Monitoring protein distributions based on patterns generated by protein adsorption behavior in a microfluidic channel

Seokheun Choi, Shuai Huang, Jing Li, Junseok Chae

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

Abstract

We report a unique monitoring technique of protein distributions based on distinctive patterns generated by protein adsorption behavior on a solid surface in a microfluidic channel. Bare gold and COOH-modified self-assembled monolayer (SAM) sensing surfaces were pre-adsorbed with one of four different proteins: lysozyme, albumin, transferrin, or IgG. Each surface provides a thermodynamically governed platform for immobilizing proteins and generates analyte-specific response patterns. Each surface has its own thermodynamic energy governing pre-adsorbed protein behaviors, so that sample proteins react with the pre-adsorbed ones to different extents depending on their sizes, isoelectric points (pI), and characteristics of the sensing surfaces. Modified surfaces were mounted and monitored in real time using surface plasmon resonance (SPR). Buffer-prepared sample matrices (α1-antitrypsin, haptoglobin, C-reactive protein (CRP), and IgM) characterized protein response patterns. Each surface generated distinctive patterns based on individual SPR angle shifts. We classified each sample with 95% accuracy using linear discriminant analysis (LDA). Our method also discriminated between different concentrations of CRP in the cocktail sample, detecting concentrations as low as 1 nM with 91.7% accuracy. This technique may be integrated with a microfluidic lab-on-a-chip system and monitor the distribution of a specific group of proteins in human serum.

Original languageEnglish (US)
Pages (from-to)3681-3688
Number of pages8
JournalLab on a Chip
Volume11
Issue number21
DOIs
StatePublished - Nov 7 2011

ASJC Scopus subject areas

  • Bioengineering
  • Biochemistry
  • General Chemistry
  • Biomedical Engineering

Fingerprint

Dive into the research topics of 'Monitoring protein distributions based on patterns generated by protein adsorption behavior in a microfluidic channel'. Together they form a unique fingerprint.

Cite this