Biology subjects

Murphy, K.

Publications and source records attributed to Murphy, K..

33 records · Page 2Linked to original sources

bioRxiv2022

Intra-islet glucagon signalling regulates pulsatile insulin secretion and glucose homeostasis

BackgroundType 2 diabetes (T2D) is characterised by the loss of pulsatile insulin secretion. We studied mice with {beta}-cell specific loss of the glucagon receptor (Gcgr fl/fl X Ins-1Cre), to investigate the role of intra-islet glucagon receptor signalling on pan-islet calcium oscillations and insulin pulsatility. MethodsFrequently sampled intravenous glucose tolerance tests were conducted on Gcgr {beta}-cell-/- and littermate controls. Crossing with GCaMP6f (STOP flox) animals further allowed for {beta}-cell specific expression of a fluorescent calcium indicator. These islets were functionally imaged in vitro and in vivo. Wild-type mice were transplanted with islets expressing GCaMP6f in {beta}-cells into the anterior eye chamber and placed on a high fat diet. Part of the cohort received a glucagon analogue (GCG-analogue) for 40 days and the control group were fed to achieve weight matching. Calcium imaging was performed regularly during the development of hyperglycaemia and in response to GCG-analogue treatment. ResultsGcgr {beta}-cell-/- mice exhibited impaired glucose tolerance following intraperitoneal glucose challenge (control 12.7mmol/L {+/-}0.6 vs. Gcgr {beta}-cell-/- 15.4mmol/L {+/-}0.0 at 15 min, p=0.002); fasting glycaemia was not different to controls. In vitro, Gcgr {beta}-cell-/- islets showed profound loss of synchronised calcium waves in response to glucose which was only partially rescued in vivo. First-phase insulin pulsatility on peripheral blood sampling (n=5) was significantly disordered in Gcgr {beta}-cell-/- mice (burst mass Gcgr {beta}-cell-/- 0.30 {+/-}0.03 versus 0.84 {+/-}0.23 for controls p=0.04). Diet induced obesity and hyperglycaemia resulted in a loss of co-ordinated [Ca2+]I waves in transplanted islets. This was reversed with GCG-analogue treatment, independently of weight-loss (n=8). ConclusionThese data provide novel evidence for the role of intra-islet GCGR signalling in sustaining synchronised calcium oscillations and support a possible therapeutic role for glucagonergic agents to restore the insulin pulsatility lost in T2D.

physiology↗

bioRxiv2022

Bayesian species distribution models integrate presence-only and presence-absence data to predict deer distribution and relative abundance.

The use of georeferenced information on the presence of a species to predict its distribution across a geographic area is one of the most common tools in management and conservation. The collection of high-quality presence-absence data through structured surveys is, however, expensive, and managers usually have more abundant low-quality presence-only data collected by citizen scientists, opportunistic observations, and culling returns for game species. Integrated Species Distribution Models (ISDMs) have been developed to make the most of the data available by combining the higher-quality, but usually less abundant and more spatially restricted presence-absence data, with the lower quality, unstructured, but usually more extensive and abundant presence-only data. Joint-likelihood ISDMs can be run in a Bayesian context using INLA (Integrated Nested Laplace Approximation) methods that allow the addition of a spatially structured random effect to account for data spatial autocorrelation. These models, however, have only been applied to simulated data so far. Here, for the first time, we apply this approach to empirical data, using presence-absence and presence-only data for the three main deer species in Ireland: red, fallow and sika deer. We collated all deer data available for the past 15 years and fitted models predicting distribution and relative abundance at a 25 km2 resolution across the island. Models predictions were associated to spatial estimate of uncertainty, allowing us to assess the quality of the model and the effect that data scarcity has on the certainty of predictions. Furthermore, we validated the three species-specific models using independent deer hunting returns. Our work clearly demonstrates the applicability of spatially-explicit ISDMs to empirical data in a Bayesian context, providing a blueprint for managers to exploit unused and seemingly unusable data that can, when modelled with the proper tools, serve to inform management and conservation policies.

ecology↗

bioRxiv2022

Characterisation and sequence mapping of large RNA and mRNA therapeutics using mass spectrometry

Large RNA including messenger RNA (mRNA) has emerged as an important new class of therapeutic. Recently this has been demonstrated by two highly efficacious vaccines based on mRNA sequences encoding for a modified version of the SARS-CoV-2 spike protein. There is currently significant demand for the development of new and improved analytical methods for the characterization of large RNA including mRNA therapeutics. In this study we have developed an automated, high throughput workflow for the rapid characterisation and direct sequence mapping of large RNA and mRNA therapeutics. Partial RNase digestions using RNase T1 immobilised on magnetic particles was performed in conjunction with high resolution liquid chromatography mass spectrometry analysis. Sequence mapping was performed using automated oligoribonucleotide annotation and identifications based on MS/MS spectra. Using this approach >80% sequence of coverage of a range of large RNAs and mRNA therapeutics including the SARS Co-V2 spike protein was obtained in a single analysis. The analytical workflow, including automated sample preparation can be completed within 90 minutes. The ability to rapidly identify, characterise and sequence map large mRNA therapeutics with high sequence coverage provides important information for identity testing, sequence validation and impurity analysis.

biochemistry↗

bioRxiv2022

EFA6R suppresses ovarian cancer cell migration and invasion

Exchange factor for ADP-ribosylation factor (Arf)6 (EFA6)R expression loss in ovarian cancer has shown to decrease patient survival. EFA6R contains the catalytic Sec7, pleckstrin homology (PH), and coiled-coil (CC) domains. To gain further insight into the role of EFA6R, this study further investigated EFA6R expression in OC and its putative role as a metastatic suppressor. EFA6R mRNA expression, assessed by RT-qPCR, was significantly downregulated in OC tissues and cell lines. OC tissue microarray staining with EFA6R antibody showed that loss of protein expression correlated with increased cancer grade. Furthermore, EFA6R protein levels, assessed by immunoblotting, were significantly reduced in OC tissues and cell lines. Treatment of SKOV-3 cells with 5-aza-2deoxycytidine, an epigenetic regulator, restored EFA6R expression and attenuated functional cell migration and invasion, which was reversed by siRNA-mediated knockdown of EFA6R expression. This study also revelated that exogenously expressed EFA6R localises to the plasma membrane, through its PH domain, and thereby inhibits cell migration and invasion in the CC domain-dependent and an Arf6-independent manner. EFA6R loss-of-function involves epigenetic mechanisms in which downregulation increases OC tumour cell migration and invasion. Summary statementEFA6R expression is epigenetically regulated in ovarian cancer cells and loss of expression correlates with increased tumour grade and enhanced tumour cell migration. EFA6R appears to mediate these effects independently of Arf6.

cell biology↗

bioRxiv2021

Myofibroblast Senescence Promotes Arrhythmogenic Remodeling in the Aged Infarcted Rabbit Heart

Progressive tissue remodeling after myocardial infarction (MI) promotes cardiac arrhythmias. This process is well studied in young animals, but little is known about pro-arrhythmic changes in aged animals. Senescent cells accumulate with age and accelerate age-associated diseases. Senescent cells interfere with cardiac function and outcome post-MI with age, but studies have not been performed in large animals, and the mechanisms are unknown. Here, we investigated the role of senescence in regulating inflammation, fibrosis, and arrhythmogenesis in young and aged infarcted rabbits. Aged rabbits exhibited increased peri-procedural mortality and arrhythmogenic electrophysiological remodeling at the infarct border zone (IBZ) compared to young rabbits. Studies of the aged infarct zone revealed persistent myofibroblast senescence and increased inflammatory signaling over a twelve-week timecourse. Senescent IBZ myofibroblasts in aged rabbits appear to be coupled to myocytes, and our computational modeling showed that senescent myofibroblast- cardiomyocyte coupling prolongs action potential duration (APD) and facilitates conduction block permissive of arrhythmias. Aged infarcted human ventricles show levels of senescence consistent with aged rabbits, and senescent myofibroblasts also couple to IBZ myocytes. Our findings suggest that senolytic drugs may mitigate arrhythmias post-MI.

cell biology↗

bioRxiv2021

Measuring arterial pulsatility with Dynamic Inflow MAgnitude Contrast (DIMAC)

The pulsatility of blood flow through cerebral arteries is clinically important, as it is intrinsically associated with cerebrovascular health. In this study we outline a new MRI approach to measuring the real-time pulsatile flow in cerebral arteries, which is based on the inflow phenomenon associated with fast gradient-recalled-echo acquisitions. Unlike traditional phase-contrast techniques, this new method, which we dub Dynamic Inflow Magnitude Contrast (DIMAC), does not require velocity-encoding gradients as sensitivity to flow velocity is derived purely from the inflow effect. We achieved this using a highly accelerated single slice EPI acquisition with a very short TR (15 ms) and a 90{degrees} flip angle, thus maximizing inflow contrast. We simulate the spoiled GRE signal in the presence of large arteries and perform a sensitivity analysis to demonstrate that in the regime of high inflow contrast it shows much greater sensitivity to flow velocity over blood volume changes. We support this theoretical prediction with in-vivo data collected in two separate experiments designed to demonstrate the utility of the DIMAC signal contrast. We perform a hypercapnia challenge experiment in order to experimentally modulate arterial tone within subjects, and thus modulate the arterial pulsatile flow waveform. We also perform a thigh-cuff release challenge, designed to induce a transient drop in blood pressure, and demonstrate that the continuous DIMAC signal captures the complex transient change in the pulsatile and non-pulsatile components of flow. In summary, this study proposes a new role for a well-established source of MR image contrast and demonstrates its potential for measuring both steady-state and dynamic changes in arterial tone. HighlightsO_LIWe present a novel method for measuring pulsatility of cerebral arteries. C_LIO_LIThe inflow effect on fast GRE imaging can be exploited to yield a flow velocity dependent signal. C_LIO_LIWe measure pulsatile flow through cerebral arteries dynamically on a beat-to-beat basis. C_LIO_LIWe use physiological challenges to demonstrate sensitivity to dynamic and steady-state changes in vascular tone. C_LI

bioengineering↗

bioRxiv2021

Alzheimer's genetic risk effects on cerebral blood flow are spatially consistent and proximal to gene expression across the lifespan

Cerebrovascular dysregulation is a hallmark feature of Alzheimers disease (AD), where alterations in cerebral blood flow (CBF) are observed decades prior to symptom onset. Genome-wide association studies (GWAS) show that AD has a polygenic aetiology, providing a tool for studying AD susceptibility across the lifespan. Here, we ascertain whether AD genetic risk effects on CBF previously observed (Chandler et al., 2019) remain consistent across the lifespan. We further provide a causal mechanism to AD genetic risk scores (AD-GRS) effects by establishing spatial convergence between AD-GRS associated regional reductions in CBF and mRNA expression of the proximal AD transcripts using independent data from the Allen Brain Atlas. We analysed grey matter (GM) CBF in a young cohort (N=75; aged 18-35) and an older cohort (N=90; aged 55-85). Critically, we observed that AD-GRS was negatively associated with whole brain GM CBF in the older cohort (standardised {beta} -0.38 [-0.68 - -0.09], P = 0.012), consistent with our prior observation in younger healthy adults (Chandler et al., 2019). We then demonstrate that the regional impact of AD-GRS on GM CBF was spatially consistent across the younger and older samples (r = 0.233, P = 0.035). Finally, we show that CBF across the cortex was related to the regional expression of the genes proximal to SNPs used to estimate AD-GRS in both younger and older cohorts (ZTWO-TAILED = -1.99, P= 0.047; ZTWO-TAILED = -2.153 P = 0.032, respectively). These observations collectively demonstrate that AD risk alleles have a negative influence on brain vascular function and likely contribute to cerebrovascular changes preceding the onset of clinical symptoms, potentially driven by regional expression of proximal AD risk genes across the brain. Our observations suggest that reduced CBF is an early antecedent of AD and a key modifiable target for therapeutic intervention in individuals with a higher cumulative genetic risk for AD. This study will further enable identification of key molecular processes that underpin AD genetic risk related reductions in CBF that could be targeted decades prior to the onset of neurodegeneration.

genetics↗

bioRxiv2020

The Vagus Nerve Mediates the Physiological but not Pharmacological Effects of PYY3-36 on Food Intake

Peptide YY (PYY3-36) is a post-prandially released gut hormone with potent appetite-reducing activity mediated by the neuropeptide Y (NPY) Y2 receptor (Y2R). However, the neuronal pathways by which PYY3-36 acts to supress appetite are unclear. Determining how the PYY3-36 system physiologically regulates food intake may help exploit its therapeutic potential. Here we demonstrate that germline and post-natal targeted knockdown of the Y2R in the afferent vagus nerve inhibits the anorectic effects of physiologically-released PYY3-36, but not peripherally-administered higher doses. Post-natal knockdown of the Y2R results in a transient body weight phenotype that is compensated for in the germline model. Loss of vagal Y2R signalling also alters meal patterning and accelerates gastric emptying. These results may facilitate the design of PYY-based anti-obesity agents. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=98 SRC="FIGDIR/small/241851v1_ufig1.gif" ALT="Figure 1"> View larger version (25K): org.highwire.dtl.DTLVardef@bef424org.highwire.dtl.DTLVardef@8e7d68org.highwire.dtl.DTLVardef@cb6757org.highwire.dtl.DTLVardef@1edb059_HPS_FORMAT_FIGEXP M_FIG C_FIG

physiology↗

bioRxiv2020

Large-scale analysis of DNA methylation identifies cellular alterations in blood from psychosis patients and molecular biomarkers of treatment-resistant schizophrenia.

ObjectivePsychosis - a complex and heterogeneous neuropsychiatric condition characterized by hallucinations and delusions - is a common feature of schizophrenia. There is evidence for altered DNA methylation (DNAm) associated with schizophrenia in both brain and peripheral tissues. We aimed to undertake a systematic analysis of variable DNAm associated with psychosis, schizophrenia, and treatment-resistant schizophrenia, also exploring measures of biological ageing, smoking, and blood cell composition derived from DNAm data to identify molecular biomarkers of disease. MethodsWe quantified DNAm across the genome in blood samples from 4,483 participants from seven case-control cohorts including patients with schizophrenia or first-episode psychosis. Measures of biological age, cellular composition and smoking status were derived from DNAm data using established algorithms. DNAm and derived measures were analyzed within each cohort and the results combined by meta-analysis. ResultsPsychosis cases were characterized by significant differences in measures of blood cell proportions and elevated smoking exposure derived from the DNAm data, with the largest differences seen in treatment-resistant schizophrenia patients. DNAm at 95 CpG sites was significantly different between psychosis cases and controls, with 1,048 differentially methylated positions (DMPs) identified between schizophrenia cases and controls. Schizophrenia-associated DMPs colocalize to regions identified in genetic association studies, with genes annotated to these sites enriched for pathways relevant to disease. Finally, a number of the schizophrenia associated differences were only present in the treatment-resistant schizophrenia subgroup. ConclusionsWe show that DNAm data can be leveraged to derive measures of blood cell counts and smoking that are strongly associated with psychosis. Our DNAm meta-analysis identified multiple DMPs associated with both psychosis and a more refined diagnosis of schizophrenia, with evidence for differential methylation associated with treatment-resistant schizophrenia that potentially reflects exposure to clozapine.

genomics↗

bioRxiv2020

IRF8 Governs Tumor-Associated Macrophage Control of T Cell Exhaustion

Tumor progression is associated with overstimulation of cytotoxic T lymphocytes (CTLs), resulting in a dysfunctional state of exhaustion. How T cell exhaustion is elicited in the tumor remains poorly understood. Here we show that tumor-associated macrophages (TAMs) present cancer cell antigen and induce CTL exhaustion through a gene expression program dependent on the transcription factor interferon regulatory factor-8 (IRF8). In a transgenic model of murine breast cancer, CTL priming was supported by IRF8-dependent dendritic cells; yet, CTL exhaustion required TAM expression of IRF8, and its ablation suppressed tumor growth. An analysis of the highly immune-infiltrated human renal cell carcinoma tumors revealed abundant TAMs that expressed IRF8 and were enriched for an IRF8 gene expression signature. The IRF8 signature co-segregated with T cell exhaustion markers and was negatively associated with long-term patient survival. Thus, CTL exhaustion is promoted by TAMs via IRF8, and this crosstalk may be disrupted in TAM-targeted therapies.

immunology↗

bioRxiv2019

A frequency-domain machine learning method for dual-calibrated fMRI mapping of oxygen extraction fraction (OEF) and cerebral metabolic rate of oxygen consumption (CMRO2)

Magnetic resonance imaging (MRI) offers the possibility to non-invasively map the brains metabolic oxygen consumption (CMRO2), which is essential for understanding and monitoring neural function in both health and disease. However, in depth study of oxygen metabolism with MRI has so far been hindered by the lack of robust methods. One MRI method of mapping CMRO2 is based on the simultaneous acquisition of cerebral blood flow (CBF) and blood oxygen level dependent (BOLD) weighted images during respiratory modulation of both oxygen and carbon dioxide. Although this dual-calibrated methodology has shown promise in the research setting, current analysis methods are unstable in the presence of noise and/or are computationally demanding. In this paper, we present a machine learning implementation for the multi-parametric assessment of dual-calibrated fMRI data. The proposed method aims to address the issues of stability, accuracy, and computational overhead, removing significant barriers to the investigation of oxygen metabolism with MRI. The method utilizes a time-frequency transformation of the acquired perfusion and BOLD-weighted data, from which appropriate feature vectors are selected for training of machine learning regressors. The implemented machine learning methods are chosen for their robustness to noise and their ability to map complex non-linear relationships (such as those that exist between BOLD signal weighting and blood oxygenation). An extremely randomized trees (ET) regressor is used to estimate resting blood flow and a multi-layer perceptron (MLP) is used to estimate CMRO2 and the oxygen extraction fraction (OEF). Synthetic data with additive noise are used to train the regressors, with data simulated to cover a wide range of physiologically plausible parameters. The performance of the implemented analysis method is compared to published methods both in simulation and with in-vivo data (n=30). The proposed method is demonstrated to significantly reduce computation time, error, and proportional bias in both CMRO2 and OEF estimates. The introduction of the proposed analysis pipeline has the potential to not only increase the detectability of metabolic difference between groups of subjects, but may also allow for single subject examinations within a clinical context.

neuroscience↗

bioRxiv2019

Single-cell RNAseq uncovers involution mimicry as an aberrant development pathway during breast cancer metastasis

Both luminal and basal breast cancer subtypes originate in the mammary luminal progenitor cell compartment. Basal breast cancer is associated with younger age, early relapse, and high mortality rate. Here we used unbiased droplet-based single-cell RNAseq to elucidate the cellular basis of tumour progression during the specification of the basal breast cancer subtype from the luminal progenitor population. Basal-like cancer cells resembled the alveolar lineage that is specified upon pregnancy and showed molecular features indicative of an interaction with the tumour microenvironment (TME) including epithelial-to-mesenchymal transition (EMT), hypoxia, lactation and involution. Involution signatures in luminal breast cancer tumours with alveolar lineage features were associated with worse prognosis and features of basal breast cancer. Our high-resolution molecular characterisation of the tumour ecosystem also revealed a highly interactive cell-cell network reminiscent of an involution process. This involution mimicry involves malignant education of cancer-associated fibroblasts and myeloid cell recruitment to support tissue remodelling and sustained inflammation. Our study shows how luminal breast cancer acquires an aberrant post-lactation developmental program that involves both cancer cells and cells from the TME, to shift molecular subtype and promote tumour progression, with potential to explain the increased risk and poor prognosis of breast cancer associated to childbirth.

cancer biology↗

bioRxiv2019

High-throughput Phenotyping with Temporal Sequences

ObjectiveHigh-throughput electronic phenotyping algorithms can accelerate translational research using data from electronic health record (EHR) systems. The temporal information buried in EHRs are often underutilized in developing computational phenotypic definitions. The objective of this study is to develop a high-throughput phenotyping method, leveraging temporal sequential patterns of discrete events from electronic health records. Materials and MethodsWe develop a representation mining algorithm to extract five classes of representations from EHR diagnosis and medication records: the aggregated vector of the records (AVR), the traditional immediate sequential patterns (SPM), the transitive sequential patterns (tSPM), as well as two hybrid classes of SPM+AVR and tSPM+AVR. A final small set of representations were selected from each class using the MSMR dimensionality reduction algorithm. Using EHR data on 10 phenotypes from Mass General Brigham Biobank, we trained regularized logistic regression algorithms, which we validated using labeled data. ResultsPhenotyping with temporal sequences resulted in a superior classification performance across all 10 phenotypes compared with the AVR representations that are conventionally used in electronic phenotyping. Although this study only utilizes the diagnosis and medication records, the high-throughput algorithms classification performance was superior or similar to the performance of previously published electronic phenotyping algorithms. We characterize and evaluate the top transitive sequences of diagnosis records paired with the records of risk factors, symptoms, complications, medications, or vaccinations. DiscussionThe proposed high-throughput phenotyping approach enables seamless discovery of sequential record combinations that may be difficult to assume from raw EHR data. A transitive sequence can offer a more accurate characterization of the phenotype, compared with its individual components. Additionally, the identified transitive sequences of a given phenotype reflect the actual lived experiences of the patients with that particular disease. ConclusionSequential data representations provide a precise mechanism for incorporating raw EHR records into downstream Machine Learning.

bioinformatics↗

bioRxiv2018

Vascular physiology drives functional brain networks

We present the first evidence for vascular regulation driving fMRI signals in specific functional brain networks. Using concurrent neuronal and vascular stimuli, we collected 30 BOLD fMRI datasets in 10 healthy individuals: a working memory task, flashing checkerboard stimulus, and CO2 inhalation challenge were delivered in concurrent but orthogonal paradigms. The resulting imaging data were averaged together and decomposed using independent component analysis, and three \"neuronal networks\" were identified as demonstrating maximum temporal correlation with the neuronal stimulus paradigms: Default Mode Network, Task Positive Network, and Visual Network. For each of these, we observed a second network component with high spatial overlap. Using dual regression in the original 30 datasets, we extracted the time-series associated with these network pairs and calculated the percent of variance explained by the neuronal or vascular stimuli using a normalized R2 parameter. In each pairing, one network was dominated by the appropriate neuronal stimulus, and the other was dominated by the vascular stimulus as represented by the end-tidal CO2 time-series recorded in each scan. We acquired a second dataset in 8 of the original participants, where no CO2 challenge was delivered and CO2 levels fluctuated naturally with breathing variations. Although splitting of functional networks was not robust in these data, performing dual regression with the network maps from the original analysis in this new dataset successfully replicated our observations. Thus, in addition to responding to localized metabolic changes, the brains vasculature may be regulated in a coordinated manner that mimics (and potentially supports) specific functional brain networks. Multi-modal imaging and advances in fMRI acquisition and analysis could facilitate further study of the dual nature of functional brain networks. It will be critical to understand network-specific vascular function, and the behavior of a coupled vascular-neural network, in future studies of brain pathology.

neuroscience↗

bioRxiv2017

A toolbox of immunoprecipitation-grade monoclonal antibodies against human transcription factors.

A key component to overcoming the reproducibility crisis in biomedical research is the development of readily available, rigorously validated and renewable protein affinity reagents. As part of the NIH Protein Capture Reagents Program (PCRP), we have generated a collection of 1406 highly validated, immunoprecipitation (IP) and/or immunoblotting (IB) grade, mouse monoclonal antibodies (mAbs) to 736 human transcription factors. We used HuProt human protein microarrays to identify mAbs that recognize their cognate targets with exceptional specificity. Using an integrated production and validation pipeline, we validated these mAbs in multiple experimental applications, and have distributed them to the Developmental Studies Hybridoma Bank (DSHB) and several commercial suppliers. This study allowed us to perform a meta-analysis that identified critical variables that contribute to the generation of high quality mAbs. We find that using full-length antigens for immunization, in combination with HuProt analysis, provides the highest overall success rates. The efficiencies built into this pipeline ensure substantial cost savings compared to current standard practices.

biochemistry↗