iSort enables automated complex microfluidic droplet sorting in an effort to democratize technology.

Fluorescence-activated droplet sorting (FADS) is a widely used microfluidic technique for high-throughput screening. However, it requires highly trained specialists to determine optimal sorting parameters, and this results in a large combinatorial space that is challenging to optimize systematically. Additionally, it is currently challenging to track every single droplet within a screen, leading to compromised sorting and "hidden" false-positive events. To overcome these limitations, we have developed a setup in which the droplet frequency, spacing, and trajectory at the sorting junction are monitored in real time using impedance analysis. The resulting data are used to continuously optimize all parameters automatically and to counteract perturbations, resulting in higher throughput, higher reproducibility, increased robustness, and a beginner-friendly character. We believe this provides a missing piece for the spreading of phenotypic single-cell analysis methods, similar to what we have seen for single-cell genomics platforms.

Fluorescence crosstalk reduction by modulated excitation-synchronous acquisition for multispectral analysis in high-throughput droplet microfluidics.

Crosstalk between fluorescent biomarkers significantly limits the resolution of multispectral fluorescence analysis in real-time droplet-microfluidics applications. The crosstalk is a result of overlapping emission and excitation spectra of different fluorophores in multiplexed analyses. To mitigate this crosstalk, we present a method that modulates multiple laser beams to selectively and sequentially excite the fluorophores by a single beam of a particular wavelength using acousto-optic modulators at a frequency of 0.1 MHz. An FPGA based data acquisition algorithm synchronized with the modulation signal then acquires the emission signals only from the fluorescence channel that corresponds to the excitation wavelength provided in that particular time window. We applied our method for fluorescence-based droplet analysis in microfluidics and demonstrate that the method is able to reduce crosstalk contribution between channels by >97% and can resolve fluorescence populations that are indistinguishable with conventional droplet analysis methods.

Design and construction of a microfluidics workstation for high-throughput multi-wavelength fluorescence and transmittance activated droplet analysis and sorting.

Droplet microfluidics has revolutionized quantitative high-throughput bioassays and screening, especially in the field of single-cell analysis where applications include cell characterization, antibody discovery and directed evolution. However, droplet microfluidic platforms capable of phenotypic, fluorescence-based readouts and sorting are still mostly found in specialized labs, because their setup is complex. Complementary to conventional FACS, microfluidic droplet sorters allow the screening of cell libraries for secreted factors, or even for the effects of secreted or surface-displayed factors on a second cell type. Furthermore, they also enable PCR-activated droplet sorting for the isolation of genetic material harboring specific markers. In this protocol, we provide a detailed step-by-step guide for the construction of a high-throughput droplet analyzer and sorter, which can be accomplished in ~45 working hours by nonspecialists. The resulting instrument is equipped with three lasers to excite the fluorophores in droplets and photosensors that acquire fluorescence signals in the blue (425-465 nm), green (505-545 nm) and red (580-630 nm) spectrum. This instrument also allows transmittance-activated droplet sorting by analyzing the brightfield light intensity transmitting through the droplets. The setup is validated by sorting droplets containing fluorescent beads at 200 Hz with 99.4% accuracy. We show results from an experiment where droplets hosting single cells were sorted on the basis of increased matrix metalloprotease activity as an application of our workstation in single-cell molecular biology, e.g., to analyze molecular determinants of cancer metastasis.