The chbG Gene of the Chitobiose (chb) Operon of Escherichia coli Encodes a Chitooligosaccharide Deacetylase

The chb operon of Escherichia coli is involved in the utilization of the beta-glucosides chitobiose and cellobiose. The function of chbG (ydjC), the sixth open reading frame of the operon that codes for an evolutionarily conserved protein is unknown. We show that chbG encodes a monodeacetylase that is essential for growth on the acetylated chitooligosaccharides chitobiose and chitotriose but is dispensable for growth on cellobiose and chitosan dimer, the deacetylated form of chitobiose. The predicted active site of the enzyme was validated by demonstrating loss of function upon substitution of its putative metal-binding residues that are conserved across the YdjC family of proteins. We show that activation of the chb promoter by the regulatory protein ChbR is dependent on ChbG, suggesting that deacetylation of chitobiose-6-P and chitotriose-6-P is necessary for their recognition by ChbR as inducers. Strains carrying mutations in chbR conferring the ability to grow on both cellobiose and chitobiose are independent of chbG function for induction, suggesting that gain of function mutations in ChbR allow it to recognize the acetylated form of the oligosaccharides. ChbR-independent expression of the permease and phospho-beta-glucosidase from a heterologous promoter did not support growth on both chitobiose and chitotriose in the absence of chbG, suggesting an additional role of chbG in the hydrolysis of chitooligosaccharides. The homologs of chbG in metazoans have been implicated in development and inflammatory diseases of the intestine, indicating that understanding the function of E. coli chbG has a broader significance.

Network approaches to drug discovery

Introduction: Advances in genomics technologies are providing a very large amount of data on genome-wide gene expression profiles, protein molecules and their interactions with other macromolecules and metabolites. Molecular interaction networks provide a useful way to capture this complex data and comprehend it. Networks are beginning to be used in drug discovery, in many steps of the modern discovery pipeline, with large-scale molecular networks being particularly useful for the understanding of the molecular basis of the disease. Areas covered: The authors discuss network approaches used for drug target discovery and lead identification in the drug discovery pipeline. By reconstructing networks of targets, drugs and drug candidates as well as gene expression profiles under normal and disease conditions, the paper illustrates how it is possible to find relationships between different diseases, find biomarkers, explore drug repurposing and study emergence of drug resistance. Furthermore, the authors also look at networks which address particular important aspects such as off-target effects, combination-targets, mechanism of drug action and drug safety. Expert opinion: The network approach represents another paradigm shift in drug discovery science. A network approach provides a fresh perspective of understanding important proteins in the context of their cellular environments, providing a rational basis for deriving useful strategies in drug design. Besides drug target identification and inferring mechanism of action, networks enable us to address new ideas that could prove to be extremely useful for new drug discovery, such as drug repositioning, drug synergy, polypharmacology and personalized medicine.

Fourteen gene GBM prognostic signature identifies association of immune response pathway and mesenchymal subtype with high risk group

Background: Recent research on glioblastoma (GBM) has focused on deducing gene signatures predicting prognosis. The present study evaluated the mRNA expression of selected genes and correlated with outcome to arrive at a prognostic gene signature. Methods: Patients with GBM (n = 123) were prospectively recruited, treated with a uniform protocol and followed up. Expression of 175 genes in GBM tissue was determined using qRT-PCR. A supervised principal component analysis followed by derivation of gene signature was performed. Independent validation of the signature was done using TCGA data. Gene Ontology and KEGG pathway analysis was carried out among patients from TCGA cohort. Results: A 14 gene signature was identified that predicted outcome in GBM. A weighted gene (WG) score was found to be an independent predictor of survival in multivariate analysis in the present cohort (HR = 2.507; B = 0.919; p < 0.001) and in TCGA cohort. Risk stratification by standardized WG score classified patients into low and high risk predicting survival both in our cohort (p = <0.001) and TCGA cohort (p = 0.001). Pathway analysis using the most differentially regulated genes (n = 76) between the low and high risk groups revealed association of activated inflammatory/immune response pathways and mesenchymal subtype in the high risk group. Conclusion: We have identified a 14 gene expression signature that can predict survival in GBM patients. A network analysis revealed activation of inflammatory response pathway specifically in high risk group. These findings may have implications in understanding of gliomagenesis, development of targeted therapies and selection of high risk cancer patients for alternate adjuvant therapies.

Network, nodes and nexus: systems approach to multitarget therapeutics

Systems biology is revealing multiple layers of regulatory networks that manifest spatiotemporal variations. Since genes and environment also influence the emergent property of a cell, the biological output requires dynamic understanding of various molecular circuitries. The metabolic networks continually adapt and evolve to cope with the changing milieu of the system, which could also include infection by another organism. Such perturbations of the functional networks can result in disease phenotypes, for instance tuberculosis and cancer. In order to develop effective therapeutics, it is important to determine the disease progression profiles of complex disorders that can reveal dynamic aspects and to develop mutitarget systemic therapies that can help overcome pathway adaptations and redundancy.

DNA STRUCTURAL FEATURES AND ARCHITECTURE OF PROMOTER REGIONS PLAY A ROLE IN GENE RESPONSIVENESS OF S. CEREVISIAE

Gene expression is the most fundamental biological process, which is essential for phenotypic variation. It is regulated by various external (environment and evolution) and internal (genetic) factors. The level of gene expression depends on promoter architecture, along with other external factors. Presence of sequence motifs, such as transcription factor binding sites (TFBSs) and TATA-box, or DNA methylation in vertebrates has been implicated in the regulation of expression of some genes in eukaryotes, but a large number of genes lack these sequences. On the other hand, several experimental and computational studies have shown that promoter sequences possess some special structural properties, such as low stability, less bendability, low nucleosome occupancy, and more curvature, which are prevalent across all organisms. These structural features may play role in transcription initiation and regulation of gene expression. We have studied the relationship between the structural features of promoter DNA, promoter directionality and gene expression variability in S. cerevisiae. This relationship has been analyzed for seven different measures of gene expression variability, along with two different regulatory effect measures. We find that a few of the variability measures of gene expression are linked to DNA structural properties, nucleosome occupancy, TATA-box presence, and bidirectionality of promoter regions. Interestingly, gene responsiveness is most intimately correlated with DNA structural features and promoter architecture.

A 16-Gene Signature Distinguishes Anaplastic Astrocytoma from Glioblastoma

Anaplastic astrocytoma (AA; Grade III) and glioblastoma (GBM; Grade IV) are diffusely infiltrating tumors and are called malignant astrocytomas. The treatment regimen and prognosis are distinctly different between anaplastic astrocytoma and glioblastoma patients. Although histopathology based current grading system is well accepted and largely reproducible, intratumoral histologic variations often lead to difficulties in classification of malignant astrocytoma samples. In order to obtain a more robust molecular classifier, we analysed RT-qPCR expression data of 175 differentially regulated genes across astrocytoma using Prediction Analysis of Microarrays (PAM) and found the most discriminatory 16-gene expression signature for the classification of anaplastic astrocytoma and glioblastoma. The 16-gene signature obtained in the training set was validated in the test set with diagnostic accuracy of 89%. Additionally, validation of the 16-gene signature in multiple independent cohorts revealed that the signature predicted anaplastic astrocytoma and glioblastoma samples with accuracy rates of 99%, 88%, and 92% in TCGA, GSE1993 and GSE4422 datasets, respectively. The protein-protein interaction network and pathway analysis suggested that the 16-genes of the signature identified epithelial-mesenchymal transition (EMT) pathway as the most differentially regulated pathway in glioblastoma compared to anaplastic astrocytoma. In addition to identifying 16 gene classification signature, we also demonstrated that genes involved in epithelial-mesenchymal transition may play an important role in distinguishing glioblastoma from anaplastic astrocytoma.

Predicting gene ontology annotations of orphan GWAS genes using protein-protein interactions

Background: The number of genome-wide association studies (GWAS) has increased rapidly in the past couple of years, resulting in the identification of genes associated with different diseases. The next step in translating these findings into biomedically useful information is to find out the mechanism of the action of these genes. However, GWAS studies often implicate genes whose functions are currently unknown; for example, MYEOV, ANKLE1, TMEM45B and ORAOV1 are found to be associated with breast cancer, but their molecular function is unknown. Results: We carried out Bayesian inference of Gene Ontology (GO) term annotations of genes by employing the directed acyclic graph structure of GO and the network of protein-protein interactions (PPIs). The approach is designed based on the fact that two proteins that interact biophysically would be in physical proximity of each other, would possess complementary molecular function, and play role in related biological processes. Predicted GO terms were ranked according to their relative association scores and the approach was evaluated quantitatively by plotting the precision versus recall values and F-scores (the harmonic mean of precision and recall) versus varying thresholds. Precisions of similar to 58% and similar to 40% for localization and functions respectively of proteins were determined at a threshold of similar to 30 (top 30 GO terms in the ranked list). Comparison with function prediction based on semantic similarity among nodes in an ontology and incorporation of those similarities in a k nearest neighbor classifier confirmed that our results compared favorably. Conclusions: This approach was applied to predict the cellular component and molecular function GO terms of all human proteins that have interacting partners possessing at least one known GO annotation. The list of predictions is available at http://severus.dbmi.pitt.edu/engo/GOPRED.html. We present the algorithm, evaluations and the results of the computational predictions, especially for genes identified in GWAS studies to be associated with diseases, which are of translational interest.

Role of DNA sequence based structural features of promoters in transcription initiation and gene expression

D Regulatory information for transcription initiation is present in a stretch of genomic DNA, called the promoter region that is located upstream of the transcription start site (TSS) of the gene. The promoter region interacts with different transcription factors and RNA polymerase to initiate transcription and contains short stretches of transcription factor binding sites (TFBSs), as well as structurally unique elements. Recent experimental and computational analyses of promoter sequences show that they often have non-B-DNA structural motifs, as well as some conserved structural properties, such as stability, bendability, nucleosome positioning preference and curvature, across a class of organisms. Here, we briefly describe these structural features, the differences observed in various organisms and their possible role in regulation of gene expression.

Direct control of type IIA topoisomerase activity by a chromosomally encoded regulatory protein

Precise control of supercoiling homeostasis is critical to DNA-dependent processes such as gene expression, replication, and damage response. Topoisomerases are central regulators of DNA supercoiling commonly thought to act independently in the recognition and modulation of chromosome superstructure; however, recent evidence has indicated that cells tightly regulate topoisomerase activity to support chromosome dynamics, transcriptional response, and replicative events. How topoisomerase control is executed and linked to the internal status of a cell is poorly understood. To investigate these connections, we determined the structure of Escherichia coil gyrase, a type HA topoisomerase bound to YacG, a recently identified chromosomally encoded inhibitor protein. Phylogenetic analyses indicate that YacG is frequently associated with coenzyme A (CoA) production enzymes, linking the protein to metabolism and stress. The structure, along with supporting solution studies, shows that YacG represses gyrase by sterically occluding the principal DNA-binding site of the enzyme. Unexpectedly, YacG acts by both engaging two spatially segregated regions associated with small-molecule inhibitor interactions (fluoroquinolone antibiotics and the newly reported antagonist GSK299423) and remodeling the gyrase holo enzyme into an inactive, ATP-trapped configuration. This study establishes a new mechanism for the protein-based control of topoisomerases, an approach that may be used to alter supercoiling levels for responding to changes in cellular state.

Social insect colony as a biological regulatory system: modelling information flow in dominance networks

Social insects provide an excellent platform to investigate flow of information in regulatory systems since their successful social organization is essentially achieved by effective information transfer through complex connectivity patterns among the colony members. Network representation of such behavioural interactions offers a powerful tool for structural as well as dynamical analysis of the underlying regulatory systems. In this paper, we focus on the dominance interaction networks in the tropical social wasp Ropalidia marginata-a species where behavioural observations indicate that such interactions are principally responsible for the transfer of information between individuals about their colony needs, resulting in a regulation of their own activities. Our research reveals that the dominance networks of R. marginata are structurally similar to a class of naturally evolved information processing networks, a fact confirmed also by the predominance of a specific substructure-the `feed-forward loop'-a key functional component in many other information transfer networks. The dynamical analysis through Boolean modelling confirms that the networks are sufficiently stable under small fluctuations and yet capable of more efficient information transfer compared to their randomized counterparts. Our results suggest the involvement of a common structural design principle in different biological regulatory systems and a possible similarity with respect to the effect of selection on the organization levels of such systems. The findings are also consistent with the hypothesis that dominance behaviour has been shaped by natural selection to co-opt the information transfer process in such social insect species, in addition to its primal function of mediation of reproductive competition in the colony.

Interactome analyses of Salmonella pathogenicity islands reveal SicA indispensable for virulence

Background: Serovars of Salmonella enterica, namely Typhi and Typhimurium, reportedly, are the bacterial pathogens causing systemic infections like gastroenteritis and typhoid fever. To elucidate the role and importance in such infection, the proteins of the Type III secretion system of Salmonella pathogenicity islands and two component signal transduction systems, have been mainly focused. However, the most indispensable of these virulent ones and their hierarchical role has not yet been studied extensively. Results: We have adopted a theoretical approach to build an interactome comprising the proteins from the Salmonella pathogeneicity islands (SPI) and two component signal transduction systems. This interactome was then analyzed by using network parameters like centrality and k-core measures. An initial step to capture the fingerprint of the core network resulted in a set of proteins which are involved in the process of invasion and colonization, thereby becoming more important in the process of infection. These proteins pertained to the Inv, Org, Prg, Sip, Spa, Ssa and Sse operons along with chaperone protein SicA. Amongst them, SicA was figured out to be the most indispensable protein from different network parametric analyses. Subsequently, the gene expression levels of all these theoretically identified important proteins were confirmed by microarray data analysis. Finally, we have proposed a hierarchy of the proteins involved in the total infection process. This theoretical approach is the first of its kind to figure out potential virulence determinants encoded by SPI for therapeutic targets for enteric infection. Conclusions: A set of responsible virulent proteins was identified and the expression level of their genes was validated by using independent, published microarray data. The result was a targeted set of proteins that could serve as sensitive predictors and form the foundation for a series of trials in the wet-lab setting. Understanding these regulatory and virulent proteins would provide insight into conditions which are encountered by this intracellular enteric pathogen during the course of infection. This would further contribute in identifying novel targets for antimicrobial agents. (C) 2014 Elsevier Ltd. All rights reserved.

Mycobacterium tuberculosis Response Regulators, DevR and NarL, Interact in Vivo and Co-regulate Gene Expression during Aerobic Nitrate Metabolism

Mycobacterium tuberculosis genes Rv0844c/Rv0845 encoding the NarL response regulator and NarS histidine kinase are hypothesized to constitute a two-component system involved in the regulation of nitrate metabolism. However, there is no experimental evidence to support this. In this study, we established M. tuberculosis NarL/NarS as a functional two-component system and identified His(241) and Asp(61) as conserved phosphorylation sites in NarS and NarL, respectively. Transcriptional profiling between M. tuberculosis H37Rv and Delta narL mutant strain during exponential growth in broth cultures with or without nitrate defined an similar to 30-gene NarL regulon that exhibited significant overlap with DevR-regulated genes, thereby implicating a role for the DevR response regulator in the regulation of nitrate metabolism. Notably, expression analysis of a subset of genes common to NarL and DevR regulons in M. tuberculosis Delta devR, Delta devS Delta dosT, and Delta narL mutant strains revealed that in response to nitrite produced during aerobic nitrate metabolism, the DevRS/DosT regulatory system plays a primary role that is augmented by NarL. Specifically, NarL itself was unable to bind to the narK2, acg, and Rv3130c promoters in phosphorylated or unphosphorylated form; however, its interaction with DevR similar to P resulted in cooperative binding, thereby enabling co-regulation of these genes. These findings support the role of physiologically derived nitrite as a metabolic signal in mycobacteria. We propose NarL-DevR binding, possibly as a heterodimer, as a novel mechanism for co-regulation of gene expression by the DevRS/DosT and NarL/NarS regulatory systems.

A cis-Regulatory Mutation in Troponin-I of Drosophila Reveals the Importance of Proper Stoichiometry of Structural Proteins During Muscle Assembly

Rapid and high wing-beat frequencies achieved during insect flight are powered by the indirect flight muscles, the largest group of muscles present in the thorax. Any anomaly during the assembly and/or structural impairment of the indirect flight muscles gives rise to a flightless phenotype. Multiple mutagenesis screens in Drosophila melanogaster for defective flight behavior have led to the isolation and characterization of mutations that have been instrumental in the identification of many proteins and residues that are important for muscle assembly, function, and disease. In this article, we present a molecular-genetic characterization of a flightless mutation, flightless-H (fliH), originally designated as heldup-a (hdp-a). We show that fliH is a cis-regulatory mutation of the wings up A (wupA) gene, which codes for the troponin-I protein, one of the troponin complex proteins, involved in regulation of muscle contraction. The mutation leads to reduced levels of troponin-I transcript and protein. In addition to this, there is also coordinated reduction in transcript and protein levels of other structural protein isoforms that are part of the troponin complex. The altered transcript and protein stoichiometry ultimately culminates in unregulated acto-myosin interactions and a hypercontraction muscle phenotype. Our results shed new insights into the importance of maintaining the stoichiometry of structural proteins during muscle assembly for proper function with implications for the identification of mutations and disease phenotypes in other species, including humans.

Roles for Transcription Factors Sp1, NF-kappa B, IRF3, and IRF7 in Expression of the Human IFNL4 Gene

The expression of a biologically active human IFN4 depends on the presence of a frameshift deletion polymorphism within the first exon of the interferon lambda 4 (IFNL4) gene. In this report, we use the lung carcinoma-derived cell line, A549, which is genetically viable to express a functional IFN4, to address transcriptional requirements of the IFNL4 gene. We show that the GC-rich DNA-binding transcription factor (TF) specificity protein 1 (Sp1) is recruited to the IFNL4 promoter and has a role in induction of gene expression upon stimulation with viral RNA mimic poly(I:C). By using RNAi and overexpression strategies, we also show key roles in IFNL4 gene expression for the virus-inducible TFs, nuclear factor kappa-light-chain-enhancer of activated B cells (NF-B), IFN regulatory factor 3 (IRF3), and IRF7. Interestingly, we also observe that overexpression of IFN4 influences IFNL4 promoter activity, which may further be dependent on the retinoic acid-inducible gene-I (RIG-I)-like receptor pathway. Together, our work for the first time reports on the functional characterization of the human IFNL4 promoter.

Peptide-utilizing carbon starvation gene yjiY is required for flagella-mediated infection caused by Salmonella

Peptide metabolism forms an important part of the metabolic network of Salmonella and to acquire these peptides the pathogen possesses a number of peptide transporters. Whilst various peptide transporters known in Salmonella are well studied, very little is known about the carbon starvation (cst) genes cstA and yjiY, which are also predicted to be involved in peptide metabolism. We investigated the role of these genes in the metabolism and pathogenesis of Salmonella, and demonstrated for the first time, to the best of our knowledge, that cst genes actually participate in transport of specific peptides in Salmonella. Furthermore, we established that the carbon starvation gene yjiY affects the expression of flagella, leading to poor adhesion of the bacterium to host cells. In contrast to the previously reported role of cstA in virulence of Salmonella in Caenorhabditis elegans, we showed that yjiY is required for successful colonization of Salmonella in the mouse gut. Thus, cst genes not only contribute to the metabolism of Salmonella, but also influence its virulence.