Evidence map›Paper›PMID 27846239›Full record

ArticlePloS one2016

High-Throughput Accurate Single-Cell Screening of Euglena gracilis with Fluorescence-Assisted Optofluidic Time-Stretch Microscopy.

Baoshan Guo, Cheng Lei, Takuro Ito, Yiyue Jiang, Yasuyuki Ozeki, Keisuke Goda

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.5field-weighted citation impact, top 17% 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

7 citing papers in PubMed, 27 citations in OpenAlex.

  1. Review
  2. Article
  3. Review
  4. Review
  5. Microfluidic technology for plankton research.Current opinion in biotechnology · 2019
    Review
  6. Article
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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

6 authors at 3 institutions in 3 countries.

Baoshan GuoDepartment of Chemistry, University of Tokyo, Tokyo 113-0033, Japan.
Cheng LeiDepartment of Chemistry, University of Tokyo, Tokyo 113-0033, Japan.
Takuro ItoJapan Science and Technology Agency, Kawaguchi 332-0012, Japan.
Yiyue JiangDepartment of Chemistry, University of Tokyo, Tokyo 113-0033, Japan.
Yasuyuki OzekiDepartment of Electrical Engineering and Information Systems, University of Tokyo, Tokyo 113-8656, Japan.
Keisuke GodaDepartment of Chemistry, University of Tokyo, Tokyo 113-0033, Japan.
The University of Tokyo · JPJapan Science and Technology Agency · JPTokyo University of Information Sciences · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The development of reliable, sustainable, and economical sources of alternative fuels is an important, but challenging goal for the world. As an alternative to liquid fossil fuels, algal biofuel is expected to play a key role in alleviating global warming since algae absorb atmospheric CO2 via photosynthesis. Among various algae for fuel production, Euglena gracilis is an attractive microalgal species as it is known to produce wax ester (good for biodiesel and aviation fuel) within lipid droplets. To date, while there exist many techniques for inducing microalgal cells to produce and accumulate lipid with high efficiency, few analytical methods are available for characterizing a population of such lipid-accumulated microalgae including E. gracilis with high throughout, high accuracy, and single-cell resolution simultaneously. Here we demonstrate high-throughput, high-accuracy, single-cell screening of E. gracilis with fluorescence-assisted optofluidic time-stretch microscopy-a method that combines the strengths of microfluidic cell focusing, optical time-stretch microscopy, and fluorescence detection used in conventional flow cytometry. Specifically, our fluorescence-assisted optofluidic time-stretch microscope consists of an optical time-stretch microscope and a fluorescence analyzer on top of a hydrodynamically focusing microfluidic device and can detect fluorescence from every E. gracilis cell in a population and simultaneously obtain its image with a high throughput of 10,000 cells/s. With the multi-dimensional information acquired by the system, we classify nitrogen-sufficient (ordinary) and nitrogen-deficient (lipid-accumulated) E. gracilis cells with a low false positive rate of 1.0%. This method holds promise for evaluating cultivation techniques and selective breeding for microalgae-based biofuel production.

Indexed as

BiofuelsLipid MetabolismEuglena gracilisHigh-Throughput Screening AssaysLab-On-A-Chip DevicesLipidsMicroscopy, FluorescenceSingle-Cell AnalysisBiofuelsLipids

Identifiers

PMID27846239
PMCPMC5112898
OpenAlexW2554119837

What OpenQuestion holds

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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.