Biology subjects

Burri, D.

Publications and source records attributed to Burri, D..

10 recordsLinked to original sources

bioRxiv2026

Laminin-α2 is required for the maintenance of the myotendinous junction in vivo

The myotendinous junction (MTJ) is a critical interface between muscle fibers and tendons, essential for force transmission between muscle and bone. Laminin-2, a key extracellular matrix (ECM) component, is strongly enriched at this interface. Mutations in the LAMA2 gene cause LAMA2-related muscular dystrophy (LAMA2 MD), an early-onset severe congenital muscular dystrophy. Here, we examined the MTJ in dyW/dyWmice, a mouse model for LAMA2 MD. We find a strong disruption of MTJ morphology, including altered muscle fiber tips, collagen XXII mislocalization, and reduced muscle tendon interface. As MTJ loading is altered in dyW/dyW mice and MTJ maintenance requires loading and unloading, we also examined MTJ structures upon denervation-induced unloading. While muscle fiber tip morphology resembled that of dyW/dyW mice, collagen XXII distribution was not affected and the muscle-tendon interface was preserved. Finally, proteomic profiling via laser capture microdissection and mass spectrometry revealed significant regional and global shifts in MTJ protein composition in dyW/dyW and denervated mice. Across both models, we identified integrin-associated remodeling as a shared response linked to the perturbed muscle fiber tip morphology. These findings demonstrate that laminin-2 is required for MTJ stability, and that mechanical unloading contributes to the observed phenotype. Importantly, our results suggest that disruptions in MTJ structure and protein composition may contribute to the pathology observed in LAMA2 MD.

molecular biology↗

bioRxiv2025

Non-cytolytic re-engineering of a viral vaccine vector enables durable effector-memory T cell immunity by reinforcing type I IFN induction

Replication-deficient viral vector systems hold promise for CD8 T cell-based vaccination, but the molecular mechanisms accounting for platform-specific differences in immunogenicity remain ill- defined. When comparing prototypic single-cycle vaccine delivery platforms we found that lymphocytic choriomeningitis virus-based vectors (rLCMV), which are non-cytolytic, elicited more durable and effector-memory-differentiated CD8 T cell responses than vectors based on cytolytic vesicular stomatitis virus (rVSV). Hence we re-engineered rVSV to be non-cytolytic (rVSVMq). This vector induced more durable and effector-differentiated CD8 T cell memory than the parental rVSV and it afforded superior protection against Listeria challenge. Improved CD8 T cell responses of non-cytolytic rVSVMq were driven by a reinforced type I interferon (IFN-I) response and its direct sensing by vaccination-induced CD8 T cells. Many vector cargo-specific CD8 T cells in the splenic marginal zone of rVSVMq- or rLCMV-vaccinated mice were in contact with vector cargo-expressing cells that co- expressed type I interferon. In contrast, rVSV-vectored cargo-expressing contacts of specific CD8 T cells were largely IFN type I-negative. Thereby, vaccination with non-cytolytic viral vectors offered an opportunity for CD8 T cells to integrate peptide-MHC and IFN-I signals during priming. These mechanistic insights should help to refine vaccines aimed at eliciting durable and protective effector- memory CD8 T cell immunity.

immunology↗

bioRxiv2025

Identification and proteomic profiling of CD90+ small EVs using a refined immunocapture separation approach targeting stromal-derived EV subpopulations in synovial fluid of arthritis patients

Extracellular vesicles (EVs) have emerged as essential drivers in disease progression and promising biomarkers across various disease conditions, including autoimmune diseases such as rheumatoid arthritis (RA). RA is characterized by chronic inflammation driven by patient-specific cellular sub-phenotypes within the synovium. Since EVs reflect their cellular origin and are detectable in biofluids like synovial fluid, they offer a promising alternative for novel biomarker discovery or diagnostics in arthritis, potentially reducing the need for invasive tissue biopsies. However, the inherent complexity, viscosity and extracellular matrix (ECM) composition of synovial fluid pose significant challenges for efficient EV isolation. Moreover, most previous studies have focused on heterogenous bulk EV populations, neglecting the diverse EV subsets present in patient biofluids. To address these challenges, we established a novel immunocapture-based separation method, that selectively targets and isolates cell type-specific EV subpopulation from the heterogenous EV pool present in synovial fluid of arthritis patients. As a proof-of-concept approach, we targeted a stromal-derived EV population by leveraging the fibroblast-associated surface marker CD90/THY1, representing a subset of synovial fibroblasts implicated as important drivers in synovitis and chronic inflammation in RA. Western Blot and data independent acquisition (DIA) liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) proteomic analysis of immunocaptured CD90+ EVs isolated from cultured primary synovial fibroblasts and synovial fluid of arthritis patients, confirmed the successful separation of stromal vs a myeloid/lymphoid EV populations. The in-depth proteomic profiling of synovial fluid EVs offers unprecedented insights into EV heterogeneity in arthritis. This analysis enables the classification of cell-type associated EV subsets and the identification of novel EV markers for future immunocapture-based EV separation strategies. Our refined fit-for-purpose EV separation approach, coupled to in depth proteomic profiling, provides a powerful tool to identify disease-relevant EV subpopulations and novel biomarker candidates in synovial fluid, facilitating advances in arthritis diagnostics and personalized medicine

immunology↗

bioRxiv2023

GDF15 mediates inflammation-associated bone loss through a brain-bone axis

Metabolic mediators play an important role in regulating chronic inflammation in the body. Here we report an unexpected role for GDF15 (Growth Differentiation Factor 15), a central mediator of food intake, in inflammation-associated bone loss. GDF15 serum levels were found to be elevated in arthritis patients and inversely correlated with bone density. Despite being associated with inflammation, we found that GDF15 itself does not cause, nor contribute to, clinical or histopathological arthritis. Rather, under inflammatory conditions, GDF15 mediates trabecular bone loss through its receptor GFRAL, which is exclusively expressed in the hindbrain. GDF15-GFRAL binding results in {beta}-adrenergic activation of MALPs (Marrow Adipocytic Lineage Precursors) in the bone marrow, which stimulate osteoclasts and trigger bone loss. These data suggest a metabolic mediator-controlled brain-bone axis in inflammation, through which bone loss is induced in a contextual rather than general manner. These findings may lead to more specific therapeutic interventions to protect bone.

immunology↗

bioRxiv2023

Extensible benchmarking of methods that identify and quantify polyadenylation sites from RNA-seq data

The tremendous rate with which data is generated and analysis methods emerge makes it increasingly difficult to keep track of their domain of applicability, assumptions, and limitations and consequently, of the efficacy and precision with which they solve specific tasks. Therefore, there is an increasing need for benchmarks, and for the provision of infrastructure for continuous method evaluation. APAeval is an international community effort, organized by the RNA Society in 2021, to benchmark tools for the identification and quantification of the usage of alternative polyadenylation (APA) sites from short-read, bulk RNA-sequencing (RNA-seq) data. Here, we reviewed 17 tools and benchmarked eight on their ability to perform APA identification and quantification, using a comprehensive set of RNA-seq experiments comprising real, synthetic, and matched 3'-end sequencing data. To support continuous benchmarking, we have incorporated the results into the OpenEBench online platform, which allows for seamless extension of the set of methods, metrics, and challenges. We envisage that our analyses will assist researchers in selecting the appropriate tools for their studies. Furthermore, the containers and reproducible workflows generated in the course of this project can be seamlessly deployed and extended in the future to evaluate new methods or datasets.

bioinformatics↗

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

Shortening of 3' UTRs in most cell types composing tumor tissues implicates alternative polyadenylation in protein metabolism

During pre-mRNA maturation 3 end processing can occur at different polyadenylation sites in the 3 untranslated region (3 UTR) to give rise to transcript isoforms that differ in the length of their 3UTRs. Longer 3 UTRs contain additional cis-regulatory elements that impact the fate of the transcript and/or of the resulting protein. Extensive alternative polyadenylation (APA) has been observed in cancers, but the mechanisms and roles remain elusive. In particular, it is unclear whether the APA occurs in the malignant cells or in other cell types that infiltrate the tumor. To resolve this, we developed a computational method, called SCUREL, that quantifies changes in 3UTR length between groups of cells, including cells of the same type originating from tumor and control tissue. We used this method to study APA in human lung adenocarcinoma (LUAD). SCUREL relies solely on annotated 3UTRs and on control systems, such as T cell activation and spermatogenesis gives qualitatively similar results at much greater sensitivity compared to the previously published scAPA method. In the LUAD samples, we find a general trend towards 3UTR shortening not only in cancer cells compared to the cell type of origin, but also when comparing other cell types from the tumor vs. the control tissue environment. However, we also find high variability in the individual targets between patients. The findings help to understand the extent and impact of APA in LUAD, which may support improvements in diagnosis and treatment.

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

Conventional NK cells and tissue-resident ILC1s join forces to control liver metastasis

The liver is a major metastatic target organ, and little is known about the role of immunity in controlling hepatic metastases. Here, we discovered that the concerted and non-redundant action of two innate lymphocyte subpopulations, conventional NK cells (cNKs) and tissue-resident type I Innate Lymphoid Cells (trILC1s), is essential for anti-metastatic defense. Using different preclinical models for liver metastasis, we found that trILC1 control metastatic seeding, whereas cNKs restrain outgrowth. The antimetastatic activity of cNKs is regulated in a tumor type-specific fashion. Thereby, individual cancer cell lines orchestrate the emergence of cNK subsets with unique phenotypic and functional traits. Understanding cancer-cell- as well as innate-cell-intrinsic factors will allow the exploitation of hepatic innate cells for development of novel cancer therapies. SignificanceInnate lymphoid cells hold great promise for the treatment of metastases. Development of effective therapies based on these versatile immune cells, however, is hampered by our limited knowledge of their behavior in the metastatic niche. Here, we describe that defense against liver metastasis requires the collaboration between two innate lymphocyte subsets, conventional NK cells (cNKs) and tissue-resident type I innate lymphoid cells (trILC1s). We show that different cancers generate their own particular metastatic niche inducing specific changes in cNKs and trILC1s. Further, we uncover specific cNK subsets that can be manipulated to improve their anti-metastatic potential. Our work contributes to understanding how cancer-specific factors and hepatic innate lymphocytes exert mutual influence and how this can be exploited for therapeutic purposes. HighlightsO_LIcNKs and trILC1s collaborate to control hepatic metastasis C_LIO_LItrILC1s restrict seeding and cNKs control outgrowth of cancer cells in the liver C_LIO_LIIndividual cancer cell lines orchestrate a distinct metastatic niche C_LIO_LIThe metastatic niche dictates the phenotype and function of cNKs C_LI

immunology↗

bioRxiv2019

Spatial structure governs the mode of tumour evolution

Characterizing the mode - the way, manner, or pattern - of evolution in tumours is important for clinical forecasting and optimizing cancer treatment. DNA sequencing studies have inferred various modes, including branching, punctuated and neutral evolution, but it is unclear why a particular pattern predominates in any given tumour.1, 2 Here we propose that differences in tumour architecture alone can explain the variety of observed patterns. We examine this hypothesis using spatially explicit population genetic models and demonstrate that, within biologically relevant parameter ranges, human tumours are expected to exhibit four distinct onco-evolutionary modes (oncoevotypes): rapid clonal expansion (predicted in leukaemia); progressive diversification (in colorectal adenomas and early-stage colorectal carcinomas); branching evolution (in invasive glandular tumours); and effectively almost neutral evolution (in certain non-glandular and poorly differentiated solid tumours). We thus provide a simple, mechanistic explanation for a wide range of empirical observations. Oncoevotypes are governed by the mode of cell dispersal and the range of cell-cell interaction, which we show are essential factors in accurately characterizing, forecasting and controlling tumour evolution.

cancer biology↗