Digital quantification and selection of high-lipid-producing microalgae through a lateral dielectrophoresis-based microfluidic platform
Lab on a Chip, ISSN: 1473-0189, Vol: 19, Issue: 24, Page: 4128-4138
2019
- 31Citations
- 22Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Citations31
- Citation Indexes31
- 31
- CrossRef26
- Captures22
- Readers22
- 22
Article Description
Microalgae are promising alternatives to petroleum as renewable biofuel sources, however not sufficiently economically competitive yet. Here, a label-free lateral dielectrophoresis-based microfluidic sorting platform that can digitally quantify and separate microalgae into six outlets based on the degree of their intracellular lipid content is presented. In this microfluidic system, the degree of cellular lateral displacement is inversely proportional to the intracellular lipid level, which was successfully demonstrated using Chlamydomonas reinhardtii cells. Using this functionality, a quick digital quantification of sub-populations that contain different intracellular lipid level in a given population was achieved. In addition, the degree of lateral displacement of microalgae could be readily controlled by simply changing the applied DEP voltage, where the level of gating in the intracellular lipid-based sorting decision could be easily adjusted. This allowed for selecting only a very small percentage of a given population that showed the highest degree of intracellular lipid content. In addition, this approach was utilized through an iterative selection process on natural and chemically mutated microalgal populations, successfully resulting in enrichment of high-lipid-accumulating microalgae. In summary, the developed platform can be exploited to quickly quantify microalgae lipid distribution in a given population in real-time and label-free, as well as to enrich a cell population with high-lipid-producing cells, or to select high-lipid-accumulating microalgal variants from a microalgal library.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85076147823&origin=inward; http://dx.doi.org/10.1039/c9lc00850k; http://www.ncbi.nlm.nih.gov/pubmed/31755503; https://xlink.rsc.org/?DOI=C9LC00850K; https://dx.doi.org/10.1039/c9lc00850k; https://pubs.rsc.org/en/content/articlelanding/2019/lc/c9lc00850k
Royal Society of Chemistry (RSC)
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