review. Clin Rev Allergy Immunol. 2013;45(3):331-79.
- Channappanavar R. & Perlman, S. Pathogenic human coronavirus infections: causes and consequences of cytokine storm and immunopathology. Semin Immunopathol. 2017;39(5):529-539.
- Dandekar, AA and Perlmam, S. Immunopathogenesis of coronavirus infections: implications for SARS. Nat Rev Immunol. 2005;5(12):917-27.
- Fitch CD. Ferriprotoporphyrin IX, phospholipids, and the antimalarial actions of quinoline drugs. Life Sciences. 2004;74(16):1957–1972.
- Gordon DE et al. A SARS-CoV-2 protein interaction map reveals targets for drug repurposing. Nature. 2020;583(7816):459-468.
- Hadjadj J et al. Impaired type I interferon activity and inflammatory responses in severe COVID-19 patients. 2020;369(6504):718-724.
- He D et al. Whole blood vs PBMC: compartmental differences in gene expression profiling exemplified in asthma. Allergy Asthma Clin Immunol. 2019;15(67).
- Huang C et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. The Lancet. 2020;395(10223):497–506.
- Jardine L. et al. Lipopolysaccharide inhalation recruits monocytes and dendritic cell subsets to the alveolar airspace. Nat Commun. 2019;10(1):1999.
- Kannan, M et al. Platelet activation markers in evaluation of thrombotic risk factors in various clinical settings. Blood Rev. 2019;37:100583.
- Kash JC & Taubenberger JK. The Role of Viral, Host, and Secondary Bacterial Factors in Influenza Pathogenesis. Am J Pathol. 2015;185(6):1528-36.
- Kim D et al. The Architecture of SARS-CoV-2 Transcriptome. Cell. 2020;181(4): 914-921.e10
- Liu X. et al. Transcriptomic signatures differentiate survival from fatal outcomes in humans infected with Ebola virus. Genome Biol. 2017;18(4).
- Lou Z. et al. Current progress in antiviral strategies. Trends in Pharmacological Sciences. 2014 35(2):86-102.
- Mao L. et al. Neurologic Manifestations of Hospitalized Patients With Coronavirus Disease 2019 in Wuhan, China. JAMA Neurol. 2020;77(6):1-9.
- Moncunill G. et al. Antigen-stimulated PBMC transcriptional protective signatures for malaria immunization. Sci. Transl. Med. 2020;12(543).
- Moore JB & June CH. Cytokine release syndrome in severe COVID-19. Science. 2020;368(6490):473–474.
- Ong, EZ et al. A Dynamic Immune Response Shapes COVID-19 Progression. Cell Host & Microbe 2020;27(6):879-882.e2.
- Prescott J. et al. Rousette Bat Dendritic Cells Overcome Marburg Virus-Mediated Antiviral Responses by Upregulation of Interferon-Related Genes While Downregulating Proinflammatory Disease Mediators. mSphere. 2019;4(6):e00728-19.
- Razonable, RR. Antiviral Drugs for Viruses Other Than Human Immunodeficiency Virus. Mayo Clin Proc. 2011;86(10):1009-26.
- Sanders JM et al. Pharmacologic Treatments for Coronavirus Disease 2019 (COVID-19): A Review. JAMA. 2020;323(18):1824–1836.
- Sardu C et al. Is COVID-19 an Endothelial Disease? Clinical and Basic Evidence. doi:10.20944/preprints202004.0204.v1.
- Singhania, A et al. The value of transcriptomics in advancing knowledge of the immune response and diagnosis in tuberculosis. Nat Immunol. 2018;19(11):1159-1168.26.
- Speranza, E et al. A conserved transcriptional response to intranasal Ebola virus exposure in nonhuman primates prior to onset of fever. Sci Transl Med. 2018;10(434):eaaq1016.
- To KKW et al. Rhinovirus – From bench to bedside. J Formos Med Assoc. 2017;116(7):496-504.
- Xiong, Y. et al. Transcriptomic characteristics of bronchoalveolar lavage fluid and peripheral blood mononuclear cells in COVID-19 patients. Emerging Microbes & Infections. 2020;9(1):761–770.
- Zhai, Y et al. Host Transcriptional Response to Influenza and Other Acute Respiratory Viral Infections –A Prospective Cohort Study. PLoS Pathog. 2015;11(6):e1004869.
- Zhang C et al. The cytokine release syndrome (CRS) of severe COVID-19 and Interleukin-6 receptor (IL-6R) antagonist Tocilizumab may be the key to reduce the mortality. International Journal of Antimicrobial Agents. 2020;55(5):105954.
- Zheng M. et al. Functional exhaustion of antiviral lymphocytes in COVID-19 patients. Cell Mol Immunol. 2020;17(5):533-535.
|Product||Product Description||Quantity||Catalog Number|
|nCounter Human Host Response Panel||Includes 785 genes; 12 internal reference genes for data normalization||12 Reactions||XT-HHR-12|
|Coronavirus Panel Plus||20 Probe Panel Plus. Includes 9 probes targeting the SARS-CoV-2 virus, 1 probe for the human viral receptor ACE2, and 10 additional probes targeting SARS and other human coronaviruses||12 Reactions||CORONAPP-12|
|Low RNA Input Kit||Kit for use with all Low RNA Input Primer Pools||48 Reactions||LOW-RNA-48|
|nCounter Master Kit (Max or FLEX Systems) Reagents and Cartridges||Reagents, cartridges, and consumables necessary for sample processing on nCounter MAX and FLEX Systems||12 Reactions||NAA-AKIT-012|
|nCounter SPRINT Cartridge 1 Cartridge, 12 lanes||Sample Cartridge for nCounter SPRINT System||12 Reactions||SPRINT-CAR-1.0|
|nCounter SPRINT Reagent Pack||nCounter SPRINT Reagent Pack containing Reagents A, B, C, and Hybridization Buffer||192 Reactions||SPRINT-REAG-KIT|
For Research Use Only. Not for use in diagnostic procedures.