63 research outputs found

    Big Domains Are Novel Ca2+-Binding Modules: Evidences from Big Domains of Leptospira Immunoglobulin-Like (Lig) Proteins

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    binds to a Big domains, which would provide a novel functional role of the proteins containing Big fold. with dissociation constants of 2–4 µM. Lig A9 and Lig A10 domains fold well with moderate thermal stability, have β-sheet conformation and form homodimers. Fluorescence spectra of Big domains show a specific doublet (at 317 and 330 nm), probably due to Trp interaction with a Phe residue. Equilibrium unfolding of selected Big domains is similar and follows a two-state model, suggesting the similarity in their fold. binding

    The Terminal Immunoglobulin-Like Repeats of LigA and LigB of Leptospira Enhance Their Binding to Gelatin Binding Domain of Fibronectin and Host Cells

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    Leptospira spp. are pathogenic spirochetes that cause the zoonotic disease leptospirosis. Leptospiral immunoglobulin (Ig)-like protein B (LigB) contributes to the binding of Leptospira to extracellular matrix proteins such as fibronectin, fibrinogen, laminin, elastin, tropoelastin and collagen. A high-affinity Fn-binding region of LigB has been localized to LigBCen2, which contains the partial 11th and full 12th Ig-like repeats (LigBCen2R) and 47 amino acids of the non-repeat region (LigBCen2NR) of LigB. In this study, the gelatin binding domain of fibronectin was shown to interact with LigBCen2R (KD = 1.91±0.40 µM). Not only LigBCen2R but also other Ig-like domains of Lig proteins including LigAVar7'-8, LigAVar10, LigAVar11, LigAVar12, LigAVar13, LigBCen7'-8, and LigBCen9 bind to GBD. Interestingly, a large gain in affinity was achieved through an avidity effect, with the terminal domains, 13th (LigA) or 12th (LigB) Ig-like repeat of Lig protein (LigAVar7'-13 and LigBCen7'-12) enhancing binding affinity approximately 51 and 28 fold, respectively, compared to recombinant proteins without this terminal repeat. In addition, the inhibited effect on MDCKs cells can also be promoted by Lig proteins with terminal domains, but these two domains are not required for gelatin binding domain binding and cell adhesion. Interestingly, Lig proteins with the terminal domains could form compact structures with a round shape mediated by multidomain interaction. This is the first report about the interaction of gelatin binding domain of Fn and Lig proteins and provides an example of Lig-gelatin binding domain binding mediating bacterial-host interaction

    Mitochondrial Localized STAT3 Is Involved in NGF Induced Neurite Outgrowth

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    Background: Signal transducer and activator of transcription 3 (STAT3) plays critical roles in neural development and is increasingly recognized as a major mediator of injury response in the nervous system. Cytokines and growth factors are known to phosphorylate STAT3 at tyrosine 705 with or without the concomitant phosphorylation at serine 727, resulting in the nuclear localization of STAT3 and subsequent transcriptional activation of genes. Recent evidence suggests that STAT3 may control cell function via alternative mechanisms independent of its transcriptional activity. Currently, the involvement of STAT3 mono-phosphorylated at residue serine 727 (P-Ser-STAT3) in neurite outgrowth and the underlying mechanism is largely unknown. Principal Findings: In this study, we investigated the role of nerve growth factor (NGF) induced P-Ser-STAT3 in mediating neurite outgrowth. NGF induced the phosphorylation of residue serine 727 but not tyrosine 705 of STAT3 in PC12 and primary cortical neuronal cells. In PC12 cells, serine but not tyrosine dominant negative mutant of STAT3 was found to impair NGF induced neurite outgrowth. Unexpectedly, NGF induced P-Ser-STAT3 was localized to the mitochondria but not in the nucleus. Mitochondrial STAT3 was further found to be intimately involved in NGF induced neurite outgrowth and the production of reactive oxygen species (ROS). Conclusion: Taken together, the findings herein demonstrated a hitherto unrecognized novel transcription independen

    Hsp60 chaperonopathies and chaperonotherapy: targets and agents.

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    Pan-cancer analysis of whole genomes

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    Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale(1-3). Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter(4); identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation(5,6); analyses timings and patterns of tumour evolution(7); describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity(8,9); and evaluates a range of more-specialized features of cancer genomes(8,10-18).Peer reviewe

    Widespread divergence of the CEACAM/PSG genes in vertebrates and humans suggests sensitivity to selection

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    In mammals, carcinoembryonic antigen cell adhesion molecules (CEACAMs) and pregnancy-specific glycoproteins (PSGs) play important roles in the regulation of pathogen transmission, tumorigenesis, insulin signaling turnover, and fetal–maternal interactions. However, how these genes evolved and to what extent they diverged in humans remain to be investigated specifically. Based on syntenic mapping of chordate genomes, we reveal that diverging homologs with a prototypic CEACAM architecture–including an extracellular domain with immunoglobulin variable and constant domain-like regions, and an intracellular domain containing ITAM motif–are present from cartilaginous fish to humans, but are absent in sea lamprey, cephalochordate or urochordate. Interestingly, the CEACAM/PSG gene inventory underwent radical divergence in various vertebrate lineages: from zero in avian species to dozens in therian mammals. In addition, analyses of genetic variations in human populations showed the presence of various types of copy number variations (CNVs) at the CEACAM/PSG locus. These copy number polymorphisms have 3–80% frequency in select populations, and encompass single to more than six PSG genes. Furthermore, we found that CEACAM/PSG genes contain a significantly higher density of nonsynonymous single nucleotide polymorphism (SNP) compared to the chromosome average, and many CEACAM/PSG SNPs exhibit high population differentiation. Taken together, our study suggested that CEACAM/PSG genes have had a more dynamic evolutionary history in vertebrates than previously thought. Given that CEACAM/PSGs play important roles in maternal–fetal interaction and pathogen recognition, these data have laid the groundwork for future analysis of adaptive CEACAM/PSG genotype-phenotypic relationships in normal and complicated pregnancies as well as other etiologies.Chia Lin Chang, Jenia Semyonov, Po Jen Cheng, Shang Yu Huang, Jae Il Park, Huai-Jen Tsai, Cheng-Yung Lin, Frank Grützner, Yung Kuei Soong, James J. Cai, Sheau Yu Teddy Hs

    Stroke genetics informs drug discovery and risk prediction across ancestries

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    Previous genome-wide association studies (GWASs) of stroke - the second leading cause of death worldwide - were conducted predominantly in populations of European ancestry(1,2). Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated (P < 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis(3), and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN) and variants (such as at GRK5 and NOS3). Using a three-pronged approach(4), we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry(5). Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries.</p
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