Biology subjects

Mueller, S.

Publications and source records attributed to Mueller, S..

4 recordsLinked to original sources

bioRxiv2018

A Chemical Toolbox for the Study of Bromodomains and Epigenetic Signaling

Bromodomains (BRDs) are evolutionary conserved epigenetic protein interaction modules which recognize (\"read\") acetyl-lysine, however their role(s) in regulating cellular states and their potential as targets for the development of targeted treatment strategies is poorly understood. Here we present a set of 25 chemical probes, selective tool small molecule inhibitors, covering 29 human bromodomain targets. We comprehensively evaluate the selectivity of this probe-set using BROMOscan(R) and demonstrate the utility of the set using studies of muscle cell differentiation and triple negative breast cancer (TNBC). We identified cross talk between histone acetylation and the glycolytic pathway resulting in a vulnerability of TNBC cell lines to inhibition of BRPF2/3 BRDs under conditions of glucose deprivation or GLUT1 inhibition. This chemical probe set will serve as a resource for future applications in the discovery of new physiological roles of bromodomain proteins in normal and disease states, and as a toolset for bromodomain target validation.

cell biology↗

bioRxiv2018

SGC-GAK-1: a chemical probe for cyclin G associated kinase (GAK)

We describe SGC-GAK-1 (11), a potent, selective, and cell-active inhibitor of cyclin G associated kinase (GAK), together with a structurally-related negative control SGC-GAK-1N (14). SGC-GAK-1 is highly selective in a kinome-wide screen, but cellular engagement assays defined RIPK2 as a collateral target. We identified 18 as a potent inhibitor of RIPK2 lacking GAK activity. Together, the chemical probe set of 11, 14, and 18 can be used to interrogate the cellular biology of GAK inhibition.

cell biology↗

bioRxiv2018

Extensive recoding of dengue virus type 2 specifically reduces replication in primate cells without gain-of-function in Aedes aegypti mosquitoes

Dengue virus (DENV), an arthropod-borne (\"arbovirus\") virus causing a range of human maladies ranging from self-limiting dengue fever to the life-threatening dengue shock syndrome, proliferates well in two different taxa of the Animal Kingdom, mosquitoes and primates. Unexpectedly, mosquitoes and primates have distinct preferences when expressing their genes by translation, e.g. members of these taxa show taxonomic group-specific intolerance to certain codon pairs. This is called \"codon pair bias\". By necessity, arboviruses evolved to delicately balance this fundamental difference in their ORFs. Using the mosquito-borne human pathogen DENV we have undone the evolutionarily conserved genomic balance in its ORF sequence and specifically shifted the encoding preference away from primates. However, this recoding of DENV raised concerns of gain-of-function, namely whether recoding could inadvertently increase fitness for replication in the arthropod vector. Using mosquito cell cultures and two strains of Aedes aegypti we did not observe any increase in fitness in DENV2 variants codon pair deoptimized for humans. This ability to disrupt and control an arboviruss host preference has great promise towards developing the next generation of synthetic vaccines not only for DENV but for other emerging arboviral pathogens such as chikungunya virus and Zika virus.

microbiology↗

bioRxiv2017

bcGST - an interactive bias-correction method to identify over-represented gene-sets in boutique arrays

Motivation: Gene annotation and pathway databases such as Gene Ontology and Kyoto Encyclopedia of Genes and Genomes are important tools in Gene Set Test (GST) that describe gene biological functions and associated pathways. GST aims to establish an association relationship between a gene set of interest and an annotation. Importantly, GST tests for over-representation of genes in an annotation term. One implicit assumption of GST is that the gene expression platform captures the complete or a very large proportion of the genome. However, this assumption is neither satisfied for the increasingly popular boutique array nor the custom designed gene expression profiling platform. Specifically, conventional GST is no longer appropriate due to the gene set selection bias induced during the construction of these platforms.\n\nResults: We propose bcGST, a bias-corrected Gene Set Test by introducing bias correction terms in the contingency table needed for calculating the Fishers Exact Test (FET). The adjustment method works by estimating the proportion of genes captured on the array with respect to the genome in order to assist filtration of annotation terms that would otherwise be falsely included or excluded. We illustrate the practicality of bcGST and its stability through multiple differential gene expression analyses in melanoma and TCGA cancer studies.\n\nAvailability: The bcGST method is made available as a Shiny web application at http://shiny.maths.usyd.edu.au/bcGST/\n\nContact: kevin.wang@sydney.edu.au

bioinformatics↗