6 research outputs found
Real-time analysis of endogenous Wnt signalling in 3D mesenchymal stromal cells
Wnt signalling has been implicated in the regulation of stem cell self-renewal and differentiation; however, the majority of in vitro studies are carried out using monolayer 2D culture techniques. Here, we used mesenchymal stromal cell (MSC) EGFP reporter lines responsive to Wnt pathway activation in a 3D spheroid culture system to mimic better the in vivo environment. Endogenous Wnt signalling was then investigated under basal conditions and when MSCs were induced to undergo osteogenic and adipogenic differentiation. Interestingly, endogenous Wnt signalling was only active during 3D differentiation whereas 2D cultures showed no EGFP expression throughout an extended differentiation time-course. Furthermore, exogenous Wnt signalling in 3D adipogenic conditions inhibited differentiation compared to unstimulated controls. In addition, suppressing Wnt signalling by Dkk-1 restored and facilitated adipogenic differentiation in MSC spheroids. Our findings indicate that endogenous Wnt signalling is active and can be tracked in 3D MSC cultures where it may act as a molecular switch in adipogenesis. The identification of the signalling pathways that regulate MSCs in a 3D in vivo-like environment will advance our understanding of the molecular mechanisms that control MSC fate
Building a Systematic Online Living Evidence Summary of COVID-19 Research
Throughout the global coronavirus pandemic, we have seen an unprecedented volume of COVID-19 researchpublications. This vast body of evidence continues to grow, making it difficult for research users to keep up with the pace of evolving research findings. To enable the synthesis of this evidence for timely use by researchers, policymakers, and other stakeholders, we developed an automated workflow to collect, categorise, and visualise the evidence from primary COVID-19 research studies. We trained a crowd of volunteer reviewers to annotate studies by relevance to COVID-19, study objectives, and methodological approaches. Using these human decisions, we are training machine learning classifiers and applying text-mining tools to continually categorise the findings and evaluate the quality of COVID-19 evidence
Development of in vitro skeletal disease models using CRISPR/Cas9 genome editing in immortalised mesenchymal stem cells
The emergence of engineered nucleases for genome editing has allowed for greater understanding
of human biology in health and disease, particularly through combination with stem cells and
differentiation protocols. Mesenchymal stem cells (MSCs) are a multipotent adult stem cell able to
differentiate into osteoblasts, chondrocytes and adipocytes. Early mesoderm differentiation
pathways are relatively well understood, yet the understanding of how mesoderm transcription
factors drive post-natal differentiation is less well studied. Additionally, the impact of skeletal
disease on MSCs is often neglected in the furthering of our understanding of pathophysiology and
disease phenotypes. To this end, this PhD project aimed to use an immortalised MSC cell line (hTERT
MSCs) to develop a methodology suitable for the generation of genetically modified MSCs (GM
hTERT MSCs). Firstly, the effects of serum in in vitro cell culture was considered by reducing serum
in hTERT MSC culture. This demonstrated in the absence of a nutrient-rich environment hTERT
MSCs shift towards a lipid-based metabolism with a consequential increase in osteogenic
capabilities. The initial targets of CRISPR/Cas9 were Runx2 and Sox9, two critical transcription
factors in the onset of osteogenesis and chondrogenesis respectively. The methodology developed
used a fluorescent sorting strategy to maximise the possibility of generating GM-hTERT MSCs and
in this way, successful genome editing was demonstrated. Genome editing of Runx2 did not appear
to absolve osteogenic potential in the hTERT MSCs and targeting of Sox9 via the CRISPR/Cas9
technology demonstrated an apparent increase in adipogenesis. To demonstrate the disease
modelling capabilities of GM-hTERT MSCs, a human disease relevant mutation was created in the
FGFR3 gene mimicking the genotype of CATSHL syndrome resulting in a striking phenotype, where
cells showed a decreased differentiation ability but an increased proliferative and migratory
capacity. These data were developed further through the use of a 3D spheroid model allowing for
the study of differentiated MSCs, including GM hTERT-MSCs, in a more in vivo like setting. Together
these results demonstrate the potential for expanding our understanding of MSC biology in
physiologically relevant in vitro conditions
Building a Systematic Online Living Evidence Summary of COVID-19 Research
Throughout the global coronavirus pandemic, we have seen an unprecedented volume of COVID-19 researchpublications. This vast body of evidence continues to grow, making it difficult for research users to keep up with the pace of evolving research findings. To enable the synthesis of this evidence for timely use by researchers, policymakers, and other stakeholders, we developed an automated workflow to collect, categorise, and visualise the evidence from primary COVID-19 research studies. We trained a crowd of volunteer reviewers to annotate studies by relevance to COVID-19, study objectives, and methodological approaches. Using these human decisions, we are training machine learning classifiers and applying text-mining tools to continually categorise the findings and evaluate the quality of COVID-19 evidence