Biology subjects

Bscheider, M.

Publications and source records attributed to Bscheider, M..

5 recordsLinked to original sources

bioRxiv2024

Recapitulating memory B cell responses in a Lymphoid Organ-Chip to evaluate mRNA vaccine boosting strategies

Predicting the immunogenicity of candidate vaccines in humans remains a challenge. To address this issue, we developed a Lymphoid Organ-Chip (LO chip) model based on a microfluidic chip seeded with human PBMC at high density within a 3D collagen matrix. Perfusion of the SARS-CoV-2 Spike protein mimicked a vaccine boost by inducing a massive amplification of Spike-specific memory B cells, plasmablast differentiation, and Spike-specific antibody secretion. Features of lymphoid tissue, including the formation of activated CD4+ T cell/B cell clusters and the emigration of matured plasmablasts, were recapitulated in the LO chip. Importantly, myeloid cells were competent at capturing and expressing mRNA vectored by lipid nanoparticles, enabling the assessment of responses to mRNA vaccines. Comparison of on-chip responses to Wuhan monovalent and Wuhan/Omicron bivalent mRNA vaccine boosts showed equivalent induction of Omicron neutralizing antibodies, pointing at immune imprinting as reported in vivo. The LO chip thus represents a versatile platform suited to the preclinical evaluation of vaccine boosting strategies.

immunology↗

bioRxiv2023

Human intestinal organoids with an autologoustissue-resident immune compartment

The intimate relationship between the epithelium and the immune system is crucial for maintaining tissue homeostasis, with perturbations in epithelial-immune interactions linked to autoimmune disease and cancer. Whereas stem cell-derived organoids are powerful models of tissue-specific epithelial function, these structures lack tissue-resident immune cells that are essential for capturing organ-level processes. We describe human intestinal immuno-organoids (IIOs), formed through self-organization of epithelial organoids and autologous tissue-resident lymphocytes (TRMs), a portion of which integrate within the IIO epithelium and survey the barrier. IIO formation was driven by TRM migration and interaction with epithelial cells, as orchestrated by TRM-enriched transcriptomic programs governing cell motility and epithelial inspection. We combined IIOs and single-cell transcriptomics to investigate intestinal inflammation triggered by cancer-targeting biologics in patients, and found that the system recapitulates clinical outcomes and the underlying cellular mechanisms. Inflammation was associated with the emergence of an activated population of CD8+ T cells, which progressively acquired intraepithelial and cytotoxic features. The appearance of this effector population was preceded and likely mediated by a Th1-like CD4+ population, which initially displayed a cytokine-producing character and subsequently became cytotoxic itself. A system amenable to direct perturbation and interrogation, IIOs allowed us to identify the Rho pathway as a novel target for mitigating immunotherapy-associated intestinal inflammation. Given that they recapitulate both the phenotypic outcomes and the underlying inter-lineage immune interactions, IIOs can be used to broadly study tissue-resident immune responses in the context of tumorigenesis, infectious and autoimmune diseases.

immunology↗

bioRxiv2023

Charting the Heterogeneity of Colorectal Cancer Consensus Molecular Subtypes using Spatial Transcriptomics

The heterogeneity of colorectal cancer (CRC) contributes to substantial differences in patient response to standard therapies. The consensus molecular subtypes (CMS) of CRC is the most widely-used gene expression-based classification and has contributed to a better understanding of disease heterogeneity and prognosis. Nevertheless, CMS intratumoral heterogeneity restricts its clinical application, stressing the necessity of further characterizing the composition and architecture of CRC. Here, we used Spatial Transcriptomics (ST) in combination with single-cell RNA sequencing (scRNA-seq) to decipher the spatially resolved cellular and molecular composition of CRC. In addition to mapping the intratumoral heterogeneity of CMS and their microenvironment, we identified cell communication events in the tumor-stroma interface of CMS2 carcinomas. This includes tumor growth-inhibiting as well as -activating signatures, such as the potential regulation of the ETV4 transcriptional activity by DCN or the PLAU-PLAUR ligand-receptor interaction. Our data show the power of ST to bring the CMS-based classification of CRC to another level and thereby gain useful molecular insights for personalized therapy.

cancer biology↗

bioRxiv2021

Human immunocompetent Organs-on-Chips platforms allow safety profiling of tumor-targeted T-cell bispecific antibodies

AbstractTraditional drug safety assessment often fails to predict complications in humans, especially when the drug targets the immune system. Here, we show the unprecedented capability of two Organs-on-Chips to evaluate the safety profile of T-cell bispecific antibodies (TCBs) targeting tumor antigens. Although promising for cancer immunotherapy, TCBs are associated with an on-target, off-tumor risk due to low levels of expression of tumor antigens in healthy tissues. We leveraged in vivo target expression and toxicity data of TCBs targeting folate receptor 1 (FOLR1) or carcinoembryonic antigen (CEA) to design and validate human immunocompetent Organs-on-Chips safety platforms. We discovered that the Lung-Chip and Intestine-Chip could reproduce and predict target-dependent TCB safety liabilities, based on sensitivity to key determinants thereof, such as target expression and antibody affinity. These novel tools broaden the research options available for mechanistic understandings of engineered therapeutic antibodies and assessing safety in tissues susceptible to adverse events.

cancer biology↗

bioRxiv2018

Branching developmental pathways through high dimensional single cell analysis in trajectory space

High-dimensional single cell profiling coupled with computational modeling is emerging as a powerful means to elucidate developmental sequences and define genetic programs directing cell lineages. Here we introduce tSpace, an algorithm based on the concept of \"trajectory space\", in which cells are defined by their distance along nearest neighbor pathways to every other cell in a population. tSpace outputs a dense matrix of cell-to-cell distances that quantitatively reflect the extent of phenotypic change along developmental paths (developmental distances). Graphical mapping of cells in trajectory space allows unsupervised reconstruction and straightforward exploration of complex developmental sequences. tSpace is robust, scalable, and implements a global approach that attempts to preserve both local and distant relationships in developmental pathways. Applied to high dimensional flow and mass cytometry data, the method faithfully reconstructs known pathways of thymic T cell development and provides novel insights into regulation of tonsillar B cell development and trafficking. Applied to single cell transcriptomic data, the method unfolds complex developmental sequences, recapitulates pathways leading from intestinal stem cells to specialized epithelial phenotypes more faithfully than existing algorithms, and reveals genetic programs that correlate with fate decisions. tSpace profiling of complex populations in high-dimensional trajectory space is well suited for hypothesis generation in developing cell systems.

bioinformatics↗