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Biology subjects

Jones, S. J.

Publications and source records attributed to Jones, S. J..

16 recordsLinked to original sources

Emergence and spread of outbreak-adapted Candidozyma auris harboring mutations in RBA1

Candidozyma auris is an emerging healthcare-associated fungal pathogen, increasingly isolated from clinical outbreaks, with a high propensity to colonize patients and the medical environment. Here, we leveraged C. auris isolates from multi-facility clinical outbreaks to identify genomic patho-adaptations promoting persistence and dissemination in the healthcare environment. Genomic and phylogenetic analyses revealed loss-of-function mutations in the uncharacterized C. auris transcription factor gene RBA1 to have independently emerged multiple times within these outbreaks. We demonstrate loss of RBA1 increases C. auris adhesion to plastic and human keratinocytes, enhances biofilm formation, and exacerbates fungal burden in a mouse model of catheter-associated urinary tract infection. Finally, we uncover mutations in RBA1 have emerged during multiple C. auris outbreaks across the globe, and that RBA1 mutant lineages are present among large ongoing clinical outbreaks. These results reveal loss-of-function mutations in C. auris RBA1 as a novel and clinically relevant genetic determinant of enhanced outbreak characteristics.

microbiology↗

The genome sequence of the hemlock woolly adelgid, Adelges tsugae Annand 1924

The genome of the hemlock woolly adelgid (Adelges tsugae) is presented in 10 chromosomal pseudomolecules along with 132 unplaced scaffolds for a combined length of 216.56 Mb. The genome is highly contiguous, with a benchmarking universal single-copy orthologs (BUSCO) completion score of 98.25%, an N50 of 20.54 Mb, and the longest scaffold 37.41 Mb in length. On the basis of chromosomal synteny with other aphid genomes, the hemlock woolly adelgids genome is composed of 8 autosomes and two sex (X) chromosomes. Annotation of the assembly identified 11,800 coding genes, 1,930 non-coding genes, and 20,403 mRNA transcripts. The mitogenome is also presented in a single, annotated, circular contig 25,980 bases in length. Species taxonomyEukaryota; Metazoa; Arthropoda; Hexapoda; Insecta; Pterygota; Neoptera; Paraneoptera; Hemiptera; Sternorrhyncha; Aphidomorpha; Adelgoidea; Adelgidae; Adelges; Annandina; Adelges (Annandina) tsugae Annand, 1924 (NCBI:txid357502)

genomics↗

Acquired Amphotericin B Resistance Attributed to a Mutated ERG3 in Candidozyma auris

First identified in 2009, Candidozyma auris (formerly Candida auris) is an emerging multidrug resistant fungus that can cause invasive infections with a crude mortality rate ranging from 30-60%. Currently, 30-50% of C. auris isolates are intrinsically resistant to amphotericin B. In this work, we characterized a clinical case of acquired amphotericin B resistance using whole genome sequencing, a large-scale phenotypic screen, comprehensive sterol profiling, and genotypic reversion using CRISPR. Data obtained in this work provides evidence that a deletion resulting in a frameshift in ERG3 contributes to the observed resistant phenotype. Characterization of this isolate also revealed a fitness cost is associated with the abrogation of ergosterol production and its replacement with other late-stage sterols. This article presents a clinical case description of amphotericin B resistance from a frameshift mutation in ERG3 in C. auris and marks an advancement in the understanding of antifungal resistance in this fungal pathogen.

genetics↗

A nuclear TRiC/CCT chaperonin assembles meiotic HORMAD proteins into chromosome axes competent for crossing over

The meiotic chromosome axis organizes chromatin and sets the stage for homolog pairing and recombination. Meiotic HORMA domain proteins (mHORMADs) are conserved axis components that conformationally transform during target binding. In C. elegans, four functionally distinct mHORMADs directly interact, but how binding between them is restricted to axis assembly is unknown. Using a mutation in the mHORMADs that delays axis assembly, we isolated a suppressor mutation in a TRiC/CCT chaperonin subunit that restored mHORMAD localization. CCT-4 associates with meiotic chromatin and forms in vivo complexes with mHORMADs, while germline disruption of TRiC results in axis defects, indicating a nuclear function for TRiC alongside meiotic chromosomes. We propose that chromosome-tethered TRiC folds mHORMADs into a conformationally active local population required for axis morphogenesis. More broadly, our results support the model that spatially-restricted folding by TRiC/CCT is a mechanism of controlling the assembly of multimeric complexes that function in tightly co-ordinated events.

cell biology↗

A Candidozyma (Candida) auris-optimized Episomal Plasmid Induced Cas9-editing system reveals the direct impact of the S639F encoding FKS1 mutation

ObjectivesMutations in the Candidozyma (Candida) auris {beta}-glucan synthase gene (FKS1) altering S639 are frequently associated with clinical echinocandin resistance. However, the direct impact of these mutations remains uncharacterized. We have developed a novel C. auris-optimized Episomal Plasmid-Induced Cas9 (EPIC) gene-editing system capable of recyclable precision genome editing and demonstrate the contribution of FKS1S639F mutation to echinocandin resistance. MethodsThe EPIC gene-editing system was generated for optimized use in C. auris, and ADE2 modification was evaluated in 5 C. auris clades. Mutations leading to Fks1S639F and Fks1WT were placed into echinocandin-susceptible and echinocandin-resistant isolates from Clade-III and -I, respectively, using the EPIC system. Echinocandin susceptibility was determined by CLSI broth microdilution, and cell wall abundance of chitin and {beta}-glucan was assessed by staining with Calcofluor White (CFW) and Aniline Blue (AB). ResultsThe EPIC system was capable of targeted ADE2 editing in C. auris isolates from 5 genetic clades and shown to be precise by confirmatory sequencing of 50 transformants. A single nucleotide change in FKS1 resulting in either the S639F substitution or a silent synonymous mutation was introduced in an echinocandin-susceptible Clade-III isolate. Precision FKS1 editing by the EPIC system was confirmed by whole genome sequencing. Subsequent susceptibility testing demonstrated introduction of the FKS1 S639F mutation to increase resistance to echinocandins. Moreover, introduction of a wildtype Fks1 sequence to an echinocandin-resistant Clade-I clinical isolate, correcting the FKS1S639F mutation, resulted in a restoration of echinocandin sensitivity. Evaluation of cell wall composition showed isolates or strains harboring FKS1S639F to contain significantly elevated {beta}-glucan and chitin content relative to isogenic comparators. ConclusionsThese data demonstrate the potential of our EPIC system in its ability to introduce single nucleotide substitutions in multiple C. auris clade backgrounds while revealing the direct impact of the S639F encoding FKS1 mutation on echinocandin resistance.

microbiology↗

Mapping in silico genetic networks of the KMT2D tumour suppressor gene to uncover novel functional associations and cancer cell vulnerabilities

Loss-of-function (LOF) alterations in tumour suppressor genes cannot be directly targeted. Approaches characterising gene function and vulnerabilities conferred by such mutations are required. Here, we computationally map genetic networks of KMT2D, a tumour suppressor gene frequently mutated in several cancer types. Using KMT2D loss-of-function (KMT2DLOF) mutations as a model, we illustrate the utility of in silico genetic networks in uncovering novel functional associations and vulnerabilities in cancer cells with LOF alterations affecting tumour suppressor genes. We revealed genetic interactors with functions in histone modification, metabolism, and immune response, and synthetic lethal (SL) candidates, including some encoding existing therapeutic targets. Analysing patient data from The Cancer Genome Atlas and the Personalized OncoGenomics Project, we showed, for example, elevated immune checkpoint response markers in KMT2DLOF cases, possibly supporting KMT2DLOF as an immune checkpoint inhibitor biomarker. Our study illustrates how tumour suppressor gene LOF alterations can be exploited to reveal potentially targetable cancer cell vulnerabilities.

bioinformatics↗

Ploidetect enables pan-cancer analysis of the causes and impacts of chromosomal instability

Cancers routinely exhibit chromosomal instability that results in copy number variants (CNVs), namely changes in the abundance of genomic material. Unfortunately, the detection of these variants in cancer genomes is difficult. We present Ploidetect, a software package that effectively identifies CNVs within whole-genome sequenced tumors. Ploidetect utilizes a coarse-to-fine segmentation approach which yields highly contiguous segments while allowing for focal CNVs to be detected with high sensitivity. We benchmark Ploidetect against popular CNV tools using synthetic data, cell line data, and real-world metastatic tumor data, and find an improvement in sensitivity and accuracy while maintaining low levels of oversegmentation. We show that the improved CNV sensitivity enables Ploidetect to recover recurrent homozygous deletions and genes associated with chromosomal instability in a multi-cancer cohort of 687 patients. Using highly contiguous CNV calls afforded by Ploidetect, we also demonstrate the use of segment N50 as a novel metric for the measurement of chromosomal instability within tumor biopsies. We propose that increasingly accurate determination of CNVs is critical for their productive study in cancer, and our work demonstrates advances made possible by progress in this regard.

cancer biology↗

Genome-Wide Detection of Imprinted Differentially Methylated Regions Using Nanopore Sequencing

Imprinting is a critical part of normal embryonic development in mammals, controlled by defined parent-of-origin (PofO) differentially methylated regions (DMRs) known as imprinting control regions. As we and others have shown, direct nanopore sequencing of DNA provides a mean to detect allelic methylation and to overcome the drawbacks of methylation array and short-read technologies. Here we leverage publicly-available nanopore sequence data for 12 standard B-lymphocyte cell lines to present the first genome-wide mapping of imprinted intervals in humans using this technology. We were able to phase 95% of the human methylome and detect 94% of the well-characterized imprinted DMRs. In addition, we found 28 novel imprinted DMRs (12 germline and 16 somatic), which we confirmed using whole-genome bisulfite sequencing (WGBS) data. Analysis of WGBS data in mus musculus, rhesus macaque, and chimpanzee suggested that 12 of these are conserved. We also detected subtle parental methylation bias spanning several kilobases at seven known imprinted clusters. These results expand the current state of knowledge of imprinting, with potential applications in the clinic. We have also demonstrated that nanopore long reads, can reveal imprinting using only parent-offspring trios, as opposed to the large multi - generational pedigrees that have previously been required.

genomics↗

ACE 2 Coding Variants: A Potential X-linked Risk Factor for COVID-19 Disease

Viral genetic variants are widely known to influence disease progression among infected humans. Given the recent and rapid emergence of pandemic SARS-CoV-2 infection, the cause of COVID-19 disease, viral protein variants have attracted research interest. However, little has yet been written about genetic risk factors among human hosts. Human genetic variation has proven to affect disease progression and outcome for important diseases such as HIV infection and malaria infestation. The fact that the human ACE2 protein is encoded on the X chromosome means that males who carry rare ACE2 coding variants will express those variants in all ACE2-expressing cells, whereas females will typically express those variants in a mosaic distribution determined by early X-inactivation events. This sex-based difference in ACE2 expression has unique implications for epidemiological studies designed to assess host genetic factors influencing progression from asymptomatic SARS-coV-2 infection to COVID-19. Here we present theoretical modelling of rare ACE2 coding variants documented to occur naturally in several human superpopulations and subpopulations, and show that rare variants predicted to affect the binding of ACE2 to the SARS-CoV-2 spike protein exist in people. Though the rs4646116 (p.Lys26Arg) allele is found in 1 in 70 Ashkenazi Jewish males, and in 1 in 172 non-Finnish European males, this allele is found at higher frequencies in females. Furthermore, the class of missense ACE2 alleles predicted to affect SARS-CoV-2 binding are found in aggregate among 1.43% and 2.16% of Ashkenazi males and females, respectively, as well as in 0.58% and 1.24% of European males and females outside of Finland. These alleles are rarer in other population groups, and almost absent from East Asians genotyped to date. Though we are aware that full genome-wide and exome-wide sequencing studies may ultimately be required to assess human genetic susceptibility to SARS-CoV-2 fully, we argue on the basis of strong prior probabilities that genotyping of this class of alleles is justified in cases of atypical SARS-CoV-2 diseases, such as asymptomatic super-spreaders (if any are identified), and in neonatal/paediatric-onset COVID-19 disease. Even relatively rare susceptibility factors (1% or fewer carriers) may become quantitatively important in the context of hundreds of thousands of infections. A small number of asymptomatic carriers, or a small number of super-spreaders, or a small segment of the population that is disproportionately likely to require intensive care, can magnify the medical, social and economic impacts of a pandemic of this size. The speed of the pandemic and the large number of affected cases worldwide justify efforts to identify all possible risk factors for adverse outcomes, including efforts to identify genetic susceptibility factors in human hosts.

bioinformatics↗

A Modular Master Regulator Landscape Determines the Impact of Genetic Alterations on the Transcriptional Identity of Cancer Cells

Despite considerable pan-cancer efforts, the link between genomics and transcriptomics in cancer remains relatively weak and mostly based on statistical rather than mechanistic principles. By performing integrative analysis of transcriptomic and mutational profiles on a sample-by-sample basis, via regulatory/signaling networks, we identified a repertoire of 407 Master-Regulator proteins responsible for canalizing the genetics of 20 TCGA cohorts into 112 transcriptionally-distinct tumor subtypes. Further analysis highlighted a highly-recurrent regulatory architecture (oncotecture) with Master-Regulators organized into 24 modular MR-Blocks, regulating highly-specific tumor-hallmark functions and predictive of patient outcome. Critically, >50% of the somatic alterations identified in individual samples were in proteins affecting Master-Regulator activity, thus yielding novel insight into mechanisms linking tumor genetics and transcriptional identity and establishing novel non-oncogene dependencies. Experimental validation of functional mutations upstream of the most conserved MR-Block confirmed their ability to affect MR-protein activity, suggesting that the proposed methodology may effectively complement and extend current pan-cancer knowledge.

bioinformatics↗

ntEdit: scalable genome sequence polishing

In the modern genomics era, genome sequence assemblies are routine practice. However, depending on the methodology, resulting drafts may contain considerable base errors. Although utilities exist for genome base polishing, they work best with high read coverage and do not scale well. We developed ntEdit, a Bloom filter-based genome sequence editing utility that scales to large mammalian and conifer genomes.\n\nWe first tested ntEdit and the state-of-the-art assembly improvement tools GATK, Pilon and Racon on controlled E. coli and C. elegans sequence data. Generally, ntEdit performs well at low sequence depths (<20X), fixing the majority (>97%) of base substitutions and indels, and its performance is largely constant with increased coverage. In all experiments conducted using a single CPU, the ntEdit pipeline executed in <14s and <3m, on average, on E. coli and C. elegans, respectively. We performed similar benchmarks on a sub-20X coverage human genome sequence dataset, inspecting accuracy and resource usage in editing chromosomes 1 and 21, and whole genome. ntEdit scaled linearly, executing in 30-40m on those sequences. We show how ntEdit ran in <2h20m to improve upon long and linked read human genome assemblies of NA12878, using high coverage (54X) Illumina sequence data from the same individual, fixing frame shifts in coding sequences. We also generated 17-fold coverage spruce sequence data from haploid sequence sources (seed megagametophyte), and used it to edit our pseudo haploid assemblies of the 20 Gbp interior and white spruce genomes in <4 and <5h, respectively, making roughly 50M edits at a (substitution+indel) rate of 0.0024.\n\nAvailabilityhttps://github.com/bcgsc/ntedit\n\nSupplemental materialavailable online.

bioinformatics↗

Text-mining clinically relevant cancer biomarkers for curation into the CIViC database

Precision oncology involves analysis of individual cancer samples to understand the genes and pathways involved in the development and progression of a cancer. To improve patient care, knowledge of diagnostic, prognostic, predisposing and drug response markers is essential. Several knowledgebases have been created by different groups to collate evidence for these associations. These include the open-access Clinical Interpretation of Variants in Cancer (CIViC) knowledgebase. These databases rely on time-consuming manual curation from skilled experts who read and interpret the relevant biomedical literature. To aid in this curation and provide the greatest coverage for these databases, particularly CIViC, we propose the use of text mining approaches to extract these clinically relevant biomarkers from all available published literature. To this end, a group of cancer genomics experts annotated biomarkers and their clinical associations discussed in 800 sentences and achieved good inter-annotator agreement. We then used a supervised learning approach to construct the CIViCmine knowledgebase (http://bionlp.bcgsc.ca/civicmine/) extracting 128,857 relevant sentences from PubMed abstracts and Pubmed Central Open Access full text papers. CIViCmine contains over 90,992 biomarkers associated with 7,866 genes, 402 drugs and 557 cancer types, representing 29,153 abstracts and 40,551 full-text publications. Through integration with CIVIC, we provide a prioritised list of curatable biomarkers as well as a resource that is valuable to other knowledgebases and precision cancer analysts in general.

bioinformatics↗

CancerMine: A literature-mined resource for drivers, oncogenes and tumor suppressors in cancer

Understanding a mutation in cancer requires knowledge of the different roles that genes play in cancer as drivers, oncogenes and tumor suppressors. We present CancerMine, a high-quality text-mined knowledgebase that catalogues over 856 genes as drivers, 2,421 as oncogenes and 2,037 as tumor suppressors in 426 cancer types. We compile 3,485 genes that are not in the IntOGen resource of drivers and complement the Cancer Gene Census with 3,136 new genes identified as oncogenes and tumor suppressors. CancerMine provides a method for gene-centric clustering of cancer types illustrating genetic similarities between cancer types of different organs and was validated against data from the Cancer Genome Atlas (TCGA) project. Finally with 178 novel cancer gene mentions in publications each month, this resource will be updated monthly, pre-empting the need to manually curate the ever-increasing number of novel cancer associated genes. CancerMine is viewable through a web portal (http://bionlp.bcgsc.ca/cancermine/) and available for download (https://github.com/jakelever/cancermine).

bioinformatics↗

Tigmint: Correcting Assembly Errors Using Linked Reads From Large Molecules

Genome sequencing yields the sequence of many short snippets of DNA (reads) from a genome. Genome assembly attempts to reconstruct the original genome from which these reads were derived. This task is difficult due to gaps and errors in the sequencing data, repetitive sequence in the underlying genome, and heterozygosity, and assembly errors are common. These misassemblies may be identified by comparing the sequencing data to the assembly, and by looking for discrepancies between the two. Once identified, these misassemblies may be corrected, improving the quality of the assembly. Although tools exist to identify and correct misassemblies using Illumina pair-end and mate-pair sequencing, no such tool yet exists that makes use of the long distance information of the large molecules provided by linked reads, such as those offered by the 10x Genomics Chromium platform. We have developed the tool Tigmint for this purpose. To demonstrate the effectiveness of Tigmint, we corrected assemblies of a human genome using short reads assembled with ABySS 2.0 and other assemblers. Tigmint reduced the number of misassemblies identified by QUAST in the ABySS assembly by 216 (27%). While scaffolding with ARCS alone more than doubled the scaffold NGA50 of the assembly from 3 to 8 Mbp, the combination of Tigmint and ARCS improved the scaffold NGA50 of the assembly over five-fold to 16.4 Mbp. This notable improvement in contiguity highlights the utility of assembly correction in refining assemblies. We demonstrate its usefulness in correcting the assemblies of multiple tools, as well as in using Chromium reads to correct and scaffold assemblies of long single-molecule sequencing. The source code of Tigmint is available for download from https://github.com/bcgsc/tigmint, and is distributed under the GNU GPL v3.0 license.

genomics↗

Simulating Pedigrees Ascertained for Multiple Disease-Affected Relatives

Background: Studies that ascertain families containing multiple relatives affected by disease can be useful for identification of causal, rare variants from next-generation sequencing data.\n\nResults: We present the R package SimRVPedigree, which allows researchers to simulate pedigrees ascertained on the basis of multiple, affected relatives. By incorporating the ascertainment process in the simulation, SimRVPedigree allows researchers to better understand the within-family patterns of relationship amongst affected individuals and ages of disease onset.\n\nConclusions: Through simulation, we show that affected members of a family segregating a rare disease variant tend to be more numerous and cluster in relationships more closely than those for sporadic disease. We also show that the family ascertainment process can lead to apparent anticipation in the age of onset. Finally, we use simulation to gain insight into the limit on the proportion of ascertained families segregating a causal variant. SimRVPedigree should be useful to investigators seeking insight into the family-based study design through simulation.

genetics↗

Conserved roles of RECQ-like helicases Sgs1 and BLM in preventing R-loop induced genome instability

Sgs1 is a yeast DNA helicase functioning in DNA replication and repair, and is the orthologue of the human Blooms syndrome helicase BLM. Here we analyze the mutation signature associated with SGS1 deletion in yeast, and find frequent copy number changes flanked by regions of repetitive sequence and high R-loop forming potential. We show that loss of SGS1 increases R-loop accumulation and sensitizes cells to replication-transcription collisions. Accordingly, in sgs1{Delta} cells the genome-wide distribution of R-loops shifts to known sites of Sgs1 action, replication pausing regions, and to long genes. Depletion of the orthologous BLM helicase from human cancer cells also increases R-loop levels, and R-loop-associated genome instability. In support of a direct effect, BLM is found physically proximal to DNA:RNA hybrids in human cells, and can efficiently unwind R-loops in vitro. Together our data describe a conserved role for Sgs1/BLM in R-loop suppression and support an increasingly broad view of DNA repair and replication fork stabilizing proteins as modulators of R-loop mediated genome instability.

cell biology↗