Light-Responsive Materials in Droplet Manipulation for Biochemical Applications.

Miniaturized droplets, characterized by well-controlled microenvironments and capability for parallel processing, have significantly advanced the studies on enzymatic evolution, molecular diagnostics, and single-cell analysis. However, manipulation of small-sized droplets, including moving, merging, and trapping of the targeted droplets for complex biochemical assays and subsequent analysis, is not trivial and remains technically demanding. Among various techniques, light-driven methods stand out as a promising candidate for droplet manipulation in a facile and flexible manner, given the features of contactless interaction, high spatiotemporal resolution, and biocompatibility. This review therefore compiles an in-depth discussion of the governing mechanisms underpinning light-driven droplet manipulation. Besides, light-responsive materials, representing the core of light-matter interaction and the key character converting light into different forms of energy, are particularly assessed in this review. Recent advancements in light-responsive materials and the most notable applications are comprehensively archived and evaluated. Continuous innovations and rational engineering of light-responsive materials are expected to propel the development of light-driven droplet manipulation, equip droplets with enhanced functionality, and broaden the applications of droplets for biochemical studies and routine biochemical investigations.

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.

On-demand light-driven release of droplets stabilized via a photoresponsive fluorosurfactant.

Water-in-oil droplets have emerged as promising microreactors for high-throughput biochemical analysis due to their features of reduced sample consumption and automated operation. For a typical screening application, droplets are often trapped for continuous monitoring of the reaction over an extended period, followed by the selective retrieval of targeted droplets based on the after-effect of biochemical reactions. While techniques for droplet trapping are well developed, retrieval of targeted droplets mainly demands complicated device fabrication or sophisticated control. Herein, facile and rapid selective droplet release is achieved by utilizing a new class of photoresponsive fluorosurfactant based on plasmonic nanoparticles. The intense photothermal response provided by this novel photoresponsive fluorosurfactant is capable of vaporizing the fluorocarbon oil at the droplet interface under laser illumination, resulting in a bubble releasing a trapped droplet on demand. A fully automated fluorescence-activated droplet release platform has also been developed to demonstrate its potential for droplet-based large-scale screening applications.

Light-Driven Spatiotemporal Pickering Emulsion Droplet Manipulation Enabled by Plasmonic Hybrid Microgels.

The past decades have witnessed the development of various stimuli-responsive materials with tailored functionalities, enabling droplet manipulation through external force fields. Among different strategies, light exhibits excellent flexibility for contactless control of droplets, particularly in three-dimensional space. Here, we present a facile synthesis of plasmonic hybrid microgels based on the electrostatic heterocoagulation between cationic microgels and anionic Au nanoparticles. The hybrid microgels are effective stabilizers of oil-in-water Pickering emulsions. In addition, the laser irradiation on Au nanoparticles creats a "cascade effect" to thermally responsive microgels, which triggers a change in microgel wettability, resulting in microgel desorption and emulsion destabilization. More importantly, the localized heating generated by a focused laser induces the generation of a vapor bubble inside oil droplets, leading to the formation of a novel air-in-oil-in-water (A/O/W) emulsion. These A/O/W droplets are able to mimic natural microswimmers in an aqueous environment by tracking the motion of a laser spot, thus achieving on-demand droplet merging and chemical communication between isolated droplets. Such proposed systems are expected to extend the applications of microgel-stabilized Pickering emulsions for substance transport, programmed release and controlled catalytic reactions.

Single-cell RNA sequencing uncovers a neuron-like macrophage subset associated with cancer pain.

Tumor innervation is a common phenomenon with unknown mechanism. Here, we discovered a direct mechanism of tumor-associated macrophage (TAM) for promoting de novo neurogenesis via a subset showing neuronal phenotypes and pain receptor expression associated with cancer-driven nocifensive behaviors. This subset is rich in lung adenocarcinoma associated with poorer prognosis. By elucidating the transcriptome dynamics of TAM with single-cell resolution, we discovered a phenomenon "macrophage to neuron-like cell transition" (MNT) for directly promoting tumoral neurogenesis, evidenced by macrophage depletion and fate-mapping study in lung carcinoma models. Encouragingly, we detected neuronal phenotypes and activities of the bone marrow-derived MNT cells (MNTs) in vitro. Adoptive transfer of MNTs into NOD/SCID mice markedly enhanced their cancer-associated nocifensive behaviors. We identified macrophage-specific Smad3 as a pivotal regulator for promoting MNT at the genomic level; its disruption effectively blocked the tumor innervation and cancer-dependent nocifensive behaviors in vivo. Thus, MNT may represent a precision therapeutic target for cancer pain.

Double emulsion-pretreated microwell culture for the in vitro production of multicellular spheroids and their in situ analysis.

Multicellular spheroids have served as a promising preclinical model for drug efficacy testing and disease modeling. Many microfluidic technologies, including those based on water-oil-water double emulsions, have been introduced for the production of spheroids. However, sustained culture and the in situ characterization of the generated spheroids are currently unavailable for the double emulsion-based spheroid model. This study presents a streamlined workflow, termed the double emulsion-pretreated microwell culture (DEPMiC), incorporating the features of (1) effective initiation of uniform-sized multicellular spheroids by the pretreatment of double emulsions produced by microfluidics without the requirement of biomaterial scaffolds; (2) sustained maintenance and culture of the produced spheroids with facile removal of the oil confinement; and (3) in situ characterization of individual spheroids localized in microwells by a built-in analytical station. Characterized by microscopic observations and Raman spectroscopy, the DEPMiC cultivated spheroids accumulated elevated lipid ordering on the apical membrane, similar to that observed in their Matrigel counterparts. Made possible by the proposed technological advancement, this study subsequently examined the drug responses of these in vitro-generated multicellular spheroids. The developed DEPMiC platform is expected to generate health benefits in personalized cancer treatment by offering a pre-animal tool to dissect heterogeneity from individual tumor spheroids.

Photo-Responsive Fluorosurfactant Enabled by Plasmonic Nanoparticles for Light-Driven Droplet Manipulation.

The past decade has witnessed a significant development of droplet microfluidics for applications such as directed evolution and single-cell analysis. While the stability and manipulation of droplets are part of the prerequisites to further their applications, most of the currently available surfactants serve solely as stabilizers between the interfaces of water and oil. In this study, we present a novel type of photo-responsive fluorosurfactant based on fluorinated plasmonic nanoparticles (NPs). The demonstration by fluorinated gold-silica core-shell NPs (f-Au@SiO2) has been shown to be effective in stabilizing the water-in-fluorocarbon oil droplets. More importantly, the photothermal response enabled by the f-Au@SiO2 has been shown to be promising for the movement of droplets as well as the alteration of interfacial stability. The unique photo-responsiveness provided by the plasmonic NPs is expected to gear up the droplet microfluidics with an "active" surfactant for reconfigurable optical manipulation.

Thermodynamic perspectives on liquid-liquid droplet reactors for biochemical applications.

Liquid-liquid droplet reactors have garnered significant interest in biochemical applications with the obvious benefits of reduced reagent consumption, well controlled droplet size and confinement of biochemical reactions away from external interference. This Tutorial Review provides a succinct overview of widely employed liquid-liquid droplet reactors, namely single emulsions, multiple emulsions and all-aqueous emulsions, under the scope of thermodynamics, with a particular emphasis on how their intrinsic interfacial properties may endow mass transport for a variety of demands. Beyond spatially compartmentalizing a thermodynamic system, the artificial interface of droplet reactors has shown initial promising for multi-step or complex reactions. Moving forward, the artificial interface shall be tailored further towards "functional" to imitate the "intelligent" interface surrounding natural vesicles or cells.