A new holistic exploratory approach to Systems Biology by Near Infrared Spectroscopy evaluated by chemometrics and data inspection

Abstract

AbstractThere is a need for an improved biological and theoretical interpretation of Near Infra‐Red Spectral (NIRS) fingerprints from tissues that could contribute with holistic overview to fine‐grained detail modelled in Systems Biology. The concept of gene expression in self‐organised networks was experimentally tested in a barley endosperm model with molecularly defined and undefined mutants. Surprisingly reproducible gene‐specific NIRS fingerprints were observed directly in log1/R MSC pre‐treated spectra that could not be accurately represented by destructive mathematical models. A mutant spectrum in an isogenic background represents the physiochemical expression of the gene in the whole network (tissue). The necessary holistic overview that is needed experimentally to introduce Ilya Prigogine's theory on self‐organisation in Systems Biology was supplied by defining the spectral phenome. Interval spectral information on genotypes and environment was classified by interval Extended Canonical Variates Analysis (iECVA). Genetic changes in spectra were interpreted by interval Partial Least Squares Regression (iPLSR) correlations to chemical variables. A new pathway regulation was detected. The finely grained ‘bottom up’ modelling of molecular and chemical data from pathways requires a coarsely grained exploratory ‘top down’ overview by NIRS to account for the outcome of self‐organisation. The amplification of expression from a gene to the phenome (pleiotropy) can now for the first time be quantified as a whole reproducible phenomenological pattern by NIRS and compared to other gene spectra. It explains published findings that transformed respectively mutated genes in genetically modified organisms (GMOs) and cancer patients can be detected unsupervised from tissues by spectroscopy, chemometrics and data inspection. Copyright © 2007 John Wiley & Sons, Ltd.