"Modeling Immuno-qPCR to Estimate Protein Quantity in a Biological Sample" Harrison Leong

Speaker:

Dr. Harrison Leong, Sr. Staff Engineer, Software, Thermo Fisher Scientific Inc. U.S.A.

Title:

Modeling Immuno-qPCR to Estimate Protein Quantity in a Biological Sample

Abstract:

Immuno-qPCR combines antibody techniques for identifying protein targets with quantitative polymerase chain reaction (qPCR) methods to provide a technology for quantifying a specific protein target in one biological sample relative to a reference sample.  Referred to as the proximity ligation assay (PLA), the assay has been observed to achieve 10,000x increase in sensitivity compared to the enzyme-linked immunosorbent assay (ELISA), the current standard for detecting and measuring targeted protein content.   An overview of PLA and qPCR will be given followed by a more detailed discussion of a mathematical model of the PLA reaction that can estimate protein quantity despite non-linear characteristics in the data that invalidate standard qPCR methods of analysis.  Though standard qPCR methods of analysis do not require calibration for a relative quantification, the model makes it clear that calibration is necessary in the case where the proteins of interest exhibit non-linear characteristics and suggests alternative calibration approaches.  Experiments have been devised and executed to generate data with “known” underlying relative protein quantities.  A calibration and quantification approach are cross-validated against these data.  Results suggest that the method can determine a difference in quantity of the targeted protein between an unknown and reference sample within a half log.

Host:

Prof. Eliot Fried, Mathematical Soft Matter Unit