Cell morphology is emerging as a key indicator of the molecular mechanisms. It not only provides a visual representation of the cell structure but also offers valuable insights into the underlying processes and functions of individual cells1. Analyzing the shape, size, and activity of immune cells at the single-cell level provides crucial insights into their behavior, heterogeneity, and roles in health and disease2,3,4,5,6.
Among these crucial cells are natural killer (NK) cells, which are a central component of the innate immune system7,8. They eliminate virus-infected and cancerous cells and regulate the adaptive immune response through cytokine release9,10,11. Cancer, viral infections, and immunodeficiencies often reduce the number of NK cells and impair their functions12,13,14. Therefore, NK cell activation serves as an important biomarker and provides information about the overall health of the immune system. Consequently, rapid single-cell assessment of NK cell activation is essential for prognosis, diagnosis, disease monitoring, and patient stratification15,16,17,18.
Currently, NK cell activity is assessed based on their cytotoxic capacity (ability to kill target cells) and cytokine production19,20,21,22. Conventional methods for measuring cell-mediated cytotoxicity23, such as chromium-51 (51Cr) release assays24,25, flow cytometric assays26,27, and enzyme-linked immunosorbent assays (ELISA) to quantify interferon-gamma (IFN-γ) secreted by NK cells after stimulation28,29,30 have several limitations. These include the lack of standardization, lengthy protocols (e.g., overnight ELISA incubation), dependence on cell labeling, and high equipment costs31,32,33. These challenges highlight the need for innovative methods that offer rapid results, cost-effectiveness, label-free analysis, and high throughput. In addition, the assessment of NK cell activation at the single-cell level provides detailed insights into population heterogeneity and individual cellular responses to stimulation.
Among the emerging technologies aimed at overcoming these limitations, lens-free shadow imaging technology (LSIT) is a particularly effective solution34,35,36. LSIT, a simplified digital inline holography (DIH), enables rapid, label-free, high-throughput analysis of NK cell activation at single-cell resolution37,38,39. The DIH captures interference patterns between scattered laser light and a collinear reference beam on a digital sensor to reconstruct three-dimensional (3D) information about microscopic objects40,41. The LSIT simplifies this approach by using a partially coherent LED, micropinhole, and CMOS sensor to capture the diffraction patterns (i.e., shadow images) of cells42,43,44,45. The rationale for this technique is based on the observation that the activation of immune cells often causes morphological changes, including variations in cell size, shape, cytoplasmic granularity, and nuclear structure46,47,48,49,50. The LSIT is highly sensitive to these changes, which have a direct effect on the diffraction patterns51,52,53.
Building on the sensitivity of LSIT to these morphological changes and their effects on diffraction patterns, this protocol presents a novel method for the rapid and accurate quantification of NK cell count and functional activity at the single-cell level using the Cellytics NK platform, hereafter referred to as the LSIT platform54. As shown in Figure 1A, the LSIT platform integrates sample processing, activation, and shadow imaging into a compact multichannel workflow. NK cells were isolated from whole blood, stimulated with a specially formulated activation stimulator cocktail (ASC), and loaded onto a dedicated assay chip. ASC induces morphological changes in NK cells within 1 h of exposure, such as increased cell size and internal complexity, which can be precisely detected using the LSIT platform55,56.
The LSIT platform uses an LED light source and a CMOS sensor to capture the DIH patterns (shadows) of individual cells (Figure 1B). A special algorithm then analyzes these shadow patterns and extracts key parameters, such as the peak-to-peak distance (PPD), which correlates with cell size, and the standard deviation of the width of the secondary maximum (WSM-SD), which correlates with the complexity and irregularity of the cytoplasm (Figure 1C,D). By comparing the values before and after stimulation, the platform calculates composite indices: the combined shadow parameter (CSP = PPD × WSM-SD) and the innate immunity index (I³), which reflect the percentage change in CSP after activation. The reason for introducing CSP is that immune activation involves both cell enlargement and increased cytoplasmic complexity. Relying on only one of the two criteria can miss borderline activation or be affected by noise, such as debris or irregular illumination. The CSP improves the classification by requiring consistent shifts in both metrics. These indices classify the activation states of different cell populations without fluorescent labeling or complex sample processing.
This protocol is particularly useful for researchers and clinicians who require a rapid, quantitative, and label-free method for monitoring activation-induced morphological changes in immune cells. It is suitable for basic immunological research, preclinical drug screening, and evaluation of immunotherapies, and can be used as a diagnostic or prognostic tool in clinical settings where rapid assessment of immune status is essential. This method requires isolated cell populations, access to the LSIT platform, and a specific NK cell activation cocktail.