Automated Microfluidic Droplet-Based Sample Chopper for Detection of Small Fluorescence Differences Using Lock-In Analysis

Abstract

Fluorescence is widely used for small-volume analysis and is a primary tool for on-chip detection in microfluidic devices, yet additional expertise, more elaborate optics, and phase-locked detectors are needed for ultrasensitive measurements. Recently, we designed a microfluidic analog to an optical beam chopper (μChopper) that alternated formation of picoliter volume sample and reference droplets. Without complex optics, the device negated large signal drifts (1/f noise), allowing absorbance detection in a mere 27 μm optical path. Here, we extend the μChopper concept to fluorescence detection with standard wide-field microscope optics. Precision of droplet control in the μChopper was improved by automation with pneumatic valves, allowing fluorescence measurements to be strictly phase locked at 0.04 Hz bandwidth to droplets generated at 3.50 Hz. A detection limit of 12 pM fluorescein was achieved when sampling 20 droplets, and as few as 310 zeptomoles (3.1 × 10−19 mol) were detectable in single droplets (8.8 nL). When applied to free fatty acid (FFA) uptake in 3T3-L1 adipocytes, this μChopper permitted single-cell FFA uptake rates to be quantified at 3.5 ± 0.2 × 10−15 mol cell−1 for the first time. Additionally, homogeneous immunoassays in droplets exhibited insulin detection limits of 9.3 nM or 190 amol (1.9 × 10−16 mol). The combination of this novel, automated μChopper with lock-in detection provides a high-performance platform for detecting small differences with standard fluorescence optics, particularly in situations where sample volume is limited. The technique should be simple to implement into a variety of other droplet fluidics devices.

Automated microfluidic droplet sampling with integrated, mix-and-read immunoassays to resolve endocrine tissue secretion dynamics

“…Previously, we reported an automated microfluidic sample chopper ( μ Chopper) which was successfully used for insulin quantification within droplets by using a fluorescence quenching based homogeneous immunoassay 25 . This μ Chopper was not able to mix the sample and immunoassay probes, nor accomplish on-chip incubation.…”

“…Based on this concept, we were able to indirectly study insulin secretion dynamics by measuring Zn 2+ (cosecreted with insulin) from single islets at about one-second temporal resolution 24 , although the lack of automation significantly limited adjustments available to this system. Pushing such devices to their sampling limit should theoretically permit sub-second resolution, and automated operation has been shown to offer compelling analytical enhancements 25, 26 .…”

“…Previously, our group developed a lock-in droplet detection system 32 , which modulated a reference signal at the same frequency and phase as the sample by alternatively making sample and reference droplets. Highly, sensitive absorbance 32 and fluorescence 25, 26 detection were achieved with this phase-locked droplet system (μChopper), even at very short optical path lengths (tens of micrometres). Unfortunately, for homogeneous fluorescence immunoassays to be quantified with this lock-in system, a limitation of our previous design is that detection immediately followed droplet formation, which does not allow for the incubation requirement of the immunoassays.…”

Microfluidic evaluation of some edible oil quality based on viscosity and interfacial tensions

“…In the microfluidic system, deionised water is injected into the inner channel; meanwhile, the oil sample to test is injected into two sheath channels. At specific flow rates, deionised water is squeezed and cut into dispersed water‐in‐oil droplets at the flow intersection (Anna, ; Chong et al ., ; Costa et al ., ; Negou et al ., ). The droplets’ dimension depends on the channel structure, size, flow rates, viscosity and interfacial tension, which can be estimated as follows (the cross‐section is square) (Cubaud & Mason, ; Liu et al ., ): where d is the steady‐state longitudinal dimension of droplet; w and h are the width and depth of main channel; m , n (negative) are the constants associated with flow channel; α 2 (α 2 = Q 2 /( Q 1 + Q 2 ) is the volume fraction of sample oil ( Q 1 and Q 2 are the flow rates, as shown in Fig.…”

A Counter Propagating Lens‐Mirror System for Ultrahigh Throughput Single Droplet Detection

“…Finally, Easley and co‐workers recently described a continuous referencing scheme (incorporating automated optical modulation with lock‐in detection) for droplet analysis that yields picomolar detection limits, albeit at very low‐throughput. [ 19 ]…”