Chronic Toxoplasma gondii in Nurr1-Null Heterozygous Mice Exacerbates Elevated Open Field Activity

Latent infection with Toxoplasma gondii is common in humans (approximately 30% of the global population) and is a significant risk factor for schizophrenia. Since prevalence of T. gondii infection is far greater than prevalence of schizophrenia (0.5-1%), genetic risk factors are likely also necessary to contribute to schizophrenia. To test this concept in an animal model, Nurr1-null heterozygous (+/-) mice and wild-type (+/+) mice were evaluate using an emergence test, activity in an open field and with a novel object, response to bobcat urine and prepulse inhibition of the acoustic startle response (PPI) prior to and 6 weeks after infection with T. gondii. In the emergence test, T. gondii infection significantly decreased the amount of time spent in the cylinder. Toxoplasma gondii infection significantly elevated open field activity in both +/+ and +/- mice but this increase was significantly exacerbated in +/- mice. T. gondii infection reduced PPI in male +/- mice but this was not statistically significant. Aversion to bobcat urine was abolished by T. gondii infection in +/+ mice. In female +/- mice, aversion to bobcat urine remained after T. gondii infection while the male +/- mice showed no aversion to bobcat urine. Antibody titers of infected mice were a critical variable associated with changes in open field activity, such that an inverted U shaped relationship existed between antibody titers and the percent change in open field activity with a significant increase in activity at low and medium antibody titers but no effect at high antibody titers. These data demonstrate that the Nurr1 +/- genotype predisposes mice to T. gondii-induced alterations in behaviors that involve dopamine neurotransmission and are associated with symptoms of schizophrenia. We propose that these alterations in murine behavior were due to further exacerbation of the altered dopamine neurotransmission in Nurr1 +/- mice.     

Genetic Ablation of Butyrate Utilization Attenuates Gastrointestinal Salmonella Disease

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Severe acute respiratory syndrome coronavirus gene 7 products contribute to virus-induced apoptosis

The proteins encoded by gene 7 of the severe acute respiratory syndrome coronavirus (SARS-CoV) have been demonstrated to have proapoptotic activity when expressed from cDNA but appear to be dispensable for virus replication. Recombinant SARS-CoVs bearing deletions in gene 7 were used to assess the contribution of gene 7 to virus replication and apoptosis in several transformed cell lines, as well as to replication and pathogenesis in golden Syrian hamsters. Deletion of gene 7 had no effect on SARS-CoV replication in transformed cell lines, nor did it alter the induction of early apoptosis markers such as annexin V binding and activation of caspase 3. However, viruses with gene 7 disruptions were not as efficient as wild-type virus in inducing DNA fragmentation, as judged by terminal deoxynucleotidyltransferase-mediated dUTP-biotin nick end labeling (TUNEL) staining, indicating that the gene 7 products do contribute to virus-induced apoptosis. Disruption of gene 7 did not affect virus replication or morbidity in golden Syrian hamsters, suggesting that the gene 7 products are not required for acute infection in vivo. The data indicate that open reading frames 7a and 7b contribute to but are not solely responsible for the apoptosis seen in SARS-CoV-infected cells.     

Bayesian meta-analysis models for microarray data: a comparative study

Background

With the growing abundance of microarray data, statistical methods are increasingly needed to integrate results across studies. Two common approaches for meta-analysis of microarrays include either combining gene expression measures across studies or combining summaries such as p-values, probabilities or ranks. Here, we compare two Bayesian meta-analysis models that are analogous to these methods.

Results

Two Bayesian meta-analysis models for microarray data have recently been introduced. The first model combines standardized gene expression measures across studies into an overall mean, accounting for inter-study variability, while the second combines probabilities of differential expression without combining expression values. Both models produce the gene-specific posterior probability of differential expression, which is the basis for inference. Since the standardized expression integration model includes inter-study variability, it may improve accuracy of results versus the probability integration model. However, due to the small number of studies typical in microarray meta-analyses, the variability between studies is challenging to estimate. The probability integration model eliminates the need to model variability between studies, and thus its implementation is more straightforward. We found in simulations of two and five studies that combining probabilities outperformed combining standardized gene expression measures for three comparison values: the percent of true discovered genes in meta-analysis versus individual studies; the percent of true genes omitted in meta-analysis versus separate studies, and the number of true discovered genes for fixed levels of Bayesian false discovery. We identified similar results when pooling two independent studies of Bacillus subtilis. We assumed that each study was produced from the same microarray platform with only two conditions: a treatment and control, and that the data sets were pre-scaled.

Conclusion

The Bayesian meta-analysis model that combines probabilities across studies does not aggregate gene expression measures, thus an inter-study variability parameter is not included in the model. This results in a simpler modeling approach than aggregating expression measures, which accounts for variability across studies. The probability integration model identified more true discovered genes and fewer true omitted genes than combining expression measures, for our data sets.     

Mixed-stock aging analysis reveals variable sea turtle maturity rates in a recovering population

Quantifying demographic parameters and variable vital rates, such as somatic growth rates, time to maturity, and reproductive longevity, is important for effective management of threatened and endangered populations such as sea turtles (Cheloniidae). To address these knowledge gaps, we applied skeletochronology to analyze and compare somatic growth rates and variation in life-history traits such as age and size at sexual maturity for 65 green turtles (Chelonia mydas) in the eastern Pacific Ocean (EP), along the west coast of the United States; turtles belonged to ≥2 nesting subpopulations that differed in body size (mean nesting size). Green turtles in the EP spend approximately 5 years in the oceanic stage before recruiting to nearshore habitats, males may be smaller and younger than females at maturation (x̅ = 17.7 ± 5.5 yr vs. 28.0 ± 8.2 yr), and younger age at sexual maturity was associated with smaller size at sexual maturity, suggesting that mean nesting body size may be reflective of maturation timing for subpopulations. Smaller body sizes for females nesting at Michoacán, Mexico (continental) rookeries, yielded a younger predicted age at sexual maturity (x̅ = ~17 yr) compared to females from Revillagigedo Islands, Mexico rookeries, which displayed larger body sizes and older age at sexual maturity (x̅ = ~30 yr). We consider possible mechanisms driving the observed divergence in life-history traits, including the possibility that earlier maturation (reduced generation length) for turtles in the Michoacán nesting subpopulation may be a response to intense harvesting in the past 50 years, and consideration of such anthropogenic impacts is warranted by population managers. Finally, our results indicate green turtles moved into nearshore neritic habitats at a young age (4–6 yr), emphasize the importance of protecting neritic habitats along the southwestern United States and northwestern Mexican coasts, and encourage the incorporation of variable maturation time in population recovery assessments.     

Innate immune activation by inhaled lipopolysaccharide, independent of oxidative stress, exacerbates silica-induced pulmonary fibrosis in mice

Acute exacerbations of pulmonary fibrosis are characterized by rapid decrements in lung function. Environmental factors that may contribute to acute exacerbations remain poorly understood. We have previously demonstrated that exposure to inhaled lipopolysaccharide (LPS) induces expression of genes associated with fibrosis. To address whether exposure to LPS could exacerbate fibrosis, we exposed male C57BL/6 mice to crystalline silica, or vehicle, followed 28 days later by LPS or saline inhalation. We observed that mice receiving both silica and LPS had significantly more total inflammatory cells, more whole lung lavage MCP-1, MIP-2, KC and IL-1β, more evidence of oxidative stress and more total lung hydroxyproline than mice receiving either LPS alone, or silica alone. Blocking oxidative stress with N-acetylcysteine attenuated whole lung inflammation but had no effect on total lung hydroxyproline. These observations suggest that exposure to innate immune stimuli, such as LPS in the environment, may exacerbate stable pulmonary fibrosis via mechanisms that are independent of inflammation and oxidative stress.     

The effect of cost surface parameterization on landscape resistance estimates

A cost or resistance surface is a representation of a landscape's permeability to animal movement or gene flow and is a tool for measuring functional connectivity in landscape ecology and genetics studies. Parameterizing cost surfaces by assigning weights to different landscape elements has been challenging however, because true costs are rarely known; thus, expert opinion is often used to derive relative weights. Assigning weights would be made easier if the sensitivity of different landscape resistance estimates to relative costs was known. We carried out a sensitivity analysis of three methods to parameterize a cost surface and two models of landscape permeability: least cost path and effective resistance. We found two qualitatively different responses to varying cost weights: linear and asymptotic changes. The most sensitive models (i.e. those leading to linear change) were accumulated least cost and effective resistance estimates on a surface coded as resistance (i.e. where high-quality elements were held constant at a low-value, and low-quality elements were varied at higher values). All other cost surface scenarios led to asymptotic change. Developing a cost surface that produces a linear response of landscape resistance estimates to cost weight variation will improve the accuracy of functional connectivity estimates, especially when cost weights are selected through statistical model fitting procedures. On the other hand, for studies where cost weights are unknown and model selection is not being used, methods where resistance estimates vary asymptotically with cost weights may be more appropriate, because of their relative insensitivity to parameterization.     

Plexin-B2 and Plexin-D1 in Dendritic Cells: Expression and IL-12/IL-23p40 Production

Plexins are a family of genes (A,B,C, and D) that are expressed in many organ systems. Plexins expressed in the immune system have been implicated in cell movement and cell-cell interaction during the course of an immune response. In this study, the expression pattern of Plexin-B2 and Plexin-D1 in dendritic cells (DCs), which are central in immune activation, was investigated. Plexin-B2 and Plexin-D1 are reciprocally expressed in myeloid and plasmacytoid DC populations. Plasmacytoid DCs have high Plexin-B2 but low Plexin-D1, while the opposite is true of myeloid DCs. Expression of Plexin-B2 and Plexin-D1 is modulated upon activation of DCs by TLR ligands, TNFα, and anti-CD40, again in a reciprocal fashion. Semaphorin3E, a ligand for Plexin-D1 and Plexin-B2, is expressed by T cells, and interestingly, is dramatically higher on Th2 cells and on DCs. The expression of Plexins and their ligands on DCs and T cells suggest functional relevance. To explore this, we utilized chimeric mice lacking Plxnb2 or Plxnd1. Absence of Plexin-B2 and Plexin-D1 on DCs did not affect the ability of these cells to upregulate costimulatory molecules or the ability of these cells to activate antigen specific T cells. Additionally, Plexin-B2 and Plexin-D1 were dispensable for chemokine-directed in-vitro migration of DCs towards key DC chemokines, CXCL12 and CCL19. However, the absence of either Plexin-B2 or Plexin-D1 on DCs leads to constitutive expression of IL-12/IL-23p40. This is the first report to show an association between Plexin-B2 and Plexin-D1 with the negative regulation of IL-12/IL-23p40 in DCs. This work also shows the presence of Plexin-B2 and Plexin-D1 on mouse DC subpopulations, and indicates that these two proteins play a role in IL-12/IL-23p40 production that is likely to impact the immune response.     

Microbial communities are indicators of parasite infection status

Growing evidence suggests that microbiomes have been shaping the evolutionary pathways of macroorganisms for millennia and that these tiny symbionts can influence, and possibly even control, species interactions like host–parasite relationships. Yet, while studies have investigated host–parasites and microbiomes separately, little has been done to understand all three groups synergistically. Here, we collected infected and uninfected Eurypanopeus depressus crab hosts from a coastal North Carolina oyster reef three times over 4 months. Infected crabs demonstrated an external stage of the rhizocephalan parasite, Loxothylacus panopaei. Community analyses revealed that microbial richness and diversity were significantly different among tissue types (uninfected crab, infected crab, parasite externae and parasite larvae) and over time (summer and fall). Specifically, the microbial communities from parasite externae and larvae had similar microbiomes that were consistent through time. Infected crabs demonstrated microbial communities spanning those of their host and parasite, while uninfected crabs showed more distinctive communities with greater variability over time. Microbial communities were also found to be indicators of early-stage infections. Resolving the microbial community composition of a host and its parasite is an important step in understanding the microbiome's role in the host–parasite relationship and determining how this tripartite relationship impacts coevolutionary processes.     

Nutlin-3a: A Potential Therapeutic Opportunity for TP53 Wild-Type Ovarian Carcinomas

Epithelial ovarian cancer is a diverse molecular and clinical disease, yet standard treatment is the same for all subtypes. TP53 mutations represent a node of divergence in epithelial ovarian cancer histologic subtypes and may represent a therapeutic opportunity in subtypes expressing wild type, including most low-grade ovarian serous carcinomas, ovarian clear cell carcinomas and ovarian endometrioid carcinomas, which represent approximately 25% of all epithelial ovarian cancer. We therefore sought to investigate Nutlin-3a—a therapeutic which inhibits MDM2, activates wild-type p53, and induces apoptosis—as a therapeutic compound for TP53 wild-type ovarian carcinomas. Fifteen epithelial ovarian cancer cell lines of varying histologic subtypes were treated with Nutlin-3a with determination of IC₅₀ values. Western Blot (WB) and quantitative real-time polymerase chain reaction (qRT-PCR) analyses quantified MDM2, p53, and p21 expression after Nutlin-3a treatment. DNA from 15 cell lines was then sequenced for TP53 mutations in exons 2-11 including intron-exon boundaries. Responses to Nutlin-3a were dependent upon TP53 mutation status. By qRT-PCR and WB, levels of MDM2 and p21 were upregulated in wild-type TP53 sensitive cell lines, and p21 induction was reduced or absent in mutant cell lines. Annexin V assays demonstrated apoptosis in sensitive cell lines treated with Nutlin-3a. Thus, Nutlin-3a could be a potential therapeutic agent for ovarian carcinomas expressing wild-type TP53 and warrants further investigation.