Anatomy and Neuroscience - Research Publications

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    Assessing and enhancing migration of human myogenic progenitors using directed iPS cell differentiation and advanced tissue modelling
    Choi, S ; Ferrari, G ; Moyle, LA ; Mackinlay, K ; Naouar, N ; Jalal, S ; Benedetti, S ; Wells, C ; Muntoni, F ; Tedesco, FS (WILEY, 2022-10-10)
    Muscle satellite stem cells (MuSCs) are responsible for skeletal muscle growth and regeneration. Despite their differentiation potential, human MuSCs have limited in vitro expansion and in vivo migration capacity, limiting their use in cell therapies for diseases affecting multiple skeletal muscles. Several protocols have been developed to derive MuSC-like progenitors from human induced pluripotent stem (iPS) cells (hiPSCs) to establish a source of myogenic cells with controllable proliferation and differentiation. However, current hiPSC myogenic derivatives also suffer from limitations of cell migration, ultimately delaying their clinical translation. Here we use a multi-disciplinary approach including bioinformatics and tissue engineering to show that DLL4 and PDGF-BB improve migration of hiPSC-derived myogenic progenitors. Transcriptomic analyses demonstrate that this property is conserved across species and multiple hiPSC lines, consistent with results from single cell motility profiling. Treated cells showed enhanced trans-endothelial migration in transwell assays. Finally, increased motility was detected in a novel humanised assay to study cell migration using 3D artificial muscles, harnessing advanced tissue modelling to move hiPSCs closer to future muscle gene and cell therapies.
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    Author Correction: Discovery of widespread transcription initiation at microsatellites predictable by sequence-based deep neural network.
    Grapotte, M ; Saraswat, M ; Bessière, C ; Menichelli, C ; Ramilowski, JA ; Severin, J ; Hayashizaki, Y ; Itoh, M ; Tagami, M ; Murata, M ; Kojima-Ishiyama, M ; Noma, S ; Noguchi, S ; Kasukawa, T ; Hasegawa, A ; Suzuki, H ; Nishiyori-Sueki, H ; Frith, MC ; FANTOM consortium, ; Chatelain, C ; Carninci, P ; de Hoon, MJL ; Wasserman, WW ; Bréhélin, L ; Lecellier, C-H (Springer Science and Business Media LLC, 2022-03-01)
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    Discovery of widespread transcription initiation at microsatellites predictable by sequence-based deep neural network.
    Grapotte, M ; Saraswat, M ; Bessière, C ; Menichelli, C ; Ramilowski, JA ; Severin, J ; Hayashizaki, Y ; Itoh, M ; Tagami, M ; Murata, M ; Kojima-Ishiyama, M ; Noma, S ; Noguchi, S ; Kasukawa, T ; Hasegawa, A ; Suzuki, H ; Nishiyori-Sueki, H ; Frith, MC ; FANTOM consortium, ; Chatelain, C ; Carninci, P ; de Hoon, MJL ; Wasserman, WW ; Bréhélin, L ; Lecellier, C-H (Springer Science and Business Media LLC, 2021-06-02)
    Using the Cap Analysis of Gene Expression (CAGE) technology, the FANTOM5 consortium provided one of the most comprehensive maps of transcription start sites (TSSs) in several species. Strikingly, ~72% of them could not be assigned to a specific gene and initiate at unconventional regions, outside promoters or enhancers. Here, we probe these unassigned TSSs and show that, in all species studied, a significant fraction of CAGE peaks initiate at microsatellites, also called short tandem repeats (STRs). To confirm this transcription, we develop Cap Trap RNA-seq, a technology which combines cap trapping and long read MinION sequencing. We train sequence-based deep learning models able to predict CAGE signal at STRs with high accuracy. These models unveil the importance of STR surrounding sequences not only to distinguish STR classes, but also to predict the level of transcription initiation. Importantly, genetic variants linked to human diseases are preferentially found at STRs with high transcription initiation level, supporting the biological and clinical relevance of transcription initiation at STRs. Together, our results extend the repertoire of non-coding transcription associated with DNA tandem repeats and complexify STR polymorphism.
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    Defining the Role of Nuclear Factor (NF)-?B p105 Subunit in Human Macrophage by Transcriptomic Analysis of NFKB1 Knockout THP1 Cells
    Somma, D ; Kok, FO ; Kerrigan, D ; Wells, CA ; Carmody, RJ (FRONTIERS MEDIA SA, 2021-10-13)
    Since its discovery over 30 years ago the NF-ĸB family of transcription factors has gained the status of master regulator of the immune response. Much of what we understand of the role of NF-ĸB in immune development, homeostasis and inflammation comes from studies of mice null for specific NF-ĸB subunit encoding genes. The role of inflammation in diseases that affect a majority of individuals with health problems globally further establishes NF-ĸB as an important pathogenic factor. More recently, genomic sequencing has revealed loss of function mutations in the NFKB1 gene as the most common monogenic cause of common variable immunodeficiencies in Europeans. NFKB1 encodes the p105 subunit of NF-ĸB which is processed to generate the NF-ĸB p50 subunit. NFKB1 is the most highly expressed transcription factor in macrophages, key cellular drivers of inflammation and immunity. Although a key role for NFKB1 in the control of the immune system is apparent from Nfkb1-/- mouse studies, we know relatively little of the role of NFKB1 in regulating human macrophage responses. In this study we use the THP1 monocyte cell line and CRISPR/Cas9 gene editing to generate a model of NFKB1-/- human macrophages. Transcriptomic analysis reveals that activated NFKB1-/- macrophages are more pro-inflammatory than wild type controls and express elevated levels of TNF, IL6, and IL1B, but also have reduced expression of co-stimulatory factors important for the activation of T cells and adaptive immune responses such as CD70, CD83 and CD209. NFKB1-/- THP1 macrophages recapitulate key observations in individuals with NFKB1 haploinsufficiency including decreased IL10 expression. These data supporting their utility as an in vitro model for understanding the role of NFKB1 in human monocytes and macrophages and indicate that of loss of function NFKB1 mutations in these cells is an important component in the associated pathology.
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    An integrated analysis of human myeloid cells identifies gaps in in vitro models of in vivo biology
    Rajab, N ; Angel, PW ; Deng, Y ; Gu, J ; Jameson, V ; Kurowska-Stolarska, M ; Milling, S ; Pacheco, CM ; Rutar, M ; Laslett, AL ; Cao, K-AL ; Choi, J ; Wells, CA (CELL PRESS, 2021-06-08)
    The Stemformatics myeloid atlas is an integrated transcriptome atlas of human macrophages and dendritic cells that systematically compares freshly isolated tissue-resident, cultured, and pluripotent stem cell-derived myeloid cells. Three classes of tissue-resident macrophage were identified: Kupffer cells and microglia; monocyte-associated; and tumor-associated macrophages. Culture had a major impact on all primary cell phenotypes. Pluripotent stem cell-derived macrophages were characterized by atypical expression of collagen and a highly efferocytotic phenotype. Myeloid subsets, and phenotypes associated with derivation, were reproducible across experimental series including data projected from single-cell studies, demonstrating that the atlas provides a robust reference for myeloid phenotypes. Implementation in Stemformatics.org allows users to visualize patterns of sample grouping or gene expression for user-selected conditions and supports temporary upload of your own microarray or RNA sequencing samples, including single-cell data, to benchmark against the atlas.
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    Challenges for Computational Stem Cell Biology: A Discussion for the Field
    Rackham, O ; Cahan, P ; Mah, N ; Morris, S ; Ouyang, JF ; Plant, AL ; Tanaka, Y ; Wells, CA (CELL PRESS, 2021-01-12)
    The first meetup for Computational Stem Cell Biologists was held at the 2020 annual meeting of the International Society for Stem Cell Research. The discussions highlighted opportunities and barriers to computational stem cell research that require coordinated action across the stem cell sector.
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    Ten simple rules for navigating the computational aspect of an interdisciplinary PhD
    Islam, S ; Wells, CA ; Schwartz, R (PUBLIC LIBRARY SCIENCE, 2021-02)
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    Stemformatics: visualize and download curated stem cell data
    Choi, J ; Pacheco, CM ; Mosbergen, R ; Korn, O ; Chen, T ; Nagpal, I ; Englart, S ; Angel, PW ; Wells, CA (OXFORD UNIV PRESS, 2019-01-08)
    Stemformatics is an established gene expression data portal containing over 420 public gene expression datasets derived from microarray, RNA sequencing and single cell profiling technologies. Developed for the stem cell community, it has a major focus on pluripotency, tissue stem cells, and staged differentiation. Stemformatics includes curated 'collections' of data relevant to cell reprogramming, as well as hematopoiesis and leukaemia. Rather than simply rehosting datasets as they appear in public repositories, Stemformatics uses a stringent set of quality control metrics and its own pipelines to process handpicked datasets from raw files. This means that about 30% of datasets processed by Stemformatics fail the quality control metrics and never make it to the portal, ensuring that Stemformatics data are of high quality and have been processed in a consistent manner. Stemformatics provides easy-to-use and intuitive tools for biologists to visually explore the data, including interactive gene expression profiles, principal component analysis plots and hierarchical clusters, among others. The addition of tools that facilitate cross-dataset comparisons provides users with snapshots of gene expression in multiple cell and tissues, assisting the identification of cell-type restricted genes, or potential housekeeping genes. Stemformatics is freely available at stemformatics.org.
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    A simple, scalable approach to building a cross-platform transcriptome atlas
    Angel, PW ; Rajab, N ; Deng, Y ; Pacheco, CM ; Chen, T ; Le Cao, K-A ; Choi, J ; Wells, CA ; Fertig, EJ (PUBLIC LIBRARY SCIENCE, 2020-09)
    Gene expression atlases have transformed our understanding of the development, composition and function of human tissues. New technologies promise improved cellular or molecular resolution, and have led to the identification of new cell types, or better defined cell states. But as new technologies emerge, information derived on old platforms becomes obsolete. We demonstrate that it is possible to combine a large number of different profiling experiments summarised from dozens of laboratories and representing hundreds of donors, to create an integrated molecular map of human tissue. As an example, we combine 850 samples from 38 platforms to build an integrated atlas of human blood cells. We achieve robust and unbiased cell type clustering using a variance partitioning method, selecting genes with low platform bias relative to biological variation. Other than an initial rescaling, no other transformation to the primary data is applied through batch correction or renormalisation. Additional data, including single-cell datasets, can be projected for comparison, classification and annotation. The resulting atlas provides a multi-scaled approach to visualise and analyse the relationships between sets of genes and blood cell lineages, including the maturation and activation of leukocytes in vivo and in vitro. In allowing for data integration across hundreds of studies, we address a key reproduciblity challenge which is faced by any new technology. This allows us to draw on the deep phenotypes and functional annotations that accompany traditional profiling methods, and provide important context to the high cellular resolution of single cell profiling. Here, we have implemented the blood atlas in the open access Stemformatics.org platform, drawing on its extensive collection of curated transcriptome data. The method is simple, scalable and amenable for rapid deployment in other biological systems or computational workflows.
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    Pharmacological validation of targets regulating CD14 during macrophage differentiation
    Jimenez-Duran, G ; Luque-Martin, R ; Patel, M ; Koppe, E ; Bernard, S ; Sharp, C ; Buchan, N ; Rea, C ; de Winther, MPJ ; Turan, N ; Angell, D ; Wells, CA ; Cousins, R ; Mander, PK ; Masters, SL (ELSEVIER, 2020-11)
    The signalling receptor for LPS, CD14, is a key marker of, and facilitator for, pro-inflammatory macrophage function. Pro-inflammatory macrophage differentiation remains a process facilitating a broad array of disease pathologies, and has recently emerged as a potential target against cytokine storm in COVID19. Here, we perform a whole-genome CRISPR screen to identify essential nodes regulating CD14 expression in myeloid cells, using the differentiation of THP-1 cells as a starting point. This strategy uncovers many known pathways required for CD14 expression and regulating macrophage differentiation while additionally providing a list of novel targets either promoting or limiting this process. To speed translation of these results, we have then taken the approach of independently validating hits from the screen using well-curated small molecules. In this manner, we identify pharmacologically tractable hits that can either increase CD14 expression on non-differentiated monocytes or prevent CD14 upregulation during macrophage differentiation. An inhibitor for one of these targets, MAP2K3, translates through to studies on primary human monocytes, where it prevents upregulation of CD14 following M-CSF induced differentiation, and pro-inflammatory cytokine production in response to LPS. Therefore, this screening cascade has rapidly identified pharmacologically tractable nodes regulating a critical disease-relevant process.