Micro sequential injection: automated insulin derivatization and separation using a lab-on-valve capillary...

Area of Science:

• Analytical Chemistry
• Biochemistry
• Biomedical Engineering

Background:

• Accurate quantification of islet proteins like insulin is crucial for diabetes research and diagnostics.
• Traditional methods for protein analysis can be time-consuming and require complex sample preparation.
• Advancements in microfluidic systems offer potential for more efficient and automated bioanalytical workflows.

Purpose of the Study:

• To develop and validate a fully integrated lab-on-valve capillary electrophoresis (LOV-CE) system for automated analysis of islet proteins.
• To optimize microfluidic tasks including sampling, fluorogenic labeling, and capillary rejuvenation for enhanced reproducibility.
• To assess the system's performance for in vitro insulin assays using biological samples.

Main Methods:

• A novel lab-on-valve (LOV) manifold integrated with capillary electrophoresis (CE) was employed for automated sample handling and analysis.
• Micro sequential injection was utilized for precise control over sampling, fluorogenic derivatization, and CE capillary rejuvenation.
• Simultaneous absorbance and fluorescence detection were achieved using a customized capillary positioning plate with fiber optic probes.
• Software control facilitated automated optimization of derivatization conditions and iterative experimental execution.

Main Results:

• The LOV-CE system demonstrated high reproducibility for fluorogenic labeling of insulin, with low relative standard deviations (RSD) for peak area (1.3%), electromigration time (0.5%), and peak height (2.8%).
• Excellent linearity was observed for fluorescence detection across a wide dynamic range for insulin (r² = 0.99999), proinsulin (r² = 0.99195), and c-peptide (r² = 0.99983).
• Hydrodynamic flushing post-analysis increased sampling frequency, and the system successfully performed an in vitro insulin assay using rat pancreatic islet excretions.

Conclusions:

• The developed LOV-CE system provides a reliable and automated platform for the sensitive and reproducible analysis of key islet proteins.
• The integration of microfluidic tasks and simultaneous detection capabilities significantly enhances analytical throughput and utility.
• This automated system holds promise for advancing diabetes research and clinical diagnostics through efficient islet protein quantification.