Evidence map›Paper›PMID 31065513›Full record

ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2019

Multiplexed, Sequential Secretion Analysis of the Same Single Cells Reveals Distinct Effector Response Dynamics Dependent on the Initial Basal State.

Zhuo Chen, Yao Lu, Kerou Zhang, Yang Xiao, Jun Lu, Rong Fan

Abstract read
In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
–field-weighted citation impact
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

19 citing papers in PubMed.

  1. Single-Cell Protein Assays in Context: From 2D to 3D and In Situ Analysis.Annual review of analytical chemistry (Palo Alto, Calif.) · 2026
    Review
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Deciphering Cell-Cell Interactions with Integrative Single-Cell Secretion Profiling.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2023
    Article
  10. Article
  11. Mapping secretome-mediated interaction between paired neuron-macrophage single cells.Proceedings of the National Academy of Sciences of the United States of America · 2022
    Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Review
  17. Review
  18. Review
  19. 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

6 authors.

Zhuo ChenDepartment of Biomedical Engineering Yale University New Haven CT 06520 USA.
Yao LuDepartment of Biomedical Engineering Yale University New Haven CT 06520 USA.
Kerou ZhangDepartment of Biomedical Engineering Yale University New Haven CT 06520 USA.
Yang XiaoDepartment of Biomedical Engineering Yale University New Haven CT 06520 USA.
Jun LuDepartment of Genetics Yale School of Medicine New Haven CT 06520 USA.
Rong FanDepartment of Biomedical Engineering Yale University New Haven CT 06520 USA.ORCID https://orcid.org/0000-0001-7805-8059

Funding

Project 3: Single Cell Measures of Intratumor Diversity for Optimal Breast Cancer TherapyU54CA193461 · NCI · DANA-FARBER CANCER INST · PI MICHOR, FRANZISKA · 2015 to 2020
$11.2M
Systems analysis of phenotypic switch in control of cancer invasionU54CA209992 · NCI · YALE UNIVERSITY · PI LEVCHENKO, ANDRE · 2016 to 2021
$10.1M
Quantitative Modeling of MicroRNA:Target Interactions in Cell Fate TransitionR01GM116855 · NIGMS · WADSWORTH CENTER · PI DING, YE, LU, JUN · 2016 to 2019
$2.2M
Single-cell cytokine analysis to detect and measure human myelofibrosisU01DK104331 · NIDDK · YALE UNIVERSITY · PI FAN, RONG, LEVINE, ROSS L · 2014 to 2018
$1.9M
The role of microRNAs in leukemic initiation and maintenanceR01CA149109 · NCI · YALE UNIVERSITY · PI LU, JUN · 2011 to 2015
$1.7M
Single cell cytokine analysis of circulating malignant hematopoietic cellsR33CA196411 · NCI · YALE UNIVERSITY · PI FAN, RONG, LEVINE, ROSS L · 2015 to 2017
$1.2M
High-throughput, Multiplexed Detection of miRNA Biomarkers in Single Cancer CellsR21CA177393 · NCI · YALE UNIVERSITY · PI DOYLE, PATRICK S, FAN, RONG · 2013 to 2015
$691k
NCI NIH HHS R01 CA149109NCI NIH HHS R21 CA177393NCI NIH HHS R33 CA196411NCI NIH HHS U54 CA193461NCI NIH HHS U54 CA209992NIDDK NIH HHS U01 DK104331NIGMS NIH HHS R01 GM116855
6 · The paper itself

Abstract

The effector response of immune cells dictated by an array of secreted proteins is a highly dynamic process, requiring sequential measurement of all relevant proteins from single cells. Herein, a microchip-based, 10-plexed, sequential secretion assay on the same single cells and at the scale of ≈5000 single cells measured simultaneously over 4 time points are shown. It is applied to investigating the time course of single human macrophage response to toll-like receptor 4 (TLR4) ligand lipopolysaccharide (LPS) and reveals four distinct activation modes for different proteins in single cells. Protein secretion dynamics classifies the cells into two major activation states dependent on the basal state of each cell. Single-cell RNA sequencing performed on the same samples at the matched time points further demonstrates the existence of two major activation states at the transcriptional level, which are enriched for translation versus inflammatory programs, respectively. These results show a cell-intrinsic heterogeneous response in a phenotypically homogeneous cell population. This work demonstrates the longitudinal tracking of protein secretion signature in thousands of single cells at multiple time points, providing dynamic information to better understand how individual immune cells react to pathogenic challenges over time and how they together constitute a population response.

Indexed as

heterogeneitymacrophage activationsequential analysissingle‐cell cytokine assaysingle‐cell RNA sequencing

Identifiers

PMID31065513
PMCPMC6498135

What OpenQuestion holds

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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.