Fung Anthony A, Li Zhi, Boote Craig, Markov Petar, Jain Sanjay, Shi Lingyan
Shu Chien-Gene Lay Department of Bioengineering, University of California San Diego, La Jolla, CA, USA 92093.
School of Optometry & Vision Sciences, Cardiff University, Cardiff, UK CF24 4HQ.
bioRxiv. 2024 Oct 29:2024.10.27.620507. doi: 10.1101/2024.10.27.620507.
Kidney disease, the ninth leading cause of death in the United States, has one of the poorest diagnostic efficiencies of only 10%. Conventional diagnostic methods often rely on light microscopy analysis of 2D fixed tissue sections with limited molecular insight compared to omics studies. Targeting multiple features in a biopsy using molecular or chemical reagents can enhance molecular phenotyping but are limited by overlap of their spatial and chromatic properties, variations in quality of the products, limited multimodal nature and need additional tissue processing. To overcome these limitations and increase the breadth of molecular information available from tissue without an impact on routine diagnostic workup, we implemented label-free imaging modalities including stimulated Raman scattering (SRS) microscopy, second harmonic generation (SHG), and two photon fluorescence (TPF) into a single microscopy setup. We visualized and identified morphological, structural, lipidomic, and metabolic biomarkers of control and diabetic human kidney biopsy samples in 2D and 3D at a subcellular resolution. The label-free biomarkers, including collagen fiber morphology, mesangial-glomerular fractional volume, lipid saturation, redox status, and relative lipid and protein concentrations in the form of Stimulated Raman Histology (SRH), illustrate distinct features in kidney disease tissues not previously appreciated. The same tissue section can be used for routine diagnostic work up thus enhancing the power of cliniopathological insights obtainable without compromising already limited tissue. The additional multimodal biomarkers and metrics are broadly applicable and deepen our understanding of the progression of kidney diseases by integrating lipidomic, fibrotic, and metabolic data.
肾病是美国第九大死因，其诊断效率极低，仅为10%。与组学研究相比，传统诊断方法通常依赖于二维固定组织切片的光学显微镜分析，分子层面的洞察有限。使用分子或化学试剂在活检中靶向多个特征可以增强分子表型分析，但受到其空间和颜色特性重叠、产品质量变化、有限的多模态性质以及需要额外组织处理的限制。为了克服这些限制并增加从组织中获取的分子信息的广度，同时不影响常规诊断检查，我们在单一显微镜设置中采用了无标记成像模式，包括受激拉曼散射（SRS）显微镜、二次谐波产生（SHG）和双光子荧光（TPF）。我们在亚细胞分辨率下以二维和三维方式可视化并识别了对照和糖尿病患者肾脏活检样本的形态、结构、脂质组学和代谢生物标志物。无标记生物标志物，包括胶原纤维形态、系膜 - 肾小球分数体积、脂质饱和度、氧化还原状态以及以受激拉曼组织学（SRH）形式呈现的相对脂质和蛋白质浓度，揭示了肾病组织中以前未被认识到的独特特征。同一组织切片可用于常规诊断检查，从而增强临床病理洞察能力，同时不影响已经有限的组织。额外的多模态生物标志物和指标具有广泛的适用性，并通过整合脂质组学、纤维化和代谢数据加深了我们对肾病进展的理解。
