Nature integrates complex biosynthetic and energy-converting tasks within compartments such as chloroplasts and mitochondria. Chloroplasts convert light into chemical energy, driving carbon dioxide fixation. We used microfluidics to develop a chloroplast mimic by encapsulating and operating photosynthetic membranes in cell-sized droplets. These droplets can be energized by light to power enzymes or enzyme cascades and analyzed for their catalytic properties in multiplex and real time. We demonstrate how these microdroplets can be programmed and controlled by adjusting internal compositions and by using light as an external trigger. We showcase the capability of our platform by integrating the crotonyl–coenzyme A (CoA)/ethylmalonyl-CoA/hydroxybutyryl-CoA (CETCH) cycle, a synthetic network for carbon dioxide conversion, to create an artificial photosynthetic system that interfaces the natural and the synthetic biological worlds.
A microfluidic on-chip imaging cell sorter has several advantages over conventional cell sorting methods, especially to identify cells with complex morphologies such as clusters. One of the remaining problems is how to efficiently discriminate targets at the species level without labelling. Hence, we developed a label-free microfluidic droplet-sorting system based on image recognition of cells in droplets. To test the applicability of this method, a mixture of two plankton species with different morphologies (Dunaliella tertiolecta and Phaeodactylum tricornutum) were successfully identified and discriminated at a rate of 10 Hz. We also examined the ability to detect the number of objects encapsulated in a droplet. Single cell droplets sorted into collection channels showed 91 ± 4.5% and 90 ± 3.8% accuracy for D. tertiolecta and P. tricornutum, respectively. Because we used image recognition to confirm single cell droplets, we achieved highly accurate single cell sorting. The results indicate that the integrated method of droplet imaging cell sorting can provide a complementary sorting approach capable of isolating single target cells from a mixture of cells with high accuracy without any staining.
An on-chip multi-imaging flow cytometry system has been developed to obtain morphometric parameters of cell clusters such as cell number, perimeter, total cross-sectional area, number of nuclei and size of clusters as “imaging biomarkers”, with simultaneous acquisition and analysis of both bright-field (BF) and fluorescent (FL) images at 200 frames per second (fps); by using this system, we examined the effectiveness of using imaging biomarkers for the identification of clustered circulating tumor cells (CTCs). Sample blood of rats in which a prostate cancer cell line (MAT-LyLu) had been pre-implanted was applied to a microchannel on a disposable microchip after staining the nuclei using fluorescent dye for their visualization, and the acquired images were measured and compared with those of healthy rats. In terms of the results, clustered cells having (1) cell area larger than 200 µm2 and (2) nucleus area larger than 90 µm2 were specifically observed in cancer cell-implanted blood, but were not observed in healthy rats. In addition, (3) clusters having more than 3 nuclei were specific for cancer-implanted blood and (4) a ratio between the actual perimeter and the perimeter calculated from the obtained area, which reflects a shape distorted from ideal roundness, of less than 0.90 was specific for all clusters having more than 3 nuclei and was also specific for cancer-implanted blood. The collected clusters larger than 300 µm2 were examined by quantitative gene copy number assay, and were identified as being CTCs. These results indicate the usefulness of the imaging biomarkers for characterizing clusters, and all of the four examined imaging biomarkers—cluster area, nuclei area, nuclei number, and ratio of perimeter—can identify clustered CTCs in blood with the same level of preciseness using multi-imaging cytometry.
To understand how membrane-free subcompartmentalization can modulate biochemical reactions by coupled spatial enzyme localization with substrate and product partitioning, we use microfluidic strategies to synthesize, stabilize and characterize micron-sized functional coacervates in waterÀ oil emulsions. Our methodologies have allowed for the first time to quantitatively characterize partition coefficients of a broad range of different molecules with different coacervate chemistries and to measure reaction rates of individual subcompartments and their surrounding aqueous environment at the single coacervate level. Our results show that sub-compartmentalisation increases the overall rates of reactions. This bottom-up synthetic strategy for the production of synthetic organelles offers a physical model for membrane-free compartmentalization in biology and provides insights into the role of sub-compartmentalisation in regulating out-of-equilibrium behaviours in biological systems.
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