Intact Cell Mass Spectrometry as a Quality Control Tool for Revealing Minute Phenotypic Changes of Cultured Human Embryonic Stem Cells

Pulsed laser ablation synthesis of fresh Te nanoparticles for matrix assisted laser desorption/ionization mass spectrometry (MALDI-MS) applications

This work aims to demonstrate the potential of pulsed laser ablation synthesis (PLA) of tellurium nanoparticles (Te NPs) for use in matrix assisted laser desorption/ionization mass spectrometry (MALDI-MS) applications. An experimental laboratory setup for PLA synthesis of fresh Te NPs was designed to prevent unwanted aggregation of uncoated Te NPs and avoid the need to use additional modifiers. Performing pulsed laser ablation synthesis in liquid (PLAL) using acetone was found to be the optimal way of preparing Te NPs. Another possibility is to use commercially available laser ablation devices for laser ablation - inductively coupled plasma mass spectrometry (LA-ICP-MS) to perform PLA in a helium atmosphere, but this approach is less efficient and results in the formation of unwanted larger particles. The prepared Te NPs were studied using the transmission electron microscopy (TEM) and dynamic light scattering (DLS) methods. TEM images showed the formation of Te NP nanochains composed of many crystallized Te NPs with sizes ranging from 8 to 15 nm. The various size distributions of the synthesized Te NPs identified using the DLS method correspond to the size distributions of aggregations rather than individual Te NPs. The synthesized Te NPs were used for a pilot study of their possible use with the MALDI-MS technique. An important effect was observed when Te NPs were used to perform a MALDI-MS analysis of the α-cyclodextrin (α-CD) and cucurbit[7]uril (CB7) macrocycles, which consisted in a decline in the formation of matrix adducts. Furthermore, several changes in MALDI-MS mass spectra of intact cells and a positive effect of Te NPs on the crystallization of the MALDI-MS matrix were observed.

Intact cell mass spectrometry coupled with machine learning reveals minute changes induced by single gene silencing

Intact (whole) cell MALDI TOF mass spectrometry is a commonly used tool in clinical microbiology for several decades. Recently it was introduced to analysis of eukaryotic cells, including cancer and stem cells. Besides targeted metabolomic and proteomic applications, the intact cell MALDI TOF mass spectrometry provides a sufficient sensitivity and specificity to discriminate cell types, isogenous cell lines or even the metabolic states. This makes the intact cell MALDI TOF mass spectrometry a promising tool for quality control in advanced cell cultures with a potential to reveal batch-to-batch variation, aberrant clones, or unwanted shifts in cell phenotype. However, cellular alterations induced by change in expression of a single gene has not been addressed by intact cell mass spectrometry yet. In this work we used a well-characterized human ovarian cancer cell line SKOV3 with silenced expression of a tumor suppressor candidate 3 gene (TUSC3). TUSC3 is involved in co-translational N-glycosylation of proteins with well-known global impact on cell phenotype. Altogether, this experimental design represents a highly suitable model for optimization of intact cell mass spectrometry and analysis of spectral data. Here we investigated five machine learning algorithms (k-nearest neighbors, decision tree, random forest, partial least squares discrimination, and artificial neural network) and optimized their performance either in pure populations or in two-component mixtures composed of cells with normal or silenced expression of TUSC3. All five algorithms reached accuracy over 90 % and were able to reveal even subtle changes in mass spectra corresponding to alterations of TUSC3 expression. In summary, we demonstrate that spectral fingerprints generated by intact cell MALDI-TOF mass spectrometry coupled to a machine learning classifier can reveal minute changes induced by alteration of a single gene, and therefore contribute to the portfolio of quality control applications in routine cell and tissue cultures.

A novel heteroleptic Cu(II)-phenanthroline-UDCA complex as lipoxygenase inhibitor and ER-stress inducer in cancer cell lines

A new heteroleptic copper(II) compound named C0-UDCA was prepared by reaction of [Cu(phen)₂(OH₂)](ClO₄)₂ (C0) with the bile ursodeoxycholic acid (UDCA). The resulting compound is able to inhibit the lipoxygenase enzyme showing more efficacy than the precursors C0 and UDCA. Molecular docking simulations clarified the interactions with the enzyme as due to allosteric modulation. The new complex shows antitumoral effect on ovarian (SKOV-3) and pancreatic (PANC-1) cancer cells at the Endoplasmic Reticulum (ER) level by activating the Unfolded Protein Response. In particular, the chaperone BiP, the pro-apoptotic protein CHOP and the transcription factor ATF6 are upregulated in the presence of C0-UDCA. The combination of Intact Cell MALDI-MS and statistical analysis have allowed us to discriminate between untreated and treated cells based on their mass spectrometry fingerprints.

Expandable Lung Epithelium Differentiated from Human Embryonic Stem Cells

BACKGROUND

The progenitors to lung airway epithelium that are capable of long-term propagation may represent an attractive source of cells for cell-based therapies, disease modeling, toxicity testing, and others. Principally, there are two main options for obtaining lung epithelial progenitors: (i) direct isolation of endogenous progenitors from human lungs and (ii) in vitro differentiation from some other cell type. The prime candidates for the second approach are pluripotent stem cells, which may provide autologous and/or allogeneic cell resource in clinically relevant quality and quantity.

METHODS

By exploiting the differentiation potential of human embryonic stem cells (hESC), here we derived expandable lung epithelium (ELEP) and established culture conditions for their long-term propagation (more than 6 months) in a monolayer culture without a need of 3D culture conditions and/or cell sorting steps, which minimizes potential variability of the outcome.

RESULTS

These hESC-derived ELEP express NK2 Homeobox 1 (NKX2.1), a marker of early lung epithelial lineage, display properties of cells in early stages of surfactant production and are able to differentiate to cells exhibitting molecular and morphological characteristics of both respiratory epithelium of airway and alveolar regions.

CONCLUSION

Expandable lung epithelium thus offer a stable, convenient, easily scalable and high-yielding cell source for applications in biomedicine.

Matrix enrichment by black phosphorus improves ionization and reproducibility of mass spectrometry of intact cells, peptides, and amino acids

Intact (whole) cell matrix-assisted laser desorption/ionization mass spectrometry (MALDI-TOF MS) is an established method for biotyping in clinical microbiology as well as for revealing phenotypic shifts in cultured eukaryotic cells. Intact cell MALDI-TOF MS has recently been introduced as a quality control tool for long-term cultures of pluripotent stem cells. Despite the potential this method holds for revealing minute changes in cells, there is still a need for improving the ionization efficiency or peak reproducibility. Here we report for the first time that supplementation by fine particles of black phosphorus to the standard MALDI matrices, such as sinapinic and α-cyano-4-hydroxycinnamic acids enhance intensities of mass spectra of particular amino acids and peptides, presumably by interactions with aromatic groups within the molecules. In addition, the particles of black phosphorus induce the formation of small and regularly dispersed crystals of sinapinic acid and α-cyano-4-hydroxycinnamic acid with the analyte on a steel MALDI target plate. Patterns of mass spectra recorded from intact cells using black phosphorus-enriched matrix were more reproducible and contained peaks of higher intensities when compared to matrix without black phosphorus supplementation. In summary, enrichment of common organic matrices by black phosphorus can improve discrimination data analysis by enhancing peak intensity and reproducibility of mass spectra acquired from intact cells.

Rapid discrimination of multiple myeloma patients by artificial neural networks coupled with mass spectrometry of peripheral blood plasma

Multiple myeloma (MM) is a highly heterogeneous disease of malignant plasma cells. Diagnosis and monitoring of MM patients is based on bone marrow biopsies and detection of abnormal immunoglobulin in serum and/or urine. However, biopsies have a single-site bias; thus, new diagnostic tests and early detection strategies are needed. Matrix-Assisted Laser Desorption/Ionization Time-of Flight Mass Spectrometry (MALDI-TOF MS) is a powerful method that found its applications in clinical diagnostics. Artificial intelligence approaches, such as Artificial Neural Networks (ANNs), can handle non-linear data and provide prediction and classification of variables in multidimensional datasets. In this study, we used MALDI-TOF MS to acquire low mass profiles of peripheral blood plasma obtained from MM patients and healthy donors. Informative patterns in mass spectra served as inputs for ANN that specifically predicted MM samples with high sensitivity (100%), specificity (95%) and accuracy (98%). Thus, mass spectrometry coupled with ANN can provide a minimally invasive approach for MM diagnostics.