An Integral Activity-Based Protein Profiling Method for Higher Throughput Determination of Protein Target Sensitivity to Small Molecules

IF 3.8 2区 生物学 Q2 BIOCHEMISTRY & MOLECULAR BIOLOGY
Chathuri J. Kombala, Agne Sveistyte, Tong Zhang, Leo J. Gorham, Gerard X. Lomas, John T. Melchior, Priscila M. Lalli, Vanessa L. Paurus, Stephen J. Callister, Aaron T. Wright* and Vivian S. Lin*, 
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Abstract

Activity-based protein profiling (ABPP) is a chemoproteomic technique that uses small molecule probes to label active enzymes selectively and covalently in complex proteomes. Competitive ABPP, which involves treatment of the active proteome with an analyte of interest, is especially powerful for profiling how small molecules impact specific protein activities. Advances in higher throughput workflows have made it possible to generate extensive competitive ABPP data across diverse biological samples, making this approach highly appealing for characterizing shared and unique proteins affected by perturbations such as drug or chemical exposures. To use the competitive ABPP approach effectively to understand potential adverse effects of chemicals of concern (CoC), a wide range of concentrations may be needed, particularly for chemicals that lack potency or toxicity data. In this work, we present an integral competitive ABPP method that enables target sensitivity determination for different organophosphate (OP) pesticides as model toxicants. Using previously developed OP-ABPs, we optimized conditions for tandem mass tag (TMT) multiplexing of ABPP samples and compared conventional competitive ABPP involving samples at discrete paraoxon concentrations to pooled samples across that same concentration range. We then expanded our approach to compare protein target sensitivities toward two additional OP pesticides, chlorpyrifos oxon and malaoxon. The results showed that differences in integral intensities for the pooled competition sample can be used to evaluate the relative sensitivity of specific proteins without increasing the overall number of samples. For 8 CoC concentrations of interest, this strategy reduced the number of TMT plexes and the corresponding number of LC–MS/MS analyses 3-fold. We envision the integral ABPP (IABPP) method will provide a means to screen diverse chemicals more rapidly to identify both high and low sensitivity protein targets.

Abstract Image

基于整体活性的蛋白质谱分析方法用于高通量测定蛋白质对小分子靶标的敏感性。
基于活性的蛋白质分析(ABPP)是一种化学蛋白质组学技术,它使用小分子探针选择性地和共价地标记复杂蛋白质组中的活性酶。竞争性ABPP,包括用感兴趣的分析物处理活性蛋白质组,在分析小分子如何影响特定蛋白质活性方面尤其强大。高通量工作流程的进步使得在不同生物样品中生成广泛的竞争性ABPP数据成为可能,使得这种方法对于表征受药物或化学物质暴露等扰动影响的共享和独特蛋白质具有很高的吸引力。为了有效地使用竞争性ABPP方法来了解关注化学品(CoC)的潜在不利影响,可能需要广泛的浓度范围,特别是对于缺乏效力或毒性数据的化学品。在这项工作中,我们提出了一种积分竞争ABPP方法,可以确定不同有机磷(OP)农药作为模型毒物的目标敏感性。使用先前开发的OP-ABPs,我们优化了ABPP样品的串联质量标签(TMT)复用条件,并比较了涉及离散对氧磷浓度样品的传统竞争性ABPP与相同浓度范围内的混合样品。然后,我们扩展了我们的方法,比较了蛋白质靶点对另外两种OP农药的敏感性,毒死蜱和丙二醇。结果表明,在不增加样品总数的情况下,混合竞争样品的积分强度差异可用于评估特定蛋白质的相对敏感性。对于感兴趣的8种CoC浓度,该策略将TMT复合物的数量和相应的LC-MS/MS分析次数减少了3倍。我们设想积分ABPP (IABPP)方法将提供一种更快速地筛选多种化学物质的方法,以识别高灵敏度和低灵敏度的蛋白质靶点。
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
ACS Chemical Biology
ACS Chemical Biology 生物-生化与分子生物学
CiteScore
7.50
自引率
5.00%
发文量
353
审稿时长
3.3 months
期刊介绍: ACS Chemical Biology provides an international forum for the rapid communication of research that broadly embraces the interface between chemistry and biology. The journal also serves as a forum to facilitate the communication between biologists and chemists that will translate into new research opportunities and discoveries. Results will be published in which molecular reasoning has been used to probe questions through in vitro investigations, cell biological methods, or organismic studies. We welcome mechanistic studies on proteins, nucleic acids, sugars, lipids, and nonbiological polymers. The journal serves a large scientific community, exploring cellular function from both chemical and biological perspectives. It is understood that submitted work is based upon original results and has not been published previously.
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