Evidence map›Paper›PMID 31245660›Full record

ArticlePlant direct2017

High-throughput droplet microfluidics screening platform for selecting fast-growing and high lipid-producing microalgae from a mutant library.

Hyun Soo Kim, Shih-Chi Hsu, Song-I Han, Hem R Thapa, Adrian R Guzman, Daniel R Browne, Mehmet Tatli, Timothy P Devarenne, David B Stern, Arum Han

Open access · goldAbstract read
In one paragraph

Article in Plant direct, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed
1.9field-weighted citation impact, top 14% 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

31 citing papers in PubMed, 83 citations in OpenAlex.

  1. Article
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  8. Article
  9. Review
  10. Multiple Rounds ofACS synthetic biology · 2023
    Article
  11. Tutorial on Lateral Dielectrophoretic Manipulations in Microfluidic Systems.IEEE transactions on biomedical circuits and systems · 2023
    Article
  12. Article
  13. Review
  14. Article
  15. Review
  16. Article
  17. High-throughput selection of cells based on accumulated growth and division using PicoShell particles.Proceedings of the National Academy of Sciences of the United States of America · 2022
    Article
  18. Article
  19. Droplet Microfluidics for Microbial Biotechnology.Advances in biochemical engineering/biotechnology · 2022
    Article
  20. 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

10 authors at 4 institutions in 2 countries.

Hyun Soo KimDepartment of Electrical and Computer Engineering Texas A&M University College Station TX USA.
Shih-Chi HsuBoyce Thompson Institute Ithaca NY USA.
Song-I HanDepartment of Electrical and Computer Engineering Texas A&M University College Station TX USA.
Hem R ThapaDepartment of Biochemistry and Biophysics Texas A&M University College Station TX USA.
Adrian R GuzmanDepartment of Electrical and Computer Engineering Texas A&M University College Station TX USA.
Daniel R BrowneDepartment of Biochemistry and Biophysics Texas A&M University College Station TX USA.
Mehmet TatliDepartment of Biochemistry and Biophysics Texas A&M University College Station TX USA.
Timothy P DevarenneDepartment of Biochemistry and Biophysics Texas A&M University College Station TX USA.
David B SternBoyce Thompson Institute Ithaca NY USA.
Arum HanDepartment of Electrical and Computer Engineering Texas A&M University College Station TX USA.
Texas A&M University · USCornell University · USIthaca College · USKorea Institute of Machinery and Materials · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Biofuels derived from microalgal lipids have demonstrated a promising potential as future renewable bioenergy. However, the production costs for microalgae-based biofuels are not economically competitive, and one strategy to overcome this limitation is to develop better-performing microalgal strains that have faster growth and higher lipid content through genetic screening and metabolic engineering. In this work, we present a high-throughput droplet microfluidics-based screening platform capable of analyzing growth and lipid content in populations derived from single cells of a randomly mutated microalgal library to identify and sort variants that exhibit the desired traits such as higher growth rate and increased lipid content. By encapsulating single cells into water-in-oil emulsion droplets, each variant was separately cultured inside an individual droplet that functioned as an independent bioreactor. In conjunction with an on-chip fluorescent lipid staining process within droplets, microalgal growth and lipid content were characterized by measuring chlorophyll and BODIPY fluorescence intensities through an integrated optical detection system in a flow-through manner. Droplets containing cells with higher growth and lipid content were selectively retrieved and further analyzed off-chip. The growth and lipid content screening capabilities of the developed platform were successfully demonstrated by first carrying out proof-of-concept screening using known

Indexed as

biofuelChlamydomonas reinhardtiidroplet microfluidicshigh‐throughput screeningmicroalgaemutant library screeningsingle‐cell analysis

Identifiers

PMID31245660
PMCPMC6508572
OpenAlexW2757827200

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.