Abstract
Determining accurate counts and size distributions for biological particles (bioparticles) is crucial in wide-ranging fields, but current ensemble 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 been 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 assessed. 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 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.
Supplementary materials
Title
Supporting Information
Description
AF4 method development using polystyrene latex, impacts of detector selection for polystyrene latex particles, table with literature dn/dc and RI values for OMV components, and detector number and corresponding angles for MALS instrumentation.
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