Development of flow cytometry assays for measuring cell-membrane enzyme activity on individual cells

Algal cell viability assessment: The role of environmental factors in phytoplankton population dynamics

The viability of algal cells is one of the most fundamental issues in marine ecological research. In this work, a method was designed to identify algal cell viability based on digital holography and deep learning, which divided algal cells into three categories: active, weak, and dead cells. This method was applied to measure algal cells in surface waters of the East China Sea in spring, revealing about 4.34 %-23.29 % weak cells and 3.98 %-19.47 % dead cells. Levels of nitrate and chlorophyll a were the main factors affecting the viability of algal cells. Furthermore, algal viability changes during the heating and cooling were observed in laboratory experiments: high temperatures led to an increase in weak algal cells. This may provide an explanation for why most harmful algal blooms occur in warming months. This study provided a novel insight into how to identify the viability of algal cells and understand their significance in the ocean.

Robust and Long-Term Cellular Protein and Enzymatic Activity Preservation in Biomineralized Mammalian Cells

Preservation of evolved biological structure and function in robust engineering materials is of interest for storage of biological samples before diagnosis and development of vaccines, sensors, and enzymatic reactors and has the potential to avoid cryopreservation and its associated cold-chain issues. Here, we demonstrate that "freezing cells in amorphous silica" is a powerful technique for long-term preservation of whole mammalian cell proteomic structure and function at room temperature. Biomimetic silicification employs the crowded protein microenvironment of mammalian cells as a catalytic framework to proximally transform monomeric silicic acid into silicates forming a nanoscopic silica shell over all biomolecular interfaces. Silicification followed by dehydration preserves and passivates proteomic information within a nanoscale thin silica coating that exhibits size selective permeability (<3.6 nm), preventing protein leaching and protease degradation of cellular contents, while providing access of small molecular constituents for cellular enzymatic reaction. Exposure of dehydrated silicified cells to mild etchant or prolonged hydrolysis removes the silica, completely rerevealing biomolecular components and restoring their accessibility and functionality.

The Molecular Basis of Different Approaches for the Study of Cancer Stem Cells and the Advantages and Disadvantages of a Three-Dimensional Culture

Cancer stem cells (CSCs) are a rare tumor subpopulation with high differentiation, proliferative and tumorigenic potential compared to the remaining tumor population. CSCs were first discovered by Bonnet and Dick in 1997 in acute myeloid leukemia. The identification and isolation of these cells in this pioneering study were carried out through the flow cytometry, exploiting the presence of specific cell surface molecular markers (CD34⁺/CD38⁻). In the following years, different strategies and projects have been developed for the study of CSCs, which are basically divided into surface markers assays and functional assays; some of these techniques also allow working with a cellular model that better mimics the tumor architecture. The purpose of this mini review is to summarize and briefly describe all the current methods used for the identification, isolation and enrichment of CSCs, describing, where possible, the molecular basis, the advantages and disadvantages of each technique with a particular focus on those that offer a three-dimensional culture.

Identification of living and dead microalgae cells with digital holography and verified in the East China Sea

The death of microalgae plays an important role in ocean energy flow and material circulation. The existing methods for the identification of dead and living microalgae cells all have defects such as the need for staining and pre-treatment. In this work, a label-free method to identify living and dead algae cells based on digital holography microscopy and machine learning was designed. At the stage of model training, ten feature vectors were extracted from the holograms, and twelve classification models of machine learning algorithm were trained. Compared with the staining method results, the accuracy of this method can reach 94.8%. At the stage of field verification, the death rate calculated by this method was also consistent with staining method. The method proposed in this paper provides a new method for the study of marine microalgae death which has the advantages of label-free, non-invasive, high accuracy and potential for in-situ application.