Data in Support of Identifying and Minimizing Primary Sources of Temporal Broadening in Online Affinity Micro Free-Flow Electrophoresis

Loading...
Thumbnail Image
Statistics
View Statistics

Collection Period

2024-01-01
2025-03-07

Date Completed

2025-07-18

item.page.dateupdated

Time period coverage

Geographic coverage

Source information

Journal Title

Journal ISSN

Volume Title

Published Date

Author Contact

Bowser, Michael
bowser@umn.edu

Abstract

Affinity micro free-flow electrophoresis (µFFE) takes advantage of continuous separations to enable real-time measurements in biological systems. Here, competitive immunoassay reagents are mixed online and streamed into the µFFE device, where bound and free labeled species are separated in real-time based on their electrophoretic mobility. In the manuscript corresponding to this dataset, we optimized the affinity µFFE platform to minimize the response time of the assay. Analyte response time was improved by 1) mitigating temporal broadening as analyte transited the fluidic system and 2) reducing surface adsorption. Fast iteration of the microfluidic parameters enabled optimization of temporal broadening due to longitudinal diffusion and parabolic flow. Minimizing incubation capillary length while ensuring adequate equilibration time for the competitive immunoassay improved rise times from 25-seconds to 10-seconds, a 2.5-fold improvement in temporal response. Incorporation of immunoassay reagents hindered response time as a result of peptide surface adsorption. Dynamic coating with 0.005% w/v bovine serum albumin was shown to mitigate surface adsorption without interfering with the binding and separation of the immunoassay components, resulting in 2.8-fold improvement in overall signal and 2-fold improvement in temporal response, which improved from 61 seconds to 30 seconds. This data set includes raw and processed data supporting this publication, as well as MATLAB code used for data processing and figure generation.

Description

Data files include MATLAB code, raw data (.csv) and processed data (.csv). The matlab code is used to process all raw data files (matrices) for generation of figures and extraction of linescans or post-processing matrices for further analysis. Raw data files are included for any experiment shown in the manuscript. These are titled "FigX_raw...". Separate files with already-extracted linescans and peak-heigh-over-time traces are included for any data shown in manuscript. These are titled "FigX_Extracted...".

Referenced by

Burke, G. S., & Bowser, M. T. (2025). Identifying and minimizing primary sources of temporal broadening in online affinity micro free-flow electrophoresis. Analyst (London).
https://doi.org/10.1039/d5an00796h

Related to

item.page.isreplacedby

License

CC0 1.0 Universal
http://creativecommons.org/publicdomain/zero/1.0/

Publisher

Funding Information

This research was funded by the National Institutes of Health (GM145956)

item.page.sponsorshipfunderid

item.page.sponsorshipfundingagency

item.page.sponsorshipgrant

Previously Published Citation

Other identifiers

Suggested Citation

Burke, Gretchen; Bowser, Michael. (2025). Data in Support of Identifying and Minimizing Primary Sources of Temporal Broadening in Online Affinity Micro Free-Flow Electrophoresis. Retrieved from the Data Repository for the University of Minnesota (DRUM), https://doi.org/10.13020/x9kn-fn14.

Content distributed via the University Digital Conservancy may be subject to additional license and use restrictions applied by the depositor. By using these files, users agree to the Terms of Use. Materials in the UDC may contain content that is disturbing and/or harmful. For more information, please see our statement on harmful content in digital repositories.