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Biology subjects

Swedlow, J.

Publications and source records attributed to Swedlow, J..

3 recordsLinked to original sources

A quantitative comparison of human embryonic and induced stem cell proteomes

Human induced pluripotent stem cells (hiPSCs) have great potential to be used as alternatives to embryonic stem cells (hESCs) in regenerative medicine and disease modelling, thereby avoiding many of the ethical issues arising from the use of embryo-derived cells. However, despite clear similarities between the two cell types, it is likely they are not identical. In this study, we characterise the proteomes of multiple hiPSC and hESC lines derived from independent donors. We find that while hESCs and hiPSCs express a near identical set of proteins, they show consistent quantitative differences in the expression levels of a wide subset of proteins. hiPSCs have increased total protein content, while maintaining a comparable cell cycle profile to hESCs. The proteomic data show hiPSCs have significantly increased abundance of vital cytoplasmic and mitochondrial proteins required to sustain high growth rates, including nutrient transporters and metabolic proteins, which correlated with phenotypic differences between hiPSCs and hESCs. Thus, higher levels of glutamine transporters correlated with increased glutamine uptake, while higher levels of proteins involved in lipid synthesis correlated with increased lipid droplet formation. Some of the biggest metabolic changes were seen in proteins involved in mitochondrial metabolism, with corresponding enhanced mitochondrial potential, shown experimentally using high-resolution respirometry. hiPSCs also produced higher levels of secreted proteins, including ECM components and growth factors, some with known tumorigenic properties, as well as proteins involved in the inhibition of the immune system. Our data indicate that reprogramming of human fibroblasts to iPSCs effectively restores protein expression in cell nuclei to a state comparable to hESCs, but does not similarly restore the profile of cytoplasmic and mitochondrial proteins, with consequences for cell phenotypes affecting growth and metabolism. The data improve understanding of the molecular differences between induced and embryonic stem cells, with implications for potential risks and benefits for their use in future disease modelling and therapeutic applications.

biochemistry↗

The Image Data Resource: A Scalable Platform for Biological Image Data Access, Integration, and Dissemination

Access to primary research data is vital for the advancement of science. To extend the data types supported by community repositories, we built a prototype Image Data Resource (IDR) that collects and integrates imaging data acquired across many different imaging modalities. IDR links high-content screening, super-resolution microscopy, time-lapse and digital pathology imaging experiments to public genetic or chemical databases, and to cell and tissue phenotypes expressed using controlled ontologies. Using this integration, IDR facilitates the analysis of gene networks and reveals functional interactions that are inaccessible to individual studies. To enable re-analysis, we also established a computational resource based on IPython notebooks that allows remote access to the entire IDR. IDR is also an open source platform that others can use to publish their own image data. Thus IDR provides both a novel on-line resource and a software infrastructure that promotes and extends publication and re-analysis of scientific image data.

bioinformatics↗

OME Files - An open source reference library for the OME-XML metadata model and the OME-TIFF file format

Digital imaging is now used throughout biological and biomedical research to measure the architecture, composition and dynamics of cells, tissues and organisms. The many different imaging technologies create data in many different formats. This diversity of data formats arises because the creation of common, cross-domain data standards is difficult and the pace of innovation challenges the durability of any defined standard and the implementation of data stewardship principles such as FAIR1. The Open Microscopy Environment (OME; http://openmicroscopy.org) has therefore developed the OME Data Model, an open, extensible specification for imaging metadata, that supports metadata related to an imaging experiment, data acquisition and any derived analytic results2-4. The OME Data Model has been implemented in OME-XML so that metadata can be stored and accessed by any sof ...

bioinformatics↗