Probing host pathogen cross-talk by transcriptional profiling of both Mycobacterium tuberculosis and infected human dendritic cells and macrophages

This study provides the proof of principle that probing the host and the microbe transcriptomes simultaneously is a valuable means to accessing unique information on host pathogen interactions. Our results also underline the extraordinary plasticity of host cell and pathogen responses to infection, and provide a solid framework to further understand the complex mechanisms involved in immunity to M. tuberculosis and in mycobacterial adaptation to different intracellular environments

Differential Producibility Analysis (DPA) of Transcriptomic Data with Metabolic Networks: Deconstructing the Metabolic Response of M. tuberculosis

A general paucity of knowledge about the metabolic state of Mycobacterium tuberculosis within the host environment is a major factor impeding development of novel drugs against tuberculosis. Current experimental methods do not allow direct determination of the global metabolic state of a bacterial pathogen in vivo, but the transcriptional activity of all encoded genes has been investigated in numerous microarray studies. We describe a novel algorithm, Differential Producibility Analysis (DPA) that uses a metabolic network to extract metabolic signals from transcriptome data. The method utilizes Flux Balance Analysis (FBA) to identify the set of genes that affect the ability to produce each metabolite in the network. Subsequently, Rank Product Analysis is used to identify those metabolites predicted to be most affected by a transcriptional signal. We first apply DPA to investigate the metabolic response of E. coli to both anaerobic growth and inactivation of the FNR global regulator. DPA successfully extracts metabolic signals that correspond to experimental data and provides novel metabolic insights. We next apply DPA to investigate the metabolic response of M. tuberculosis to the macrophage environment, human sputum and a range of in vitro environmental perturbations. The analysis revealed a previously unrecognized feature of the response of M. tuberculosis to the macrophage environment: a down-regulation of genes influencing metabolites in central metabolism and concomitant up-regulation of genes that influence synthesis of cell wall components and virulence factors. DPA suggests that a significant feature of the response of the tubercle bacillus to the intracellular environment is a channeling of resources towards remodeling of its cell envelope, possibly in preparation for attack by host defenses. DPA may be used to unravel the mechanisms of virulence and persistence of M. tuberculosis and other pathogens and may have general application for extracting metabolic signals from other “-omics” data

Limited Transplantation of Antigen-Expressing Hematopoietic Stem Cells Induces Long-Lasting Cytotoxic T Cell Responses

Harnessing the ability of cytotoxic T lymphocytes (CTLs) to recognize and eradicate tumor or pathogen-infected cells is a critical goal of modern immune-based therapies. Although multiple immunization strategies efficiently induce high levels of antigen-specific CTLs, the initial increase is typically followed by a rapid contraction phase resulting in a sharp decline in the frequency of functional CTLs. We describe a novel approach to immunotherapy based on a transplantation of low numbers of antigen-expressing hematopoietic stem cells (HSCs) following nonmyeloablative or partially myeloablative conditioning. Continuous antigen presentation by a limited number of differentiated transgenic hematopoietic cells results in an induction and prolonged maintenance of fully functional effector T cell responses in a mouse model. Recipient animals display high levels of antigen-specific CTLs four months following transplantation in contrast to dendritic cell-immunized animals in which the response typically declines at 4–6 weeks post-immunization. Majority of HSC-induced antigen-specific CD8+ T cells display central memory phenotype, efficiently kill target cells in vivo, and protect recipients against tumor growth in a preventive setting. Furthermore, we confirm previously published observation that high level engraftment of antigen-expressing HSCs following myeloablative conditioning results in tolerance and an absence of specific cytotoxic activity in vivo. In conclusion, the data presented here supports potential application of immunization by limited transplantation of antigen-expressing HSCs for the prevention and treatment of cancer and therapeutic immunization of chronic infectious diseases such as HIV-1/AIDS

Identification of gene targets against dormant phase Mycobacterium tuberculosis infections

<p>Abstract</p> <p>Background</p> <p><it>Mycobacterium tuberculosis</it>, the causative agent of tuberculosis (TB), infects approximately 2 billion people worldwide and is the leading cause of mortality due to infectious disease. Current TB therapy involves a regimen of four antibiotics taken over a six month period. Patient compliance, cost of drugs and increasing incidence of drug resistant <it>M. tuberculosis </it>strains have added urgency to the development of novel TB therapies. Eradication of TB is affected by the ability of the bacterium to survive up to decades in a dormant state primarily in hypoxic granulomas in the lung and to cause recurrent infections.</p> <p>Methods</p> <p>The availability of <it>M. tuberculosis </it>genome-wide DNA microarrays has lead to the publication of several gene expression studies under simulated dormancy conditions. However, no single model best replicates the conditions of human pathogenicity. In order to identify novel TB drug targets, we performed a meta-analysis of multiple published datasets from gene expression DNA microarray experiments that modeled infection leading to and including the dormant state, along with data from genome-wide insertional mutagenesis that examined gene essentiality.</p> <p>Results</p> <p>Based on the analysis of these data sets following normalization, several genome wide trends were identified and used to guide the selection of targets for therapeutic development. The trends included the significant up-regulation of genes controlled by <it>devR</it>, down-regulation of protein and ATP synthesis, and the adaptation of two-carbon metabolism to the hypoxic and nutrient limited environment of the granuloma. Promising targets for drug discovery were several regulatory elements (<it>devR/devS</it>, <it>relA</it>, <it>mprAB</it>), enzymes involved in redox balance and respiration, sulfur transport and fixation, pantothenate, isoprene, and NAD biosynthesis. The advantages and liabilities of each target are discussed in the context of enzymology, bacterial pathways, target tractability, and drug development.</p> <p>Conclusion</p> <p>Based on our bioinformatics analysis and additional discussion of in-depth biological rationale, several novel anti-TB targets have been proposed as potential opportunities to improve present therapeutic treatments for this disease.</p

Patterns of nucleotide diversity at the regions encompassing the Drosophila insulin-like peptide (dilp) genes: demography vs positive selection in Drosophila melanogaster.

In Drosophila, the insulin-signaling pathway controls some life history traits, such as fertility and lifespan, and it is considered to be the main metabolic pathway involved in establishing adult body size. Several observations concerning variation in body size in the Drosophila genus are suggestive of its adaptive character. Genes encoding proteins in this pathway are, therefore, good candidates to have experienced adaptive changes and to reveal the footprint of positive selection. The Drosophila insulin-like peptides (DILPs) are the ligands that trigger the insulin-signaling cascade. In Drosophila melanogaster, there are several peptides that are structurally similar to the single mammalian insulin peptide. The footprint of recent adaptive changes on nucleotide variation can be unveiled through the analysis of polymorphism and divergence. With this aim, we have surveyed nucleotide sequence variation at the dilp1-7 genes in a natural population of D. melanogaster. The comparison of polymorphism in D. melanogaster and divergence from D. simulans at different functional classes of the dilp genes provided no evidence of adaptive protein evolution after the split of the D. melanogaster and D. simulans lineages. However, our survey of polymorphism at the dilp gene regions of D. melanogaster has provided some evidence for the action of positive selection at or near these genes. The regions encompassing the dilp1-4 genes and the dilp6 gene stand out as likely affected by recent adaptive events

From evolutionary computation to the evolution of things

Evolution has provided a source of inspiration for algorithm designers since the birth of computers. The resulting field, evolutionary computation, has been successful in solving engineering tasks ranging in outlook from the molecular to the astronomical. Today, the field is entering a new phase as evolutionary algorithms that take place in hardware are developed, opening up new avenues towards autonomous machines that can adapt to their environment. We discuss how evolutionary computation compares with natural evolution and what its benefits are relative to other computing approaches, and we introduce the emerging area of artificial evolution in physical systems

Chronic Apocynin Treatment Attenuates Beta Amyloid Plaque Size and Microglial Number in hAPP(751)SL Mice

Background: NADPH oxidase is implicated in neurotoxic microglial activation and the progressive nature of Alzheimer’s Disease (AD). Here, we test the ability of two NADPH oxidase inhibitors, apocynin and dextromethorphan (DM), to reduce learning deficits and neuropathology in transgenic mice overexpressing human amyloid precursor protein with the Swedish and London mutations (hAPP(751)SL). Methods: Four month old hAPP(751)SL mice were treated daily with saline, 15 mg/kg DM, 7.5 mg/kg DM, or 10 mg/kg apocynin by gavage for four months. Results: Only hAPP(751)SL mice treated with apocynin showed reduced plaque size and a reduction in the number of cortical microglia, when compared to the saline treated group. Analysis of whole brain homogenates from all treatments tested (saline, DM, and apocynin) demonstrated low levels of TNFa, protein nitration, lipid peroxidation, and NADPH oxidase activation, indicating a low level of neuroinflammation and oxidative stress in hAPP(751)SL mice at 8 months of age that was not significantly affected by any drug treatment. Despite in vitro analyses demonstrating that apocynin and DM ameliorate Ab-induced extracellular superoxide production and neurotoxicity, both DM and apocynin failed to significantly affect learning and memory tasks or synaptic density in hAPP(751)SL mice. To discern how apocynin was affecting plaque levels (plaque load) and microglial number in vivo, in vitro analysis of microglia was performed, revealing no apocynin effects on beta-amyloid (Ab) phagocytosis, microglial proliferation, or microglial survival. Conclusions: Together, this study suggests that while hAPP(751)SL mice show increases in microglial number and plaque load, they fail to exhibit elevated markers of neuroinflammation consistent with AD at 8 months of age, which may be a limitation of this animal model. Despite absence of clear neuroinflammation, apocynin was still able to reduce both plaque size and microglial number, suggesting that apocynin may have additional therapeutic effects independent of anti-inflammatory characteristics

Genome-Wide Diet-Gene Interaction Analyses for Risk of Colorectal Cancer

Dietary factors, including meat, fruits, vegetables and fiber, are associated with colorectal cancer; however, there is limited information as to whether these dietary factors interact with genetic variants to modify risk of colorectal cancer. We tested interactions between these dietary factors and approximately 2.7 million genetic variants for colorectal cancer risk among 9,287 cases and 9,117 controls from ten studies. We used logistic regression to investigate multiplicative gene-diet interactions, as well as our recently developed Cocktail method that involves a screening step based on marginal associations and gene-diet correlations and a testing step for multiplicative interactions, while correcting for multiple testing using weighted hypothesis testing. Per quartile increment in the intake of red and processed meat were associated with statistically significant increased risks of colorectal cancer and vegetable, fruit and fiber intake with lower risks. From the case-control analysis, we detected a significant interaction between rs4143094 (10p14/near GATA3) and processed meat consumption (OR = 1.17; p = 8.7E-09), which was consistently observed across studies (p heterogeneity = 0.78). The risk of colorectal cancer associated with processed meat was increased among individuals with the rs4143094-TG and -TT genotypes (OR = 1.20 and OR = 1.39, respectively) and null among those with the GG genotype (OR = 1.03). Our results identify a novel gene-diet interaction with processed meat for colorectal cancer, highlighting that diet may modify the effect of genetic variants on disease risk, which may have important implications for prevention. © 2014