Biology subjects

Robertson, N.

Publications and source records attributed to Robertson, N..

17 recordsLinked to original sources

bioRxiv2026

Isotope-Free Mapping of protein:RNA Interactions Using fCRAC and trxtools

Defining high-confidence RNA interaction sites for specific proteins is essential to understand RNA biology, but existing methods face trade-offs between specificity, sensitivity, and experimental accessibility. Here, we present fluorescent Cross-linking and analysis of cDNAs (fCRAC), a mammalian-cell optimized update to the CRAC protocol. In fCRAC, a fluorescent adaptor is used, in place of radiolabeling, to visualize RNA-protein complexes during gel-purification. fCRAC retains the tandem affinity purification and stringent, denaturing conditions of classical CRAC, enabling nucleotide-resolution mapping of protein:RNA interactions with high signal to noise ratio. We initially tested fCRAC using RPP25L, a component the RNase MRP and RNase P complexes. RPP25L almost exclusively bound to predicted, single sites in the RNA components (RMRP and RPPH1), showing excellent selectivity with nucleotide resolution. To support analysis of UV cross-linking data for more complex targets, we developed the trxtools package and example pipeline for standardized processing, quality control, and analysis of data from fCRAC and related methods. We include tailored strategies for repetitive RNA classes, such as tRNA and rRNA, which can be challenging to analyze using other approaches. We applied fCRAC and trxtools to define the RNA interactome of human CYCLON/CCDC86, a nuclear protein previously implicated in oncogenesis. This revealed specific interactions with rRNA, tRNA and ncRNAs involved in pre-rRNA and pre-tRNA processing. HighlightsO_LINucleotide-resolution definition of RNAs interacting with specific proteins, including rRNA and tRNA C_LIO_LIStringent denaturing purifications and robust visualization steps, with no requirement for radioactive labelling C_LIO_LITrxtools provides an integrated analysis pipeline with approaches for analyzing both single and multi-copy RNA species C_LI

molecular biology↗

bioRxiv2025

Inference of clonal hematopoiesis using the collective behaviour of DNA methylation states

Clonal expansion occurs when descendants of a single progenitor cell come to dominate a tissue. We show that this process generates a predictable collective behaviour in DNA methylation landscapes: at CpG sites that faithfully transmit their allelic methylation status across cell divisions, methylation proportions shift toward discrete values (0%, 50%, or 100%) as clones expand. We demonstrate this phenomenon in clonal hematopoiesis, in which a hematopoietic stem cell acquires a fitness-conferring mutation that leads to clonal expansion. Exploiting these dynamics, we developed COMET (Clonal Observation from METhylation), which quantifies clonal burden from bulk methylation data without prior knowledge of driving mutations. Validation against targeted sequencing demonstrated robust prediction across mutation types, accurate longitudinal tracking, and detection of sequencing artifacts. Applied to 15,900 individuals, COMET-predicted clonal hematopoiesis replicated known genetic associations (TCL1A, NRIP1) and phenotypic relationships with smoking and chronic obstructive pulmonary disease. These findings reveal fundamental principles of how clonal dynamics manifest epigenetically and establish a mutation-agnostic approach for clonal burden assessment.

genetics↗

bioRxiv2025

BenchHub enables an inclusive and transparent ecosystem for community-focused benchmarking in computational biology

The rapid growth of computational methods for the computational biology field highlights the critical role of benchmarking in guiding method selection. However, there is no standardised data structure that effectively links and stores datasets, performance metrics and available ground truth. Without such a unified and shareable structure, it is difficult for the community to contribute, update and extend existing benchmarking studies to ensure long-term relevancy. To address this challenge, we present BenchHub, a community-oriented ecosystem with a modular R6-based structure that enables "living benchmarking." BenchHub comprises three key components: (i) a Trio database that links datasets, performance metrics, and supporting evidence (e.g. ground truth), (ii) a BenchmarkStudy structure that captures the different benchmark study designs, and (iii) a series of tools together with vignettes and interactive platform that allow users to gain insights from the benchmarking results. Together, these components streamline the benchmarking process for benchmark study developers, methods contributors, and benchmark consumers, promoting reproducibility, comparability, and long-term sustainability in computational biology.

bioinformatics↗

bioRxiv2025

Computational design of dynamic biosensors for emerging synthetic opioids

Nitazenes are an emergent class of synthetic opioids that rival or exceed fentanyl in their potency. These compounds have been detected internationally in illicit drugs and are the cause of increasing numbers of hospitalizations and overdoses. New analogs are consistently released, making detection challenging - new ways of testing a wide range of nitazenes and their metabolic products are urgently needed. Here, we developed a computational protocol to redesign the plant abscisic acid receptor PYR1 to bind diverse nitazenes and maintain its dynamic transduction mechanism. The best design has a low nanomolar limit of detection in vitro against nitazene and menitazene. Deep mutational scanning yielded sensors able to recognize a range of clinically relevant nitazenes and the common metabolic byproduct in complex biological matrices with limited cross-specificity against unrelated opioids. Application of protein design tools on privileged receptors like PYR1 may yield general sensors for a wide range of applications in vitro and in vivo.

biochemistry↗

bioRxiv2024

SpatioMark: Quantifying the impact of spatial proximity on cell phenotype

As research advances in spatially resolving the biological archetype of various diseases, technologies that capture the spatial relationships between cells are demonstrating increasing value. Whilst there are an increasing number of analytical methods being developed to identify the complex web of interactions between cells, the downstream impacts of these cell-cell relationships are under explored. Here, we present SpatioMark, a statistical framework that simplifies the assessment of gene or protein expression in relation to the spatial proximity of different cell types. We demonstrate its performance across spatial proteomics and transcriptomics datasets and link identified relationships with differences in patient survival. We highlight key challenges in identifying changes in molecular markers associated with the localisation of cells and propose corrections which reduce artefact induced relationships. SpatioMark is implemented in the Statial R package hosted on the Bioconductor Project, ensuring interoperability with existing spatial analysis tools. Ultimately, this work highlights strategies for identifying and interpreting changes in cell phenotype associated with cellular relationships in spatial omics data, with broad applicability across various multiplexed imaging platforms.

bioinformatics↗

bioRxiv2024

Kontextual: Reframing analysis of spatial omics data reveals consistent cell relationships across images

State-of-the-art spatial proteomic and transcriptomic technologies can deeply pheno-type cells in their native tissue environment, providing a high throughput means to effectively quantify spatial relationships between diverse cell populations. However, the experimental design choice of which regions of a tissue will be imaged can greatly impact the interpretation of spatial quantifications. That is, spatial relationships identified in one region of interest may not be interpreted consistently across other regions. To address this challenge, we introduce Kontextual, a method which considers alternative frames of reference for contextualising spatial relationships. These contexts may represent landmarks, spatial domains, or groups of functionally similar cells which are consistent across regions. By modelling spatial relationships between cells relative to these contexts, Kontextual produces robust spatial quantifications that are not confounded by the region selected. We demonstrate in spatial proteomics and spatial transcriptomics datasets that modelling spatial relationships this way is biologically meaningful. We also demonstrate how this approach can be used in a classification setting to improve prediction of patient prognosis.

bioinformatics↗

bioRxiv2023

MoleculeExperiment enables consistent infrastructure for molecule-resolved spatial transcriptomics data in Bioconductor

Imaging-based spatial transcriptomics technologies have achieved subcellular resolution, enabling detection of individual molecules in their native tissue context. Data associated with these technologies promises unprecedented opportunity towards understanding cellular and subcellular biology. However, in R/Bioconductor there is a scarcity of existing computational infrastructure to represent such data, and particularly to summarise and transform it for existing widely adopted computational tools in single cell transcriptomics analysis, including SingleCellExperiment and SpatialExperiment classes. With the emergence of several commercial offerings of imaging-based spatial transcriptomics, there is a pressing need to develop consistent data structure standards for these technologies at the individual molecule level. To this end, we have developed MoleculeExperiment, an R/Bioconductor package, which i) stores molecule and cell segmentation boundary information at the molecule-level, ii) standardises this molecule-level information across different imaging-based ST technologies, including 10x Genomics Xenium, and iii) streamlines transition from a MoleculeExperiment object to a SpatialExperiment object. Overall, MoleculeExperiment is generally applicable as a data infrastructure class for consistent analysis of imaging-based spatial transcriptomics data.

bioinformatics↗

bioRxiv2022

Template-Directed RIG-I Agonist Assembly for Targeted Cancer Immunotherapy

Recent developments in the use of pattern recognition receptors (PRRs) aim to harness the innate power of the immune system for cancer therapy. Understanding how to recruit PRRs, such as RIG-I, in a tumor-selective manner is critical for its adoption in the clinic. We describe the use of a tumor-selective template-based agonist of RIG-I to induce type-I IFN signaling and tumor cell apoptosis. The agonist, termed ss-ppp-miRNA-21, comprises a single stranded RNA oligonucleotide modified with a 5-triphosphate and complementary to an endogenous miRNA enriched in tumor cells. We demonstrate the efficacy of the template-directed approach and detail mechanistic studies validating the hypothesis of a template-directed RIG-I agonist assembly using miRNA-21 as a target. The template-directed strategy described here moves us closer to making RIG-I a clinically relevant target in oncology because it achieves targeted activation of innate immunity in the tumor microenvironment in the context of systemic agonist injection.

bioengineering↗

bioRxiv2022

Spurious intragenic transcription is a hallmark of mammalian cellular senescence and tissue aging

Mammalian aging is characterized by the progressive loss of tissue integrity and function manifesting in ill health and increased risk for developing multiple chronic conditions. Accumulation of senescent cells in aging tissues partly contributes to this decline and targeted depletion of senescent cells in vivo ameliorates many age-related phenotypes. However, the fundamental molecular mechanisms responsible for the decline of cellular health and fitness during senescence and aging are largely unknown. In this study, we investigated whether chromatin-mediated loss of transcriptional fidelity, known to contribute to fitness and survival in yeast and worms, also occurs during human cellular senescence and mouse aging. Our findings reveal that aberrant transcription initiation inside genes is widespread in senescence and aging. It co-occurs with changes in the chromatin landscape and formation of non-canonical transcription start sites. Interventions that alter spurious transcripts have dramatic consequences on cellular health primarily affecting intracellular signal transduction pathways. We propose that spurious transcription is a conserved hallmark of aging that promotes a noisy transcriptome and degradation of coherent transcriptional networks.

genomics↗

bioRxiv2021

A disease-linked lncRNA mutation in RNase MRP inhibits ribosome synthesis

RMRP encodes a non-coding RNA forming the core of the RNase MRP ribonucleoprotein complex. Mutations cause Cartilage Hair Hypoplasia (CHH), characterized by skeletal abnormalities and impaired T cell activation. Yeast RNase MRP cleaves a specific site in the pre-ribosomal RNA (pre-rRNA) during ribosome synthesis. CRISPR-mediated disruption of RMRP in human cells lines caused growth arrest, with pre-rRNA accumulation. Here, we analyzed disease-relevant primary cells, showing that mutations in RMRP impair mouse T cell activation and delay pre-rRNA processing. Patient-derived human fibroblasts with CHH-linked mutations showed similar pre-rRNA processing delay. Human cells engineered with the most common CHH mutation (70AG in RMRP) show specifically impaired pre-rRNA processing, resulting in reduced mature rRNA and a reduced ratio of cytosolic to mitochondrial ribosomes. Moreover, the 70AG mutation caused a reduction in intact RNase MRP complexes. Together, these results indicate that CHH is a ribosomopathy, and the first processing-specific human disorder to be described. HighlightsO_LIMutations in RMRP lncRNA impair pre-rRNA processing and T cell activation C_LIO_LIPatient derived fibroblasts show impaired pre-rRNA processing C_LIO_LICells with the most common disease-linked mutation have specific processing defects C_LIO_LICytoplasmic ribosomes and intact RNase MRP complexes are also reduced in these cells C_LI

cell biology↗

bioRxiv2020

BRD4-mediated repression of p53 is a target for combination therapy in AML

Acute Myeloid Leukemia (AML) is a typically-lethal molecularly heterogeneous disease, with few broad-spectrum therapeutic targets. Unusually, most AML retain wild-type TP53, encoding the pro-apoptotic tumor suppressor p53. MDM2 inhibitors (MDM2i), which activate wild-type p53, and BET inhibitors (BETi), targeting the BET-family co-activator BRD4, both show encouraging pre-clinical activity, but limited clinical activity as single agents. Here, we report synergistic toxicity of combined MDM2i and BETi towards AML cell lines, primary human blasts and mouse models, resulting from BETis ability to evict an unexpected repressive form of BRD4 from p53 target genes, and hence potentiate MDM2i-induced p53 activation. These results indicate that wild-type TP53 and a transcriptional repressor function of BRD4 together represent a potential broad-spectrum synthetic therapeutic vulnerability for AML.

cell biology↗

bioRxiv2020

Integrative Vectors for Regulated Expression of SARS-CoV-2 Proteins Implicated in RNA Metabolism

Infection with SARS-CoV-2 is expected to result in substantial reorganization of host cell RNA metabolism. We identified 14 proteins that were predicted to interact with host RNAs or RNA binding proteins, based on published data for SARS-CoV and SARS-CoV-2. Here, we describe a series of affinity-tagged and codon-optimized expression constructs for each of these 14 proteins. Each viral gene was separately tagged at the N-terminus with Flag-His8, the C-terminus with His8-Flag, or left untagged. The resulting constructs were stably integrated into the HEK293 Flp-In TREx genome. Each viral gene was expressed under the control of an inducible Tet-On promoter, allowing expression levels to be tuned to match physiological conditions during infection. Expression time courses were successfully generated for most of the fusion proteins and quantified by western blot. A few fusion proteins were poorly expressed, whereas others, including Nsp1, Nsp12, and N protein, were toxic unless care was taken to minimize background expression. All plasmids can be obtained from Addgene and cell lines are available. We anticipate that availability of these resources will facilitate a more detailed understanding of coronavirus molecular biology.

cell biology↗

bioRxiv2018

Maternal and fetal genetic effects on birth weight and their relevance to cardio-metabolic risk factors

Birth weight (BW) variation is influenced by fetal and maternal genetic and non-genetic factors, and has been reproducibly associated with future cardio-metabolic health outcomes. These associations have been proposed to reflect the lifelong consequences of an adverse intrauterine environment. In earlier work, we demonstrated that much of the negative correlation between BW and adult cardio-metabolic traits could instead be attributable to shared genetic effects. However, that work and other previous studies did not systematically distinguish the direct effects of an individuals own genotype on BW and subsequent disease risk from indirect effects of their mothers correlated genotype, mediated by the intrauterine environment. Here, we describe expanded genome-wide association analyses of own BW (n=321,223) and offspring BW (n=230,069 mothers), which identified 278 independent association signals influencing BW (214 novel). We used structural equation modelling to decompose the contributions of direct fetal and indirect maternal genetic influences on BW, implicating fetal- and maternal-specific mechanisms. We used Mendelian randomization to explore the causal relationships between factors influencing BW through fetal or maternal routes, for example, glycemic traits and blood pressure. Direct fetal genotype effects dominate the shared genetic contribution to the association between lower BW and higher type 2 diabetes risk, whereas the relationship between lower BW and higher later blood pressure (BP) is driven by a combination of indirect maternal and direct fetal genetic effects: indirect effects of maternal BP-raising genotypes act to reduce offspring BW, but only direct fetal genotype effects (once inherited) increase the offsprings later BP. Instrumental variable analysis using maternal BW-lowering genotypes to proxy for an adverse intrauterine environment provided no evidence that it causally raises offspring BP. In successfully separating fetal from maternal genetic effects, this work represents an important advance in genetic studies of perinatal outcomes, and shows that the association between lower BW and higher adult BP is attributable to genetic effects, and not to intrauterine programming.

genetics↗

bioRxiv2018

Variation in the plasma membrane monoamine transporter (PMAT, encoded in SLC29A4) and organic cation transporter 1 (OCT1, encoded in SLC22A1) and gastrointestinal intolerance to metformin in type 2 diabetes: an IMI DIRECT study

Objectives20-30% of patients with metformin treated type 2 diabetes experience gastrointestinal side effects leading to premature discontinuation in 5-10% of the cases. Gastrointestinal intolerance may reflect localised high concentrations of metformin in the gut. We hypothesized that reduced transport of metformin into the circulation via the plasma membrane monoamine transporter (PMAT) and organic cation transporter 1 (OCT1) could increase the risk of severe GI side effects.\n\nResearch Design and MethodsThe study included 286 severe metformin intolerant and 1128 tolerant individuals from the IMI DIRECT consortium. We assessed the association of patient characteristics, concomitant medication and the burden of mutations in the SLC29A4 and SLC22A1, genes that encode PMAT and OCT1, respectively, on odds of metformin intolerance using a logistic regression model.\n\nResultsWomen (p < 0.001) and older people (p < 0.001) were more likely to develop metformin intolerance. Concomitant use of metformin transporter inhibiting drugs increased the odds of intolerance by more than 70% (OR = 1.72 [1.26-2.32], p < 0.001). In a logistic regression model adjusted for age, sex, weight and population substructure, the G allele at rs3889348 (SLC29A4) was associated with GI intolerance (OR = 1.34[1.09-1.65], p = 0.005). rs3889348 is the top cis-eQTL for SLC29A4 in gut tissue where carriers of the G allele had reduced expression. Homozygous carriers of the G allele treated with metformin transporter inhibiting drugs had over three times higher odds of intolerance compared to carriers of no G allele and not treated with inhibiting drugs (OR = 3.23 [1.71-6.39], p < 0.001). Using a genetic risk score (GRS) derived from SLC29A4 (rs3889348) and previously reported SLC22A1 variants (M420del, R61C, G401S), the odds of intolerance was more than twice in individuals who carry three or more risk alleles compared with those carrying none (OR = 2.15 [1.20-4.12], p = 0.01).\n\nConclusionsThese results suggest that intestinal metformin transporters and concomitant medications play an important role in gastrointestinal side effects of metformin.

genetics↗

bioRxiv2018

Fatigue and cognitive performance change in MS: multifactorial with disparate influences

BackgroundFatigue is a common and disabling symptom in Multiple Sclerosis (MS) with a variety of direct and indirect influences, but remains poorly understood. Performance-based and self-report measures of fatigue are only weakly correlated and may have independent predictors. We adopted a multifactorial approach, utilising a measure of concurrent cognitive performance change in order to examine the clinical, psychological, and cognitive factors influencing subjective and objective fatigue in MS.\n\nMethodsSixty-one people with MS were assessed. Subjective fatigue was measured using the Modified Fatigue Impact Scale, Fatigue Assessment Instrument, and a Visual Analogue Scale (VAS). The Conners Continuous Performance Test 3 (CCPT3) and VAS were administered before and after two hours of cognitive testing, representing a period of cognitive effort. The differences in scores formed measures of objective performance fatigue and subjective fatigue change, respectively. We examined differences across baseline fatigue, fatigue change and performance change classifications, using regression analysis to uncover predictors of subjective fatigue and performance change.\n\n\n\nO_TBL View this table:\norg.highwire.dtl.DTLVardef@81ec81org.highwire.dtl.DTLVardef@1ce44e8org.highwire.dtl.DTLVardef@10e1bdeorg.highwire.dtl.DTLVardef@147c5ceorg.highwire.dtl.DTLVardef@10b831f_HPS_FORMAT_FIGEXP M_TBL O_FLOATNOTable 1.C_FLOATNO O_TABLECAPTIONDemographic and clinical features of the sample\n\nC_TABLECAPTION C_TBL ResultsDepression, sleep, and emotion-focused coping each predicted baseline fatigue and together explained 53.5% of variance. Increased subjective fatigue was linked with anxiety, lower self-efficacy and gender. Cognitive performance change on the CCPT3 was however predicted by estimated general cognitive ability, self-efficacy and post-intervention fatigue.\n\nConclusionSubjective fatigue in MS is a multifactorial construct, with subjective and objective cognitive performance fatigue largely influenced by indirect psychological and cognitive factors. The varying factors driving subjective and objective fatigue suggest that future studies need to take into account these disparate aspects when developing fatigue assessment tools. Targeting influential fatigue drivers such as psychological variables, and even using gender specific interventions may have the potential to improve the burden of fatigue and quality of life of people with MS.

neuroscience↗

bioRxiv2018

Length-independent telomere damage drives cardiomyocyte senescence

Ageing is the biggest risk factor for cardiovascular health and is associated with increased incidence of cardiovascular disease. Cellular senescence, a process driven in part by telomere shortening, has been implicated in age-related tissue dysfunction. Here, we address the question of how senescence is induced in rarely dividing/post-mitotic cardiomyocytes and investigate if clearance of senescent cells attenuates age related cardiac dysfunction. During ageing, human and murine cardiomyocytes acquire a senescent-like phenotype characterised by persistent DNA damage at telomere regions that can be driven by mitochondrial dysfunction, and crucially can occur independently of cell-division and telomere length. Length-independent telomere damage in cardiomyocytes activates the classical senescence-inducing pathways, p21CIP and p16INK4a and results in a non-canonical senescence-associated secretory phenotype. Pharmacological or genetic clearance of senescent cells in mice alleviates myocardial hypertrophy and fibrosis, detrimental features of cardiac ageing, and promotes cardiomyocyte regeneration. Our data describes a mechanism by which senescence can occur and contribute to ageing in post-mitotic tissues.

cell biology↗

bioRxiv2018

Neuregulin 1 type III reduces severity in a mouse model of Congenital Hypomyelinating Neuropathy

Myelin sheath thickness is precisely regulated and essential for rapid propagation of action potentials along myelinated axons. In the peripheral nervous system, extrinsic signals from the axonal protein neuregulin 1 type III regulate Schwann cell fate and myelination. Here we ask if modulating neuregulin 1 type III levels in neurons would restore myelination in a model of congenital hypomyelinating neuropathy (CHN). Using a mouse model of CHN, we rescued the myelination defects by early overexpression of neuregulin 1 type III. Surprisingly, the rescue was independent from the upregulation of Egr2 or essential myelin genes. Rather, we observed the activation of MAPK/ERK and other myelin genes such as peripheral myelin protein 2 (Pmp2) and oligodendrocyte myelin glycoprotein (Omg). We also confirmed that the permanent activation of MAPK/ERK in Schwann cells has detrimental effects on myelination. Our findings demonstrate that the modulation of axon-to-glial neuregulin 1 type III signaling has beneficial effects and restores myelination defects during development in a model of CHN.\n\n\n\nO_TBL View this table:\norg.highwire.dtl.DTLVardef@103281aorg.highwire.dtl.DTLVardef@3dc68eorg.highwire.dtl.DTLVardef@1b6c5feorg.highwire.dtl.DTLVardef@80e419org.highwire.dtl.DTLVardef@1ff2591_HPS_FORMAT_FIGEXP M_TBL C_TBL

neuroscience↗