基于生物素标记的抗体芯片用于高通量蛋白质表达谱分析。

A biotin label-based antibody array for high-content profiling of protein expression.

机构信息

RayBiotech, Inc., Norcross, GA 30092, USA.

出版信息

Cancer Genomics Proteomics. 2010 May-Jun;7(3):129-41.

PMID:20551245

Abstract

BACKGROUND/AIM: Profiling protein expression on a global scale will have significant impact on biomedical research, particularly in the discovery and development of drugs and biomarkers. Through the years, several antibody array systems have been invented and developed for multiple protein detection. However, a reliable and high-content system for protein profiling from many biological samples has yet been developed. This study aimed to develop a reliable, easy to use and cost effective method to profile protein expression levels in high-content manner with sufficient sensitivity and specificity.

MATERIALS AND METHODS

To address this problem, a high density antibody array was developed and used this technology to uncover the potential biomarkers of ovarian cancer. In this system, biological samples are labeled with biotin. The biotinylated proteins are then incubated with antibody chips. The presence of proteins captured by the antibody chip is detected using streptavidin-conjugated fluorescent dye (Cy3 equivalent) as a reporter. The signals, which are visualized by laser scanning, are normalized using positive, negative, and internal controls.

RESULTS

Using this biotin label-based antibody array technology, the expression levels of 507 human, 308 mouse and 90 rat target proteins can be simultaneously detected, including of cytokines, chemokines, adipokines, growth factors, angiogenic factors, proteases, soluble receptors, soluble adhesion molecules, and other proteins in a variety of samples. Most proteins can be detected at pg/ml and ng/ml levels, with a coefficient of variation of less than 20%. Using human biotin-based antibody arrays, we screened the serum expression profiles of 507 proteins in ovarian cancer patients and healthy individuals. A panel of protein expression showed significant difference between normal and cancer samples (p<0.05). By classification analysis and split-point score analysis of these two groups, a small group of proteins were found to be useful in distinguishing ovarian cancer patients from normal subjects.

CONCLUSION

Our results suggest the biotin label-based antibody arrays that we have developed have great potential in applications for biomarker discovery.

摘要

背景/目的：全面分析蛋白质表达将对生物医学研究产生重大影响，特别是在药物和生物标志物的发现和开发方面。多年来，已经发明和开发了几种用于多种蛋白质检测的抗体微阵列系统。然而，尚未开发出用于从许多生物样品中进行蛋白质分析的可靠、高通量且具有成本效益的方法。本研究旨在开发一种可靠、易于使用且具有成本效益的方法，以高通量方式分析蛋白质表达水平，并具有足够的灵敏度和特异性。

材料和方法

为了解决这个问题，开发了高密度抗体阵列，并使用该技术揭示卵巢癌的潜在生物标志物。在该系统中，生物样品用生物素标记。然后将生物素化蛋白与抗体芯片孵育。使用链霉亲和素缀合的荧光染料（Cy3 等价物）作为报告物检测被抗体芯片捕获的蛋白质的存在。通过激光扫描可视化信号，并使用阳性、阴性和内部对照进行归一化。

结果

使用这种基于生物素标记的抗体微阵列技术，可以同时检测 507 个人类、308 个小鼠和 90 个大鼠靶标蛋白的表达水平，包括细胞因子、趋化因子、脂肪因子、生长因子、血管生成因子、蛋白酶、可溶性受体、可溶性粘附分子和其他各种样品中的蛋白质。大多数蛋白质可以在 pg/ml 和 ng/ml 水平检测到，变异系数小于 20%。使用人类基于生物素的抗体微阵列，我们筛选了卵巢癌患者和健康个体的 507 种蛋白质的血清表达谱。一组蛋白质在正常和癌症样本之间表现出显著差异（p<0.05）。通过对这两组进行分类分析和分割点评分分析，发现一小部分蛋白质可用于区分卵巢癌患者和正常个体。