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Ulfenborg, B.

Publications and source records attributed to Ulfenborg, B..

3 recordsLinked to original sources

Defined human PSC culture conditions robustly maintain human PSC pluripotency through Ca2+ signaling.

Human pluripotent stem cells (hPSCs) have significant potential for disease modeling and cell therapies. However, their clinical applicability is limited due to the need for undefined conditions for PSC cultivation, which increase the risk of immunogenicity, result in batch-to-batch variability and finite scalability. These limitations may be circumvented by xeno-free, defined culture conditions. However, biological processes that preserve robust, homogenous PSCs in defined conditions remain to be characterized. Here, we compared gene expression data from over 100 hPSC cell lines cultivated in undefined and defined culture conditions. Defined culture conditions significantly reduced inter-PSC line variability, highlighting the importance of standardization to minimize PSC biases. This variability is concurrent with decreased germ layer differentiation and increased expression of Ca2+-binding proteins. The significance of tightly controlled Ca2+ signaling in hPSC pluripotency in defined culture conditions was also confirmed. A deeper understanding of these processes may aid in standardizing defined hPSC culture conditions. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=174 HEIGHT=200 SRC="FIGDIR/small/552440v1_ufig1.gif" ALT="Figure 1"> View larger version (61K): org.highwire.dtl.DTLVardef@1e5729aorg.highwire.dtl.DTLVardef@c6fa28org.highwire.dtl.DTLVardef@1515b91org.highwire.dtl.DTLVardef@52c6b6_HPS_FORMAT_FIGEXP M_FIG C_FIG In BriefEidhof et al. compared gene expression array data obtained from more than 100 hPSC cell lines to study the biological differences between PSCs cultivated under defined and undefined culture conditions. HighlightsO_LIDefined culture conditions reduce inter-hPSC line variability. C_LIO_LIDefined conditions decrease the expression of germ layer differentiation markers. C_LIO_LICa2+ signaling associated genes capture specific hPSC states in defined conditions. C_LIO_LIHigh Ca2+ activity drives pluripotency, low Ca2+ activity drives differentiation. C_LI

cell biology↗

Artificial intelligence supports automated characterization of differentiated human pluripotent stem cells

Revolutionary advances in AI and deep learning in recent years have resulted in an upsurge of papers exploring applications within the biomedical field. Within stem cell research, promising results have been reported from analyses of microscopy images to e.g., distinguish between pluripotent stem cells and differentiated cell types derived from stem cells. In this work, we investigated the possibility of using a deep learning model to predict the differentiation stage of pluripotent stem cells undergoing differentiation towards hepatocytes, based on morphological features of cell cultures. We were able to achieve close to perfect classification of images from early and late time points during differentiation, and this aligned very well with the experimental validation of cell identity and function. Our results suggest that deep learning models can distinguish between different cell morphologies, and provide alternative means of semi-automated functional characterization of stem cell cultures.

cell biology↗

Vertical and horizontal integration of multi-omics data with miodin

SummaryStudies on multiple modalities of omics data such as transcriptomics, genomics and proteomics are growing in popularity, since they allow us to investigate complex mechanisms across molecular layers. Integration of multi-omics data remains challenging and requires combination of several software tools to process data and generate biological insights. This paper presents miodin, a software package for streamlined data analysis and integration of omics data across experiments on the same samples, or across studies on the same variables.\n\nAvailability and implementationThe miodin package is implemented in R and is freely available for use and extension under the GPL-3 license. Package source, reference documentation and user manual are available at https://gitlab.com/algoromics/miodin.\n\nContactbenjamin.ulfenborg@his.se

bioinformatics↗