Biology subjects

Joppich, M.

Publications and source records attributed to Joppich, M..

6 recordsLinked to original sources

bioRxiv2025

PLO(SC)2: Plots and Scripts for scRNA-seq analysis

BackgroundscRNA-seq analysis has become a standard technique for studying biological systems. As costs decrease, scRNA-seq experiments become increasingly complex. While typical scRNA-seq analysis frameworks provide basic functionality to analyze such data sets, downstream analysis and visualization become a bottleneck. Standard plots are not always suitable to provide specific insight into such complex data sets and should be extended to provide camera-ready, meaningful plots. ResultsWith PLO(SC)2, a collection of plotting and analysis scripts for use in Seurat-based scRNA-seq data analyses is presented, which are accessible for custom script-based analyses or within an R shiny app. The analysis scripts mainly provide a collection of code blocks which enable a comfortable basic analysis of scRNA-seq data from Seurat object creation, filtering, and over data set integration in less than 10 function calls. Subsequently, code blocks for performing differential and enrichment analyses and corresponding visualizations are provided. Finally, several enhanced visualizations are provided, such as the enhanced Heatmap, DotPlot and comparative Box-/Violin plots. These, particularly, allow the user to specify how the shown values should be scaled, allowing the accurate creation of condition-wise plots. ConclusionWith the PLO(SC)2 framework data analysis of scRNA-seq experiments is performed more comfortable and stream-lined, while visualizations are enhanced to be suitable for interpreting complex datasets. The PLO(SC)2 scripts are available from GitHub and include a vignette showing how PLO(SC)2 is applied within a script-based analysis, as well as an R shiny app.

bioinformatics↗

bioRxiv2025

Text Mining miRNA-gene Interactions for the mx-plore Platform

miRNAs are post-transcriptional regulators which bind to the specific mRNA of expressed genes and induce increased mRNA degradation, thereby reducing the gene expression of their target genes. miRNAs perform their regulatory functions in a context-specific manner. Several databases contain collections of miRNA-target interactions, which are either experimentally validated, derived from high-throughput experiments, or computationally predicted or captured from existing literature. For most databases, the specific context of the miRNA-target interaction is unknown or missing in these databases. mx-plore is not only a database of text-dervied miRNA-gene interactions, but it enhances the found interactions including detailed context information from scientific publications. To derive the entries in the mx-plore database, a newly developed text mining strategy combining dependency graph analysis and rule-based systems has been used. The mx-plore platform makes miRNA-gene interactions accessible and searchable on various levels, such as by cell type, disease or involved processes. The platform is available at https://rest.bio.ifi.lmu.de/mxplore and corresponding source code is deposited on GitHub. Author summaryO_LIThe mx-plore platform is a comprehensive database of miRNA:target interactions as described in the scientific literature. C_LIO_LImx-plore is a new text-mining approach to extract context-dependent miRNA interactions from Pubmed abstracts and PMC full texts. C_LIO_LImx-plore allows to query the comprehensive database in a context-specific manner, both on- and off-line. C_LI

bioinformatics↗

bioRxiv2024

PICASO: Profiling Integrative Communities of Aggregated Single-cell Omics data

Various single-cell modalities covering transcriptomics, epigenetic and spatio-temporal changes in health and disease phenotypes are used in an exploratory way to understand biological systems at single-cell resolution. However, the vast amount of such single-cell data is not systematically linked to existing biomedical data. Networks have previously been used to represent harmonized biomedical data. Integrating various resources of biomedical data in networks has recently received increasing attention. These aggregated networks can provide additional insight into the biology of complex human diseases at cell-type level, however, lack inclusion of single cell expression data. Here, we present the PICASO framework, which incorporates single-cell gene expression data as an additional layer to represent associations between cell types, disease phenotypes, drugs and genes. The PICASO network includes several standardized biomedical databases such as STRING, Uniprot, GeneOntology, Reactome, OmniPath and OpenTargets. Using multiple cell type-specific instances of the framework, each annotated and scored with their respective expression data, comparisons between disease states can be made by computing respective sub-networks and comparing the expression scores between conditions. Ultimately, these group-specific networks will allow the identification of relevant genes, processes and potentially druggable targets, as well as the comparison of different measured groups and thus the identification of group-specific communities and interactions.

bioinformatics↗

bioRxiv2024

Immunothrombolytic monocyte-neutrophil axes dominate the single-cell landscape of human thrombosis

AbstractThrombotic diseases remain the major cause of death and disability worldwide with insufficient preventive and therapeutic strategies available. In the last decades a prominent inflammatory component has been identified as a key driver in the initiation and propagation of thrombosis - named thromboinflammation. However, a comprehensive investigation of the human immune system in thromboinflammation, beyond histological quantification, is lacking, which is essential for the development of novel therapeutic approaches. We therefore mapped the trajectories, functional states, and intercommunication of immune cells in stroke thrombi, retrieved by thrombectomy, at single-cell resolution. We reveal distinct leukocyte subpopulations with prothrombotic and, surprisingly, prominent fibrinolytic properties characterized by aberrant activation of intracellular host defense as well as hypoxia induced pathways. A prominent thrombolytic PLAUhigh, PLAURhigh, THBDhigh thrombus neutrophil subset, also expressing high levels of pro-recanalizing VEGFA and VEGFB, dominated the thrombus neutrophil environment. On the other hand CD16high NR4A1high non-classical monocytes with strong CXCL8, CXCL2, CXCL1 and CXCL16 mediated neutrophil- attracting and PLAU, PLAUR, THBD and TFPI mediated thrombolytic properties defined the thrombus monocyte environment. These thrombus monocyte subsets were characterized by high expression of TIMP1 and TREM1. These novel innate immune- cell subsets provide insights into the thrombogenic and pro-resolving properties of innate immune-cells. To provide mechanistic insight into these multi-omic findings, we utilized reverse translation approaches. In vitro as well as murine in vivo thrombosis models underlined the causal relevance of these immune-cell axes for thrombolysis: NR4A1high thrombus monocytes acquired a neutrophil-chemoattractive transcriptomic phenotype, neutrophils continuously infiltrated established murine thrombi in vivo and acquired a HIF1-mediated thrombolytic phenotype in vitro. A depletion of NR4A1high thrombus monocytes reduced thrombus neutrophil influx and exacerbated thrombosis in vivo. Together, this unravels cross-communicating monocyte and neutrophil subsets with thrombus-resolving properties and provide a publicly accessible immune-landscape of thrombosis. This provides a valuable resource for future research on thrombo- inflammation and might pave the way for novel immune-modulatory approaches for prevention or resolution of thrombosis.

immunology↗

bioRxiv2023

Resident and recruited macrophages differentially contribute to cardiac healing after myocardial ischemia

Cardiac macrophages are heterogenous in phenotype and functions, which has been associated with differences in their ontogeny. Despite extensive research, our understanding of the precise role of different subsets of macrophages in ischemia/reperfusion injury remains incomplete. We here investigated macrophage lineages and ablated tissue macrophages in homeostasis and after I/R injury in a CSF1R-dependent manner. Genomic deletion of a fms-intronic regulatory element (FIRE) in the Csf1r locus resulted in specific absence of resident homeostatic and antigen-presenting macrophages, without affecting the recruitment of monocyte-derived macrophages to the infarcted heart. Specific absence of homeostatic, monocyte-independent macrophages altered the immune cell crosstalk in response to injury and induced proinflammatory neutrophil polarization, resulting in impaired cardiac remodelling without influencing infarct size. In contrast, continuous CSF1R inhibition led to depletion of both resident and recruited macrophage populations. This augmented adverse remodelling after I/R and led to an increased infarct size and deterioration of cardiac function. In summary, resident macrophages orchestrate inflammatory responses improving cardiac remodelling, while recruited macrophages determine infarct size after I/R injury. These findings attribute distinct beneficial effects to different macrophage populations in the context of myocardial infarction. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=88 SRC="FIGDIR/small/539799v4_ufig1.gif" ALT="Figure 1"> View larger version (34K): org.highwire.dtl.DTLVardef@14fa4bcorg.highwire.dtl.DTLVardef@1c86bbborg.highwire.dtl.DTLVardef@118edfcorg.highwire.dtl.DTLVardef@1b06916_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

bioRxiv2021

Protective immune trajectories in early viral containment of non-pneumonic SARS-CoV-2 infection

The immune system of most SARS-CoV-2 infected individuals limits viral spread to the upper airways without pulmonary involvement. This prevents the development of pneumonic COVID-19. However, the protective immunological responses causative of successful viral containment in the upper airways remain unclear. Here, we combine longitudinal single-cell RNA sequencing, proteomic profiling, multidimensional flow cytometry, RNA-Seq of FACS-sorted leukocyte subsets and multiplex plasma interferon profiling to uncover temporally resolved protective immune signatures in non-pneumonic and ambulatory SARS-CoV-2 infected patients. We compare host responses in a high-risk patient population infected with SARS-CoV-2 but without pulmonary involvement to patients with COVID-19 pneumonia. Our data reveal a distinct immunological signature of successful viral containment, characterized by an early prominent interferon stimulated gene (ISG) upregulation across immune cell subsets. In addition, reduced cytotoxic potential of Natural Killer (NK) and T cells, as well as a monocyte phenotype with immune-modulatory potential are hallmarks of protective immunity. Temporal resolution across disease trajectories highlights ISG upregulation as particularly prominent early in the disease and confirms increased expression also in comparison to healthy controls. We validate this distinct temporal ISG signature by in-depth RNA-seq of FACS-sorted leukocyte subsets in a large prospective ambulatory SARS-CoV-2 infected cohort confirming early and robust ISG upregulation particularly in monocytes and T cells. In conclusion, our data demonstrate a protective ISG phenotype in patients with successful containment of SARS-CoV-2 infection without progression to COVID-19. This early protective interferon response might be exploited as a therapeutic approach and for disease course prediction.

immunology↗