Molecular component distribution imaging of living cells by multivariate curve resolution analysis of space-resolved Raman spectra

Masahiro Ando,Hiro-O Hamaguchi

doi:10.1117/1.jbo.19.1.011016

Abstract

Label-free Raman microspectroscopy combined with a multivariate curve resolution (MCR) analysis can be a powerful tool for studying a wide range of biomedical molecular systems. The MCR with the alternating least squares (MCR-ALS) technique, which retrieves the pure component spectra from complicatedly overlapped spectra, has been successfully applied to in vivo and molecular-level analysis of living cells. The principles of the MCR-ALS analysis are reviewed with a model system of titanium oxide crystal polymorphs, followed by two examples of in vivo Raman imaging studies of living yeast cells, fission yeast, and budding yeast. Due to the non-negative matrix factorization algorithm used in the MCR-ALS analysis, the spectral information derived from this technique is just ready for physical and/or chemical interpretations. The corresponding concentration profiles provide the molecular component distribution images (MCDIs) that are vitally important for elucidating life at the molecular level, as stated by Schroedinger in his famous book, "What is life?" Without any a priori knowledge about spectral profiles, time- and space-resolved Raman measurements of a dividing fission yeast cell with the MCR-ALS elucidate the dynamic changes of major cellular components (lipids, proteins, and polysaccharides) during the cell cycle. The MCR-ALS technique also resolves broadly overlapped OH stretch Raman bands of water, clearly indicating the existence of organelle-specific water structures in a living budding yeast cell.

Highlights

Raman microspectroscopy, Raman spectroscopy under a microscope, is widely used in molecular-level investigations in various fields of bioscience and biotechnology.[1,2,3,4,5] It is well established as a strategic analytical tool in these fields
We have successfully applied the multivariate curve resolution (MCR)-ALS method to the analysis of molecular component distribution imaging (MCDI) in living cells, whose raw spectra contain a number of unknown spectral components and are hard to interpret without a priori information
Unlike other factorization methods such as singular value decomposition (SVD) and Principal component analysis (PCA), the MCR with the alternating least squares (MCR-ALS) does not require the orthogonality of each component but only requires their non-negativity

Summary

Introduction

Raman spectroscopy under a microscope, is widely used in molecular-level investigations in various fields of bioscience and biotechnology.[1,2,3,4,5] It is well established as a strategic analytical tool in these fields. In the MCR method, the experimental data is approximated by a linear combination of several spectral components.[51,52] The decomposition of superposed spectral data sets is done with ALS calculation, under appropriate model constraints, such as non-negativity of spectral profiles and their concentrations Due to these constraints, this method provides physically interpretable spectral components, without any a priori information on chemical components in the sample specimen such as a living cell. This method provides physically interpretable spectral components, without any a priori information on chemical components in the sample specimen such as a living cell Using this advantage, we have successfully applied the MCR-ALS method to the analysis of molecular component distribution imaging (MCDI) in living cells, whose raw spectra contain a number of unknown spectral components and are hard to interpret without a priori information. Important and otherwise unobtainable MCDI information has been obtained for the two living cell systems in vivo

Method

Example of TiO2 Crystal Polymorphs Discrimination

Analysis of Living Cells

Conclusion