Nuclear Distributions of NUP62 and NUP214 Suggest Architectural Diversity and Spatial Patterning among Nuclear Pore Complexes

The shape of nuclei in many adherent cultured cells approximates an oblate ellipsoid, with contralateral flattened surfaces facing the culture plate or the medium. Observations of cultured cell nuclei from orthogonal perspectives revealed that nucleoporin p62 (NUP62) and nucleoporin 214 (NUP214) are differentially distributed between nuclear pore complexes on the flattened surfaces and peripheral rim of the nucleus. High resolution stimulated emission depletion (STED) immunofluorescence microscopy resolved individual NPCs, and suggested both heterogeneity and microheterogeneity in NUP62 and NUP214 immunolabeling among in NPC populations. Similar to nuclear domains and interphase chromosome territories, architectural diversity and spatial patterning of NPCs may be an intrinsic property of the nucleus that is linked to the functions and organization of underlying chromatin

Cdk Phosphorylation of a Nucleoporin Controls Localization of Active Genes through the Cell Cycle

The localization of active genes to the nuclear periphery is regulated through the cell cycle by Cdk1 phosphorylation of a single nuclear pore protein

Identification of novel risk loci, causal insights, and heritable risk for Parkinson's disease: a meta-analysis of genome-wide association studies

Background Genome-wide association studies (GWAS) in Parkinson's disease have increased the scope of biological knowledge about the disease over the past decade. We aimed to use the largest aggregate of GWAS data to identify novel risk loci and gain further insight into the causes of Parkinson's disease. Methods We did a meta-analysis of 17 datasets from Parkinson's disease GWAS available from European ancestry samples to nominate novel loci for disease risk. These datasets incorporated all available data. We then used these data to estimate heritable risk and develop predictive models of this heritability. We also used large gene expression and methylation resources to examine possible functional consequences as well as tissue, cell type, and biological pathway enrichments for the identified risk factors. Additionally, we examined shared genetic risk between Parkinson's disease and other phenotypes of interest via genetic correlations followed by Mendelian randomisation. Findings Between Oct 1, 2017, and Aug 9, 2018, we analysed 7·8 million single nucleotide polymorphisms in 37 688 cases, 18 618 UK Biobank proxy-cases (ie, individuals who do not have Parkinson's disease but have a first degree relative that does), and 1·4 million controls. We identified 90 independent genome-wide significant risk signals across 78 genomic regions, including 38 novel independent risk signals in 37 loci. These 90 variants explained 16–36% of the heritable risk of Parkinson's disease depending on prevalence. Integrating methylation and expression data within a Mendelian randomisation framework identified putatively associated genes at 70 risk signals underlying GWAS loci for follow-up functional studies. Tissue-specific expression enrichment analyses suggested Parkinson's disease loci were heavily brain-enriched, with specific neuronal cell types being implicated from single cell data. We found significant genetic correlations with brain volumes (false discovery rate-adjusted p=0·0035 for intracranial volume, p=0·024 for putamen volume), smoking status (p=0·024), and educational attainment (p=0·038). Mendelian randomisation between cognitive performance and Parkinson's disease risk showed a robust association (p=8·00 × 10−7). Interpretation These data provide the most comprehensive survey of genetic risk within Parkinson's disease to date, to the best of our knowledge, by revealing many additional Parkinson's disease risk loci, providing a biological context for these risk factors, and showing that a considerable genetic component of this disease remains unidentified. These associations derived from European ancestry datasets will need to be followed-up with more diverse data. Funding The National Institute on Aging at the National Institutes of Health (USA), The Michael J Fox Foundation, and The Parkinson's Foundation (see appendix for full list of funding sources)

Human induced pluripotent stem cell-derived planar neural organoids assembled on synthetic hydrogels

The tailorable properties of synthetic polyethylene glycol (PEG) hydrogels make them an attractive substrate for human organoid assembly. Here, we formed human neural organoids from iPSC-derived progenitor cells in two distinct formats: (i) cells seeded on a Matrigel surface; and (ii) cells seeded on a synthetic PEG hydrogel surface. Tissue assembly on synthetic PEG hydrogels resulted in three dimensional (3D) planar neural organoids with greater neuronal diversity, greater expression of neurovascular and neuroinflammatory genes, and reduced variability when compared with tissues assembled upon Matrigel. Further, our 3D human tissue assembly approach occurred in an open cell culture format and created a tissue that was sufficiently translucent to allow for continuous imaging. Planar neural organoids formed on PEG hydrogels also showed higher expression of neural, vascular, and neuroinflammatory genes when compared to traditional brain organoids grown in Matrigel suspensions. Further, planar neural organoids contained functional microglia that responded to pro-inflammatory stimuli, and were responsive to anti-inflammatory drugs. These results demonstrate that the PEG hydrogel neural organoids can be used as a physiologically relevant in vitro model of neuro-inflammation

sj-docx-1-tej-10.1177_20417314241230633 – Supplemental material for Human induced pluripotent stem cell-derived planar neural organoids assembled on synthetic hydrogels

Supplemental material, sj-docx-1-tej-10.1177_20417314241230633 for Human induced pluripotent stem cell-derived planar neural organoids assembled on synthetic hydrogels by Joydeb Majumder, Elizabeth E Torr, Elizabeth A Aisenbrey, Connie S Lebakken, Peter F Favreau, William D Richards, Yanhong Yin, Qiang Chang and William L Murphy in Journal of Tissue Engineering</p