Biology subjects

Taylor, V.

Publications and source records attributed to Taylor, V..

6 recordsLinked to original sources

bioRxiv2018

Notch2 signaling regulates Id4 and cell cycle genes to maintain neural stem cell quiescence in the adult hippocampus

Neural stem cells (NSCs) in the adult hippocampal dentate gyrus (DG) can be quiescent or proliferative, but how they are maintained is largely unknown. With age DG NSCs become increasingly dormant, which impinges on neuron generation. We addressed how NSC activity is controlled and found that Notch2 promotes quiescence by regulating their transition to the activated state. Notch2-ablation induces cell cycle genes and markers of active NSCs. Conversely, quiescent NSC-associated genes, including Id4, are down regulated after Notch2 deletion. We found that Notch2 binds the Id4 promoter and positively regulates transcription. Similar to Notch2, Id4 overexpression promotes DG NSC quiescence and Id4 knockdown rescues proliferation, even when Notch2 signaling is activated. We show that Notch2 regulates age-dependent DG NSC dormancy and Notch2 inhibition rejuvenates neurogenesis in the DG of aged mice. Our data indicate that a Notch2-Id4 axis promotes adult DG NSC quiescence and dormancy.

neuroscience↗

bioRxiv2018

Jagged1/Notch2 Controls Kidney Fibrosis via Tfam-mediated Metabolic Reprogramming

While Notch signaling has been proposed to play a key role in fibrosis, the direct molecular pathways targeted by Notch signaling and the precise ligand and receptor pair that are responsible for kidney disease remain poorly defined.\n\nIn this study, we found that JAG1 and NOTCH2 showed the strongest correlation with the degree of interstitial fibrosis in a genome wide expression analysis of a large cohort of human kidney samples. RNA sequencing analysis of kidneys of mice with folic acid nephropathy, unilateral ureteral obstruction, or APOL1-associated kidney disease indicated that Jag1 and Notch2 levels were higher in all analyzed kidney fibrosis models. Mice with tubule-specific deletion of Jag1 or Notch2 (Kspcre/Jag1flox/flox, and Kspcre/Notch2flox/flox) had no kidney-specific alterations at baseline, but showed protection from folic acid induced kidney fibrosis. Tubule-specific genetic deletion of Notch1 and global knock-out of Notch3 had no effect on fibrosis. In vitro chromatin immunoprecipitation experiments and genome-wide expression studies identified the mitochondrial transcription factor A (Tfam) as a direct Notch target. Re-expression of Tfam in tubule cells prevented Notch-induced metabolic and profibrotic reprogramming. Kidney tubule specific deletion of Tfam resulted in perinatal lethality.\n\nIn summary, Jag1/Notch2 plays a key role in kidney fibrosis development by regulating Tfam expression and metabolic reprogramming.

pathology↗

bioRxiv2017

Development of noninvasive biomarkers of response to proteasome inhibitor therapy (ixazomib) by imaging disrupted protein homeostasis in mouse models of solid tumors

With clinically-approved proteasome inhibitors now a standard of care for multiple myeloma, and increasing interest in their use in solid tumors, methods for monitoring therapeutic response in vivo are critically required. Here, we show that tumor protein homeostasis can be noninvasively monitored, using chemical exchange (CEST) magnetic resonance imaging (MRI) as a surrogate marker for proteasome inhibition, alongside diffusion MRI and relaxometry. We show that the in vivo CEST signal associated with amides and amines increases in proportion to proteasome inhibitor dose (ixazomib) and the magnitude of therapeutic effect in colorectal cancer xenografts. Moreover, we show that SW1222 and LS174T human colorectal cancer cell lines demonstrate differing sensitivities to ixazomib, which was reflected in our MRI measurements. We also found evidence of a mild stimulation in tumor growth at low ixazomib doses. Our results therefore identify CEST MRI as a promising method for safely and noninvasively monitoring changes in tumor protein homeostasis.

biophysics↗

bioRxiv2017

Deep learning diffusion fingerprinting to detect brain tumour response to chemotherapy

Artificial neural networks are being widely implemented for a range of different biomedical imaging applications.Convolutional neural networks are by far the most popular type of deep earning architecture,but often require very large datasets for robust training and evaluation We introduce deep learning diffusion fingerprinting (DLDF), which we have used to classifydiffusion-weighted magnetic resonance imaging voxels in a mouse model of glioblastoma (GL261 cell line), both prior to and in response to Temozolomide (TMZ) chemotherapy.We show that, even with limited training, DLDF can automatically segment brain tumours from normal brain, can automatically distinguish between young and older (after 9 days of growth) tumours and that DLDF can detect whether or not a tumour has been treated with chemotherapy.Our results also suggest that DLDF can detect localised changes in the underlying tumour microstructure, which are not evident using conventional measurements of the apparent diffusion coefficient (ADC).Tissue category maps generated by DLDF showed regions containing a mixture of normal brain and tumour cells, and in some cases evidence of tumour invasion across the corpus callosum, which were broadly consistent with histology.In conclusion, DLDF shows the potential for applying deep learning on a pixel-wise level,which reduces the need for vast training datasets and could easily be applied to other multi-dimensional imaging acquisitions\n\nAbbreviations

biophysics↗

bioRxiv2017

Quantitation of brain tumour microstructure response to Temozolomide therapy using non-invasive VERDICT MRI

There has been slow progress in the development of new therapeutic strategies for treating brain tumours, partly because assessment of treatment response is difficult and largely reliant on simple bi-dimensional measurements of MRI contrast-enhancing regions. Hence, there is a clinical need to develop improved imaging techniques for monitoring treatment response. In this study, we evaluate VERDICT (Vascular, Extracellular and Restricted Diffusion for Cytometry in Tumors) MRI in mouse glioblastomas for the quantification of tumour microstructure and assessment of response to Temozolomide (TMZ) chemotherapy, and, we investigate the feasibility of applying VERDICT MRI in a range of human gliomas. VERDICT MRI detected response to TMZ earlier than structural and apparent diffusion coefficient (ADC) measurements. A significant reduction in the cell radius parameter was detected three days earlier than ADC and six days earlier than structural MRI. Histological analysis showed the same trend as VERDICT of decreased intracellular volume fraction in the TMZ-treated mice. Vascular volume fraction was not altered by TMZ, which was consistent with optical projection tomography measurements. In patients, glioblastoma compartmental volume fractions showed good agreement with mouse glioblastoma parameters. The VERDICT parameters varied across the human gliomas, with raised intracellular volume fraction in the oligodendrogliomas and elevated cell radius in both low-grade tumours subtypes. In conclusion, our results suggest that VERDICT MRI is more sensitive at detecting TMZ response than structural or ADC measurements. In patients, VERDICT is feasible within clinical scan times, and performed best at characterising glioblastoma. Further optimisation should improve assessment of different glioma subtypes.

biophysics↗

bioRxiv2017

Universal Microfluidic System for Analysis and Control of Cell Dynamics

Dynamical control of the cellular microenvironment is highly desired for quantitative studies of stem cells and immune signaling. Here, we present an automated microfluidic system for high-throughput culture, differentiation and analysis of a wide range of cells in precisely defined dynamic microenvironments recapitulating cellular niches. This system delivers complex, time-varying biochemical signals to 1,500 independently programmable cultures containing either single cells, 2-D populations, or 3-D organoids, and dynamically stimulates adherent or non-adherent cells while tracking and retrieving them for end-point analysis. Using this system, we investigated the signaling landscape of neural stem cell differentiation under combinatorial and dynamic stimulation with growth factors. Experimental and computational analyses identified \"cellular logic rules\" for stem cell differentiation, and demonstrated the importance of signaling sequence and timing in brain development. This universal platform greatly enhances capabilities of microfluidic cell culture, allows dissection of previously hidden aspects of cellular dynamics, and enables accelerated biological discovery.

bioengineering↗