Real-Time Cellular Exometabolome Analysis with a Microfluidic-Mass Spectrometry Platform

To address the challenges of tracking the multitude of signaling molecules and metabolites that is the basis of biological complexity, we describe a strategy to expand the analytical techniques for dynamic systems biology. Using microfluidics, online desalting, and mass spectrometry technologies, we constructed and validated a platform well suited for sampling the cellular microenvironment with high temporal resolution. Our platform achieves success in: automated cellular stimulation and microenvironment control; reduced non-specific adsorption to polydimethylsiloxane due to surface passivation; real-time online sample collection; near real-time sample preparation for salt removal; and real-time online mass spectrometry. When compared against the benchmark of “in-culture” experiments combined with ultraperformance liquid chromatography-electrospray ionization-ion mobility-mass spectrometry (UPLC-ESI-IM-MS), our platform alleviates the volume challenge issues caused by dilution of autocrine and paracrine signaling and dramatically reduces sample preparation and data collection time, while reducing undesirable external influence from various manual methods of manipulating cells and media (e.g., cell centrifugation). To validate this system biologically, we focused on cellular responses of Jurkat T cells to microenvironmental stimuli. Application of these stimuli, in conjunction with the cell’s metabolic processes, results in changes in consumption of nutrients and secretion of biomolecules (collectively, the exometabolome), which enable communication with other cells or tissues and elimination of waste. Naïve and experienced T-cell metabolism of cocaine is used as an exemplary system to confirm the platform’s capability, highlight its potential for metabolite discovery applications, and explore immunological memory of T-cell drug exposure. Our platform proved capable of detecting metabolomic variations between naïve and experienced Jurkat T cells and highlights the dynamics of the exometabolome over time. Upregulation of the cocaine metabolite, benzoylecgonine, was noted in experienced T cells, indicating potential cellular memory of cocaine exposure. These metabolomics distinctions were absent from the analogous, traditional “in-culture” UPLC-ESI-IM-MS experiment, further demonstrating this platform’s capabilities.

为破解作为生物复杂性核心根基的海量信号分子与代谢物追踪难题，我们提出一种可拓展动态系统生物学分析技术的研究策略。本研究借助微流控（microfluidics）、在线脱盐与质谱（mass spectrometry）技术，构建并验证了一款可实现高时间分辨率细胞微环境采样的平台。该平台可实现以下功能：自动化细胞刺激与微环境调控；通过表面钝化工艺减少聚二甲基硅氧烷（polydimethylsiloxane）表面的非特异性吸附；实时在线样本采集；用于脱盐的近实时样本前处理；以及实时在线质谱分析。相较于结合超高效液相色谱-电喷雾电离-离子迁移谱-质谱（UPLC-ESI-IM-MS）的传统「培养中」对照实验，本平台可缓解因自分泌与旁分泌信号稀释引发的样本量难题，大幅缩短样本前处理与数据采集时长，同时减少各类手动操控细胞及培养基的操作（如细胞离心）所带来的非必要外界干扰。为从生物学层面验证该系统的有效性，我们以Jurkat T细胞对微环境刺激的应答为研究对象。施加这类刺激并结合细胞代谢过程，会引发营养物质消耗与生物分子分泌的变化——这类物质统称为胞外代谢组（exometabolome），其可介导细胞与其他细胞或组织间的通讯，并清除代谢废物。我们以可卡因作用下的初始型与致敏型T细胞代谢为范例体系，用以验证平台性能、凸显其在代谢物发现领域的应用潜力，并探究T细胞对药物暴露的免疫记忆特性。本平台可有效检测初始型与致敏型Jurkat T细胞间的代谢组差异，并清晰呈现胞外代谢组随时间的动态变化特征。致敏型T细胞中可卡因代谢物苯甲酰芽子碱（benzoylecgonine）的表达出现上调，这提示其可能存在可卡因暴露的细胞记忆效应。这类代谢组学差异在传统的同类「培养中」UPLC-ESI-IM-MS实验中并未被观测到，进一步印证了本平台的优异性能。