Multiplexed evaluation of capture agent binding kinetics using arrays of silicon photonic microring resonators.

High affinity capture agents recognizing biomolecular targets are essential in the performance of many proteomic detection methods. Herein, we report the application of a label-free silicon photonic biomolecular analysis platform for simultaneously determining kinetic association and dissociation constants for two representative protein capture agents: a thrombin-binding DNA aptamer and an anti-thrombin monoclonal antibody. The scalability and inherent multiplexing capability of the technology make it an attractive platform for simultaneously evaluating the binding characteristics of multiple capture agents recognizing the same target antigen, and thus a tool complementary to emerging high-throughput capture agent generation strategies.

Efficient bioconjugation of protein capture agents to biosensor surfaces using aniline-catalyzed hydrazone ligation.

Aniline-catalyzed hydrazone ligation between surface-immobilized hydrazines and aldehyde-modified antibodies is shown to be an efficient method for attaching protein capture agents to model oxide-coated biosensor substrates. Silicon photonic microring resonators are used to directly evaluate the efficiency of this surface bioconjugate reaction at various pHs and in the presence or absence of aniline as a nucleophilic catalyst. It is found that aniline significantly increases the net antibody loading for surfaces functionalized over a pH range from 4.5 to 7.4, allowing derivatization of substrates with reduced incubation time and sample consumption. This increase in antibody loading directly results in more sensitive antigen detection when functionalized microrings are employed in a label-free immunoassay. Furthermore, these experiments also reveal an interesting pH-dependent noncovalent binding trend that plays an important role in dictating the amount of antibody attached onto the substrate, highlighting the competing contributions of the bioconjugate reaction rate and the dynamic interactions that control opportunities for a solution-phase biomolecule to react with a substrate-bound reagent.

Label-free technologies for quantitative multiparameter biological analysis.

In the postgenomic era, information is king and information-rich technologies are critically important drivers in both fundamental biology and medicine. It is now known that single-parameter measurements provide only limited detail and that quantitation of multiple biomolecular signatures can more fully illuminate complex biological function. Label-free technologies have recently attracted significant interest for sensitive and quantitative multiparameter analysis of biological systems. There are several different classes of label-free sensors that are currently being developed both in academia and in industry. In this critical review, we highlight, compare, and contrast some of the more promising approaches. We describe the fundamental principles of these different methods and discuss advantages and disadvantages that might potentially help one in selecting the appropriate technology for a given bioanalytical application.

Comparison of proteome between hepatitis B virus- and hepatitis C virus-associated hepatocellular carcinoma.

PURPOSE: Hepatocellular carcinoma (HCC) is one of the most common malignant cancers closely associated with chronic infection by the hepatitis B virus (HBV) or the hepatitis C virus (HCV) throughout the world. Differential expression of the proteome in HBV- and HCV-associated HCC was investigated to identify any useful biomarkers indicating virus-specific hepatocarcinogenesis. EXPERIMENTAL DESIGN: Twenty-one pairs of specimens (tumorous and surrounding nontumorous liver tissues) were obtained from 21 HCC patients. They were divided into three HCC types by viral markers: 7 hepatitis B surface antigen-positive (B-type HCC), 7 anti-HCV-positive (C-type HCC), and 7 hepatitis B surface antigen-negative and anti-HCV-negative. Total proteins were analyzed by two-dimensional gel electrophoresis and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry, and alterations in the proteome were examined. RESULTS: Sixty proteins were identified that show significant changes in the expression level between nontumorous and tumorous tissues. Among these, 14 proteins were commonly changed in all three of the HCC types, but 46 proteins showed a tendency of viral marker specificity. CONCLUSIONS: The identified proteins were classified according to the viral factor as being involved in B-type and C-type HCC. These results suggest strongly that the expression pattern of proteome in HCC tissues is closely associated with etiologic factors. The different protein profiles between B-type and C-type HCC indicate that the pathogenetic mechanisms of hepatocarcinogenesis may be different according to the viral factor, HBV and HCV.