Cellaca® PLX image cytometer as an alternative for immunophenotyping, GFP/RFP transfection efficiencies, and apoptosis analysis.

Cell and gene therapy is a fast-growing field for cancer therapeutics requiring reliable instrumentation and technologies. Key parameters essential for satisfying Chemistry Manufacturing and Controls criteria standards are routinely performed using flow cytometry. Recently, image cytometry was developed for cell characterization and cell-based assays but had not yet demonstrated sufficient sensitivity for surface marker detection. We developed the Cellaca® PLX image cytometry system and the respective methodologies required for immunophenotyping, GFP and RFP transfection/transduction efficiencies, and cell health analyses for routine cell characterization. All samples tested were compared directly to results from the CytoFLEX flow cytometer. PBMCs were stained with T-cell surface markers for immunophenotyping, and results show highly comparable CD3, CD4, and CD8 populations (within 5 %). GFP- or RFP-expressing cell lines were analyzed for transfection/transduction efficiencies, and the percentage positive cells and respective viabilities were equivalent on both systems. Staurosporine-treated Jurkat cells were stained for apoptotic markers, where annexin V and caspase-3 positive cells were within 5 % comparing both instruments. The proposed system may provide a complementary tool for performing routine cell-based experiments with improved efficiency and sensitivity compared to prior image cytometers, which may be significantly valuable to the cell and gene therapy field.

A novel image-based method for simultaneous counting of Lactobacillus and Saccharomyces in mixed culture fermentation.

Mixed microorganism cultures are prevalent in the food industry. A variety of microbiological mixtures have been used in these unique fermenting processes to create distinctive flavor profiles and potential health benefits. Mixed cultures are typically not well characterized, which may be due to the lack of simple measurement tools. Image-based cytometry systems have been employed to automatically count bacteria or yeast cells. In this work, we aim to develop a novel image cytometry method to distinguish and enumerate mixed cultures of yeast and bacteria in beer products. Cellometer X2 from Nexcelom was used to count of Lactobacillus plantarum and Saccharomyces cerevisiae in mixed cultures using fluorescent dyes and size exclusion image analysis algorithm. Three experiments were performed for validation. (1) Yeast and bacteria monoculture titration, (2) mixed culture with various ratios, and (3) monitoring a Berliner Weisse mixed culture fermentation. All experiments were validated by comparing to manual counting of yeast and bacteria colony formation. They were highly comparable with ANOVA analysis showing p-value > 0.05. Overall, the novel image cytometry method was able to distinguish and count mixed cultures consistently and accurately, which may provide better characterization of mixed culture brewing applications and produce higher quality products.