Department of Chemistry, Colorado School of Mines, 1500 Illinois St., Golden, CO 80401, United States.
Renewable Resources and Enabling Sciences Center, National Renewable Energy Laboratory, Golden, CO 80401, United States.
J Chromatogr A. 2024 Nov 22;1737:465460. doi: 10.1016/j.chroma.2024.465460. Epub 2024 Oct 19.
Determining accurate counts and size distributions for biological particles (bioparticles) is crucial in wide-ranging fields, but current methods to this end are susceptible to bias from polydispersity in size. This bias can be mitigated by incorporating a separation step prior to characterization. For this reason, asymmetrical flow field-flow fractionation (AF4) with on-line multiangle light scattering (MALS) has become an important platform for determining particle size. AF4-MALS has also been increasingly used to report particle concentration, particularly for complex biological particles, yet the impact of light scattering models and particle refractive indices (RI) have not been quantitatively evaluated. Here, we develop an analysis workflow using AF4-MALS to simultaneously separate and determine particles sizes and concentrations. The impacts of the MALS particle counting model used to process data and the chosen RI value(s) on particle counts are systematically assessed for polystyrene latex (PSL) particles and bacterial outer membrane vesicles (OMVs) in the 20-500 nm size range. Across spherical models, PSL and OMV particle counts varied up to 13 % or 200 %, respectively. For the coated-sphere model used in the analysis of OMV samples, the sphere RI value greatly impacts particle counts. As the sphere RI value approaches the RI of the suspending medium, the model becomes increasingly sensitive to the light scattering signal-to-noise ratio ultimately causing erroneous particle counts. Overall, this work establishes the importance of selecting appropriate MALS models and RI values for bioparticles to obtain accurate counts and provides an AF4-MALS method to separate, enumerate, and size polydisperse bioparticles.
确定生物颗粒(bioparticles)的准确计数和粒径分布在广泛的领域中至关重要,但目前达到这一目的的方法容易受到粒径多分散性的偏差的影响。通过在表征之前引入分离步骤,可以减轻这种偏差。出于这个原因,不对称流场流分离(AF4)与在线多角度光散射(MALS)已成为确定粒径的重要平台。AF4-MALS 也越来越多地用于报告颗粒浓度,特别是对于复杂的生物颗粒,但光散射模型和颗粒折射率(RI)的影响尚未得到定量评估。在这里,我们开发了一种使用 AF4-MALS 同时分离和确定颗粒大小和浓度的分析工作流程。系统评估了用于处理数据的 MALS 颗粒计数模型和所选 RI 值(多个)对聚苯乙烯乳胶(PSL)颗粒和细菌外膜囊泡(OMV)在 20-500nm 尺寸范围内的颗粒计数的影响。在球形模型中,PSL 和 OMV 颗粒计数的变化高达 13%或 200%。对于用于分析 OMV 样品的涂覆球模型,球体 RI 值对颗粒计数有很大影响。随着球体 RI 值接近悬浮介质的 RI,该模型对光散射信号与噪声比变得越来越敏感,最终导致错误的颗粒计数。总的来说,这项工作确立了为了获得准确的计数,为生物颗粒选择适当的 MALS 模型和 RI 值的重要性,并提供了一种 AF4-MALS 方法来分离、计数和测量多分散生物颗粒的大小。