Single-cell multi-omics analysis of the immune response in COVID-19

Analysis of human blood immune cells provides insights into the coordinated response to viral infections such as severe acute respiratory syndrome coronavirus 2, which causes coronavirus disease 2019 (COVID-19). We performed single-cell transcriptome, surface proteome and T and B lymphocyte antigen receptor analyses of over 780,000 peripheral blood mononuclear cells from a cross-sectional cohort of 130 patients with varying severities of COVID-19. We identified expansion of nonclassical monocytes expressing complement transcripts (CD16+C1QA/B/C+) that sequester platelets and were predicted to replenish the alveolar macrophage pool in COVID-19. Early, uncommitted CD34+ hematopoietic stem/progenitor cells were primed toward megakaryopoiesis, accompanied by expanded megakaryocyte-committed progenitors and increased platelet activation. Clonally expanded CD8+ T cells and an increased ratio of CD8+ effector T cells to effector memory T cells characterized severe disease, while circulating follicular helper T cells accompanied mild disease. We observed a relative loss of IgA2 in symptomatic disease despite an overall expansion of plasmablasts and plasma cells. Our study highlights the coordinated immune response that contributes to COVID-19 pathogenesis and reveals discrete cellular components that can be targeted for therapy

Single-cell multi-omics analysis of the immune response in COVID-19

Peer reviewedPublisher PD

Biologically Interpretable, Integrative Deep Learning for Cancer Survival Analysis

Identifying complex biological processes associated to patients\u27 survival time at the cellular and molecular level is critical not only for developing new treatments for patients but also for accurate survival prediction. However, highly nonlinear and high-dimension, low-sample size (HDLSS) data cause computational challenges in survival analysis. We developed a novel family of pathway-based, sparse deep neural networks (PASNet) for cancer survival analysis. PASNet family is a biologically interpretable neural network model where nodes in the network correspond to specific genes and pathways, while capturing nonlinear and hierarchical effects of biological pathways associated with certain clinical outcomes. Furthermore, integration of heterogeneous types of biological data from biospecimen holds promise of improving survival prediction and personalized therapies in cancer. Specifically, the integration of genomic data and histopathological images enhances survival predictions and personalized treatments in cancer study, while providing an in-depth understanding of genetic mechanisms and phenotypic patterns of cancer. Two proposed models will be introduced for integrating multi-omics data and pathological images, respectively. Each model in PASNet family was evaluated by comparing the performance of current cutting-edge models with The Cancer Genome Atlas (TCGA) cancer data. In the extensive experiments, PASNet family outperformed the benchmarking methods, and the outstanding performance was statistically assessed. More importantly, PASNet family showed the capability to interpret a multi-layered biological system. A number of biological literature in GBM supported the biological interpretation of the proposed models. The open-source software of PASNet family in PyTorch is publicly available at https://github.com/DataX-JieHao

Investigating the impact of JAK inhibitor tofacitinib on the CD4+ T cell-dendritic cell interactions in murine models of rheumatoid arthritis

Rheumatoid arthritis (RA) is a chronic autoimmune condition manifested by synovial inflammation and joint destruction and is associated with high morbidity and mortality. While the existing biologic therapies revolutionised the management of RA, considerable unmet needs in disease management require the development of new therapeutic agents. Janus kinases (JAKs) are intracellular tyrosine kinases employed by Type I and Type II cytokine receptors and transducing the signals from a range of cytokines and growth factors. They are indispensable in mediating the signaling of inflammatory cytokines implicated in the pathogenesis of autoimmune conditions, thus present attractive targets for therapeutic intervention. Tofacitinib was the first JAK inhibitor approved for the treatment of RA, which was effective in patients refractory to existing treatments. Among its immunomodulatory mechanisms, tofacitinib was reported to impair the proliferation, differentiation, and pro-inflammatory cytokine production in CD4+ T cells, both in vitro and in vivo. However, the impact of tofacitinib as well as the stage of the drug interference (priming or re-activation) on cognate CD4+ T cell-dendritic cell (DC) interaction, which underlies both breakdown of self-tolerance and autoimmune response propagation in RA, remains to be elucidated. Using the antigen-specific cell system both in vitro and in vivo, I have shown that tofacitinib treatment impaired the priming of the CD4+ T cells by DCs, resulting in their diminished ability to differentiate into T helper 1 (Th1) subset and exhibit associated T-bet expression and IFNy production. This effect on CD4+ T cells was observed both in vitro and in vivo and persisted upon secondary antigenic challenge. On the contrary, the antigen-experienced CD4+ T cells primed in the absence of tofacitinib retained their functional capacity upon re-activation in the presence of the drug. Tofacitinib efficacy assessment in the mouse model of early RA similarly revealed that the antigen-experienced CD4+ T lymphocytes, from both adoptively transferred and endogenous populations, remained unaffected by tofacitinib treatment. While JAK inhibitor had no impact on paw thickness, it induced notable (although non-significant) improvement in features of joint pathology, which, together with the absence of effect on CD4+ T lymphocytes, suggested tofacitinib targeting other inflammatory cells contributing to the autoimmune response. Overall, these results have shown that tofacitinib interferes with the naive CD4+ T cell differentiation into the Th1 subset, thereby indicating a mechanism by which tofacitinib might in part achieve clinical efficacy in RA patients. The antigen-specific system and early RA mouse model are warranted as useful platforms for further investigation of tofacitinib immunomodulatory mechanisms with the view of the optimization of its clinical use

Single-cell multi-omics analysis of the immune response in COVID-19

Funder: Lister Institute of Preventive Medicine; doi: https://doi.org/10.13039/501100001255Funder: University College London, Birkbeck MRC Doctoral Training ProgrammeFunder: The Jikei University School of MedicineFunder: Action Medical Research (GN2779)Funder: NIHR Clinical Lectureship (CL-2017-01-004)Funder: NIHR (ACF-2018-01-004) and the BMA FoundationFunder: Chan Zuckerberg Initiative (grant 2017-174169) and from Wellcome (WT211276/Z/18/Z and Sanger core grant WT206194)Funder: UKRI Innovation/Rutherford Fund Fellowship allocated by the MRC and the UK Regenerative Medicine Platform (MR/5005579/1 to M.Z.N.). M.Z.N. and K.B.M. have been funded by the Rosetrees Trust (M944)Funder: Barbour FoundationFunder: ERC Consolidator and EU MRG-Grammar awardsFunder: Versus Arthritis Cure Challenge Research Grant (21777), and an NIHR Research Professorship (RP-2017-08-ST2-002)Funder: European Molecular Biology Laboratory (EMBL)Abstract: Analysis of human blood immune cells provides insights into the coordinated response to viral infections such as severe acute respiratory syndrome coronavirus 2, which causes coronavirus disease 2019 (COVID-19). We performed single-cell transcriptome, surface proteome and T and B lymphocyte antigen receptor analyses of over 780,000 peripheral blood mononuclear cells from a cross-sectional cohort of 130 patients with varying severities of COVID-19. We identified expansion of nonclassical monocytes expressing complement transcripts (CD16+C1QA/B/C+) that sequester platelets and were predicted to replenish the alveolar macrophage pool in COVID-19. Early, uncommitted CD34+ hematopoietic stem/progenitor cells were primed toward megakaryopoiesis, accompanied by expanded megakaryocyte-committed progenitors and increased platelet activation. Clonally expanded CD8+ T cells and an increased ratio of CD8+ effector T cells to effector memory T cells characterized severe disease, while circulating follicular helper T cells accompanied mild disease. We observed a relative loss of IgA2 in symptomatic disease despite an overall expansion of plasmablasts and plasma cells. Our study highlights the coordinated immune response that contributes to COVID-19 pathogenesis and reveals discrete cellular components that can be targeted for therapy

Dysregulated Notch signaling in breast cancer and liver disease

The evolutionarily conserved Notch signaling pathway regulates crucial aspects of development and tissue homeostasis. This thesis contributes research towards understanding a role of non-canonical Notch signaling in the tumor-stroma interaction of breast cancer, provides a bioinformatics-based technology to study these interactions, and proposes a novel mouse model of the liver disease in Alagille syndrome. In Paper I, we report a novel target for non-canonical Notch signaling in breast cancer, the cytokine IL-6. In human breast cancer cell lines, we observe increased IL-6 mRNA and protein levels when Notch signaling is amplified, in turn activating the JAK/STAT pathway in a p53-dependent, but CSL-independent fashion, via IKKα and IKKβ of the NF-κB pathway. These data add a new facet to the existing body of knowledge on hyperactivated Notch signaling in promoting inflammation in breast tumors. In Paper II, we present and validate a new bioinformatics-based approach of species-specific sequencing (S3). Using an intermixed human tumor and mouse stroma cell population from xenografted cells, we demonstrate a way to decode transcriptomes, separated by their species-specific differences, with 99% accuracy. This technique circumvents current problems in mechanically separating mixed tissue, and paves the way to efficiently analyze in vivo cell-cell interactions. In Paper III, we characterize a mouse strain, with a missense mutation in the Jagged1 gene, as a potential model for the rare genetic disorder Alagille syndrome. We show that this model recapitulates pathologies in the liver, heart, lens and kidney observed in Alagille patients, and identify dysregulated biliary morphogenesis caused by this mutation. We also use the S3 technology, developed in Paper II, to investigate signaling specifically in receptor-expressing cells by wild type and mutated Jagged1. In summary, the work presented in this thesis sheds new light on the role of Notch signaling in breast cancer and liver disease, and provides a novel technology to facilitate the detailed study of cell-cell interactions

Engineering Stem Cell Responses with Two-Dimensional Nanomaterials

Two-dimensional (2D) nanomaterials are an emerging class of biomaterials that have garnered unprecedented attention due to their unique atomically thin, layered, and well-defined structure. These nanomaterials, however, have limited investigations into their cytocompatibility and potential use in regenerative medicine particularly from the perspective of 3D scaffolds. Here we report two chemically unique 2D nanomaterials and their biophysical and biochemical interactions with stem cells. The first is a naturally occurring nanosilicate which is made up of a unique combination of minerals (Na^+, L^i+, Mg^2+, Si(OH)v4) within an octahedral sheet sandwiched between two tetrahedral lattices (Laponite XLG®). The second is a transition metal dichalcogenide (TMD) of molybdenum disulfide (MoSv2) which forms 2D sheets nanometers in thickness. Using molecular biology techniques that capture a holistic snapshot of cell signaling, like RNA-sequencing (RNA-seq), we can begin to examine mechanisms behind changes in behavior. With this information, we can then interrogate specific pathways of interest to generate a desired cell response. Furthermore, we can incorporate these nanomaterials into polymeric scaffolds to localize both cells and bioactive materials for delivery in vivo. Specifically, we utilized formulations of the polysaccharide kappa-Carrageenan with the nanosilicates and a thiol-modified 4-arm polyethylene glycol (PEG) with 2D MoSv2. Using these studies as a framework, researchers can begin to tailor new polymeric scaffolds around emergent 2D nanomaterials for a variety of regenerative applications including bioprinting