Evidence map›Paper›PMID 30221644›Full record

ArticleThe Analyst2018

Digital enzyme assay using attoliter droplet array.

Takao Ono, Takanori Ichiki, Hiroyuki Noji

Open access · hybridAbstract read
In one paragraph

Article in The Analyst, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.0field-weighted citation impact, top 24% 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

9 citing papers in PubMed, 34 citations in OpenAlex.

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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

3 authors at 2 institutions in 3 countries.

Takao OnoDepartment of Applied Chemistry, Graduate School of Engineering, The University of Tokyo, Japan. hnoji@appchem.t.u-tokyo.ac.jp.
Takanori Ichiki
Hiroyuki Noji
The University of Tokyo · JPJapan Science and Technology Agency · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Single-molecule digital enzyme assay using micron-sized droplet array is a promising analysis method to quantify biomolecules at extremely low concentrations. However, multiplex digital enzyme assays are still difficult to access because the best buffer conditions can vary largely among enzymes. In addition, the best conditions for flurogenic compounds to retain high quantum efficiency and to avoid leakage into the oil phase can be also very different. In this study, digital enzyme assay was performed using an array of nanometer-sized droplets of 200 aL volume, termed 'nanocell'. Due to the small reaction volume, nanocell enhanced the accumulation rate of fluorescent products by a factor of 100 when compared with micron-sized reactors. Nanocell also enabled oil-free sealing of reactors: when flushed with an air flow, nanocell displayed water droplets under air, allowing enzymes to catalyze the reaction at the same rate as in oil-sealed reactors. Dual digital enzyme assay was also demonstrated using β-galactosidase and alkaline phosphatase (ALP) at pH 7.4, which is far from the optimum condition for ALP. Even under such a non-optimum condition, ALP molecules were successfully detected. Nanocell could largely expand the applicability of digital bioassay for enzymes under non-optimum conditions or enzymes of low turnover rate. The sealing of the reactor with air would also expand the applicability, allowing the use of fluorescent dyes that leak into oil.

Indexed as

Alkaline Phosphatasebeta-GalactosidaseEnzyme AssaysEnzyme-Linked Immunosorbent AssayEscherichia coliEscherichia coli ProteinsFluoresceinsFluorescent DyesHydrogen-Ion ConcentrationAlkaline Phosphatasebeta-GalactosidaseEscherichia coli ProteinsFluoresceinsFluorescent Dyes

Identifiers

PMID30221644
PMCPMC6180314
OpenAlexW2890403996

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.