Deep-qGFP: A Generalist Deep Learning Assisted Pipeline for Accurate Quantification of Green Fluorescent Protein Labeled Biological Samples in Microreactors.

Absolute quantification of biological samples provides precise numerical expression levels, enhancing accuracy, and performance for rare templates. Current methodologies, however, face challenges-flow cytometers are costly and complex, whereas fluorescence imaging, relying on software or manual counting, is time-consuming and error-prone. It is presented that Deep-qGFP, a deep learning-aided pipeline for the automated detection and classification of green fluorescent protein (GFP) labeled microreactors, enables real-time absolute quantification. This approach achieves an accuracy of 96.23% and accurately measures the sizes and occupancy status of microreactors using standard laboratory fluorescence microscopes, providing precise template concentrations. Deep-qGFP demonstrates remarkable speed, quantifying over 2000 microreactors across ten images in just 2.5 seconds, with a dynamic range of 56.52-1569.43 copies µL-1 . The method demonstrates impressive generalization capabilities, successfully applied to various GFP-labeling scenarios, including droplet-based, microwell-based, and agarose-based applications. Notably, Deep-qGFP is the first all-in-one image analysis algorithm successfully implemented in droplet digital polymerase chain reaction (PCR), microwell digital PCR, droplet single-cell sequencing, agarose digital PCR, and bacterial quantification, without requiring transfer learning, modifications, or retraining. This makes Deep-qGFP readily applicable in biomedical laboratories and holds potential for broader clinical applications.

Thermo-Induced Coalescence of Dual Cores in Double Emulsions for Single-Cell RT-PCR.

Single-cell reverse-transcription polymerase chain reaction (RT-PCR) has shown significant promise for transcriptional profiling of heterogeneous cells. However, currently developed microfluidic droplet-based methodologies for single-cell RT-PCR often require complex chip design to accommodate the associated multistep processes as well as customized detection platforms for high-throughput analysis. Herein, we proposed a dual-core double emulsion (DE)-based method to streamline the single-cell RT-PCR through thermo-induced coalescence of the dual cores. The dual-core DEs were produced by pairing two water-in-oil single emulsions containing a single-cell/lysis buffer and RT-PCR mix, respectively. After complete lysis of single cells in one of the cores, the dual-core DEs were merged by gentle heating, made possible by the optimized glycerol concentration present in the cores. Upon the coalescence of dual cores, the alkaline lysis buffer present in the core of the cell lysate was neutralized by the reaction buffer presented in the RT-PCR core, allowing TaqMan assay-based RT-PCR to occur effectively within the DEs. To demonstrate the potential of this streamlined dual-core platform, AKR1B10-positive A549 cells and AKR1B10-negative HEK293 cells were investigated via the TaqMan assay. Subsequently, specific transcript of AKR1B10 was readily available for quantitative profiling at the single-cell level using a commercially available flow cytometer in a high-throughput manner.

Multiple splitting of droplets using multi-furcating microfluidic channels.

Removing volumes from droplets is a challenging but critical step in many droplet-based applications. Geometry-mediated droplet splitting has the potential to reliably divide droplets and thus facilitate the implementation of this step. In this paper, we report the design of multi-furcating microfluidic channels for efficient droplet splitting. We studied the splitting regimes as the size of the mother droplets varied and investigated the dependence of the transition between splitting regimes on the capillary number and the dimensionless droplet length. We found that the results obtained with our device agreed with the reported dimensionless analysis law in T-junctions. We further investigated the effect of channel lengths on the volume allocation in branch channels and achieved droplet splitting with various splitting ratios. This study proposed an efficient on-demand droplet splitting method and the findings could potentially be applied in washing steps in droplet-based biological assays or assays that require aliquot.

Dean Flow Assisted Single Cell and Bead Encapsulation for High Performance Single Cell Expression Profiling.

Droplet microfluidics-based platform (Drop-seq) has been shown to be a powerful tool for single cell expression profiling. Nevertheless, this platform required the simultaneous encapsulation of single cell and single barcoded bead, the incidence of which was very low, limiting its efficiency. Spiral channels were reported to focus the barcoded beads and thus increased the efficiency, but focusing of cells was not demonstrated, which could potentially further enhance the performance. Here, we designed spiral and serpentine channels to focus both bead and cell solutions and implemented this microfluidic design on Drop-seq. We characterized the effect of cell/bead concentration on encapsulation results and tested the performance by coencapsulating barcoded beads and human-mouse cell mixtures followed by sequencing. The results showed ∼300% and ∼40% increase in cell utilization rate compared to the traditional Drop-seq device and the device focusing beads alone, respectively. This chip design showed great potential for high efficiency single cell expression profiling.

Capillary-based integrated digital PCR in picoliter droplets.

The droplet digital polymerase chain reaction (ddPCR) is becoming more and more popular in diagnostic applications in academia and industry. In commercially available ddPCR systems, after they have been made by a generator, the droplets have to be transferred manually to modules for amplification and detection. In practice, some of the droplets (∼10%) are lost during manual transfer, leading to underestimation of the targets. In addition, the droplets are also at risk of cross-contamination during transfer. By contrast, in labs, some chip-based ddPCRs have been demonstrated where droplets always run in channels. However, the droplets easily coalesce to large ones in chips due to wall wetting as well as thermal oscillation. The loss of droplets becomes serious when such ddPCRs are applied to absolutely quantify rare mutations, such as in early diagnostics in clinical research or when measuring biological diversity at the cell level. Here, we propose a capillary-based integrated ddPCR system that is used for the first time to realize absolute quantification in this way. In this system, a HPLC T-junction is used to generate droplets and a long HPLC capillary connects the generator with both a capillary-based thermocycler and a capillary-based cytometer. The performance of the system is validated by absolute quantification of a gene specific to lung cancer (LunX). The results show that this system has very good linearity (0.9988) at concentrations ranging from NTC to 2.4 × 10-4 copies per µL. As compared to qPCR, the all-in-one scheme is superior both in terms of the detection limit and the smaller fold changes measurement. The system of ddPCR might provide a powerful approach for clinical or academic applications where rare events are mostly considered.