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Abstract
The development of microfabricated devices that will provide high-throughput quantitative data and high resolution in a fast, repeatable and reproducible manner is essential for plant biology research.
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Affiliation(s)
- Meltem Elitaş
- Department of Mechatronics
- Faculty of Engineering and Natural Sciences
- Sabanci University
- 34956, Istanbul
- Turkey
| | - Meral Yüce
- Nanotechnology Research and Application Centre
- Sabanci University
- 34956, Istanbul
- Turkey
| | - Hikmet Budak
- Department of Molecular Biology
- Genetics and Bioengineering
- Faculty of Engineering and Natural Sciences
- Sabanci University
- 34956, Istanbul
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2
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Cao C, Zhou D, Chen T, Streets AM, Huang Y. Label-Free Digital Quantification of Lipid Droplets in Single Cells by Stimulated Raman Microscopy on a Microfluidic Platform. Anal Chem 2016; 88:4931-9. [PMID: 27041129 DOI: 10.1021/acs.analchem.6b00862] [Citation(s) in RCA: 38] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
Quantitative characterization of a single-cell phenotype remains challenging. We combined a scalable microfluidic array of parallel cell culture chambers and stimulated Raman scattering (SRS) microscopy to quantitatively characterize the response of lipid droplet (LD) formation to free-fatty-acid stimuli with single-LD resolution at the single-cell level. By enabling the systematic live-cell imaging with SRS microscopy in a microfluidic device, we were able to quantify the morphology of over a thousand live cells in 10 different chemical environments and with 8 replicates for each culture condition, in a single experiment, and without relying on fluorescent labeling. We developed an image processing pipeline for cell segmentation and LD morphology quantification using dual-channel SRS images. This allows us to construct distributions of the morphological parameters of LDs in the cellular population and expose the vast phenotypic heterogeneity among genetically similar cells. Specifically, this approach provides an analytical tool for quantitatively investigating LD morphology in live cells in situ. With this high-throughput, high-resolution, and label-free method, we found that LD growth dynamics showed considerable cell to cell variation. Lipid accumulation in nonadipocyte cells is mainly reflected in the increase of LD number, as opposed to an increase in their size or lipid concentration. Our method allows statistical single-cell quantification of the LD distribution for further investigation of lipid metabolism and dynamic behavior, and also extends the possibility to couple with other "omics" technologies in the future.
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Affiliation(s)
- Chen Cao
- Biodynamic Optical Imaging Center (BIOPIC), School of Life Sciences, Peking University , Beijing 100871, China
| | - Dong Zhou
- Biodynamic Optical Imaging Center (BIOPIC), School of Life Sciences, Peking University , Beijing 100871, China.,College of Engineering, Peking University , Beijing 100871, China
| | - Tao Chen
- Biodynamic Optical Imaging Center (BIOPIC), School of Life Sciences, Peking University , Beijing 100871, China.,College of Engineering, Peking University , Beijing 100871, China
| | - Aaron M Streets
- Biodynamic Optical Imaging Center (BIOPIC), School of Life Sciences, Peking University , Beijing 100871, China.,College of Engineering, Peking University , Beijing 100871, China
| | - Yanyi Huang
- Biodynamic Optical Imaging Center (BIOPIC), School of Life Sciences, Peking University , Beijing 100871, China.,College of Engineering, Peking University , Beijing 100871, China.,Peking-Tsinghua Center for Life Sciences, Peking University , Beijing 100871, China
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Single cell multiplexed assay for proteolytic activity using droplet microfluidics. Biosens Bioelectron 2016; 81:408-414. [PMID: 26995287 DOI: 10.1016/j.bios.2016.03.002] [Citation(s) in RCA: 55] [Impact Index Per Article: 6.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2015] [Revised: 02/24/2016] [Accepted: 03/02/2016] [Indexed: 11/21/2022]
Abstract
Cellular enzymes interact in a post-translationally regulated fashion to govern individual cell behaviors, yet current platform technologies are limited in their ability to measure multiple enzyme activities simultaneously in single cells. Here, we developed multi-color Förster resonance energy transfer (FRET)-based enzymatic substrates and use them in a microfluidics platform to simultaneously measure multiple specific protease activities from water-in-oil droplets that contain single cells. By integrating the microfluidic platform with a computational analytical method, Proteolytic Activity Matrix Analysis (PrAMA), we are able to infer six different protease activity signals from individual cells in a high throughput manner (~100 cells/experimental run). We characterized protease activity profiles at single cell resolution for several cancer cell lines including breast cancer cell line MDA-MB-231, lung cancer cell line PC-9, and leukemia cell line K-562 using both live-cell and in-situ cell lysis assay formats, with special focus on metalloproteinases important in metastasis. The ability to measure multiple proteases secreted from or expressed in individual cells allows us to characterize cell heterogeneity and has potential applications including systems biology, pharmacology, cancer diagnosis and stem cell biology.
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