Laurentius Lars B, Crawford Alexis C, Mulvihill Timothy S, Granger Jennifer H, Robinson Ryan, Spencer John S, Chatterjee Delphi, Hanson Kimberly E, Porter Marc D
The Nano Institute of Utah, University of Utah, Salt Lake City, UT 84112, USA.
Department of Chemistry, University of Utah, Salt Lake City, UT 84112, USA.
Analyst. 2016 Dec 19;142(1):177-185. doi: 10.1039/c6an02109c.
Patient care and prevention of disease outbreaks rely heavily on the performance of diagnostic tests. These tests are typically carried out in serum, urine, and other complex sample matrices, but are often plagued by a number of matrix effects such as nonspecific adsorption and complexation with circulating proteins. This paper demonstrates the importance of sample pretreatment to overcome matrix effects, enabling the low-level detection of a disease marker for tuberculosis (TB). The impact of pretreatment is illustrated by detecting a cell wall component unique to mycobacteria, lipoarabinomannan (LAM). LAM is a major virulence factor in the infectious pathology of Mycobacterium tuberculosis (Mtb) and has been successfully detected in the body fluids of TB-infected individuals; however, its clinical sensitivity - identifying patients with active infection - remains problematic. This and the companion paper show that the detection of LAM in an immunoassay is plagued by its complexation with proteins and other components in serum. Herein, we present the procedures and results from an investigation of several different pretreatment schemes designed to disrupt complexation and thereby improve detection. These sample pretreatment studies, aimed at determining the optimal conditions for complex disruption, were carried out by using a LAM simulant derived from the nonpathogenic M. smegmatis, a mycobacterium often used as a model for Mtb. We have found that a perchloric acid-based pretreatment step improves the ability to detect this simulant by ∼1500× with respect to that in untreated serum. This paper describes the approach to pretreatment, how pretreatment improves the detection of the LAM simulant in human serum, and the results from a preliminary investigation to identify possible contributors to complexation by fractionating serum according to molecular weight. The companion paper applies this pretreatment approach to assays of TB patient samples.
患者护理和疾病爆发的预防在很大程度上依赖于诊断测试的性能。这些测试通常在血清、尿液和其他复杂样本基质中进行，但常常受到多种基质效应的困扰，如非特异性吸附以及与循环蛋白的络合。本文证明了样本预处理对于克服基质效应的重要性，从而能够对结核病（TB）的疾病标志物进行低水平检测。通过检测分枝杆菌特有的一种细胞壁成分——脂阿拉伯甘露聚糖（LAM）来说明预处理的影响。LAM是结核分枝杆菌（Mtb）感染病理学中的一种主要毒力因子，并且已在TB感染个体的体液中成功检测到；然而，其临床敏感性——识别活动性感染患者——仍然存在问题。本文以及配套论文表明，在免疫测定中检测LAM受到其与血清中蛋白质和其他成分络合的困扰。在此，我们展示了对几种不同预处理方案进行研究的程序和结果，这些方案旨在破坏络合并从而改善检测。这些样本预处理研究旨在确定络合破坏的最佳条件，通过使用源自非致病性耻垢分枝杆菌的LAM模拟物进行，耻垢分枝杆菌是一种常被用作Mtb模型的分枝杆菌。我们发现，基于高氯酸的预处理步骤相对于未处理的血清，将检测这种模拟物的能力提高了约1500倍。本文描述了预处理方法、预处理如何改善在人血清中对LAM模拟物的检测，以及通过根据分子量对血清进行分级分离来识别可能导致络合的因素的初步调查结果。配套论文将这种预处理方法应用于TB患者样本的检测。
