Serial flow cytometry in an inertial focusing optofluidic microchip for direct assessment of measurement variations. Issue 17 (20th July 2022)

• Record Type: Journal Article
• Authors: DiSalvo, Matthew; Patrone, Paul N.; Kearsley, Anthony J.; Cooksey, Gregory A.
• Is Part Of: Lab on a chip. Volume 22:Issue 17(2022)
• Page Start: 3217
• Page End: 3228
• Publication Date: 2022-07-20
• Subjects: Miniature electronic equipment -- Periodicals; Combinatorial chemistry -- Periodicals; Biotechnology -- Periodicals; 543.0813
• DOI: 10.1039/d1lc01169c
• Languages: English
• ISSNs: 1473-0197

Abstract

Abstract : We present a microfluidic serial flow cytometer that repeats measurements on flowing objects for per-object uncertainty quantification. The automated system assessed measurement precision as a function of its flow focusing operating parameters. Abstract : Flow cytometry is an invaluable technology in biomedical research, but confidence in single-cell measurements remains limited due to a lack of appropriate techniques for uncertainty quantification (UQ). It is particularly challenging to evaluate the potential for different instrumentation designs or operating parameters to influence the measurement physics in ways that change measurement repeatability. Here, we report a direct experimental approach to UQ using a serial flow cytometer that measured each particle more than once along a flow path. The instrument was automated for real-time characterization of measurement precision and operated with particle velocities exceeding 1 m s −1, throughputs above 100 s −1, and analysis yields better than 99.9%. These achievements were enabled by a novel hybrid inertial and hydrodynamic particle focuser to tightly control particle positions and velocities. The cytometer identified ideal flow conditions with fluorescence area measurement precision on the order of 1% and characterized tradeoffs between precision, throughput, and analysis yield. The serial cytometer is anticipated to improve single-cell measurements through estimation (and subsequent control) of uncertainty contributions from various other instrument parameters leading to overall improvements in the ability to better classify sample composition and to find rare events.