Kristian Händler

Bio: Kristian Händler is an academic researcher from University of Bonn. The author has contributed to research in topics: Medicine & Biology. The author has an hindex of 14, co-authored 22 publications receiving 2081 citations. Previous affiliations of Kristian Händler include Trinity College, Dublin & German Center for Neurodegenerative Diseases.

Specification of tissue-resident macrophages during organogenesis

Abstract: INTRODUCTION Embryonic development and tissue homeostasis depend on cooperation between specialized cell types. Resident macrophages are professional phagocytes that survey their surroundings; eliminate unfit cells, microorganisms, and metabolic waste; and produce a large range of bioactive molecules and growth factors. Resident macrophages also serve tissue-specific purposes: For example, microglia in the central nervous system support neuronal circuit development, Kupffer cells scavenge blood particles and dying red blood cells in the liver, and alveolar macrophages uptake surfactant and remove airborne pollutants and microbes from the airways. Resident macrophage diversity in adult mice is reflected in tissue-specific gene expression profiles, which may be due to responses to specific cues from their microenvironment, different developmental processes, and the contribution of distinct progenitors cell types. Altogether, the mechanisms responsible for the generation of tissue-resident macrophage diversity remain unclear. RATIONALE Tissue-resident macrophages originate, at least in part, from mesodermal erythro-myeloid progenitors (EMPs) from the yolk sac, which invade the embryo proper at the onset of organogenesis. These tissue-resident macrophages are also self-maintained in postnatal tissues, independently of definitive hematopoietic stem cells (HSCs) in a steady state. We therefore hypothesized that resident macrophages represent a founding cell type within most organ anlagen. In this model, the generation of macrophage diversity, as observed in the tissues of postnatal mice, may be integral to organogenesis. RESULTS To test this hypothesis and explore the molecular basis of macrophage diversity in mammals, we performed a spatiotemporal analysis of macrophage development in mice, from embryonic day 9 (E9) to 3 weeks after birth. Unbiased single-cell RNA sequencing (RNA-seq) analysis of CD45 + cells, combined with RNA-seq analyses of sorted cell populations, genetic fate mapping, and in situ analyses, revealed that EMPs give rise to a population of premacrophages (pMacs) that colonize the whole embryo from E9.5, as they acquire a core macrophage differentiation program that includes pattern recognition, scavengers, and cytokine receptors. The chemokine receptor Cx3cr1 is up-regulated in pMacs and is important for embryo colonization, which is delayed in Cx3cr1 -deficient embryos. Fate mapping of pMacs using a Tnfrsf11a –Cre reporter labels homogeneously fetal and adult tissue-resident macrophages but not HSCs and their progeny. Transcriptional regulators that identify postnatal tissue-resident macrophages in the brain, liver, kidney, skin, and lung were specifically up-regulated immediately after colonization. These dynamic changes mark the onset of diversification into adult macrophages. We identified Id3 as a Kupffer cell–specific transcriptional regulator. Deletion of Id3 in pMacs resulted in Kupffer cell deficiency but did not affect development of microglia and kidney macrophages. CONCLUSION Our study shows that EMP-derived precursors colonize embryonic tissues and simultaneously acquire a full core macrophage program. This is followed by their diversification into tissue-specific macrophages during organogenesis, likely via the expression of distinct sets of transcriptional regulators. These results indicate that differentiation of tissue-resident macrophages is an integral part of organogenesis and identify a spatiotemporal molecular road map for the generation of macrophage diversity in vivo. Our findings provide a conceptual framework to analyze and understand the consequence(s) of genetic variation for macrophage contribution to development, homeostasis, and disease pathogenesis in different tissues and will support efforts to differentiate specialized macrophages in vitro.

Mapping the human DC lineage through the integration of high-dimensional techniques

Abstract: INTRODUCTION Dendritic cells (DC) are professional antigen-presenting cells that orchestrate immune responses. The human DC population comprises multiple subsets, including plasmacytoid DC (pDC) and two functionally specialized lineages of conventional DC (cDC1 and cDC2), whose origins and differentiation pathways remain incompletely defined. RATIONALE As DC are essential regulators of the immune response in health and disease, potential intervention strategies aiming at manipulation of these cells will require in-depth insights of their origins, the mechanisms that govern their homeostasis, and their functional properties. Here, we employed two unbiased high-dimensional technologies to characterize the human DC lineage from bone marrow to blood. RESULTS We isolated the DC-containing population (Lineage − HLA − DR + CD135 + cells) from human blood and defined the transcriptomes of 710 individual cells using massively parallel single-cell mRNA sequencing. By combining complementary bioinformatic approaches, we identified a small cluster of cells within this population as putative DC precursors (pre-DC). We then confirmed this finding using cytometry by time-of-flight (CyTOF) to simultaneously measure the expression of a panel of 38 different proteins at the single-cell level on Lineage − HLA − DR + cells and found that pre-DC possessed a CD123 + CD33 + CD45RA + phenotype. We confirmed the precursor potential of pre-DC by establishing their potential to differentiate in vitro into cDC1 and cDC2, but not pDC, in the known proportions found in vivo . Interestingly, pre-DC also express classical pDC markers, including CD123, CD303, and CD304. Thus, any previous studies using these markers to identify or isolate pDC will have inadvertently included CD123 + CD33 + pre-DC. We provide here new markers that can be used to identify unambiguously pre-DC from pDC, including CD33, CX3CR1, CD2, CD5, and CD327. When CD123 + CD33 + pre-DC and CD123 + CD33 − pDC were isolated separately, we observed that pre-DC have unique functional properties that were previously attributed to pDC. Although pDC remain bona fide interferon-α–producing cells, their reported interleukin-12 (IL-12) production and CD4 T cell allostimulatory capacity can likely be attributed to “contaminating” pre-DC. We then asked whether the pre-DC population contained both uncommitted and committed pre-cDC1 and pre-cDC2 precursors, as recently shown in mice. Using microfluidic single-cell mRNA sequencing (scmRNAseq), we showed that the human pre-DC population contains cells exhibiting transcriptomic priming toward cDC1 and cDC2 lineages. Flow cytometry and in vitro DC differentiation experiments further identified CD123 + CADM1 − CD1c − putative uncommitted pre-DC, alongside CADM1 + CD1c − pre-cDC1 and CADM1 − CD1c + pre-cDC2. Finally, we found that pre-DC subsets expressed T cell costimulatory molecules and induced comparable proliferation and polarization of naive CD4 T cells as adult DC. However, exposure to the Toll-like receptor 9 (TLR9) ligand CpG triggered IL-12p40 and tumor necrosis factor–α production by early pre-DC, pre-cDC1, and pre-cDC2, in contrast to differentiated cDC1 and cDC2, which do not express TLR9. CONCLUSION Using unsupervised scmRNAseq and CyTOF analyses, we have unraveled the complexity of the human DC lineage at the single-cell level, revealing a continuous process of differentiation that starts in the bone marrow (BM) with common DC progenitors (CDP), diverges at the point of emergence of pre-DC and pDC potential, and culminates in maturation of both lineages in the blood and spleen. The pre-DC compartment contains functionally and phenotypically distinct lineage-committed subpopulations, including one early uncommitted CD123 + pre-DC subset and two CD45RA + CD123 lo lineage-committed subsets. The discovery of multiple committed pre-DC populations with unique capabilities opens promising new avenues for the therapeutic exploitation of DC subset-specific targeting.

The transcriptional landscape and small RNAs of Salmonella enterica serovar Typhimurium

Abstract: More than 50 y of research have provided great insight into the physiology, metabolism, and molecular biology of Salmonella enterica serovar Typhimurium (S. Typhimurium), but important gaps in our knowledge remain. It is clear that a precise choreography of gene expression is required for Salmonella infection, but basic genetic information such as the global locations of transcription start sites (TSSs) has been lacking. We combined three RNA-sequencing techniques and two sequencing platforms to generate a robust picture of transcription in S. Typhimurium. Differential RNA sequencing identified 1,873 TSSs on the chromosome of S. Typhimurium SL1344 and 13% of these TSSs initiated antisense transcripts. Unique findings include the TSSs of the virulence regulators phoP, slyA, and invF. Chromatin immunoprecipitation revealed that RNA polymerase was bound to 70% of the TSSs, and two-thirds of these TSSs were associated with σ(70) (including phoP, slyA, and invF) from which we identified the -10 and -35 motifs of σ(70)-dependent S. Typhimurium gene promoters. Overall, we corrected the location of important genes and discovered 18 times more promoters than identified previously. S. Typhimurium expresses 140 small regulatory RNAs (sRNAs) at early stationary phase, including 60 newly identified sRNAs. Almost half of the experimentally verified sRNAs were found to be unique to the Salmonella genus, and <20% were found throughout the Enterobacteriaceae. This description of the transcriptional map of SL1344 advances our understanding of S. Typhimurium, arguably the most important bacterial infection model.

Swarm Learning for decentralized and confidential clinical machine learning.

Abstract: Fast and reliable detection of patients with severe and heterogeneous illnesses is a major goal of precision medicine1,2. Patients with leukaemia can be identified using machine learning on the basis of their blood transcriptomes3. However, there is an increasing divide between what is technically possible and what is allowed, because of privacy legislation4,5. Here, to facilitate the integration of any medical data from any data owner worldwide without violating privacy laws, we introduce Swarm Learning-a decentralized machine-learning approach that unites edge computing, blockchain-based peer-to-peer networking and coordination while maintaining confidentiality without the need for a central coordinator, thereby going beyond federated learning. To illustrate the feasibility of using Swarm Learning to develop disease classifiers using distributed data, we chose four use cases of heterogeneous diseases (COVID-19, tuberculosis, leukaemia and lung pathologies). With more than 16,400 blood transcriptomes derived from 127 clinical studies with non-uniform distributions of cases and controls and substantial study biases, as well as more than 95,000 chest X-ray images, we show that Swarm Learning classifiers outperform those developed at individual sites. In addition, Swarm Learning completely fulfils local confidentiality regulations by design. We believe that this approach will notably accelerate the introduction of precision medicine.

Integrated analysis of multimodal single-cell data

Abstract: The simultaneous measurement of multiple modalities, known as multimodal analysis, represents an exciting frontier for single-cell genomics and necessitates new computational methods that can define cellular states based on multiple data types. Here, we introduce ‘weighted-nearest neighbor’ analysis, an unsupervised framework to learn the relative utility of each data type in each cell, enabling an integrative analysis of multiple modalities. We apply our procedure to a CITE-seq dataset of hundreds of thousands of human white blood cells alongside a panel of 228 antibodies to construct a multimodal reference atlas of the circulating immune system. We demonstrate that integrative analysis substantially improves our ability to resolve cell states and validate the presence of previously unreported lymphoid subpopulations. Moreover, we demonstrate how to leverage this reference to rapidly map new datasets, and to interpret immune responses to vaccination and COVID-19. Our approach represents a broadly applicable strategy to analyze single-cell multimodal datasets, including paired measurements of RNA and chromatin state, and to look beyond the transcriptome towards a unified and multimodal definition of cellular identity. Availability Installation instructions, documentation, tutorials, and CITE-seq datasets are available at http://www.satijalab.org/seurat

Integrative Genomics Viewer

Abstract: Rapid improvements in sequencing and array-based platforms are resulting in a flood of diverse genome-wide data, including data from exome and whole-genome sequencing, epigenetic surveys, expression profiling of coding and noncoding RNAs, single nucleotide polymorphism (SNP) and copy number profiling, and functional assays. Analysis of these large, diverse data sets holds the promise of a more comprehensive understanding of the genome and its relation to human disease. Experienced and knowledgeable human review is an essential component of this process, complementing computational approaches. This calls for efficient and intuitive visualization tools able to scale to very large data sets and to flexibly integrate multiple data types, including clinical data. However, the sheer volume and scope of data pose a significant challenge to the development of such tools.

A lineage of myeloid cells independent of Myb and hematopoietic stem cells

Abstract: Macrophage Development Rewritten Macrophages provide protection against a wide variety of infections and critically shape the inflammatory environment in many tissues. These cells come in many flavors, as determined by differences in gene expression, cell surface phenotype and specific function. Schulz et al. (p. 86, published online 22 March) investigated whether adult macrophages all share a common developmental origin. Immune cells, including most macrophages, are widely thought to arise from hematopoietic stem cells (HSCs), which require the transcription factor Myb for their development. Analysis of Myb-deficient mice revealed that a population of yolk-sac–derived, tissue-resident macrophages was able to develop and persist in adult mice in the absence of HSCs. Importantly, yolk sac–derived macrophages also contributed substantially to the tissue macrophage pool even when HSCs were present. In mice, a population of tissue-resident macrophages arises independently of bone marrow–derived stem cells. Macrophages and dendritic cells (DCs) are key components of cellular immunity and are thought to originate and renew from hematopoietic stem cells (HSCs). However, some macrophages develop in the embryo before the appearance of definitive HSCs. We thus reinvestigated macrophage development. We found that the transcription factor Myb was required for development of HSCs and all CD11bhigh monocytes and macrophages, but was dispensable for yolk sac (YS) macrophages and for the development of YS-derived F4/80bright macrophages in several tissues, such as liver Kupffer cells, epidermal Langerhans cells, and microglia—cell populations that all can persist in adult mice independently of HSCs. These results define a lineage of tissue macrophages that derive from the YS and are genetically distinct from HSC progeny.