Evidence map›Paper›PMID 20824632›Full record

ArticleCytometry. Part A : the journal of the International Society for Analytical Cytology2010

Tyramide signal amplification for analysis of kinase activity by intracellular flow cytometry.

Matthew R Clutter, Garrett C Heffner, Peter O Krutzik, Kacey L Sachen, Garry P Nolan

Open access · bronzeAbstract read
In one paragraph

Article in Cytometry. Part A : the journal of the International Society for Analytical Cytology, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
1.4field-weighted citation impact, top 20% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

20 citing papers in PubMed, 45 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Review
  6. Review
  7. Science translational medicine · 2025
    Article
  8. Article
  9. Type-Independent 3D Writing and Nano-Patterning of Confined Biopolymers.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2023
    Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Spectral flow cytometry.Current protocols in cytometry · 2013
    Review
  19. Single-cell protein analysis.Current opinion in biotechnology · 2012
    Review
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 2 institutions in 1 country.

Matthew R ClutterDepartment of Microbiology and Immunology, Baxter Laboratory for Stem Cell Biology, Stanford University School of Medicine, Stanford, California, USA.
Garrett C Heffner
Peter O Krutzik
Kacey L Sachen
Garry P Nolan
Stanford University · USBaxter (United States) · US

Funding

Using a tonsil organoid system to probe conditions for the induction of protective antibody and T cell responses to influenza.U19AI057229 · NIAID · STANFORD UNIVERSITY · PI Mark Morris Davis · 2003 to 2026
$88.5M
Systems Approach to Innate Immunity-Inflammation-SepsisU54AI054523 · NIAID · SCRIPPS RESEARCH INSTITUTE, THE · PI ULEVITCH, RICHARD J · 2002 to 2006
$28.0M
MOLECULAR &CELLULAR IMMUNOBIOLOGYT32AI007290 · NIAID · STANFORD UNIVERSITY · PI Sean Curtis Bendall, Olivia M Martinez · 1985 to 2026
$27.0M
TRIGGERING CELL DEATH IN B CELL LYMPHOMAP01CA034233 · NCI · STANFORD UNIVERSITY · PI NOLAN, GARRY P · 1985 to 2010
$19.5M
Software & Hardware Inference Engines for Automated Determination of Primary CellR01CA130826 · NCI · STANFORD UNIVERSITY · PI NOLAN, GARRY P · 2008 to 2011
$6.7M
NHLBI PROTEOMICS INITIATIVE-N01HV28183N01HV028183 · HV · STANFORD UNIVERSITY · PI NOLAN, GARRY P · 2002 to 2006
–
NCI NIH HHS 1R01CA130826NCI NIH HHS P01 CA034233NCI NIH HHS P01 CA034233-24NCI NIH HHS R01 CA130826NHLBI NIH HHS N01-HV-28183NIAID NIH HHS HHSN272200700038CNIAID NIH HHS T32 AI007290NIAID NIH HHS U19 AI057229NIAID NIH HHS U54 AI054523
6 · The paper itself

Abstract

Intracellular flow cytometry permits quantitation of diverse molecular targets at the single-cell level. However, limitations in detection sensitivity inherently restrict the method, sometimes resulting in the inability to measure proteins of very low abundance or to differentiate cells expressing subtly different protein concentrations. To improve these measurements, an enzymatic amplification approach called tyramide signal amplification (TSA) was optimized for assessment of intracellular kinase cascades. First, Pacific Blue, Pacific Orange, and Alexa Fluor 488 tyramide reporters were shown to exhibit low nonspecific binding in permeabilized cells. Next, the effects of antibody concentration, tyramide concentration, and reaction time on assay resolution were characterized. Use of optimized TSA resulted in a 10-fold or greater improvement in measurement resolution of endogenous Erk and Stat cell signaling pathways relative to standard, nonamplified detection. TSA also enhanced assay sensitivity and, in conjunction with fluorescent cell barcoding, improved assay performance according to a metric used to evaluate high-throughput drug screens. TSA was used to profile Stat1 phosphorylation in primary immune system cells, which revealed heterogeneity in various populations, including CD4+ FoxP3+ regulatory T cells. We anticipate the approach will be broadly applicable to intracellular flow cytometry assays with low signal-to-noise ratios.

Indexed as

AnimalsCell Line, TumorCell SeparationExtracellular Signal-Regulated MAP KinasesFemaleFlow CytometryHumansInterferon-gammaInterleukin-6Jurkat CellsLeukemiaLimit of DetectionLymphomaMiceMice, Inbred BALB CNucleic Acid Amplification TechniquesExtracellular Signal-Regulated MAP KinasesInterferon-gammaInterleukin-6PhosphoproteinsTyramine

Identifiers

PMID20824632
PMCPMC3036012
OpenAlexW2074203840

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.