Nomenclature updates resulting from the evolution of avian influenza A(H5) virus clades 2.1.3.2a, 2.2.1, and 2.3.4 during 2013-2014.

AIM: The A/goose/Guangdong/1/96-like hemagglutinin (HA) genes of highly pathogenic avian influenza (HPAI) A(H5) viruses have continued to rapidly evolve since the most recent update to the H5 clade nomenclature by the WHO/OIE/FAO H5N1 Evolution Working Group. New clades diverging beyond established boundaries need to be identified and designated accordingly. METHOD: Hemagglutinin sequences deposited in publicly accessible databases up to December 31, 2014, were analyzed by phylogenetic and average pairwise distance methods to identify new clades that merit nomenclature changes. RESULTS: Three new clade designations were recommended based on division of clade 2·1·3·2a (Indonesia), 2·2·1 (Egypt), and 2·3·4 (widespread detection in Asia, Europe, and North America) that includes newly emergent HPAI virus subtypes H5N2, H5N3, H5N5, H5N6, and H5N8. CONCLUSION: Continued global surveillance for HPAI A(H5) viruses in all host species and timely reporting of sequence data will be critical to quickly identify new clades and assess their potential impact on human and animal health.The Melbourne WHO Collaborating Centre for Reference and Research on Influenza is supported by the Australian Government Department of Health.This is the final version of the article. It first appeared from Wiley via http://dx.doi.org/10.1111/irv.1232

Surveillance and characterisation of influenza viruses among patients with influenza-like illness in Bali, Indonesia, July 2010-June 2014.

BACKGROUND: Although Indonesia has high fatality rate of human A/H5N1 cases, epidemiological and clinical data on influenza virus circulation among humans has been limited. Within Indonesia, Bali province is of interest due to high population densities of humans, pigs and poultry. This study aims to characterize and compare the epidemiological and clinical patterns of influenza viruses in humans through surveillance among patients with influenza-like illness (ILI) in Bali, Indonesia. METHODS: ILI patients were recruited at 21 sentinel health facilities across all nine regencies in Bali, from July 2010 to June 2014. PCR-based assays were used for detection and subtyping of influenza viruses. Demographic, behavioural and clinical data were tested for associations with influenza using chi-squared tests and logistic regression. RESULTS: Of 2077 ILI patients, 291 (14.0%) tested positive for influenza A, 152 (7.3%) for influenza B, and 16 (0.77%) for both influenza A and B. Of the influenza A isolates, the majority 61.2% were A/H3N2, followed by A/H1N1-pdm09 (80; 26.1%). Two A/H5N1 were identified. Influenza positive rates were significantly higher during wet season months (28.3%), compared with the dry season (13.8%; χ2 = 61.1; df = 1; p < 0.0001). Clinical predictors for infection varied by virus type, with measured fever (≥38 °C) more strongly associated with influenza B (AOR: 1.62; 95% CI: 1.10, 2.39). CONCLUSION: Influenza circulates year-round among humans in Bali with higher activity during the wet season. High contact rates with poultry and pigs, along with influenza virus detection that could not be subtyped through conventional assays, highlight the need for molecular studies to characterize epidemiological and evolutionary dynamics of influenza in this setting

Two novel human cytomegalovirus NK cell evasion functions target MICA for lysosomal degradation

NKG2D plays a major role in controlling immune responses through the regulation of natural killer (NK) cells, αβ and γδ T-cell function. This activating receptor recognizes eight distinct ligands (the MHC Class I polypeptide-related sequences (MIC) A andB, and UL16-binding proteins (ULBP)1–6) induced by cellular stress to promote recognition cells perturbed by malignant transformation or microbial infection. Studies into human cytomegalovirus (HCMV) have aided both the identification and characterization of NKG2D ligands (NKG2DLs). HCMV immediate early (IE) gene up regulates NKGDLs, and we now describe the differential activation of ULBP2 and MICA/B by IE1 and IE2 respectively. Despite activation by IE functions, HCMV effectively suppressed cell surface expression of NKGDLs through both the early and late phases of infection. The immune evasion functions UL16, UL142, and microRNA(miR)-UL112 are known to target NKG2DLs. While infection with a UL16 deletion mutant caused the expected increase in MICB and ULBP2 cell surface expression, deletion of UL142 did not have a similar impact on its target, MICA. We therefore performed a systematic screen of the viral genome to search of addition functions that targeted MICA. US18 and US20 were identified as novel NK cell evasion functions capable of acting independently to promote MICA degradation by lysosomal degradation. The most dramatic effect on MICA expression was achieved when US18 and US20 acted in concert. US18 and US20 are the first members of the US12 gene family to have been assigned a function. The US12 family has 10 members encoded sequentially through US12–US21; a genetic arrangement, which is suggestive of an ‘accordion’ expansion of an ancestral gene in response to a selective pressure. This expansion must have be an ancient event as the whole family is conserved across simian cytomegaloviruses from old world monkeys. The evolutionary benefit bestowed by the combinatorial effect of US18 and US20 on MICA may have contributed to sustaining the US12 gene family

Association of early life factors and acute lymphoblastic leukaemia in childhood: historical cohort study

In a historical cohort study of all singleton live births in Northern Ireland from 1971–86 (n=434 933) associations between early life factors and childhood acute lymphoblastic leukaemia were investigated. Multivariable analyses showed a positive association between high paternal age (⩾35 years) and acute lymphoblastic leukaemia (relative risk=1.49; 95% confidence interval (CI)=0.96–2.31) but no association with maternal age. High birth weight (⩾3500 g) was positively associated with acute lymphoblastic leukaemia (relative risk=1.66; 95% CI=1.18–2.33). Children of mothers with a previous miscarriage or increased gestation (⩾40 weeks) had reduced risks of ALL (respective relative risks=0.49; 95% CI=0.29–0.80, and 0.67; 95% CI=0.48–0.94). Children born into more crowded households (⩾1 person per room) had substantially lower risks than children born into less crowded homes with also some evidence of a lower risk for children born into homes with three adults (relative risks=0.56; 95% CI=0.35–0.91 and 0.58; 95% CI=0.21–1.61 respectively). These findings indicate that several early life factors, including living conditions in childhood and maternal miscarriage history, influence risk of acute lymphoblastic leukaemia in childhood

T Regulatory Cells in Cord Blood—FOXP3 Demethylation as Reliable Quantitative Marker

Regulatory T-cells (Tregs), characterized as CD4+CD25(hi) T-cells expressing FOXP3, play a crucial role in controlling healthy immune development during early immune maturation. Recently, FOXP3 demethylation was suggested to be a novel marker for natural Tregs in adults. In cord blood, the role and function of Tregs and its demethylation is poorly understood. We assessed FOXP3 demethylation in cord blood in relation to previously used Treg markers such as CD4+CD25(hi), FOXP3 mRNA, protein expression, and suppressive Treg function

Factors Influencing Engagement, Perceived Usefulness and Behavioral Mechanisms Associated with a Text Message Support Program

Introduction Many studies have now demonstrated the efficacy of text messaging in positively changing behaviours. We aimed to identify features and factors that explain the effectiveness of a successful text messaging program in terms of user engagement, perceived usefulness, behavior change and program delivery preferences. Methods Mixed methods qualitative design combining four data sources; (i) analytic data extracted directly from the software system, (ii) participant survey, (iii) focus groups to identify barriers and enablers to implementation and mechanisms of effect and (iv) recruitment screening logs and text message responses to examine engagement. This evaluation was conducted within the TEXT ME trial—a parallel design, single-blind randomized controlled trial (RCT) of 710 patients with coronary heart disease (CHD). Qualitative data were interpreted using inductive thematic analysis. Results 307/352 (87% response rate) of recruited patients with CHD completed the program evaluation survey at six months and 25 participated in a focus group. Factors increasing engagement included (i) ability to save and share messages, (ii) having the support of providers and family, (iii) a feeling of support through participation in the program, (iv) the program being initiated close to the time of a cardiovascular event, (v) personalization of the messages, (vi) opportunity for initial face-to-face contact with a provider and (vii) that program and content was perceived to be from a credible source. Clear themes relating to program delivery were that diet and physical activity messages were most valued, four messages per week was ideal and most participants felt program duration should be provided for at least for six months or longer. Conclusions This study provides context and insight into the factors influencing consumer engagement with a text message program aimed at improving health-related behavior. The study suggests program components that may enhance potential success but will require integration at the development stage to optimize up-scaling

Bayesian Orthogonal Least Squares (BOLS) algorithm for reverse engineering of gene regulatory networks

<p>Abstract</p> <p>Background</p> <p>A reverse engineering of gene regulatory network with large number of genes and limited number of experimental data points is a computationally challenging task. In particular, reverse engineering using linear systems is an underdetermined and ill conditioned problem, i.e. the amount of microarray data is limited and the solution is very sensitive to noise in the data. Therefore, the reverse engineering of gene regulatory networks with large number of genes and limited number of data points requires rigorous optimization algorithm.</p> <p>Results</p> <p>This study presents a novel algorithm for reverse engineering with linear systems. The proposed algorithm is a combination of the orthogonal least squares, second order derivative for network pruning, and Bayesian model comparison. In this study, the entire network is decomposed into a set of small networks that are defined as unit networks. The algorithm provides each unit network with P(D|H_i), which is used as confidence level. The unit network with higher P(D|H_i) has a higher confidence such that the unit network is correctly elucidated. Thus, the proposed algorithm is able to locate true positive interactions using P(D|H_i), which is a unique property of the proposed algorithm.</p> <p>The algorithm is evaluated with synthetic and <it>Saccharomyces cerevisiae </it>expression data using the dynamic Bayesian network. With synthetic data, it is shown that the performance of the algorithm depends on the number of genes, noise level, and the number of data points. With Yeast expression data, it is shown that there is remarkable number of known physical or genetic events among all interactions elucidated by the proposed algorithm.</p> <p>The performance of the algorithm is compared with Sparse Bayesian Learning algorithm using both synthetic and <it>Saccharomyces cerevisiae </it>expression data sets. The comparison experiments show that the algorithm produces sparser solutions with less false positives than Sparse Bayesian Learning algorithm.</p> <p>Conclusion</p> <p>From our evaluation experiments, we draw the conclusion as follows: 1) Simulation results show that the algorithm can be used to elucidate gene regulatory networks using limited number of experimental data points. 2) Simulation results also show that the algorithm is able to handle the problem with noisy data. 3) The experiment with Yeast expression data shows that the proposed algorithm reliably elucidates known physical or genetic events. 4) The comparison experiments show that the algorithm more efficiently performs than Sparse Bayesian Learning algorithm with noisy and limited number of data.</p

Expression and genomic analysis of midasin, a novel and highly conserved AAA protein distantly related to dynein

BACKGROUND: The largest open reading frame in the Saccharomyces genome encodes midasin (MDN1p, YLR106p), an AAA ATPase of 560 kDa that is essential for cell viability. Orthologs of midasin have been identified in the genome projects for Drosophila, Arabidopsis, and Schizosaccharomyces pombe. RESULTS: Midasin is present as a single-copy gene encoding a well-conserved protein of ~600 kDa in all eukaryotes for which data are available. In humans, the gene maps to 6q15 and encodes a predicted protein of 5596 residues (632 kDa). Sequence alignments of midasin from humans, yeast, Giardia and Encephalitozoon indicate that its domain structure comprises an N-terminal domain (35 kDa), followed by an AAA domain containing six tandem AAA protomers (~30 kDa each), a linker domain (260 kDa), an acidic domain (~70 kDa) containing 35–40% aspartate and glutamate, and a carboxy-terminal M-domain (30 kDa) that possesses MIDAS sequence motifs and is homologous to the I-domain of integrins. Expression of hemagglutamin-tagged midasin in yeast demonstrates a polypeptide of the anticipated size that is localized principally in the nucleus. CONCLUSIONS: The highly conserved structure of midasin in eukaryotes, taken in conjunction with its nuclear localization in yeast, suggests that midasin may function as a nuclear chaperone and be involved in the assembly/disassembly of macromolecular complexes in the nucleus. The AAA domain of midasin is evolutionarily related to that of dynein, but it appears to lack a microtubule-binding site

DSIF and RNA Polymerase II CTD Phosphorylation Coordinate the Recruitment of Rpd3S to Actively Transcribed Genes

Histone deacetylase Rpd3 is part of two distinct complexes: the large (Rpd3L) and small (Rpd3S) complexes. While Rpd3L targets specific promoters for gene repression, Rpd3S is recruited to ORFs to deacetylate histones in the wake of RNA polymerase II, to prevent cryptic initiation within genes. Methylation of histone H3 at lysine 36 by the Set2 methyltransferase is thought to mediate the recruitment of Rpd3S. Here, we confirm by ChIP–Chip that Rpd3S binds active ORFs. Surprisingly, however, Rpd3S is not recruited to all active genes, and its recruitment is Set2-independent. However, Rpd3S complexes recruited in the absence of H3K36 methylation appear to be inactive. Finally, we present evidence implicating the yeast DSIF complex (Spt4/5) and RNA polymerase II phosphorylation by Kin28 and Ctk1 in the recruitment of Rpd3S to active genes. Taken together, our data support a model where Set2-dependent histone H3 methylation is required for the activation of Rpd3S following its recruitment to the RNA polymerase II C-terminal domain

Memory in Microbes: Quantifying History-Dependent Behavior in a Bacterium

Memory is usually associated with higher organisms rather than bacteria. However, evidence is mounting that many regulatory networks within bacteria are capable of complex dynamics and multi-stable behaviors that have been linked to memory in other systems. Moreover, it is recognized that bacteria that have experienced different environmental histories may respond differently to current conditions. These “memory” effects may be more than incidental to the regulatory mechanisms controlling acclimation or to the status of the metabolic stores. Rather, they may be regulated by the cell and confer fitness to the organism in the evolutionary game it participates in. Here, we propose that history-dependent behavior is a potentially important manifestation of memory, worth classifying and quantifying. To this end, we develop an information-theory based conceptual framework for measuring both the persistence of memory in microbes and the amount of information about the past encoded in history-dependent dynamics. This method produces a phenomenological measure of cellular memory without regard to the specific cellular mechanisms encoding it. We then apply this framework to a strain of Bacillus subtilis engineered to report on commitment to sporulation and degradative enzyme (AprE) synthesis and estimate the capacity of these systems and growth dynamics to ‘remember’ 10 distinct cell histories prior to application of a common stressor. The analysis suggests that B. subtilis remembers, both in short and long term, aspects of its cell history, and that this memory is distributed differently among the observables. While this study does not examine the mechanistic bases for memory, it presents a framework for quantifying memory in cellular behaviors and is thus a starting point for studying new questions about cellular regulation and evolutionary strategy