Publication details

Multivariate Calibration Approach for Quantitative Determination of Cell-Line Cross Contamination by Intact Cell Mass Spectrometry and Artificial Neural Networks

Authors

VALLETTA Elisa KUČERA Lukáš PROKEŠ Lubomír AMATO Filippo PIVETTA Tiziana HAMPL Aleš HAVEL Josef VAŇHARA Petr

Year of publication 2016
Type Article in Periodical
Magazine / Source Plos One
MU Faculty or unit

Faculty of Medicine

Citation
Doi http://dx.doi.org/10.1371/journal.pone.0147414
Field Genetics and molecular biology
Keywords EMBRYONIC STEM-CELLS; LASER-DESORPTION/IONIZATION-TIME; LEAST-SQUARES REGRESSION; MALDI-TOF; EXPERIMENTAL-DESIGN; CANCER-DIAGNOSIS; MAMMALIAN-CELLS; CLASSIFICATION; SPECTRA; CULTURE
Description 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.
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