Biology subjects

Jost, P. J.

Publications and source records attributed to Jost, P. J..

8 recordsLinked to original sources

bioRxiv2025

miR-196a-5p and miR-342-3p mediate skeletal muscle and thermogenic adipose tissue crosstalk through extracellular vesicles

Small extracellular vesicles (small EVs) are nanovesicles found in tissues and body fluids that contain regulatory molecules including microRNAs, termed exomiRs. Research in murine models has demonstrated that exercise can trigger the release of small EVs into the circulation. The aim of this study was to study exomiR release in humans pre and post exercise and to characterise the function of these microRNAs especially in relation to thermogenic fat. We found that exercise increased the release of exomiR-196a-5p in endurance athletes, a microRNA that induces UCP1 expression and browning of white adipocytes. We observed that myotubes specifically release miR-196a-5p within small EVs after in vitro exercise-mimicking conditions such as electrical pulse stimulation and cAMP treatment. Likewise, the expression at basal levels of the exercise-induced exomiR-342-3p negatively correlated with BMI and age. EV proteomics revealed a positive correlation between FABP4+ and miR-342-3p, suggesting an adipocyte cell origin. Overexpression of miR-342-3p increased Myogenin levels during skeletal muscle cell differentiation, indicating a positive role in muscle differentiation. Our results suggest that oxidative extreme metabolic capacities in endurance athletes contribute to the enhanced release of circulatory exomiRs after exercise mediating bi-directional crosstalk between skeletal muscle and thermogenic adipose tissue. Graphical abstractO_LISerum-EVs from endurance athletes increase UCP1 expression in white adipocytes. C_LIO_LImiR-196a and miR-342-3p are increased in serum-EVs from endurance athletes. C_LIO_LIMuscle cells release EVs enriched in miR-196a after electrical pulse stimulation. C_LIO_LImiR-196a and miR-342-3p have browning and myogenic potential, respectively. C_LI O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=143 SRC="FIGDIR/small/656129v1_ufig1.gif" ALT="Figure 1"> View larger version (31K): org.highwire.dtl.DTLVardef@1bd9b25org.highwire.dtl.DTLVardef@114a549org.highwire.dtl.DTLVardef@6f863borg.highwire.dtl.DTLVardef@1d5c528_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology↗

bioRxiv2025

Pseudo-time trajectory of single-cell lipidomics: Suggestion for experimental setup and computational analysis

Cellular heterogeneity is a fundamental facet of cell biology, influencing cellular signaling, metabolism, and gene regulation. Its accurate quantification requires measurements at the single-cell level. Most high-throughput single-cell technologies provide only a snapshot of cellular heterogeneity at a specific time point because the measurement is destructive. This limits our current ability to understand the dynamics of cellular behavior and quantify cell-specific parameters. We propose an experimental setup combined with a model-based analysis framework, enabling the extraction of longitudinal data from a single destructive measurement. Although broadly applicable, we focus on lipid metabolism, a domain where obtaining longitudinal single-cell data has remained elusive due to technical constraints. Our method leverages multiple labels whose measurements are linked to a shared dynamic. This allows the estimation of cell-specific parameters and the quantification of heterogeneity. This framework establishes a foundation for future investigations, providing a roadmap toward a deeper understanding of dynamic cellular processes.

systems biology↗

bioRxiv2024

cOmicsArt - a customizable Omics Analysis and reporting tool

MotivationThe availability of bulk-omic data is steadily increasing, necessitating collaborative efforts between experimental and computational researchers. While software tools with graphical user interfaces (GUIs) enable rapid and interactive data assessment, they are limited to pre-implemented methods, often requiring transitions to custom code for further adjustments. However, most available tools lack GUI-independent reproducibility such as direct integration with R, resulting in very limited support for transition. ResultsWe introduce the customizable Omics Analysis and reporting tool - cOmicsArt. cOmicsArt aims to enhance collaboration through integration of GUI-based analysis with R. The GUI allows researchers to perform user-friendly exploratory and statistical analyses with interactive visualizations and automatic documentation. Downloadable R scripts and results ensure reproducibility and seamless integration with R, supporting both novice and experienced programmers by enabling easy customizations and serving as a foundation for more advanced analyses. This versatility also allows for usage in educational settings guiding students from GUI-based analysis to R Code. AvailabilitycOmicsArt is freely available at https://shiny.iaas.uni-bonn.de/cOmicsArt/ User documentation is available at https://icb-dcm.github.io/cOmicsArt/ Source code is available on GitHub https://github.com/ICB-DCM/cOmicsArt A docker image can be retrieved from https://hub.docker.com/r/pauljonasjost/comicsart/tags A snapshot upon publication can be found on Zenodo: https://zenodo.org/records/13740904 A screen recording of cOmicsArt is available at: https://www.youtube.com/watch?v=pTGjtIYQOakp Contactjan.hasenauer@uni-bonn.de Supplementary informationSupplementary data are available online.

bioinformatics↗

bioRxiv2022

Proteogenomic analysis reveals RNA as an important source for tumor-agnostic neoantigen identification correlating with T-cell infiltration

Systemic pan-tumor analyses may reveal the significance of common features implicated in cancer immunogenicity and patient survival. Here, we provide a comprehensive multi-omics data set for 32 patients across 25 tumor types by combining proteogenomics with phenotypic and functional analyses. By using an optimized computational approach, we discovered a large number of novel tumor-specific and tumor-associated antigens including shared common target candidates. To create a pipeline for the identification of neoantigens in our cohort, we combined deep DNA and RNA sequencing with MS- based immunopeptidomics of tumor specimens, followed by the assessment of their immunogenicity. In fact, we could detect a broad variety of non-wild type HLA-binding peptides in the majority of patients and confirmed the immunogenicity of 24 neoantigens. Most interestingly, the majority of total and immunogenic neoantigens originated from variants identified in the RNA dataset, illustrating the importance of RNA as a still understudied source of cancer antigens. Moreover, the amount of these mainly RNA-based immunogenic neoantigens correlated positively with overall CD8+ tumor-infiltrating T cells. This study therefore underlines the importance of RNA-centered variant detection for the identification of shared biomarkers and potentially relevant neoantigen candidates. Statement of significanceThe significance of this study lies not only in the potential of our optimized proteogenomic workflow for the discovery of neoantigens (in particular RNA-derived neoantigens) for clinical application, but sheds light on the entity-agnostic prevalence of HLA class I peptide presentation of RNA processing events to be used for tumor targeting.

cancer biology↗

bioRxiv2022

Tyrosine kinase inhibitors trigger lysosomal damage-associated cell lysis to activate the NLRP3 inflammasome

Inflammasomes are intracellular protein complexes that control proteolytic maturation and secretion of inflammatory interleukin-1 (IL-1) family cytokines and are thus important in host defense. While some inflammasomes are activated simply by binding to pathogen-derived molecules, others, including those nucleated by NLRP3 and NLRP1, have more complex activation mechanisms that are not fully understood. We screened a library of small molecules to identify new inflammasome activators that might shed light on activation mechanisms. In addition to validating dipeptidyl peptidase (DPP) inhibitors as NLRP1 activators, we find that clinical tyrosine kinase inhibitors (TKIs) including imatinib and masitinib activate the NLRP3 inflammasome. Mechanistically, these TKIs cause lysosomal swelling and damage, leading to cathepsin-mediated destabilization of myeloid cell membranes and cell lysis. This is accompanied by potassium (K+) efflux, which activates NLRP3. Both lytic cell death and NLRP3 activation but not lysosomal damage induced by TKIs are prevented by the cytoprotectant high molecular weight polyethylene glycol (PEG). Our study establishes a screening method that can be expanded for inflammasome research and immunostimulatory drug development, and provides new insight into immunological off-targets that may contribute to efficacy or adverse effects of TKIs. One Sentence SummaryA functional small molecule screen identifies imatinib, masitinib and other tyrosine kinase inhibitors that destabilize myeloid cell lysosomes, leading to cell lysis and K+ efflux-dependent NLRP3 inflammasome activation.

immunology↗

bioRxiv2020

In vivo inducible reverse genetics in patients' tumors to identify individual therapeutic targets

High-throughput sequencing describes multiple alterations in each tumor (1), but their functional relevance is often unclear. Clinic-close, individualized molecular model systems are required for functional validation and to identify therapeutic targets of high significance for each patient (2). Here, we established a Cre-ERT2-loxP based inducible RNAi-mediated gene silencing system in patient-derived xenograft (PDX) models of acute leukemias in vivo. Mimicking anti-cancer therapy in patients, gene inhibition was initiated in mice harboring orthotopic tumors. Fluorochrome guided, competitive in vivo trials identified a major tumor-maintaining potency of the MLL-AF4 fusion protein and validated MCL1 as vulnerability in some, but not all patients tumors. We could prove DUX4 to play an essential role in patients leukemias carrying the recently described DUX4-IGH translocation. By individualizing functional genomics in established tumors in vivo, our technique decisively complements the value chain of precision oncology. Being broadly applicable to tumors of all kinds, it will considerably reinforce personalizing anti-cancer treatment in the future.

cancer biology↗

bioRxiv2019

Inferring immunological control mechanisms from TKI dose alterations in CML patients

Recent clinical findings in chronic myeloid leukemia (CML) patients suggest that the risk of molecular recurrence after stopping tyrosine kinase inhibitors (TKI) treatment substantially depend on an individual, leukemia-specific immune response. However, it is still not possible to prospectively identify patients that will most likely remain in a long-term treatment free remission (TFR). Here, we use a mathematical model for CML, which explicitly includes an anti-leukemic (presumably immunological) effect and apply it to a set of patients (n=60) for whom BCR-ABL/ABL time courses had been quantified before and after TKI stop. We demonstrate that such a feedback control is conceptually necessary to explain long-term remission as observed in about half of the patients. Based on simulation results we classify the patient data sets into three different groups according to their predicted immune system configuration. While one class of patients requires a complete CML eradication to achieve TFR, other patients are able to control the leukemia after treatment cessation. Among them, we identified a third class of patients, which only maintains TFR if an optimal balance between leukemia abundance and immunological activation is achieved before treatment cessation. Further, we demonstrate that the immune response classification of the patients cannot be obtained solely from BCR-ABL measurements before treatment cessation. However, our results strongly suggest that changes in the BCR-ABL dynamics arising after system perturbations, such as TKI dose reduction, holds the information to predict the individual outcome after treatment cessation.

systems biology↗

bioRxiv2019

TNFR2 induced priming of NLRP3-inflammasome via RIPK1 leads to pyroptosis in XIAP deficient cells

Recent data suggests that LPS stimulation can trigger inflammasome activation through a TNFR2/TNF/TNFR1 mediated loop in xiap-/- macrophages. Yet, the direct role TNFR2-specific activation plays in the absence of XIAP is unknown. We found TNFR2-specific activation lead to cell death in xiap-/- myeloid cells, particularly in the absence the RING domain. RIPK1/TAK1 kinase activity downstream of TNFR2 resulted in a TNF/TNFR1 cell death independent of necroptosis. TNFR2-specific activation lead to a similar inflammatory NF-kB driven transcriptional profile as TNFR1 activation with the exception of up-regulation of NLRP3 and caspase-11. Activation and up-regulation of the canonical inflammasome was mediated by RIPK1 kinase activity and ROS production. While both RIPK1 kinase activity and ROS production reduced cell death as well as release of IL-1{beta}, the release of IL-18 was not reduced to basal levels. This study supports, targeting TNFR2 specifically to reduce IL-18 release in XIAP deficient (XLP-2) patients.

immunology↗