Multiplexed protease activity profiling for host response-based Sepsis diagnosis

IF 4.1 3区 医学 Q2 MEDICAL LABORATORY TECHNOLOGY
Clinica Chimica Acta Pub Date : 2027-03-15 Epub Date: 2026-10-19 DOI:10.1016/j.cca.2026.122903
Emily R. Caton, Yezhi Pan, Kiana M. Kiser, Caroline R. Haddaway, Wayne A. Bryden, Michael McLoughlin, Marek A. Mirski, Robert H. Christenson, Cindy C. Sevilla, Shuo Chen, Sheng Feng, Dapeng Chen
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引用次数: 0

Abstract

Human proteases play major roles in various pathological conditions, including dysregulated immune responses in sepsis, making them strong candidates for developing diagnostic markers. Despite this potential, the process of developing protease-based diagnostic tools has remained slow due to significant technical barriers associated with measuring protease activity, mainly stemming from the vast diversity of human proteases and the lack of substrate specificity, which complicates the interpretation of activity profiles. In this work, we advanced the current state of assay development by engineering substrate molecules and implementing an analytical approach based on mass spectrometry. Specifically, we developed a novel approach to chemically modify protease substrates for human neutrophil elastase (HNE) and matrix metalloproteinases (MMPs) to enhance specificity and generate unique mass-to-charge signatures, allowing the deconvolution of protease activities. We then integrated the modified substrates into a mass spectrometry-based platform for quantifying multiple protease activities within a single analytical run. We applied the assay to spared plasma samples and demonstrated that the assay detects distinct protease activity profiles. We further demonstrated that the assay achieved a diagnostic sensitivity of 88% and specificity of 87% for sepsis detection within a three-hour timeframe.

One Sentence Summary

We developed a novel multiplexed protease activity profiling approach to quantify immune responses and improve sepsis diagnosis.
基于宿主反应的脓毒症诊断的多重蛋白酶活性分析。
人类蛋白酶在各种病理状况中发挥重要作用,包括败血症中失调的免疫反应,使其成为开发诊断标记物的有力候选者。尽管有这种潜力,但由于与测量蛋白酶活性相关的重大技术障碍,开发基于蛋白酶的诊断工具的过程仍然缓慢,这主要源于人类蛋白酶的巨大多样性和缺乏底物特异性,这使得活性谱的解释变得复杂。在这项工作中,我们通过工程底物分子和实施一种基于质谱的分析方法来推进分析发展的现状。具体来说,我们开发了一种新的方法来化学修饰人类中性粒细胞弹性酶(HNE)和基质金属蛋白酶(MMPs)的蛋白酶底物,以增强特异性并产生独特的质量-电荷特征,从而允许蛋白酶活性的反褶合。然后,我们将修饰的底物整合到基于质谱的平台中,用于在单次分析运行中定量多种蛋白酶活性。我们将该分析应用于备用血浆样品,并证明该分析检测到不同的蛋白酶活性谱。我们进一步证明,该方法在3小时内检测脓毒症的诊断灵敏度为88%,特异性为87%。摘要:我们开发了一种新的多重蛋白酶活性分析方法来量化免疫反应并改善败血症的诊断。
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
Clinica Chimica Acta
Clinica Chimica Acta 医学-医学实验技术
CiteScore
10.10
自引率
2.00%
发文量
1268
审稿时长
23 days
期刊介绍: The Official Journal of the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) Clinica Chimica Acta is a high-quality journal which publishes original Research Communications in the field of clinical chemistry and laboratory medicine, defined as the diagnostic application of chemistry, biochemistry, immunochemistry, biochemical aspects of hematology, toxicology, and molecular biology to the study of human disease in body fluids and cells. The objective of the journal is to publish novel information leading to a better understanding of biological mechanisms of human diseases, their prevention, diagnosis, and patient management. Reports of an applied clinical character are also welcome. Papers concerned with normal metabolic processes or with constituents of normal cells or body fluids, such as reports of experimental or clinical studies in animals, are only considered when they are clearly and directly relevant to human disease. Evaluation of commercial products have a low priority for publication, unless they are novel or represent a technological breakthrough. Studies dealing with effects of drugs and natural products and studies dealing with the redox status in various diseases are not within the journal''s scope. Development and evaluation of novel analytical methodologies where applicable to diagnostic clinical chemistry and laboratory medicine, including point-of-care testing, and topics on laboratory management and informatics will also be considered. Studies focused on emerging diagnostic technologies and (big) data analysis procedures including digitalization, mobile Health, and artificial Intelligence applied to Laboratory Medicine are also of interest.
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