Genome-Wide Screen of Three Herpesviruses for Protein Subcellular Localization and Alteration of PML Nuclear Bodies

Herpesviruses are large, ubiquitous DNA viruses with complex host interactions, yet many of the proteins encoded by these viruses have not been functionally characterized. As a first step in functional characterization, we determined the subcellular localization of 234 epitope-tagged proteins from herpes simplex virus, cytomegalovirus, and Epstein–Barr virus. Twenty-four of the 93 proteins with nuclear localization formed subnuclear structures. Twelve of these localized to the nucleolus, and five at least partially localized with promyelocytic leukemia (PML) bodies, which are known to suppress viral lytic infection. In addition, two proteins disrupted Cajal bodies, and 19 of the nuclear proteins significantly decreased the number of PML bodies per cell, including six that were shown to be SUMO-modified. These results have provided the first functional insights into over 120 previously unstudied proteins and suggest that herpesviruses employ multiple strategies for manipulating nuclear bodies that control key cellular processes

Critical Assessment of Metagenome Interpretation:A benchmark of metagenomics software

International audienceIn metagenome analysis, computational methods for assembly, taxonomic profilingand binning are key components facilitating downstream biological datainterpretation. However, a lack of consensus about benchmarking datasets andevaluation metrics complicates proper performance assessment. The CriticalAssessment of Metagenome Interpretation (CAMI) challenge has engaged the globaldeveloper community to benchmark their programs on datasets of unprecedentedcomplexity and realism. Benchmark metagenomes were generated from newlysequenced ~700 microorganisms and ~600 novel viruses and plasmids, includinggenomes with varying degrees of relatedness to each other and to publicly availableones and representing common experimental setups. Across all datasets, assemblyand genome binning programs performed well for species represented by individualgenomes, while performance was substantially affected by the presence of relatedstrains. Taxonomic profiling and binning programs were proficient at high taxonomicranks, with a notable performance decrease below the family level. Parametersettings substantially impacted performances, underscoring the importance ofprogram reproducibility. While highlighting current challenges in computationalmetagenomics, the CAMI results provide a roadmap for software selection to answerspecific research questions

Physiological Correlates of Volunteering

We review research on physiological correlates of volunteering, a neglected but promising research field. Some of these correlates seem to be causal factors influencing volunteering. Volunteers tend to have better physical health, both self-reported and expert-assessed, better mental health, and perform better on cognitive tasks. Research thus far has rarely examined neurological, neurochemical, hormonal, and genetic correlates of volunteering to any significant extent, especially controlling for other factors as potential confounds. Evolutionary theory and behavioral genetic research suggest the importance of such physiological factors in humans. Basically, many aspects of social relationships and social activities have effects on health (e.g., Newman and Roberts 2013; Uchino 2004), as the widely used biopsychosocial (BPS) model suggests (Institute of Medicine 2001). Studies of formal volunteering (FV), charitable giving, and altruistic behavior suggest that physiological characteristics are related to volunteering, including specific genes (such as oxytocin receptor [OXTR] genes, Arginine vasopressin receptor [AVPR] genes, dopamine D4 receptor [DRD4] genes, and 5-HTTLPR). We recommend that future research on physiological factors be extended to non-Western populations, focusing specifically on volunteering, and differentiating between different forms and types of volunteering and civic participation

TRY plant trait database – enhanced coverage and open access

Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Human Immunodeficiency Virus (HIV)-Specific Gamma Interferon Secretion Directed against All Expressed HIV Genes: Relationship to Rate of CD4 Decline

Immune responses to human immunodeficiency virus (HIV) are detected at all stages of infection and are believed to be responsible for controlling viremia. This study seeks to determine whether gamma interferon (IFN-γ)-secreting HIV-specific T-cell responses influence disease progression as defined by the rate of CD4 decline. The study population consisted of 31 subjects naïve to antiretroviral therapy. All were monitored clinically for a median of 24 months after the time they were tested for HIV-specific responses. The rate of CD4(+)-T-cell loss was calculated for all participants from monthly CD4 counts. Within this population, 17 subjects were classified as typical progressors, 6 subjects were classified as fast progressors, and 8 subjects were classified as slow progressors. Peripheral blood mononuclear cells were screened for HIV-specific IFN-γ responses to all expressed HIV genes. Among the detected immune responses, 48% of the recognized peptides were encoded by Gag and 19% were encoded by Nef gene products. Neither the breadth nor the magnitude of HIV-specific responses correlated with the viral load or rate of CD4 decline. The breadth and magnitude of HIV-specific responses did not differ significantly among typical, fast, and slow progressors. These results support the conclusion that although diverse HIV-specific IFN-γ-secreting responses are mounted during the asymptomatic phase, these responses do not seem to modulate disease progression rates

An Oxygen-Sensing Two-Component System in the Burkholderia cepacia Complex Regulates Biofilm, Intracellular Invasion, and Pathogenicity

Burkholderia dolosa is a member of the Burkholderia cepacia complex (BCC), which is a group of bacteria that cause chronic lung infection in patients with cystic fibrosis (CF) and can be associated with outbreaks carrying high morbidity and mortality. While investigating the genomic diversity of B. dolosa strains collected from an outbreak among CF patients, we previously identified fixL as a gene showing signs of strong positive selection. This gene has homology to fixL of the rhizobial FixL/FixJ two-component system. The goals of this study were to determine the functions of FixLJ and their role in virulence in B. dolosa. We generated a fixLJ deletion mutant and complemented controls in B. dolosa strain AU0158. Using a fixK-lacZ reporter we found that FixLJ was activated in low oxygen in multiple BCC species. In a murine pneumonia model, the B. dolosa fixLJ deletion mutant was cleared faster from the lungs and spleen than wild-type B. dolosa strain AU0158 at 7 days post infection. Interestingly, the fixLJ deletion mutant made more biofilm, albeit with altered structure, but was less motile than strain AU0158. Using RNA-seq with in vitro grown bacteria, we found ~11% of the genome was differentially expressed in the fixLJ deletion mutant relative to strain AU0158. Multiple flagella-associated genes were down-regulated in the fixLJ deletion mutant, so we also evaluated virulence of a fliC deletion mutant, which lacks a flagellum. We saw no difference in the ability of the fliC deletion mutant to persist in the murine model relative to strain AU0158, suggesting factors other than flagella caused the phenotype of decreased persistence. We found the fixLJ deletion mutant to be less invasive in human lung epithelial and macrophage-like cells. In conclusion, B. dolosa fixLJ is a global regulator that controls biofilm formation, motility, intracellular invasion/persistence, and virulence

Strains used in this study.

<p>Strains used in this study.</p

<i>B</i>. <i>dolosa</i> virulence is independent of the presence of flagella.

<p>(A) <i>B</i>. <i>dolosa</i> strain AU0158 and its <i>fliC</i> deletion mutant were plated on low-density (0.3%) LB agar and swimming distance was measured after incubation for 48 hours. *P<0.05 by 1-way NOVA with Tukey’s multiple comparison test. Bars represent mean measurements of 3–4 replicates and error bars represent one standard deviation (representative of three independent experiments). (B) Overnight cultures of <i>B</i>. <i>dolosa</i> strain AU0158, the <i>fixLJ</i> deletion mutant, or the <i>fliC</i> deletion mutant were diluted 1:100 in TSB with 1% glucose, incubated for 48 hours, and then assessed for biofilm formation using crystal violet. Bars represent mean measurements of 6 replicates and error bars represent one standard deviation of the data (representative of three independent experiments). (C-D) C57BL/6 mice were intranasally challenged with 4.8 x10⁸ CFU/mouse of strain AU0158 or its <i>fliC</i> deletion mutant. Bacterial loads were measured 7 days after infection in the lungs (C) and spleen (D). Data are derived from one experiment done with 7–8 mice per group. Each point represents one mouse and bars represent medians.</p

The <i>B</i>. <i>dolosa fixLJ</i> deletion mutant is less motile.

<p>(A) <i>B</i>. <i>dolosa</i> strain AU0158, its <i>fixLJ</i> deletion mutant, and the <i>fixLJ</i> deletion mutant complemented with <i>fixLJ</i> under the control of its own promoter or empty vector (EV) were plated on low-density (0.3%) LB agar and swimming distance was measured after incubation for 48 hours. *<i>P</i><0.05 by 1-way ANOVA with Tukey’s multiple comparison test. (B) The <i>B</i>. <i>dolosa fixLJ</i> -deletion mutant complemented with <i>fixLJ</i> under the control of a rhamnose-inducible promoter or empty vector grown in the presence of glucose (0.4%, which represses <i>fixLJ</i> expression) or rhamnose (0.4%). *P<0.05 by 1-way ANOVA with Tukey’s multiple comparison test relative to the complemented strain (Δ<i>fixLJ</i> + <i>fixLJ</i>) grown in rhamnose-containing media. For all panels, bars represent mean measurements of 3–4 replicates and error bars represent one standard deviation (representative of three independent experiments).</p

The <i>B</i>. <i>dolosa fixLJ</i> deletion mutant produces more biofilm by crystal violet staining and has a different biofilm structure.

<p>Biofilm formation of <i>B</i>. <i>dolosa</i> AU0158 constructs on PVC plates as measured by crystal violet staining at 48 hours. (A) <i>B</i>. <i>dolosa</i> strain AU0158 produces less biofilm than its <i>fixLJ</i> deletion mutant. Strains were grown in TSB with 1% glucose at varying inocula. (B) The <i>B</i>. <i>dolosa fixLJ</i> deletion mutant complemented with <i>fixLJ</i> under the control of its own promoter produces less biofilm compared to the strain carrying an empty vector (EV). (C) A <i>B</i>. <i>dolosa fixLJ</i> deletion mutant complemented with <i>fixLJ</i> under the control of a rhamnose-inducible promoter or empty vector grown in LB in the presence of glucose (0.4%, which represses the promoter) or rhamnose (0.4%) and compared to the Δ<i>fixLJ</i> + <i>fixLJ</i> strain grown in rhamnose-containing medium. For panels A-C, bars represent mean measurements of 5–6 replicates and error bars represent one standard deviation (representative of three independent experiments). *P<0.05 compared to AU0158 by 1-way ANOVA with Tukey’s multiple comparison test. Representative mosaic images of biofilms of strain AU0158 (D) and its <i>fixLJ</i> deletion mutant (E) grown on 8-well chamber slides for 48 hours, stained with live/dead stain, and imaged by confocal microscopy. For panels D and E, live bacteria are stained green and dead are red. The inset of panel D shows Z-stack images taken at 1 μm intervals; gridlines denote 5 μm lengths. Images are representative of two independent experiments conducted with four replicates.</p