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Garner, T.

Publications and source records attributed to Garner, T..

15 recordsLinked to original sources

Higher-Order Organization Links Circulating Metabolites to Glucocorticoid Action in Human Adipose Tissue

Glucocorticoids (GCs) are regulators of metabolism, yet how physiological GC exposure remodels adipose metabolism and its relationship with circulating biomarkers remains poorly understood. In a randomised cross-over study of individuals with primary adrenal insufficiency, near-physiological GC exposure was compared to withdrawal using integrated serum metabolomics, abdominal subcutaneous microdialysis metabolomics, and adipose tissue transcriptomics. GC exposure induced coordinated changes in adipose lipid and amino-acid metabolism. Pathway-level entropy analysis revealed GC-state-dependent transcriptional reorganisation, with concentrated organisation during exposure and diffuse organisation during withdrawal. Integrative hypergraph and topological analyses revealed GC-state-dependent reorganisation of circulating metabolite-adipose tissue relationships, with greater higher-order coordination during exposure. The circulating phenylalanine/kynurenine ratio discriminated GC state, showed the strongest shared connectivity to GC-regulated adipose networks, persisted at midnight and in an independent dose-response study, and exhibited circadian rhythmicity. These findings reveal dynamic GC regulation of adipose metabolism and identify a circulating biomarker with potential to guide personalised GC therapy.

systems biology↗

Host species composition, not priority effects, determines infection risk in multihost-multiparasite amphibian communities

Novel parasite emergences are posing uncertain threats to wildlife communities worldwide. Because parasites typically infect multiple host species and interact with other parasites, the degree of threat posed by these emergences is known to depend both on a communitys host species composition and history of exposure to other parasites. What is not known is how these two factors - multi-host effects and multi-parasite effects - interact to shape the outcomes of parasite emergences. We experimentally investigated the outcomes of sequential emergences by two amphibian parasites of major concern to global biodiversity, Batrachochytrium dendrobatidis (Bd) and Ranavirus (Rv). Mimicking sequential Bd and Rv emergence in communities comprising either larval common toads (Bufo bufo), larval common frogs (Rana temporaria), or both host species, showed that host community composition influenced subsequent patterns of Bd and Rv infection much more than the presence of the other parasite. Bd prevalence varied predictably with host community composition; toads exhibited consistently higher Bd infection probabilities than frogs across all scenarios. Variation in community-level prevalence therefore was explained by differences in the relative abundance of toads. In contrast, community-level Rv prevalence was not consistently driven by a single host species. Going from single-host to two-host communities reversed relative Rv infection probabilities in frogs versus toads; when kept separately, frogs had a higher Rv infection probability than toads, but toads had a higher infection probability than frogs when the two species were co-housed. Host species composition can therefore alter multi-parasite infection dynamics not only through changes in the abundance of primary host species, but also through changes in which species appear to act as the primary hosts. These insights suggest that Bd-Rv dynamics in single-host scenarios may not reflect those occurring in natural multihost communities, and the observed context-dependency in the apparent primary host species for Rv highlights an overlooked factor potentially shaping biodiversity-disease relationships.

ecology↗

Spatial transcriptomic profiling reveals distinct signatures in acute versus chronic wounds through hypergraph modelling and transcriptomic entropy analysis.

IntroductionThe financial burden of wounds to healthcare systems continues to increase, with little progression on advanced treatment options. Single cell RNA sequencing studies have predominantly focused on phenotypically different cell types and are generally descriptive in their analyses. Coordination within the transcriptome can be modelled using hypergraphs, which quantify higher order interactions (coordination between two or more genes) in transcriptomic data. Hypergraph modelling and analysis of transcriptomic entropy of wound samples will further elucidate differences between healing and non-healing wounds. MethodsSpatial transcriptomic analysis (Visium Spatial Gene Expression) was performed on three acute wounds, three chronic wounds and two healthy, unwounded skin samples. Standard transcriptomic analyses were performed in Python using the packages Scanpy and Squidpy. Hypergraph modelling and transcriptomic entropy analyses were performed in R. ResultsAcross the samples, twenty-nine Leiden clusters were defined, with keratinocytes, fibroblasts and adipocytes subclusters present. Fifteen marker genes for acute and chronic wounds were identified, with pathway analysis identifying immune responses and cellular homeostasis present in acute wounds, whilst in chronic wounds, pathways included immune responses and extracellular matrix structure. Spatial transcriptomics allowed for a descriptive analysis of the Leiden clusters within the samples, with each tissue sample being divided up into upper, middle and lower layer for this purpose. Hypergraph analyses of the whole transcriptome from the pathology groups and the independent transcriptomic Leiden clustering, revealed differences in underlying transcriptomic coordination. The top 1000 highly connected genes from each pathology group were analysed by Over Representation Analysis, with integrated stress response signalling, maintenance of cell number and myeloid and mononuclear cell differentiation pathways present in acute samples (all FDR <0.05) compared to regulation of vasculature development, mononuclear cell differentiation and epithelial cell proliferation (all FDR <0.05) in the chronic samples. Analysis of transcriptomic entropy identified further differences between acute and chronic wounds, with decreasing entropy from control to acute to chronic samples (all p-adjusted <0.001). When comparing Leiden clusters that were present in at least two sample groups, there was a statistically significant difference in entropy, although Leiden clusters varied in high or low entropy between acute and chronic wound samples (all p< 2.2 x 10-16). By mapping high and low entropy values to spatial images of each sample, lower transcriptomic entropy within the wound bed was identified compared to the rest of the tissue sample. ConclusionsSpatial transcriptomic analysis allowed for distinct spatial patterning to be observed which delineated acute and chronic wounds. Analysis of higher order interactions within the wound sample transcriptome identified key pathways that were not identified using traditional analyses. Transcriptomic entropy analysis further highlighted the differences between the wound samples. This work has implications for the future development of biomarkers of chronic wounds.

physiology↗

Epigenome and transcriptome changes in KMT2D-related Kabuki syndrome Type 1 iPSCs, neuronal progenitors and cortical neurons

Kabuki syndrome type 1 (KS1) is a neurodevelopmental disorder caused by loss-of-function variants in KMT2D which encodes a H3K4 methyltransferase. The mechanisms underlying neurodevelopmental problems in KS1 are still largely unknown. Here, we track the epigenome and transcriptome across three stages of neuronal differentiation using patient-derived induced pluripotent stem cells (iPSCs) to gain insights into the disease mechanism of KS1. In KS1 iPSCs we detected significantly lower levels of functional KMT2D transcript and KMT2D protein, and lower global H3K4me1 and H3K4me2 levels. We identify loss of thousands of H3K4me1 peaks in iPSCs, neuronal progenitors (NPs) and early cortical neurons (CNs) in KS1. We show that the number of lost peaks increase as differentiation progresses. We also identify hundreds of differentially expressed genes (DEGs) in iPSCs, NPs and CNs in KS1. In contrast with the epigenomic changes, the number of DEGs decrease as differentiation progresses. Our analysis reveals significant enrichment of differentially downregulated genes in areas containing putative enhancer regions with H3K4me1 loss. We also identify a set of distinct transcription factor binding sites in differentially methylated regions and a set of DEGs related to KS1 phenotypes. We find that genes regulated by SUZ12, a subunit of Polycomb Repressive complex 2, are over-represented in KS1 DEGs at early stages of differentiation. In conclusion, we present a disease-relevant human cellular model for KS1 that provides mechanistic insights for the disorder and could be used for high throughput drug screening for KS1.

genetics↗

Single Cell Transcriptomic Modelling of the Fallopian Tube Epithelium Identifies Cellular Specialisation, Novel Differentiation Trajectories, and Gene Network Associations with Ectopic Pregnancy

STUDY QUESTIONCan network modelling of single cell transcriptomic data identify cellular developmental trajectories of fallopian tube (FT) epithelium and reveal functional and pathological divergence from the endometrium? SUMMARY ANSWERA bidirectional secretory and ciliated differentiation trajectory was apparent from a novel OVGP1+ progenitor population of FT epithelial cells. A causal network model of whole transcriptome action in the FT and endometrium revealed specific functional divergence between secretory cells of these tissues. The network model reflected the latest ectopic pregnancy genome wide association study (GWAS), invoking MUC1 and other candidate genes in mature secretory cells for ectopic and eutopic implantation. WHAT IS KNOWN ALREADYThe fallopian tube forms the in vivo peri-conceptual environment, which has a significant impact on programming offspring health. The fallopian tube epithelium establishes this environment, however the epithelial cell types are poorly characterised in health and disease. STUDY DESIGN, SIZE, DURATIONPublicly available benign FT single cell RNA sequencing (scRNA-seq) samples from thirteen women across three studies were combined. Endometrial scRNA-seq samples from thirteen women from one study were used to demonstrate transcriptomic differences between the epithelia of the two tissues. Network models of transcriptomic action were constructed with hypergraphs. PARTICIPANTS/MATERIALS, SETTING, METHODSA meta-analysis of FT scRNA-seq samples was performed to identify epithelial populations. Differential gene expression assessed differences between fallopian tube and endometrial epithelial scRNA-seq data. Functional differences between secretory cells in the tissues were characterised using hypergraph models. To identify associations with ectopic pregnancy, expression quantitative trait loci (eQTLs) from a recent GWAS were mapped onto the network models. MAIN RESULTS AND THE ROLE OF CHANCEEpithelial cells (n=14,360) were clustered into 8 secretory and ciliated epithelial populations in the meta-analysis of 3 scRNA-seq datasets. A novel OVGP1+ epithelial progenitor cell was also identified, and its bi-directional differentiation to mature secretory or mature ciliated populations was mapped by RNA velocity analysis. This progenitor exhibited a high velocity magnitude (12.47) and low confidence (0.69), a combination strongly indicative of multipotent progenitor status. Comparing FT epithelial cells with endometrial epithelial cells revealed 5.3-fold fewer shared genes between FT and endometrial glandular secretory cells than between FT and endometrial ciliated cells, suggesting functional divergence of secretory cells along the reproductive tract. Hypergraphs were used to identify highly coordinated regions of the transcriptome robustly associated with functional gene networks. In the FT secretory cells, these networks were enriched for lipid (FDR<0.002) and immune (FDR<0.00007) related pathways. We mapped eQTLs from a GWAS meta-analysis of 7070 women with ectopic pregnancy over a range of significance (P = 1.68 x 10-21- 5.8 x 10-4) to the hypergraphs of FT and endometrium. Of the 22 genes present in the hypergraphs, 13 of these clustered as highly coordinated genes. This demonstrated the functional importance of MUC1 in the FT and endometrium, (GWAS Study P = 5.32x10-9) and identified additional genes (SLC7A2, CLDN1, GLS, PEX6, PLXNA4, NR2F1, CLGN, PGGHG, ANKRD36) implicated in ectopic pregnancy and eutopic pregnancy. LIMITATIONS, REASONS FOR CAUTIONThe sample size of reproductive age women was limited in previous studies, and though causal network modelling was used and previous mechanistic data supports candidate gene involvement, no in vitro or in vivo validation of candidate was performed. WIDER IMPLICATIONS OF THE FINDINGSThese findings consolidate the existing single cell transcriptomic datasets of the FT to provide a comprehensive understanding of epithelial populations and define functionally distinct secretory cells that contribute to the peri-conceptual environment of the FT. We further implicate the role of MUC1 and secretory cells in ectopic pregnancy and suggest future targets for investigating embryo implantation in the FT and endometrium.

developmental biology↗

Analysis of higher order interactions quantifies co-ordination in the epigenome and reveals novel biological relationships in Kabuki syndrome

Complex direct and indirect relationships between multiple variables are a characteristic of all natural systems and are defined as higher order interactions (HOIs). Traditional differential and network analyses fail to account for the richness of omic datasets and miss HOIs. We investigated genome-wide peripheral blood DNA methylation data from Kabuki syndrome type 1 (KS1) and control individuals, identified 2,002 differentially methylated points (DMPs), and inferred 17 differentially methylated regions, which represent only 189 DMPs. We followed these results with quantification of HOIs by applying hypergraph network models on all the CpGs in the two datasets and revealed differences in co-ordination of the DMPs along with lower entropy and higher co-ordination of the peripheral epigenome in KS1 implying reduced network complexity. We demonstrate that the hypergraph approach captures substantially more information, enables factoring trans-relationships, and identifies biologically relevant pathways that escape the standard analyses. These findings construct the basis of a suitable model that is not computationally intensive for the analysis of the organisation of the epigenome in rare diseases. This approach can be applied to other types of omic datasets, and to other fields of science and medicine to investigate mechanism in big data.

systems biology↗

Standard methods for marking caudate amphibians do not impair animal welfare over the short term: an experimental approach

Major advancements in ecology and biodiversity conservation have been made thanks to methods for marking and individually tracking animals. Marking animals is both widely used and controversial due to the potential consequences to animal welfare, which are often incompletely evaluated before implementation. Two outstanding knowledge gaps concerning the welfare consequences of individual marking concerns their short-term behavioural impacts and the relative impacts from marking versus the handling of animals while carrying out procedures. We addressed these knowledge gaps through an experimental study of alpine newts (Ichthyosaura alpestris) in which we varied handling and marking procedures. Examining individual responses to handling, toe-clipping and visible implant elastomer (VIE) injection over 21 days showed that handling and marking elicited increased newt activity and hesitancy to feed compared to animals that did not get handled or marked. These effects were apparent even when animals were handled only (not marked), and marking did not further increase the magnitude of responses. Increases in newt activity and feeding hesitancy were transient; they were not observed in the weeks following handling and marking. Whereas previous studies emphasize the welfare impacts of marking procedures themselves, these findings highlight that handling alone can elicit behavioural changes with possible costs to welfare. Yet, the transient nature of behavioural responses observed here suggests that immediate costs of handling may be subsequently compensated for.

animal behavior and cognition↗

Monocarboxylate Transporters are Involved in Extracellular Matrix Remodelling in Pancreatic Ductal Adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive malignancy with a five-year survival rate of <8%. PDAC is characterised by desmoplasia with abundant extracellular matrix (ECM) rendering current therapies ineffective. Monocarboxylate transporters (MCTs) are key regulators of cellular metabolism and are upregulated in different cancers, however their role in PDAC desmoplasia is little understood. Here, we investigated MCT and ECM gene expression in primary PDAC patient biopsies using RNA-sequencing data obtained from Gene Expression Omnibus. We generated a hypernetwork model from these data to investigate whether a causal relationship exists between MCTs and ECMs. Our analysis of stromal and epithelial tissues (n=189) revealed 9 differentially expressed MCTs, including upregulation of SLC16A2/6/10 and the non-coding SLC16A1-AS1, and 502 ECMs including collagens, laminins, and ECM remodelling enzymes (false discovery rate<0.05). Causal hypernetwork analysis demonstrated a bidirectional relationship between MCTs and ECMs; 4 MCT and 255 ECM-related transcripts correlated with 90% of differentially expressed ECMs (n=376) and MCTs (n=7), respectively. The hypernetwork model was robust, established by two independent approaches involving iterated sampling and silencing of indirect interactions in the network. This transcriptomic analysis highlights the role of MCTs in PDAC desmoplasia via associations with ECMs, opening novel treatment pathways to improve patient survival. Simple SummaryMonocarboxylate transporters (MCTs) carry a variety of substrates with MCT1-4 being well characterised and involved in proton-coupled transport of monocarboxylates (such as lactate) which can be used as metabolic fuel for cancer cells. Increased acidity of tumour microenvironment via MCTs favours remodelling of extracellular matrix (ECM) leading to desmoplasia associated with tumour metastasis and poor patient outcomes. Although MCT1-2/4 are upregulated in several cancers, their expression and role in pancreatic ductal adenocarcinoma desmoplasia is little understood. Here, we aimed to understand the role of MCTs in desmoplasia through their associations with ECM components. Our analysis using hypernetworks showed the presence of bidirectional associations of MCTs and ECMs, suggesting the presence of a causal relationship and the need to further investigate their functional associations. It confirms the role of MCTs in desmoplasia highlighting their importance as therapeutic targets alone or in combination with key ECM components to potentially improve patient outcomes.

cancer biology↗

Ocean-Warming During Embryogenesis Programs a Lasting Transcriptomic Signature in Fishes

Exposure to elevated temperatures during embryogenesis can influence the plasticity of tissues in later-life. Despite these long-term changes in plasticity, few differentially expressed genes are ever identified, suggesting that the developmental programming of later-life plasticity may occur through the modulation of other aspects of the transcriptomic architecture, such as gene network function. Here, we use network modelling approaches to demonstrate that warm temperatures during embryonic development (developmental warming) have consistent effects in later-life on the organisation of transcriptomic networks across four diverse species of fishes: Scyliorhinus canicula, Danio rerio, Dicentrarchus labrax, and Gasterosteus aculeatus. The transcriptomes of developmentally warmed fishes are characterised by an increased entropy of their pairwise gene interaction networks, implying a less structured, more random set of gene interactions. We also show that, in zebrafish subject to developmental warming, the entropy of an individual gene within a network is associated with that genes probability of expression change during temperature acclimation in later-life. However, this association is absent in animals reared under control conditions. Thus, the thermal environment experienced during embryogenesis can alter transcriptomic organisation in later-life, and these changes may influence an individuals responsiveness to future temperature challenges.

developmental biology↗

Grb10a knockdown in Danio rerio during early life alters growth and cardiometabolic function associated with a remodelled transcriptome

Embryonic growth trajectory is a risk factor for chronic metabolic and cardiovascular disorder. Grb10 is a negative regulator of the main pathways driving embryonic growth. This study investigates the long-term cardiometabolic consequences and transcriptomic profiles of transient disruption of grb10a expression in Danio rerio. Knockdown was associated with increased embryonic growth (+7%) and metabolic rate (+25%), and decreased heart rate (- 50%) in early life. Juvenile growth and respiratory rate were also elevated (+30% and 7-fold increase respectively). The transcriptome was permanently remodelled by this transient disruption, with dysregulation of multiple growth, cardiac, and metabolic pathways. Phenotypic alteration persisted into adulthood, resulting in a leaner body with elevated skeletal and cardiac muscle content and aerobic scope (43%). This study not only confirms for the first time that transient disruption of a single gene can result in permanent transcriptomic remodelling but correlates this remodelling with persistent alterations to the adult cardiometabolic phenotype.

developmental biology↗

Trophectoderm differentiation to invasive syncytiotrophoblast is induced by endometrial epithelial cells during human embryo implantation

At implantation, trophoblast derived from the trophectoderm of the blastocyst-stage embryo invades the endometrium to establish pregnancy. To understand how embryos breach the endometrial epithelium, we modelled human implantation using blastocysts or trophoblast stem cell spheroids cultured with endometrial epithelial cells (EEC). Blastocyst invasion of the EEC layer was initiated by multinuclear syncytiotrophoblast. Spheroids also invaded the epithelium with syncytiotrophoblast, and EEC induced upregulation of syncytiotrophoblast markers. Modelling implantation in silico using blastocyst and EEC transcriptomes revealed gene networks that exhibited greater connectivity and organisation in trophectoderm of the polar region of the embryonic axis. However, gene ontologies and machine learning suggested that EEC drives syncytiotrophoblast differentiation in polar and mural trophectoderm. This is the first evidence for endometrial epithelium-induced trophectoderm differentiation to invasive syncytiotrophoblast as the cellular mechanism of embryonic breaching of the endometrium in humans, with implications for reproductive medicine and our understanding of human embryonic development.

developmental biology↗

Gene expression signatures predict response to therapy with growth hormone

Recombinant human growth hormone (r-hGH) is used as a therapeutic agent for disorders of growth including growth hormone deficiency (GHD) and Turner syndrome (TS). Treatment is costly and current methods to model response can only account for up to 60% of the variance. The aim of this work was to take a novel genomic approach to growth prediction. GHD (n=71) and TS patients (n=43) were recruited in a study on the long term response to r-hGH over five years of therapy. Pharmacogenomic analysis was performed using 1219 genetic markers and baseline blood transcriptome. Random forest was used to determine predictive value of transcriptomic data associated with growth response. No genetic marker passed the stringency criteria required for predictive value. However, we demonstrated that transcriptomic data can be used to predict growth with a high accuracy (AUC > 0.9) for short and long term therapeutic response in GHD and TS. Network models identified an identical core set of genes in both GHD and TS at each year of therapy whose expression can be used to classify therapeutic response to r-hGH. Combining transcriptomic markers with clinical phenotype was shown to significantly reduce predictive error. We have characterised the utility of baseline transcriptome for the prediction of growth response including the identification of a set of common genes in GHD and TS. This work could be translated into a single genomic test linked to a prediction algorithm to improve clinical management. One Sentence SummaryA blood transcriptome signature predicts response to recombinant human growth hormone in both growth hormone deficient and Turner syndrome children Trial registration numbers: NCT00256126 & NCT00699855

clinical trials↗

Interactome comparison of human embryonic stem cell lines with the inner cell mass and trophectoderm

Human embryonic stem cells (hESCs) derived from the pluripotent Inner cell mass (ICM) of the blastocyst are fundamental tools for understanding human development, yet are not identical to their tissue of origin. To investigate this divergence we compared the transcriptomes of genetically paired ICM and trophectoderm (TE) samples with three hESC lines: MAN1, HUES3 and HUES7 at similar passage. We generated inferred interactome networks using transcriptomic data unique to the ICM or TE, and defined a hierarchy of modules (highly connected regions with shared function). We compared network properties and the modular hierarchy and show that the three hESCs had limited overlap with ICM specific transcriptome (6%-12%). However this overlap was enriched for network properties related to transcriptional activity in ICM (p=0.016); greatest in MAN1 compared to HUES3 (p=0.048) or HUES7 (p=0.012). The hierarchy of modules in the ICM interactome contained a greater proportion of MAN1 specific gene expression (46%) compared to HUES3 (28%) and HUES7 (25%) (p=9.0x10-4). These findings show that traditional methods based on transcriptome overlap are not sufficient to identify divergence of hESCs from ICM. Our approach also provides a valuable approach to the quantification of differences between hESC lines. And Manchester Academic Health Sciences Centre

developmental biology↗

Direct Small Molecule Activation of Mitofusins

Mitochondrial fusion is a physiological process that is regulated by mitofusins on the outer mitochondrial membrane. Conformational plasticity between anti- and pro-tethering conformations of mitofusins permits mitochondrial tethering and subsequent fusion. Here we developed a pharmacophore-based model to rationally manipulate the conformational plasticity of mitofusin 2 and perfomed an in silico small-molecule screen. This enabled the discovery of a direct activator of mitofusins, MASM7, capable of potently promoting mitochondrial fusion. The specificity of the MASM7-mitofusin 2 interaction is highlighted by structure-activity relationships of MASM7 analogues, FRET, NMR and mitochondrial fusion studies using mitofusin mutants. Our study identified the first-in-class direct activator of mitofusins, demonstrating a new paradigm for chemical modulation of mitochondrial fusion and downstream processes.

biochemistry↗

Host Microbiome Richness Predicts Resistance to Disturbance by Pathogenic Infection in a Vertebrate Host

Environmental heterogeneity is known to modulate the interactions between pathogens and hosts. However, the impact of environmental heterogeneity on the structure of host-associated microbial communities, and how these communities respond to pathogenic exposure remain poorly understood. Here we use an experimental framework to probe the links between environmental heterogeneity, skin microbiome structure and infection by the emerging pathogen Ranavirus in a vertebrate host, the European common frog (Rana temporaria). We provide evidence that environmental complexity directly influences the diversity and structure of the host skin microbiome, and that more diverse microbiomes are more resistant to perturbation associated with exposure to Ranavirus. Our data also indicate that host microbiome diversity covaries with survival following exposure to Ranavirus. Our study highlights the importance of extrinsic factors in driving host-pathogen dynamics in vertebrate hosts, and suggests that environment-mediated variation in the structure of the host microbiome may covary with observed differences in host susceptibility to disease in the wild.

ecology↗