Biology subjects

Davis, M. J.

Publications and source records attributed to Davis, M. J..

At least 19 recordsLinked to original sources

bioRxiv2025

Improved marker detection for rare population in single-cell transcriptomics through text mining-inspired scoring approach

Accurate identification of cell types and states is a crucial step when analysing single cell RNA-seq data. Inaccurate cell type annotation leads to spurious results and biological interpretations in subsequent analyses. Cell type identification is traditionally done using established marker genes of each cell population. However, many existing methods do not perform well for imbalanced cell populations, which often occurs in the presence of rare cell types. Most existing methods tend to be biased towards the dominant cell populations or highly expressed genes, leading to inaccurate results. Here, we introduce the package smartid, which accurately identifies markers from even imbalanced data across batches by employing a modified Term Frequency-Inverse Document Frequency approach with Gaussian Mixture Model. smartid is also a gene-set scoring method which is able to distinguish the target group of interest. smartid is implemented in R and is freely available on Bioconductor at https://bioconductor.org/packages/release/bioc/html/smartid.html.

bioinformatics↗

bioRxiv2025

Roles of G-protein coupled receptors and mechanosensitive ion channels in pressure-induced chronotropy of lymphatic vessels

Active lymph pumping relies on the spontaneous contractions of collecting lymphatic vessels, whose contraction frequencies are exquisitely sensitive to changes in intraluminal pressure. This homeostatic and mechanosensitive mechanism, termed pressure-induced lymphatic chronotropy, enables lymph transport to be matched to the filling state of the lymphatic capillary network. The mechanistic basis of pressure-induced chronotropy was investigated using ex vivo contraction assays of mouse popliteal collecting vessels, in which contraction frequency increases >10-fold with pressure changed from 0.5 to 5 cmH2O. The contractile, electrophysiological and transcriptional similarities between lymphatic muscle cells (LMCs) and arterial smooth muscle led us to hypothesize that pressure-dependent chronotropy shares a parallel signaling process with pressure-induced arterial depolarization/constriction. Thus, we probed two major mechanisms: 1) pressure-induced activation of mechanosensitive cation channels, including TRPC6, TRPM4, PKD1/2, TRPV2 and ENaC, and 2) mechano-activation of GNAQ/GNA11-coupled G-protein receptors (GPCRs) that would generate second messengers to activate those channels. Contraction assays were combined with scRNAseq analysis of the respective targets, with maximum use made of transgenic mice to avoid non-specific effects of pharmacological inhibitors, particularly those used to block TRP channels. Our findings rule out significant roles for the above TRP channels and other putative mechanosensitive channels implicated in arterial myogenic constriction, as well as channels implicated in ionic pacemaking of other tissues. In contrast, smooth-muscle specific knock out or inhibition of ANO1 or IP3R1 significantly blunted the effect of pressure on frequency. Pressure-induced chronotropy was suppressed by [~]70-90% at all pressures in GNAQ/GNA11 double knockout vessels, but with responsiveness partially maintained at pressures above 5 cmH2O. Pressure-induced chronotropy was also suppressed after acute Gq/11 inhibition with YM254890, but was normal in vessels from GNA12/GNA13 double knock out mice. These results support a scheme whereby mechano-activation of one or more GNAQ/GNA11-coupled GPCRs generates IP3, which induces SR Ca2+ release through IP3R1 and drives depolarization through the activation of ANO1 Cl- channels. The major GPCRs expressed in LMCs were subsequently identified and ranked by scRNAseq analysis but knock out or pharmacological inhibition of each of the top 7 candidates failed to significantly affect pressure-induced chronotropy. Our results strongly implicate one or more GNAQ/GNA11-coupled GPCRs in mediating this homeostatic process; however, the specific mechanosensitive GPCRs remain to be identified.

physiology↗

bioRxiv2025

Mojave Desert microbial communities show high resistance and resilience over three years despite widespread plant mortality following the Dome Fire

O_LIHigh severity desert fires are uncommon but typically chart a new successional trajectory altering plant communities for at least 65 years. These aboveground vegetation shifts can have large implications for belowground microbial communities that maintain soil structure and nutrient cycling. High severity wildfires in forests or shrublands can severely reduce microbial species richness and biomass and alter microbiomes for decades but impacts on desert soil microbiomes are virtually unknown. C_LIO_LIThe 2020 Mojave Desert Dome Fire burned 43,273 acres of Eastern Joshua tree (Yucca jaegeriana) habitat, burning roughly 1 million trees. To track aboveground and belowground impacts of the Dome Fire, we established 9 plots (6 burned; 3 unburned) and sampled 4 subsamples per plot for 5 time points ranging from 2 weeks to 3 years post-fire. We measured initial ash depth as a proxy of soil burn severity and assessed plant mortality, plant richness, soil chemical characteristics, estimated soil microbial biomass with qPCR, and microbial richness and composition with Illumina MiSeq of 16S and ITS2 amplicons. C_LIO_LIBelowground communities were highly diverse, containing 25,444 bacterial, 269 archaeal, and 6,683 fungal ASVs amplicon sequence variants (ASVs) or microbial taxa. We identified at least 65 plant species and saw 80% Eastern Joshua tree mortality in burned plots over three years, with reduced plant richness post-fire except an abundance of annual herbs at 1-year post-fire, yet the fire did not significantly reduce microbial biomass or richness at any time point. C_LIO_LIMicrobial communities for both bacteria and fungi showed small but significant changes, enriching for pyrophilous microbes in burned plots. We identified increases of pyrophilous microbes such as Tumebacillus, Massilia, Noviherbaspirillum bacteria and Pseudotricharina, Penicillium, Coniochaeta and Naganishia fungi. C_LIO_LISynthesis: We present the first comprehensive above and belowground examination following a natural desert wildfire including Archaea, Bacteria, and Fungi. Despite the widespread mortality of Eastern Joshua trees across 3 years, microbial biomass, richness, and community composition were mostly resistant to change, like microbial responses to low-intensity fast-moving grassland fires. Despite high resistance overall, wildfire still increased several pyrophilous bacterial and fungal taxa common after high severity shrubland and forest wildfires. C_LI

microbiology↗

bioRxiv2024

A novel HLA Class II presentation prediction algorithm deciphers immunogenic CD4 epitopes specific to KRAS G12C

Accurate prediction of peptide presentation by HLA molecules is important for generation of effective individualized cancer vaccines and immunotherapies. While presentation prediction algorithms for HLA class I have been successfully applied in the context of such therapies, improved prediction algorithms for class II are needed. EDGE-II is a novel algorithm based on a protein large language model that has a learned allele deconvolution network trained on existing and new immunopeptidomics data. It delivers state-of-the-art performance on prediction of peptide presentation by HLA class II and immunogenicity elicited by CD4+ T-cell epitopes. In a patient with a KRAS G12C positive tumor treated with a KRAS G12C targeting immunotherapy, EDGE-II identified KRAS G12C class II neoantigens that elicited clonally expanded CD4+ T cells with cytotoxic transcriptional profiles post-vaccination. EDGE-II could play an important role in the development of effective cancer immunotherapies by elucidating an enriched understanding of the immunopeptidome.

bioinformatics↗

bioRxiv2024

Comprehensive Longitudinal ctDNA Monitoring in Metastatic Cancer Patients Treated with an Individualized Neoantigen-directed Vaccine

PurposeCirculating-tumor DNA (ctDNA) is an emerging, minimally invasive diagnostic and prognostic biomarker for patients receiving a variety of cancer therapies. Comprehensive and robust longitudinal monitoring of ctDNA can provide an understanding of tumor burden, heterogeneity, and response or resistance to treatment. Experimental DesignctDNA of 28 metastatic cancer patients receiving an individualized neoantigen-directed immunotherapy was monitored longitudinally, up to two years, using a unique hybrid next generation sequencing assay targeting tumor-informed and tumor-naive variants. Patient-specific panels were designed targeting an average of 144 variants per patient. A tumor-naive universal panel was also designed for inclusion with patient-specific panels to monitor recurrently mutated tumor hotspots (e.g., KRAS and TP53) and genes implicated in immunotherapy resistance (B2M, TAP1/2). ResultsAnalytical characterization of the assay established linearity with a mean variant allele frequency (VAF) [≥]0.049%, and a variant-level limit of detection (LOD95) of 0.12%. Tumor-informed variants were detected in 26/28 patients, and de novo variants were observed in 25/28 patients. HLA LOH was also observed. Longitudinal ctDNA data provided key insights into patients responses to vaccine treatment. ConclusionsThe hybrid design of the ctDNA monitoring assay provides the sensitivity and specificity required for evaluating patient samples undergoing individualized therapy. It provides an improved capability to understand patient response to experimental therapies and further supports the utility of ctDNA as a cancer biomarker.

genomics↗

bioRxiv2024

S1PR1 Regulates Lymphatic Valve Development And Prevents Ileitis-Independent Tertiary Lymphoid Organ Formation

Lymphatic vessels function throughout the body to drain interstitial fluids. Efficient lymph flow is ensured by lymphatic valves (LVs). However, the mechanisms that regulate LV development are incompletely understood. Here, we show that the deletion of the GPCR sphingosine 1-phosphate receptor-1 (S1PR1) from lymphatic endothelial cells (LECs) results in fewer LVs. Interestingly, LVs that remained in the terminal-ileum draining lymphatic vessels were specifically dysfunctional, and tertiary lymphoid organs (TLOs) formed in this location. TLOs in the terminal ileum are associated with ileitis in humans and mice. However, mice lacking S1PR1 did not develop obvious characteristics of ileitis. Sphingosine kinases 1 and 2 (SPHK1/2) are required for the synthesis of S1P, the ligand of S1PR1. Mice that lack Sphk1/2 in LECs recapitulate the LV and TLO phenotypes of mice that lack S1PR1. Mechanistically, S1PR1 regulates shear stress signaling and the expression of the valve-regulatory molecules FOXC2 and connexin-37. Importantly, Foxc2+/- mice, a model for lymphedema-distichiasis syndrome, also develop TLOs in the terminal ileum. Thus, we have discovered S1PR1 as a previously unknown regulator of LV and TLO development. We also suggest that TLOs are a sign of subclinical inflammation that can form due to lymphatic disorders in the absence of ileitis.

developmental biology↗

bioRxiv2024

Transient inhibition of type I interferon enhances CD8+ T cell stemness and vaccine protection

Developing vaccines that promote CD8+ T cell memory is a challenge for infectious disease and cancer immunotherapy. TCF-1+ stem cell-like memory T (TSCM) cells are important determinants of long-lived memory. Yet, the developmental requirements for TSCM formation are unclear. Here, we identify the temporal window for type I interferon (IFN-I) receptor (IFNAR) blockade to drive TSCM cell generation. TSCM cells were transcriptionally distinct and emerged from a transitional precursor of exhausted (TPEX) cellular state concomitant with viral clearance. TSCM differentiation correlated with T cell retention within the lymph node paracortex, due to increased CXCR3 chemokine abundance which disrupted gradient formation. These affects were due a counterintuitive increase in IFN{psi}, which controlled cell location. Combining IFNAR inhibition with mRNA-LNP vaccination promoted specific TSCM differentiation and enhanced protection against chronic infection. These finding propose a new approach to vaccine design whereby modulation of inflammation promotes memory formation and function. HIGHLIGHTSO_LIEarly, transient inhibition of the type I interferon (IFN) receptor (IFNAR) during acute viral infection promotes stem cell-like memory T (TSCM) cell differentiation without establishing chronic infection. C_LIO_LITSCM and precursor of exhausted (TPEX) cellular states are distinguished transcriptionally and by cell surface markers. C_LIO_LIDevelopmentally, TSCM cell differentiation occurs via a transition from a TPEX state coinciding with viral clearance. C_LIO_LITransient IFNAR blockade increases IFN{psi} production to modulate the ligands of CXCR3 and couple TSCM differentiation to cell retention within the T cell paracortex of the lymph node. C_LIO_LISpecific promotion of TSCM cell differentiation with nucleoside-modified mRNA-LNP vaccination elicits enhanced protection against chronic viral challenge. C_LI

immunology↗

bioRxiv2024

Divergent cytokine and transcriptional signatures control functional T follicular helper cell heterogeneity

Adaptive immune responses protect against multiple classes of pathogens, including viral, bacterial, fungal, and helminth infections. In all these settings, CD4+ T follicular helper (Tfh) cells tailor high-affinity class-switched B cells responses. How Tfh lineage sovereignty is established while allowing for this context-specific functional heterogeneity is unclear. Here, we identify Tfh transcriptional networks in response to diverse infections. While Bcl-6 is the transcriptional linchpin of the core Tfh signature, this is overlayed with pathogen-specific transcriptional modules that shape Tfh function. Cytokine-transcriptional Tfh programing in mouse and human lymphoid tissue demonstrated that type I interferon and TGF{beta} signaling direct individual Tfh subpopulations to instruct B cell output. Here, we provide a transcriptional map and cell surface resource to interrogate Tfh diversity in humans and mice. This resource can be leveraged to further understand the origins of immune flexibility, perform immune monitoring in infection and antibody-mediated diseases and to develop context-specific vaccines. ONE-SENTENCE SUMMARYDalit, Tan and colleagues provide a resource that functionally and transcriptionally profiles T follicular helper cells (Tfh) during diverse pathogen responses to reveal a blueprint for transcriptional flexibility and new tools to interrogate Tfh heterogeneity in mice and humans.

immunology↗

bioRxiv2024

SpaNorm: spatially-aware normalisation for spatial transcriptomics data

Library size normalisation is necessary to enable comparisons between observations in transcriptomic datasets. Numerous methods have been developed to normalise these effects with sample and gene specific adjustments. However, in spatial transcriptomics data, normalisation is complicated by the fact that spatial region-specific library size confounds biology. The most popular approach of adapting methods developed for single-cell RNA-seq data has been shown to excessively remove biological signals associated with spatial domains and thus results in poorer downstream domain identification. To this end, we propose the first spatially-aware normalisation method, SpaNorm. SpaNorm concurrently models spatial library size effects and the underlying smooth biology, to tease apart these effects, and thereby remove library size effects without removing biology. This is achieved through optimal decomposition of spatially smooth variation into those related and unrelated to library size and the use of location-specific scaling factors. Using 27 tissue samples from 6 datasets spanning 4 spatial platforms, we show that SpaNorm outperforms current state of the art methods at retaining biological information in the form of spatial domains and spatially variable genes (SVGs) better than 4 commonly used single-cell normalisation approaches. SpaNorm is versatile and it can be used for both spot-based and subcellular spatial transcriptomics data. Notably, the benefit of using SpaNorm is more pronounced for the latter data such as those from Xenium, STOmics and CosMx platforms for which the proportion of genes exhibiting region-specific library size effect is higher. SpaNorm works equally well with segmented cell-level data and spot-based data where each spot contains multiple cells.

bioinformatics↗

bioRxiv2024

mastR: Marker Automated Screening Tool for multi-omics data

MotivationBiomarker discovery and utilization is important and offers insight into potential underlying mechanisms of disease. Existing marker identification methods primarily focus on single cell RNA sequencing (scRNA-seq) data, with no specific automated methods designed to learn from the bulk RNA-seq data. Furthermore, when adapting scRNA-seq methods to bulk RNA-seq, the background expressions of non-targeted cell types are not accounted for. Here we bridge this gap with an automated marker identification method that works for bulk RNA sequencing data. ResultsWe developed mastR, a novel computational tool for accurate marker identification from omics data. It leverages robust pipelines from edgeR and limma R/Bioconductor packages, performing pairwise comparisons between groups, and aggregating the results through rank-product-based permutation test. A signal-to-noise ratio approach is implemented to minimize background signals. We assess the performance of a mastR-derived NK cell signature against curated published signatures and find our derived signature performs as well if not better than published signatures. We also demonstrate the utility of mastR on simulated scRNA sequencing data and provide examples of mastR outperforming Seurat in marker selection. Availability and implementationAll statistical analyses were carried out using R (version 4.3.0 or higher) and Bioconductor (version 3.17 and higher). MastR is available as an R/Bioconductor package with a comprehensive vignette for ease of use (https://bioconductor.org/packages/release/bioc/html/mastR.html) and a guide hosted on GitHub: https://davislaboratory.github.io/mastR/.

bioinformatics↗

bioRxiv2024

hoodscanR: profiling single-cell neighborhoods in spatial transcriptomics data

Understanding complex cellular niches and neighborhoods have provided new insights into tissue biology. Thus, accurate neighborhood identification is crucial, yet existing methodologies often struggle to detect informative neighborhoods and generate cell-specific neighborhood profiles. To address these limitations, we developed hoodscanR, a Bioconductor package designed for neighborhood identification and downstream analyses using spatial data. Applying hoodscanR to breast and lung cancer datasets, we showcase its efficacy in conducting detailed neighborhood analyses and identify subtle transcriptional changes in tumor cells from different neighborhoods. Such analyses can help researchers gain valuable insights into disease mechanisms and potential therapeutic targets.

bioinformatics↗

bioRxiv2023

An EPHB4-RASA1 signaling complex inhibits shear stress-induced Ras-MAPK activation in lymphatic endothelial cells to promote the development of lymphatic vessel valves

EPHB4 is a receptor protein tyrosine kinase that is required for the development of lymphatic vessel (LV) valves. We show here that EPHB4 is necessary for the specification of LV valves, their continued development after specification, and the maintenance of LV valves in adult mice. EPHB4 promotes LV valve development by inhibiting the activation of the Ras-MAPK pathway in LV endothelial cells (LEC). For LV specification, this role for EPHB4 depends on its ability to interact physically with the p120 Ras-GTPase-activating protein (RASA1) that acts as a negative regulator of Ras. Through physical interaction, EPHB4 and RASA1 dampen oscillatory shear stress (OSS)-induced Ras-MAPK activation in LEC, which is required for LV specification. We identify the Piezo1 OSS sensor as a focus of EPHB4-RASA1 regulation of OSS-induced Ras-MAPK signaling mediated through physical interaction. These findings contribute to an understanding of the mechanism by which EPHB4, RASA1 and Ras regulate lymphatic valvulogenesis.

developmental biology↗

bioRxiv2023

Identification of cell types, states and programs by learning gene set representations

As single cell molecular data expand, there is an increasing need for algorithms that efficiently query and prioritize gene programs, cell types and states in single-cell sequencing data, particularly in cell atlases. Here we present scDECAF, a statistical learning algorithm to identify cell types, states and programs in single-cell gene expression data using vector representation of gene sets, which improves biological interpretation by selecting a subset of most biologically relevant programs. We applied scDECAF to scRNAseq data from PBMC, Lung, Pancreas, Brain and slide-tags snRNA of human prefrontal cortex for automatic cell type annotation. We demonstrate that scDECAF can recover perturbed gene programs in Lupus PBMC cells stimulated with IFNbeta and TGFBeta-induced cells undergoing epithelial-to-mesenchymal transition. scDECAF delineates patient-specific heterogeneity in cellular programs in Ovarian Cancer data. Using a healthy PBMC reference, we apply scDECAF to a mapped query PBMC COVID-19 case-control dataset and identify multicellular programs associated with severe COVID-19. scDECAF can improve biological interpretation and complement reference mapping analysis, and provides a method for gene set and pathway analysis in single cell gene expression data.

bioinformatics↗

bioRxiv2023

Lymphatic muscle cells are the innate pacemaker cells regulating mouse lymphatic collecting vessel contractions

Collecting lymphatic vessels (cLVs) exhibit spontaneous contractions with a pressure-dependent frequency, but the identity of the lymphatic pacemaker cell is still debated. Here we combined immunofluorescence and scRNAseq analyses with electrophysiological methods to examine the cellular constituents of the mouse cLV wall and assess whether any cell type exhibited morphological and functional processes characteristic of pacemaker cells. We employed inducible Cre (iCre) mouse models to target specific cell populations including c-kitCreERT2 to target interstitial cells of Cajal like cells; Pdgfr{beta}CreERT2to target pericyte-like cells; PdgfrCreERTMto target CD34+ adventitial cells; and Myh11CreERT2to target lymphatic muscle cells (LMCs) directly. These inducible Cre lines were crossed to the fluorescent reporter ROSA26mT/mG, the genetically encoded Ca2+ sensor GCaMP6f, and the light- activated cation channel rhodopsin2 (ChR2). Only LMCs consistently, but heterogeneously, displayed spontaneous Ca2+ events during the diastolic period of the contraction cycle, and whose frequency was modulated in a pressure-dependent manner. Further, optogenetic depolarization with ChR2 only induced propagated contractions in LMCs. Membrane potential recordings in LMCs demonstrated that the rate of diastolic depolarization significantly correlated with contraction frequency. These findings support the conclusion that LMCs, or a subset of LMCs, are responsible for mouse cLV pacemaking. ImpactLymphatic muscle cells, but not CD34+ adventitial cells, exhibited pacemaker behaviors such as pressure-dependent depolarization, pressure-dependent calcium mobilization during diastole, and propagated contraction waves induced by focal, optogenetic depolarization via enforced channel- rhodopsin2.

physiology↗

bioRxiv2023

standR: a Bioconductor package for analysing transcriptomic Nanostring GeoMx DSP data

To gain a better understanding of the complexity of gene expression in normal and diseased tissues it is important to account for the spatial context and identity of cell in situ. State-of-the-art spatial profiling technologies, such as the Nanostring GeoMx Digital Spatial Profiler (DSP), now allow quantitative spatially resolved measurement of the transcriptome in tissues. However, the bioinformatics pipelines currently used to analyse GeoMx data often fail to successfully account for the technical variability within the data and the complexity of experimental designs, thus limiting the accuracy and reliability of subsequent analysis. Carefully designed quality control workflows, that include in-depth experiment-specific investigations into technical variation and appropriate adjustment for such variation can address this issue. Here we present standR, a R/Bioconductor package that enables an end-to-end analysis of GeoMx DSP data. With four case studies from previously published experiments, we demonstrate how the standR workflow can enhance the statistical power of GeoMx DSP data analysis and how application of standR enables scientists to develop in-depth insights into the biology of interest.

bioinformatics↗

bioRxiv2023

Library size confounds biology in spatial transcriptomics data

Spatial molecular technologies have revolutionised the study of disease microenvironments by providing spatial context to tissue heterogeneity. Recent spatial technologies are increasing the throughput and spatial resolution of measurements, resulting in larger datasets. The added spatial dimension and volume of measurements poses an analytics challenge that has, in the short-term, been addressed by adopting methods designed for the analysis of single-cell RNA-seq data. Though these methods work well in some cases, not all necessarily translate appropriately to spatial technologies. A common assumption is that total sequencing depth, also known as library size, represents technical variation in single-cell RNA-seq technologies, and this is often normalised out during analysis. Through analysis of several different spatial datasets, we noted that this assumption does not necessarily hold in spatial molecular data. To formally assess this, we explore the relationship between library size and independently annotated spatial regions, across 23 samples from 4 different spatial technologies with varying throughput and spatial resolution. We found that library size confounded biology across all technologies, regardless of the tissue being investigated. Statistical modelling of binned total transcripts shows that tissue region is strongly associated with library size across all technologies, even after accounting for cell density of the bins. Through a benchmarking experiment, we show that normalising out library size leads to sub-optimal spatial domain identification using common graph-based clustering algorithms. On average, better clustering was achieved when library size effects were not normalised out explicitly, especially with data from the newer sub-cellular localised technologies. Taking these results into consideration, we recommend that spatial data should not be specifically corrected for library size prior to analysis unless strongly motivated. We also emphasise that spatial data are different to single-cell RNA-seq and care should be taken when adopting algorithms designed for single cell data.

bioinformatics↗

bioRxiv2023

Spatial transcriptomic analysis of Sonic Hedgehog Medulloblastoma identifies that the loss of heterogeneity and promotion of differentiation underlies the response to CDK4/6 inhibition

BackgroundMedulloblastoma (MB) is a malignant tumour of the cerebellum which can be classified into four major subgroups based on gene expression and genomic features. Single cell transcriptome studies have defined the cellular states underlying each MB subgroup, however the spatial organisation of these diverse cell states and how this impacts response to therapy remains to be determined. MethodsHere, we used spatially resolved transcriptomics to define the cellular diversity within a sonic hedgehog (SHH) patient-derived model of MB and identify how cells specific to a transcriptional state or spatial location are pivotal in responses to treatment with the CDK4/6 inhibitor, Palbociclib. We integrated spatial gene expression with histological annotation and single cell gene expression data from MB, developing a analysis strategy to spatially map cell type responses within the hybrid system of human and mouse cells and their interface within an intact brain tumour section. ResultsWe distinguish neoplastic and non-neoplastic cells within tumours and from the surrounding cerebellar tissue, further refining pathological annotation. We identify a regional response to Palbociclib, with reduced proliferation and induced neuronal differentiation in both treated tumours. Additionally, we resolve at a cellular resolution a distinct tumour interface where the tumour contacts neighbouring mouse brain tissue consisting of abundant astrocytes and microglia and continues to proliferate despite Palbociclib treatment. ConclusionsOur data highlight the power of using spatial transcriptomics to characterise the response of a tumour to a targeted therapy and provide further insights into the molecular and cellular basis underlying the response and resistance to CDK4/6 inhibitors in SHH MB.

genomics↗

bioRxiv2022

A dual-clock-driven model emulating the effects of either Ano1 or IP3R knock-out on lymphatic muscle cell pace-making

Lymphoedema, a common dysfunction of the lymphatic system, results in fluid accumulating between cells. Fluid return through the lymphatic vascular system is primarily provided by contractions of muscle cells in the walls of lymphatic vessels, driven by electrochemical oscillations causing rhythmic action potentials and associated surges in intracellular calcium ion concentration. There is incomplete understanding of the mechanisms involved in these repeated events, restricting the development of pharmacological treatments for dysfunction. Previously, we proposed a model where autonomous oscillations in the membrane potential (M-clock) drove passive oscillations in the calcium concentration (C-clock). In this paper, to model more accurately what is known about the underlying physiology, we extend this model to the case where the M-clock and the C-clock oscillators are both active but coupled together, and thus both driving the action potentials. This extension results from modifications to the model for the IP3 receptor, a key C-clock mechanism. The synchronized dual-driving clock behaviour enables the model to match IP3 receptor knock-out data, resolving an issue with previous models. We also use phase-plane analysis to explain the mechanisms for the dual-clock coupling. The model has the potential to help determine mechanisms and find targets for pharmacological treatment of lymphoedema.

biophysics↗