The efficient selection and isolation of individual cells of interest from a mixed population is desired in many biomedical and clinical applications. Here we show the concept of using photoswitchable semiconducting polymer dots (Pdots) as an optical 'painting' tool, which enables the selection of certain adherent cells based on their fluorescence, and their spatial and morphological features, under a microscope. We first develop a Pdot that can switch between the bright (ON) and dark (OFF) states reversibly with a 150-fold contrast ratio on irradiation with ultraviolet or red light. With a focused 633-nm laser beam that acts as a 'paintbrush' and the photoswitchable Pdots as the 'paint', we select and 'paint' individual Pdot-labelled adherent cells by turning on their fluorescence, then proceed to sort and recover the optically marked cells (with 90% recovery and near 100% purity), followed by genetic analysis.
The ability to correlate single-cell genetic information to cellular phenotypes will provide the kind of detailed insight into human physiology and disease pathways that is not possible to infer from bulk cell analysis. Microfluidic technologies are attractive for single-cell manipulation due to precise handling and low risk of contamination. Additionally, microfluidic single-cell techniques can allow for high-throughput and detailed genetic analyses that increase accuracy and decreases reagent cost compared to bulk techniques. Incorporating these microfluidic platforms into research and clinical laboratory workflows can fill an unmet need in biology, delivering the highly accurate, highly informative data necessary to develop new therapies and monitor patient outcomes. In this perspective, we describe the current and potential future uses of microfluidics at all stages of single-cell genetic analysis, including cell enrichment and capture, single-cell compartmentalization and manipulation, and detection and analyses.
This paper describes a sample digitization method that generates tens of thousands of nanoliter-sized droplets in a high-density array in a matter of minutes. We show that the sample digitization depends on both the geometric design of the microfluidic device and the viscoelastic forces between the aqueous sample and a continuous oil phase. Our design avoids sample loss: Samples are split into tens of thousands of discreet volumes with close to 100% efficiency without the need for any expensive valving or pumping systems. We envision this technology will have broad applications that require simple sample digitization within minutes, such as digital polymerase chain reactions and single-cell studies.
Quantification of mRNA in single cells provides direct insight into how intercellular heterogeneity plays a role in disease progression and outcomes. Quantitative polymerase chain reaction (qPCR), the current gold standard for evaluating gene expression, is insufficient for providing absolute measurement of single-cell mRNA transcript abundance. Challenges include difficulties in handling small sample volumes and the high variability in measurements. Microfluidic digital PCR provides far better sensitivity for minute quantities of genetic material, but the typical format of this assay does not allow for counting of the absolute number of mRNA transcripts samples taken from single cells. Furthermore, a large fraction of the sample is often lost during sample handling in microfluidic digital PCR. Here, we report the absolute quantification of single-cell mRNA transcripts by digital, one-step reverse transcription PCR in a simple microfluidic array device called the self-digitization (SD) chip. By performing the reverse transcription step in digitized volumes, we find that the assay exhibits a linear signal across a wide range of total RNA concentrations and agrees well with standard curve qPCR. The SD chip is found to digitize a high percentage (86.7%) of the sample for single-cell experiments. Moreover, quantification of transferrin receptor mRNA in single cells agrees well with single-molecule fluorescence in situ hybridization experiments. The SD platform for absolute quantification of single-cell mRNA can be optimized for other genes and may be useful as an independent control method for the validation of mRNA quantification techniques.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.