101
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Situ C, Mooney MH, Elliott CT, Buijs J. Advances in surface plasmon resonance biosensor technology towards high-throughput, food-safety analysis. Trends Analyt Chem 2010. [DOI: 10.1016/j.trac.2010.09.003] [Citation(s) in RCA: 134] [Impact Index Per Article: 8.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
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102
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Kastl KF, Lowe CR, Norman CE. Label-free genetic and proteomic marker detection within a single flowcell assay. Biosens Bioelectron 2010; 26:1719-22. [DOI: 10.1016/j.bios.2010.07.111] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2010] [Revised: 07/26/2010] [Accepted: 07/27/2010] [Indexed: 10/19/2022]
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103
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Szláma G, Kondás K, Trexler M, Patthy L. WFIKKN1 and WFIKKN2 bind growth factors TGFβ1, BMP2 and BMP4 but do not inhibit their signalling activity. FEBS J 2010; 277:5040-50. [PMID: 21054789 DOI: 10.1111/j.1742-4658.2010.07909.x] [Citation(s) in RCA: 32] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Abstract
WFIKKN1 and WFIKKN2 are large extracellular multidomain proteins consisting of a WAP domain, a follistatin domain, an immunoglobulin domain, two Kunitz-type protease inhibitor domains and an NTR domain. Recent experiments have shown that both proteins have high affinity for growth and differentiation factor (GDF)8 and GDF11. Here we study the interaction of WFIKKN proteins with several additional representatives of the transforming growth factor (TGF)β family using SPR measurements. Analyses of SPR sensorgrams suggested that, in addition to GDF8 and GDF11, both WFIKKN proteins bind TGFβ1, bone morphogenetic protein (BMP)2 and BMP4 with relatively high affinity (K(d) ∼ 10(-6) m). To assess the biological significance of these interactions we studied the effect of WFIKKN proteins on the activity of GDF8, GDF11, TGFβ1, BMP2 and BMP4 using reporter assays. These studies revealed that WFIKKN1 and WFIKKN2 inhibited the biological activity of GDF8 and GDF11 in the nanomolar range, whereas they did not inhibit the activities of TGFβ1, BMP2 and BMP4 even in the micromolar range. Our data indicate that WFIKKN proteins are antagonists of GDF8 and GDF11, but in the case of TGFβ1, BMP2 and BMP4 they function as growth factor binding proteins. It is suggested that the physical association of WFIKKN proteins with these growth factors may localize their action and thus help to establish growth factor gradients in the extracellular space.
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104
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Wilson JL, Scott IM, McMurry JL. Optical biosensing: Kinetics of protein A-IGG binding using biolayer interferometry. BIOCHEMISTRY AND MOLECULAR BIOLOGY EDUCATION : A BIMONTHLY PUBLICATION OF THE INTERNATIONAL UNION OF BIOCHEMISTRY AND MOLECULAR BIOLOGY 2010; 38:400-7. [PMID: 21567869 DOI: 10.1002/bmb.20442] [Citation(s) in RCA: 24] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/02/2023]
Abstract
An undergraduate biochemistry laboratory experiment has been developed using biolayer interferometry (BLI), an optical biosensing technique similar to surface plasmon resonance (SPR), in which students obtain and analyze kinetic data for a protein-protein interaction. Optical biosensing is a technique of choice to determine kinetic and affinity constants for biomolecular interactions. Measurements can be made in real-time without labels, making biosensing particularly appropriate for the teaching laboratory. In the described exercise, students investigate the kinetics of Protein A-human Immunoglobin G binding under conditions that mimic simple 1:1 binding. Students prepare appropriate serial dilutions of IgG and set up a microplate for the experiment by aliquotting biotinylated Protein A, buffer, and IgG solutions. A commercial BLI sensor, the FortéBio Octet QK, is used to measure binding. While data are collected students prepare a spreadsheet with which they will simulate the data to determine k(on) , k(off) , and K(D) . Raw data from the sensor are then exported to the spreadsheets for analysis. Optimized experiment timing, regeneration methods and other parameters are described to increase throughput and reduce cost. The experiment is readily adaptable to other biosensing platforms such as SPR instruments.
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Affiliation(s)
- Jo Leanna Wilson
- Department of Chemistry and Biochemistry, Kennesaw State University, Kennesaw, Georgia 30144, USA
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105
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Linman MJ, Abbas A, Cheng Q. Interface design and multiplexed analysis with surface plasmon resonance (SPR) spectroscopy and SPR imaging. Analyst 2010; 135:2759-67. [PMID: 20830330 PMCID: PMC7365140 DOI: 10.1039/c0an00466a] [Citation(s) in RCA: 48] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
Ever since the advent of surface plasmon resonance (SPR) and SPR imaging (SPRi) in the early 1990s, their use in biomolecular interaction analysis (BIA) has expanded phenomenally. An important research area in SPR sensor development is the design of novel and effective interfaces that allow for the probing of a variety of chemical and biological interactions in a highly selective and sensitive manner. A well-designed and robust interface is a necessity to obtain both accurate and pertinent biological information. This review covers the recent research efforts in this area with a specific focus towards biointerfaces, new materials for SPR biosensing, and novel array designs for SPR imaging. Perspectives on the challenges ahead and next steps for SPR technology are discussed.
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Affiliation(s)
- Matthew J. Linman
- Department of Chemistry, University of California, Riverside, California 92521
| | - Abdennour Abbas
- Department of Chemistry, University of California, Riverside, California 92521
| | - Quan Cheng
- Department of Chemistry, University of California, Riverside, California 92521
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106
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Singhal A, Haynes CA, Hansen CL. Microfluidic Measurement of Antibody−Antigen Binding Kinetics from Low-Abundance Samples and Single Cells. Anal Chem 2010; 82:8671-9. [DOI: 10.1021/ac101956e] [Citation(s) in RCA: 48] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Affiliation(s)
- Anupam Singhal
- Department of Chemical and Biological Engineering, University of British Columbia, 2360 East Mall; Vancouver, British Columbia, Canada V6T 1Z3, Michael Smith Laboratories, University of British Columbia, 2185 East Mall #301, Vancouver, British Columbia, Canada V6T 1Z4, Department of Physics and Astronomy, University of British Columbia, 6224 Agricultural Road, Vancouver, British Columbia, Canada V6T 1Z1, and Centre for High-Throughput Biology, University of British Columbia, 2125 East Mall, Vancouver,
| | - Charles A. Haynes
- Department of Chemical and Biological Engineering, University of British Columbia, 2360 East Mall; Vancouver, British Columbia, Canada V6T 1Z3, Michael Smith Laboratories, University of British Columbia, 2185 East Mall #301, Vancouver, British Columbia, Canada V6T 1Z4, Department of Physics and Astronomy, University of British Columbia, 6224 Agricultural Road, Vancouver, British Columbia, Canada V6T 1Z1, and Centre for High-Throughput Biology, University of British Columbia, 2125 East Mall, Vancouver,
| | - Carl L. Hansen
- Department of Chemical and Biological Engineering, University of British Columbia, 2360 East Mall; Vancouver, British Columbia, Canada V6T 1Z3, Michael Smith Laboratories, University of British Columbia, 2185 East Mall #301, Vancouver, British Columbia, Canada V6T 1Z4, Department of Physics and Astronomy, University of British Columbia, 6224 Agricultural Road, Vancouver, British Columbia, Canada V6T 1Z1, and Centre for High-Throughput Biology, University of British Columbia, 2125 East Mall, Vancouver,
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107
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Reis CR, van Assen AHG, Quax WJ, Cool RH. Unraveling the binding mechanism of trivalent tumor necrosis factor ligands and their receptors. Mol Cell Proteomics 2010; 10:M110.002808. [PMID: 20852190 DOI: 10.1074/mcp.m110.002808] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
Characterization of the binding of a tumor necrosis factor (TNF) ligand to its receptor(s) is pivotal to understand how these proteins initiate signal transduction pathways. Unfortunately, kinetic elucidation of these interactions is strongly hampered by the multivalent nature of the binding partners. The interaction between TNF-related apoptosis-inducing ligand and its death receptors was analyzed using in-depth applications of surface plasmon resonance technology. Variations in receptor density and sensor chip type allowed us to manipulate the stoichiometry of the formed complex, and the rate constants describing the binding of trimeric TNF-related apoptosis-inducing ligand to only one receptor molecule were determined. Remarkably, the affinity of this trimer-monomer complex is in the picomolar range, and its dissociation very slow. Further analysis showed that the second and third receptor molecules bind with lower affinity to the preformed trimer-monomer complex. This together with results obtained with receptor activator of NF-κB ligand and B cell-activating factor strongly suggests that the binding of TNF family ligands to their receptors is initiated via the formation of a trimer-monomer complex that is sufficiently stable to allow binding of two additional receptor molecules. These results suggest that avidity does not play a significant role and thus provide new insight in how TNF ligands form the biologically important complexes with their receptors.
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Affiliation(s)
- Carlos R Reis
- Department of Pharmaceutical Biology, University of Groningen, Antonius Deusinglaan 1, 9713 AV Groningen, The Netherlands
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108
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Kenny PW. Comment on: Rich and Myszka, grading the commercial optical biosensor literature--class of 2008: 'the mighty binders'. J. Mol. Recognit. 2010, 23, 1-64. J Mol Recognit 2010; 23:393; author reply 392. [PMID: 20549673 DOI: 10.1002/jmr.1045] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
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109
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Hearty S, Conroy PJ, Ayyar BV, Byrne B, O'Kennedy R. Surface plasmon resonance for vaccine design and efficacy studies: recent applications and future trends. Expert Rev Vaccines 2010; 9:645-64. [PMID: 20518719 DOI: 10.1586/erv.10.52] [Citation(s) in RCA: 30] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
The lack of a clear correlation between design and protection continues to present a barrier to progress in vaccine research. In this article, we outline how surface plasmon resonance (SPR) biosensors are emerging as tools to help resolve some of the key biophysical determinants of protection and, thereby, facilitate more rational vaccine design campaigns. SPR technology has contributed significantly to our understanding of the complex biophysical determinants of HIV neutralization and offers a platform for preclinical evaluation of vaccine candidates. In particular, the concept of reverse-engineering HIV vaccine targets based on known broadly neutralizing antibody modalities is explored and extended to include other infectious diseases, such as malaria and influenza, and other diseases such as cancer. The analytical capacity afforded by SPR includes serum screening to monitor immune responses and highly efficient quality-control surveillance measures. These are discussed alongside key technological advances, such as developments in sample throughput, and a perspective predicting continued growth and diversification of the role of SPR in vaccine development is proposed.
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Affiliation(s)
- Stephen Hearty
- Biomedical Diagnostics Institute, Dublin City University, Dublin 9, Ireland
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110
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Vorup-Jensen T. Coping with complexity (in macromolecular interactions)-a comment on Rebecca L. Rich's and David G. Myszka's “Grading the commercial optical biosensor literature-Class of 2008: ‘The Mighty Binders”’. J Mol Recognit 2010; 23:389-91; author reply 392. [DOI: 10.1002/jmr.1046] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
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111
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Rich RL, Myszka DG. Kinetic analysis and fragment screening with Fujifilm AP-3000. Anal Biochem 2010; 402:170-8. [PMID: 20371220 DOI: 10.1016/j.ab.2010.03.043] [Citation(s) in RCA: 12] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2010] [Revised: 03/30/2010] [Accepted: 03/31/2010] [Indexed: 12/26/2022]
Abstract
We evaluated the performance of Fujifilm's new AP-3000 surface plasmon resonance biosensor for kinetic analysis and fragment screening. Using carbonic anhydrase II as a model system, we characterized a set of 10 sulfonamide-based inhibitors that range in molecular mass from 98 to 341Da and approximately 10,000-fold in affinity (0.4mM to 20nM). Although the data collected from the AP-3000 were generally similar to those collected using a Biacore T100, the AP-3000's stop-flow analyte delivery system complicated the shapes of the association- and dissociation-phase binding responses. We illustrate how reasonable estimates of the kinetic rate constants can be extracted from AP-3000 data by limiting data analysis to only the regions of the responses collected during flow conditions. We also provide an example of the results obtained for a fragment-screening study with the AP-3000, which is the ideal application of this technology.
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Affiliation(s)
- Rebecca L Rich
- Center for Biomolecular Interaction Analysis, University of Utah School of Medicine, Salt Lake City, 84132, USA
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