Biology subjects

Ascher, D. B.

Publications and source records attributed to Ascher, D. B..

32 records · Page 2Linked to original sources

bioRxiv2022

Drug resistance-associated mutations in Plasmodium UBP-1 disrupt ubiquitin hydrolysis

Deubiquitinating enzymes function to cleave ubiquitin moieties from modified proteins, serving to maintain the pool of free ubiquitin in the cell while simultaneously impacting the fate and function of a target protein. Like all eukaryotes, Plasmodium parasites rely on the dynamic addition and removal of ubiquitin for their own growth and survival. While humans possess around 100 DUBs, Plasmodium contains [~]20 putative ubiquitin hydrolases, many of which bear little to no resemblance to those of other organisms. In this study, we characterize PfUBP-1, a large ubiquitin hydrolase unique to Plasmodium spp that has been linked to endocytosis and drug resistance. We demonstrate its ubiquitin activity, linkage specificity and assess the repercussions of point mutations associated with drug resistance on catalytic activity and parasite fitness.

microbiology↗

bioRxiv2022

A recurrent de novo splice site variant involving DNM1 alternative exon 10a causes developmental and epileptic encephalopathy through a dominant-negative mechanism

Heterozygous pathogenic variants in DNM1 cause developmental and epileptic encephalopathy (DEE) due to a dominant-negative mechanism impeding vesicular fission. Thus far, pathogenic variants in DNM1 have been studied using a canonical transcript that includes the alternatively spliced exon 10b. However, after performing RNA sequencing in thirty-nine pediatric brain samples, we find the primary transcript expressed in the brain includes the downstream exon 10a instead. Using this information, we evaluated genotype-phenotype correlations of variants affecting exon 10a and identified a cohort of eleven previously unreported individuals. Eight individuals harbor a recurrent de novo splice site variant, NG_029726.1(NM_001288739.1):c.1197-8G>A, which affects exon 10a and leads to DEE consistent with the classical DNM1 phenotype. We find this splice site variant leads to disease through an unexpected dominant-negative mechanism. Functional testing reveals an in-frame upstream splice acceptor causing insertion of two amino acids predicted to impair oligomerization-dependent activity. This is supported by neuropathological samples showing accumulation of synaptic vesicles adherent to the plasma membrane consistent with impaired vesicular fission. Two additional individuals with missense variants affecting exon 10a, p.(Arg399Trp) and p.(Gly401Asp), had a similar DEE phenotype. In contrast, a single individual with a missense variant affecting exon 10b, p.(Pro405Leu), which is less expressed in the brain, had a correspondingly less severe presentation. Thus, we implicate variants affecting exon 10a as causing the severe DEE typically associated with DNM1-related disorders. We highlight the importance of considering relevant isoforms for disease-causing variants, as well as the possibility of splice site variants acting through a dominant-negative mechanism.

genetics↗

bioRxiv2021

VIVID: a web application for variant interpretation and visualisation in multidimensional analyses

Large-scale comparative genomics- and population genetic studies generate enormous amounts of polymorphism data in the form of DNA variants. Ultimately, the goal of many of these studies is to associate genetic variants to phenotypes or fitness. We introduce VIVID, an interactive, user-friendly web application that integrates a wide range of approaches for encoding genotypic to phenotypic information in any organism or disease, from an individual or population, in three-dimensional (3D) space. It allows mutation mapping and annotation, calculation of interactions and conservation scores, prediction of harmful effects, analysis of diversity and selection, and 3-dimensional (3D) visualisation of genotypic information encoded in Variant Call Format (VCF) on AlphaFold2 protein models. VIVID enables the rapid assessment of genes of interest in the study of adaptive evolution and the genetic load, and it helps prioritising targets for experimental validation. We demonstrate the utility of VIVID by exploring the evolutionary genetics of the parasitic protist Plasmodium falciparum, revealing geographic variation in the signature of balancing selection in potential targets of functional antibodies.

bioinformatics↗

bioRxiv2021

A structural biology community assessment of AlphaFold 2 applications

Most proteins fold into 3D structures that determine how they function and orchestrate the biological processes of the cell. Recent developments in computational methods have led to protein structure predictions that have reached the accuracy of experimentally determined models. While this has been independently verified, the implementation of these methods across structural biology applications remains to be tested. Here, we evaluate the use of AlphaFold 2 (AF2) predictions in the study of characteristic structural elements; the impact of missense variants; function and ligand binding site predictions; modelling of interactions; and modelling of experimental structural data. For 11 proteomes, an average of 25% additional residues can be confidently modelled when compared to homology modelling, identifying structural features rarely seen in the PDB. AF2-based predictions of protein disorder and protein complexes surpass state-of-the-art tools and AF2 models can be used across diverse applications equally well compared to experimentally determined structures, when the confidence metrics are critically considered. In summary, we find that these advances are likely to have a transformative impact in structural biology and broader life science research.

biophysics↗

bioRxiv2021

Sequence grammar underlying unfolding and phase separation of globular proteins

Aberrant phase separation of globular proteins is associated with many diseases. Here, we use a model protein system to understand how unfolded states of globular proteins drive phase separation and the formation of unfolded protein deposits (UPODs). For UPODs to form, the concentrations of unfolded molecules must be above a threshold value. Additionally, unfolded molecules must possess appropriate sequence grammars to drive phase separation. While UPODs recruit molecular chaperones, their compositional profiles are also influenced by synergistic physicochemical interactions governed by the sequence grammars of unfolded proteins and sequence features of cellular proteins. Overall, we find that the driving forces for phase separation and the compositional profiles of UPODs are governed by the sequence grammar of unfolded proteins. Our studies highlight the need for uncovering the sequence grammars of unfolded proteins that drive UPOD formation and lead to gain-of-function interactions whereby proteins are aberrantly recruited into UPODs. HighlightsO_LIUnfolded states of globular proteins phase separate to form UPODs in cells C_LIO_LIThe fraction of unfolded molecules and the sticker grammar govern phase separation C_LIO_LIHydrophobic residues act as stickers that engage in intermolecular interactions C_LIO_LISticker grammar also influences gain-of-function recruitment into aberrant UPODs C_LI

biophysics↗

bioRxiv2021

Insights from spatial measures of intolerance to identify pathogenic variants in developmental and epileptic encephalopathies

Developmental and epileptic encephalopathies (DEEs) are a group of epilepsies with early onset and severe symptoms that sometimes lead to death. While a number of genes have been successfully implicated, it remains challenging to identify causative mutations within these genes from the background variation present in all individuals due to disease heterogeneity. Our ability to detect likely pathogenic variants has continued to improve as in silico predictors of deleteriousness have advanced. We investigate their use in prioritising likely pathogenic variants in epileptic encephalopathy patient whole exome sequences and show that the inclusion of structure-based predictors of intolerance improve upon previous attempts to demonstrate enrichment within epilepsy genes.

neuroscience↗

bioRxiv2021

HGDiscovery: an online tool providing functional and phenotypic information on novel variants of homogentisate 1,2- dioxigenase

Alkaptonuria (AKU), a rare genetic disorder, is characterized by the accumulation of homogentisic acid (HGA) in the body. Affected individuals lack enough functional levels of an enzyme required to breakdown HGA. Mutations in the HGD gene cause AKU and they are responsible for deficient levels of functional homogentisate 1,2-dioxygenase (HGD), which, in turn, leads to excess levels of HGA. Although HGA is rapidly cleared from the body by the kidneys, in the long term it starts accumulating in various tissues, especially cartilage. Over time (rarely before adulthood), it eventually changes the color of affected tissue to slate blue or black. Here we report a comprehensive mutation analysis of 111 pathogenic and 190 non-pathogenic HGD missense mutations using protein structural information. Using our comprehensive suite of graph-based signature methods, mCSM complemented with sequence-based tools, we studied the functional and molecular consequences of each mutation on protein stability, interaction and evolutionary conservation. The scores generated from the structure and sequence-based tools were used to train a supervised machine learning algorithm with 84% accuracy. The empirical classifier was used to generate the variant phenotype for novel HGD missense mutations. All this information is deployed as a user friendly freely available web server called HGDiscovery (http://biosig.unimelb.edu.au/hgdiscovery/).

bioinformatics↗

bioRxiv2021

Modelling tuberculosis drug resistance amplification rates in high-burden settings

BackgroundAntimicrobial resistance develops following the accrual of mutations in the bacterial genome, and may variably impact organism fitness and hence, transmission risk. Classical representation of tuberculosis (TB) dynamics using a single or two strain (DS/MDR-TB) model typically does not capture elements of this important aspect of TB epidemiology. To understand and estimate the likelihood of resistance spreading in high drug-resistant TB incidence settings, we used molecular understanding to develop a compartmental epidemiological model of Mycobacterium tuberculosis (Mtb) transmission. MethodsA four-strain (drug-susceptible (DS), isoniazid mono-resistant (INH-R), rifampicin mono-resistant (RIF-R) and multidrug-resistant (MDR)) compartmental deterministic Mtb transmission model was developed to explore the progression from DS-to MDR-TB. The model incorporated strain-specific fitness costs and was calibrated using data from national tuberculosis prevalence surveys and drug resistance surveys from Philippines and Viet Nam. Using an adaptive Metropolis algorithm, we estimated drug resistance amplification and transmission rates. ResultsThe posterior estimates for the proportion of isoniazid mono-resistant amplification among treatment failure was 0.75 (0.64 - 0.85) for Philippines and 0.55 (0.39 - 0.63) for Viet Nam. The proportion of rifampicin mono-resistant amplification among treatment failure was 0.05 (0.04 - 0.06) for Philippines and 0.011 (0.010 - 0.012) for Viet Nam. In Philippines, the estimated proportion of primary resistance resulting from transmission was 56% (42 - 68) for INH-R, 48% (34 - 62) for RIF-R and 42% (34 - 50) for MDR-TB. For Viet Nam, the estimated proportion of drug resistance due to transmission was 79% (70 - 86) for INH-R, 68% (58 - 75) for RIF-R and 50% (45 - 53) for MDR-TB. DiscussionRIF-R strains were more likely to be transmitted than acquired through amplification, while both mechanisms of acquisition were important contributors in the case of INH-R. These findings highlight the complexity of drug resistance dynamics in high-incidence settings, and emphasize the importance of prioritizing testing algorithms which also allow for early detection of INH-R.

microbiology↗

bioRxiv2020

Designing safe and potent herbicides with the cropCSM online resource

Herbicides have revolutionised weed management, increased crop yields and improved profitability allowing for an increase in worldwide food security. Their widespread use, however, has also led to not only a rise in resistance but also concerns about their environmental impact. To help identify new, potent, non-toxic and environmentally safe herbicides we have employed interpretable predictive models to develop the online tool cropCSM (http://biosig.unimelb.edu.au/crop_csm).

bioinformatics↗

bioRxiv2020

Mercury methylation by metabolically versatile and cosmopolitan marine bacteria

Microbes transform aqueous mercury (Hg) into methylmercury (MeHg), a potent neurotoxin in terrestrial and marine food webs. This process requires the gene pair hgcAB, which encodes for proteins that actuate Hg methylation, and has been well described for anoxic environments. However, recent studies report potential MeHg formation in suboxic seawater, although the microorganisms involved remain poorly understood. In this study, we conducted large-scale multi-omic analyses to search for putative microbial Hg methylators along defined redox gradients in Saanich Inlet (SI), British Columbia, a model natural ecosystem with previously measured Hg and MeHg concentration profiles. Analysis of gene expression profiles along the redoxcline identified several putative Hg methylating microbial groups, including Calditrichaeota, SAR324 and Marinimicrobia, with the last by far the most active based on hgc transcription levels. Marinimicrobia hgc genes were identified from multiple publicly available marine metagenomes, consistent with a potential key role in marine Hg methylation. Computational homology modelling predicted that Marinimicrobia HgcAB proteins contain the highly conserved structures required for functional Hg methylation. Furthermore, a number of terminal oxidases from aerobic respiratory chains were associated with several SI putative novel Hg methylators. Our findings thus reveal potential novel marine Hg-methylating microorganisms with a greater oxygen tolerance and broader habitat range than previously recognised.

microbiology↗

bioRxiv2020

COVID-3D: An online resource to explore the structural distribution of genetic variation in SARS-CoV-2 and its implication on therapeutic development

The emergence of the COVID-19 pandemic has spurred a global rush to uncover basic biological mechanisms, to inform effective vaccine and drug development. Despite viral novelty, global sequencing efforts have already identified genomic variation across isolates. To enable easy exploration and spatial visualization of the potential implications of SARS-CoV-2 mutations on infection, host immunity and drug development we have developed COVID-3D (http://biosig.unimelb.edu.au/covid3d/).

bioinformatics↗

bioRxiv2019

Widespread remodelling of proteome solubility in response to different protein homeostasis stresses

The accumulation of protein deposits in neurodegenerative diseases involves the presence of a metastable subproteome vulnerable to aggregation. To investigate this subproteome and the mechanisms that regulates it, we measured the proteome solubility of the Neuro2a cell line under protein homeostasis stresses induced by Huntington Disease proteotoxicity; Hsp70, Hsp90, proteasome and ER-mediated folding inhibition; and oxidative stress. We found one-quarter of the proteome extensively changed solubility. Remarkably, almost all the increases in insolubility were counteracted by increases in solubility of other proteins. Each stress directed a highly specific pattern of change, which reflected the remodelling of protein complexes involved in adaptation to perturbation, most notably stress granule proteins, which responded differently to different stresses. These results indicate that the robustness of protein homeostasis relies on the absence of proteins highly vulnerable to aggregation and on large changes in aggregation state of regulatory mechanisms that restore protein solubility upon specific perturbations.

biochemistry↗

bioRxiv2019

Computational Saturation Mutagenesis of the β subunit of RNA polymerase in Mycobacterium leprae

In contrast to the situation with tuberculosis, rifampin resistance in leprosy may remain undetected due to the lack of rapid and effective diagnostic methods. A quick and reliable method is essential to determine the impacts of emerging detrimental mutations. The functional consequences of missense mutations within the {beta}-subunit of RNA polymerase in Mycobacterium leprae (M. leprae) contribute to phenotypic rifampin resistance outcomes in leprosy. Here we report in-silico saturation mutagenesis of all residues in the {beta}-subunit of RNA polymerase to all other 19 amino acid types and predict their impacts on overall thermodynamic stability, on interactions at subunit interfaces, and on {beta}-subunit-RNA and rifampin affinities using state-of-the-art structure, sequence and normal mode analysis-based methods. A total of 21,394 mutations were analysed, and it was noted that mutations in the conserved residues that line the active-site cleft show largely destabilizing effects, resulting in increased relative solvent accessibility and concomitant decrease in depth of the mutant residues. The mutations at residues S437, G459, H451, P489, K884 and H1035 are identified as extremely detrimental as they induce highly destabilizing effects on the overall stability, nucleic acid and rifampin affinities. Destabilizing effects were predicted for all the experimentally identified rifampin-resistant mutations in M. leprae indicating that this model can be used as a surveillance tool to monitor emerging detrimental mutations conferring rifampin resistance in leprosy.\n\nAUTHOR SUMMARYEmergence of primary and secondary drug resistance to rifampin in leprosy is a growing concern and poses threat to the leprosy control and elimination measures globally. In the absence of an effective in-vitro system to detect and monitor phenotypic rifampin resistance in leprosy, most of the diagnosis relies on detecting mutations in the drug resistance determining regions of the rpoB gene that encodes the {beta} subunit of RNA polymerase in M. leprae. Few labs in the world perform mouse food pad propagation of M. leprae in the presence of drugs (rifampin) to determine growth patterns and confirm resistance, however the duration of these methods lasts from 8 to 12 months making them impractical for diagnosis. Understanding molecular mechanisms of drug resistance is vital to associating mutations to clinical resistance outcomes in leprosy. Here we propose an in-silico saturation mutagenesis approach to comprehensively elucidate the structural implications of any mutations that exist or can arise in the {beta} subunit of RNA polymerase in M. leprae. Most of the predicted mutations may not occur in M. leprae due to fitness costs but the information thus generated by this approach help decipher the impacts of mutations across the structure and conversely enable identification of stable regions in the protein that are least impacted by mutations (mutation coolspots) which can be a choice for small molecule binding and structure guided drug discovery.

bioinformatics↗

bioRxiv2017

Evolution of carbapenem resistance in Acinetobacter baumannii during a prolonged infection

Acinetobacter baumannii is a common causative agent of hospital-acquired infections and a leading cause of infection in burns patients. Carbapenem resistant A. baumannii is considered a major public health threat and has been identified by the World Health Organization as the top priority organism requiring new antimicrobials. The most common mechanism for carbapenem resistance in A. baumannii is via horizontal acquisition of carbapenemase genes. In this study, we sampled 20 A. baumannii isolates from a patient with extensive burns, and characterized the evolution of carbapenem resistance over a 45-day period via Illumina and Oxford Nanopore sequencing. All isolates were multi-drug resistant, carrying two genomic islands that harboured several antibiotic resistance genes. Most isolates were genetically identical and represent a single founder genotype. We identified three novel non-synonymous substitutions associated with meropenem resistance: F136L and G288S in AdeB (part of the AdeABC efflux pump) associated with an increase in meropenem MIC to [≥]8 g/mL; and A515V in FtsI (PBP3, a penicillin-binding protein) associated with a further increase in MIC to 32 g/mL. Structural modelling of AdeB and FtsI showed that these mutations affected their drug binding sites and revealed mechanisms for meropenem resistance. Notably, one of the adeB mutations arose prior to meropenem therapy but following ciprofloxacin therapy, suggesting exposure to one drug whose resistance is mediated by the efflux pump can induce collateral resistance to other drugs to which the bacteria has not yet been exposed.\n\nDATA SUMMARYO_LIAll raw genome sequences, including Illumina paired end short reads and Oxford Nanopore long reads, have been deposited in the SRA under project PRJNA396979. Individual accessions for each strain are provided in Table S1.\nC_LIO_LIThe annotated genome assembly for strain A2, the reference genome for the founder genotype, has been submitted to GenBank under accession CP024124 (chromosome) and CP024125 (plasmid).\nC_LIO_LIHybrid assemblies for strains A1, A3, A8, A13, A15, A17 and A20 are available in FigShare, doi: 10.4225/49/5987e14e9b530 (note they were not deposited in GenBank as they differ from A2 by only 1-4 SNPs as indicated).\nC_LI\n\nIMPACT STATEMENTSAcinetobacter baumannii is a highly drug resistant pathogen that is frequently found within intensive care units (ICUs) and especially impacts patients with severe burns. While several studies have examined the global population structure of A. baumannii, few have investigated within-host evolution of A. baumannii in direct response to antibiotic treatment in a single patient. Here, we analysed the genetic evolution of A. baumannii isolated from a patient with severe burns over the course of their stay in ICU. The A. baumannii population on this patient was highly drug resistant, carrying two distinct genomic islands encoding resistance to several antibiotics but not carbapenems. The bacterial population comprised four distinct subclades, two of which had evolved carbapenem resistance over the course of antibiotic treatment through novel mutations in genes associated with drug binding. One subclade was also transmitted to another patient on the ward. While carbapenem resistance is common in A. baumannii, this is generally attributed to horizontally transferred carbapenemase genes. These data provide evidence for carbapenem resistance arising in vivo via non-synonymous substitutions during a single infection episode, demonstrating carbapenem resistance can emerge in genetic isolation in response to exposure to carbapenems and other drugs.

genomics↗