Dichotomous intronic polyadenylation profiles reveal multifaceted gene functions in the pan-cancer transcriptome.

Alternative cleavage and polyadenylation within introns (intronic APA) generate shorter mRNA isoforms; however, their physiological significance remains elusive. In this study, we developed a comprehensive workflow to analyze intronic APA profiles using the mammalian target of rapamycin (mTOR)-regulated transcriptome as a model system. Our investigation revealed two contrasting effects within the transcriptome in response to fluctuations in cellular mTOR activity: an increase in intronic APA for a subset of genes and a decrease for another subset of genes. The application of this workflow to RNA-seq data from The Cancer Genome Atlas demonstrated that this dichotomous intronic APA pattern is a consistent feature in transcriptomes across both normal tissues and various cancer types. Notably, our analyses of protein length changes resulting from intronic APA events revealed two distinct phenomena in proteome programming: a loss of functional domains due to significant changes in protein length or minimal alterations in C-terminal protein sequences within unstructured regions. Focusing on conserved intronic APA events across 10 different cancer types highlighted the prevalence of the latter cases in cancer transcriptomes, whereas the former cases were relatively enriched in normal tissue transcriptomes. These observations suggest potential, yet distinct, roles for intronic APA events during pathogenic processes and emphasize the abundance of protein isoforms with similar lengths in the cancer proteome. Furthermore, our investigation into the isoform-specific functions of JMJD6 intronic APA events supported the hypothesis that alterations in unstructured C-terminal protein regions lead to functional differences. Collectively, our findings underscore intronic APA events as a discrete molecular signature present in both normal tissues and cancer transcriptomes, highlighting the contribution of APA to the multifaceted functionality of the cancer proteome.

TMEM9 activates Rab9-dependent alternative autophagy through interaction with Beclin1.

Transmembrane protein 9 (TMEM9) is a transmembrane protein that regulates lysosomal acidification by interacting with the v-type ATPase complex. However, the role of TMEM9 in the lysosome-dependent autophagy machinery has yet to be identified. In this study, we demonstrate that the lysosomal protein TMEM9, which is involved in vesicle acidification, regulates Rab9-dependent alternative autophagy through its interaction with Beclin1. The cytosolic domain of TMEM9 interacts with Beclin1 via its Bcl-2-binding domain. This interaction between TMEM9 and Beclin1 dissociates Bcl-2, an autophagy-inhibiting partner, from Beclin1, thereby activating LC3-independent and Rab9-dependent alternative autophagy. Late endosomal and lysosomal TMEM9 apparently colocalizes with Rab9 but not with LC3. Furthermore, we show that multiple glycosylation of TMEM9, essential for lysosomal localization, is essential for its interaction with Beclin1 and the activation of Rab9-dependent alternative autophagy. These findings reveal that TMEM9 recruits and activates the Beclin1 complex at the site of Rab9-dependent autophagosome to induce alternative autophagy.

Evolution of the clinical-stage hyperactive TcBuster transposase as a platform for robust non-viral production of adoptive cellular therapies.

Cellular therapies for the treatment of human diseases, such as chimeric antigen receptor (CAR) T and natural killer (NK) cells have shown remarkable clinical efficacy in treating hematological malignancies; however, current methods mainly utilize viral vectors that are limited by their cargo size capacities, high cost, and long timelines for production of clinical reagent. Delivery of genetic cargo via DNA transposon engineering is a more timely and cost-effective approach, yet has been held back by less efficient integration rates. Here, we report the development of a novel hyperactive TcBuster (TcB-M) transposase engineered through structure-guided and in vitro evolution approaches that achieves high-efficiency integration of large, multicistronic CAR-expression cassettes in primary human cells. Our proof-of-principle TcB-M engineering of CAR-NK and CAR-T cells shows low integrated vector copy number, a safe insertion site profile, robust in vitro function, and improves survival in a Burkitt lymphoma xenograft model in vivo. Overall, TcB-M is a versatile, safe, efficient and open-source option for the rapid manufacture and preclinical testing of primary human immune cell therapies through delivery of multicistronic large cargo via transposition.

APA-Scan: detection and visualization of 3'-UTR alternative polyadenylation with RNA-seq and 3'-end-seq data.

BACKGROUND: The eukaryotic genome is capable of producing multiple isoforms from a gene by alternative polyadenylation (APA) during pre-mRNA processing. APA in the 3'-untranslated region (3'-UTR) of mRNA produces transcripts with shorter or longer 3'-UTR. Often, 3'-UTR serves as a binding platform for microRNAs and RNA-binding proteins, which affect the fate of the mRNA transcript. Thus, 3'-UTR APA is known to modulate translation and provides a mean to regulate gene expression at the post-transcriptional level. Current bioinformatics pipelines have limited capability in profiling 3'-UTR APA events due to incomplete annotations and a low-resolution analyzing power: widely available bioinformatics pipelines do not reference actionable polyadenylation (cleavage) sites but simulate 3'-UTR APA only using RNA-seq read coverage, causing false positive identifications. To overcome these limitations, we developed APA-Scan, a robust program that identifies 3'-UTR APA events and visualizes the RNA-seq short-read coverage with gene annotations. METHODS: APA-Scan utilizes either predicted or experimentally validated actionable polyadenylation signals as a reference for polyadenylation sites and calculates the quantity of long and short 3'-UTR transcripts in the RNA-seq data. APA-Scan works in three major steps: (i) calculate the read coverage of the 3'-UTR regions of genes; (ii) identify the potential APA sites and evaluate the significance of the events among two biological conditions; (iii) graphical representation of user specific event with 3'-UTR annotation and read coverage on the 3'-UTR regions. APA-Scan is implemented in Python3. Source code and a comprehensive user's manual are freely available at https://github.com/compbiolabucf/APA-Scan . RESULT: APA-Scan was applied to both simulated and real RNA-seq datasets and compared with two widely used baselines DaPars and APAtrap. In simulation APA-Scan significantly improved the accuracy of 3'-UTR APA identification compared to the other baselines. The performance of APA-Scan was also validated by 3'-end-seq data and qPCR on mouse embryonic fibroblast cells. The experiments confirm that APA-Scan can detect unannotated 3'-UTR APA events and improve genome annotation. CONCLUSION: APA-Scan is a comprehensive computational pipeline to detect transcriptome-wide 3'-UTR APA events. The pipeline integrates both RNA-seq and 3'-end-seq data information and can efficiently identify the significant events with a high-resolution short reads coverage plots.

AS-Quant: Detection and Visualization of Alternative Splicing Events with RNA-seq Data.

(1) Background: A simplistic understanding of the central dogma falls short in correlating the number of genes in the genome to the number of proteins in the proteome. Post-transcriptional alternative splicing contributes to the complexity of the proteome and is critical in understanding gene expression. mRNA-sequencing (RNA-seq) has been widely used to study the transcriptome and provides opportunity to detect alternative splicing events among different biological conditions. Despite the popularity of studying transcriptome variants with RNA-seq, few efficient and user-friendly bioinformatics tools have been developed for the genome-wide detection and visualization of alternative splicing events. (2) Results: We propose AS-Quant, (Alternative Splicing Quantitation), a robust program to identify alternative splicing events from RNA-seq data. We then extended AS-Quant to visualize the splicing events with short-read coverage plots along with complete gene annotation. The tool works in three major steps: (i) calculate the read coverage of the potential spliced exons and the corresponding gene; (ii) categorize the events into five different categories according to the annotation, and assess the significance of the events between two biological conditions; (iii) generate the short reads coverage plot for user specified splicing events. Our extensive experiments on simulated and real datasets demonstrate that AS-Quant outperforms the other three widely used baselines, SUPPA2, rMATS, and diffSplice for detecting alternative splicing events. Moreover, the significant alternative splicing events identified by AS-Quant between two biological contexts were validated by RT-PCR experiment. (3) Availability: AS-Quant is implemented in Python 3.0. Source code and a comprehensive user's manual are freely available online.

A large-scale comparative study of isoform expressions measured on four platforms.

BACKGROUND: Most eukaryotic genes produce different transcripts of multiple isoforms by inclusion or exclusion of particular exons. The isoforms of a gene often play diverse functional roles, and thus it is necessary to accurately measure isoform expressions as well as gene expressions. While previous studies have demonstrated the strong agreement between mRNA sequencing (RNA-seq) and array-based gene and/or isoform quantification platforms (Microarray gene expression and Exon-array), the more recently developed NanoString platform has not been systematically evaluated and compared, especially in large-scale studies across different cancer domains. RESULTS: In this paper, we present a large-scale comparative study among RNA-seq, NanoString, array-based, and RT-qPCR platforms using 46 cancer cell lines across different cancer types. The goal is to understand and evaluate the calibers of the platforms for measuring gene and isoform expressions in cancer studies. We first performed NanoString experiments on 59 cancer cell lines with 404 custom-designed probes for measuring the expressions of 478 isoforms in 155 genes, and additional RT-qPCR experiments for a subset of the measured isoforms in 13 cell lines. We then combined the data with the matched RNA-seq, Exon-array, and Microarray data of 46 of the 59 cell lines for the comparative analysis. CONCLUSION: In the comparisons of the platforms for measuring the expressions at both isoform and gene levels, we found that (1) the agreement on isoform expressions is lower than the agreement on gene expressions across the four platforms; (2) NanoString and Exon-array are not consistent on isoform quantification even though both techniques are based on hybridization reactions; (3) RT-qPCR experiments are more consistent with RNA-seq and Exon-array than NanoString in isoform quantification; (4) different RNA-seq isoform quantification methods show varying estimation results, and among the methods, Net-RSTQ and eXpress are more consistent across the platforms; and (5) RNA-seq has the best overall consistency with the other platforms on gene expression quantification.

Platform-integrated mRNA isoform quantification.

MOTIVATION: Accurate estimation of transcript isoform abundance is critical for downstream transcriptome analyses and can lead to precise molecular mechanisms for understanding complex human diseases, like cancer. Simplex mRNA Sequencing (RNA-Seq) based isoform quantification approaches are facing the challenges of inherent sampling bias and unidentifiable read origins. A large-scale experiment shows that the consistency between RNA-Seq and other mRNA quantification platforms is relatively low at the isoform level compared to the gene level. In this project, we developed a platform-integrated model for transcript quantification (IntMTQ) to improve the performance of RNA-Seq on isoform expression estimation. IntMTQ, which benefits from the mRNA expressions reported by the other platforms, provides more precise RNA-Seq-based isoform quantification and leads to more accurate molecular signatures for disease phenotype prediction. RESULTS: In the experiments to assess the quality of isoform expression estimated by IntMTQ, we designed three tasks for clustering and classification of 46 cancer cell lines with four different mRNA quantification platforms, including newly developed NanoString's nCounter technology. The results demonstrate that the isoform expressions learned by IntMTQ consistently provide more and better molecular features for downstream analyses compared with five baseline algorithms which consider RNA-Seq data only. An independent RT-qPCR experiment on seven genes in twelve cancer cell lines showed that the IntMTQ improved overall transcript quantification. The platform-integrated algorithms could be applied to large-scale cancer studies, such as The Cancer Genome Atlas (TCGA), with both RNA-Seq and array-based platforms available. AVAILABILITY AND IMPLEMENTATION: Source code is available at: https://github.com/CompbioLabUcf/IntMTQ. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

mTOR-regulated U2af1 tandem exon splicing specifies transcriptome features for translational control.

U2 auxiliary factor 1 (U2AF1) functions in 3'-splice site selection during pre-mRNA processing. Alternative usage of duplicated tandem exons in U2AF1 produces two isoforms, U2AF1a and U2AF1b, but their functional differences are unappreciated due to their homology. Through integrative approaches of genome editing, customized-transcriptome profiling and crosslinking-mediated interactome analyses, we discovered that the expression of U2AF1 isoforms is controlled by mTOR and they exhibit a distinctive molecular profile for the splice site and protein interactomes. Mechanistic dissection of mutually exclusive alternative splicing events revealed that U2AF1 isoforms' inherent differential preferences of nucleotide sequences and their stoichiometry determine the 3'-splice site. Importantly, U2AF1a-driven transcriptomes feature alternative splicing events in the 5'-untranslated region (5'-UTR) that are favorable for translation. These findings unveil distinct roles of duplicated tandem exon-derived U2AF1 isoforms in the regulation of the transcriptome and suggest U2AF1a-driven 5'-UTR alternative splicing as a molecular mechanism of mTOR-regulated translational control.

An integrative model for alternative polyadenylation, IntMAP, delineates mTOR-modulated endoplasmic reticulum stress response.

3'-untranslated regions (UTRs) can vary through the use of alternative polyadenylation sites during pre-mRNA processing. Multiple publically available pipelines combining high profiling technologies and bioinformatics tools have been developed to catalog changes in 3'-UTR lengths. In our recent RNA-seq experiments using cells with hyper-activated mammalian target of rapamycin (mTOR), we found that cellular mTOR activation leads to transcriptome-wide alternative polyadenylation (APA), resulting in the activation of multiple cellular pathways. Here, we developed a novel bioinformatics algorithm, IntMAP, which integrates RNA-Seq and PolyA Site (PAS)-Seq data for a comprehensive characterization of APA events. By applying IntMAP to the datasets from cells with hyper-activated mTOR, we identified novel APA events that could otherwise not be identified by either profiling method alone. Several transcription factors including Cebpg (CCAAT/enhancer binding protein gamma) were among the newly discovered APA transcripts, indicating that diverse transcriptional networks may be regulated by mTOR-coordinated APA. The prevention of APA in Cebpg using the CRISPR/cas9-mediated genome editing tool showed that mTOR-driven 3'-UTR shortening in Cebpg is critical in protecting cells from endoplasmic reticulum (ER) stress. Taken together, we present IntMAP as a new bioinformatics algorithm for APA analysis by which we expand our understanding of the physiological role of mTOR-coordinated APA events to ER stress response. IntMAP toolbox is available at http://compbio.cs.umn.edu/IntMAP/.

Ribo-Proteomics Approach to Profile RNA-Protein and Protein-Protein Interaction Networks.

Characterizing protein-protein and protein-RNA interaction networks is a fundamental step to understanding the function of an RNA-binding protein. In many cases, these interactions are transient and highly dynamic. Therefore, capturing stable as well as transient interactions in living cells for the identification of protein-binding partners and the mapping of RNA-binding sequences is key to a successful establishment of the molecular interaction network. In this chapter, we will describe a method for capturing the molecular interactions in living cells using formaldehyde as a crosslinker and enriching a specific RNA-protein complex from cell extracts followed by mass spectrometry and Next-Gen sequencing analyses.

Network-Based Isoform Quantification with RNA-Seq Data for Cancer Transcriptome Analysis.

High-throughput mRNA sequencing (RNA-Seq) is widely used for transcript quantification of gene isoforms. Since RNA-Seq data alone is often not sufficient to accurately identify the read origins from the isoforms for quantification, we propose to explore protein domain-domain interactions as prior knowledge for integrative analysis with RNA-Seq data. We introduce a Network-based method for RNA-Seq-based Transcript Quantification (Net-RSTQ) to integrate protein domain-domain interaction network with short read alignments for transcript abundance estimation. Based on our observation that the abundances of the neighboring isoforms by domain-domain interactions in the network are positively correlated, Net-RSTQ models the expression of the neighboring transcripts as Dirichlet priors on the likelihood of the observed read alignments against the transcripts in one gene. The transcript abundances of all the genes are then jointly estimated with alternating optimization of multiple EM problems. In simulation Net-RSTQ effectively improved isoform transcript quantifications when isoform co-expressions correlate with their interactions. qRT-PCR results on 25 multi-isoform genes in a stem cell line, an ovarian cancer cell line, and a breast cancer cell line also showed that Net-RSTQ estimated more consistent isoform proportions with RNA-Seq data. In the experiments on the RNA-Seq data in The Cancer Genome Atlas (TCGA), the transcript abundances estimated by Net-RSTQ are more informative for patient sample classification of ovarian cancer, breast cancer and lung cancer. All experimental results collectively support that Net-RSTQ is a promising approach for isoform quantification. Net-RSTQ toolbox is available at http://compbio.cs.umn.edu/Net-RSTQ/.

mRNA 3'-UTR shortening is a molecular signature of mTORC1 activation.

Mammalian target of rapamycin (mTOR) enhances translation from a subset of messenger RNAs containing distinct 5'-untranslated region (UTR) sequence features. Here we identify 3'-UTR shortening of mRNAs as an additional molecular signature of mTOR activation and show that 3'-UTR shortening enhances the translation of specific mRNAs. Using genetic or chemical modulations of mTOR activity in cells or mouse tissues, we show that cellular mTOR activity is crucial for 3'-UTR shortening. Although long 3'-UTR-containing transcripts minimally contribute to translation, 3-'UTR-shortened transcripts efficiently form polysomes in the mTOR-activated cells, leading to increased protein production. Strikingly, selected E2 and E3 components of ubiquitin ligase complexes are enriched by this mechanism, resulting in elevated levels of protein ubiquitination on mTOR activation. Together, these findings identify a previously uncharacterized role for mTOR in the selective regulation of protein synthesis by modulating 3'-UTR length of mRNAs.

Identification of glucose-6-phosphate transporter as a key regulator functioning at the autophagy initiation step.

Autophagy is a catabolic process involving autophagosome formation via lysosome. However, the initiation step of autophagy is largely unknown. We found an interaction between ULK1 and ATG9 in mammalian cells and utilized the interaction to identify novel regulators of autophagy upstream of ULK1. We established a cell-based screening assay employing bimolecular fluorescence complementation. By performing gain-of-function screening, we identified G6PT as an autophagy activator. G6PT enhanced the interaction between N-terminal Venus-tagged ULK1 and C-terminal Venus-tagged ATG9, and increased autophagic flux independent of its transport activity. G6PT negatively regulated mTORC1 activity, demonstrating that G6PT functions upstream of mTORC1 in stimulating autophagy.

BECN1/Beclin 1 is recruited into lipid rafts by prion to activate autophagy in response to amyloid ß 42.

Prion protein (PRNP) has been implicated in various types of neurodegenerative diseases. Although much is known about prion diseases, the function of cellular PRNP remains cryptic. Here, we show that PRNP mediates amyloid ß1­42 (Aß42)-induced autophagy activation through its interaction with BECN1. Treatment with Aß42 enhanced autophagy flux in neuronal cells. Aß42-induced autophagy activation, however, was impaired in prnp-knockout primary cortical neurons and Prnp-knockdown or prnp-knockout neuronal cells. Immunoprecipitation assays revealed that PRNP interacted with BECN1 via the BCL2-binding domain of BECN1. This interaction promoted the subcellular localization of BECN1 into lipid rafts of the plasma membrane and enhanced activity of PtdIns3K (whose catalytic subunit is termed PIK3C3, mammalian ortholog of yeast VPS34) in lipid rafts by generating PtdIns3P in response to Aß42. Further, the levels of lipid rafts that colocalized with BECN1, decreased in the brains of aged C57BL/6 mice, as did PRNP. These results suggested that PRNP interacts with BECN1 to recruit the PIK3C3 complex into lipid rafts and thus activates autophagy in response to Aß42, defining a novel role of PRNP in the regulation of autophagy.

Calsenilin contributes to neuronal cell death in ischemic stroke.

Calsenilin is a calcium sensor protein that interacts with presenilin and increases calcium-triggered neuronal apoptosis, and γ-secretase activity. Notch is a cell surface receptor that regulates cell-fate decisions and synaptic plasticity in brain. The aim of the present study was to characterize the role of calsenilin as a regulator of the γ-secretase cleavage of Notch in ischemic stroke. Here, we determined the modulation of expression level and cellular distribution of calsenilin in neurons subjected to ischemic-like conditions. The levels of calsenilin and presenilin were increased in primary neurons after oxygen and glucose deprivation. Furthermore, calsenilin was found to enhance the γ-secretase cleavage of Notch and to contribute to cell death under ischemia-like conditions. The inhibition of γ-secretase activity and a presenilin deficiency were both found to protect against calsenilin-mediated ischemic neuronal death. The expression of calsenilin was found to be increased in brain following experimental ischemic stroke. These findings establish a specific molecular mechanism by which the induction of calsenilin enhances Notch activation in ischemic stroke, and identify calsenilin as an upstream of the γ-secretase cleavage of Notch.

IRE1 plays an essential role in ER stress-mediated aggregation of mutant huntingtin via the inhibition of autophagy flux.

Huntington's disease (HD), an inherited neurodegenerative disorder, is caused by an expansion of cytosine-adenine-guanine repeats in the huntingtin gene. The aggregation of mutant huntingtin (mtHTT) and striatal cell loss are representative features to cause uncontrolled movement and cognitive defect in HD. However, underlying mechanism of mtHTT aggregation and cell toxicity remains still elusive. Here, to find new genes modulating mtHTT aggregation, we performed cell-based functional screening using the cDNA expression library and isolated IRE1 gene, one of endoplasmic reticulum (ER) stress sensors. Ectopic expression of IRE1 led to its self-activation and accumulated detergent-resistant mtHTT aggregates. Treatment of neuronal cells with ER stress insults, tunicamycin and thapsigargin, increased mtHTT aggregation via IRE1 activation. The kinase activity of IRE1, but not the endoribonuclease activity, was necessary to stimulate mtHTT aggregation and increased death of neuronal cells, including SH-SY5Y and STHdhQ111/111 huntingtin knock-in striatal cells. Interestingly, ER stress impaired autophagy flux via IRE1-TRAF2 pathway, thus enhancing cellular accumulation of mtHTT. Atg5 deficiency in M5-7 cells increased mtHTT aggregation but blocked ER stress-induced mtHTT aggregation. Further, ER stress markers including p-IRE1 and autophagy markers such as p62 were up-regulated exclusively in the striatal tissues of HD mouse models and in HD patients. Moreover, down-regulation of IRE1 expression rescues the rough-eye phenotype by mtHTT in a HD fly model. These results suggest that IRE1 plays an essential role in ER stress-mediated aggregation of mtHTT via the inhibition of autophagy flux and thus neuronal toxicity of mtHTT aggregates in HD.

Lithium rescues the impaired autophagy process in CbCln3(Δex7/8/Δex7/8) cerebellar cells and reduces neuronal vulnerability to cell death via IMPase inhibition.

Juvenile neuronal ceroid lipofuscinosis (Batten disease) is a neurodegenerative disorder caused by mutation in CLN3. Defective autophagy and concomitant accumulation of autofluorescence enriched with mitochondrial ATP synthase subunit c were previously discovered in Cln3 mutant knock-in mice. In this study, we show that treatment with lithium reduces numbers of LC3-positive autophagosomes and accumulation of LC3-II in Cln3 mutant knock-in cerebellar cells (CbCln3(Δex7/8/Δex7/8) ). Lithium, an inhibitor of GSK3 and IMPase, reduces the accumulation of mitochondrial ATP synthase subunit c and autofluorescence in CbCln3(Δex7/8/Δex7/8) cells, and mitigates the abnormal subcellular distribution of acidic vesicles in the cells. L690,330, an IMPase inhibitor, is as effective as lithium in restoring autophagy in CbCln3(Δex7/8/Δex7/8) cells. Moreover, lithium or down-regulation of IMPase expression protects CbCln3(Δex7/8/Δex7/8) cells from cell death induced by amino acid deprivation. These results suggest that lithium overcomes the autophagic defect in CbCln3(Δex7/8/Δex7/8) cerebellar cells probably through IMPase, thereby reducing their vulnerability to cell death.

SCAMP5 links endoplasmic reticulum stress to the accumulation of expanded polyglutamine protein aggregates via endocytosis inhibition.

Accumulation of expanded polyglutamine proteins is considered to be a major pathogenic biomarker of Huntington disease. We isolated SCAMP5 as a novel regulator of cellular accumulation of expanded polyglutamine track protein using cell-based aggregation assays. Ectopic expression of SCAMP5 augments the formation of ubiquitin-positive and detergent-resistant aggregates of mutant huntingtin (mtHTT). Expression of SCAMP5 is markedly increased in the striatum of Huntington disease patients and is induced in cultured striatal neurons by endoplasmic reticulum (ER) stress or by mtHTT. The increase of SCAMP5 impairs endocytosis, which in turn enhances mtHTT aggregation. On the contrary, down-regulation of SCAMP5 alleviates ER stress-induced mtHTT aggregation and endocytosis inhibition. Moreover, stereotactic injection into the striatum and intraperitoneal injection of tunicamycin significantly increase mtHTT aggregation in the striatum of R6/2 mice and in the cortex of N171-82Q mice, respectively. Taken together, these results suggest that exposure to ER stress increases SCAMP5 in the striatum, which positively regulates mtHTT aggregation via the endocytosis pathway.

Protection of cardiomyocytes from ischemic/hypoxic cell death via Drbp1 and pMe2GlyDH in cardio-specific ARC transgenic mice.

The ischemic death of cardiomyocytes is associated in heart disease and heart failure. However, the molecular mechanism underlying ischemic cell death is not well defined. To examine the function of apoptosis repressor with a caspase recruitment domain (ARC) in the ischemic/hypoxic damage of cardiomyocytes, we generated cardio-specific ARC transgenic mice using a mouse alpha-myosin heavy chain promoter. Compared with the control, the hearts of ARC transgenic mice showed a 3-fold overexpression of ARC. Langendoff preparation showed that the hearts isolated from ARC transgenic mice exhibited improved recovery of contractile performance during reperfusion. The cardiomyocytes cultured from neonatal ARC transgenic mice were significantly resistant to hypoxic cell death. Furthermore, the ARC C-terminal calcium-binding domain was as potent to protect cardiomyocytes from hypoxic cell death as ARC. Genome-wide RNA expression profiling uncovered a list of genes whose expression was changed (>2-fold) in ARC transgenic mice. Among them, expressional regulation of developmentally regulated RNA-binding protein 1 (Drbp1) or the dimethylglycine dehydrogenase precursor (pMe(2)GlyDH) affected hypoxic death of cardiomyocytes. These results suggest that ARC may protect cardiomyocytes from hypoxic cell death by regulating its downstream, Drbp1 and pMe(2)GlyDH, shedding new insights into the protection of heart from hypoxic damages.

Characterization of subcellular localization and Ca2+ modulation of calsenilin/DREAM/KChIP3.

Earlier reports found that calsenilin is a transcriptional repressor or a subunit of plasma membrane channel, and indicated that calsenilin was present in the nucleus or plasma membrane. Immunohistochemical and subcellular fractionation analysis, however, revealed that calsenilin/DREAM/KChIP3 was distributed throughout the cytoplasm of SK-N-BE2(C), Jurkat, and HeLa cells. In addition, the expression of calsenilin suppressed the ATP-induced increase in intracellular Ca2+ concentrations. By increase in intracellular calcium concentration, calsenilin was translocated into the nucleus.