98 research outputs found

    Dysfunction of contractile proteins in hypertrophic cardiomyopathy

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    The contractility of human heart samples from patients diagnosed with hypertrophic cardiomyopathy were studied using a quantitative in vitro motility assay. The aim of this work was to investigate the molecular phenotype of thin filament proteins in the HCM heart. Three biopsy samples with thin filament mutations were studied alongside samples acquired from a subset of HCM patients classified with hypertrophic obstructive cardiomyopathy. The primary effect of thin filament mutations was investigated by reconstituting Factin with ACTC E99K into thin filament with donor troponin. The E99K actin filaments had a higher Ca2+-sensitivity then filaments composed of donor F-actin (with no mutation) (EC50 E99K/donor 0.78±0.14, p=0.02). A similar higher Ca2+- sensitivity was found when recombinant TnT K273N was incorporated into donor troponin and compared to native donor troponin (EC50 K273N/donor 0.54±0.17, p=0.006). Troponin was also purified from HOCM heart samples. This troponin did not contain a causative mutation but behaved abnormally in the response of thin filament Ca2+- sensitivity to changes in TnI phosphorylation (EC50 PKA-HOCM/HOCM 1.08±0.25, p=0.3) as mean TnI phosphorylation of PKA-HOCM was 1.56 molsPi/molsTnI and HOCM was 0.29 molsPi/molsTnI. Thus, thin filament Ca2+-sensitivity was uncoupled from TnI phosphorylation in thin filaments with HOCM troponin. When the native TnT subunits were replaced with recombinant TnT this coupling was restored (EC50 HOCM rTnT/HOCM 0.63±0.26, p=0.03). It would appear that the result of HCM-causing mutations are two-fold. The primary effect of the HCM-causing mutations is to increase thin filament Ca2+-sensitivity. However, the contraction machinery appears to be the target of secondary modifications, that occur due to the pathology of the disease. Resulting in further changes, such as changes in protein composition and post-translational modification. One major consequence of these modifications may be to uncouple the relatively labile regulation of thin filament Ca2+-sensitivity by TnI phosphorylation

    High allelic diversity in the methyltransferase gene of a phase variable type III restriction-modification system has implications for the fitness of Haemophilus influenzae

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    Phase variable restriction-modification (R-M) systems are widespread in Eubacteria. Haemophilus influenzae encodes a phase variable homolog of Type III R-M systems. Sequence analysis of this system in 22 non-typeable H.influenzae isolates revealed a hypervariable region in the central portion of the mod gene whereas the res gene was conserved. Maximum likelihood (ML) analysis indicated that most sites outside this hypervariable region experienced strong negative selection but evidence of positive selection for a few sites in adjacent regions. A phylogenetic analysis of 61 Type III mod genes revealed clustering of these H.influenzae mod alleles with mod genes from pathogenic Neisseriae and, based on sequence analysis, horizontal transfer of the mod–res complex between these species. Neisserial mod alleles also contained a hypervariable region and all mod alleles exhibited variability in the repeat tract. We propose that this hypervariable region encodes the target recognition domain (TRD) of the Mod protein and that variability results in alterations to the recognition sequence of this R-M system. We argue that the high allelic diversity and phase variable nature of this R-M system have arisen due to selective pressures exerted by diversity in bacteriophage populations but also have implications for other fitness attributes of these bacterial species

    Sunyaev Zel'dovich Effect Observations of Strong Lensing Galaxy Clusters: Probing the Over-Concentration Problem

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    We have measured the Sunyaev Zel'dovich (SZ) effect for a sample of ten strong lensing selected galaxy clusters using the Sunyaev Zel'dovich Array (SZA). The SZA is sensitive to structures on spatial scales of a few arcminutes, while the strong lensing mass modeling constrains the mass at small scales (typically < 30"). Combining the two provides information about the projected concentrations of the strong lensing clusters. The Einstein radii we measure are twice as large as expected given the masses inferred from SZ scaling relations. A Monte Carlo simulation indicates that a sample randomly drawn from the expected distribution would have a larger median Einstein radius than the observed clusters about 3% of the time. The implied overconcentration has been noted in previous studies with smaller samples of lensing clusters. It persists for this sample, with the caveat that this could result from a systematic effect such as if the gas fractions of the strong lensing clusters are substantially below what is expected.Comment: submitte

    IntCal09 and Marine09 radiocarbon age calibration curves, 0-50,000yeats cal BP

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    The IntCal04 and Marine04 radiocarbon calibration curves have been updated from 12 cal kBP (cal kBP is here defined as thousands of calibrated years before AD 1950), and extended to 50 cal kBP, utilizing newly available data sets that meet the IntCal Working Group criteria for pristine corals and other carbonates and for quantification of uncertainty in both the 14C and calendar timescales as established in 2002. No change was made to the curves from 0–12 cal kBP. The curves were constructed using a Markov chain Monte Carlo (MCMC) implementation of the random walk model used for IntCal04 and Marine04. The new curves were ratified at the 20th International Radiocarbon Conference in June 2009 and are available in the Supplemental Material at www.radiocarbon.org

    Regulation of Human PINK1 ubiquitin kinase by Serine167, Serine228 and Cysteine412 phosphorylation.

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    Loss-of-function mutations in the human PINK1 kinase (hPINK1) are causative of early-onset Parkinson’s disease (PD). Activation of hPINK1 induces phosphorylated ubiquitin to initiate removal of damaged mitochondria by autophagy. Previously we solved the structure of the insect PINK1 orthologue, Tribolium castaneum PINK1, and showed that autophosphorylation of Ser205 was critical for ubiquitin interaction and phosphorylation (Kumar, Tamjar, Waddell et al., 2017). Here we report new findings on the regulation of hPINK1 by phosphorylation. We reconstitute E. coli expressed hPINK1 activity in vitro by direct incorporation of phosphoserine at the equivalent site Serine 228 (pSer228), providing direct evidence for a role for Ser228 phosphorylation in hPINK1 activation. Furthermore, using mass spectrometry, we identify six novel Ser/Thr autophosphorylation sites including regulatory Serine167 phosphorylation (pSer167), which in addition to pSer228 is required for ubiquitin recognition and phosphorylation. Strikingly, we also detect phosphorylation of a conserved Cysteine412 (pCys412) residue in the hPINK1 activation segment. Structural modelling suggests that pCys412 inhibits ubiquitin recognition and we demonstrate that mutation of Cys412 to Ala renders hPINK1 more active towards ubiquitin when expressed in human cells. These results outline new insights into hPINK1 activation by pSer167 and pSer228 and a novel inhibitory mechanism mediated by pCys412. These findings will aid in the development of small molecule activators of hPINK1

    Regulation of Human PINK1 ubiquitin kinase by Serine167, Serine228 and Cysteine412 phosphorylation.

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    Loss-of-function mutations in the human PINK1 kinase (hPINK1) are causative of early-onset Parkinson’s disease (PD). Activation of hPINK1 induces phosphorylated ubiquitin to initiate removal of damaged mitochondria by autophagy. Previously we solved the structure of the insect PINK1 orthologue, Tribolium castaneum PINK1, and showed that autophosphorylation of Ser205 was critical for ubiquitin interaction and phosphorylation (Kumar, Tamjar, Waddell et al., 2017). Here we report new findings on the regulation of hPINK1 by phosphorylation. We reconstitute E. coli expressed hPINK1 activity in vitro by direct incorporation of phosphoserine at the equivalent site Serine 228 (pSer228), providing direct evidence for a role for Ser228 phosphorylation in hPINK1 activation. Furthermore, using mass spectrometry, we identify six novel Ser/Thr autophosphorylation sites including regulatory Serine167 phosphorylation (pSer167), which in addition to pSer228 is required for ubiquitin recognition and phosphorylation. Strikingly, we also detect phosphorylation of a conserved Cysteine412 (pCys412) residue in the hPINK1 activation segment. Structural modelling suggests that pCys412 inhibits ubiquitin recognition and we demonstrate that mutation of Cys412 to Ala renders hPINK1 more active towards ubiquitin when expressed in human cells. These results outline new insights into hPINK1 activation by pSer167 and pSer228 and a novel inhibitory mechanism mediated by pCys412. These findings will aid in the development of small molecule activators of hPINK1

    Automatic vetting of planet candidates from ground based surveys : machine learning with NGTS

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    State of the art exoplanet transit surveys are producing ever increasing quantities of data. To make the best use of this resource, in detecting interesting planetary systems or in determining accurate planetary population statistics, requires new automated methods. Here we describe a machine learning algorithm that forms an integral part of the pipeline for the NGTS transit survey, demonstrating the efficacy of machine learning in selecting planetary candidates from multi-night ground based survey data. Our method uses a combination of random forests and self-organising-maps to rank planetary candidates, achieving an AUC score of 97.6% in ranking 12368 injected planets against 27496 false positives in the NGTS data. We build on past examples by using injected transit signals to form a training set, a necessary development for applying similar methods to upcoming surveys. We also make the autovet code used to implement the algorithm publicly accessible. autovet is designed to perform machine learned vetting of planetary candidates, and can utilise a variety of methods. The apparent robustness of machine learning techniques, whether on space-based or the qualitatively different ground-based data, highlights their importance to future surveys such as TESS and PLATO and the need to better understand their advantages and pitfalls in an exoplanetary context
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