Development of "Imprint-and-Report" Dynamic Combinatorial Libraries for Differential Sensing Applications

Area of Science:

• Chemical sensing
• Analytical chemistry
• Biomolecular detection

Background:

• Sensor arrays are crucial for analyte detection via indicator displacement.
• Receptor synthesis and characterization are significant bottlenecks in sensor array development.
• Dynamic combinatorial libraries (DCLs) aid receptor discovery but are underutilized in complex arrays.

Purpose of the Study:

• To develop a high-throughput sensor array method that bypasses receptor synthesis and isolation.
• To leverage the inherent complexity of DCLs for enhanced analyte differentiation.
• To create a sensor array for distinguishing post-translational modifications (PTMs).

Main Methods:

• Utilized an "imprint-and-report" dynamic combinatorial library (DCL) strategy.
• Employed in situ fluorescent indicator displacement analysis after templating DCLs with analytes.
• Investigated both analyte-templated and reporter-templated DCLs for differential sensing.
• Applied the method to differentiate methylated arginine and lysine PTMs.

Main Results:

• Demonstrated a sensor array workflow that obviates the need for individual receptor synthesis.
• Showcased the "imprint-and-report" DCL strategy for high-throughput analyte differentiation.
• Achieved sensitive differentiation of 7 post-translational modifications using 19 combinations of DCL data sets.
• Validated the effectiveness of reporter-templated DCLs for enhanced sensitivity.

Conclusions:

• The "imprint-and-report" DCL approach offers a streamlined and efficient method for sensor array development.
• Leveraging differential library speciation within DCLs unlocks significant information for complex analyte detection.
• This strategy provides a powerful platform for sensitive and high-throughput analysis of challenging analytes like PTMs.