Nanopore-based single-molecule detection has recently become established as a new tool in single molecule biophysics. Evidence is presented that single antibodies can be observed with a nanopore detector, which presents a wide range of possibilities for immunological research. The hypothesis to be tested is that nanopore-based detection can be used to study single molecule dynamics of antibody-antigen interaction and analyze conformational changes that occur in antibody upon binding to antigen. This application aims to develop the utility of the nanopore-based approach through improvements in both the detection device and the software used to extract information from the channel current signal. At the same time, these studies will allow the Candidate to gain expertise in immunology and the biophysical study of protein structure and function. To study the single molecule dynamics of antibody-antigen interaction, the following three specific aims are proposed: 1. Extend nanopore based detection to nanopore/antibody based detection. 2. Implement machine learning software for automated nanopore/antibody signal analysis and experimental feedback. 3. Use well-characterized, genetically engineered, antibodies to test the utility of the nanopore device to analyze motion in the antibody molecule. These studies will expand the utility of nanopore devices to study single molecule protein interactions. Information gained will lead to a better understanding of the molecular dynamics associated with antigen binding by antibody and the subsequent initiation of effector functions. Since most biological nanopore variants derive from pore-forming toxins, nanopore device enhancements eventually may lead to new methods for antibody and antimicrobial-peptide immunological screening. Antibody-based nanopore devices may also serve as highly sensitive immunosensors.

National Institute of Health (NIH)
National Library of Medicine (NLM)
Career Transition Award (K22)
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Special Emphasis Panel (ZLM1-HS-K (M3))
Program Officer
Ye, Jane
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Children's Hospital (New Orleans)
New Orleans
United States
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Eren, A Murat; Amin, Iftekhar; Alba, Amanda et al. (2010) Pattern recognition-informed feedback for nanopore detector cheminformatics. Adv Exp Med Biol 680:99-108
Churbanov, Alexander; Winters-Hilt, Stephen (2008) Clustering ionic flow blockade toggles with a mixture of HMMs. BMC Bioinformatics 9 Suppl 9:S13
Churbanov, Alexander; Winters-Hilt, Stephen; Koonin, Eugene V et al. (2008) Accumulation of GC donor splice signals in mammals. Biol Direct 3:30
Landry, Matthew; Winters-Hilt, Stephen (2007) Analysis of nanopore detector measurements using Machine-Learning methods, with application to single-molecule kinetic analysis. BMC Bioinformatics 8 Suppl 7:S12
Churbanov, Alexander; Baribault, Carl; Winters-Hilt, Stephen (2007) Duration learning for analysis of nanopore ionic current blockades. BMC Bioinformatics 8 Suppl 7:S14
Winters-Hilt, Stephen; Baribault, Carl (2007) A novel, fast, HMM-with-Duration implementation - for application with a new, pattern recognition informed, nanopore detector. BMC Bioinformatics 8 Suppl 7:S19
Winters-Hilt, Stephen; Morales, Eric; Amin, Iftekhar et al. (2007) Nanopore-based kinetics analysis of individual antibody-channel and antibody-antigen interactions. BMC Bioinformatics 8 Suppl 7:S20
Winters-Hilt, Stephen; Davis, Amanda; Amin, Iftekhar et al. (2007) Nanopore current transduction analysis of protein binding to non-terminal and terminal DNA regions: analysis of transcription factor binding, retroviral DNA terminus dynamics, and retroviral integrase-DNA binding. BMC Bioinformatics 8 Suppl 7:S10
Winters-Hilt, Stephen; Merat, Sam (2007) SVM clustering. BMC Bioinformatics 8 Suppl 7:S18
Thomson, Karen; Amin, Iftekhar; Morales, Eric et al. (2007) Preliminary nanopore cheminformatics analysis of aptamer-target binding strength. BMC Bioinformatics 8 Suppl 7:S11

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