Parainfluenza virus 5 genomes are located in viral cytoplasmic bodies whilst the virus dismantles the interferon-induced antiviral state of cells

Although the replication cycle of parainfluenza virus type 5 (PIV5) is initially severely impaired in cells in an interferon (IFN)-induced antiviral state, the virus still targets STAT1 for degradation. As a consequence, the cells can no longer respond to IFN and after 24−48 h, they go out of the antiviral state and normal virus replication is established. Following infection of cells in an IFN-induced antiviral state, viral nucleocapsid proteins are initially localized within small cytoplasmic bodies, and appearance of these cytoplasmic bodies correlates with the loss of STAT1 from infected cells. In situ hybridization, using probes specific for the NP and L genes, demonstrated the presence of virus genomes within these cytoplasmic bodies. These viral cytoplasmic bodies do not co-localize with cellular markers for stress granules, cytoplasmic P-bodies or autophagosomes. Furthermore, they are not large insoluble aggregates of viral proteins and/or nucleocapsids, as they can simply and easily be dispersed by ‘cold-shocking’ live cells, a process that disrupts the cytoskeleton. Given that during in vivo infections, PIV5 will inevitably infect cells in an IFN-induced antiviral state, we suggest that these cytoplasmic bodies are areas in which PIV5 genomes reside whilst the virus dismantles the antiviral state of the cells. Consequently, viral cytoplasmic bodies may play an important part in the strategy that PIV5 uses to circumvent the IFN system

Measurement of HbA1c and HbA2 by Capillarys 2 Flex Piercing HbA1c programme for simultaneous management of diabetes and screening for thalassemia

Introduction: Thalassemia could interfere with some assays for haemoglobin A1c (HbA1c) measurement, therefore, it is useful to be able to screen for thalassemia while measuring HbA1c. We used Capillarys 2 Flex Piercing (Capillarys 2FP) HbA1c programme to simultaneously measure HbA1c and screen for thalassemia. Materials and methods: Samples from 498 normal controls and 175 thalassemia patients were analysed by Capillarys 2FP HbA1c programme (Sebia, France). For method comparison, HbA1c was quantified by Premier Hb9210 (Trinity Biotech, Ireland) in 98 thalassaemia patients samples. For verification, HbA1c from eight thalassaemia patients was confirmed by IFCC reference method. Results: Among 98 thalassaemia samples, Capillarys 2FP did not provide an HbA1c result in three samples with HbH due to the overlapping of HbBart’s with HbA1c fraction; for the remaining 95 thalassaemia samples, Bland-Altman plot showed 0.00 ± 0.35% absolute bias between two systems, and a significant positive bias above 7% was observed only in two HbH samples. The HbA1c values obtained by Capillarys 2FP were consistent with the IFCC targets (relative bias below ± 6%) in all of the eight samples tested by both methods. For screening samples with alpha (α-) thalassaemia silent/trait or beta (β-) thalassemia trait, the optimal HbA2 cut-off values were ≤ 2.2% and > 2.8%, respectively. Conclusions: Our results demonstrated the Capillarys 2FP HbA1c system could report an accurate HbA1c value in thalassemia silent/trait, and HbA2 value (≤ 2.2% for α-thalassaemia silent/trait and > 2.8% for β-thalassemia trait) and abnormal bands (HbH and/or HbBart’s for HbH disease, HbF for β-thalassemia) may provide valuable information for screening

Anatomy of protein disorder, flexibility and disease-related mutations.

Integration of protein structural information with human genetic variation and pathogenic mutations is essential to understand molecular mechanisms associated with the effects of polymorphisms on protein interactions and cellular processes. We investigate occurrences of non-synonymous SNPs in ordered and disordered protein regions by systematic mapping of common variants and disease-related SNPs onto these regions. We show that common variants accumulate in disordered regions; conversely pathogenic variants are significantly depleted in disordered regions. These different occurrences of pathogenic and common SNPs can be attributed to a negative selection on random mutations in structurally highly constrained regions. New approaches in the study of quantitative effects of pathogenic-related mutations should effectively account for all the possible contexts and relative functional constraints in which the sequence variation occurs.This research was supported by the Biotechnology and Biological Sciences Research Council (BB/H018409/1 to FF), the British Heart Foundation (FS/12/41/29724 to AF and FF) and the Leukaemia & Lymphoma Research (to FF). SSC is funded by a Leukaemia & Lymphoma Research Gordon Piller PhD Studentship

Gene expression landscape of Chronic Myeloid Leukemia K562 cells overexpressing the tumor suppressor gene PTPRG

This study concerns the analysis of the modulation of Chronic Myeloid Leukemia (CML) cell model K562 transcriptome following transfection with the tumor suppressor gene encoding for Protein Tyrosine Phosphatase Receptor Type G (PTPRG) and treatment with the tyrosine kinase inhibitor (TKI) Imatinib. Specifically, we aimed at identifying genes whose level of expression is altered by PTPRG modulation and Imatinib concentration. Statistical tests as differential expression analysis (DEA) supported by gene set enrichment analysis (GSEA) and modern methods of ontological term analysis are presented along with some results of current interest for forthcoming experimental research in the field of the transcriptomic landscape of CML. In particular, we present two methods that differ in the order of the analysis steps. After a gene selection based on fold-change value thresholding, we applied statistical tests to select differentially expressed genes. Therefore, we applied two different methods on the set of differentially expressed genes. With the first method (Method 1), we implemented GSEA, followed by the identification of transcription factors. With the second method (Method 2), we first selected the transcription factors from the set of differentially expressed genes and implemented GSEA on this set. Method 1 is a standard method commonly used in this type of analysis, while Method 2 is unconventional and is motivated by the intention to identify transcription factors more specifically involved in biological processes relevant to the CML condition. Both methods have been equipped in ontological knowledge mining and word cloud analysis, as elements of novelty in our analytical procedure. Data analysis identified RARG and CD36 as a potential PTPRG up-regulated genes, suggesting a possible induction of cell differentiation toward an erithromyeloid phenotype. The prediction was confirmed at the mRNA and protein level, further validating the approach and identifying a new molecular mechanism of tumor suppression governed by PTPRG in a CML context

A First Search for coincident Gravitational Waves and High Energy Neutrinos using LIGO, Virgo and ANTARES data from 2007

We present the results of the first search for gravitational wave bursts associated with high energy neutrinos. Together, these messengers could reveal new, hidden sources that are not observed by conventional photon astronomy, particularly at high energy. Our search uses neutrinos detected by the underwater neutrino telescope ANTARES in its 5 line configuration during the period January - September 2007, which coincided with the fifth and first science runs of LIGO and Virgo, respectively. The LIGO-Virgo data were analysed for candidate gravitational-wave signals coincident in time and direction with the neutrino events. No significant coincident events were observed. We place limits on the density of joint high energy neutrino - gravitational wave emission events in the local universe, and compare them with densities of merger and core-collapse events.Comment: 19 pages, 8 figures, science summary page at http://www.ligo.org/science/Publication-S5LV_ANTARES/index.php. Public access area to figures, tables at https://dcc.ligo.org/cgi-bin/DocDB/ShowDocument?docid=p120000

A new mutant genetic resource for tomato crop improvement by TILLING technology

<p>Abstract</p> <p>Background</p> <p>In the last decade, the availability of gene sequences of many plant species, including tomato, has encouraged the development of strategies that do not rely on genetic transformation techniques (GMOs) for imparting desired traits in crops. One of these new emerging technology is TILLING (Targeting Induced Local Lesions In Genomes), a reverse genetics tool, which is proving to be very valuable in creating new traits in different crop species.</p> <p>Results</p> <p>To apply TILLING to tomato, a new mutant collection was generated in the genetic background of the processing tomato cultivar Red Setter by treating seeds with two different ethylemethane sulfonate doses (0.7% and 1%). An associated phenotype database, LycoTILL, was developed and a TILLING platform was also established. The interactive and evolving database is available online to the community for phenotypic alteration inquiries. To validate the Red Setter TILLING platform, induced point mutations were searched in 7 tomato genes with the mismatch-specific ENDO1 nuclease. In total 9.5 kb of tomato genome were screened and 66 nucleotide substitutions were identified. The overall mutation density was estimated and it resulted to be 1/322 kb and 1/574 kb for the 1% EMS and 0.7% EMS treatment respectively.</p> <p>Conclusions</p> <p>The mutation density estimated in our collection and its comparison with other TILLING populations demonstrate that the Red Setter genetic resource is suitable for use in high-throughput mutation discovery. The Red Setter TILLING platform is open to the research community and is publicly available via web for requesting mutation screening services.</p

Core module biomarker identification with network exploration for breast cancer metastasis

<p>Abstract</p> <p>Background</p> <p>In a complex disease, the expression of many genes can be significantly altered, leading to the appearance of a differentially expressed "disease module". Some of these genes directly correspond to the disease phenotype, (i.e. "driver" genes), while others represent closely-related first-degree neighbours in gene interaction space. The remaining genes consist of further removed "passenger" genes, which are often not directly related to the original cause of the disease. For prognostic and diagnostic purposes, it is crucial to be able to separate the group of "driver" genes and their first-degree neighbours, (i.e. "core module") from the general "disease module".</p> <p>Results</p> <p>We have developed COMBINER: COre Module Biomarker Identification with Network ExploRation. COMBINER is a novel pathway-based approach for selecting highly reproducible discriminative biomarkers. We applied COMBINER to three benchmark breast cancer datasets for identifying prognostic biomarkers. COMBINER-derived biomarkers exhibited 10-fold higher reproducibility than other methods, with up to 30-fold greater enrichment for known cancer-related genes, and 4-fold enrichment for known breast cancer susceptible genes. More than 50% and 40% of the resulting biomarkers were cancer and breast cancer specific, respectively. The identified modules were overlaid onto a map of intracellular pathways that comprehensively highlighted the hallmarks of cancer. Furthermore, we constructed a global regulatory network intertwining several functional clusters and uncovered 13 confident "driver" genes of breast cancer metastasis.</p> <p>Conclusions</p> <p>COMBINER can efficiently and robustly identify disease core module genes and construct their associated regulatory network. In the same way, it is potentially applicable in the characterization of any disease that can be probed with microarrays.</p

Heart Rate Variability Characteristics in Sedentary Postmenopausal Women Following Six Months of Exercise Training: The DREW Study

Article on heart rate variability characteristics in sedentary postmenopausal women following six months of exercise training