Microscopy is an essential method in modern biology, and brightfield microscopy methods (phase contrast, differential interference contrast, etc.) are being widely used and actively developed since they don’t require sample fixation and staining. But they produce low contrast images, where cells have similar intensity to the background. In this work we developed and tested a set of deep learning object detection YOLO models that detect cell nuclei in phase contrast images, which allows cell count and tracking without staining. We created a large dataset consisting of more than 100,000 640×640 pixels images with more than 3 million nuclei of 4 different cell cultures (CHO, HEK293, iPSCs, and MSCs). Using images from various microscopes and cameras, as well as full-scale augmentations, we developed a set of highly generalized models that can detect nuclei in images across different cell types and imaging conditions, including different microscopes and contrast methods. Combined with sliced inference methods, these algorithms can be applied to images of any size, allowing studies of large quantities of cells. Moreover, we developed a training-free calibration and testing algorithm based on confidence threshold optimization. It allows for fine-tuning of models for specific cell types and/or imaging options and evaluating the accuracy of the calibrated model. This provides a highly controllable and reliable method for studying cell proliferation rate, single cell tracking and other scenarios. Additionally, we developed a NuclePhaser plugin for Napari ( https://github.com/nikvo1/napari-nuclephaser ), which allows users to calibrate, test and apply our models in code-free manner. Given that the YOLO models are fast and can run at sufficient speeds even on CPUs, this makes our work highly accessible to a wide range of researchers.

Genetically encoded fluorescent biosensors (GEBs) are extensively utilized for investigating intracellular signaling processes. Nevertheless, the potential impact of these sensors on intracellular signaling pathways and overall cellular functionality is frequently overlooked, which may lead to inaccuracies in experimental results. In this study, the authors examined the effects of a widely used fluorescent biosensor, which binds to phosphatidylinositol 3,4,5-trisphosphate (PIP3), on the phosphoinositide 3-kinase (PI3K)-signaling pathway in an immortalized multipotent mesenchymal stromal cell (MSC) line. To achieve this, two immortalized MSC lines with distinct levels of biosensor expression were generated. The introduction of the biosensor led to a reduction in the adipogenic potential of these cell lines compared to the parental line. This effect was attributed to the inhibition of the PI3K signaling pathway, which is activated by insulin—a critical regulator of adipogenic differentiation. The biosensor to PIP3 interfered with the recruitment of downstream effectors, namely PDK and Akt. This was evidenced by diminished levels of phosphorylated Akt (p-Akt) following insulin stimulation in the transduced cell lines relative to the parental line, with the cell line exhibiting higher biosensor expression showing lower p-Akt levels than the line with lower expression. In contrast, the levels of phosphorylated ERK, a marker of another insulin-dependent signaling pathway, remained consistent across all cell lines, indicating that the biosensor selectively inhibited the PIP3-dependent pathway. This case emphasizes the necessity of a careful and cautious approach when employing GEBs in biological research. Prior to their use, it is imperative to verify that these biosensors do not disrupt intracellular signaling cascades or alter cellular behavior.

The key processes determining cell differentiation are the synthesis of new proteins and restructuring of the extracellular matrix. The production of matrix and cytosolic proteins, in turn, requires the constant involvement of the heat shock protein system — chaperones that ensure the proper folding of newly synthesized protein molecules and maintain their functional state. The aim of this study was to evaluate the effect of the heat shock protein inducer geranylgeranylacetone (GGA) on the differentiation of human mesenchymal stem cells. The study found that pretreating cells with GGA for 24 hours altered the pattern of calcium responses to the pro- osteogenic stimulus, parathyroid hormone. There was an increase in the number of cells responding to anti- osteogenic calcium oscillations associated with a decrease in the osteogenic potential of MSCs. Induction of osteogenic differentiation demonstrated a decrease in calcium deposition and and gene expression. However, the addition of GGA had no significant effect on adipogenic differentiation. In search of a possible anti- osteogenic mechanism for the action of GGA, we analyzed the MSC proteomes treated with GGA or DMSO as controls. We found that incubation with GGA resulted in the absence of several proteins. Among these, calmodulin proteins (CALM1, CALM2, and CALM3), coactivators of adenylate cyclases, and proteins that regulate the actin cytoskeleton play a key role in osteogenesis. Thus, we demonstrated that the effect of GGA leads to a significant reduction in the capacity of MSCs for osteogenic, but not adipogenic, differentiation. A more detailed study of the mechanism of GGA action on embryonic and postnatal stem cells will further elucidate key features of the formation of new osteoblasts during embryogenesis and postnatal tissue renewal.