Orthogonal projections to latent structures discriminant analysis modeling on in situ FT-IR spectral imaging of liver tissue for identifying sources of variability

Anal Chem. 2008 Sep 15;80(18):6898-906. doi: 10.1021/ac8005318. Epub 2008 Aug 20.

Abstract

In this study, the orthogonal projections to latent structures discriminant analysis (OPLS-DA) method was used to assess the in situ chemical composition of two different cell types in mouse liver samples, hepatocytes and erythrocytes. High spatial resolution FT-IR microspectroscopy equipped with a focal plan array (FPA) detector is capable of simultaneously recording over 4000 spectra from 64 x 64 pixels with a maximum spatial resolution of about 5 microm x 5 microm, which allows for the differentiation of individual cells. The main benefit with OPLS-DA lies in the ability to separate predictive variation (between cell type) from variation that is uncorrelated to cell type in order to facilitate understanding of different sources of variation. OPLS-DA was able to differentiate between chemical properties and physical properties (e.g., edge effects). OPLS-DA model interpretation of the chemical features that separated the two cell types clearly highlighted proteins and lipids/bile acids. The modeled variation that was uncorrelated to cell type made up a larger portion of the total variation and displayed strong variability in the amide I region. This could be traced back to a gradient in the high intensity (high-density) areas vs the low intensity areas (close to empty areas) that as a result of normalization had an adverse effect on FT-IR spectral profiles. This highlights that OPLS-DA provides an effective solution to identify different sources of variability, both predictive and uncorrelated, and also facilitates understanding of any sampling, experimental, or preprocessing issues.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Analysis of Variance
  • Animals
  • Discriminant Analysis
  • Erythrocytes / chemistry
  • Female
  • Hepatocytes / chemistry
  • Least-Squares Analysis
  • Liver / cytology*
  • Mice
  • Models, Biological
  • Principal Component Analysis
  • Spectroscopy, Fourier Transform Infrared