Network Modelling using Transcription Sequence Data Reveals Novel MAPK Interactions Important for Drug Resistance
Ontology highlight
ABSTRACT:
ORGANISM(S): Aspergillus fumigatus
PROVIDER: GSE55743 | GEO | 2015/10/06
SECONDARY ACCESSION(S): PRJNA240892
REPOSITORIES: GEO
Similar Datasets
Project description:Aspergillus fumigatus response to caspofungin
| PRJNA486252 | ENA
Project description:The transcription factor CrzA influences cell wall organization in the pathogenic fungus Aspergillus fumigatus, and also binds to the promoter regions of chitin synthase genes upon exposure to the antifungal drug caspofungin. To gain an overview of the genes directly regulated by CrzA, the CrzA binding sites were determined genome-wide by ChIP-seq
2021-08-02 | GSE179132 | GEO
Project description:Fungal infections have increased dramatically in the last two decades and fighting infectious diseases require innovative approaches such as the combination of two drugs acting on different targets, or even target a salvage pathway of one of the drugs. The fungal cell wall biosynthesis is inhibited by the clinically used antifungal drug caspofungin. This antifungal activity has been found to be potentiated by humidimycin, a new natural product identified from the screening of a collection of 20,000 microbial extracts and with no major effect when used alone. The analysis of transcriptomes and selected A. fumigatus mutants indicated that humidimycin affects the high osmolarity glycerol response pathway. By combining humidimycin and caspofungin a strong increase of caspofungin efficacy was achieved, demonstrating that targeting different signaling pathways provides an excellent basis to develop novel anti-infective strategies.
2015-06-03 | GSE55663 | GEO
Project description:Competing endogenous RNA (ceRNA) regulations and crosstalk between various types of non-coding RNA in humans is an important and under-explored subject. Several studies have pointed out that an alteration in miRNA:target interaction can result in unexpected changes due to indirect and complex interactions. In this article, we defined a new network-based model that incorporates miRNA:ceRNA interactions with expression values. Our approach calculates network-wide effects of perturbations in the expression level of one or more nodes in the presence or absence of miRNA interaction factors such as seed type, binding energy. We carried out the analysis of large-scale miRNA:target networks from breast cancer patients. Highly perturbing genes identified by our approach coincide with breast cancer-associated genes and miRNAs. Our network-based approach takes the sponge effect into account and helps to unveil the crosstalk between nodes in miRNA:target network. The model has potential to reveal unforeseen regulations that are only evident in the network context. Our tool is scalable and can be plugged in with emerging miRNA effectors such as circRNAs, lncRNAs, and available as R package ceRNAnetsim: https://www.bioconductor.org/packages/release/bioc/html/ceRNAnetsim.html.
| S-EPMC7983860 | biostudies-literature
Project description:Aspergillus species are a leading cause of invasive fungal infections. As resistance to first-line therapy involving triazole antifungal agents is rising, second-line therapy with echinocandins is expanding. Resistance to echinocandins is well-established to result from amino acid substitutions in the echinocandin drug target β-(1,3)-D-glucan synthase encoded by the fks1 gene. Recently, we identified several high MIC clinical isolates of A. fumigatus from patients failing echinocandin therapy that did not contain any mutation in the fks1 gene, indicating that echinocandin resistance in these isolates results from an undefined mechanism. To explore possible new mechanisms of resistance, we used a lab-derived strain, RG101, with a nearly identical susceptibility phenotype, as a model system. This strain does not contain fks1 mutations but showed prominent resistance to the echinocandin class drug caspofungin (CAS), while remaining sensitive to other echinocandins, azoles and polyenes. Glucan synthase isolated from RG101 was fully sensitive to drug. Yet, exposure to CAS during its growth yielded a modified enzyme that was insensitive (4-log orders) in kinetic inhibition assays to CAS, as well as other echinocandins. This induction of cross-resistance by CAS was also observed in clinical isolates. To determine the nature of a presumptive posttranslational modification (PTM) of the enzyme, we analyzed whole enzyme PTMs, including the known hot-spot regions, for methylation, acetylation and phosphorylation. While we did not identify any PTMs linked to resistance, analysis of the lipid microenvironment of CAS-induced resistant enzyme revealed a prominent increase in the abundance of dihydrosphingosine (DhSph) and phytosphingosine (PhSph). Exogenous addition of DhSph and PhSph to sensitive enzyme in in vitro kinetic inhibition assays recapitulated the CAS insensitivity of the cellular-derived enzyme. To further examine induction of drug-induced resistance, we used an in vitro assay to demonstrate that CAS, but not other echinocandin class drugs, prominently induced the production of mitochondrial-derived Reactive Oxygen Species (ROS) in A. fumigatus. RNASeq evaluation of whole cells confirmed a ROS signature in cells treated with CAS. Dampening the formation of ROS by antimycin A or thiourea eliminated the induction of drug resistance by CAS. We conclude that CAS-induced formation of ROS promotes a cellular stress response that alters the composition of plasma membrane lipids surrounding glucan synthase, changing its enzymatic properties to make it insensitive to echinocandins. This stress-induced response constitutes a novel mechanism of echinocandin resistance in Aspergillus, with implications for drug resistance and/or tolerance mechanisms in other fungal pathogens.
2019-09-03 | PXD012438 | Pride
Project description:Drug-drug interactions (DDIs) can lead to serious and potentially lethal adverse events. In recent years, several drugs have been withdrawn from the market due to interaction-related adverse events (AEs). Current methods for detecting DDIs rely on the accumulation of sufficient clinical evidence in the post-market stage - a lengthy process that often takes years, during which time numerous patients may suffer from the adverse effects of the DDI. Detection methods are further hindered by the extremely large combinatoric space of possible drug-drug-AE combinations. There is therefore a practical need for predictive tools that can identify potential DDIs years in advance, enabling drug safety professionals to better prioritize their limited investigative resources and take appropriate regulatory action. To meet this need, we describe Predictive Pharmacointeraction Networks (PPINs) - a novel approach that predicts unknown DDIs by exploiting the network structure of all known DDIs, together with other intrinsic and taxonomic properties of drugs and AEs. We constructed an 856-drug DDI network from a 2009 snapshot of a widely-used drug safety database, and used it to develop PPIN models for predicting future DDIs. We compared the DDIs predicted based solely on these 2009 data, with newly reported DDIs that appeared in a 2012 snapshot of the same database. Using a standard multivariate approach to combine predictors, the PPIN model achieved an AUROC (area under the receiver operating characteristic curve) of 0.81 with a sensitivity of 48% given a specificity of 90%. An analysis of DDIs by severity level revealed that the model was most effective for predicting "contraindicated" DDIs (AUROC?=?0.92) and less effective for "minor" DDIs (AUROC?=?0.63). These results indicate that network based methods can be useful for predicting unknown drug-drug interactions.
| S-EPMC3631217 | biostudies-literature
Project description:The Mitogen-Activated Protein Kinase (MAPK) network consists of tightly interconnected signalling pathways involved in diverse cellular processes, such as cell cycle, survival, apoptosis and differentiation. Although several studies reported the involvement of these signalling cascades in cancer deregulations, the precise mechanisms underlying their influence on the balance between cell proliferation and cell death (cell fate decision) in pathological circumstances remain elusive. Based on an extensive analysis of published data, we have built a comprehensive and generic reaction map for the MAPK signalling network, using CellDesigner software. In order to explore the MAPK responses to different stimuli and better understand their contributions to cell fate decision, we have considered the most crucial components and interactions and encoded them into a logical model, using the software GINsim. Our logical model analysis particularly focuses on urinary bladder cancer, where MAPK network deregulations have often been associated with specific phenotypes. To cope with the combinatorial explosion of the number of states, we have applied novel algorithms for model reduction and for the compression of state transition graphs, both implemented into the software GINsim. The results of systematic simulations for different signal combinations and network perturbations were found globally coherent with published data. In silico experiments further enabled us to delineate the roles of specific components, cross-talks and regulatory feedbacks in cell fate decision. Finally, tentative proliferative or anti-proliferative mechanisms can be connected with established bladder cancer deregulations, namely Epidermal Growth Factor Receptor (EGFR) over-expression and Fibroblast Growth Factor Receptor 3 (FGFR3) activating mutations.
| S-EPMC3821540 | biostudies-literature
Project description:The diversity of human immunodeficiency virus type 1 (HIV-1) has given rise to multiple subtypes and recombinant strains. The majority of research into antiretroviral agents and drug resistance has been performed on subtype B viruses, yet non-subtype B strains are responsible for 90% of global infections. Although it seems that combination antiretroviral regimens are effective against all HIV-1 subtypes, there is emerging evidence of subtype differences in drug resistance, relevant to antiretroviral strategies in different parts of the world. For this purpose, extensive sampling of HIV genetic diversity, curation and analyses are required to inform antiretroviral strategies in different parts of the world.
| S-EPMC3951383 | biostudies-literature
Project description:To determine the effect of caspofungin (CSP) treatment and/or loss of the SET domain-containing CgSet4 protein on the transcriptional response of log-phase C. glabrata cells. RNA-Seq analysis was conducted on CAA medium-grown log-phase Candida glabrata wild-type (wt) and CgSET4-deleted (Cgset4D) cells in the presence and absence of caspofungin.
2022-09-12 | GSE202654 | GEO
Project description:ObjectivesThe aim of this study was to simulate the drug-drug interaction (DDI) between ritonavir-boosted atazanavir (ATV/r) and rifampicin (RIF) using physiologically based pharmacokinetic (PBPK) modelling, and to predict suitable dose adjustments for ATV/r for the treatment of people living with HIV (PLWH) co-infected with tuberculosis.MethodsA whole-body DDI PBPK model was designed using Simbiology 9.6.0 (MATLAB R2019a) and verified against reported clinical data for all drugs administered alone and concomitantly. The model contained the induction mechanisms of RIF and ritonavir (RTV), the inhibition effect of RTV for the enzymes involved in the DDI, and the induction and inhibition mechanisms of RIF and RTV on the uptake and efflux hepatic transporters. The model was considered verified if the observed versus predicted pharmacokinetic values were within twofold. Alternative ATV/r dosing regimens were simulated to achieve the trough concentration (Ctrough) clinical cut-off of 150 ng/mL.ResultsThe PBPK model was successfully verified according to the criteria. Simulation of different dose adjustments predicted that a change in regimen to twice-daily ATV/r (300/100 or 300/200 mg) may alleviate the induction effect of RIF on ATV Ctrough, with > 95% of individuals predicted to achieve Ctrough above the clinical cut-off.ConclusionsThe developed PBPK model characterized the induction-mediated DDI between RIF and ATV/r, accurately predicting the reduction of ATV plasma concentrations in line with observed clinical data. A change in the ATV/r dosing regimen from once-daily to twice-daily was predicted to mitigate the effect of the DDI on the Ctrough of ATV, maintaining plasma concentration levels above the therapeutic threshold for most patients.
| S-EPMC9481493 | biostudies-literature