Predicting new molecular targets for rhein using network pharmacology

<p>Abstract</p> <p>Background</p> <p>Drugs can influence the whole biological system by targeting interaction reactions. The existence of interactions between drugs and network reactions suggests a potential way to discover targets. The in silico prediction of potential interactions between drugs and target proteins is of core importance for the identification of new drugs or novel targets for existing drugs. However, only a tiny portion of drug-targets in current datasets are validated interactions. This motivates the need for developing computational methods that predict true interaction pairs with high accuracy. Currently, network pharmacology has used in identifying potential drug targets to predicting the spread of drug activity and greatly contributed toward the analysis of biological systems on a much larger scale than ever before.</p> <p>Methods</p> <p>In this article, we present a computational method to predict targets for rhein by exploring drug-reaction interactions. We have implemented a computational platform that integrates pathway, protein-protein interaction, differentially expressed genome and literature mining data to result in comprehensive networks for drug-target interaction. We used Cytoscape software for prediction rhein-target interactions, to facilitate the drug discovery pipeline.</p> <p>Results</p> <p>Results showed that 3 differentially expressed genes confirmed by Cytoscape as the central nodes of the complicated interaction network (99 nodes, 153 edges). Of note, we further observed that the identified targets were found to encompass a variety of biological processes related to immunity, cellular apoptosis, transport, signal transduction, cell growth and proliferation and metabolism.</p> <p>Conclusions</p> <p>Our findings demonstrate that network pharmacology can not only speed the wide identification of drug targets but also find new applications for the existing drugs. It also implies the significant contribution of network pharmacology to predict drug targets.</p

Global network analysis of drug tolerance, mode of action and virulence in methicillin-resistant S. aureus

Background: Staphylococcus aureus is a major human pathogen and strains resistant to existing treatments continue to emerge. Development of novel treatments is therefore important. Antimicrobial peptides represent a source of potential novel antibiotics to combat resistant bacteria such as Methicillin-Resistant Staphylococcus aureus (MRSA). A promising antimicrobial peptide is ranalexin, which has potent activity against Gram-positive bacteria, and particularly S. aureus. Understanding mode of action is a key component of drug discovery and network biology approaches enable a global, integrated view of microbial physiology, including mechanisms of antibiotic killing. We developed a systems-wide functional association network approach to integrate proteome and transcriptome profiles, enabling study of drug resistance and mode of action. Results: The functional association network was constructed by Bayesian logistic regression, providing a framework for identification of antimicrobial peptide (ranalexin) response modules from S. aureus MRSA-252 transcriptome and proteome profiling. These signatures of ranalexin treatment revealed multiple killing mechanisms, including cell wall activity. Cell wall effects were supported by gene disruption and osmotic fragility experiments. Furthermore, twenty-two novel virulence factors were inferred, while the VraRS two-component system and PhoU-mediated persister formation were implicated in MRSA tolerance to cationic antimicrobial peptides. Conclusions: This work demonstrates a powerful integrative approach to study drug resistance and mode of action. Our findings are informative to the development of novel therapeutic strategies against Staphylococcus aureus and particularly MRSA.Publisher PDFPeer reviewe

Développement d'un vaccin vivant atténué pour la protection contre les infections intramammaires à partir d'un small-colony variant (SCV) de Staphylococcus aureus

Staphylococcus aureus est un pathogène opportuniste au potentiel de virulence élevé et particulièrement diversifié. Responsable d'intoxications alimentaires, d'infections localisées suppurées et, dans certains cas extrêmes, d’infections systémiques graves, celui-ci est pleinement capable de causer la mortalité chez des patients immunodéprimés. Pourtant, S. aureus est également la cause de divers types d’infections à fort caractère chronique et de persistance chez l’homme et les animaux, infections qui sont difficiles à traiter par antibiothérapie, et qui le plus souvent échappent au contrôle du système immunitaire. Les mammites à S. aureus sont considérées comme l’une des maladies majeures chez les bovins d’élevage, causant de lourdes pertes économiques pour l’industrie laitière. Elles se caractérisent fréquemment par des formes sous-cliniques et chroniques, rendant leur diagnostic et contrôle difficiles. La vaccination contre les infections intramammaires à S. aureus pourrait permettre de protéger les animaux contre les nouvelles infections, diminuant la propagation contagieuse du pathogène lors de la traite, et permettre ainsi de réduire la prévalence de celui-ci dans les troupeaux. Pourtant, aucune formulation n’a pu montrer de réelle efficacité de protection à ce jour. Puisque le déploiement d’une immunité adaptative strictement basée sur la réponse en anticorps n’est pas adéquat pour protéger contre un pathogène chronique tel que S. aureus, le besoin criant de développer de nouvelles méthodes et formulations de vaccin se penche maintenant sur l’amélioration de la réponse à médiation cellulaire, considérée indispensable pour une meilleure protection. Les vaccins vivants atténués, basés sur leur capacité à imiter une infection naturelle, ont su prouver leur efficacité dans le développement d’immunités spécifiques et fortes contre de nombreux microorganismes, en particulier les pathogènes intracellulaires et chroniques. On a démontré que ces souches atténuées pouvait être utilisées comme vecteurs antigéniques et aider à balancer la réponse vers des fonctions effectrices de l’immunité qui permettent de combattre plus adéquatement ce type d’infections. Cette étude a eu pour objectif principal la construction d’une souche atténuée de S. aureus pour l’utilisation à titre de vaccin vivant contre les infections intramammaires. Cette souche vaccinale atténuée est fondée sur la stabilisation génétique du phénotype small-colony variant, à la fois comme base d’atténuation de la virulence et comme facteur permettant l’internalisation temporaire et non destructive dans les cellules de l’hôte. Cette souche a été caractérisée et évaluée dans un modèle d’infection de cellules en culture et dans un modèle in vivo de mammite chez la souris, qui ont tous deux pu confirmer sa robuste atténuation et établir un première preuve de son innocuité comme vaccin

Comparative genomics of the skin Staphylococci

The human skin is a complex ecosystem which supports a diverse population of bacteria. Comparative genomic analyses are increasingly being used to explore the functional potential of this bacterial population . The ubiquity of Staphylococcus on human skin means this genus represents the most well-studied of the microbial skin residents, however most analysis has focussed on the significant clinical pathogenic species S. epidermidis and S. aureus. To investigate the biology of S. hominis, the second most frequent Staphylococcus species isolated from human skin after S. epidermidis, seven isolates were sequenced using Illumina and PacBio technologies. An intraspecies comparative genomic analysis was performed with these and several publically available S. hominis genomes to identify core and accessory genes. The complement of encoded cell wall-anchored proteins was studied using bioinformatics to describe the range of surface-attached proteins and revealed a unique species set. Investigation also revealed the presence of S. hominis genes described as virulence factors in S. aureus and S. epidermidis. This further highlights non-pathogenic staphylococci as a reservoir of genes, which can be exchanged with pathogenic S. aureus, and the potential for recruitment of these genes into virulence pathways. Interspecies comparative analysis of twenty Staphylococcus species, based on clusters of orthologous genes, confirmed the designation of staphylococcal species groups previously established by DNA-DNA hybridisation and single gene analysis methods. The bioinformatic algorithm randomForest was used to identify drivers forming species groups based on the orthologous gene cluster analysis leading to a subset of orthologous clusters defined as being contributory. This interspecies analysis also revealed diversity between the staphylococcal species groups with respect to their response mechanisms for antimicrobial peptide (AMP) resistance. Specifically, the presence or absence of the BraRS two-component system (TCS) was identified to be one of the important drivers differentiating a nine species member group that included S. aureus, S. hominis and S. epidermidis.. Experimental evolution in the presence of the lantibiotic nisin was used to dissect differences in the global response of the BraRS-positive species S. hominis and S. aureus, from the BraRS-negative species S. saprophyticus, . Identified SNPs from the resistance evolution revealed complex relationships between the regulons of staphylococcal TCSs and identified that YurK should be investigated for a potential role in AMP resistance of S. aureus and S. hominis

Strategies to identify novel therapeutic targets for oesophageal adenocarcinoma

Oesophageal adenocarcinoma (OAC) is a leading cause of cancer death in the UK and current systemic therapies are ineffective for the majority of patients. The central aim of this work was to explore strategies to identify novel therapeutic targets. Research has failed, thus far, to identify a dominant oncogene in OAC, although the tumour suppressor p53 is frequently mutated. Inhibiting the mitotic kinase, polo-like kinase 1 (PLK-1), was proposed as a synthetic lethal strategy. PLK-1 was demonstrated to be over-expressed in both verified OAC cell lines and human OAC tissue compared to non-transformed cells and epithelium. Mutation of p53 was associated with over-expression of PLK-1 in both OAC and ovarian cancer tissue. Using a carefully validated viability assay, both an established and novel PLK-1 inhibitor were demonstrated to induce a G2/M arrest and reduce OAC cell proliferation. Relative selectivity was demonstrated for OAC compared to non-transformed cells. This therapeutic window could be enhanced with the induction of cancer cell cytotoxicity by pulsed administration of a short half-life inhibitor. Immunotherapeutics offer potential tumour-selectivity but no OAC-specific proteins have been defined. A comparative proteomic approach was employed to identify OAC-specific proteins as potential therapeutic targets. A tissue resource was established and methods to lyse fresh frozen biopsies optimised. An isobaric quantitative proteomic workflow was applied to OAC and matched normal biopsies and quantitative accuracy confirmed for 6 candidate proteins by immunohistochemistry. Proteome coverage and quantitative dynamic range were compared between isobaric and label-free systematic sequencing proteomic strategies applied to further patients’ tissues. The challenges of combining incomplete datasets were approached with a Bayesian framework to estimate the probability that a protein was missed during an experiment compared to not being present in the sample. This method was applied to generate a complete set of protein identifications and relative tissue expression. To gain insight into the dysregulated cellular processes in human OAC tissue, a network analysis was applied to the quantitative proteomic data. Enriched functional clusters were identified suggesting deranged glucose metabolism, potentially due to the Warburg effect. These findings were duplicated and candidate tumour-specific proteins identified in a further set of biopsies using the optimised quantitative proteomic method. The combined quantitative oesophageal proteomic dataset represents the largest in OAC to date. This thesis demonstrates a hypothesis-driven, synthetic lethal approach can yield cancer-selective therapeutic effects. Novel candidate therapeutic targets are also revealed through the development of quantitative proteomic methods and the application of network analysis