Biology subjects

Parker, A.

Publications and source records attributed to Parker, A..

28 records · Page 2Linked to original sources

bioRxiv2021

Impaired local intrinsic immunity to SARS-CoV-2 infection in severe COVID-19

Infection with SARS-CoV-2, the virus that causes COVID-19, can lead to severe lower respiratory illness including pneumonia and acute respiratory distress syndrome, which can result in profound morbidity and mortality. However, many infected individuals are either asymptomatic or have isolated upper respiratory symptoms, which suggests that the upper airways represent the initial site of viral infection, and that some individuals are able to largely constrain viral pathology to the nasal and oropharyngeal tissues. Which cell types in the human nasopharynx are the primary targets of SARS-CoV-2 infection, and how infection influences the cellular organization of the respiratory epithelium remains incompletely understood. Here, we present nasopharyngeal samples from a cohort of 35 individuals with COVID-19, representing a wide spectrum of disease states from ambulatory to critically ill, as well as 23 healthy and intubated patients without COVID-19. Using standard nasopharyngeal swabs, we collected viable cells and performed single-cell RNA-sequencing (scRNA-seq), simultaneously profiling both host and viral RNA. We find that following infection with SARS-CoV-2, the upper respiratory epithelium undergoes massive reorganization: secretory cells diversify and expand, and mature epithelial cells are preferentially lost. Further, we observe evidence for deuterosomal cell and immature ciliated cell expansion, potentially representing active repopulation of lost ciliated cells through coupled secretory cell differentiation. Epithelial cells from participants with mild/moderate COVID-19 show extensive induction of genes associated with anti-viral and type I interferon responses. In contrast, cells from participants with severe lower respiratory symptoms appear globally muted in their anti-viral capacity, despite substantially higher local inflammatory myeloid populations and equivalent nasal viral loads. This suggests an essential role for intrinsic, local epithelial immunity in curbing and constraining viral-induced pathology. Using a custom computational pipeline, we characterized cell-associated SARS-CoV-2 RNA and identified rare cells with RNA intermediates strongly suggestive of active replication. Both within and across individuals, we find remarkable diversity and heterogeneity among SARS-CoV-2 RNA+ host cells, including developing/immature and interferon-responsive ciliated cells, KRT13+ "hillock"-like cells, and unique subsets of secretory, goblet, and squamous cells. Finally, SARS-CoV-2 RNA+ cells, as compared to uninfected bystanders, are enriched for genes involved in susceptibility (e.g., CTSL, TMPRSS2) or response (e.g., MX1, IFITM3, EIF2AK2) to infection. Together, this work defines both protective and detrimental host responses to SARS-CoV-2, determines the direct viral targets of infection, and suggests that failed anti-viral epithelial immunity in the nasal mucosa may underlie the progression to severe COVID-19.

immunology↗

bioRxiv2020

The Ensembl COVID-19 resource: Ongoing integration of public SARS-CoV-2 data

The COVID-19 pandemic has seen unprecedented use of SARS-CoV-2 genome sequencing for epidemiological tracking and identification of emerging variants. Understanding the potential impact of these variants on the infectivity of the virus and the efficacy of emerging therapeutics and vaccines has become a cornerstone of the fight against the disease. To support the maximal use of genomic information for SARS-CoV-2 research, we launched the Ensembl COVID-19 browser, incorporating a new Ensembl gene set, multiple variant sets (including novel variation calls), and annotation from several relevant resources integrated into the reference SARS-CoV-2 assembly. This work included key adaptations of existing Ensembl genome annotation methods to model ribosomal slippage, stringent filters to elucidate the highest confidence variants and utilisation of our comparative genomics pipelines on viruses for the first time. Since May 2020, the content has been regularly updated and tools such as the Ensembl Variant Effect Predictor have been integrated. The Ensembl COVID-19 browser is freely available at https://covid-19.ensembl.org.

bioinformatics↗

bioRxiv2020

MDM2 Inhibition in Combination with Endocrine Therapy and CDK4/6 Inhibition for the Treatment of ER-Positive Breast Cancer.

BackgroundResistance to endocrine therapy is a major clinical challenge in the management of estrogen receptor (ER)-positive breast cancer. In this setting p53 is frequently wildtype and its activity may be suppressed via upregulation of its key regulator MDM2. This underlies our rationale to evaluate MDM2 inhibition as a therapeutic strategy in treatment resistant ER-positive breast cancer. MethodsWe used the MDM2 inhibitor NVP-CGM097 to treat in vitro and in vivo models alone and in combination with fulvestrant or palbociclib. We perform cell viability, cell cycle, apoptosis and senescence assays to evaluate antitumor effects in p53 wildtype and p53 mutant ER positive cell lines (MCF-7, ZR75-1, T-47D) and MCF-7 lines resistant to endocrine therapy and to CDK4/6 inhibition. We further assess the drug effects in patient-derived xenograft (PDX) models of endocrine-sensitive and -resistant ER positive breast cancer. ResultsWe demonstrate that MDM2 inhibition results in cell cycle arrest and increased apoptosis in p53-wildtype in vitro and in vivo breast cancer models, leading to potent anti-tumour activity. We find that endocrine therapy or CDK4/6 inhibition synergises with MDM2 inhibition but does not further enhance apoptosis. Instead, combination treatments result in profound regulation of cell cycle-related transcriptional programmes, with synergy achieved through increased antagonism of cell cycle progression. Combination therapy pushes cell lines resistant to fulvestrant or palbociclib to become senescent and significantly reduces tumour growth in a fulvestrant resistant patient derived xenograft model. ConclusionsWe conclude that MDM2 inhibitors in combination with ER degraders or CDK4/6 inhibitors represent a rational strategy for treating advanced, endocrine resistant ER-positive breast cancer, operating through synergistic activation of cell cycle co-regulatory programs.

cancer biology↗

bioRxiv2020

Single-cell analysis reveals diverse stromal subsets associated with immune evasion in triple-negative breast cancer

The tumour stroma regulates nearly all stages of carcinogenesis. Stromal heterogeneity in human triple-negative breast cancers (TNBCs) remains poorly understood, limiting the development of stromal-targeted therapies. Single cell RNA-sequencing of five TNBCs revealed two cancer-associated fibroblast (CAF) and two perivascular-like (PVL) subpopulations. CAFs clustered into two states, the first with features of myofibroblasts and the second characterised by high expression of growth factors and immunomodulatory molecules. PVL cells clustered into two states consistent with a differentiated and immature phenotype. We showed that these stromal states have distinct morphologies, spatial relationships and functional properties in regulating the extracellular matrix. Using cell-signalling predictions, we provide evidence that stromal-immune crosstalk acts via a diverse array of immunoregulatory molecules. Importantly, the investigation of gene signatures from inflammatory-CAFs and differentiated-PVL cells in independent TNBC patient cohorts revealed strong associations with cytotoxic T-cell dysfunction and exclusion, respectively. Such insights present promising candidates to further investigate for new therapeutic strategies in the treatment of TNBCs.

cancer biology↗

bioRxiv2019

Markers of BRCAness in breast cancer

BackgroundMutations in BRCA1 and BRCA2 cause deficiencies in homologous recombination repair (HR), resulting in repair of DNA double-strand breaks by the alternative non-homologous end-joining pathway, which is more error prone. HR deficiency of breast tumors is important because it is associated with better responses to platinum salt therapies and PARP inhibitors. Among other consequences of HR deficiency are characteristic somatic-mutation signatures and gene-expression patterns. The term "BRCAness" describes tumors that harbor an HR defect but have no detectable germline mutation in BRCA1 or BRCA2. A better understanding of the genes and molecular events associated with BRCAness could provide mechanistic insights and guide development of targeted treatments. MethodsUsing data from The Cancer Genome Atlas (TCGA) for 1101 breast-cancer patients, we identified individuals with a germline mutation, somatic mutation, homozygous deletion, and/or hypermethylation event in BRCA1, BRCA2, and 59 other cancer-predisposition genes. Based on the assumption that BRCAness events would have similar downstream effects on tumor biology as BRCA1/BRCA2 germline mutations, we quantified these effects based on somatic-mutation signatures and gene-expression profiles. We reduced the dimensionality of the somatic-mutation signatures and expression data and used a statistical resampling approach to quantify similarities between patients who had a BRCA1/BRCA2 germline mutation, another type of aberration in BRCA1 or BRCA2, or any type of aberration in one of the other genes. ResultsSomatic-mutation signatures of tumors having a somatic mutation, homozygous deletion, or hypermethylation event in BRCA1/BRCA2 (n = 80) were generally similar to each other and to tumors from BRCA1/BRCA2 germline carriers (n = 44). Additionally, somatic-mutation signatures of tumors with germline or somatic events in ATR (n = 16) and BARD1 (n = 8) showed high similarity to tumors from BRCA1/BRCA2 carriers. Other genes also showed high similarity but only for a small number of events or for a single event type. Tumors with germline mutations or hypermethylation of BRCA1 had relatively similar gene-expression profiles and overlapped considerably with the Basal-like subtype; but the transcriptional effects of the other events lacked consistency. ConclusionsOur findings confirm previously known relationships between molecular signatures and germline or somatic events in BRCA1/BRCA2 and suggest additional genes that may be considered for inclusion in the definition of BRCAness.

cancer biology↗

bioRxiv2018

A free boundary model of epithelial dynamics

In this work we analyse a one-dimensional, cell-based model of an epithelial sheet. In this model, cells interact with their nearest neighbouring cells and move deterministically. Cells also proliferate stochastically, with the rate of proliferation specified as a function of the cell length. This mechanical model of cell dynamics gives rise to a free boundary problem. We construct a corresponding continuum-limit description where the variables in the continuum limit description are expanded in powers of the small parameter 1/N, where N is the number of cells in the population. By carefully constructing the continuum limit description we obtain a free boundary partial differential equation description governing the density of the cells within the evolving domain, as well as a free boundary condition that governs the evolution of the domain. We show that care must be taken to arrive at a free boundary condition that conserves mass. By comparing averaged realisations of the cell-based model with the numerical solution of the free boundary partial differential equation, we show that the new mass-conserving boundary condition enables the coarsegrained partial differential equation model to provide very accurate predictions of the behaviour of the cell-based model, including both evolution of the cell density, and the position of the free boundary, across a range of interaction potentials and proliferation functions in the cell based model.

systems biology↗

bioRxiv2018

Flux-Balance Based Modeling of Biofilm Communities

Models of microbial community dynamics generally rely on a sub-scale model for microbial metabolisms. In systems such as distributed multispecies communities like biofilms, where it is not reasonable to simplify to a small number of limiting substrates, tracking the large number of active metabolites likely requires measurement or estimation of large numbers of kinetic and regulatory parameters. Alternatively, a largely kinetics-free methodology is proposed combining cellular level constrained, steady state metabolic flux analysis with macro scale microbial community models. The methodology easily allows coupling of macroscale information, including measurement data, with cell-scale metabolism. Illustrative examples are included.

microbiology↗

bioRxiv2018

Chronic inflammation delays cell migration to villi in the intestinal epithelium

The intestinal epithelium is a single layer of cells which provides the first line of defence of the intestinal mucosa to bacterial infection. Cohesion of this physical barrier is supported by renewal of epithelial stem cells, residing in invaginations called crypts, and by crypt cell migration onto protrusions called villi; dysregulation of such mechanism may render the gut susceptible to chronic inflammation. The impact that excessive or misplaced epithelial cell death may have on villus cell migration is currently unknown. We integrated cell-tracking methods with computational models to determine how epithelial homeostasis is affected by acute and chronic inflammatory cell death. Parameter inference reveals that acute inflammatory cell death has a transient effect on epithelial cell dynamics, whereas cell death caused by chronic inflammation causes a delay in the accumulation of labelled cells onto the villus compared to control. Such a delay may be reproduced by using a cell-based model to simulate the dynamics of each cell in a crypt-villus geometry, showing that a prolonged increase in cell death slows the migration of cells from the crypt to the villus. This investigation highlights which injuries (acute or chronic) may be regenerated and which cause disruption of healthy epithelial homeostasis.

systems biology↗

bioRxiv2017

Automated evaluation of quaternary structures from protein crystals

A correct assessment of the quaternary structure of proteins is a fundamental prerequisite to understanding their function, physico-chemical properties and mode of interaction with other proteins. Currently about 90% of structures in the Protein Data Bank are crystal structures, in which the correct quaternary structure is embedded in the crystal lattice among a number of crystal contacts. Computational methods are required to 1) classify all protein-protein contacts in crystal lattices as biologically relevant or crystal contacts and 2) provide an assessment of how the biologically relevant interfaces combine into a biological assembly In our previous work we addressed the first problem with our EPPIC (Evolutionary Protein Protein Interface Classifier) method. Here, we present our solution to the second problem with a new method that combines the interface classification results with symmetry and topology considerations. The new algorithm enumerates all possible valid assemblies within the crystal using a graph representation of the lattice and predicts the most probable biological unit based on the pairwise interface scoring. Our method achieves 85% precision on a new dataset of 1,481 biological assemblies with consensus of PDB annotations. Although almost the same precision is achieved by PISA, currently the most popular quaternary structure assignment method, we show that, due to the fundamentally different approach to the problem, the two methods are complementary and could be combined to improve biological assembly assignments. The software for the automatic assessment of protein assemblies (EPPIC version 3) has been made available through a web server at http://www.eppic-web.org.\n\nAuthor summaryX-ray diffraction experiments are the main experimental technique to reveal the detailed atomic 3-dimensional structure of proteins. In these experiments, proteins are packed into crystals, an environment that is far away from their native solution environment. Determining which parts of the structure reflect the proteins state in the cell rather than being artifacts of the crystal environment can be a difficult task. How the different protein subunits assemble together in solution is known as the quaternary structure. Finding the correct quaternary structure is important both to understand protein oligomerization and for the understanding of protein-protein interactions at large. Here we present a new method to automatically determine the quaternary structure of proteins given their crystal structure. We provide a theoretical basis for properties that correct protein assemblies should possess, and provide a systematic evaluation of all possible assemblies according to these properties. The method provides a guidance to the experimental structural biologist as well as to structural bioinformaticians analyzing protein structures in bulk. Assemblies are provided for all proteins in the Protein Data Bank through a public website and database that is updated weekly as new structures are released.

bioinformatics↗

bioRxiv2017

The impact of experimental design choices on parameter inference for models of growing cell colonies

To better understand development, repair and disease progression it is useful to quantify the behaviour of proliferative and motile cell populations as they grow and expand to fill their local environment. Inferring parameters associated with mechanistic models of cell colony growth using quantitative data collected from carefully designed experiments provides a natural means to elucidate the relative contributions of various processes to the growth of the colony. In this work we explore how experimental design impacts our ability to infer parameters for simple models of the growth of proliferative and motile cell populations. We adopt a Bayesian approach, which allows us to characterise the uncertainty associated with estimates of the model parameters. Our results suggest that experimental designs that incorporate initial spatial heterogeneities in cell positions facilitate parameter inference without the requirement of cell tracking, whilst designs that involve uniform initial placement of cells require cell tracking for accurate parameter inference. As cell tracking is an experimental bottleneck in many studies of this type, our recommendations for experimental design provide for significant potential time and cost savings in the analysis of cell colony growth.

cell biology↗