Reddy Syon, Chen Yu-Lin, Suzuki Aussie
McArdle Laboratory for Cancer Research, Department of Oncology, University of Wisconsin-Madison, Madison, WI, USA.
Carbone Cancer Center, University of Wisconsin-Madison, Madison, WI, USA.
Bio Protoc. 2025 Aug 5;15(15):e5407. doi: 10.21769/BioProtoc.5407.
Accurate identification of cell cycle stages is essential for investigating fundamental biological processes such as proliferation, differentiation, and tumorigenesis. While flow cytometry remains a widely used technique for such analyses, it is limited by its lack of single-cell resolution and its requirement for large sample sizes due to its population-based approach. These limitations underscore the need for alternative or complementary methods that offer single-cell precision with compatibility for small-scale applications. We present ImmunoCellCycle-ID, an immunofluorescence-based method that leverages the spatial distribution of endogenous markers, such as DNA, proliferating cell nuclear antigen (PCNA), centromere protein F (CENP-F), and centromere protein C (CENP-C), to reliably distinguish G1, early S, late S, early G2, late G2, and all mitotic sub-stages. This technique does not rely on precise signal quantification and utilizes standard immunofluorescence protocols alongside conventional laboratory microscopes, ensuring broad accessibility. Importantly, ImmunoCellCycle-ID detects endogenous proteins without the need for genetic modification, making it readily applicable to a wide range of human cell lines. Beyond its utility for single-cell resolution, the method can be scaled for population-level analyses, similar to flow cytometry. With its precision, versatility, and ease of implementation, ImmunoCellCycle-ID offers a powerful tool for high-resolution cell cycle profiling across diverse experimental platforms. Key features • Enables high-precision identification of cell cycle stages at single-cell resolution. • Broadly applicable to diverse human cell lines without genetic modification. • Fully compatible with standard fluorescence microscopy; no specialized equipment needed. • Requires only minimal image analysis and no complex quantification.
准确识别细胞周期阶段对于研究增殖、分化和肿瘤发生等基本生物学过程至关重要。虽然流式细胞术仍然是用于此类分析的广泛使用的技术,但由于其基于群体的方法,缺乏单细胞分辨率且需要大样本量,因此存在局限性。这些局限性凸显了对替代或补充方法的需求,这些方法能够提供单细胞精度并适用于小规模应用。我们提出了免疫细胞周期识别法(ImmunoCellCycle-ID),这是一种基于免疫荧光的方法,利用内源性标志物(如DNA、增殖细胞核抗原(PCNA)、着丝粒蛋白F(CENP-F)和着丝粒蛋白C(CENP-C))的空间分布,可靠地区分G1期、早S期、晚S期、早G2期、晚G2期以及所有有丝分裂亚阶段。该技术不依赖于精确的信号定量,并且使用标准免疫荧光方案以及传统实验室显微镜,确保了广泛的可及性。重要的是,免疫细胞周期识别法无需基因改造即可检测内源性蛋白质,使其易于应用于广泛的人类细胞系。除了在单细胞分辨率方面的效用外,该方法还可以扩展用于群体水平分析,类似于流式细胞术。凭借其精度、多功能性和易于实施的特点,免疫细胞周期识别法为跨不同实验平台的高分辨率细胞周期分析提供了一个强大的工具。关键特性 • 能够在单细胞分辨率下高精度识别细胞周期阶段。 • 广泛适用于各种人类细胞系,无需基因改造。 • 与标准荧光显微镜完全兼容;无需专门设备。 • 仅需最少的图像分析,无需复杂的定量。