Evidence map›Paper›PMID 28181485›Full record

ArticleScientific reports2017

High-throughput single-cell analysis for the proteomic dynamics study of the yeast osmotic stress response.

Rongfei Zhang, Haiyu Yuan, Shujing Wang, Qi Ouyang, Yong Chen, Nan Hao, Chunxiong Luo

Abstract read
In one paragraph

Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Metabolic cost of rapid adaptation of single yeast cells.Proceedings of the National Academy of Sciences of the United States of America · 2020
    Article
  5. Genome-scale transcriptional dynamics and environmental biosensing.Proceedings of the National Academy of Sciences of the United States of America · 2020
    Article
  6. Review
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

7 authors.

Rongfei ZhangCenter for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China.
Haiyu YuanThe State Key Laboratory for Artificial Microstructures and Mesoscopic Physics, School of Physics, Peking University, Beijing, China.
Shujing WangCenter for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China.
Qi OuyangCenter for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China.
Yong ChenEcole Normale Superieure, 24 rue Lhomond, 75231 Paris, France.
Nan HaoSection of Molecular Biology, Division of Biological Sciences, University of California San Diego, La Jolla, California, USA.
Chunxiong LuoCenter for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China.

Funding

Dynamically compartmentalized control of gene expression by messenger ribonucleoprotein granulesR01GM111458 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI HAO, NAN · 2014 to 2022
$3.4M
NIGMS NIH HHS R01 GM111458
6 · The paper itself

Abstract

Motorized fluorescence microscopy combined with high-throughput microfluidic chips is a powerful method to obtain information about different biological processes in cell biology studies. Generally, to observe different strains under different environments, high-throughput microfluidic chips require complex preparatory work. In this study, we designed a novel and easily operated high-throughput microfluidic system to observe 96 different GFP-tagged yeast strains in one switchable culture condition or 24 different GFP-tagged yeast strains in four parallel switchable culture conditions. A multi-pipette is the only additional equipment required for high-throughput patterning of cells in the chip. Only eight connections are needed to control 96 conditions. Using these devices, the proteomic dynamics of the yeast stress response pathway were carefully studied based on single-cell data. A new method to characterize the proteomic dynamics using a single cell's data is proposed and compared to previous methods, and the new technique should be useful for studying underlying control networks. Our method provides an easy and systematic way to study signaling pathways at the single-cell level.

Indexed as

ProteomicsHigh-Throughput Screening AssaysLab-On-A-Chip DevicesOsmoregulationSaccharomyces cerevisiaeSignal TransductionSingle-Cell Analysis

Identifiers

PMID28181485
PMCPMC5299847

What OpenQuestion holds

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Registered trials

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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.