Manganese exposure in juvenile C57BL/6 mice increases glial inflammatory responses in the substantia nigra following infection with H1N1 influenza virus.

Infection with Influenza A virus can lead to the development of encephalitis and subsequent neurological deficits ranging from headaches to neurodegeneration. Post-encephalitic parkinsonism has been reported in surviving patients of H1N1 infections, but not all cases of encephalitic H1N1 infection present with these neurological symptoms, suggesting that interactions with an environmental neurotoxin could promote more severe neurological damage. The heavy metal, manganese (Mn), is a potential interacting factor with H1N1 because excessive exposure early in life can induce long-lasting effects on neurological function through inflammatory activation of glial cells. In the current study, we used a two-hit model of neurotoxin-pathogen exposure to examine whether exposure to Mn during juvenile development would induce a more severe neuropathological response following infection with H1N1 in adulthood. To test this hypothesis, C57BL/6 mice were exposed to MnCl2 in drinking water (50 mg/kg/day) for 30 days from days 21-51 postnatal, then infected intranasally with H1N1 three weeks later. Analyses of dopaminergic neurons, microglia and astrocytes in basal ganglia indicated that although there was no significant loss of dopaminergic neurons within the substantia nigra pars compacta, there was more pronounced activation of microglia and astrocytes in animals sequentially exposed to Mn and H1N1, as well as altered patterns of histone acetylation. Whole transcriptome Next Generation Sequencing (RNASeq) analysis was performed on the substantia nigra and revealed unique patterns of gene expression in the dual-exposed group, including genes involved in antioxidant activation, mitophagy and neurodegeneration. Taken together, these results suggest that exposure to elevated levels of Mn during juvenile development could sensitize glial cells to more severe neuro-immune responses to influenza infection later in life through persistent epigenetic changes

Iterative feature removal yields highly discriminative pathways

BACKGROUND: We introduce Iterative Feature Removal (IFR) as an unbiased approach for selecting features with diagnostic capacity from large data sets. The algorithm is based on recently developed tools in machine learning that are driven by sparse feature selection goals. When applied to genomic data, our method is designed to identify genes that can provide deeper insight into complex interactions while remaining directly connected to diagnostic utility. We contrast this approach with the search for a minimal best set of discriminative genes, which can provide only an incomplete picture of the biological complexity. RESULTS: Microarray data sets typically contain far more features (genes) than samples. For this type of data, we demonstrate that there are many equivalently-predictive subsets of genes. We iteratively train a classifier using features identified via a sparse support vector machine. At each iteration, we remove all the features that were previously selected. We found that we could iterate many times before a sustained drop in accuracy occurs, with each iteration removing approximately 30 genes from consideration. The classification accuracy on test data remains essentially flat even as hundreds of top-genes are removed. Our method identifies sets of genes that are highly predictive, even when comprised of genes that individually are not. Through automated and manual analysis of the selected genes, we demonstrate that the selected features expose relevant pathways that other approaches would have missed. CONCLUSIONS: Our results challenge the paradigm of using feature selection techniques to design parsimonious classifiers from microarray and similar high-dimensional, small-sample-size data sets. The fact that there are many subsets of genes that work equally well to classify the data provides a strong counter-result to the notion that there is a small number of “top genes” that should be used to build classifiers. In our results, the best classifiers were formed using genes with limited univariate power, thus illustrating that deeper mining of features using multivariate techniques is important

Genetic identification of unique immunological responses in mice infected with virulent and attenuated Francisella tularensis

Francisella tularensis is a category A select agent based on its infectivity and virulence but disease mechanisms in infection remain poorly understood. Murine pulmonary models of infection were therefore employed to assess and compare dissemination and pathology and to elucidate the host immune response to infection with the highly virulent Type A F. tularensis strain Schu4 versus the less virulent Type B live vaccine strain (LVS). We found that dissemination and pathology in the spleen was significantly greater in mice infected with F. tularensis Schu4 compared to mice infected with F. tularensis LVS. Using gene expression rofiling to compare the response to infection with the two F. tularensis strains, we found that there were significant differences in the expression of genes involved in the apoptosis pathway, antigen processing and presentation pathways, and inflammatory response pathways in mice infected with Schu4 when compared to LVS. These transcriptional differences coincided with marked differences in dissemination and severity of organ lesions in mice infected with the Schu4 and LVS strains. Therefore, these findings indicate that altered apoptosis, antigen presentation and production of inflammatory mediators explain the differences in pathogenicity of F. tularensis Schu4 and LVS

<it>Mycobacterium tuberculosis </it>septum site determining protein, Ssd encoded by <it>rv3660c</it>, promotes filamentation and elicits an alternative metabolic and dormancy stress response

<p>Abstract</p> <p>Background</p> <p>Proteins that are involved in regulation of cell division and cell cycle progression remain undefined in <it>Mycobacterium tuberculosis</it>. In addition, there is a growing appreciation that regulation of cell replication at the point of division is important in establishing a non-replicating persistent state. Accordingly, the objective of this study was to use a systematic approach consisting of consensus-modeling bioinformatics, ultrastructural analysis, and transcriptional mapping to identify septum regulatory proteins that participate in adaptive metabolic responses in <it>M. tuberculosis</it>.</p> <p>Results</p> <p>Septum site determining protein (Ssd), encoded by <it>rv3660c </it>was discovered to be an ortholog of septum site regulating proteins in actinobacteria by bioinformatics analysis. Increased expression of <it>ssd </it>in <it>M. smegmatis </it>and <it>M. tuberculosis </it>inhibited septum formation resulting in elongated cells devoid of septa. Transcriptional mapping in <it>M. tuberculosis </it>showed that increased <it>ssd </it>expression elicited a unique response including the dormancy regulon and alternative sigma factors that are thought to play a role in adaptive metabolism. Disruption of <it>rv3660c </it>by transposon insertion negated the unique transcriptional response and led to a reduced bacterial length.</p> <p>Conclusions</p> <p>This study establishes the first connection between a septum regulatory protein and induction of alternative metabolism consisting of alternative sigma factors and the dormancy regulon that is associated with establishing a non-replicating persistent intracellular lifestyle. The identification of a regulatory component involved in cell cycle regulation linked to the dormancy response, whether directly or indirectly, provides a foundation for additional studies and furthers our understanding of the complex mechanisms involved in establishing a non-replicating state and resumption of growth.</p

Transient <i>In Vivo</i> Resistance Mechanisms of <i>Burkholderia pseudomallei</i> to Ceftazidime and Molecular Markers for Monitoring Treatment Response

<div><p>Much is known about the mode of action of drugs and resistance mechanisms under laboratory growth conditions, but research on the bacterial transcriptional response to drug pressure <i>in vivo</i> or efficacious mode of action and transient resistance mechanisms of clinically employed drugs is limited. Accordingly, to assess active alternative metabolism and transient resistance mechanisms, and identify molecular markers of treatment response, the <i>in vivo</i> transcriptional response of <i>Burkholderia pseudomallei</i> 1026b to treatment with ceftazidime in infected lungs was compared to the <i>in vitro</i> bacterial response in the presence of drug. There were 1,688 transcriptionally active bacterial genes identified that were unique to <i>in vivo</i> treated conditions. Of the <i>in vivo</i> transcriptionally active bacterial genes, 591 (9.4% coding capacity) genes were differentially expressed by ceftazidime treatment. In contrast, only 186 genes (2.7% coding capacity) were differentially responsive to ceftazidime treatment under <i>in vitro</i> culturing conditions. Within the genes identified were alternative PBP proteins that may compensate for target inactivation and transient resistance mechanisms, such as β-lactamses that may influence the potency of ceftazidime. This disparate observation is consistent with the thought that the host environment significantly alters the bacterial metabolic response to drug exposure compared to the response observed under <i>in vitro</i> growth. Notably, this study revealed 184 bacterial genes and ORFs that were unique to <i>in vivo</i> ceftazidime treatment and thus provide candidate molecular markers for treatment response. This is the first report of the unique transcriptional response of <i>B</i>. <i>pseudomallei</i> from host tissues in an animal model of infection and elucidates the <i>in vivo</i> metabolic vulnerabilities, which is important in terms of defining the efficacious mode of action and transient resistance mechanisms of a frontline meliodosis chemotherapeutic, and biomarkers for monitoring treatment outcome.</p></div

Ceftazidime treatment of B. pseudomallei 1026b <i>In vitro</i> and <i>In vivo</i>.

<p>(A) Mid-log phase <i>B</i>. <i>pseudomallei</i> 1026b was treated with 2X MIC (4μg/ml) for two hours and cells harvested for total RNA and CFU determination. (B) 5–6 week old Balb/c mice were infected with 5000 CFU <i>B</i>. <i>pseudomallei</i> 1026b. Mice were treated with 200 mg/kg ceftazidime intraperitoneally at 36 hours post infection and received a second dose at 48 hours post infection. Mice were euthanized and lungs harvested at 36, 48, and 60 hours post infection for total RNA and for CFU determination. Significance is determined by a p value <0.01 by Two-way ANOVA when compared to untreated control. (C) Ceftazidime treated mice were monitored for survival after withdrawal of treatment.</p

Molecular markers unique to <i>in vivo</i> infection.

<p>Molecular markers unique to <i>in vivo</i> infection.</p

Molecular markers ceftazidime treatment <i>in vivo</i>.

<p>Molecular markers ceftazidime treatment <i>in vivo</i>.</p