PKC Signaling Regulates Drug Resistance of the Fungal Pathogen Candida albicans via Circuitry Comprised of Mkc1, Calcineurin, and Hsp90

Fungal pathogens exploit diverse mechanisms to survive exposure to antifungal drugs. This poses concern given the limited number of clinically useful antifungals and the growing population of immunocompromised individuals vulnerable to life-threatening fungal infection. To identify molecules that abrogate resistance to the most widely deployed class of antifungals, the azoles, we conducted a screen of 1,280 pharmacologically active compounds. Three out of seven hits that abolished azole resistance of a resistant mutant of the model yeast Saccharomyces cerevisiae and a clinical isolate of the leading human fungal pathogen Candida albicans were inhibitors of protein kinase C (PKC), which regulates cell wall integrity during growth, morphogenesis, and response to cell wall stress. Pharmacological or genetic impairment of Pkc1 conferred hypersensitivity to multiple drugs that target synthesis of the key cell membrane sterol ergosterol, including azoles, allylamines, and morpholines. Pkc1 enabled survival of cell membrane stress at least in part via the mitogen activated protein kinase (MAPK) cascade in both species, though through distinct downstream effectors. Strikingly, inhibition of Pkc1 phenocopied inhibition of the molecular chaperone Hsp90 or its client protein calcineurin. PKC signaling was required for calcineurin activation in response to drug exposure in S. cerevisiae. In contrast, Pkc1 and calcineurin independently regulate drug resistance via a common target in C. albicans. We identified an additional level of regulatory control in the C. albicans circuitry linking PKC signaling, Hsp90, and calcineurin as genetic reduction of Hsp90 led to depletion of the terminal MAPK, Mkc1. Deletion of C. albicans PKC1 rendered fungistatic ergosterol biosynthesis inhibitors fungicidal and attenuated virulence in a murine model of systemic candidiasis. This work establishes a new role for PKC signaling in drug resistance, novel circuitry through which Hsp90 regulates drug resistance, and that targeting stress response signaling provides a promising strategy for treating life-threatening fungal infections

Unsupervised Bayesian linear unmixing of gene expression microarrays

Background: This paper introduces a new constrained model and the corresponding algorithm, called unsupervised Bayesian linear unmixing (uBLU), to identify biological signatures from high dimensional assays like gene expression microarrays. The basis for uBLU is a Bayesian model for the data samples which are represented as an additive mixture of random positive gene signatures, called factors, with random positive mixing coefficients, called factor scores, that specify the relative contribution of each signature to a specific sample. The particularity of the proposed method is that uBLU constrains the factor loadings to be non-negative and the factor scores to be probability distributions over the factors. Furthermore, it also provides estimates of the number of factors. A Gibbs sampling strategy is adopted here to generate random samples according to the posterior distribution of the factors, factor scores, and number of factors. These samples are then used to estimate all the unknown parameters. Results: Firstly, the proposed uBLU method is applied to several simulated datasets with known ground truth and compared with previous factor decomposition methods, such as principal component analysis (PCA), non negative matrix factorization (NMF), Bayesian factor regression modeling (BFRM), and the gradient-based algorithm for general matrix factorization (GB-GMF). Secondly, we illustrate the application of uBLU on a real time-evolving gene expression dataset from a recent viral challenge study in which individuals have been inoculated with influenza A/H3N2/Wisconsin. We show that the uBLU method significantly outperforms the other methods on the simulated and real data sets considered here. Conclusions: The results obtained on synthetic and real data illustrate the accuracy of the proposed uBLU method when compared to other factor decomposition methods from the literature (PCA, NMF, BFRM, and GB-GMF). The uBLU method identifies an inflammatory component closely associated with clinical symptom scores collected during the study. Using a constrained model allows recovery of all the inflammatory genes in a single factor

Aberrant Cell Cycle and Apoptotic Changes Characterise Severe Influenza A Infection – A Meta-Analysis of Genomic Signatures in Circulating Leukocytes

Influenza A infection is a global disease that has been responsible for four pandemics over the last one hundred years. However, it remains poorly understood as to why some infected individuals succumb to life threatening complications whilst others recover and are relatively unaffected. Using gene-expression analysis of circulating leukocytes, here we show that the progression towards severe influenza A infection is characterised by an abnormal transcriptional reprogramming of cell cycle and apoptosis pathways. In severely infected humans, leukocyte gene-expression profiles display opposing cell cycle activities; an increased aberrant DNA replication in the G1/S phase yet delayed progression in the G2/M phase. In mild infection, cell cycle perturbations are fewer and are integrated with an efficient apoptotic program. Importantly, the loss of integration between cell cycle perturbations and apoptosis marks the transition from a mild viral illness to a severe, life threatening infection. Our findings suggest that circulating immune cells may play a significant role in the evolution of the host response. Further study may reveal alternative host response factors previously unrecognized in the current disease model of influenza

Caveolin-1 protects B6129 mice against Helicobacter pylori gastritis.

Caveolin-1 (Cav1) is a scaffold protein and pathogen receptor in the mucosa of the gastrointestinal tract. Chronic infection of gastric epithelial cells by Helicobacter pylori (H. pylori) is a major risk factor for human gastric cancer (GC) where Cav1 is frequently down-regulated. However, the function of Cav1 in H. pylori infection and pathogenesis of GC remained unknown. We show here that Cav1-deficient mice, infected for 11 months with the CagA-delivery deficient H. pylori strain SS1, developed more severe gastritis and tissue damage, including loss of parietal cells and foveolar hyperplasia, and displayed lower colonisation of the gastric mucosa than wild-type B6129 littermates. Cav1-null mice showed enhanced infiltration of macrophages and B-cells and secretion of chemokines (RANTES) but had reduced levels of CD25+ regulatory T-cells. Cav1-deficient human GC cells (AGS), infected with the CagA-delivery proficient H. pylori strain G27, were more sensitive to CagA-related cytoskeletal stress morphologies ("humming bird") compared to AGS cells stably transfected with Cav1 (AGS/Cav1). Infection of AGS/Cav1 cells triggered the recruitment of p120 RhoGTPase-activating protein/deleted in liver cancer-1 (p120RhoGAP/DLC1) to Cav1 and counteracted CagA-induced cytoskeletal rearrangements. In human GC cell lines (MKN45, N87) and mouse stomach tissue, H. pylori down-regulated endogenous expression of Cav1 independently of CagA. Mechanistically, H. pylori activated sterol-responsive element-binding protein-1 (SREBP1) to repress transcription of the human Cav1 gene from sterol-responsive elements (SREs) in the proximal Cav1 promoter. These data suggested a protective role of Cav1 against H. pylori-induced inflammation and tissue damage. We propose that H. pylori exploits down-regulation of Cav1 to subvert the host's immune response and to promote signalling of its virulence factors in host cells

Adenosine Deaminase Activity Is a Sensitive Marker for the Diagnosis of Tuberculous Pleuritis in Patients with Very Low CD4 Counts

Background: Adenosine Deaminase Activity (ADA) is a commonly used marker for the diagnosis of tuberculous pleural effusion. There has been concern about its usefulness in immunocompromised patients, especially HIV positive patients with very low CD4 counts. The objective of this study was to evaluate the sensitivity of ADA in pleural fluid in patients with low CD4 counts. Materials and Methods: This was a retrospective case control study. Medical files of patients with tuberculous pleuritis and non-tuberculous pleuritis were reviewed. Clinical characteristics, CD4 cell counts in blood and biochemical markers in pleural fluid, including ADA were recorded. Results: One ninety seven tuberculous pleuritis and 40 non- tuberculous pleuritis patients were evaluated. Using the cut-off value of 30 U/L, the overall sensitivity, specificity, positive likelihood ratio, and negative likelihood ratio of ADA was 94%, 95%, 19, and 0.06 respectively. The mean CD4 cell counts among TB pleuritis patients was 29 and 153 cells/microL in patients with CD4 ,50 cells/microL and .50 cells/microL, (p,0.05) respectively. The corresponding mean ADA values for these patients were 76 U/L and 72 U/L respectively (p.0.5). There was no correlation between ADA values and CD4 cell counts (r =20.120, p = 0.369). Conclusion: ADA analysis is a sensitive marker of tuberculous pleuritis even in HIV patients with very low CD4 counts in a high TB endemic region. The ADA assay is inexpensive, rapid, and simple to perform and is of great value for the immediate diagnosis of tuberculous pleuritis while waiting for culture result and this has a positive impact on patient outcome

Integrating Factor Analysis and a Transgenic Mouse Model to Reveal a Peripheral Blood Predictor of Breast Tumors

Abstract Background Transgenic mouse tumor models have the advantage of facilitating controlled in vivo oncogenic perturbations in a common genetic background. This provides an idealized context for generating transcriptome-based diagnostic models while minimizing the inherent noisiness of high-throughput technologies. However, the question remains whether models developed in such a setting are suitable prototypes for useful human diagnostics. We show that latent factor modeling of the peripheral blood transcriptome in a mouse model of breast cancer provides the basis for using computational methods to link a mouse model to a prototype human diagnostic based on a common underlying biological response to the presence of a tumor. Methods We used gene expression data from mouse peripheral blood cell (PBC) samples to identify significantly differentially expressed genes using supervised classification and sparse ANOVA. We employed these transcriptome data as the starting point for developing a breast tumor predictor from human peripheral blood mononuclear cells (PBMCs) by using a factor modeling approach. Results The predictor distinguished breast cancer patients from healthy individuals in a cohort of patients independent from that used to build the factors and train the model with 89% sensitivity, 100% specificity and an area under the curve (AUC) of 0.97 using Youden's J-statistic to objectively select the model's classification threshold. Both permutation testing of the model and evaluating the model strategy by swapping the training and validation sets highlight its stability. Conclusions We describe a human breast tumor predictor based on the gene expression of mouse PBCs. This strategy overcomes many of the limitations of earlier studies by using the model system to reduce noise and identify transcripts associated with the presence of a breast tumor over other potentially confounding factors. Our results serve as a proof-of-concept for using an animal model to develop a blood-based diagnostic, and it establishes an experimental framework for identifying predictors of solid tumors, not only in the context of breast cancer, but also in other types of cancer.</p

Diagnosis of Partial Body Radiation Exposure in Mice Using Peripheral Blood Gene Expression Profiles

In the event of a terrorist-mediated attack in the United States using radiological or improvised nuclear weapons, it is expected that hundreds of thousands of people could be exposed to life-threatening levels of ionizing radiation. We have recently shown that genome-wide expression analysis of the peripheral blood (PB) can generate gene expression profiles that can predict radiation exposure and distinguish the dose level of exposure following total body irradiation (TBI). However, in the event a radiation-mass casualty scenario, many victims will have heterogeneous exposure due to partial shielding and it is unknown whether PB gene expression profiles would be useful in predicting the status of partially irradiated individuals. Here, we identified gene expression profiles in the PB that were characteristic of anterior hemibody-, posterior hemibody- and single limb-irradiation at 0.5 Gy, 2 Gy and 10 Gy in C57Bl6 mice. These PB signatures predicted the radiation status of partially irradiated mice with a high level of accuracy (range 79–100%) compared to non-irradiated mice. Interestingly, PB signatures of partial body irradiation were poorly predictive of radiation status by site of injury (range 16–43%), suggesting that the PB molecular response to partial body irradiation was anatomic site specific. Importantly, PB gene signatures generated from TBI-treated mice failed completely to predict the radiation status of partially irradiated animals or non-irradiated controls. These data demonstrate that partial body irradiation, even to a single limb, generates a characteristic PB signature of radiation injury and thus may necessitate the use of multiple signatures, both partial body and total body, to accurately assess the status of an individual exposed to radiation

Two Genes on A/J Chromosome 18 Are Associated with Susceptibility to Staphylococcus aureus Infection by Combined Microarray and QTL Analyses

Although it has recently been shown that A/J mice are highly susceptible to Staphylococcus aureus sepsis as compared to C57BL/6J, the specific genes responsible for this differential phenotype are unknown. Using chromosome substitution strains (CSS), we found that loci on chromosomes 8, 11, and 18 influence susceptibility to S. aureus sepsis in A/J mice. We then used two candidate gene selection strategies to identify genes on these three chromosomes associated with S. aureus susceptibility, and targeted genes identified by both gene selection strategies. First, we used whole genome transcription profiling to identify 191 (56 on chr. 8, 100 on chr. 11, and 35 on chr. 18) genes on our three chromosomes of interest that are differentially expressed between S. aureus-infected A/J and C57BL/6J. Second, we identified two significant quantitative trait loci (QTL) for survival post-infection on chr. 18 using N2 backcross mice (F1 [C18A]×C57BL/6J). Ten genes on chr. 18 (March3, Cep120, Chmp1b, Dcp2, Dtwd2, Isoc1, Lman1, Spire1, Tnfaip8, and Seh1l) mapped to the two significant QTL regions and were also identified by the expression array selection strategy. Using real-time PCR, 6 of these 10 genes (Chmp1b, Dtwd2, Isoc1, Lman1, Tnfaip8, and Seh1l) showed significantly different expression levels between S. aureus-infected A/J and C57BL/6J. For two (Tnfaip8 and Seh1l) of these 6 genes, siRNA-mediated knockdown of gene expression in S. aureus–challenged RAW264.7 macrophages induced significant changes in the cytokine response (IL-1 β and GM-CSF) compared to negative controls. These cytokine response changes were consistent with those seen in S. aureus-challenged peritoneal macrophages from CSS 18 mice (which contain A/J chromosome 18 but are otherwise C57BL/6J), but not C57BL/6J mice. These findings suggest that two genes, Tnfaip8 and Seh1l, may contribute to susceptibility to S. aureus in A/J mice, and represent promising candidates for human genetic susceptibility studies

Interferon-Inducible CXC Chemokines Directly Contribute to Host Defense against Inhalational Anthrax in a Murine Model of Infection

Chemokines have been found to exert direct, defensin-like antimicrobial activity in vitro, suggesting that, in addition to orchestrating cellular accumulation and activation, chemokines may contribute directly to the innate host response against infection. No observations have been made, however, demonstrating direct chemokine-mediated promotion of host defense in vivo. Here, we show that the murine interferon-inducible CXC chemokines CXCL9, CXCL10, and CXCL11 each exert direct antimicrobial effects in vitro against Bacillus anthracis Sterne strain spores and bacilli including disruptions in spore germination and marked reductions in spore and bacilli viability as assessed using CFU determination and a fluorometric assay of metabolic activity. Similar chemokine-mediated antimicrobial activity was also observed against fully virulent Ames strain spores and encapsulated bacilli. Moreover, antibody-mediated neutralization of these CXC chemokines in vivo was found to significantly increase host susceptibility to pulmonary B. anthracis infection in a murine model of inhalational anthrax with disease progression characterized by systemic bacterial dissemination, toxemia, and host death. Neutralization of the shared chemokine receptor CXCR3, responsible for mediating cellular recruitment in response to CXCL9, CXCL10, and CXCL11, was not found to increase host susceptibility to inhalational anthrax. Taken together, our data demonstrate a novel, receptor-independent antimicrobial role for the interferon-inducible CXC chemokines in pulmonary innate immunity in vivo. These data also support an immunomodulatory approach for effectively treating and/or preventing pulmonary B. anthracis infection, as well as infections caused by pathogenic and potentially, multi-drug resistant bacteria including other spore-forming organisms