Biology subjects

Boersch, A.

Publications and source records attributed to Boersch, A..

8 recordsLinked to original sources

bioRxiv2026

Metabolic-secretory decoupling defines a disease-intrinsic state in rheumatoid arthritis monocytes

ObjectivesCirculating monocytes from rheumatoid arthritis (RA) patients are pre-primed for inflammatory activation, but their disease-intrinsic features have not been systematically characterized. Given the important role of metabolism in shaping immune cell function, we aimed to determine how this pre-primed state is underpinned metabolically and whether these changes persist across different activation states, using an unbiased multi-omics approach. MethodsPeripheral blood CD14 monocytes from RA patients and matched healthy donors were analyzed in an undifferentiated state (M0) and after differentiation into classically activated M(IFN{gamma}+LPS) and alternatively activated M(IL-4) macrophages, followed by acute lipopolysaccharide (LPS) stimulation. Metabolomic (untargeted LC-MS/MS), transcriptomic (RNA-seq), and proteomic (label-free mass LC-MS/MS) profiling were performed. Data was comprehensively analyzed by weighted gene correlation network analysis, differential analysis, gene set enrichment analysis, multi-omics factor analysis and metabolic flux modeling. ResultsRA monocytes exhibited a stable disease-driven signature across activation states. Integration of metabolomic, transcriptomic and proteomic data revealed an unexpected convergence on metabolic-secretory coupling, with depletion of nucleotide and redox metabolites, downregulation of mitochondrial and translational pathways, and remodeling of the secretory apparatus, including loss of cis-Golgi components. Consistently, metabolic modeling predicted reduced glycosylation fluxes, connecting metabolic changes to altered secretory capacity. ConclusionsRA monocytes adopt a stable, disease-intrinsic state that persists across activation conditions. Multi-omics data identify a linked metabolic and secretory defect, with reduced glycosylation capacity as a potential functional consequence. This metabolic-secretory coupling represents a defining feature of RA monocyte dysfunction and a potential therapeutic target.

immunology↗

bioRxiv2023

Modelling Osteoarthritis pathogenesis through Mechanical Loading in an Osteochondral Unit-on-Chip

A cure for osteoarthritis (OA), the most prevalent musculoskeletal disease, remains an unmet need. Investigating the molecular and cellular processes leading to OA is challenged by the absence of human models that capture the complex interplay among different tissues in the joint under pathophysiological mechanical loading. In this study, we have engineered an OsteoChondral Unit (OCU)-on-chip system where composite hyaline cartilage - mineralized osseous microtissue analogues are exposed to controlled, tissue-specific compression regimes akin to those of the OCU in vivo. Through single-cell transcriptomic analysis, we demonstrate the critical relevance of the mineralized layer in inducing chondrocyte subpopulations implicated in the progression of OA. Upon exposure to hyperphysiological loading, the OCU-on-chip captures early phenotypic traits of OA pathogenesis, comprising alterations of subchondral mineral content and acquisition of previously described OA genetic signatures. This system enabled to identify novel upstream drivers of OA metabolic changes, including mechanically induced ribosomal alterations, as well as associated molecular targets towards the development of disease-modifying OA therapies.

bioengineering↗

bioRxiv2023

Engagement of sialylated glycans with Siglec receptors on myeloid suppressor cells inhibit anti-cancer immunity via CCL2

Overexpression of sialic acids on glycans, called hypersialylation is a common alteration found in cancer. Hypersialylation can, for example, enhance immune evasion via interaction with sialic acid-binding immunoglobulin-like lectin (Siglec) receptors on tumor-infiltrating immune cells. Here, we tested the role of sialic acid on myeloid-derived suppressor cells (MDSCs) and their interaction with Siglec receptors. We found that MDSCs derived from the blood of lung cancer patients and tumor-bearing mice strongly express inhibitory Siglec receptors. In murine cancer models of emergency myelopoiesis, Siglec-E knockout on myeloid cells resulted in prolonged survival and increased infiltration of activated T cells. Targeting suppressive myeloid cells by blocking Siglec receptors or desialylation led to strong reduction of their suppressive potential. We further identified CCL2 as mediator involved in T cell suppression upon interaction of sialoglycans and Siglec receptors on MDSCs. Our results provide mechanistic insights how sialylated glycans inhibit anti-cancer immunity by facilitating CCL2 expression. O_FIG O_LINKSMALLFIG WIDTH=142 HEIGHT=200 SRC="FIGDIR/small/547025v1_ufig1.gif" ALT="Figure 1"> View larger version (42K): org.highwire.dtl.DTLVardef@e7664forg.highwire.dtl.DTLVardef@1edd220org.highwire.dtl.DTLVardef@7e630dorg.highwire.dtl.DTLVardef@198ff40_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

bioRxiv2022

Combined multidimensional single-cell protein and RNA profiling dissects the cellular and functional heterogeneity of thymic epithelial cells

The network of thymic stromal cells provides essential niches with unique molecular cues controlling T-cell development and selection. Recent single-cell RNA-sequencing studies uncovered a large transcriptional heterogeneity among thymic epithelial cells (TEC) demonstrating a previously unappreciated complexity. However, there are only very few cell markers that allow a comparable phenotypic identification of TEC. Here we deconvoluted by massively parallel flow cytometry and machine learning known and novel TEC phenotypes into novel subpopulations and related these by CITEseq to the corresponding TEC subtypes defined by the cells individual RNA profiles. This approach phenotypically identified perinatal cTEC, physically located these cells within the cortical stromal scaffold, displayed their dynamic change during the life course and revealed their exceptional efficiency in positively selecting immature thymocytes. Collectively, we have identified novel markers that allow for an unprecedented dissection of the thymus stromal complexity, the cells physical isolation and assignment of specific functions to individual TEC subpopulations.

immunology↗

bioRxiv2021

ZARP: An automated workflow for processing of RNA-seq data

RNA sequencing (RNA-seq) is a crucial technique for many scientific studies and multiple models, and software packages have been developed for the processing and analysis of such data. Given the plethora of available tools, choosing the most appropriate ones is a time-consuming process that requires an in-depth understanding of the data, as well as of the principles and parameters of each tool. In addition, packages designed for individual tasks are developed in different programming languages and have dependencies of various degrees of complexity, which renders their installation and execution challenging for users with limited computational expertise. The use of workflow languages and execution engines with support for virtualization and encapsulation options such as containers and Conda environments facilitates these tasks considerably. Computational workflows defined in those languages can be reliably shared with the scientific community, enhancing reusability, while improving reproducibility of results by making individual analysis steps more transparent. Here we present ZARP, a general purpose RNA-seq analysis workflow which builds on state-of-the-art software in the field to facilitate the analysis of RNA-seq data sets. ZARP is developed in the Snakemake workflow language using best software development practices. It can run locally or in a cluster environment, generating extensive reports not only of the data but also of the options utilized. It is built using modern technologies with the ultimate goal to reduce the hands-on time for bioinformaticians and non-expert users. ZARP is available under a permissive Open Source license and open to contributions by the scientific community. Contactmihaela.zavolan@unibas.ch, alexander.kanitz@unibas.ch

bioinformatics↗

bioRxiv2021

Distinct and additive effects of calorie restriction and rapamycin in aging skeletal muscle

As global life expectancy continues to climb, maintaining skeletal muscle function is increasingly essential to ensure a good life quality for aging populations. Calorie restriction (CR) is the most potent and reproducible intervention to extend health and lifespan, but is largely unachievable in humans. Therefore, identification of "CR mimetics" has received much attention. CR targets nutrient-sensing pathways centering on mTORC1. The mTORC1 inhibitor, rapamycin, has been proposed as a potential CR mimetic and is proven to counteract age-related muscle loss. Therefore, we tested whether rapamycin acts via similar mechanisms as CR to slow muscle aging. Contrary to our expectation, long-term CR and rapamycin-treated geriatric mice display distinct skeletal muscle gene expression profiles despite both conferring benefits to aging skeletal muscle. Furthermore, CR improved muscle integrity in a mouse with nutrient-insensitive sustained muscle mTORC1 activity and rapamycin provided additive benefits to CR in aging mouse muscles. Therefore, RM and CR exert distinct, compounding effects in aging skeletal muscle, opening the possibility of parallel interventions to counteract muscle aging.

physiology↗

bioRxiv2020

The transcriptional landscape of a hepatoma cell line grown on scaffolds of extracellular matrix proteins

The behavior of cells in vivo is complex and highly dynamic, as it results from an interplay between components of the intercellular matrix proteins with surface receptor and other microenvironmental cues. Although the effects of the cellular niche have been investigated for a number of cell types using different molecular approaches, comprehensive assessments of how the global transcriptome responds to 3D scaffolds composed of various extracellular matrix (ECM) constituents are still lacking. In this study, we explored the effect of the biomechanical parameters of Collagen I and Matrigel (ECM) on transcriptional gene regulation in a cell culture system. Using Huh-7 cells cultured on traditional cell culture plates or on the components of the ECM at different concentrations to modulate microenvironment properties, we have generated transcriptome sequencing data that may be further explored to understand the differentiation and growth potential of this cell for the development of 3D cultures. Assessment of the hepatocyte phenotype in relation to our transcriptomic data set would be very useful for the development of systems mimicking the in vivo structure and function of liver cells which still remains a challenge.

systems biology↗

bioRxiv2019

AGO1x prevents dsRNA-induced interferon signaling to promote breast cancer cell proliferation

Initially reported for viral RNA, elongation of polypeptide chains beyond the stop codon (translational readthrough (TR)) also occurs on eukaryotic transcripts. TR diversifies the proteome and can modulate protein levels 1-6. Here we report that AGO1x, a conserved TR isoform of Argonaute 1, is generated in highly proliferative breast cancer cells, where it curbs accumulation of double stranded RNAs, the induction of the interferon response and apoptosis. In contrast to other mammalian Argonaute protein family members with primarily cytoplasmic functions, AGO1x localizes to the nucleus, in the vicinity of nucleoli. We identify a novel interaction of AGO1x with the Polyribonucleotide Nucleotidyltransferase 1, depletion of either protein leading to dsRNA accumulation and impaired cell proliferation. Our study thus uncovers a novel function of an Argonaute protein outside of the miRNA effector pathway, in buffering dsRNA-induced interferon responses. As AGO1x expression is tightly linked to breast cancer cell proliferation, our study suggests a new direction for limiting tumor growth.

cell biology↗