Biology subjects

Parker, P.

Publications and source records attributed to Parker, P..

3 recordsLinked to original sources

bioRxiv2022

PKN2 deficiency leads both to prenatal congenital cardiomyopathy and defective angiotensin II stress responses.

BackgroundThe protein kinase PKN2 is required for embryonic development, and PKN2 knockout mice die as a result of failure in expansion of mesoderm tissues, cardiac development and neural tube closure. In the adult, cardiomyocyte PKN2 and PKN1 (in combination) are required for cardiac adaptation to pressure-overload. The role of PKN2 in contractile cardiomyocytes during development and its role in the adult heart remain to be fully established. MethodsWe used mice with cardiomyocyte-directed knockout of PKN2 or global PKN2 haploinsufficiency. Cardiac function and dimensions were assessed with high resolution episcopic microscopy, MRI, micro-CT and echocardiography. Biochemical and histological changes were assessed. ResultsCardiomyocyte-directed PKN2 knockout embryos displayed striking abnormalities in the compact myocardium, with frequent myocardial clefts and diverticula, ventricular septal defects and abnormal heart shape. The sub-Mendelian homozygous knockout survivors developed cardiac failure. RNASeq data showed upregulation of PKN2 in patients with dilated cardiomyopathy, suggesting an involvement in adult heart disease. Given the rarity of homozygous survivors with cardiomyocyte-specific deletion of PKN2, this was explored using mice with constitutive heterozygous PKN2 knockout. Cardiac hypertrophy resulting from hypertension induced by angiotensin II was reduced in haploinsufficient PKN2 mice relative to wild-type littermates, with suppression of cardiomyocyte hypertrophy and cardiac fibrosis. ConclusionsCardiomyocyte PKN2 is essential for heart development and formation of compact myocardium, and is also required for cardiac hypertrophy in hypertension. Thus, PKN signalling may offer therapeutic options for managing congenital and adult heart diseases.

developmental biology↗

bioRxiv2022

Cell-specific regulation of gene expression using splicing-dependent frameshifting.

Precise and reliable cell-specific gene delivery remains technically challenging. Here we report a splicing-based approach for controlling gene expression whereby separate translational reading frames are coupled to the inclusion or exclusion of cell-specific alternative exons. Candidate exons are identified by analyzing thousands of publicly available RNA sequencing datasets and filtering by cell specificity, sequence conservation, and local intron length. This method, which we denote splicing-linked expression design (SLED), can be combined in a Boolean manner with existing techniques such as minipromoters and viral capsids. SLED vectors can leverage the strong expression of constitutive promoters, without sacrificing precision, by decoupling the tradeoff between promoter strength and selectivity. We generated SLED vectors to selectively target all neurons, photoreceptors, or excitatory neurons, and demonstrated that specificity was retained in vivo when delivered using AAVs. We further demonstrated the utility of SLED by creating what would otherwise be unobtainable research tools, specifically a GluA2 flip/flop reporter and a dual excitatory/inhibitory neuronal calcium indicator. Finally, we show the translational potential of SLED by rescuing photoreceptor degeneration in Prph2rds/rds mice and by developing an oncolytic vector that can selectively induce apoptosis in SF3B1 mutant cancer cells. The flexibility of SLED technology enables new avenues for basic and translational research.

molecular biology↗

bioRxiv2020

ImmunoCluster: A computational framework for the non-specialist to immune profile cellular heterogeneity using liquid and imaging mass, and flow cytometry datasets

High dimensional cytometry is an innovative tool for immune monitoring in health and disease, it has provided novel insight into the underlying biology as well as biomarkers for a variety of diseases. However, the analysis of multiparametric "big data" usually requires specialist computational knowledge. Here we describe ImmunoCluster (https://github.com/kordastilab/ImmunoCluster) an R package for immune profiling cellular heterogeneity in high dimensional liquid and imaging mass cytometry, and flow cytometry data, designed to facilitate computational analysis by a non-specialist. The analysis framework implemented within ImmunoCluster is readily scalable to millions of cells and provides a variety of visualization and analytical approaches, as well as a rich array of plotting tools that can be tailored to users needs. The protocol consists of three core computational stages: 1, data import and quality control, 2, dimensionality reduction and unsupervised clustering; and 3, annotation and differential testing, all contained within an R-based open-source framework.

systems biology↗