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Ncounter analysis technology

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The NCounter analysis technology is a digital, molecular barcoding platform that enables precise and multiplexed measurement of gene expression and other biomolecules. The core function of this technology is to directly detect and count individual molecules of target analytes in a sample.

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Lab products found in correlation

Direct zol rna miniprep plus kit, by Zymo Research (2 mentions) Tempus, by Thermo Fisher Scientific (2 mentions) Maxwell 16 lev blood rna kit, by Promega (2 mentions) Maxwell extractor, by Promega (2 mentions) Paxgene, by BD (2 mentions) Rneasy plus micro kit, by Qiagen (2 mentions) Paxgene blood rna tube, by BD (2 mentions) Hd 1 analyzer, by Quanterix (1 mentions)

6 protocols using ncounter analysis technology

1

IL-23 Modulates Metabolism Pathways

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Cells were stimulated with IL-23 or left untreated, and RNA was purified using a Direct-zol RNA miniprep plus kit (Zymo Research, Irvine, CA). RNA expression profiling was performed via NanoString nCounter Analysis Technology (NanoString, Seattle, WA) using an nCounter mouse metabolism pathways panel with 748 genes and 20 internal reference genes. Data were analyzed using the nSolver 4.0 software package. In brief, raw transcript counts were normalized using negative and positive synthetic sequences provided within each code set to account for background noise and technical variation, respectively. Differential gene expression between untreated and IL-23–treated cells was examined. Genes upregulated or downregulated 2-fold or more with adjusted p < 0.05 were identified as modulated by IL-23.
Sah P, & Zenewicz L.A. (2023). The Polyamine Putrescine Is a Positive Regulator of Group 3 Innate Lymphocyte Activation. ImmunoHorizons, 7(1), 41-48.
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2

Transcriptional profiling of IL-23 response

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Cells were stimulated with IL-23 or left untreated, and RNA was purified using a Direct-zol RNA miniprep plus kit (Zymo Research; Irvine, CA). RNA expression profiling was performed via NanoString nCounter Analysis Technology (NanoString; Seattle, WA) using an nCounter mouse metabolism pathways panel with 748 genes and 20 internal reference genes. Data were analyzed using the nSolver 4.0 software package. Briefly, raw transcript counts were normalized using negative and positive synthetic sequences provided within each code set to account for background noise and technical variation, respectively. Differential gene expression between untreated and IL-23-treated cells was examined. Genes up- or down-regulated two-fold or more with adjusted p-value less than 0.05 were identified as modulated by IL-23.
Lorito M., Woo S.L., Fernandez I.G., Colucci G., Harman G.E., Pintor-Toro J.A., Filippone E., Muccifora S., Lawrence C.B., Zoina A., Tuzun S, & Scala F. (1998). Genes from mycoparasitic fungi as a source for improving plant resistance to fungal pathogens. Proceedings of the National Academy of Sciences of the United States of America, 95(14), 7860-7865.
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3

Transcriptome Analysis of COVID-19 Patients

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Whole blood was collected into PAXgene (BD Biosciences) or Tempus (Thermo Fisher Scientific) blood RNA tubes or EDTA tubes. RNA was extracted with the corresponding RNA extraction kits or with the Maxwell 16 LEV Blood RNA kit and a Maxwell extractor (Promega) and quantified by spectrometry (Nanovue). For P5, RNA was extracted from sorted T cells with the RNeasy Plus microkit (Qiagen). Relative expression levels were determined for TRBV 11–2 with nCounter analysis technology (NanoString Technologies), by calculating TRBV 11–2 mRNA levels relative to other TRBV mRNA levels and normalizing against the median value for the healthy volunteer group. Blood samples from P1, P2, and P5 were obtained on days 7, 4, and 9 after symptom onset, respectively.
Boyce F.M., Beggs A.H., Feener C, & Kunkel L.M. (1991). Dystrophin is transcribed in brain from a distant upstream promoter.. Proceedings of the National Academy of Sciences of the United States of America, 88(4), 1276-1280.
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4

Transcriptome Analysis of COVID-19 Patients

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Whole blood was collected into PAXgene (BD Biosciences) or Tempus (Thermo Fisher Scientific) blood RNA tubes or EDTA tubes. RNA was extracted with the corresponding RNA extraction kits or with the Maxwell 16 LEV Blood RNA kit and a Maxwell extractor (Promega) and quantified by spectrometry (Nanovue). For P5, RNA was extracted from sorted T cells with the RNeasy Plus microkit (Qiagen). Relative expression levels were determined for TRBV 11–2 with nCounter analysis technology (NanoString Technologies), by calculating TRBV 11–2 mRNA levels relative to other TRBV mRNA levels and normalizing against the median value for the healthy volunteer group. Blood samples from P1, P2, and P5 were obtained on days 7, 4, and 9 after symptom onset, respectively.
Lee D., Pen J.L., Yatim A., Dong B., Aquino Y., Ogishi M., Pescarmona R., Talouarn E., Rinchai D., Zhang P., Perret M., Liu Z., Jordan I., Bozdemir S.E., Bayhan G.I., Beaufils C., Bizien L., Bisiaux A., Lei W., Hasan M., Chen J., Gaughan C., Asthana A., Libri V., Luna J.M., Jaffré F., Hoffmann H.H., Michailidis E., Moreews M., Seeleuthner Y., Bilguvar K., Mane S., Flores C., Zhang Y., Arias A.A., Bailey R., Schlüter A., Milisavljevic B., Bigio B., Voyer T.L., Materna M., Gervais A., Moncada-Velez M., Pala F., Lazarov T., Levy R., Neehus A.L., Rosain J., Peel J., Chan Y.H., Morin M.P., Pino-Ramirez R.M., Belkaya S., Lorenzo L., Anton J., Delafontaine S., Toubiana J., Bajolle F., Fumadó V., DeDiego M.L., Fidouh N., Rozenberg F., Pérez-Tur J., Chen S., Evans T., Geissmann F., Lebon P., Weiss S.R., Bonnet D., Duval X., Pan-Hammarström Q., Planas A.M., Meyts I., Haerynck F., Pujol A., Sancho-Shimizu V., Dalgard C.L., Bustamante J., Puel A., Boisson-Dupuis S., Boisson B., Maniatis T., Zhang Q., Bastard P., Notarangelo L., Béziat V., de Diego R.P., Rodriguez-Gallego C., Su H.C., Lifton R.P., Jouanguy E., Cobat A., Alsina L., Keles S., Haddad E., Abel L., Belot A., Quintana-Murci L., Rice C.M., Silverman R.H., Zhang S.Y, & Casanova J.L. (2023). Inborn errors of OAS–RNase L in SARS-CoV-2–related multisystem inflammatory syndrome in children. Science (New York, N.Y.), 379(6632), eabo3627.
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5

Quantification of Cytokines and IFN Biomarkers

Cited 1 time
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Cytokines were measured in serum using SimpleplexⓇ technology using ELLA instrument (ProteinSimpleⓇ, San Jose, CA), following manufacturer's instructions. Plasma IFNα2 concentrations were determined by single-molecule Array (SIMOAⓇ) on a HD-1 Analyzer (Quanterix, Lexington, Massachusetts) using a commercial kit for IFN-α2 quantification (Quanterix). Lymphocyte subsets was performed on an automated volumetric flow cytometer from Beckman Coulter (Aquios CL)(12). For IFN‑stimulated genes (ISG) score (IFN score) calculation, whole blood was collected on PAXgene blood RNA tubes (BD, Grenoble, France) and frozen at −80°C until RNA extraction. IFN score was obtained using nCounterⓇ analysis technology (NanoString Technologies, Seattle, WA), as previously described (10 (link)).
Conti F., Oriol G., Cheynet V., Tardiveau C., Cerrato E., Rimmelé T., Lukaszewicz A.C., Argaud L., Cour M., Brengel-Pesce K., Venet F, & Monneret G. (2021). Seroconversion in septic ICU patients presenting with COVID-19: necessary but not sufficient. Archives of Medical Research, 52(8), 850-857.
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6

IFN Signature Determination Protocol

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Whole blood was collected on PAXgene blood RNA tubes (BD, Grenoble, France) for IFN signature and frozen at − 80 °C until RNA extraction. IFN score was obtained using nCounter® analysis technology (NanoString Technologies, Seattle, WA) by calculating the median of the normalized count of 6 ISGs using standardized protocols fulfilling clinical and diagnostic laboratories accreditation requirements from the International Organization for Standardization. As previously described, six interferon responsive genes were monitored: SIGLEC1 (sialic acid binding Ig like lectin 1), IFI27 (interferon alpha inducible protein27), IFI44L (interferon induced protein 44 like), IFIT1 (interferon induced protein with tetratricopeptide repeats 1), ISG15 (interferon-stimulated gene 15) and RSAD2 (radical S-adenosyl methionine domain-containing 2). Three references genes were also measured: ACTB (Actin beta), HPRT1 (hypoxanthine phosphoribosyltransferase 1) and POLR2A (RNA Polymerase II Subunit A) [18 (link)].
Venet F., Cour M., Rimmelé T., Viel S., Yonis H., Coudereau R., Amaz C., Abraham P., Monard C., Casalegno J.S., Brengel-Pesce K., Lukaszewicz A.C., Argaud L, & Monneret G. (2021). Longitudinal assessment of IFN-I activity and immune profile in critically ill COVID-19 patients with acute respiratory distress syndrome. Critical Care, 25, 140.
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