title: Multivariate Calibration Approach for Quantitative Determination of Cell-Line Cross Contamination by Intact Cell Mass Spectrometry and Artificial Neural Networks.
abstract: Cross-contamination of eukaryotic cell lines used in biomedical research represents a highly relevant problem. Analysis of repetitive DNA sequences, such as Short Tandem Repeats (STR), or Simple Sequence Repeats (SSR), is a widely accepted, simple, and commercially available technique to authenticate cell lines. However, it provides only qualitative information that depends on the extent of reference databases for interpretation. In this work, we developed and validated a rapid and routinely applicable method for evaluation of cell culture cross-contamination levels based on mass spectrometric fingerprints of intact mammalian cells coupled with artificial neural networks (ANNs). We used human embryonic stem cells (hESCs) contaminated by either mouse embryonic stem cells (mESCs) or mouse embryonic fibroblasts (MEFs) as a model. We determined the contamination level using a mass spectra database of known calibration mixtures that served as training input for an ANN. The ANN was then capable of correct quantification of the level of contamination of hESCs by mESCs or MEFs. We demonstrate that MS analysis, when linked to proper mathematical instruments, is a tangible tool for unraveling and quantifying heterogeneity in cell cultures. The analysis is applicable in routine scenarios for cell authentication and/or cell phenotyping in general.
authors.affiliation: Department of Chemistry, Faculty of Science, Masaryk University, Brno, Czech Republic.|Department of Chemical and Geological Sciences, University of Cagliari, Monserrato (CA), Italy.
authors.forename: Elisa
authors.initials: E
authors.lastname: Valletta
authors.affiliation: Department of Histology and Embryology, Faculty of Medicine, Masaryk University, Brno, Czech Republic.
authors.forename: Lukáš
authors.initials: L
authors.lastname: Kučera
authors.affiliation: Department of Chemistry, Faculty of Science, Masaryk University, Brno, Czech Republic.
authors.forename: Lubomír
authors.initials: L
authors.lastname: Prokeš
authors.affiliation: Department of Chemistry, Faculty of Science, Masaryk University, Brno, Czech Republic.
authors.forename: Filippo
authors.initials: F
authors.lastname: Amato
authors.affiliation: Department of Chemical and Geological Sciences, University of Cagliari, Monserrato (CA), Italy.
authors.forename: Tiziana
authors.initials: T
authors.lastname: Pivetta
authors.affiliation: Department of Histology and Embryology, Faculty of Medicine, Masaryk University, Brno, Czech Republic.|International Clinical Research Center, St. Anne's University Hospital Brno, Pekarska 53, 656 91, Brno, Czech Republic.
authors.forename: Aleš
authors.initials: A
authors.lastname: Hampl
authors.affiliation: Department of Chemistry, Faculty of Science, Masaryk University, Brno, Czech Republic.
authors.forename: Josef
authors.initials: J
authors.lastname: Havel
authors.affiliation: Department of Histology and Embryology, Faculty of Medicine, Masaryk University, Brno, Czech Republic.
authors.forename: Petr
authors.initials: P
authors.lastname: Vaňhara
mesh_terms: D000818:Animals; D002138:Calibration; D002460:Cell Line; D018920:Coculture Techniques; D000066449:Human Embryonic Stem Cells / Q000502:physiology; D006801:Humans; D013058:Mass Spectrometry / Q000379:methods*; D051379:Mice; D015999:Multivariate Analysis; D016571:Neural Networks, Computer; D025341:Principal Component Analysis; D013048:Specimen Handling
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