Biology subjects

Filby, A.

Publications and source records attributed to Filby, A..

At least 19 recordsLinked to original sources

bioRxiv2025

Flow cytometry-based isolation combined with ultra-sensitive proteomics of Salmonella-containing phagosomes reveals novel insights into host-pathogen interactions

Macrophages engulf pathogens into dynamic phagosomes, which many bacteria manipulate for survival. However, isolating pure pathogen-containing phagosomes remains challenging. Here, we developed a novel flow cytometry-based isolation and ultrasensitive proteomics approach to analyse phagosomal and bacterial proteomes from macrophages infected with wild-type (WT) Salmonella enterica serovar Typhimurium (STM) or a {Delta}phoP mutant at 30 min and 4 hrs post-infection. Our approach provides higher throughput, requires lower cell numbers and quantifies more proteins than previous techniques. Our data reveals key host-pathogen interactions, showing induction of PhoP-dependent virulence factors and novel putative proteins that shape STMs intracellular niche. Moreover, our data indicates that bacteria-containing phagosomes recruit mitochondrial membrane for production of reactive oxygen species. These findings provide new insights into Salmonellas manipulation of phagosomal maturation and intracellular niche formation.

microbiology↗

bioRxiv2025

Spatial profiling of longitudinal glioblastoma reveals consistent changes in cellular architecture, post-treatment

Glioblastoma (GBM), the most aggressive adult brain cancer, comprises a complex tumour microenvironment (TME) with diverse cellular interactions driving progression and pathobiology. How these spatial patterns and interactions evolve with treatment remains unclear. Here, we apply imaging mass cytometry to analyse protein-level changes in paired pre- and post-treatment GBM samples from five patients. We find a significant post-treatment increase in normal brain cells alongside a reduction in vascular cells. Moreover, despite minimal overall change in cellular diversity, interactions among astrocytes, oligodendrocytes, and vascular cells increase post-treatment, suggesting reorganisation of the TME. The GBM TME cells form spatially organized layers driven by hypoxia pre-treatment, but this influence diminishes post-treatment, giving way to less organised layers with organisation driven by reactive astrocytes and lymphocytes. These findings provide insight into treatment-induced shifts in GBMs cellular landscape, highlighting aspects of the evolving TME that appear to facilitate recurrence and are, therefore, potential therapeutic targets. Key pointsO_LISpatial organisation in primary GBM consist of layers driven by the presence of hypoxia C_LIO_LIThe layers in recurrent GBM appear are driven more by the presence of reactive astrocytes C_LIO_LIIncreased cellular cross-talk in recurrent GBM presents novel therapeutic targets C_LI

cancer biology↗

bioRxiv2024

Ex-vivo mouse precision cut tumour slices for modelling hepatocellular carcinoma; A 3Rs solution for at-scale drug screening

Disease modelling is vital for improving knowledge of disease mechanisms and for development of new therapeutic molecules and strategies. Modelling the intact living tumour microenvironment (TME) is increasingly considered to be vital not only for gaining a better understanding of the biology of cancer but for examining the efficacy of novel oncology drugs. To date, pre-clinical mouse models of cancer have represented the mainstay methodology for studying the evolving TME and for determining the effects of potential therapeutic molecules on tumour evolution and growth. Regarding drug screening, in vivo mouse models are expensive, require the use of large cohorts of mice and involve the administration of drugs with unknown toxicities to animals which often result in adverse effects that can cause animal suffering and the discontinuation of drug investigations. Hepatocellular carcinoma (HCC) is a primary cancer of the liver for which there is an urgent need for improved systemic treatments due to the disease usually being diagnosed at an advanced stage and current treatments having limited efficacy. To provide a practical solution to the screening of drugs for their likely efficacy in HCC we have developed an ex-vivo model in which orthotopic tumours are excised from the liver and subsequently processed to generate precision-cut tumour slices (PCTS) which provide an intact culture model of the HCC-TME. We describe simplified culture conditions that maintain the viability and metabolic activity of live PCTS which maintain the architecture, cellular complexity, drug sensitivity and responsiveness to immunotherapy of the original tumour. Importantly, we show that HCC derived PCTS can be miniaturised to 96-well scale and modified to express soluble luciferase, which in combination enabled non-destructive screening of a library of 26 drugs at two doses using just 5 tumours as the source for PCTS. This screen identified two small molecules, salinomycin and rottlerin, that have potent anti-tumour activities in HCC-PCTS and subsequently validated salinomycin as effective in vivo. In summary, we report a 3Rs (reduction, refinement and replacement) solution for study of HCC biology and for 96-well-scale screening of potential therapeutic agents in the context of an intact, metabolically active TME.

cancer biology↗

bioRxiv2024

A novel channel invariant architecture for the segmentation of cells and nuclei in multiplexed images using InstanSeg

The quantitative analysis of bioimaging data increasingly depends on the accurate segmentation of cells and nuclei, a significant challenge for the analysis of high-plex imaging data. Current deep learning-based approaches to segment cells in multiplexed images require reducing the input to a small and fixed number of input channels, discarding imaging information in the process. We present Channel Net, a novel deep learning architecture for generating three-channel representations of multiplexed images irrespective of the number or ordering of imaged biomarkers. When combined with InstanSeg, ChannelNet sets a new benchmark for the segmentation of cells and nuclei on public multiplexed imaging datasets. We provide an open implementation of our method and integrate it in open source software. Our code and models are available on https://github.com/instanseg/instanseg.

bioinformatics↗

bioRxiv2024

Distinct tissue-niche localization and function of synovial tissue myeloid DC subsets in health, and in active and remission Rheumatoid Arthritis

Current rheumatoid arthritis (RA) treatments do not restore immune tolerance. Investigating dendritic cell (DC) populations in human synovial tissue (ST) may reveal pathways to re-instate tolerance in RA. With single-cell and spatial-transcriptomics of synovial tissue biopsies, validated by micro co-culture systems, we identified condition and niche-specific myeloid DC clusters with distinct differentiation trajectories and functions. Healthy synovium contains a unique tolerogenic AXLpos DC2 cluster in the superficial sublining layer. In active RA, a macrophage-rich lining-layer niche becomes populated with inflammatory DC3 clusters that specifically activate memory CCL5pos TEM and CCL5posCXCL13pos TPH, promoting synovitis. In the sublining lymphoid niche, CCR7pos DC2 mReg specifically interact with naive-T-cells, potentially driving the local expansion of new effector T-cells. Sustained remission sees the resolution of these niches but lacks the recovery of tolerogenic AXLpos DC2, indicating latent potential for disease flare. A human RA disease-flare model showed that the activation of blood predecessor of ST-DC3 clusters precedes the onset of inflammation in joints. Therapeutic strategies targeting pathogenic ST-DC3 clusters, or reinstating tolerogenic AXLpos DC2, may restore immune homeostasis in RA. In briefDeconstruction of human RA synovium, using single-cell spatial transcriptomics and micro-culture systems, reveals distinct neighbourhoods within the synovial architecture across health, and RA patients with active disease or sustained remission. Discrete niches are identified that contain distinct myeloid DC clusters that differ in frequency, differentiation trajectories, and effector functions. HighlightsO_LIHuman RA synovium exhibits condition and niche specific myeloid DC clusters that vary in their tissue differentiation trajectories and functions. C_LIO_LIST-CD14pos DC3 (iDC3) support inflammatory CCL5pos TEM and CCL5pos TPH cell activation in the hyperplastic lining layer. C_LIO_LIST-CCR7pos DC2 (mReg), driven by MIR155, interact with naive-T-cells in sublining lymphoid niches. C_LIO_LIA specific inflammatory signature of blood predecessors of ST-DC3s predict flare in RA. C_LI Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=199 HEIGHT=200 SRC="FIGDIR/small/600758v1_ufig1.gif" ALT="Figure 1"> View larger version (74K): org.highwire.dtl.DTLVardef@27ab01org.highwire.dtl.DTLVardef@4be238org.highwire.dtl.DTLVardef@1f10734org.highwire.dtl.DTLVardef@1102056_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

bioRxiv2023

Integrated histopathology, spatial and single cell transcriptomics resolve cellular drivers of early and late alveolar damage in COVID-19

The most common cause of death due to COVID-19 remains respiratory failure. Yet, our understanding of the precise cellular and molecular changes underlying lung alveolar damage is limited. Here, we integrate single cell transcriptomic data of COVID-19 donor lungs with spatial transcriptomic data stratifying histopathological stages of diffuse alveolar damage (DAD). We identify changes in cellular composition across progressive DAD, including waves of molecularly distinct macrophages and depleted epithelial and endothelial populations throughout different types of tissue damage. Predicted markers of pathological states identify immunoregulatory signatures, including IFN-alpha and metallothionein signatures in early DAD, and fibrosis-related collagens in organised DAD. Furthermore, we predict a fibrinolytic shutdown via endothelial upregulation of SERPINE1/PAI-1. Cell-cell interaction analysis revealed macrophage-derived SPP1/osteopontin signalling as a key regulator during early DAD. These results provide the first comprehensive, spatially resolved atlas of DAD stages, highlighting the cellular mechanisms underlying pro-inflammatory and pro-fibrotic pathways across alveolar damage progression.

pathology↗

bioRxiv2023

A stagewise response to mitochondrial dysfunction in mitochondrial DNA maintenance disorders

Mitochondrial DNA deletions clonally expand in skeletal muscle of patients with mtDNA maintenance disorders, impairing mitochondrial oxidative phosphorylation dysfunction. Previously we have shown that these mtDNA deletions originally arise and accumulate in the perinuclear mitochondria causing localised mitochondrial dysfunction before spreading through the muscle fibre. We believe that mito-nuclear signalling is a key contributor in this process. To further understand the role of mito-nuclear signalling, we use imaging mass cytometry to characterise the levels of mitochondrial respiratory complexes I-IV and ATP synthase alongside a mitochondrial mass marker, in a cohort of patients with mtDNA maintenance dosirders. We then expanded this panel to include protein markers of key signalling pathways to investigate the cellular response in fibres with different combinations of oxidative phosphorylation dysfunction and in ragged red fibres. We find CI and CIV deficiency to be most common, with a smaller proportion of cells that are also CIII and/or CV deficient. Interestingly, we also note that in cells deficient for one or more complexes, any complexes which are not deficient are commonly upregulated beyond the increase of mitochondrial mass typically observed in ragged red fibres. We further find that oxidative phosphorylation deficient fibres exhibit an increase in abundance of proteins involved in the proteostasis e.g. HSP60 and LONP1, and mitochondrial protein synthesis e.g. PHB1. Our analysis suggests that the cellular response to mitochondrial dysfunction changes depending on the combination of deficient oxidative phosphorylation complexes in each cell.

cell biology↗

bioRxiv2023

A human prenatal skin cell atlas reveals immune cell regulation of skin morphogenesis

Human prenatal skin is populated by innate immune cells including macrophages, and whether they act solely in immunity or have additional functions in morphogenesis is unclear. We assembled the first comprehensive multi-omic reference atlas of prenatal human skin (7-16 post-conception weeks), combining single cell and spatial transcriptomic data, to characterise the skins microenvironmental cellular organisation. This revealed that crosstalk between non-immune and immune cells underpins formation of hair follicles, has implications for scarless wound healing, and is critical for skin angiogenesis. We benchmarked a skin organoid model, derived from human embryonic stem (ES) and induced pluripotent stem (iPS) cells, against prenatal and adult skin, demonstrating close recapitulation of the epidermal and dermal skin components during hair follicle development. Notably, the skin organoid lacked immune cells and had markedly diminished endothelial cell heterogeneity and quantity. From our in vivo skin cell atlas data, we found that macrophages and macrophage-derived growth factors play a key role in driving endothelial development prenatally. Indeed, vascular network formation was enhanced following transfer of autologous iPS-derived macrophages into both endothelial cell angiogenesis assays and skin organoid cultures. In summary, innate immune cells moonlight as key players in skin morphogenesis beyond their conventional immune roles, a function they achieve via extensive crosstalk with non-immune cells. Finally, we leveraged our human prenatal skin cell atlas to further our understanding of the pathogenesis of genetic hair and skin disorders.

developmental biology↗

bioRxiv2023

OPTIMAL: An OPTimsed Imaging Mass cytometry AnaLysis framework for Segmentation and Data Exploration

Analysis of Imaging Mass Cytometry (IMC) data and other low-resolution multiplexed tissue imaging technologies is often confounded by poor single cell segmentation and sub-optimal approaches for data visualisation and exploration. This can lead to inaccurate identification of cell phenotypes, states or spatial relationships compared to reference data from single cell suspension technologies. To this end we have developed the "OPTIMAL" framework to benchmark any approaches for cell segmentation, parameter transformation, batch effect correction, data visualisation/clustering and spatial neighbourhood analysis. Using a panel of 27 metal-tagged antibodies recognising well characterised phenotypic and functional markers to stain the same FFPE human tonsil sample Tissue Microarray (TMA) over 12 temporally distinct batches we tested several cell segmentation models, a range of different arcsinh cofactor parameter transformation values, five different dimensionality reduction algorithms and two clustering methods. Finally we assessed the optimal approach for performing neighbourhood analysis. We found that single cell segmentation was improved by the use of an Ilastik-derived probability map but that issues with poor segmentation were only really evident after clustering and cell type/state identification and not always evident when using "classical" bi-variate data display techniques. The optimal arcsinh cofactor for parameter transformation was 1 as it maximised the statistical separation between negative and positive signal distributions and a simple Z-score normalisation step after arcsinh transformation eliminated batch effects. Of the five different dimensionality reduction approaches tested, PacMap gave the best data structure with FLOWSOM clustering out-performing Phenograph in terms of cell type identification. We also found that neighbourhood analysis was influenced by the method used for finding neighbouring cells with a "disc" pixel expansion outperforming a "bounding box" approach combined with the need for filtering objects based on size and image-edge location. Importantly OPTIMAL can be used to assess and integrate with any existing approach to IMC data analysis and, as it creates .FCS files from the segmentation output, allows for single cell exploration to be conducted using a wide variety of accessible software and algorithms familiar to conventional flow cytometrists.

bioinformatics↗

bioRxiv2022

GBMdeconvoluteR accurately infers proportions of neoplastic and immune cell populations from bulk glioblastoma transcriptomics data

The biological and clinical impact of neoplastic and immune cell type ratios in the glioblastoma (GBM) tumour microenvironment is being realised. Characterising and quantifying cell types within GBMs at scale will facilitate a better understanding of the association between the cellular landscape and tumour phenotypes or clinical correlates. This study aimed to develop a tool that can deconvolute immune and neoplastic cells within the GBM tumour microenvironment from bulk RNA sequencing data. We developed an IDH wild-type (IDHwt) GBM specific single immune cell reference dataset, from four independent studies, consisting of B cells, T cells, NK cells, microglia, tumour associated macrophages, monocytes, mast and DC cells. We used this alongside an existing neoplastic single cell-type dataset consisting of astrocyte-like, oligodendrocyte- and neuronal-progenitor like and mesenchymal GBM cancer cells to create both marker and gene signature matrix-based deconvolution tools. We then applied single-cell resolution imaging mass cytometry (IMC) to ten IDHwt GBM samples, five paired primary and recurrent tumours, in parallel with these tools to determine which performed best. Marker based gene expression deconvolution using GBM tissue specific markers, which we have packaged as GBMdeconvoluteR, gave the most accurate results. The correlation between immune cell quantification by IMC and by GBMdeconvoluteR for primary IDHwt GBM samples was 0.52 (Pearsons P=7.8x10-3) and between neoplastic cell quantification by IMC and by GBMdeconvoluteR was 0.75 (Pearsons P=1.2x10-3). We applied GBMdeconvoluteR to bulk GBM RNAseq data from The Cancer Genome Atlas (TCGA) and were able to recapitulate recent findings from multi-omics single cell studies with regards associations between mesenchymal GBM cancer cells and both lymphoid and myeloid cells. Furthermore, we were able to expand upon this to show that these associations are stronger in patients with worse prognosis. GBMdeconvoluteR is accessible online at https://gbmdeconvoluter.leeds.ac.uk. Key pointsGBMdeconvoluteR is a glioblastoma-specific cellular deconvolution tool. When applied to bulk GBM RNAseq data, it accurately quantifies the neoplastic and immune cells in that tumour. It is available online at https://gbmdeconvoluter.leeds.ac.uk

cancer biology↗

bioRxiv2022

A scalable, reproducible and open-source pipeline for morphologically profiling image cytometry data

Due to high resolution and throughput of modern image cytometry platforms, morphologically profiling generated datasets poses a significant computational challenge. Here, we present Scalable Cytometry Image Processing (SCIP), an image processing software aimed at running on distributed high performance computing infrastructure. SCIP is scalable, flexible, open-source and enables reproducible image processing. It performs projection, illumination correction, segmentation, background masking and extensive morphological profiling on various imaging types. We showcase SCIPs capabilities on three large-scale image cytometry datasets. First, we process an imaging flow cytometry (IFC) dataset of human white blood cells and show how the obtained features are used to classify cells into 8 cell types based on bright- and darkfield imagery. Secondly, we process an automated microscopy dataset of human white blood cells to divide them into cell types in an unsupervised manner. Finally, a high-content screening dataset of breast cancer cells is processed to predict the mechanism-of-action of a large set of compound treatments. The software can be installed from the PyPi repository. Its source code is available at https://github.com/ScalableCytometryImageProcessing/SCIP under the GNU General Public License version 3. It has been tested on Unix operating systems. Issues with the software can be submitted at https://github.com/ScalableCytometryImageProcessing/SCIP/issues. 1 Author SummaryCytometry is a field of biology that studies cells by measuring their characteristics. In image cytometry, this is done by acquiring images of cells. In order to gain biological insight from a set of images, an extensive amount of measurements are derived from them describing the cells they contain. These measurements include, for instance, a cells area, diameter, or the average brightness of the cell image. These measurements can then be analyzed using automated software tools to understand, for example, how cells respond to drug treatments, or how cells differ between a healthy and a diseased person. In this work, we present a novel software tool that is able to efficiently compute image measurements on large datasets of images. We do this by harnessing the power of high performance computing infrastructure. By enabling image cytometry researchers to make use of more computational power, they can more efficiently process complex and large datasets, paving the way to novel, fascinating biological discoveries.

bioinformatics↗

bioRxiv2022

Programmed cell death-1 receptor mediated regulation of Tbet+ NK1.1- Innate Lymphoid Cells within the Tumor Microenvironment

Innate Lymphoid Cells (ILCs) play a key role in tissue mediated immunity and can be controlled by co-receptor signaling. Here we define a subset of ILCs that are Tbet+NK1.1- and are present within the tumor microenvironment (TME). We show programmed death-1 receptor (PD-1) expression on ILCs within TME is found in Tbet+NK1.1-ILCs. PD-1 significantly controlled the proliferation and function of Tbet+NK1.1-ILCs in multiple murine and human tumors. We found tumor derived lactate enhanced PD-1 expression on Tbet+NK1.1-ILCs within the TME, which resulted in dampened mTOR signaling along with increased fatty acid uptake. In line with these metabolic changes, PD-1 deficient Tbet+NK1.1-ILCs expressed significantly increased IFN{gamma}, granzyme B and K. Furthermore, PD1 deficient Tbet+NK1.1- ILCs contributed towards diminished tumor growth in an experimental murine model of melanoma. These data demonstrate that PD-1 can regulate anti-tumor responses of Tbet+NK1.1-ILCs within the tumor microenvironment. HighlightsO_LITbet+NK1.1- ILCs are found in WT and PD1 ko mice C_LIO_LIPD-1 is expressed on Tbet+NK1.1- ILC1s within multiple TME C_LIO_LIPD-1 controls the proliferation and function of Tbet+NK1.1- ILCs within the tumor microenvironment by modulating fatty acid metabolism. C_LIO_LIPD-1 regulates the proliferation of human Tbet+ ILC1s in human cutaneous squamous cell carcinoma (cSCC) and melanoma tumor microenvironment. C_LI

immunology↗

bioRxiv2022

CXCR2 inhibition enables NASH-HCC immunotherapy

ObjectiveHepatocellular carcinoma (HCC) is increasingly associated with non-alcoholic steatohepatitis (NASH). HCC immunotherapy offers great promise; however, recent data suggests NASH-HCC may be less sensitive to conventional immune checkpoint inhibition (ICI). We hypothesised that targeting neutrophils using a CXCR2 small molecule inhibitor may sensitise NASH-HCC to ICI therapy. DesignNeutrophil infiltration was characterised in human HCC and mouse models of HCC. Late-stage intervention with anti-PD1 and/or a CXCR2 inhibitor was performed in murine models of NASH-HCC. The tumour immune microenvironment was characterised by imaging mass cytometry, RNA-seq and flow cytometry. ResultsNeutrophils expressing CXCR2, a receptor crucial to neutrophil recruitment in acute-injury, are highly represented in human NASH-HCC. In models of NASH-HCC lacking response to ICI, the combination of a CXCR2 antagonist with anti-PD1 suppressed tumour burden and extended survival. Combination therapy increased intratumoral XCR1+ dendritic cell activation and CD8+ T cell numbers which are associated with anti-tumoral immunity, this was confirmed by loss of therapeutic effect upon genetic impairment of myeloid cell recruitment, neutralisation of the XCR1-ligand XCL1 or depletion of CD8+ T cells. Therapeutic benefit was accompanied by an unexpected increase in tumour-associated neutrophils (TANs) which switched from a pro-tumor to anti-tumour progenitor-like neutrophil phenotype. Reprogrammed TANs were found in direct contact with CD8+ T cells in clusters that were enriched for the cytotoxic anti-tumoural protease granzyme B. Neutrophil reprogramming was not observed in the circulation indicative of the combination therapy selectively influencing TANs. ConclusionCXCR2-inhibition induces reprogramming of the tumour immune microenvironment that promotes ICI in NASH-HCC. Significance of this studyWhat is already known on this subject? O_LIImmune checkpoint inhibition therapy is emerging as a promising new therapy for the treatment of advanced hepatocellular carcinoma (HCC). C_LIO_LIOnly a minority of HCC patients will respond to immune checkpoint inhibition (ICI) therapy and recent data suggest that HCC on the background of NASH may have reduced sensitivity to this treatment strategy. C_LIO_LINeutrophils are a typical myeloid component of the liver in NASH and are found either within the HCC tumour microenvironment or in a peritumoural location. C_LIO_LINeutrophils have considerable phenotypic plasticity and can exist in both tumour promoting and tumour suppressing states. C_LIO_LINeutrophils may have the ability to influence ICI therapy. C_LI What are the new findings? O_LICXCR2+ neutrophils are found in human NASH and within the tumour of both human and mouse models of NASH-HCC. C_LIO_LIThe resistance of NASH-HCC to anti-PD1 therapy is overcome by co-treatment with a CXCR2 small molecule inhibitor, with evidence of reduced tumour burden and extended survival. C_LIO_LIAnti-PD1 and CXCR2 inhibitor combine to selectively reprogramme tumour-associated neutrophils (TANs) from a pro- to an anti-tumour phenotype. C_LIO_LIReprogrammed TANs proliferate locally within Granzyme B+ immune clusters that contain physically associating CD8+ T cells and antigen presenting cells. C_LIO_LIConventional XCR1+ dendritic cells (cDC1s) are found to be elevated in anti-PD1 and CXCR2 inhibitor treated HCCs and together with CD8+ T cells are required for therapeutic benefit. C_LI How might it impact on clinical practice in the foreseeable future? O_LITANs can be selectively manipulated to adopt an anti-tumour phenotype which unlocks their potential for cancer therapy. The ability of CXCR2 antagonism to combine with ICI therapy to bring about enhanced therapeutic benefit in NASH-HCC (and potentially in HCC of other aetiologies) warrents clinical investigation. C_LI

cancer biology↗

bioRxiv2021

Intrinsic and extrinsic regulation of human fetal bone marrow haematopoiesis and perturbations in Down syndrome

Throughout postnatal life, haematopoiesis in the bone marrow (BM) maintains blood and immune cell production. Haematopoiesis first emerges in human BM at 12 post conception weeks while fetal liver (FL) haematopoiesis is still expanding. Yet, almost nothing is known about how fetal BM evolves to meet the highly specialised needs of the fetus and newborn infant. Here, we detail the development of fetal BM including stroma using single cell RNA-sequencing. We find that the full blood and immune cell repertoire is established in fetal BM in a short time window of 6-7 weeks early in the second trimester. Fetal BM promotes rapid and extensive diversification of myeloid cells, with granulocytes, eosinophils and dendritic cell (DC) subsets emerging for the first time. B-lymphocyte expansion occurs, in contrast with erythroid predominance in FL at the same gestational age. We identify transcriptional and functional differences that underlie tissue-specific identity and cellular diversification in fetal BM and FL. Finally, we reveal selective disruption of B-lymphocyte, erythroid and myeloid development due to cell intrinsic differentiation bias as well as extrinsic regulation through an altered microenvironment in the fetal BM from constitutional chromosome anomaly Down syndrome during this crucial developmental time window.

developmental biology↗

bioRxiv2021

A human iPSC derived bone marrow milieu identifies a novel target against niche-conferred leukaemia proliferation and treatment resistance

Leukaemia cells re-program their microenvironment to provide proliferation support and protection from standard chemotherapy, molecularly targeted therapies, and immunotherapy. Although much is becoming known about molecules that drive niche-dependent treatment resistance; means of targeting these in the clinics has remained a key obstacle. To address this challenge, we have developed human induced pluripotent stem cell engineered niches ex vivo to reveal insights into druggable cancer-niche dependencies. We show that mesenchymal (iMSC) and vascular niche-like (iANG) cells support ex vivo proliferation of patient-derived leukaemia cells, impact dormancy and mediate therapy resistance. iMSC protected both non-cycling and cycling blasts against dexamethasone treatment while iANG protected only dormant blasts. Leukaemia proliferation and protection from dexamethasone induced-apoptosis was dependent on direct cell-cell contact and mediated by CDH2. To explore the therapeutic potential of disrupting this cell-cell interaction, we tested the CDH2 antagonist ADH-1 (previously in phase I / II for solid tumours) in a very aggressive patient-derived xenograft leukaemia mouse model. ADH-1 showed high in vivo efficacy. ADH-1/ dexamethasone combination therapy was superior to dexamethasone alone with no ADH1 conferred additional toxicity. These findings provide a proof-of-concept starting point to develop novel, potentially safer therapeutics that target niche-mediated cancer cell dependencies in haematological malignancies. SummaryCDH2 mediated niche-dependent cancer proliferation and treatment resistance is clinically targetable via ADH-1, a low toxic agent that could be potentially repurposed for future clinical trials in acute leukaemia.

cancer biology↗

bioRxiv2021

Inter-laboratory automation of the in vitro micronucleus assay using imaging flow cytometry and deep learning

The in vitro micronucleus assay is a globally significant method for DNA damage quantification used for regulatory compound safety testing in addition to inter-individual monitoring of environmental, lifestyle and occupational factors. However it relies on time-consuming and user-subjective manual scoring. Here we show that imaging flow cytometry and deep learning image classification represents a capable platform for automated, inter-laboratory operation. Images were captured for the cytokinesis-block micronucleus (CBMN) assay across three laboratories using methyl methanesulphonate (1.25 - 5.0 {micro}g/mL) and/or carbendazim (0.8 - 1.6 {micro}g/mL) exposures to TK6 cells. Human-scored image sets were assembled and used to train and test the classification abilities of the "DeepFlow" neural network in both intra- and inter-laboratory contexts. Harnessing image diversity across laboratories yielded a network able to score unseen data from an entirely new laboratory without any user configuration. Image classification accuracies of 98%, 95%, 82% and 85% were achieved for mononucleates, binucleates, mononucleates with MN and binucleates with MN, respectively. Successful classifications of trinucleates (90%) and tetranucleates (88%) in addition to other or unscorable phenotypes (96%) were also achieved. Attempts to classify extremely rare, tri- and tetranucleated cells with micronuclei into their own categories were less successful ([≤] 57%). Benchmark dose analyses of human or automatically scored micronucleus frequency data yielded quantitation of the same equipotent dose regardless of scoring method. We conclude that this automated approach offers significant potential to broaden the practical utility of the CBMN method across industry, research and clinical domains. We share our strategy using openly-accessible frameworks.

pharmacology and toxicology↗

bioRxiv2020

Poised cell circuits in human skin are activated in disease

The human skin confers biophysical and immunological protection through a complex cellular network that is established early in development. We profiled ~500,000 single cells using RNA-sequencing from healthy adult and developing skin, and skin from patients with atopic dermatitis and psoriasis. Our findings reveal a predominance of innate lymphoid cells and macrophages in developing skin in contrast to T cells and migratory dendritic cells in adult skin. We demonstrate dual keratinocyte differentiation trajectories and activated cellular circuits comprising vascular endothelial cells mediating immune cell trafficking, disease-specific clonally expanded IL13/IL22 and IL17A/F-expressing lymphocytes, epidermal IL23-expressing dendritic cells and inflammatory keratinocytes in disease. Our findings provide key insights into the dynamic cellular landscape of human skin in health and disease. One Sentence SummarySingle cell atlas of human skin reveals cell circuits which are quantitatively and qualitatively reconfigured in inflammatory skin disease.

immunology↗

bioRxiv2020

A cell atlas of human thymic development defines T cell repertoire formation

The thymus provides a nurturing environment for the differentiation and selection of T cells, a process orchestrated by their interaction with multiple thymic cell types. We utilised single-cell RNA-sequencing (scRNA-seq) to create a cell census of the human thymus and to reconstruct T-cell differentiation trajectories and T-cell receptor (TCR) recombination kinetics. Using this approach, we identified and located in situ novel CD8+ T-cell populations, thymic fibroblast subtypes and activated dendritic cell (aDC) states. In addition, we reveal a bias in TCR recombination and selection, which is attributed to genomic position and suggests later commitment of the CD8+ T-cell lineage. Taken together, our data provide a comprehensive atlas of the human thymus across the lifespan with new insights into human T-cell development.

immunology↗