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基于适配体的多重蛋白质组学技术用于生物标志物发现。

Aptamer-based multiplexed proteomic technology for biomarker discovery.

机构信息

SomaLogic, Boulder, Colorado, USA.

出版信息

PLoS One. 2010 Dec 7;5(12):e15004. doi: 10.1371/journal.pone.0015004.

Abstract

BACKGROUND

The interrogation of proteomes ("proteomics") in a highly multiplexed and efficient manner remains a coveted and challenging goal in biology and medicine.

METHODOLOGY/PRINCIPAL FINDINGS: We present a new aptamer-based proteomic technology for biomarker discovery capable of simultaneously measuring thousands of proteins from small sample volumes (15 µL of serum or plasma). Our current assay measures 813 proteins with low limits of detection (1 pM median), 7 logs of overall dynamic range (~100 fM-1 µM), and 5% median coefficient of variation. This technology is enabled by a new generation of aptamers that contain chemically modified nucleotides, which greatly expand the physicochemical diversity of the large randomized nucleic acid libraries from which the aptamers are selected. Proteins in complex matrices such as plasma are measured with a process that transforms a signature of protein concentrations into a corresponding signature of DNA aptamer concentrations, which is quantified on a DNA microarray. Our assay takes advantage of the dual nature of aptamers as both folded protein-binding entities with defined shapes and unique nucleotide sequences recognizable by specific hybridization probes. To demonstrate the utility of our proteomics biomarker discovery technology, we applied it to a clinical study of chronic kidney disease (CKD). We identified two well known CKD biomarkers as well as an additional 58 potential CKD biomarkers. These results demonstrate the potential utility of our technology to rapidly discover unique protein signatures characteristic of various disease states.

CONCLUSIONS/SIGNIFICANCE: We describe a versatile and powerful tool that allows large-scale comparison of proteome profiles among discrete populations. This unbiased and highly multiplexed search engine will enable the discovery of novel biomarkers in a manner that is unencumbered by our incomplete knowledge of biology, thereby helping to advance the next generation of evidence-based medicine.

摘要

背景

以高度多重和高效的方式对蛋白质组(“蛋白质组学”)进行分析仍然是生物学和医学领域令人向往和具有挑战性的目标。

方法/主要发现:我们提出了一种新的基于适体的蛋白质组学技术,用于生物标志物发现,能够从小样本量(15 µL 血清或血浆)中同时测量数千种蛋白质。我们目前的测定法可测量 813 种蛋白质,具有较低的检测限(中位数 1 pM),整体动态范围为 7 个对数(~100 fM-1 µM),中位数变异系数为 5%。这项技术得益于新一代的适体,其中包含了化学修饰的核苷酸,这大大扩展了适体选择的大型随机核酸文库的理化多样性。复杂基质(如血浆)中的蛋白质是通过一种将蛋白质浓度特征转化为相应的 DNA 适体浓度特征的过程进行测量的,然后在 DNA 微阵列上对其进行定量。我们的测定法利用了适体作为具有定义形状和可通过特定杂交探针识别的独特核苷酸序列的折叠蛋白结合实体的双重性质。为了证明我们的蛋白质组学生物标志物发现技术的实用性,我们将其应用于慢性肾脏病(CKD)的临床研究。我们鉴定出两种已知的 CKD 生物标志物以及另外 58 种潜在的 CKD 生物标志物。这些结果表明,我们的技术具有快速发现各种疾病状态独特蛋白质特征的潜力。

结论/意义:我们描述了一种通用且强大的工具,允许在离散人群中对蛋白质组谱进行大规模比较。这种无偏且高度多重的搜索引擎将能够以不受我们生物学知识不完整的限制的方式发现新的生物标志物,从而有助于推进下一代循证医学。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/566f/3000457/a0f1817e7eb9/pone.0015004.g001.jpg

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