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Title

Assessment of tissue-specific multifactor effects in environmental –omics studies of heterogeneous biological samples: Combining hyperspectral image information and chemometrics

AuthorsOlmos, Víctor; Marro, Mónica; Loza-Alvarez, Pablo; Raldúa, Demetrio; Prats, Eva; Piña, Benjamin; Tauler, Romà; De Juan, Anna
KeywordsANOVA-Simultaneous Component Analysis (ASCA)
Environmental –omics
Hyperspectral imaging
Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS)
Raman spectroscopy
Issue Date1-Mar-2019
PublisherElsevier
CitationTalanta - the International Journal of Pure and Applied Analyt Chemistry 194: 390-398 (2019)
AbstractThe use of hyperspectral imaging techniques in biological studies has increased in the recent years. Hyperspectral images (HSI) provide chemical information and preserve the morphology and original structure of heterogeneous biological samples, which can be potentially useful in environmental –omics studies when effects due to several factors, e.g., contaminant exposure, phenotype,… at a specific tissue level need to be investigated. Yet, no available strategies exist to exploit adequately this kind of information. This work offers a novel chemometric strategy to pass from the raw image information to useful knowledge in terms of statistical assessment of the multifactor effects of interest in –omic studies. To do so, unmixing of the hyperspectral image measurement is carried out to provide tissue-specific information. Afterwards, several specific ANOVA-Simultaneous Component Analysis (ASCA) models are generated to properly assess and interpret the diverse effect of the factors of interest on the spectral fingerprints of the different tissues characterized. The unmixing step is performed by Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS) on multisets of biological images related to each studied condition and provides reliable HSI spectral signatures and related image maps for each specific tissue in the regions imaged. The variability associated with these signatures within a population is obtained through an MCR-based resampling step on representative pixel subsets of the images analyzed. All spectral fingerprints obtained for a particular tissue in the different conditions studied are used to obtain the related ASCA model that will help to assess the significance of the factors studied on the tissue and, if relevant, to describe the associated fingerprint modifications. The potential of the approach is assessed in a real case of study linked to the investigation of the effect of exposure time to chlorpyrifos-oxon (CPO) on ocular tissues of different phenotypes of zebrafish larvae from Raman HSI of eye cryosections. The study allowed the characterization of melanin, crystalline and internal eye tissue and the phenotype, exposure time and the interaction of the two factors were found to be significant in the changes found in all kind of tissues. Factor-related changes in the spectral fingerprint were described and interpreted per each kind of tissue characterized. © 2018 Elsevier B.V.
Publisher version (URL)https://doi.org/10.1016/j.talanta.2018.10.029
URIhttp://hdl.handle.net/10261/177098
DOI10.1016/j.talanta.2018.10.029
Appears in Collections:(IDAEA) Artículos
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