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

PLoS One

Aleš Hampl¹  Lukáš Kučera¹  Elisa Valletta²  Tiziana Pivetta²  Filippo Amato²  Josef Havel³  Lubomír Prokeš³  Petr Vaňhara⁴ 

[1] Department of Chemical and Geological Sciences, University of Cagliari, Monserrato (CA), Italy;Department of Chemistry, Faculty of Science, Masaryk University, Brno, Czech Republic;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

关键词: Mass spectra;    Artificial neural networks;    Cell cultures;    Embryonic stem cells;    Matrix-assisted laser desorption ionization time-of-flight mass spectrometry;    Stem cell lines;    Fibroblasts;    Matrix-assisted laser desorption ionization mass spectrometry;   

DOI  :  10.1371/journal.pone.0147414

学科分类：医学（综合）

来源: Public Library of Science

【 摘 要 】

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.

【 授权许可】

CC BY