Evidence map›Paper›PMID 24753730›Full record

ArticleBiomicrofluidics2014

A highly parallel microfluidic droplet method enabling single-molecule counting for digital enzyme detection.

Zhichao Guan, Yuan Zou, Mingxia Zhang, Jiangquan Lv, Huali Shen, Pengyuan Yang, Huimin Zhang, Zhi Zhu, Chaoyong James Yang

Abstract read
In one paragraph

Article in Biomicrofluidics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
3.3field-weighted citation impact, top 8% 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

16 citing papers in PubMed, 57 citations in OpenAlex.

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  9. Journal of chemical education · 2019
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  11. Mobile platform for rapid sub-picogram-per-milliliter, multiplexed, digital droplet detection of proteins.Proceedings of the National Academy of Sciences of the United States of America · 2019
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  12. Review
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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

9 authors at 2 institutions in 1 country.

Zhichao GuanState Key Laboratory of Physical Chemistry of Solid Surfaces, the Key Laboratory for Chemical Biology of Fujian Province, The MOE Key Laboratory of Spectrochemical Analysis & Instrumentation, Department of Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, People's Republic of China.
Yuan ZouState Key Laboratory of Physical Chemistry of Solid Surfaces, the Key Laboratory for Chemical Biology of Fujian Province, The MOE Key Laboratory of Spectrochemical Analysis & Instrumentation, Department of Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, People's Republic of China.
Mingxia ZhangState Key Laboratory of Physical Chemistry of Solid Surfaces, the Key Laboratory for Chemical Biology of Fujian Province, The MOE Key Laboratory of Spectrochemical Analysis & Instrumentation, Department of Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, People's Republic of China.
Jiangquan LvState Key Laboratory of Physical Chemistry of Solid Surfaces, the Key Laboratory for Chemical Biology of Fujian Province, The MOE Key Laboratory of Spectrochemical Analysis & Instrumentation, Department of Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, People's Republic of China.
Huali ShenDepartment of Chemistry and Institutes of Biomedical Sciences, Fudan University, Shanghai 200433, China.
Pengyuan YangDepartment of Chemistry and Institutes of Biomedical Sciences, Fudan University, Shanghai 200433, China.
Huimin ZhangState Key Laboratory of Physical Chemistry of Solid Surfaces, the Key Laboratory for Chemical Biology of Fujian Province, The MOE Key Laboratory of Spectrochemical Analysis & Instrumentation, Department of Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, People's Republic of China.
Zhi ZhuState Key Laboratory of Physical Chemistry of Solid Surfaces, the Key Laboratory for Chemical Biology of Fujian Province, The MOE Key Laboratory of Spectrochemical Analysis & Instrumentation, Department of Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, People's Republic of China.
Chaoyong James YangState Key Laboratory of Physical Chemistry of Solid Surfaces, the Key Laboratory for Chemical Biology of Fujian Province, The MOE Key Laboratory of Spectrochemical Analysis & Instrumentation, Department of Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, People's Republic of China.
Xiamen University · CNFudan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Although digital detection of nucleic acids has been achieved by amplification of single templates in uniform microfluidic droplets and widely used for genetic analysis, droplet-based digital detection of proteins has rarely been reported, largely due to the lack of an efficient target amplification method for protein in droplets. Here, we report a key step towards digital detection of proteins using a highly parallel microfluidic droplet approach for single enzyme molecule detection in picoliter droplets via enzyme catalyzed signal amplification. An integrated microfluidic chip was designed for high throughput uniform droplet generation, monolayer droplet collection, incubation, detection, and release. Single β-galatosidase (β-Gal) molecules and the fluorogenic substrate fluorescein di-β-D-galactopyranoside were injected from two separated inlets to form uniform 20 μm droplets in fluorinated oil at a frequency of 6.6 kHz. About 200 000 droplets were captured as a monolayer in a capture well on-chip for subsequent imaging detection. A series of β-Gal solutions at different concentrations were analyzed at the single-molecule level. With no enzyme present, no droplets were found to fluoresce, while brightly fluorescent droplets were observed under single-enzyme molecule conditions. Droplet fluorescence intensity distribution analysis showed that the distribution of enzyme molecules under single-molecule conditions matched well with theoretical prediction, further proving the feasibility of detecting single enzyme molecules in emulsion droplets. Moreover, the population of fluorescent droplets increased as the β-Gal concentration increased. Based on a digital counting method, the measured concentrations of the enzyme were found to match well with input enzyme concentration, establishing the accuracy of the digital detection method for the quantification of β-Gal enzyme molecules. The capability of highly parallel detection of single enzyme molecules in uniform picoliter droplets paves the way to microdroplet based digital detection of proteins.

Identifiers

PMID24753730
PMCPMC3977795
OpenAlexW2075456535

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.