The anti-sigma factor RsrA responds to oxidative stress by reburying its hydrophobic core

Redox-regulated effector systems that counteract oxidative stress are essential for all forms of life. Here we uncover a new paradigm for sensing oxidative stress centred on the hydrophobic core of a sensor protein. RsrA is an archetypal zinc-binding anti-sigma factor that responds to disulfide stress in the cytoplasm of Actinobacteria. We show that RsrA utilizes its hydrophobic core to bind the sigma factor σ R preventing its association with RNA polymerase, and that zinc plays a central role in maintaining this high-affinity complex. Oxidation of RsrA is limited by the rate of zinc release, which weakens the RsrA-σ R complex by accelerating its dissociation. The subsequent trigger disulfide, formed between specific combinations of RsrA's three zinc-binding cysteines, precipitates structural collapse to a compact state where all σ R-binding residues are sequestered back into its hydrophobic core, releasing σ R to activate transcription of anti-oxidant genes

Mixing of Honeybees with Different Genotypes Affects Individual Worker Behavior and Transcription of Genes in the Neuronal Substrate

Division of labor in social insects has made the evolution of collective traits possible that cannot be achieved by individuals alone. Differences in behavioral responses produce variation in engagement in behavioral tasks, which as a consequence, generates a division of labor. We still have little understanding of the genetic components influencing these behaviors, although several candidate genomic regions and genes influencing individual behavior have been identified. Here, we report that mixing of worker honeybees with different genotypes influences the expression of individual worker behaviors and the transcription of genes in the neuronal substrate. These indirect genetic effects arise in a colony because numerous interactions between workers produce interacting phenotypes and genotypes across organisms. We studied hygienic behavior of honeybee workers, which involves the cleaning of diseased brood cells in the colony. We mixed ∼500 newly emerged honeybee workers with genotypes of preferred Low (L) and High (H) hygienic behaviors. The L/H genotypic mixing affected the behavioral engagement of L worker bees in a hygienic task, the cooperation among workers in uncapping single brood cells, and switching between hygienic tasks. We found no evidence that recruiting and task-related stimuli are the primary source of the indirect genetic effects on behavior. We suggested that behavioral responsiveness of L bees was affected by genotypic mixing and found evidence for changes in the brain in terms of 943 differently expressed genes. The functional categories of cell adhesion, cellular component organization, anatomical structure development, protein localization, developmental growth and cell morphogenesis were overrepresented in this set of 943 genes, suggesting that indirect genetic effects can play a role in modulating and modifying the neuronal substrate. Our results suggest that genotypes of social partners affect the behavioral responsiveness and the neuronal substrate of individual workers, indicating a complex genetic architecture underlying the expression of behavior

Understanding the Role of PknJ in Mycobacterium tuberculosis: Biochemical Characterization and Identification of Novel Substrate Pyruvate Kinase A

Reversible protein phosphorylation is a prevalent signaling mechanism which modulates cellular metabolism in response to changing environmental conditions. In this study, we focus on previously uncharacterized Mycobacterium tuberculosis Ser/Thr protein kinase (STPK) PknJ, a putative transmembrane protein. PknJ is shown to possess autophosphorylation activity and is also found to be capable of carrying out phosphorylation on the artificial substrate myelin basic protein (MyBP). Previous studies have shown that the autophosphorylation activity of M. tuberculosis STPKs is dependent on the conserved residues in the activation loop. However, our results show that apart from the conventional conserved residues, additional residues in the activation loop may also play a crucial role in kinase activation. Further characterization of PknJ reveals that the kinase utilizes unusual ions (Ni2+, Co2+) as cofactors, thus hinting at a novel mechanism for PknJ activation. Additionally, as shown for other STPKs, we observe that PknJ possesses the capability to dimerize. In order to elucidate the signal transduction cascade emanating from PknJ, the M. tuberculosis membrane-associated protein fraction is treated with the active kinase and glycolytic enzyme Pyruvate kinase A (mtPykA) is identified as one of the potential substrates of PknJ. The phospholabel is found to be localized on serine and threonine residue(s), with Ser37 identified as one of the sites of phosphorylation. Since Pyk is known to catalyze the last step of glycolysis, our study shows that the fundamental pathways such as glycolysis can also be governed by STPK-mediated signaling

HDNetDB: A Molecular Interaction Database for Network-Oriented Investigations into Huntington’s Disease

Huntington's disease (HD) is a progressive and fatal neurodegenerative disorder caused by an expanded CAG repeat in the huntingtin gene. Although HD is monogenic, its molecular manifestation appears highly complex and involves multiple cellular processes. The recent application of high throughput platforms such as microarrays and mass-spectrometry has indicated multiple pathogenic routes. The massive data generated by these techniques together with the complexity of the pathogenesis, however, pose considerable challenges to researchers. Network-based methods can provide valuable tools to consolidate newly generated data with existing knowledge, and to decipher the interwoven molecular mechanisms underlying HD. To facilitate research on HD in a network-oriented manner, we have developed HDNetDB, a database that integrates molecular interactions with many HD-relevant datasets. It allows users to obtain, visualize and prioritize molecular interaction networks using HD-relevant gene expression, phenotypic and other types of data obtained from human samples or model organisms. We illustrated several HDNetDB functionalities through a case study and identified proteins that constitute potential cross-talk between HD and the unfolded protein response (UPR). HDNetDB is publicly accessible at http://hdnetdb.sysbiolab.eu.CHDI Foundation [A-2666]; Portuguese Fundacao para a Ciencia e a Tecnologia [SFRH/BPD/70718/2010, SFRH/BPD/96890/2013, IF/00881/2013, UID/BIM/04773/2013 - CBMR, UID/Multi/04326/2013 - CCMAR]info:eu-repo/semantics/publishedVersio

The Mycobacterium tuberculosis Drugome and Its Polypharmacological Implications

We report a computational approach that integrates structural bioinformatics, molecular modelling and systems biology to construct a drug-target network on a structural proteome-wide scale. The approach has been applied to the genome of Mycobacterium tuberculosis (M.tb), the causative agent of one of today's most widely spread infectious diseases. The resulting drug-target interaction network for all structurally characterized approved drugs bound to putative M.tb receptors, we refer to as the ‘TB-drugome’. The TB-drugome reveals that approximately one-third of the drugs examined have the potential to be repositioned to treat tuberculosis and that many currently unexploited M.tb receptors may be chemically druggable and could serve as novel anti-tubercular targets. Furthermore, a detailed analysis of the TB-drugome has shed new light on the controversial issues surrounding drug-target networks [1]–[3]. Indeed, our results support the idea that drug-target networks are inherently modular, and further that any observed randomness is mainly caused by biased target coverage. The TB-drugome (http://funsite.sdsc.edu/drugome/TB) has the potential to be a valuable resource in the development of safe and efficient anti-tubercular drugs. More generally the methodology may be applied to other pathogens of interest with results improving as more of their structural proteomes are determined through the continued efforts of structural biology/genomics

The Pathway Coexpression Network: Revealing pathway relationships.

A goal of genomics is to understand the relationships between biological processes. Pathways contribute to functional interplay within biological processes through complex but poorly understood interactions. However, limited functional references for global pathway relationships exist. Pathways from databases such as KEGG and Reactome provide discrete annotations of biological processes. Their relationships are currently either inferred from gene set enrichment within specific experiments, or by simple overlap, linking pathway annotations that have genes in common. Here, we provide a unifying interpretation of functional interaction between pathways by systematically quantifying coexpression between 1,330 canonical pathways from the Molecular Signatures Database (MSigDB) to establish the Pathway Coexpression Network (PCxN). We estimated the correlation between canonical pathways valid in a broad context using a curated collection of 3,207 microarrays from 72 normal human tissues. PCxN accounts for shared genes between annotations to estimate significant correlations between pathways with related functions rather than with similar annotations. We demonstrate that PCxN provides novel insight into mechanisms of complex diseases using an Alzheimer's Disease (AD) case study. PCxN retrieved pathways significantly correlated with an expert curated AD gene list. These pathways have known associations with AD and were significantly enriched for genes independently associated with AD. As a further step, we show how PCxN complements the results of gene set enrichment methods by revealing relationships between enriched pathways, and by identifying additional highly correlated pathways. PCxN revealed that correlated pathways from an AD expression profiling study include functional clusters involved in cell adhesion and oxidative stress. PCxN provides expanded connections to pathways from the extracellular matrix. PCxN provides a powerful new framework for interrogation of global pathway relationships. Comprehensive exploration of PCxN can be performed at http://pcxn.org/

Future perspectives in melanoma research: meeting report from the "Melanoma Bridge";: Napoli, December 3rd-6th 2014.

The fourth "Melanoma Bridge Meeting" took place in Naples, December 3-6th, 2014. The four topics discussed at this meeting were: Molecular and Immunological Advances, Combination Therapies, News in Immunotherapy, and Tumor Microenvironment and Biomarkers. Until recently systemic therapy for metastatic melanoma patients was ineffective, but recent advances in tumor biology and immunology have led to the development of new targeted and immunotherapeutic agents that prolong progression-free survival (PFS) and overall survival (OS). New therapies, such as mitogen-activated protein kinase (MAPK) pathway inhibitors as well as other signaling pathway inhibitors, are being tested in patients with metastatic melanoma either as monotherapy or in combination, and all have yielded promising results. These include inhibitors of receptor tyrosine kinases (BRAF, MEK, and VEGFR), the phosphatidylinositol 3 kinase (PI3K) pathway [PI3K, AKT, mammalian target of rapamycin (mTOR)], activators of apoptotic pathway, and the cell cycle inhibitors (CDK4/6). Various locoregional interventions including radiotherapy and surgery are still valid approaches in treatment of advanced melanoma that can be integrated with novel therapies. Intrinsic, adaptive and acquired resistance occur with targeted therapy such as BRAF inhibitors, where most responses are short-lived. Given that the reactivation of the MAPK pathway through several distinct mechanisms is responsible for the majority of acquired resistance, it is logical to combine BRAF inhibitors with inhibitors of targets downstream in the MAPK pathway. For example, combination of BRAF/MEK inhibitors (e.g., dabrafenib/trametinib) have been demonstrated to improve survival compared to monotherapy. Application of novel technologies such sequencing have proven useful as a tool for identification of MAPK pathway-alternative resistance mechanism and designing other combinatorial therapies such as those between BRAF and AKT inhibitors. Improved survival rates have also been observed with immune-targeted therapy for patients with metastatic melanoma. Immune-modulating antibodies came to the forefront with anti-CTLA-4, programmed cell death-1 (PD-1) and PD-1 ligand 1 (PD-L1) pathway blocking antibodies that result in durable responses in a subset of melanoma patients. Agents targeting other immune inhibitory (e.g., Tim-3) or immune stimulating (e.g., CD137) receptors and other approaches such as adoptive cell transfer demonstrate clinical benefit in patients with melanoma as well. These agents are being studied in combination with targeted therapies in attempt to produce longer-term responses than those more typically seen with targeted therapy. Other combinations with cytotoxic chemotherapy and inhibitors of angiogenesis are changing the evolving landscape of therapeutic options and are being evaluated to prevent or delay resistance and to further improve survival rates for this patient population. This meeting's specific focus was on advances in combination of targeted therapy and immunotherapy. Both combination targeted therapy approaches and different immunotherapies were discussed. Similarly to the previous meetings, the importance of biomarkers for clinical application as markers for diagnosis, prognosis and prediction of treatment response was an integral part of the meeting. The overall emphasis on biomarkers supports novel concepts toward integrating biomarkers into contemporary clinical management of patients with melanoma across the entire spectrum of disease stage. Translation of the knowledge gained from the biology of tumor microenvironment across different tumors represents a bridge to impact on prognosis and response to therapy in melanoma