Online Affinity Micro Free Flow Electrophoresis Assays for Continuous Monitoring of Biochemical Messengers

前提：靶标抗体等生物分子提供的选择性和亲和力的组合 配体使它们成为生物分析的理想识别元件。虽然这些亲和试剂使 开发了许多重要的生物测定，这些测量几乎总是作为静态分析来执行 在一个单独的时间点。亲和试剂的减速使响应性分析的发展 能够监测分析物浓度随时间的变化是一项挑战。试剂降解，非特定表面 相互作用和生物污损带来了额外的困难。我们的目标是发展一种在线的、流畅的、亲和力 一种可连续监测动态变化的生物化学信使外流的分析方法 实时的系统。我们的前提是微流控一体化的灌注室，在线混合的亲和力 试剂和连续微量自由流动电泳(µFFE)分离将直接解决以下限制 到目前为止，已经限制了基于时间反应亲和分析的发展。 创新：我们将使用微流控、流通式方法开发时间响应性亲和分析。这个 生物模型(即细胞培养)将被安置在灌注室中。Perusate将在网上与一个 选择性结合目标分析物的荧光标记亲和试剂(即抗体或适配子)。线上 然后使用µFFE将分析物-亲和试剂复合体与过量亲和试剂连续分离 实时的。在线亲和力µFFE具有多项优势。连续流消除了对以下方面的限制：关闭速度 时间反应。暴露在生物基质中是最小的，减缓了试剂的降解。信号是 在溶液中测量，限制了非特定表面相互作用和生物污垢的影响。µFFE分离 使分析物-亲和试剂复合体即使在亲和试剂 大量应用，提高了检测的精密度。 方法：将为来自三个生化部门的代表性分析物开发亲和力分析方法 信使系统：神经肽Y(NPY，神经传递)、瘦素(能量调节)和肿瘤坏死 因子α(肿瘤坏死因子-α，免疫反应)。将在使用抗体(AIM)的化验之间进行直接比较 #1)或适配子(目标#2)作为亲和剂。将用于评估分析性能的优值系数 包括：LOD、时间响应、最小可检测变化和长期稳定性。一旦完全优化， 亲和力分析将用于持续监测细胞模型的基线和刺激外排 用于神经传递(神经元)、能量调节(脂肪细胞)和免疫反应(肥大细胞)。 基准测试：我们预计亲和力uFFE将达到以下性能指标：LOD≤1 nm； 时间响应≤1 S；最小可检测变化≤5%；4小时内长期稳定性≤10%。 影响：时间响应µFFE分析将使研究人员能够研究≤1上发生的动态变化S 首次在几个关键的生化信使系统中进行了时间刻度。

Premise: The combination of selectivity and affinity afforded by biomolecules such as antibodies for their target ligands make them ideal recognition elements for bioassays. While these affinity reagents have enabled the development of many important bioassays, these measurements are almost always performed as static analyses at an individual time point. The slow off rates of affinity reagents makes development of responsive assays that can monitor changes in analyte concentration over time a challenge. Reagent degradation, non-specific surface interactions, and biofouling present additional difficulties. Our goal is to develop an online, flow-through, affinity assay that can continuously monitor the efflux of biochemical messengers from dynamically changing biological systems in real time. Our premise is that microfluidic integration of a perfusion chamber, online mixing of affinity reagents and continuous micro free flow electrophoresis (µFFE) separations will directly address limitations that have restricted the development of time responsive affinity-based assays to date. Innovation: We will use a microfluidic, flow through approach to develop time responsive affinity assays. The biological model (i.e., cell culture) will be housed in a perfusion chamber. Perfusate will be mixed online with a fluorescently labeled affinity reagent (i.e., antibody or aptamer) that selectively binds the target analyte. Online µFFE will then be used to continuously separate the analyte-affinity reagent complex from excess affinity reagent in real time. Online affinity µFFE offers several advantages. Continuous flow removes off rate as a limitation to temporal response. Exposure to the biological matrix is minimal, mitigating reagent degradation. Signal is measured in solution, limiting the effect of non-specific surface interactions and biofouling. µFFE separation enables interference free measurement of the analyte-affinity reagent complex even when the affinity reagent is applied in large excess, improving the LOD of the assay. Approach: Affinity µFFE assays will be developed for representative analytes from three biochemical messenger systems: neuropeptide Y (NPY, neurotransmission), leptin (energy regulation), and tumor necrosis factor α (TNF-α, immune response). Direct comparisons will be made between assays that use antibodies (Aim #1) or aptamers (Aim #2) as the affinity reagent. Figures of merit that will be used to assess assay performance include: LOD, temporal response, minimum detectable change, and long-term stability. Once fully optimized, affinity µFFE assays will be used to continuously monitor both baseline and stimulated efflux from cell models for neurotransmission (neurons), energy regulation (adipocytes) and immune response (mast cells). Benchmarks: We anticipate that affinity µFFE will achieve the following performance metrics: LOD ≤ 1nM; temporal response ≤ 1 s; minimum detectable change ≤ 5%; and long-term stability ≤ 10% over 4 h. Impact: Time responsive µFFE assays will allow researchers to study dynamic changes that occur on a ≤1 s timescale in several critical biochemical messenger systems for the first time.