Biology subjects

Ingelfinger, F.

Publications and source records attributed to Ingelfinger, F..

6 recordsLinked to original sources

bioRxiv2025

CytoVI: Deep generative modeling of antibody-based single cell technologies

Due to their robustness, dynamic range and scalability, antibody-based single cell technologies, such as flow cytometry, mass cytometry and CITE-seq, have become an irreplaceable part of routine clinics and a powerful tool for basic research. However, their analysis is complicated by measurement noise and bias, differences between batches, technology platforms, and restricted antibody panels. This results in a limited capacity to accumulate knowledge across technologies, studies, experimental batches, or across different antibody panels. Here, we present CytoVI - a probabilistic generative model designed to address these challenges and enable statistically rigorous and integrative analysis for antibody-based single cell technologies. We show that CytoVI outperforms existing computational methods and effectively handles a variety of integration scenarios. CytoVI enables key functionalities such as generating informative cell embeddings, imputing missing measurements, differential protein expression testing, and automated annotation of cells. We applied CytoVI to generate an integrated B cell maturation atlas across 350 proteins from a set of smaller antibody panels measured by conventional mass cytometry, and identified proteins associated with immunoglobulin class-switching in healthy humans. Using a cohort of B cell non-Hodgkin lymphoma patients measured by flow cytometry, CytoVI uncovered T cell states that are associated with disease. Finally, we show that CytoVI is a robust probabilistic framework for the analysis of standard diagnostic flow cytometry antibody panels, enabling the automated detection of tumor populations and diagnoses of incoming patient samples. CytoVI facilitates accurate and automated analysis in both preclinical and clinical settings and is available as open-source software at scvi-tools.org.

bioinformatics↗

bioRxiv2025

Mapping Leukocyte Dynamics during Neuroinflammation Identifies Meningeal Monocyte-Derived Macrophages as Drivers of Progressive Disease

Multiple sclerosis (MS) is a chronic inflammatory disease of the central nervous system (CNS) characterized by increasing disability. The cellular and molecular drivers of clinical transition towards progressive disease are poorly understood. Here, we combine single-cell profiling technologies with genetic and pharmacological perturbations across the course of murine CNS inflammation to dissect the role of the local immune landscape in disease progression. We uncover a chronic monocyte-to-phagocyte transition as a hallmark of progressive disease, characterized by the emergence of maladaptive, lipid-associated macrophages (LAMs) marked by lysosomal activation and fibrotic features. Spatial transcriptomics and multiplexed imaging revealed that these LAMs localized to the leptomeninges in close proximity to parenchymal colony-stimulating factor (CSF)-1 producing disease-associated microglia (DAMs) and meningeal granulocyte-macrophage (GM)-CSF-expressing T helper cells that license their differentiation. Interference with this local cytokine network revealed a protective role for resident microglia and implicated monocyte-derived phagocytes as key drivers of progressive neuroinflammation. Notably, LAM-like macrophages could also be identified in the meninges of people with MS, indicating a homology to human disease. By elucidating their ontogeny, spatial niche, and regulatory cytokine milieu, we provide a mechanistic framework for targeting harmful myeloid states while preserving reparative CNS immunity in progressive MS.

immunology↗

bioRxiv2025

Aging-Associated Microbiota Drives Treg Dysfunction via TNF Signaling

Aging is associated with a chronic, low-grade inflammatory state referred to as inflammaging, which contributes to impaired immune regulation and increased susceptibility to disease. While regulatory T (Treg) cells are key mediators of immune homeostasis, their role in the context of age-related inflammation remains poorly understood. Here we demonstrate that age-related changes in the microbiota promote impaired Treg cell function, resulting in the differentiation of inflammatory T cells. In agreement, we find that aged germ-free (GF) mice exhibited a more balanced immune profile, where the Treg cells are functional and pro-inflammatory mediators are reduced, suggesting that microbial exposure is essential for the establishment of inflammaging. Furthermore, we show that the use of old microbiota in young animals was sufficient to induce pro-inflammatory T cell responses and impaired mucosal Treg cell proliferation, while young microbiota restored Treg cell function in old animals. Mechanistically, we show that exposure to aged microbiota was associated with sustained TNF signaling, elevated oxidative stress, DNA damage, and increased expression of senescence markers such as {gamma}H2AX and p16 in Treg cells. These findings uncover a microbiota-TNF-dependent mechanism by which age-associated microbial dysbiosis drives Treg cell dysfunction and promotes immune aging, highlighting the therapeutic potential of microbiota-targeted strategies to restore immune homeostasis in the elderly.

immunology↗

bioRxiv2025

scVIVA: a probabilistic framework for representation of cells and their environments in spatial transcriptomics

Spatial transcriptomics provides a significant advance over studies of dissociated cells in that it reveals the environment in which cells reside, thus opening the way for a more complete description of their state and function. However, most current methods for embedding and discovery of cell states rely only on the cells own gene expression profile, thus raising the need for ways to account for the neighboring cells as well. Here, we introduce scVIVA, a deep generative model that leverages both cell-intrinsic and neighboring gene expression profiles to output stochastic embeddings of cell states as well as normalized gene expression profiles. We demonstrate that scVIVA produces informative fine-grained partitions of cells that reflect both their internal state and the surrounding tissue and that its generative model facilitates the testing of hypotheses of differential expression between tissue niches. We leverage these properties of scVIVA to uncover a spatially-restricted tumor-promoting endothelial population in breast cancer and niche-associated T cell states that are shared across multiple cancers. scVIVA is available as open source software within scvi-tools.org.

bioinformatics↗

bioRxiv2024

Monocyte-derived cells but not Microglia cause Oxidative Tissue Damage in Neuroinflammation

Multiple sclerosis (MS) is characterized by neuroinflammation, oxidative stress, iron toxicity and mitochondrial dysfunction. Reactive oxygen species (ROS) produced by mononuclear phagocytes (MPs) are widely held to drive tissue damage, yet the specific roles of central nervous system (CNS)- resident versus CNS-invading MPs remain unclear. Here, by combining single-cell profiling with conditional gene targeting, we systematically dissected and interfered with ROS production across CNS MPs in a preclinical model for neuroinflammation. We show that CNS-invading monocyte derived cells (MdCs) exhibit a higher oxidative stress gene signature and produce more ROS compared to CNS-resident microglia. While NADPH oxidase 2 (NOX2), a phagocytic source of ROS, proved redundant, our findings underscore the critical role of mitochondrial ROS (mtROS) in driving oxidative tissue damage. Quenching mtROS through mitocatalase overexpression in MdCs, but not microglia, significantly alleviated neuroinflammation in mice. Thus, our study resolves a longstanding controversy, identifying MdCs as the primary driver of ROS-mediated neuropathology.

immunology↗

bioRxiv2022

Neuroprotective tissue adaptation induced by IL-12 attenuates CNS inflammation

IL-12 is a well-established driver of type 1 immune responses. Paradoxically, in several autoimmune conditions including neuroinflammation, IL-12 reduces pathology and exhibits regulatory properties. Yet, the mechanism and the involved cellular players behind this immune regulation remain elusive. To identify the IL-12-responsive elements which prevent immunopathology, we generated mouse models lacking a functional IL-12 receptor either in all cells or in specific populations within the immune or central nervous system (CNS) compartments, and induced experimental autoimmune encephalomyelitis (EAE), which models human Multiple Sclerosis (MS). This revealed that the CNS tissue-protective features of IL-12 are mediated by cells of the neuroectoderm, and not immune cells. Importantly, sections of brain from patients with MS show comparable patterns of expression, indicating parallel mechanisms in humans. By combining spectral flow cytometry, bulk and single-nucleus RNA sequencing, we uncovered an IL-12-induced neuroprotective adaption of the neuroectoderm critically involved in maintaining CNS tissue integrity during inflammation.

immunology↗