TDP-43 knockdown impairs neurite outgrowth dependent on its target histone deacetylase 6

<p>Abstract</p> <p>Background</p> <p>Trans-activation response element (TAR) DNA binding protein of 43kDa (TDP-43) is causally related to the neurodegenerative diseases frontotemporal dementia and amyotrophic lateral sclerosis being the hallmark protein in the disease-characteristic neuropathological lesions and via genetic linkage. Histone deacetylase 6 (HDAC6) is an established target of the RNA-binding protein TDP-43. HDAC6 is an unusual cytosolic deacetylase enzyme, central for a variety of pivotal cellular functions including aggregating protein turnover, microtubular dynamics and filopodia formation. All these functions are important in the context of neurodegenerative proteinopathies involving TDP-43. We have previously shown in a human embryonic kidney cell line that TDP-43 knockdown significantly impairs the removal of a toxic, aggregating polyQ ataxin-3 fusion protein in an HDAC6-dependent manner. Here we investigated the influence of TDP-43 and its target HDAC6 on neurite outgrowth.</p> <p>Results</p> <p>Human neuroblastoma SH-SY5Y cells with stably silenced TDP-43 showed a significant reduction of neurite outgrowth induced by retinoic acid and brain-derived neurotrophic factor. Re-transfection with TDP-43 as well as HDAC6 rescued retinoic acid-induced neurite outgrowth. In addition, we show that silencing of HDAC6 alone is sufficient to reduce neurite outgrowth of <it>in vitro </it>differentiated SH-SY5Y cells.</p> <p>Conclusions</p> <p>TDP-43 deficiency leads to impairment of neurite growth in an HDAC6-dependent manner, thereby contributing to neurodegenerative events in TDP-43 diseases.</p

TDP-43 regulates global translational yield by splicing of exon junction complex component SKAR

TDP-43 is linked to neurodegenerative diseases including frontotemporal dementia and amyotrophic lateral sclerosis. Mostly localized in the nucleus, TDP-43 acts in conjunction with other ribonucleoproteins as a splicing co-factor. Several RNA targets of TDP-43 have been identified so far, but its role(s) in pathogenesis remains unclear. Using Affymetrix exon arrays, we have screened for the first time for splicing events upon TDP-43 knockdown. We found alternative splicing of the ribosomal S6 kinase 1 (S6K1) Aly/REF-like target (SKAR) upon TDP-43 knockdown in non-neuronal and neuronal cell lines. Alternative SKAR splicing depended on the first RNA recognition motif (RRM1) of TDP-43 and on 5′-GA-3’ and 5′-UG-3′ repeats within the SKAR pre-mRNA. SKAR is a component of the exon junction complex, which recruits S6K1, thereby facilitating the pioneer round of translation and promoting cell growth. Indeed, we found that expression of the alternatively spliced SKAR enhanced S6K1-dependent signaling pathways and the translational yield of a splice-dependent reporter. Consistent with this, TDP-43 knockdown also increased translational yield and significantly increased cell size. This indicates a novel mechanism of deregulated translational control upon TDP-43 deficiency, which might contribute to pathogenesis of the protein aggregation diseases frontotemporal dementia and amyotrophic lateral sclerosis

Clinical correlates of plasma insulin levels over the life course and association with incident type 2 diabetes: the Framingham Heart Study

Introduction Insulin is a glucose-lowering hormone that affects carbohydrate, lipid, and protein metabolism. Limited data exist on the correlates of insulin levels over the life course in healthy community-dwelling individuals. Research design and methods Using multilevel modeling of multiple serial observations over 21 years, we assessed the longitudinal correlates of fasting insulin and the cross-sectional correlates of fasting and 2-hour (2h, post 75 g glucose challenge) plasma insulin concentrations in 2140 relatively healthy Framingham Heart Study participants without diabetes (61% women; mean age, 42 years). We used multivariable-adjusted Cox regression to relate glycemic markers (fasting and 2h-insulin, fasting glucose, 2h-glucose, and hemoglobin A1C) to the risk of type 2 diabetes during follow-up. Results Over the life course, fasting insulin concentrations were inversely associated with age, male sex, and physical activity, whereas waist circumference, the total/high-density lipoprotein (HDL) cholesterol ratio, and blood triglycerides were positively associated with insulin levels (p<0.005 for all). Male sex (inversely related) and the total/HDL cholesterol ratio (positively related) emerged as the most important cross-sectional correlates of 2h-insulin (p<0.005 for all). All markers were associated with higher risk of type 2 diabetes (352 cases, median follow-up 18 years, p<0.001 for all). Conclusions We observed common and distinct correlates of fasting and 2h-insulin levels. Our findings highlight a potential role of insulin in lipid and lipoprotein metabolism. Furthermore, fasting and 2h-insulin are critical markers of future diabetes risk. Further studies are needed to confirm our findings

miQC : An adaptive probabilistic framework for quality control of single-cell RNA-sequencing data

Single-cell RNA-sequencing (scRNA-seq) has made it possible to profile gene expression in tissues at high resolution. An important preprocessing step prior to performing downstream analyses is to identify and remove cells with poor or degraded sample quality using quality control (QC) metrics. Two widely used QC metrics to identify a 'low-quality' cell are (i) if the cell includes a high proportion of reads that map to mitochondrial DNA (mtDNA) encoded genes and (ii) if a small number of genes are detected. Current best practices use these QC metrics independently with either arbitrary, uniform thresholds (e.g. 5%) or biological context-dependent (e.g. species) thresholds, and fail to jointly model these metrics in a data-driven manner. Current practices are often overly stringent and especially untenable on certain types of tissues, such as archived tumor tissues, or tissues associated with mitochondrial function, such as kidney tissue [1]. We propose a data-driven QC metric (miQC) that jointly models both the proportion of reads mapping to mtDNA genes and the number of detected genes with mixture models in a probabilistic framework to predict the low-quality cells in a given dataset. We demonstrate how our QC metric easily adapts to different types of single-cell datasets to remove low-quality cells while preserving high-quality cells that can be used for downstream analyses. Our software package is available at https://bioconductor.org/packages/miQC. Author summary We developed the miQC package to predict the low-quality cells in a given scRNA-seq dataset by jointly modeling both the proportion of reads mapping to mitochondrial DNA (mtDNA) genes and the number of detected genes using mixture models in a probabilistic framework. We demonstrate how our QC metric easily adapts to different types of single-cell datasets to remove low-quality cells while preserving high-quality cells that can be used for downstream analyses.Peer reviewe

Using satellite data to develop environmental indicators

Environmental indicators are increasingly being used in policy and management contexts, yet serious data deficiencies exist for many parameters of interest to environmental decision making. With its global synoptic coverage and the wide range of instruments available, satellite remote sensing has the potential to fill a number of these gaps, yet their potential contribution to indicator development has largely remained untested. In this paper we present results of a pilot effort to develop satellite-derived indicators in three major issue areas: ambient air pollution, coastal eutrophication, and biomass burning. A primary focus is on the vetting of indicators by an advisory group composed of remote sensing scientists and policy makers

Comprehensive analysis of Arabidopsis expression level polymorphisms with simple inheritance

In Arabidopsis thaliana, gene expression level polymorphisms (ELPs) between natural accessions that exhibit simple, single locus inheritance are promising quantitative trait locus (QTL) candidates to explain phenotypic variability. It is assumed that such ELPs overwhelmingly represent regulatory element polymorphisms. However, comprehensive genome-wide analyses linking expression level, regulatory sequence and gene structure variation are missing, preventing definite verification of this assumption. Here, we analyzed ELPs observed between the Eil-0 and Lc-0 accessions. Compared with non-variable controls, 5′ regulatory sequence variation in the corresponding genes is indeed increased. However, ∼42% of all the ELP genes also carry major transcription unit deletions in one parent as revealed by genome tiling arrays, representing a >4-fold enrichment over controls. Within the subset of ELPs with simple inheritance, this proportion is even higher and deletions are generally more severe. Similar results were obtained from analyses of the Bay-0 and Sha accessions, using alternative technical approaches. Collectively, our results suggest that drastic structural changes are a major cause for ELPs with simple inheritance, corroborating experimentally observed indel preponderance in cloned Arabidopsis QTL

Attenuation of Murine Collagen‐Induced Arthritis by Targeting CD6

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/156498/2/art41288_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/156498/1/art41288.pd

β-cell metabolic alterations under chronic nutrient overload in rat and human islets

The aim of this study was to assess multifactorial β-cell responses to metabolic perturbations in primary rat and human islets. Treatment of dispersed rat islet cells with elevated glucose and free fatty acids (FFAs, oleate:palmitate = 1:1 v/v) resulted in increases in the size and the number of lipid droplets in β-cells in a time- and concentration-dependent manner. Glucose and FFAs synergistically stimulated the nutrient sensor mammalian target of rapamycin complex 1 (mTORC1). A potent mTORC1 inhibitor, rapamycin (25 nM), significantly reduced triglyceride accumulation in rat islets. Importantly, lipid droplets accumulated only in β-cells but not in α-cells in an mTORC1-dependent manner. Nutrient activation of mTORC1 upregulated the expression of adipose differentiation related protein (ADRP), known to stabilize lipid droplets. Rat islet size and new DNA synthesis also increased under nutrient overload. Insulin secretion into the culture medium increased steadily over a 4-day period without any significant difference between glucose (10 mM) alone and the combination of glucose (10 mM) and FFAs (240 μM). Insulin content and insulin biosynthesis, however, were significantly reduced under the combination of nutrients compared with glucose alone. Elevated nutrients also stimulated lipid droplet formation in human islets in an mTORC1-dependent manner. Unlike rat islets, however, human islets did not increase in size under nutrient overload despite a normal response to nutrients in releasing insulin. The different responses of islet cell growth under nutrient overload appear to impact insulin biosynthesis and storage differently in rat and human islets