Biology subjects

Beck, S.

Publications and source records attributed to Beck, S..

At least 37 records · Page 2Linked to original sources

bioRxiv2021

Leveraging Allele-Specific Expression for Therapeutic Response Gene Discovery in Glioblastoma.

Glioblastoma is the most prevalent primary malignant brain tumor in adults and is characterized by poor prognosis and universal tumor recurrence. Effective glioblastoma treatments are lacking, in part due to somatic mutations and epigenetic reprogramming that alter gene expression and confer drug resistance. Here, we interrogated allele-specific expression (ASE) in 43 patient-derived glioblastoma stem cells (GSCs) to identify recurrently dysregulated genes in glioblastoma. We identified 118 genes with recurrent ASE preferentially found in GSCs compared to normal tissues. These genes were enriched for apoptotic regulators, including Schlafen Family Member 11 (SLFN11). Loss of SLFN11 gene expression was associated with aberrant promoter methylation and conferred resistance to chemotherapy and poly ADP ribose polymerase inhibition. Conversely, low SLFN11 expression rendered GSCs susceptible to the oncolytic flavivirus Zika, which suggests a potential alternative treatment strategy for chemotherapy resistant GBMs.

cancer biology↗

bioRxiv2021

Performance comparison and in-silico harmonisation of commercial platforms for DNA methylome analysis by targeted bisulfite sequencing

DNA methylation is a key epigenetic modification in the regulation of cell fate and differentiation, and its analysis is gaining increasing importance in both basic and clinical research. Targeted Bisulfite Sequencing (TBS) has become the method of choice for the cost-effective, targeted analysis of the human methylome at base-pair resolution. Here we benchmarked five commercially available TBS platforms, including three hybridization capture-based (Agilent, Roche, and Illumina) and two RRBS-based (Diagenode and NuGen), across 16 samples. A subset of these were also compared to whole-genome DNA methylation sequencing with the Illumina and Oxford Nanopore platforms. We assessed performance with respect to workflow complexity, on/off-target performance, coverage, accuracy and reproducibility. We find all platforms able to produce usable data but major differences for some performance criteria, especially in the number and identity of the CpG sites covered, which affects the interoperability of datasets generated on these different platforms. To overcome this limitation, we used imputation and show that it improves the interoperability from an average of 10.35% (0.8M CpG sites) to 97% (7.6M CpG sites). Our study provides cross-validated guidance on which TBS platform to use for different features of the methylome and offers an imputation-based harmonization solution for improved interoperability between platforms, allowing comparative and integrative analysis.

genomics↗

bioRxiv2021

Calling differential DNA methylation at cell-type resolution: avoiding misconceptions and promoting best practices

The accurate detection of cell-type specific DNA methylation alterations in the context of general epigenome studies is an important task to improve our understanding of epigenomics in disease development. Although a number of statistical algorithms designed to address this problem have emerged, the task remains challenging. Here we show that a recent commentary by Rahmani et al, that aims to address misconceptions and best practices in the field, continues to suffer from critical misconceptions in how statistical algorithms should be compared and evaluated. In addition, we report contradictory results on real EWAS datasets.

bioinformatics↗

bioRxiv2021

A conserved paint box underlies color pattern diversity in Estrildid finches

Many animals exhibit typical color patterns that have been linked to key adaptive functions, yet the developmental mechanisms establishing these crucial designs remain unclear. Here, we surveyed color distribution in the plumage across a large number of passerine finches. Despite extreme apparent pattern diversity, we identified a small set of conserved color regions whose combinatory association can explain all observed patterns. We found these domains are instructed by early embryonic landmarks, and through profiling and comparative analyses produced a molecular map marking putative color domains in the developing skin. This revealed cryptic pre-patterning common to differently colored species, uncovering a simple molecular landscape underlying extensive color pattern variation.

developmental biology↗

bioRxiv2020

Epigenetic alterations underlie airway macrophage differentiation and phenotype during lung fibrosis

Airway macrophages (AMs) are key regulators of the lung environment and are implicated in the pathogenesis of idiopathic pulmonary fibrosis (IPF), a fatal respiratory disease with no cure. However, the epigenetics of AMs development and function in IPF are limited. Here, we characterised the DNA-methylation (DNAm) profile of AMs from IPF (n=30) and healthy (n=14) donors. Our analysis revealed epigenetic heterogeneity was a key characteristic of IPF AMs. DNAm clock analysis indicated epigenetic alterations in IPF-AMs was not associated with accelerated ageing. In differential DNAm analysis, we identified numerous differentially methylated positions (DMPs, n=11) and regions (DMRs, n=49) between healthy and IPF AMs respectively. DMPs and DMRs encompassed genes involved in lipid (LPCAT1) and glucose (PFKB3) metabolism and importantly, DNAm status was associated with disease severity in IPF. Collectively, our data identify that profound changes in the epigenome underpin the development and function of AMs in the IPF lung.

immunology↗

bioRxiv2020

A short course of Tofacitinib sustains the immunoregulatory effect of CTLA4-Ig in presence of inflammatory cytokines and promotes long-term survival of murine cardiac allografts

Costimulation blockade-based regimens are a promising strategy for management of transplant recipients. However, maintenance immunosuppression via CTLA4-Ig monotherapy is characterized by high frequency of rejection episodes. Recent evidence suggests that inflammatory cytokines contribute to alloreactive T cell activation in a CD28-independent manner, a reasonable contributor to the limited efficacy of CTLA4-Ig. In this study, we investigated the possible synergism of a combined short-term inhibition of cytokine signaling and CD28 engagement on the modulation of rejection. Our results demonstrate that the JAK/STAT inhibitor Tofacitinib restored the immunomodulatory effect of CTLA4-Ig on mouse alloreactive T cells in presence of inflammatory cytokines. Tofacitinib exposure conferred dendritic cells with a tolerogenic phenotype reducing their cytokine secretion and costimulatory molecules expression. JAK inhibition also directly affected T cell activation. In vivo, the combination of CTLA4-Ig and Tofacitinib induced long-term survival of heart allografts and, importantly, it was equally effective when using grafts subjected to prolonged ischemia. Transplant survival correlated with a reduction in effector T cells and intragraft accumulation of regulatory T cells. Collectively, our studies demonstrate a powerful synergism between CTLA4-Ig and Tofacitinib and suggest their combined use is a promising strategy for improved management of transplanted patients.

immunology↗

bioRxiv2020

Copy number-aware deconvolution of tumor-normal DNA methylation profiles

Aberrant methylation is a hallmark of cancer, but bulk tumor data is confounded by admixed normal cells and copy number changes. Here, we introduce Copy number-Aware Methylation Deconvolution Analysis of Cancers (CAMDAC; https://github.com/VanLoo-lab/CAMDAC), which outputs tumor purity, allele-specific copy number and deconvolved methylation estimates. We apply CAMDAC to 122 multi-region samples from 38 TRACERx non-small cell lung cancers profiled by reduced representation bisulfite sequencing. CAMDAC copy number profiles parallel those derived from genome sequencing and highlight widespread chromosomal instability. Deconvolved polymorphism-independent methylation rates enable unbiased tumor-normal and tumor-tumor differential methylation calling. Read-phasing validates CAMDAC methylation rates and directly links genotype and epitype. We show increased epigenetic instability in adenocarcinoma vs. squamous cell carcinoma, frequent hypermethylation at sites carrying somatic mutations, and parallel copy number losses and methylation changes at imprinted loci. Unlike bulk methylomes, CAMDAC profiles recapitulate tumor phylogenies and evidence distinct patterns of epigenetic heterogeneity in lung cancer.

genomics↗

bioRxiv2020

A cysteine protease inhibitor blocks SARS-CoV-2 infection of human and monkey cells

K777 is a di-peptide analog that contains an electrophilic vinyl-sulfone moiety and is a potent, covalent inactivator of cathepsins. Vero E6, HeLa/ACE2, Caco-2, A549/ACE2, and Calu-3, cells were exposed to SARS-CoV-2, and then treated with K777. K777 reduced viral infectivity with EC50 values of inhibition of viral infection of: 74 nM for Vero E6, <80 nM for A549/ACE2, and 4 nM for HeLa/ACE2 cells. In contrast, Calu-3 and Caco-2 cells had EC50 values in the low micromolar range. No toxicity of K777 was observed for any of the host cells at 10-100 M inhibitor. K777 did not inhibit activity of the papain-like cysteine protease and 3CL cysteine protease, encoded by SARS-CoV-2 at concentrations of [≤] 100 M. These results suggested that K777 exerts its potent anti-viral activity by inactivation of mammalian cysteine proteases which are essential to viral infectivity. Using a propargyl derivative of K777 as an activity-based probe, K777 selectively targeted cathepsin B and cathepsin L in Vero E6 cells. However only cathepsin L cleaved the SARS-CoV-2 spike protein and K777 blocked this proteolysis. The site of spike protein cleavage by cathepsin L was in the S1 domain of SARS-CoV-2, differing from the cleavage site observed in the SARS CoV-1 spike protein. These data support the hypothesis that the antiviral activity of K777 is mediated through inhibition of the activity of host cathepsin L and subsequent loss of viral spike protein processing. SIGNIFICANCEThe virus causing COVID-19 is highly infectious and has resulted in a global pandemic. We confirm that a cysteine protease inhibitor, approved by the FDA as a clinical-stage compound, inhibits SARS-CoV-2 infection of several human and monkey cell lines with notable(nanomolar) efficacy. The mechanism of action of this inhibitor is identified as a specific inhibition of host cell cathepsin L. This in turn inhibits host cell processing of the coronaviral spike protein, a step required for cell entry. Neither of the coronaviral proteases are inhibited, and the cleavage site of spike protein processing is different from that reported in other coronaviruses. Hypotheses to explain the differential activity of the inhibitor with different cell types are discussed.

biochemistry↗

bioRxiv2020

Machine Learning Models Identify Inhibitors of SARS-CoV-2

With the ongoing SARS-CoV-2 pandemic there is an urgent need for the discovery of a treatment for the coronavirus disease (COVID-19). Drug repurposing is one of the most rapid strategies for addressing this need and numerous compounds have been selected for in vitro testing by several groups already. These have led to a growing database of molecules with in vitro activity against the virus. Machine learning models can assist drug discovery through prediction of the best compounds based on previously published data. Herein we have implemented several machine learning methods to develop predictive models from recent SARS-CoV-2 in vitro inhibition data and used them to prioritize additional FDA approved compounds for in vitro testing selected from our in-house compound library. From the compounds predicted with a Bayesian machine learning model, CPI1062 and CPI1155 showed antiviral activity in HeLa-ACE2 cell-based assays and represent potential repurposing opportunities for COVID-19. This approach can be greatly expanded to exhaustively virtually screen available molecules with predicted activity against this virus as well as a prioritization tool for SARS-CoV-2 antiviral drug discovery programs. The very latest model for SARS-CoV-2 is available at www.assaycentral.org.Competing Interest StatementSE is CEO and owner of Collaborations Pharmaceuticals, Inc. DHF, KMZ, TRL, AP are employees of Collaborations Pharmaceuticals, Inc.View Full Text

pharmacology and toxicology↗

bioRxiv2020

Inhalation: A means to explore and optimize nintedanib's pharmacokinetic/pharmacodynamic relationship

Oral nintedanib is marketed for the treatment of idiopathic pulmonary fibrosis (IPF). While effective slowing fibrosis progression, as an oral medicine nintedanib is limited. To reduce side effects and maximize efficacy, nintedanib was reformulated as a solution for nebulization and inhaled administration. To predict effectiveness treating IPF, the nintedanib pharmacokinetic/pharmacodynamic relationship was dissected. Pharmacokinetic analysis indicated oral-delivered nintedanib plasma exposure and lung tissue partitioning were not dose-proportional and resulting lung levels were substantially higher than blood. Although initial-oral absorbed nintedanib efficiently partitioned into the lung, only a quickly eliminated fraction appeared available to epithelial lining fluid (ELF). Because IPF disease appears to initiate and progress near the epithelial surface, this observation suggests short duration nintedanib exposure (oral portion efficiently partitioned to ELF) is sufficient for IPF efficacy. To test this hypothesis, exposure duration required for nintedanib activity was explored. In vitro, IPF-cellular matrix (IPF-CM) increased primary normal human fibroblast (nHLF) aggregate size and reduced nHLF cell count. IPF-CM also increased nHLF ACTA2 and COL1A expression. Whether short duration (inhalation mimic) or continuous exposure (oral mimic), nintedanib (1-100 nM) reversed these effects. In vivo, intubated silica produced a strong pulmonary fibrotic response. Once-daily (QD) 0.021, 0.21 and 2.1 mg/kg intranasal (IN; short duration inhaled exposure) and twice daily (BID) 30 mg/kg oral (PO; long duration oral exposure) showed that at equivalent-delivered lung concentrations, QD short duration inhaled nintedanib exposure (0.21 mg/kg IN vs. 30 mg/kg PO) exhibited equivalent-to-superior activity as BID oral (reduced silica-induced elastance, alpha-smooth muscle actin, interleukin-1 beta (IL-1{beta}) and soluble collagen, and lung macrophage and neutrophils). An increased lung dose (2.1 mg/kg IN vs. 30 mg/kg PO) exhibited increased effect by further reducing silica-induced elastance, IL-1{beta} and soluble collagen. Neither oral nor inhaled nintedanib reduced silica-induced parenchymal collagen. Both QD inhaled and BID oral nintedanib reduced silica-induced inflammatory index with oral achieving significance. In summary, nintedanib pulmonary anti-fibrotic activity can be achieved using small, infrequent inhaled doses to deliver oral equivalent-to-superior therapeutic effect.

pharmacology and toxicology↗

bioRxiv2020

GenomeChronicler: The Personal Genome Project UK Genomic Report Generator Pipeline

In recent years, there has been a significant increase in whole genome sequencing data of individual genomes produced by research projects as well as direct to consumer service providers. While many of these sources provide their users with an interpretation of the data, there is a lack of free, open tools for generating reports exploring the data in an easy to understand manner. GenomeChronicler was developed as part of the Personal Genome Project UK (PGP-UK) to address this need. PGP-UK provides genomic, transcriptomic, epigenomic and self-reported phenotypic data under an open-access model with full ethical approval. As a result, the reports generated by GenomeChronicler are intended for research purposes only and include information relating to potentially beneficial and potentially harmful variants, but without clinical curation. GenomeChronicler can be used with data from whole genome or whole exome sequencing, producing a genome report containing information on variant statistics, ancestry and known associated phenotypic traits. Example reports are available from the PGP-UK data page (personalgenomes.org.uk/data). The objective of this method is to leverage existing resources to find known phenotypes associated with the genotypes detected in each sample. The provided trait data is based primarily upon information available in SNPedia, but also collates data from ClinVar, GETevidence and gnomAD to provide additional details on potential health implications, presence of genotype in other PGP participants and population frequency of each genotype. The analysis can be run in a self-contained environment without requiring internet access, making it a good choice for cases where privacy is essential or desired: any third party project can embed GenomeChronicler within their off-line safe-haven environments. GenomeChronicler can be run for one sample at a time, or in parallel making use of the Nextflow workflow manager. The source code is available from GitHub (https://github.com/PGP-UK/GenomeChronicler), container recipes are available for Docker and Singularity, as well as a pre-built container from SingularityHub (https://singularity-hub.org/collections/3664) enabling easy deployment in a variety of settings. Users without access to computational resources to run GenomeChronicler can access the software from the Lifebit CloudOS platform (https://lifebit.ai/cloudos) enabling the production of reports and variant calls from raw sequencing data in a scalable fashion.

bioinformatics↗

bioRxiv2019

A CellAge epigenetic clock for expedited discovery of anti-ageing compounds in vitro

We aim to improve anti-ageing drug discovery, currently achieved through laborious and lengthy longevity analysis. Recent studies demonstrated that the most accurate molecular method to measure human age is based on CpG methylation profiles, as exemplified by several epigenetics clocks that can accurately predict an individuals age. Here, we developed CellAgeClock, a new epigenetic clock that measures subtle ageing changes in primary human cells in vitro. As such, it provides a unique tool to measure effects of relatively short pharmacological treatments on ageing. We validated the CellAgeClock against known longevity drugs such as rapamycin and trametinib. Moreover, we uncovered novel anti-ageing drugs, torin2 and Dactolisib (BEZ-235), demonstrating the value of our approach as a screening and discovery platform for anti-ageing strategies. The CellAgeClock outperforms other epigenetic clocks in measuring subtle ageing changes in primary human cells in culture. The tested drug treatments reduced senescence and other ageing markers, further consolidating our approach as a screening platform. Finally, we show that the novel anti-ageing drugs we uncovered in vitro, indeed increased longevity in vivo. Our method expands the scope of CpG methylation profiling from measuring human chronological and biological age from human samples in years, to accurately and rapidly detecting anti-ageing potential of drugs using human cells in vitro, providing a novel accelerated discovery platform to test sought after geroprotectors.

molecular biology↗

bioRxiv2019

The Personal Genome Project-UK: an open access resource of human multi-omics data

Integrative analysis of multi-omics data is a powerful approach for gaining functional insights into biological and medical processes. Conducting these multifaceted analyses on human samples is often complicated by the fact that the raw sequencing output is rarely available under open access. The Personal Genome Project UK (PGP-UK) is one of few resources that recruits its participants under open consent and makes the resulting multi-omics data freely and openly available. As part of this resource, we describe the PGP-UK multi-omics reference panel consisting of ten genomic, methylomic and transcriptomic data. Specifically, we outline the data processing, quality control and validation procedures which were implemented to ensure data integrity and exclude sample mix-ups. In addition, we provide a REST API to facilitate the download of the entire PGP-UK dataset. The data are also available from two cloud-based environments, providing platforms for free integrated analysis. In conclusion, the genotype-validated PGP-UK multi-omics human reference panel described here provides a valuable new open access resource for integrated analyses in support of personal and medical genomics.

bioinformatics↗

bioRxiv2019

Activity of Selected Nucleoside Analogue ProTides against Zika Virus in Human Neural Stem Cells

Zika virus (ZIKV), an emerging flavivirus which causes neurodevelopmental impairment to fetuses and has been linked to Guillain-Barre syndrome, continues to threaten global health due to the absence of targeted prophylaxis or treatment. Nucleoside analogues are good examples of efficient anti-viral inhibitors, and prodrug strategies using phosphate masking groups (ProTides) have been employed to improve the bioavailability of ribonucleoside analogues. Here, we synthesized and tested a library of 13 ProTides against ZIKV in human neural stem cells. Strong activity was observed for 2'-C-methyluridine and 2'-C-ethynyluridine ProTides with an aryloxyl phosphoramidate masking group. Conversion of the aryloxyl phosphoramidate ProTide group of 2'-C-methyluridine to a 2-(methylthio)ethyl phosphoramidate completely abolished antiviral activity of the compound. The aryloxyl phosphoramidate ProTide of 2'-C-methyluridine outperformed the hepatitis C virus (HCV) drug sofosbuvir in suppression of viral titers and protection from cytopathic effect, while the former compounds triphosphate active metabolite was better incorporated by purified ZIKV NS5 polymerase over time. Molecular superpositioning revealed different orientations of residues opposite the 2'-fluoro group of sofosbuvir. These findings suggest both a nucleobase and ProTide group bias for the anti-ZIKV activity of nucleoside analogue ProTides in a disease-relevant cell model.

microbiology↗

bioRxiv2018

Mechanism of action of methotrexate against Zika virus

Zika virus (ZIKV), which is associated with microcephaly in infants and Guillain-Barre syndrome, reemerged as a serious public health threat in Latin America in recent years. Previous high-throughput screening (HTS) campaigns have revealed several potential hit molecules against ZIKV, including methotrexate (MTX), which is clinically used as an anti-cancer chemotherapy and anti-rheumatoid agent. We studied the mechanism of action of MTX against ZIKV in relation to its inhibition of dihydrofolate reductase (DHFR) in vitro using Vero and human neural stem cells (hNSCs). As expected, an antiviral effect for MTX against ZIKV was observed, showing up to ten-fold decrease in virus titer during MTX treatment. We also observed that addition of leucovorin (a downstream metabolite of DHFR pathway) rescued the ZIKV replication impaired by MTX treatment in ZIKV-infected cells, explaining the antiviral effect of MTX through inhibition of DHFR. We also found that addition of adenosine to ZIKV-infected cells was able to rescue ZIKV replication inhibited by MTX, suggesting that restriction of de novo synthesis adenosine triphosphate (ATP) pools suppresses viral replication. These results confirm that the DFHR pathway can be targeted to inhibit replication of ZIKV, similar to other published results showing this effect in related flaviviruses.

microbiology↗

bioRxiv2018

Identification of differentially methylated cell-types in Epigenome-Wide Association Studies

An outstanding challenge of Epigenome-Wide Association Studies (EWAS) performed in complex tissues is the identification of the specific cell-type(s) responsible for the observed differential DNA methylation. Here, we present a novel statistical algorithm, called CellDMC, which is able to identify not only differentially methylated positions, but also the specific cell-type(s) driving the differential methylation. We provide extensive validation of CellDMC on in-silico mixtures of DNA methylation data generated with different technologies, as well as on real mixtures from epigenome-wide-association and cancer epigenome studies. We demonstrate how CellDMC can achieve over 90% sensitivity and specificity in scenarios where current state-of-the-art methods fail to identify differential methylation. By applying CellDMC to a smoking EWAS performed in buccal swabs, we identify differentially methylated positions occurring in the epithelial compartment, which we validate in smoking-related lung cancer. CellDMC may help towards the identification of causal DNA methylation alterations in disease.

bioinformatics↗

bioRxiv2018

Selfish mutations dysregulating RAS-MAPK signaling are pervasive in aged human testes

Mosaic mutations present in the germline have important implications for reproductive risk and disease transmission. We previously demonstrated a phenomenon occurring in the male germline, whereby specific mutations arising spontaneously in stem cells (spermatogonia) lead to clonal expansion, resulting in elevated mutation levels in sperm over time. This process, termed selfish spermatogonial selection, explains the high spontaneous birth prevalence and strong paternal age-effect of disorders such as achondroplasia, Apert, Noonan and Costello syndromes, with direct experimental evidence currently available for specific positions of six genes (FGFR2, FGFR3, RET, PTPN11, HRAS and KRAS). We present a discovery screen to identify novel mutations and genes showing evidence of positive selection in the male germline, by performing massively parallel simplex PCR using RainDance technology to interrogate mutational hotspots in 67 genes (51.5 kb in total) in 276 biopsies of testes from 5 men (median age: 83 years). Following ultra-deep sequencing (~16,000x), development of a low-frequency variant prioritization strategy and targeted validation, we identified 61 distinct variants present at frequencies as low as 0.06%, including 54 variants not previously directly associated with selfish selection. The majority (80%) of variants identified have previously been implicated in developmental disorders and/or oncogenesis and include mutations in six newly associated genes (BRAF, CBL, MAP2K1, MAP2K2, RAF1 and SOS1), all of which encode components of RAS-MAPK pathway and activate signaling. Our findings extend the link between mutations dysregulating the RAS-MAPK pathway and selfish selection, and show that the ageing male germline is a repository for such deleterious mutations.

genetics↗

bioRxiv2018

Increased DNA methylation variability in rheumatoid arthritis discordant monozygotic twins

BackgroundRheumatoid arthritis is a common autoimmune disorder influenced by both genetic and environmental factors. Epigenome-wide association studies can identify environmentally mediated epigenetic changes such as altered DNA methylation, which may also be influenced by genetic factors. To investigate possible contributions of DNA methylation to the aetiology of rheumatoid arthritis with minimum confounding genetic heterogeneity, we investigated genome-wide DNA methylation in disease discordant monozygotic twin pairs.\n\nMethodsGenome-wide DNA methylation was assessed in 79 monozygotic twin pairs discordant for rheumatoid arthritis using the HumanMethylation450 BeadChip array (Illumina). Discordant twins were tested for both differential DNA methylation and methylation variability between RA and healthy twins. The methylation variability signature was then compared with methylation variants from studies of other autoimmune diseases and with an independent healthy population.\n\nResultsWe have identified a differentially variable DNA methylation signature, that suggests multiple stress response pathways may be involved in the aetiology of the disease. This methylation variability signature also highlighted potential epigenetic disruption of multiple RUNX3 transcription factor binding sites as being associated with disease development. Comparison with previously performed epigenome-wide association studies of rheumatoid arthritis and type 1 diabetes identified shared pathways for autoimmune disorders, suggesting that epigenetics plays a role in autoimmunity and offering the possibility of identifying new targets for intervention.\n\nConclusionsThrough genome-wide analysis of DNA methylation in disease discordant monozygotic twins, we have identified a differentially variable DNA methylation signature, in the absence of differential methylation in rheumatoid arthritis. This finding supports the importance of epigenetic variability as an emerging component in autoimmune disorders.

genomics↗