High-Content Screening of Plankton Alkaline Phosphatase Activity in Microfluidics.

One way for phytoplankton to survive orthophosphate depletion is to utilize dissolved organic phosphorus by expressing alkaline phosphatase. The actual methods to assay alkaline phosphate activity-either in bulk or as a presence/absence of enzyme activity-fail to provide information on individual living cells. In this context, we develop a new microfluidic method to compartmentalize cells in 0.5 nL water-in-oil droplets and measure alkaline phosphatase activity at the single-cell level. We use enzyme-labeled fluorescence (ELF), which is based on the hydrolysis of ELF-P substrate, to monitor in real time and at the single-cell level both qualitative and quantitative information on cell physiology (i.e., localization and number of active enzyme sites and alkaline phosphatase kinetics). We assay the alkaline phosphatase activity of Tetraselmis sp. as a function of the dissolved inorganic phosphorus concentration and show that the time scale of the kinetics spans 1 order of magnitude. The advantages of subnanoliter-scale compartmentalization in droplet-based microfluidics provide a precise characterization of a population with single-cell resolution. Our results highlight the key role of cell physiology to efficiently access dissolved organic phosphorus.

Algorithm for the precise detection of single and cluster cells in microfluidic applications.

Recent advances in imaging flow cytometry and microfluidic applications have led to the development of suitable mathematical algorithms capable of detecting and identifying targeted cells in images. In contrast to currently existing algorithms, we herein proposed the identification and reconstruction of cell edges based on original approaches that overcome frequent detection limitations such as halos, noise, and droplet boundaries in microfluidic applications. Reconstructed cells are then discriminated between single cells and clusters of round-shaped cells, and cell information such as the area and location of a cell in an image is output. Using this method, 76% of cells detected in an image had an error <5% of the cell area size and 41% of the image had an error <1% of the cell area size (n = 1,000). The method developed in the present study is the first image processing algorithm designed to be flexible in use (i.e. independent of the size of an image, using a microfluidic droplet system or not, and able to recognize cell clusters in an image) and provides the scientific community with a very accurate imaging algorithm in the field of microfluidic applications. © 2016 International Society for Advancement of Cytometry.

Variable inter and intraspecies alkaline phosphatase activity within single cells of revived dinoflagellates.

Adaptation of cell populations to environmental changes is mediated by phenotypic variability at the single-cell level. Enzyme activity is a key factor in cell phenotype and the expression of the alkaline phosphatase activity (APA) is a fundamental phytoplankton strategy for maintaining growth under phosphate-limited conditions. Our aim was to compare the APA among cells and species revived from sediments of the Bay of Brest (Brittany, France), corresponding to a pre-eutrophication period (1940's) and a beginning of a post-eutrophication period (1990's) during which phosphate concentrations have undergone substantial variations. Both toxic marine dinoflagellate Alexandrium minutum and the non-toxic dinoflagellate Scrippsiella acuminata were revived from ancient sediments. Using microfluidics, we measured the kinetics of APA at the single-cell level. Our results indicate that all S. acuminata strains had significantly higher APA than A. minutum strains. For both species, the APA in the 1990's decade was significantly lower than in the 1940's. For the first time, our results reveal both inter and intraspecific variabilities of dinoflagellate APA and suggest that, at a half-century timescale, two different species of dinoflagellate may have undergone similar adaptative evolution to face environmental changes and acquire ecological advantages.

Light-powered CO2 fixation in a chloroplast mimic with natural and synthetic parts.

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.

Microfluidic technology for plankton research.

Plankton produces numerous chemical compounds used in cosmetics and functional foods. They also play a key role in the carbon budget on the Earth. In a context of global change, it becomes important to understand the physiological response of these microorganisms to changing environmental conditions. Their adaptations and the response to specific environmental conditions are often restricted to a few active cells or individuals in large populations. Using analytical capabilities at the subnanoliter scale, microfluidic technology has also demonstrated a high potential in biological assays. Here, we review recent advances in microfluidic technologies to overcome the current challenges in high content analysis both at population and the single cell level.

An on-chip imaging droplet-sorting system: a real-time shape recognition method to screen target cells in droplets with single cell resolution.

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.

Development of on-chip multi-imaging flow cytometry for identification of imaging biomarkers of clustered circulating tumor cells.

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.