Recommendations for mRNA analysis of micro-dissected glomerular tufts from paraffin-embedded human kidney biopsy samples

IF 2.946 Q3 Biochemistry, Genetics and Molecular Biology
Clemens L. Bockmeyer, Juliane Wittig, Karen Säuberlich, Philipp Selhausen, Marc Eßer, Philip Zeuschner, Friedrich Modde, Kerstin Amann, Christoph Daniel
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引用次数: 6

Abstract

Glomeruli are excellent pre-determined natural structures for laser micro-dissection. Compartment-specific glomerular gene expression analysis of formalin-fixed paraffin-embedded renal biopsies could improve research applications. The major challenge for such studies is to obtain good-quality RNA from small amounts of starting material, as applicable for the analysis of glomerular compartments. In this work, we provide data and recommendations for an optimized workflow of glomerular mRNA analysis.

With a proper resolution of the camera and screen provided by the next generation of micro-dissection systems, we are able to separate parietal epithelial cells from glomerular tufts. Selected compartment-specific transcripts (WT1 and GLEPP1 for glomerular tuft as well as PAX2 for parietal epithelial cells) seem to be reliable discriminators for these micro-dissected glomerular substructures. Using the phenol–chloroform extraction and hemalaun-stained sections?(2?μm), high amounts of Bowman’s capsule transections (>?300) reveal sufficient RNA concentrations (>?300?ng mRNA) for further analysis. For comparison, in unstained sections from a number of 60 glomerular transections upwards, a minimum amount of 157?ng mRNA with a reasonable mRNA purity [A260/A280 ratio of 1.5 (1.4/1.7) median (25th/75th percentiles)] was reversely transcribed into cDNA. Comparing the effect of input RNA (20, 60, 150 and 300 micro-dissected glomerular transections), transcript expression of POLR2A significantly correlated when 60 and 150 laser micro-dissected glomerular transections were used for analysis. There was a lower inter-assay coefficient of variability for ADAMTS13, when at least 60 glomerular transections were used. According to the algorithms of geNormPlus and NormFinder, PGK1 and PPIA are more stable glomerular reference transcripts compared to GUSB, GAPDH, POLR2A, RPLPO, TBP, B2M, ACTB, 18SrRNA and HMBS.

Our approach implements compartment-specific glomerular mRNA expression analysis into research applications, even regarding glomerular substructures like parietal epithelial cells. We recommend using of at least 60 micro-dissected unstained glomerular or 300 hemalaun-stained Bowman’s capsule transections to obtain sufficient input mRNA for reproducible results. Hereby, the range of RNA concentrations in 60 micro-dissected glomeruli is low and appropriate normalization of Cq values using our suggested reference transcripts (PGK1 and PPIA) allows compensation with respect to different amounts of RNA purity and quantity.

Abstract Image

石蜡包埋人肾活检标本微解剖肾小球簇mRNA分析建议
肾小球是用于激光显微解剖的优良的预先确定的自然结构。福尔马林固定石蜡包埋肾活检细胞间室特异性肾小球基因表达分析可提高研究应用。这类研究面临的主要挑战是如何从少量起始材料中获得高质量的RNA,以用于肾小球室的分析。在这项工作中,我们为优化肾小球mRNA分析工作流程提供了数据和建议。利用下一代显微解剖系统提供的适当分辨率的相机和屏幕,我们能够从肾小球簇中分离壁上皮细胞。选定的室特异性转录物(肾小球簇的WT1和GLEPP1以及壁上皮细胞的PAX2)似乎是这些微解剖肾小球亚结构的可靠鉴别物。使用苯酚-氯仿提取和血细胞染色切片(2 μm),大量的鲍曼囊切片(>?300)显示出足够的RNA浓度(>?300?ng mRNA)作进一步分析。相比之下,在60例以上的未染色肾小球切片中,至少有157?以合理的mRNA纯度[A260/A280比值为1.5(1.4/1.7)中位数(25 /75百分位数)]逆转录到cDNA中。对比输入RNA(20、60、150和300个微解剖肾小球切片)的影响,用60和150个激光微解剖肾小球切片进行分析时,POLR2A转录物表达显著相关。当使用至少60个肾小球横断时,ADAMTS13的测定间变异性系数较低。根据geNormPlus和NormFinder算法,与GUSB、GAPDH、POLR2A、RPLPO、TBP、B2M、ACTB、18SrRNA和HMBS相比,PGK1和PPIA是更稳定的肾小球参考转录物。我们的方法将室特异性肾小球mRNA表达分析应用于研究,甚至涉及肾小球亚结构,如壁上皮细胞。我们建议使用至少60个未染色的微解剖肾小球或300个未染色的鲍曼囊切片来获得足够的输入mRNA,以获得可重复的结果。因此,60个微解剖肾小球的RNA浓度范围很低,使用我们建议的参考转录物(PGK1和PPIA)适当正常化Cq值可以补偿不同数量的RNA纯度和数量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
BMC Molecular Biology
BMC Molecular Biology 生物-生化与分子生物学
CiteScore
4.80
自引率
0.00%
发文量
0
审稿时长
>12 weeks
期刊介绍: BMC Molecular Biology is an open access journal publishing original peer-reviewed research articles in all aspects of DNA and RNA in a cellular context, encompassing investigations of chromatin, replication, recombination, mutation, repair, transcription, translation and RNA processing and function.
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