Dr. Hartmann received a B.Sc. and M.Sc. in Molecular Biotechnology from the University of Heidelberg, Germany and his PhD from the University of Zurich, Switzerland for his research on T cell effector functions in human autoimmune diseases. In 2017, he joined Stanford University as a postdoctoral fellow to study cancer immunology using highly multiplexed tissue imaging technologies. His research combines novel single-cell and imaging proteomic technologies with novel biological assays to reveal interactions of immune cells with their local environment and how this impacts clinical outcome in human cancer. Most recently, he has developed a novel approach that enables analysis of cellular metabolism in individual cells and with spatial resolution.
Dr. Hartmann has been the recipient of a Van Riemsdijk PhD Fellowship, a Swiss National Science Foundation Postdoctoral Scholarship (2016), a Novartis Foundation for biomedical research Postdoctoral Fellowship and a European Molecular Biology Organization (EMBO) LongTerm Postdoctoral Fellowship. He has received numerous awards, including a Distinction Award for his Ph.D. Thesis (2016), the Pfizer Research Award (2016), and a Young Investigator Award from the American Association of Immunologists (2019). In 2020, he has received a Young Investigator Grant from the Helmholtz Association.
Honors & Awards
AAI Young Investigator Award, American Association of Immunologists (2020)
EMBO Longterm Fellowship, EMBO (2018-2020)
Postdoctoral Fellowship, Novartis Foundation for bio-medical Research (2018-19)
SNF Early.Postdoc Fellowship, Swiss National Science Foundation (2017-2018)
Distinction Award for Doctoral Thesis, University of Zurich (2016)
Pfizer Research Prize, Pfizer Foundation (2016)
Van Riemsdijk PhD Fellowship, Van Riemsdijk Foundation (2012-2014)
Doctor of Philosophy, University of Zurich (2016)
Bachelor of Science, Ruprecht Karl Universitat Heidelberg (2009)
Master of Science, Ruprecht Karl Universitat Heidelberg (2011)
Sean Bendall, Postdoctoral Faculty Sponsor
Single-cell metabolic profiling of human cytotoxic T cells.
Cellular metabolism regulates immune cell activation, differentiation and effector functions, but current metabolic approaches lack single-cell resolution and simultaneous characterization of cellular phenotype. In this study, we developed an approach to characterize the metabolic regulome of single cells together with their phenotypic identity. The method, termed single-cell metabolic regulome profiling (scMEP), quantifies proteins that regulate metabolic pathway activity using high-dimensional antibody-based technologies. We employed mass cytometry (cytometry by time of flight, CyTOF) to benchmark scMEP against bulk metabolic assays by reconstructing the metabolic remodeling of in vitro-activated naive and memory CD8+ T cells. We applied the approach to clinical samples and identified tissue-restricted, metabolically repressed cytotoxic T cells in human colorectal carcinoma. Combining our method with multiplexed ion beam imaging by time of flight (MIBI-TOF), we uncovered the spatial organization of metabolic programs in human tissues, which indicated exclusion of metabolically repressed immune cells from the tumor-immune boundary. Overall, our approach enables robust approximation of metabolic and functional states in individual cells.
View details for DOI 10.1038/s41587-020-0651-8
View details for PubMedID 32868913
Immune monitoring usingmass cytometry and related high-dimensional imaging approaches.
Nature reviews. Rheumatology
The cellular complexity and functional diversity of the human immune system necessitate the use of high-dimensional single-cell tools to uncover its role in multifaceted diseases such as rheumatic diseases, as well as other autoimmune and inflammatory disorders. Proteomic technologies that use elemental (heavy metal) reporter ions, such as mass cytometry (also known as CyTOF) and analogous high-dimensional imaging approaches (including multiplexed ion beam imaging (MIBI) and imaging mass cytometry (IMC)), have been developed from their low-dimensional counterparts, flow cytometry and immunohistochemistry, to meet this need. A growing number of studies have been published that use these technologies to identify functional biomarkers and therapeutic targets in rheumatic diseases, but the full potential of their application to rheumatic disease research has yet to be fulfilled. This Review introduces the underlying technologies for high-dimensional immune monitoring and discusses aspects necessary for their successful implementation, including study design principles, analytical tools and future developments for the field of rheumatology.
View details for DOI 10.1038/s41584-019-0338-z
View details for PubMedID 31892734
GM-CSF and CXCR4 define a T helper cell signature in multiple sclerosis.
Cytokine dysregulation is a central driver of chronic inflammatory diseases such as multiple sclerosis (MS). Here, we sought to determine the characteristic cellular and cytokine polarization profile in patients with relapsing-remitting multiple sclerosis (RRMS) by high-dimensional single-cell mass cytometry (CyTOF). Using a combination of neural network-based representation learning algorithms, we identified an expanded T helper cell subset in patients with MS, characterized by the expression of granulocyte-macrophage colony-stimulating factor and the C-X-C chemokine receptor type 4. This cellular signature, which includes expression of very late antigen 4 in peripheral blood, was also enriched in the central nervous system of patients with relapsing-remitting multiple sclerosis. In independent validation cohorts, we confirmed that this cell population is increased in patients with MS compared with other inflammatory and non-inflammatory conditions. Lastly, we also found the population to be reduced under effective disease-modifying therapy, suggesting that the identified T cell profile represents a specific therapeutic target in MS.
View details for DOI 10.1038/s41591-019-0521-4
View details for PubMedID 31332391
Comprehensive Immune Monitoring of Clinical Trials to Advance Human Immunotherapy.
2019; 28 (3): 819
The success of immunotherapy has led to a myriad of clinical trials accompanied by efforts to gain mechanistic insight and identify predictive signatures for personalization. However, many immune monitoring technologies face investigator bias, missing unanticipated cellular responses in limited clinical material. We present here a mass cytometry (CyTOF) workflow for standardized, systems-level biomarker discovery in immunotherapy trials. To broadly enumerate immune cell identity and activity, we established and extensively assessed a reference panel of 33 antibodies to cover major cell subsets, simultaneously quantifying activation and immune checkpoint molecules in a single assay. This assay enumerates ≥98% of peripheral immune cells with ≥4 positively identifying antigens. Robustness and reproducibility are demonstrated on multiple samples types, across two research centers and by orthogonal measurements. Using automated analysis, we identify stratifying immune signatures in bone marrow transplantation-associated graft-versus-host disease. Together, this validated workflow ensures comprehensive immunophenotypic analysis and data comparability and will accelerate biomarker discovery.
View details for DOI 10.1016/j.celrep.2019.06.049
View details for PubMedID 31315057
A Universal Live Cell Barcoding-Platform for Multiplexed Human Single Cell Analysis.
2018; 8 (1): 10770
Single-cell barcoding enables the combined processing and acquisition of multiple individual samples as one. This maximizes assay efficiency and eliminates technical variability in both sample preparation and analysis. Remaining challenges are the barcoding of live, unprocessed cells to increase downstream assay performance combined with the flexibility of the approach towards a broad range of cell types. To that end, we developed a novel antibody-based platform that allows the robust barcoding of live human cells for mass cytometry (CyTOF). By targeting both the MHC class I complex (beta-2-microglobulin) and a broadly expressed sodium-potassium ATPase-subunit (CD298) with platinum-conjugated antibodies, human immune cells, stem cells as well as tumor cells could be multiplexed in the same single-cell assay. In addition, we present a novel palladium-based covalent viability reagent compatible with this barcoding strategy. Altogether, this platform enables mass cytometry-based, live-cell barcoding across a multitude of human sample types and provides a scheme for multiplexed barcoding of human single-cell assays in general.
View details for PubMedID 30018331
High-dimensional single-cell analysis reveals the immune signature of narcolepsy.
journal of experimental medicine
Narcolepsy type 1 is a devastating neurological sleep disorder resulting from the destruction of orexin-producing neurons in the central nervous system (CNS). Despite its striking association with the HLA-DQB1*06:02 allele, the autoimmune etiology of narcolepsy has remained largely hypothetical. Here, we compared peripheral mononucleated cells from narcolepsy patients with HLA-DQB1*06:02-matched healthy controls using high-dimensional mass cytometry in combination with algorithm-guided data analysis. Narcolepsy patients displayed multifaceted immune activation in CD4(+) and CD8(+) T cells dominated by elevated levels of B cell-supporting cytokines. Additionally, T cells from narcolepsy patients showed increased production of the proinflammatory cytokines IL-2 and TNF. Although it remains to be established whether these changes are primary to an autoimmune process in narcolepsy or secondary to orexin deficiency, these findings are indicative of inflammatory processes in the pathogenesis of this enigmatic disease.
View details for PubMedID 27821550
View details for PubMedCentralID PMC5110028
Multiple sclerosis-associated IL2RA polymorphism controls GM-CSF production in human T-H cells
Genome-wide association studies implicate dysregulation of immune mechanisms in the pathogenesis of multiple sclerosis (MS). Particularly, polymorphisms in genes involved in T helper (TH) cell differentiation are associated with risk of developing MS. However, the underlying mechanism by which these risk alleles influence MS susceptibility has remained elusive. Initiation of neuroinflammation in animal models of MS has been shown to be dependent on TH cell-derived granulocyte-macrophage colony-stimulating factor (GM-CSF). We here report association of GM-CSF expression by human TH cells with MS disease severity. GM-CSF is strongly induced by interleukin 2 (IL-2). We show that an MS-associated polymorphism in the IL-2 receptor alpha (IL2RA) gene specifically increases the frequency of GM-CSF-producing TH cells. The IL2RA polymorphism regulates IL-2 responsiveness of naive TH cells and their propensity to develop into GM-CSF-producing memory TH cells. These findings mechanistically link an immunologically relevant genetic risk factor with a functional feature of TH cells in MS.
View details for DOI 10.1038/ncomms6056
View details for Web of Science ID 000343975500001
View details for PubMedID 25278028
- Immune-stimulating antibody conjugates elicit robust myeloid activation and durable antitumor immunity NATURE CANCER 2021; 2 (1): 18-+
An Integrated Multi-omic Single-Cell Atlas of Human B Cell Identity.
2020; 53 (1): 217–32.e5
B cells are capable of a wide range of effector functions including antibody secretion, antigen presentation, cytokine production, and generation of immunological memory. A consistent strategy for classifying human B cells by using surface molecules is essential to harness this functional diversity for clinical translation. We developed a highly multiplexed screen to quantify the co-expression of 351 surface molecules on millions of human B cells. We identified differentially expressed molecules and aligned their variance with isotype usage, VDJ sequence, metabolic profile, biosynthesis activity, and signaling response. Based on these analyses, we propose a classification scheme to segregate B cells from four lymphoid tissues into twelve unique subsets, including a CD45RB+CD27- early memory population, a class-switched CD39+ tonsil-resident population, and a CD19hiCD11c+ memory population that potently responds to immune activation. This classification framework and underlying datasets provide a resource for further investigations of human B cell identity and function.
View details for DOI 10.1016/j.immuni.2020.06.013
View details for PubMedID 32668225
Multiplexed single-cell morphometry for hematopathology diagnostics.
2020; 26 (3): 408–17
The diagnosis of lymphomas and leukemias requires hematopathologists to integrate microscopically visible cellular morphology with antibody-identified cell surface molecule expression. To merge these into one high-throughput, highly multiplexed, single-cell assay, we quantify cell morphological features by their underlying, antibody-measurable molecular components, which empowers mass cytometers to 'see' like pathologists. When applied to 71 diverse clinical samples, single-cell morphometric profiling reveals robust and distinct patterns of 'morphometric' markers for each major cell type. Individually, lamin B1 highlights acute leukemias, lamin A/C helps distinguish normal from neoplastic mature T cells, and VAMP-7 recapitulates light-cytometric side scatter. Combined with machine learning, morphometric markers form intuitive visualizations of normal and neoplastic cellular distribution and differentiation. When recalibrated for myelomonocytic blast enumeration, this approach is superior to flow cytometry and comparable to expert microscopy, bypassing years of specialized training. The contextualization of traditional surface markers on independent morphometric frameworks permits more sensitive and automated diagnosis of complex hematopoietic diseases.
View details for DOI 10.1038/s41591-020-0783-x
View details for PubMedID 32161403
Scalable Conjugation and Characterization of Immunoglobulins with Stable Mass Isotope Reporters for Single-Cell Mass Cytometry Analysis.
Methods in molecular biology (Clifton, N.J.)
2019; 1989: 55–81
The advent of mass cytometry (CyTOF®) has permitted simultaneous detection of more than 40 antibody parameters at the single-cell level, although a limited number of metal-labeled antibodies are commercially available. Here we present optimized and scalable protocols for conjugation of lanthanide as well as bismuth ions to immunoglobulin (Ig) using a maleimide-functionalized chelating polymer and for characterization of the conjugate. The maleimide functional group is reactive with cysteine sulfhydryl groups generated through partial reduction of the Ig Fc region. Incubation of Ig with polymer pre-loaded with lanthanide ions produces metal-labeled Ig without disrupting antigen specificity. Antibody recovery rates can be determined by UV spectrophotometry and frequently exceeds 60%. Each custom-conjugated antibody is validated using positive and negative cellular control populations and is titrated for optimal staining at concentrations ranging from 0.1 to 10 μg/mL. The preparation of metal-labeled antibodies can be completed in 4.5 h, and titration requires an additional 3-5 h.
View details for PubMedID 31077099
High-dimensional single-cell analysis predicts response to anti-PD-1 immunotherapy.
Immune-checkpoint blockade has revolutionized cancer therapy. In particular, inhibition of programmed cell death protein 1 (PD-1) has been found to be effective for the treatment of metastatic melanoma and other cancers. Despite a dramatic increase in progression-free survival, a large proportion of patients do not show durable responses. Therefore, predictive biomarkers of a clinical response are urgently needed. Here we used high-dimensional single-cell mass cytometry and a bioinformatics pipeline for the in-depth characterization of the immune cell subsets in the peripheral blood of patients with stage IV melanoma before and after 12 weeks of anti-PD-1 immunotherapy. During therapy, we observed a clear response to immunotherapy in the T cell compartment. However, before commencing therapy, a strong predictor of progression-free and overall survival in response to anti-PD-1 immunotherapy was the frequency of CD14+CD16-HLA-DRhi monocytes. We confirmed this by conventional flow cytometry in an independent, blinded validation cohort, and we propose that the frequency of monocytes in PBMCs may serve in clinical decision support.
View details for DOI 10.1038/nm.4466
View details for PubMedID 29309059
High-Dimensional Single-Cell Mapping of Central Nervous System Immune Cells Reveals Distinct Myeloid Subsets in Health, Aging, and Disease.
2018; 48 (2): 380–95.e6
Individual reports suggest that the central nervous system (CNS) contains multiple immune cell types with diverse roles in tissue homeostasis, immune defense, and neurological diseases. It has been challenging to map leukocytes across the entire brain, and in particular in pathology, where phenotypic changes and influx of blood-derived cells prevent a clear distinction between reactive leukocyte populations. Here, we applied high-dimensional single-cell mass and fluorescence cytometry, in parallel with genetic fate mapping systems, to identify, locate, and characterize multiple distinct immune populations within the mammalian CNS. Using this approach, we revealed that microglia, several subsets of border-associated macrophages and dendritic cells coexist in the CNS at steady state and exhibit disease-specific transformations in the immune microenvironment during aging and in models of Alzheimer's disease and multiple sclerosis. Together, these data and the described framework provide a resource for the study of disease mechanisms, potential biomarkers, and therapeutic targets in CNS disease.
View details for DOI 10.1016/j.immuni.2018.01.011
View details for PubMedID 29426702
High Dimensional Cytometry of Central Nervous System Leukocytes During Neuroinflammation.
Methods in molecular biology (Clifton, N.J.)
2017; 1559: 321–32
Autoimmune diseases like multiple sclerosis (MS) develop from the activation and complex interactions of a wide network of immune cells, which penetrate the central nervous system (CNS) and cause tissue damage and neurological deficits. Experimental autoimmune encephalomyelitis (EAE) is a model used to study various aspects of MS, including the infiltration of autoaggressive T cells and pathogenic, inflammatory myeloid cells into the CNS. Various signature landscapes of immune cell infiltrates have proven useful in shedding light on the causes of specific EAE symptoms in transgenic mice. However, single cell analysis of these infiltrates has thus far been limited in conventional fluorescent flow cytometry methods by 14-16 parameter staining panels. With the advent of mass cytometry and metal-tagged antibodies, a staining panel of 35-45 parameters is now possible. With the aid of dimensionality reducing and clustering algorithms to visualize and analyze this high dimensional data, this allows for a more comprehensive picture of the different cell populations in an inflamed CNS, at a single cell resolution level. Here, we describe the induction of active EAE in C56BL/6 mice and, in particular, the staining of microglia and CNS invading immune cells for mass cytometry with subsequent data visualization and analysis.
View details for DOI 10.1007/978-1-4939-6786-5_22
View details for PubMedID 28063054
CyTOF workflow: differential discovery in high-throughput high-dimensional cytometry datasets.
2017; 6: 748
High dimensional mass and flow cytometry (HDCyto) experiments have become a method of choice for high throughput interrogation and characterization of cell populations.Here, we present an R-based pipeline for differential analyses of HDCyto data, largely based on Bioconductor packages. We computationally define cell populations using FlowSOM clustering, and facilitate an optional but reproducible strategy for manual merging of algorithm-generated clusters. Our workflow offers different analysis paths, including association of cell type abundance with a phenotype or changes in signaling markers within specific subpopulations, or differential analyses of aggregated signals. Importantly, the differential analyses we show are based on regression frameworks where the HDCyto data is the response; thus, we are able to model arbitrary experimental designs, such as those with batch effects, paired designs and so on. In particular, we apply generalized linear mixed models to analyses of cell population abundance or cell-population-specific analyses of signaling markers, allowing overdispersion in cell count or aggregated signals across samples to be appropriately modeled. To support the formal statistical analyses, we encourage exploratory data analysis at every step, including quality control (e.g. multi-dimensional scaling plots), reporting of clustering results (dimensionality reduction, heatmaps with dendrograms) and differential analyses (e.g. plots of aggregated signals).
View details for DOI 10.12688/f1000research.11622.1
View details for PubMedID 28663787
View details for PubMedCentralID PMC5473464
The end of gating? An introduction to automated analysis of high dimensional cytometry data
EUROPEAN JOURNAL OF IMMUNOLOGY
2016; 46 (1): 34-43
Ever since its invention half a century ago, flow cytometry has been a major tool for single-cell analysis, fueling advances in our understanding of a variety of complex cellular systems, in particular the immune system. The last decade has witnessed significant technical improvements in available cytometry platforms, such that more than 20 parameters can be analyzed on a single-cell level by fluorescence-based flow cytometry. The advent of mass cytometry has pushed this limit up to, currently, 50 parameters. However, traditional analysis approaches for the resulting high-dimensional datasets, such as gating on bivariate dot plots, have proven to be inefficient. Although a variety of novel computational analysis approaches to interpret these datasets are already available, they have not yet made it into the mainstream and remain largely unknown to many immunologists. Therefore, this review aims at providing a practical overview of novel analysis techniques for high-dimensional cytometry data including SPADE, t-SNE, Wanderlust, Citrus, and PhenoGraph, and how these applications can be used advantageously not only for the most complex datasets, but also for standard 14-parameter cytometry datasets.
View details for DOI 10.1002/eji.201545774
View details for Web of Science ID 000368234800005
View details for PubMedID 26548301
The Cytokine GM-CSF Drives the Inflammatory Signature of CCR2(+) Monocytes and Licenses Autoimmunity
2015; 43 (3): 502-514
Granulocyte-macrophage colony-stimulating factor (GM-CSF) has emerged as a crucial cytokine produced by auto-reactive T helper (Th) cells that initiate tissue inflammation. Multiple cell types can sense GM-CSF, but the identity of the pathogenic GM-CSF-responsive cells is unclear. By using conditional gene targeting, we systematically deleted the GM-CSF receptor (Csf2rb) in specific subpopulations throughout the myeloid lineages. Experimental autoimmune encephalomyelitis (EAE) progressed normally when either classical dendritic cells (cDCs) or neutrophils lacked GM-CSF responsiveness. The development of tissue-invading monocyte-derived dendritic cells (moDCs) was also unperturbed upon Csf2rb deletion. Instead, deletion of Csf2rb in CCR2(+)Ly6C(hi) monocytes phenocopied the EAE resistance seen in complete Csf2rb-deficient mice. High-dimensional analysis of tissue-infiltrating moDCs revealed that GM-CSF initiates a combination of inflammatory mechanisms. These results indicate that GM-CSF signaling controls a pathogenic expression signature in CCR2(+)Ly6C(hi) monocytes and their progeny, which was essential for tissue damage.
View details for DOI 10.1016/j.immuni.2015.08.010
View details for Web of Science ID 000370965900003
View details for PubMedID 26341401
HLA Class II tetramers reveal tissue-specific regulatory T cells that suppress T-cell responses in breast carcinoma patients.
2013; 2 (6): e24962
Regulatory T cells (Tregs) play an important role in controlling antitumor T-cell responses and hence represent a considerable obstacle for cancer immunotherapy. The abundance of specific Treg populations in cancer patients has been poorly analyzed so far. Here, we demonstrate that in breast cancer patients, Tregs often control spontaneous effector memory T-cell responses against mammaglobin, a common breast tissue-associated antigen that is overexpressed by breast carcinoma. Using functional assays, we identified a HLA-DRB1*04:01- and HLA-DRB1*07:01-restricted epitope of mammaglobin (mam34-48) that was frequently recognized by Tregs isolated from breast cancer patients. Using mam34-48-labeled HLA Class II tetramers, we quantified mammaglobin-specific Tregs and CD4(+) conventional T (Tcon) cells in breast carcinoma patients as well as in healthy individuals. Both mammaglobin-specific Tregs and Tcon cells were expanded in breast cancer patients, each constituting approximately 0.2% of their respective cell subpopulations. Conversely, mammaglobin-specific Tregs and CD4(+) Tcon cells were rare in healthy individuals (0.07%). Thus, we provide here for the first time evidence supporting the expansion of breast tissue-specific Tregs and CD4(+) Tcon cells in breast cancer patients. In addition, we substantiate the potential implications of breast tissue-specific Tregs in the suppression of antitumor immune responses in breast cancer patients. The HLA Class II tetramers used in this study may constitute a valuable tool to elucidate the role of antigen-specific Tregs in breast cancer immunity and to monitor breast cancer-specific CD4(+) T cells.
View details for DOI 10.4161/onci.24962
View details for PubMedID 23894725
In vitro evaluation of liposomes containing bio-enhancers for the oral delivery of macromolecules
EUROPEAN JOURNAL OF PHARMACEUTICS AND BIOPHARMACEUTICS
2010; 76 (3): 394-403
The aim of this work was to develop a new type of liposomes containing bio-enhancers for oral delivery of hydrophilic macromolecules. The study focused on EPC/cholesterol-based formulations combined with TPGS 1000 and 400, cholylsarcosine (CS), cetylpyridinium chloride (CpCl) and stearylamine (SA) covering a broad range of different types of enhancers. Most of the tested liposomal formulations and enhancers showed neither influence on cell viability in the Alamar Blue® assay nor an increase in lactate dehydrogenase LDH release. But, at a concentration of 1 mM, CpCl exhibited a strong toxicity after 2 h, TPGS 1000 reduced the cell viability at the same concentration after 8h significantly. Only one liposomal formulation with 25% CpCl led to a decrease in viability to 60.0% after 8h at a total lipid concentration of 5 mM. In the Caco-2 Transwell® model, one formulation with 5% TPGS 400 improved the permeation of FITC-dextran 70 kDa 3.34 ± 0.62-fold, one with 10% CpCl 3.69 ± 0.67 and one with 10% CS and 2.5% SA 3.41 ± 0.51-fold without influencing the TER. Liposomes with 10% SA or 25% CpCl increased the permeation of FITC-dextran 29.02 ± 5.84, respectively 39.28 ± 2.10-fold, but led also to a strong reduction in the TER. Especially, the three formulations which enhanced the permeation of FITC-dextran around 3.5-fold without showing any cell toxicity or decrease in TER should be safe and effective candidates for the development of an oral delivery system for hydrophilic macromolecules.
View details for DOI 10.1016/j.ejpb.2010.09.002
View details for Web of Science ID 000285279900010
View details for PubMedID 20849953