Mass spectrometry for monitoring and quality control of differentiation of pluripotent stem cells to lung progenitors using biostatistical models

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14310%2F23%3A00134279" target="_blank" >RIV/00216224:14310/23:00134279 - isvavai.cz</a>

Result on the web

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DOI - Digital Object Identifier

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Result language

angličtina

Original language name

Mass spectrometry for monitoring and quality control of differentiation of pluripotent stem cells to lung progenitors using biostatistical models

Original language description

With increasing demands on precise analyses of biological samples in complex biological matrices, there is also need to develop and optimize mass spectrometric (MS) methods. The whole cell MALDI TOF MS is already used in clinical microbiology and diagnostics. In recent years it has been introduced also to cell biology, immunology, and cancer biology. Recently we used the whole cell-MS to monitor cultures of stem cells and progenitors and elucidate phenotypic shifts in long-term cultures. Here we demonstrated precise tracking of differentiation trajectory of human embryonic stem cells (hESCs) to lung epithelial progenitors by whole cell MS coupled with biostatistical modelling. Human embryonic stem cells (hESCs) possess unlimited differentiation potential and capacity to self-renew indefinitely. The hESC-derived, expandable lung epithelia (ELEP) used in this study were recently established in our lab to address histogenesis and regeneration of functional lung cell types. Differentiation of hESCs towards ELEPs is a complex process that shows substantial heterogeneity and can also produce aberrant cells with unwanted properties, such as lack of functional phenotype, or propensity to cancer growth. The differentiation process can be outlined specifically by molecular markers, but an unbiased, sensitive, and robust tool for the discrimination of ELEPs from pluripotent or transitional stages is still missing. In this work, we optimized the whole cell MS for lipid analysis, and coupled it with the multivariate statistical methods and supervised methods based on machine learning to follow differentiation of hESCs to ELEPs. We visualized the full differentiation trajectory based on spectral data only and revealed also some phenotypic abnormalities linked to passage number, and by proxy aneuploidy status of hESCs. Various extraction methods were tested to monitor changes in cellular lipids during the differentiation process. Finally, Folch´s method using chloroform/methanol/water has been selected and followed through this work. Sinapinic acid and 9-Aminoacridine matrix were used for MS measurement. MS measurements were combined with in-house developed R scripts. Data obtained from mass spectra were analyzed via several methods including principal component analysis (PCA), heatmap, and boxplots. Data were also analyzed by supervised methods (decision tree, random forest, and artificial neural networks). Mass spectra at various differentiation stages revealed different spectral fingerprints which allowed for successful classification in mathematical space using PCA and others. In summary, whole cell-MS is a promising tool for complex cultures of hESC-derived lung cells and progenitors, with potential clinical translation. Supported by the Grant Agency of Czech Republic (GA23-06675S) and by Masaryk University (MUNI/A/1298/2022, MUNI/A/1301/2022, and MUNI/11/ACC/3/2022).

Czech name

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Czech description

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Type

O - Miscellaneous

CEP classification

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OECD FORD branch

30402 - Technologies involving the manipulation of cells, tissues, organs or the whole organism (assisted reproduction)

Project

<a href="/en/project/GA23-06675S" target="_blank" >GA23-06675S: Pulmonary stress and regeneration</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2023

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů