Herrmann Yvonne, Kulawik Andreas, Kühbach Katja, Hülsemann Maren, Peters Luriano, Bujnicki Tuyen, Kravchenko Kateryna, Linnartz Christina, Willbold Johannes, Zafiu Christian, Bannach Oliver, Willbold Dieter
Forschungszentrum Jülich, ICS-6 Structural Biochemistry, 52428 Jülich, Germany.
Forschungszentrum Jülich, ICS-6 Structural Biochemistry, 52428 Jülich, Germany; Heinrich-Heine-Universität Düsseldorf, Institut für Physikalische Biologie, 40225 Düsseldorf, Germany.
Clin Biochem. 2017 Mar;50(4-5):244-247. doi: 10.1016/j.clinbiochem.2016.11.001. Epub 2016 Nov 5.
Alzheimer's disease (AD) is a neurodegenerative disorder with yet non-existent therapeutic and limited diagnostic options. Reliable biomarker-based AD diagnostics are of utmost importance for the development and application of therapeutic substances. We have previously introduced a platform technology designated 'sFIDA' for the quantitation of amyloid β peptide (Aβ) aggregates as AD biomarker. In this study we implemented the sFIDA assay on an automated platform to enhance robustness and performance of the assay.
In sFIDA (surface-based fluorescence intensity distribution analysis) Aβ species are immobilized by a capture antibody to a glass surface. Aβ aggregates are then multiply loaded with fluorescent antibodies and quantitated by high resolution fluorescence microscopy. As a model system for Aβ aggregates, we used Aβ-conjugated silica nanoparticles (Aβ-SiNaPs) diluted in PBS buffer and cerebrospinal fluid, respectively. Automation of the assay was realized on a liquid handling system in combination with a microplate washer.
The automation of the sFIDA assay results in improved intra-assay precision, linearity and sensitivity in comparison to the manual application, and achieved a limit of detection in the sub-femtomolar range.
Automation improves the precision and sensitivity of the sFIDA assay, which is a prerequisite for high-throughput measurements and future application of the technology in routine AD diagnostics.
阿尔茨海默病(AD)是一种神经退行性疾病,目前尚无有效的治疗方法,诊断选择也有限。基于可靠生物标志物的AD诊断对于治疗药物的开发和应用至关重要。我们之前引入了一种名为“sFIDA”的平台技术,用于定量检测淀粉样β肽(Aβ)聚集体作为AD生物标志物。在本研究中,我们在自动化平台上实施了sFIDA检测,以提高检测的稳健性和性能。
在sFIDA(基于表面的荧光强度分布分析)中,Aβ物种通过捕获抗体固定在玻璃表面。然后用荧光抗体多次加载Aβ聚集体,并通过高分辨率荧光显微镜进行定量。作为Aβ聚集体的模型系统,我们分别使用了稀释在PBS缓冲液和脑脊液中的Aβ偶联二氧化硅纳米颗粒(Aβ-SiNaPs)。该检测的自动化是在液体处理系统与微孔板洗涤器结合的基础上实现的。
与手动操作相比,sFIDA检测的自动化提高了检测内精度、线性和灵敏度,并在亚飞摩尔范围内达到了检测限。
自动化提高了sFIDA检测的精度和灵敏度,这是高通量测量以及该技术未来在常规AD诊断中应用的先决条件。