Biology subjects

Johnson, D.

Publications and source records attributed to Johnson, D..

51 records · Page 3Linked to original sources

bioRxiv2020

Analytical Validation of a COVID-19 qRT-PCR Detection Assay Using a 384-well Format and Three Extraction Methods

The COVID-19 global pandemic is an unprecedented health emergency. Insufficient access to testing has hampered effective public health interventions and patient care management in a number of countries. Furthermore, the availability of regulatory-cleared reagents has challenged widespread implementation of testing. We rapidly developed a qRT-PCR SARS-CoV-2 detection assay using a 384-well format and tested its analytic performance across multiple nucleic acid extraction kits. Our data shows robust analytic accuracy on residual clinical biospecimens. Limit of detection sensitivity and specificity was confirmed with currently available commercial reagents. Our methods and results provide valuable information for other high-complexity laboratories seeking to develop effective, local, laboratory-developed procedures with high-throughput capability to detect SARS-CoV-2.

pathology↗

bioRxiv2019

Concerted cutting by Spo11 illuminates DNA break mechanisms and initiates gap repair during meiosis

Genetic variation arises during meiosis via repair of DNA double-strand breaks (DSBs) created by the topoisomerase-like Spo11 protein. These DSBs are thought to always occur sparsely across the genome, with isolated DSBs generating discrete recombination events. We challenge this view, demonstrating that hyper-localised coincident DSBs frequently form within hotspots in both S. cerevisiae and mouse--a process suppressed by the DNA damage response kinase Tel1/ATM. Remarkably, the distances separating coincident DSBs vary with [~]10.5 bp periodicity, invoking a model where adjacent Spo11 molecules have a fixed orientation relative to the DNA helix. Deep sequencing of meiotic progeny identifies recombination scars consistent with gap repair initiated by adjacent DSBs. Our results revise current thinking about how genetic recombination initiates, reviving original concepts of meiotic recombination as double-strand gap repair.

molecular biology↗

bioRxiv2019

Plasma-derived exosomal analysis and deconvolution enables prediction and tracking of melanoma checkpoint blockade response

PurposeImmune checkpoint inhibitors (ICI) have demonstrated promising therapeutic benefit although a majority will not respond. Here we identify and validate predictive biomarkers from plasma-derived exosomes that allow non-invasive monitoring of tumor intrinsic and host immune status and prediction of ICI success.\n\nExperimental DesignTranscriptomic profiling of peripheral blood bulk exosomes and tumors from a discovery cohort of 50 patients with metastatic melanoma treated with ICI was undertaken; a further validation cohort of 30 patients was utilized to validate findings from the discovery cohort. We designed a Bayesian probabilistic model to partition bulk exosomes into tumor-specific and non-tumor-specific proportions.\n\nResultsExosomal RNA signatures exhibit significant correlations with tumor transcriptomes. Exosomal profiles reflect several key biological drivers of ICI resistance or melanoma progression, exhibit significantly differentially expressed genes and pathways, and correlate with and are predictive of clinical response to therapy. Our deconvolution model estimates contributions from tumor and non-tumor sources, enabling more precise interpretation of differentially-expressed genes and pathways. Exosomal RNA-seq mutational information can be used to segregate responders and non-responders.\n\nConclusionsPeripheral blood-derived exosomes can serve as a non-invasive biomarker to jointly probe tumor-intrinsic and immune changes to ICI, and can potentially function as predictive markers of ICI responsiveness and a monitoring tool for tumor persistence and immune activation.\n\nStatement of SignificanceWe use transcriptomic analysis of bulk, non-selected, peripheral blood derived exosomes to reveal both tumor-intrinsic and immune-derived signatures predictive of early response to immune checkpoint inhibitor therapy. We develop a novel computational model to classify exosomal transcripts into tumor and non-tumor components and establish relevance in immune checkpoint blockade therapy. We show that tumor driver load from RNA-seq mutational calls are significantly different between responders and non-responders.

cancer biology↗

bioRxiv2019

COPO: a metadata platform for brokering FAIR data in the life sciences

Scientific innovation is increasingly reliant on data and computational resources. Much of todays life science research involves generating, processing, and reusing heterogeneous datasets that are growing exponentially in size. Demand for technical experts (data scientists and bioinformaticians) to process these data is at an all-time high, but these are not typically trained in good data management practices. That said, we have come a long way in the last decade, with funders, publishers, and researchers themselves making the case for open, interoperable data as a key component of an open science philosophy. In response, recognition of the FAIR Principles (that data should be Findable, Accessible, Interoperable and Reusable) has become commonplace. However, both technical and cultural challenges for the implementation of these principles still exist when storing, managing, analysing and disseminating both legacy and new data.\n\nCOPO is a computational system that attempts to address some of these challenges by enabling scientists to describe their research objects (raw or processed data, publications, samples, images, etc.) using community-sanctioned metadata sets and vocabularies, and then use public or institutional repositories to share it with the wider scientific community. COPO encourages data generators to adhere to appropriate metadata standards when publishing research objects, using semantic terms to add meaning to them and specify relationships between them. This allows data consumers, be they people or machines, to find, aggregate, and analyse data which would otherwise be private or invisible. Building upon existing standards to push the state of the art in scientific data dissemination whilst minimising the burden of data publication and sharing.\n\nAvailabilityCOPO is entirely open source and freely available on GitHub at https://github.com/collaborative-open-plant-omics. A public instance of the platform for use by the community, as well as more information, can be found at copo-project.org.

bioinformatics↗

bioRxiv2019

Kinetic Inference Resolves Epigenetic Mechanism of Drug Resistance in Melanoma

Drug-induced dedifferentiation towards a drug-tolerant persister state is a common mechanism cancer cells exploit to escape therapies, posing a significant obstacle to sustained therapeutic efficacy. The dynamic coordination of epigenomic and transcriptomic programs at the early-stage of drug exposure, which initiates and orchestrates these reversible dedifferentiation events, remains largely unexplored. Here we employ high-temporal-resolution multi-omics profiling, information-theoretic approaches, and dynamic system modeling to probe these processes in BRAF-mutant melanoma models and patient specimens. We uncover a hysteretic transition trajectory of melanoma cells in response to oncogene inhibition and subsequent release, driven by the sequential operation of two tightly coupled transcriptional waves, which orchestrate genome-scale chromatin state reconfiguration. Modeling of the transcriptional wave interactions predicts NF-{kappa}B/RelA-driven chromatin remodeling as the underlying mechanism of cell-state dedifferentiation, a finding we validate experimentally. Our results identify critical RelA-target genes that are epigenetically modulated to drive this process, establishing a quantitative epigenome gauge to measure cell-state plasticity in melanomas, which supports the potential use of drugs targeting epigenetic machineries to potentiate oncogene inhibition. Extending our investigation to other cancer models, we identify oxidative stress-mediated NF-{kappa}B/RelA activation as a common mechanism driving cellular transitions towards drug-tolerant persister states, revealing a novel and pivotal role for the NF-{kappa}B signaling axis in linking cellular oxidative stress to cancer progression.

cancer biology↗

bioRxiv2019

Inhibition of A20 deubiquitinase activity by KSHV vFLIP: A SUMO dependent mechanism?

KSHV viral FLICE inhibitory protein (vFLIP) is a potent activator of NF-{kappa}B signaling and an inhibitor of apoptosis and autophagy. Inhibition of vFLIP function and NF-{kappa}B signaling promotes lytic reactivation. Here we provide evidence for a novel function of vFLIP in promoting NF{kappa}B signaling through inhibition of the DUB activity of the negative regulator, A20. We demonstrate interaction of vFLIP with the Itch/A20 ubiquitin editing complex. We have identified a SUMO interaction motif in vFLIP that is required for NF-{kappa}B activation. Mutation of the SIM in BAC16 resulted in increased spontaneous RTA expression and loss of spindle cell morphology. Our results suggest a role for SUMO in mediating vFLIP function and provide evidence for vFLIP modulation of the negative regulation of NF-{kappa}B signaling by A20. Our results provide further insight into the function of vFLIP and SUMO in the regulation of NF-{kappa}B signaling and the latent lytic transition.

microbiology↗

bioRxiv2019

Removal of Spo11 from meiotic DNA breaks in vitro but not in vivo by Tyrosyl DNA Phosphodiesterase 2

Meiotic recombination events are initiated by DNA double-strand breaks (DSBs) created by the topoisomerase-like protein, Spo11. Similar to type-II topoisomerases, Spo11 becomes covalently linked to the 5' ends generated on each side of the DSB. Whilst Spo11-oligos--the product of nucleolytic removal by Mre11--have been detected in a number of biological systems, the lifetime of the covalent Spo11-DSB precursor has not been systematically determined and may be subject to alternative processing reactions. Here we explore the activity of human Tyrosyl DNA Phosphodiesterase, TDP2, on Spo11-DSBs isolated from S. cerevisiae cells. We demonstrate that TDP2 can remove Spo11 from natural ssDNA-oligos, and dsDNA ends even when in the presence of excess competitor genomic DNA. Interestingly, TDP2-processed Spo11-DSBs are refractory to resection by Exo1, suggesting that ssDNA generated by Mre11 may be essential in vivo to facilitate resection-dependent HR at Spo11-DSBs even if TDP2 were active. Moreover, although TDP2 can remove Spo11 peptides in vitro, TDP2 was unable to remove Spo11 in vivo--unlike during the repair of topoisomerase-induced DNA lesions. These results suggest that Spo11-DNA, but not topoisomerase-DNA cleavage complexes, are inaccessible to the TDP2 enzyme, perhaps due to occlusion by higher order protein complexes resident at sites of meiotic recombination.

molecular biology↗

bioRxiv2018

Galaxy-Kubernetes integration: scaling bioinformatics workflows in the cloud

Making reproducible, auditable and scalable data-processing analysis workflows is an important challenge in the field of bioinformatics. Recently, software containers and cloud computing introduced a novel solution to address these challenges. They simplify software installation, management and reproducibility by packaging tools and their dependencies. In this work we implemented a cloud provider agnostic and scalable container orchestration setup for the popular Galaxy workflow environment. This solution enables Galaxy to run on and offload jobs to most cloud providers (e.g. Amazon Web Services, Google Cloud or OpenStack, among others) through the Kubernetes container orchestrator. AvailabilityAll code has been contributed to the Galaxy Project and is available (since Galaxy 17.05) at https://github.com/galaxyproject/ in the galaxy and galaxy-kubernetes repositories. https://public.phenomenal-h2020.eu/ is an example deployment. Suppl. InformationSupplementary Files are available online. Contactpmoreno@ebi.ac.uk, European Molecular Biology Laboratory, EMBL-EBI, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK, Tel: +44-1223-494267, Fax: +44-1223-484696.

bioinformatics↗

bioRxiv2018

PhenoMeNal: Processing and analysis of Metabolomics data in the Cloud

BackgroundMetabolomics is the comprehensive study of a multitude of small molecules to gain insight into an organisms metabolism. The research field is dynamic and expanding with applications across biomedical, biotechnological and many other applied biological domains. Its computationally-intensive nature has driven requirements for open data formats, data repositories and data analysis tools. However, the rapid progress has resulted in a mosaic of independent - and sometimes incompatible - analysis methods that are difficult to connect into a useful and complete data analysis solution.\n\nFindingsThe PhenoMeNal (Phenome and Metabolome aNalysis) e-infrastructure provides a complete, workflow-oriented, interoperable metabolomics data analysis solution for a modern infrastructure-as-a-service (IaaS) cloud platform. PhenoMeNal seamlessly integrates a wide array of existing open source tools which are tested and packaged as Docker containers through the projects continuous integration process and deployed based on a kubernetes orchestration framework. It also provides a number of standardized, automated and published analysis workflows in the user interfaces Galaxy, Jupyter, Luigi and Pachyderm.\n\nConclusionsPhenoMeNal constitutes a keystone solution in cloud infrastructures available for metabolomics. It provides scientists with a ready-to-use, workflow-driven, reproducible and shareable data analysis platform harmonizing the software installation and configuration through user-friendly web interfaces. The deployed cloud environments can be dynamically scaled to enable large-scale analyses which are interfaced through standard data formats, versioned, and have been tested for reproducibility and interoperability. The flexible implementation of PhenoMeNal allows easy adaptation of the infrastructure to other application areas and omics research domains.

bioinformatics↗

bioRxiv2018

Measuring Illumina Size Bias Using REcount: A Novel Method for Highly Accurate Quantification of Engineered Genetic Constructs

Quantification of DNA sequence tags associated with engineered genetic constructs underlies many genomics measurements. Typically, such measurements are done using PCR to enrich sequence tags and add adapters, followed by next-generation sequencing (NGS). However, PCR amplification can introduce significant quantitative error into these measurements. Here we describe REcount, a novel PCR-free direct counting method for NGS-based quantification of engineered genetic constructs. By comparing measurements of defined plasmid pools to droplet digital PCR data, we demonstrate that this method is highly accurate and reproducible. We further demonstrate that the REcount approach is amenable to multiplexing through the use of orthogonal restriction enzymes. Finally, we use REcount to provide new insights into clustering biases due to molecule length across different Illumina sequencing platforms.

genomics↗

bioRxiv2018

Population sequencing reveals clonal diversity and ancestral inbreeding in the grapevine cultivar Chardonnay

Chardonnay is the basis of some of the worlds most iconic wines and its success is underpinned by a historic program of clonal selection. There are numerous clones of Chardonnay available that exhibit differences in key viticultural and oenological traits that have arisen from the accumulation of somatic mutations during centuries of asexual propagation. However, the genetic variation that underlies these differences remains largely unknown. To address this knowledge gap, a high-quality, diploid-phased Chardonnay genome assembly was produced from single-molecule real time sequencing, and combined with re-sequencing data from 15 different commercial Chardonnay clones. There were 1620 markers identified that distinguish the 15 Chardonnay clones. These markers were reliably used for clonal identification of validation genomic material, as well as in identifying a potential genetic basis for some clonal phenotypic differences. The predicted parentage of the Chardonnay haplomes was elucidated by mapping sequence data from the predicted parents of Chardonnay (Gouais blanc and Pinot noir) against the Chardonnay reference genome. This enabled the detection of instances of heterosis, with differentially-expanded gene families being inherited from the parents of Chardonnay. Most surprisingly however, the patterns of nucleotide variation present in the Chardonnay genome indicate that Pinot noir and Gouais blanc share an extremely high degree of kinship that has resulted in the Chardonnay genome displaying characteristics that are indicative of inbreeding.\n\nAuthor SummaryPhenotypic variation within a grapevine cultivar arises from an accumulation of mutations from serial vegetative propagation. Old cultivars such as Chardonnay have been propagated for centuries resulting in hundreds of available clones containing unique genetic mutations and a range of various phenotypic peculiarities. The genetic mutations can be leveraged as genetic markers and are useful in identifying specific clones for authenticity testing, or as breeding markers for new clonal selections where particular mutations are known to confer a phenotypic trait. We produced a high-quality genome assembly for Chardonnay, and using re-sequencing data for 15 popular clones, were able to identify a large selection of markers that are unique to at least one clone. We identified mutations that may confer phenotypic effects, and were able to identify clones from material independently sourced from nurseries and vineyards. The marker detection framework we describe for authenticity testing would be applicable to other grapevine cultivars or even other agriculturally important woody-plant crops that are vegetatively propagated such as fruit orchards. Finally, we show that the Chardonnay genome contains extensive evidence for parental inbreeding, such that its parents, Gouais blanc and Pinot noir, may even represent first-degree relatives.

genomics↗

bioRxiv2018

The Nucleome of Developing Murine Rod Photoreceptors

The nuclei of rod photoreceptors in mice and other nocturnal species have an unusual inverted chromatin structure: the heterochromatin is centrally located to help focus light and improve photosensitivity. To better understand this unique nuclear organization, we performed ultra-deep Hi-C analysis on murine retina at 3 stages of development and on purified rod photoreceptors. Predicted looping interactions from the Hi-C data were validated with fluorescence in situ hybridization (FISH). We discovered that a subset of retinal genes that are important for retinal development, cancer, and stress response are localized to the facultative heterochromatin domain. We also used machine learning to develop an algorithm based on our chromatin Hidden Markov Modeling (chromHMM) of retinal development to predict heterochromatin domains and study their dynamics during retinogenesis. FISH data for 264 genomic loci were used to train and validate the algorithm. The integrated data were then used to identify a developmental stage- and cell type-specific core regulatory circuit super-enhancer (CRC-SE) upstream of the Vsx2 gene, which is required for bipolar neuron expression. Deletion of the Vsx2 CRC-SE in mice led to the loss of bipolar neurons in the retina.

neuroscience↗

bioRxiv2018

Stepwise C-Terminal Truncation of Cardiac Troponin T Alters Function at Low and Saturating Ca2+

Activation of striated muscle contraction occurs in response to Ca2+ binding to troponin C (TnC). The resulting reorganization of troponin repositions tropomyosin on actin and permits activation of myosin catalyzed ATP hydrolysis. It now appears that the levels of activity at both low and saturating Ca2+ are modulated by the C-terminal 14 amino acids of cardiac troponin T (TnT). We made a series of mutants of human cardiac troponin T, isoform 2, with deletions from the C-terminal end: {Delta}4, {Delta}6, {Delta}8, {Delta}10 and {Delta}14. We measured the effect of these mutations on the normalized ATPase activity at saturating Ca2+, the change in acrylodan tropomyosin fluorescence at low Ca2+, and the degree of Ca2+ stimulation of the rate of binding of rigor myosin S1 to pyrene-labeled actin-tropomyosin-troponin. Together, these measurements define the distribution of actin-tropomyosin-troponin among the 3 regulatory states. Results from rates of rigor S1 binding deviated from other measurements when > 8 residues of TnT were deleted. That deviation was due to increased rates of binding of rigor S1 to pyrene-labeled actin with truncated TnT at saturating Ca2+. Such behavior violated a key assumption in the determination of the B state by this method. Nevertheless, all methods show that as residues were removed from the C-terminus of TnT there was approximately a proportional loss of the inactive B state at low Ca2+ and an increase in the active M state at saturating Ca2+. Most of the C-terminal 14 residues of human cardiac troponin T are essential for forming the inactive B state at low Ca2+ and for limiting the formation of the active M state at saturating Ca2+.

biochemistry↗

bioRxiv2017

Interoperable and scalable metabolomics data analysis with microservices

Developing a robust and performant data analysis workflow that integrates all necessary components whilst still being able to scale over multiple compute nodes is a challenging task. We introduce a generic method based on the microservice architecture, where software tools are encapsulated as Docker containers that can be connected into scientific workflows and executed in parallel using the Kubernetes container orchestrator. The access point is a virtual research environment which can be launched on-demand on cloud resources and desktop computers. IT-expertise requirements on the user side are kept to a minimum, and established workflows can be re-used effortlessly by any novice user. We validate our method in the field of metabolomics on two mass spectrometry studies, one nuclear magnetic resonance spectroscopy study and one fluxomics study, showing that the method scales dynamically with increasing availability of computational resources. We achieved a complete integration of the major software suites resulting in the first turn-key workflow encompassing all steps for mass-spectrometry-based metabolomics including preprocessing, multivariate statistics, and metabolite identification. Microservices is a generic methodology that can serve any scientific discipline and opens up for new types of large-scale integrative science.

bioinformatics↗

bioRxiv2017

Reflected stochastic differential equation models for constrained animal movement

Movement for many animal species is constrained in space by barriers such as rivers, shore-lines, or impassable cliffs. We develop an approach for modeling animal movement constrained in space by considering a class of constrained stochastic processes, reflected stochastic differential equations. Our approach generalizes existing methods for modeling unconstrained animal movement. We present methods for simulation and inference based on augmenting the constrained movement path with a latent unconstrained path and illustrate this augmentation with a simulation example and an analysis of telemetry data from a Steller sea lion (Eumatopias jubatus) in southeast Alaska.

animal behavior and cognition↗