Secondary ion mass spectrometry as a tool to evaluate chemical composition within model and cellular membranes

Anderton, Christopher R.

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https://hdl.handle.net/2142/24447 Copy

Description

Title

Secondary ion mass spectrometry as a tool to evaluate chemical composition within model and cellular membranes

Author(s)

Anderton, Christopher R.

Issue Date

2011-05-25T14:25:12Z

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

Kraft, Mary L.

Doctoral Committee Chair(s)

Kraft, Mary L.

Committee Member(s)

• Sweedler, Jonathan V.
• Granick, Steve
• Petrov, Ivan G.

Department of Study

Chemistry

Discipline

Chemistry

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

Ph.D.

Degree Level

Dissertation

Date of Ingest

2011-05-25T14:25:12Z

Keyword(s)

• Secondary Ion Mass Spectrometry
• Model Membranes
• Atomic Force Microscopy
• Principal Component Analysis

Abstract

Developing tools to elucidate the chemical distribution of lipid components within the eukaryotic cellular membrane is critical to understanding their role in many cell processes. Secondary ion mass spectrometry (SIMS) is a technique that offers both chemical and spatial specificity, and has become popularized over the last decade for analyzing model and native cellular membranes. Herein, this thesis describes the use and development of SIMS for such samples. By employing high-resolution SIMS, performed on a Cameca NanoSIMS 50, and atomic force microscopy (AFM) the influence of cholesterol on the phase behavior of supported lipid membranes containing saturated phosphatidylcholine lipid species was studied. While the NanoSIMS 50 afforded unprecedented lateral resolution on the chemical distribution of these model membranes, it was achieved at the cost of employing stable-isotope labels for component identification. Time-of-flight SIMS (TOF-SIMS), on the other hand, is a molecular imaging technique that does not require the use of labeled species. However, the ability to image characteristic lipid fragments (i.e. lipid headgroups, etc.) at lateral resolutions comparable to the NanoSIMS 50 is challenging. Furthermore, many of the characteristic fragments are common between structurally similar lipids, such as different phosphatidylcholine species, making discrimination between these species difficult. This challenge was overcome by developing a multivariate analysis (MVA) method, called principal component analysis (PCA), for evaluating the TOF-SIMS spectra of these samples. As a result, the ability to image and identify saturated phosphatidylcholine lipids that differ only in chain length within phase-separated membranes was achieved and could be registered to the corresponding AFM image. By performing PCA to compare TOF-SIMS spectra of labeled and unlabeled species, the molecular ion peaks that are associated with these phosphatidylcholine lipids were identified. These known ion peaks were then used to optimize PCA for TOF-SIMS imaging of phase-separated supported lipid membranes to attain a greater lateral characterization of these samples. The ability to gain quantitative information from TOF-SIMS analysis of homogenous supported lipid membranes was made possible by performing partial least squares regression (PLSR) on the resulting mass spectrum. Here, calibration samples were modeled, and then used to quantitatively predict the content of unknown membrane samples. Lastly, a TOF-SIMS MVA approach was utilized to evaluate native cellular membranes with the goals of differentiating between cell types, and in a separate project, identify the binding of vascular endothelial growth factors to human endothelial cells.

Graduation Semester

2011-05

Permalink

http://hdl.handle.net/2142/24447

Copyright and License Information

Copyright 2011 Christopher R. Anderton

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