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Abstract :Static droplet array (SDA) is a pivotal tool for high-capacity screening assays, yet extraction and collection the target droplets that contain unique analytes or cells from the SDA remains one major technical bottleneck that limits its broader application. Here we present an optical-based on-demand droplet release (OODR) system by incorporating a 1064 nm laser-responsive indium tin oxide (ITO) layer into a chamber array-based droplet microfluidic chip. By focusing the 1064 nm laser onto the ITO layer, microbubbles can be created via local heating to selectively push-out the droplets from the chamber. Then the released droplet is readily exported in a one-droplet-one-tube (ODOT) manner by the inherent capillary force into pipette tip. Releasing of the droplets containing fluorescein sodium demonstrated ∼100% successful rate (9 out of 6400 droplets were successfully released) and low residual (only ∼5% of the droplet volume remains in the chamber). White or fluorescence image-based releasing of single-cell-droplets directly after cell loading or multi-cells-droplets derived from on-chip single-cell cultivation for both E. coli and yeast cells further demonstrated the wide applicability of OODR. The present system is user-friendly and has the potential to be applied in various high-throughput screening assays, including single molecule/cell analysis, drug screening, and phenotype-based cell sorting.

Abstract :By directly converting solar energy and carbon dioxide into biobased products, cyanobacteria are promising chassis for photosynthetic biosynthesis. To make cyanobacterial photosynthetic biosynthesis technology economically feasible on industrial scales, exploring and engineering cyanobacterial chassis and cell factories with fast growth rates and carbon fixation activities facing environmental stresses are of great significance. To simplify and accelerate the screening for fast-growing cyanobacteria strains, a method called Individual Cyanobacteria Vitality Tests and Screening (iCyanVS) was established. We show that the 13C incorporation ratio of carotenoids can be used to measure differences in cell growth and carbon fixation rates in individual cyanobacterial cells of distinct genotypes that differ in growth rates in bulk cultivations, thus greatly accelerating the process screening for fastest-growing cells. The feasibility of this approach is further demonstrated by phenotypically and then genotypically identifying individual cyanobacterial cells with higher salt tolerance from an artificial mutant library via Raman-activated gravity-driven encapsulation and sequencing. Therefore, this method should find broad applications in growth rate or carbon intake rate based screening of cyanobacteria and other photosynthetic cell factories.

Abstract :Antimicrobial susceptibility tests (ASTs) are pivotal tools for detecting and combating infections caused by multidrug-resistant rapidly growing mycobacteria (RGM) but are time-consuming and labor-intensive.We used a Mycobacterium abscessus-based RGM model to develop a rapid (24-h) AST from the beginning of the strain culture, the Clinical Antimicrobials Susceptibility Test Ramanometry for RGM (CAST-R-RGM). The ASTs obtained for 21 clarithromycin (CLA)-treated and 18 linezolid (LZD)-treated RGM isolates.CAST-R-RGM employs D2O-probed Raman microspectroscopy to monitor RGM metabolic activity, while also revealing bacterial antimicrobial drug resistance mechanisms. The results of clarithromycin (CLA)-treated and linezolid (LZD)-treated RGM isolates exhibited 90% and 83% categorical agreement, respectively, with conventional AST results of the same isolates. Furthermore, comparisons of time- and concentration-dependent Raman results between CLA- and LZD-treated RGM strains revealed distinct metabolic profiles after 48-h and 72-h drug treatments, despite similar profiles obtained for both drugs after 24-h treatments.Ultimately, the rapid, accurate, and low-cost CAST-R-RGM assay offers advantages over conventional culture-based ASTs that warrant its use as a tool for improving patient treatment outcomes and revealing bacterial drug resistance mechanisms.

Abstract :Rapid expansion of the probiotics industry demands fast, sensitive, comprehensive, and low-cost strategies for quality assessment. Here, we introduce a culture-free, one-cell-resolution, phenome-genome-combined strategy called Single-Cell Identification, Viability and Vitality tests, and Source-tracking (SCIVVS). For each cell directly extracted from the product, the fingerprint region of D2O-probed single-cell Raman spectrum (SCRS) enables species-level identification with 93% accuracy, based on a reference SCRS database from 21 statutory probiotic species, whereas the C–D band accurately quantifies viability, metabolic vitality plus their intercellular heterogeneity. For source-tracking, single-cell Raman-activated Cell Sorting and Sequencing can proceed, producing indexed, precisely one-cell-based genome assemblies that can reach ~99.40% genome-wide coverage. Finally, we validated an integrated SCIVVS workflow with automated SCRS acquisition where the whole process except sequencing takes just 5 h. As it is >20-fold faster, >10-time cheaper, vitality-revealing, heterogeneity-resolving, and automation-prone, SCIVVS is a new technological and data framework for quality assessment of live-cell products.

Abstract :Rapid and accurate microbial screening, which is important in industrial breeding, enzyme directed evolution and synthetic biology, is currently time-consulting. Fluorescence-activated droplet sorting (FADS) system offers a promising alternative for microbial screening with high-throughput analysis. However, pre-labeling steps are required before use. Here, a low-cost, label-free droplet-based mini integrated microfluidic platform is developed for bacterial growth phenotype screening based on the difference in droplet autofluorescence properties. The platform integrates the main functions into a box, in which droplets are passed through the detection area and transmitted the signal of the light directly to the photomultiplier tubes (PMT) through the optical fiber inserted in a specially designed chip. After optimizing the chip structure and parameter, we firstly verify the capabilities of this platform for bacteria automatic counting. Then, label-free counting and sorting of the cultured bacteria in droplet have been well performed in this platform with the support of a voltage amplifier. We also employee this platform to determine the growth phenotype for microbial strain in droplets and screen the fast-growth bacteria in an automatic way. The label-free droplet-based platform provides an automated method for rapid bacteria growth phenotype screening, which can be further employed in high quality industrial strains screening, antibiotic resistance and directed evolution.

Abstract :A full-spectrum spontaneous single-cell Raman spectrum (fs-SCRS) captures the metabolic phenome for a given cellular state of the cell in a label-free, landscape-like manner. Herein a positive dielectrophoresis induced deterministic lateral displacement-based Raman flow cytometry (pDEP-DLD-RFC) is established. This robust flow cytometry platform utilizes a periodical positive dielectrophoresis induced deterministic lateral displacement (pDEP-DLD) force that is exerted to focus and trap fast-moving single cells in a wide channel, which enables efficient fs-SCRS acquisition and extended stable running time. It automatically produces deeply sampled, heterogeneity-resolved, and highly reproducible ramanomes for isogenic cell populations of yeast, microalgae, bacteria, and human cancers, which support biosynthetic process dissection, antimicrobial susceptibility profiling, and cell-type classification. Moreover, when coupled with intra-ramanome correlation analysis, it reveals state- and cell-type-specific metabolic heterogeneity and metabolite-conversion networks. The throughput of ≈30–2700 events min−1 for profiling both nonresonance and resonance marker bands in a fs-SCRS, plus the >5 h stable running time, represent the highest performance among reported spontaneous Raman flow cytometry (RFC) systems. Therefore, pDEP-DLD-RFC is a valuable new tool for label-free, noninvasive, and high-throughput profiling of single-cell metabolic phenomes.