Chapter 2 Genetics at the Cell Level

Image-based and sequencing-based spatial technologies can currently be used to locate cells anatomically within a tissue; the Human Vell Atlas allows its users to navigate the human body at various levels of resolution to identify patterns and interactions among its fundamental elements, zooming in and out depending on the research goals. Integrating data types or simultaneously measuring multiple modalities is invaluable when defining cell identities

Innate Immune Mechanisms to Protect Against Infection at the Human Decidual-Placental Interface.

During pregnancy, the placenta forms the anatomical barrier between the mother and developing fetus. Infectious agents can potentially breach the placental barrier resulting in pathogenic transmission from mother to fetus. Innate immune responses, orchestrated by maternal and fetal cells at the decidual-placental interface, are the first line of defense to avoid vertical transmission. Here, we outline the anatomy of the human placenta and uterine lining, the decidua, and discuss the potential capacity of pathogen pattern recognition and other host defense strategies present in the innate immune cells at the placental-decidual interface. We consider major congenital infections that access the placenta from hematogenous or decidual route. Finally, we highlight the challenges in studying human placental responses to pathogens and vertical transmission using current experimental models and identify gaps in knowledge that need to be addressed. We further propose novel experimental strategies to address such limitations

Genetic And Epigenetic Determinants In Autoinflammatory Diseases

The concept of autoinflammation has evolved over the past 20 years, beginning with the discovery that mutations in the Mediterranean Fever (MEFV) gene were causative of Familial Mediterranean Fever. Currently, autoinflammatory diseases comprise a wide range of disorders with the common features of recurrent fever attacks, prevalence of hyperreactive innate immune cells, and signs of inflammation that can be systemic or organ specific in the absence of pathogenic infection of autoimmunity. Innate immune cells from the myeloid compartment are the main effectors of uncontrolled inflammation that is caused in great extent by the overproduction of inflammatory cytokines such as IL-1 beta and IL-18. Defects in several signaling pathways that control innate immune defense, particularly the hyperreactivity of one or more inflammasomes, are at the core of pathologic autoinflammatory phenotypes. Although many of the autoinflammatory syndromes are known to be monogenic, some of them are genetically complex and are impacted by environmental factors. Recently, epigenetic dysregulation has surfaced as an additional contributor to pathogenesis. In the present review, we discuss data that are currently available to describe the contribution of epigenetic mechanisms in autoinflammatory diseases

CellPhoneDB v5: inferring cell-cell communication from single-cell multiomics data

Cell-cell communication is essential for tissue development, regeneration and function, and its disruption can lead to diseases and developmental abnormalities. The revolution of single-cell genomics technologies offers unprecedented insights into cellular identities, opening new avenues to resolve the intricate cellular interactions present in tissue niches. CellPhoneDB is a bioinformatics toolkit designed to infer cell-cell communication by combining a curated repository of bona fide ligand-receptor interactions with a set of computational and statistical methods to integrate them with single-cell genomics data. Importantly, CellPhoneDB captures the multimeric nature of molecular complexes, thus representing cell-cell communication biology faithfully. Here we present CellPhoneDB v5, an updated version of the tool, which offers several new features. Firstly, the repository has been expanded by one-third with the addition of new interactions. These encompass interactions mediated by non-protein ligands such as endocrine hormones and GPCR ligands. Secondly, it includes a differentially expression-based methodology for more tailored interaction queries. Thirdly, it incorporates novel computational methods to prioritise specific cell-cell interactions, leveraging other single-cell modalities, such as spatial information or TF activities (i.e. CellSign module). Finally, we provide CellPhoneDBViz, a module to interactively visualise and share results amongst users. Altogether, CellPhoneDB v5 elevates the precision of cell-cell communication inference, ushering in new perspectives to comprehend tissue biology in both healthy and pathological states.Comment: 30 pages, 3 figures and 2 tables. Added previously missing figures and tables; Updated the reference for 'An integrated single-cell reference atlas of the human endometrium' pape

Single cell profiling of COVID-19 patients: an international data resource from multiple tissues

In late 2019 and through 2020, the COVID-19 pandemic swept the world, presenting both scientific and medical challenges associated with understanding and treating a previously unknown disease. To help address the need for great understanding of COVID-19, the scientific community mobilized and banded together rapidly to characterize SARS-CoV-2 infection, pathogenesis and its distinct disease trajectories. The urgency of COVID-19 provided a pressing use-case for leveraging relatively new tools, technologies, and nascent collaborative networks. Single-cell biology is one such example that has emerged over the last decade as a powerful approach that provides unprecedented resolution to the cellular and molecular underpinnings of biological processes. Early foundational work within the single-cell community, including the Human Cell Atlas, utilized published and unpublished data to characterize the putative target cells of SARS-CoV-2 sampled from diverse organs based on expression of the viral receptor ACE2 and associated entry factors TMPRSS2 and CTSL (Muus et al., 2020; Sungnak et al., 2020; Ziegler et al., 2020). This initial characterization of reference data provided an important foundation for framing infection and pathology in the airway as well as other organs. However, initial community analysis was limited to samples derived from uninfected donors and other previously-sampled disease indications. This report provides an overview of a single-cell data resource derived from samples from COVID-19 patients along with initial observations and guidance on data reuse and exploration

Single-Cell RNA Sequencing Reveals a Dynamic Stromal Niche That Supports Tumor Growth

Here, using single-cell RNA sequencing, we examine the stromal compartment in murine melanoma and draining lymph nodes (LNs) at points across tumor development, providing data at http://www.teichlab.org/data/. Naive lymphocytes from LNs undergo activation and clonal expansion within the tumor, before PD1 and Lag3 expression, while tumor-associated myeloid cells promote the formation of a suppressive niche. We identify three temporally distinct stromal populations displaying unique functional signatures, conserved across mouse and human tumors. Whereas "immune" stromal cells are observed in early tumors, "contractile" cells become more prevalent at later time points. Complement component C3 is specifically expressed in the immune population. Its cleavage product C3a supports the recruitment of C3aR(+) macrophages, and perturbation of C3a and C3aR disrupts immune infiltration, slowing tumor growth. Our results highlight the power of scRNA-seq to identify complex interplays and increase stromal diversity as a tumor develops, revealing that stromal cells acquire the capacity to modulate immune landscapes from early disease.Peer reviewe

DMRT1 regulates human germline commitment

Germline commitment following primordial germ cell (PGC) specification during early human development establishes an epigenetic programme and competence for gametogenesis. Here we follow the progression of nascent PGC-like cells derived from human embryonic stem cells in vitro. We show that switching from BMP signalling for PGC specification to Activin A and retinoic acid resulted in DMRT1 and CDH5 expression, the indicators of migratory PGCs in vivo. Moreover, the induction of DMRT1 and SOX17 in PGC-like cells promoted epigenetic resetting with striking global enrichment of 5-hydroxymethylcytosine and locus-specific loss of 5-methylcytosine at DMRT1 binding sites and the expression of DAZL representing DNA methylation-sensitive genes, a hallmark of the germline commitment programme. We provide insight into the unique role of DMRT1 in germline development for advances in human germ cell biology and in vitro gametogenesis

Comprehensive mapping of tissue cell architecture via integrated single cell and spatial transcriptomics

elocation-id: 2020.11.15.378125elocation-id: 2020.11.15.378125The spatial organization of cell types in tissues fundamentally shapes cellular interactions and function, but the high-throughput spatial mapping of complex tissues remains a challenge. We present сell2location, a principled and versatile Bayesian model that integrates single-cell and spatial transcriptomics to map cell types in situ in a comprehensive manner. We show that сell2location outperforms existing tools in accuracy and comprehensiveness and we demonstrate its utility by mapping two complex tissues. In the mouse brain, we use a new paired single nucleus and spatial RNA-sequencing dataset to map dozens of cell types and identify tissue regions in an automated manner. We discover novel regional astrocyte subtypes including fine subpopulations in the thalamus and hypothalamus. In the human lymph node, we resolve spatially interlaced immune cell states and identify co-located groups of cells underlying tissue organisation. We spatially map a rare pre-germinal centre B-cell population and predict putative cellular interactions relevant to the interferon response. Collectively our results demonstrate how сell2location can serve as a versatile first-line analysis tool to map tissue architectures in a high-throughput manner.Competing Interest StatementThe authors have declared no competing interest