Applying secondary ion mass spectrometry to cellular and model membranes to image component distribution and quantify composition

Wilson, Robert

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https://hdl.handle.net/2142/42139 Copy

Description

Title

Applying secondary ion mass spectrometry to cellular and model membranes to image component distribution and quantify composition

Author(s)

Wilson, Robert

Issue Date

2013-02-03T19:16:57Z

Director of Research (if dissertation) or Advisor (if thesis)

Kraft, Mary L.

Doctoral Committee Chair(s)

Kraft, Mary L.

Committee Member(s)

• Bailey, Ryan C.
• Murphy, Catherine J.
• Suslick, Kenneth S.

Department of Study

Chemistry

Discipline

Chemistry

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

Ph.D.

Degree Level

Dissertation

Keyword(s)

• Time-of-flight Secondary ion mass spectrometry (TOF-SIMS)
• Lipid bilayers
• NanoSIMS
• Nanoparticle
• Surface analysis
• Multivariate analysis
• Partial least squares regression
• Spatial statistics
• Stem cells

Abstract

Abstract Secondary ion mass spectrometry (SIMS) returns chemically specific data on membrane component distribution and composition. Of particular interest is a membrane protein’s lipid environment, which may play a role in the protein’s function. Herein, this thesis describes the synthesis of fluorine-functionalized colloidal gold immunolabels that facilitate the imaging of specific proteins in parallel with stable isotope labeled lipids in the cellular membrane using high-resolution SIMS performed with a NanoSIMS. Further, the spatial statistical analysis tools are outlined and applied to NanoSIMS data to test the hypothesis of colocalization of the flu virus protein hemagglutinin and sphingolipids. While the NanoSIMS has very high lateral resolution, it requires isotope labels for component identification. Time-of-flight SIMS (TOF-SIMS) detects large portions of the mass spectrum, allowing species to be identified by their fragmentation pattern. Ionization yields in TOF-SIMS, however, limit the lateral resolution and the maximum m/z that can be used consistently for analysis. These challenges can be addressed using multivariate analysis (MVA). TOF-SIMS and the MVA method partial least squares discriminant analysis (PLS-DA) was used to identify the differentiation stage of hematopoietic cells. Since TOF-SIMS is a location-specific technique, it can be used to investigate how varying chemical and material environments on one sample affect stem cell fate decisions. Another MVA method, partial least squares regression (PLSR), uses a calibrated model to return quantitative information from TOF-SIMS data. This was used to determine the concentration of cholesterol in homogeneous supported lipid membranes.

Graduation Semester

2012-12

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http://hdl.handle.net/2142/42139

Copyright and License Information

Copyright 2012 Robert Wilson

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