Biology subjects

Hagen, L.

Publications and source records attributed to Hagen, L..

7 recordsLinked to original sources

bioRxiv2026

The interactome of the receptor kinase THESEUS1 reveals how cell wall integrity is linked to hormone signalling in Arabidopsis

The receptor kinase THESEUS1 (THE1) activates responses to impairment of cell wall integrity (CWI). However, the interaction partners enabling THE1 to mediate the responses remain underexplored, impeding a mechanistic understanding of THE1. We produced a set of THE1 GFP fusion constructs in which THE1 is either wild type, mutated in its kinase domain, has a loss of function mutation in its ectodomain, or lacks the kinase or extracellular domain. We used these constructs to perform localization studies and immunoprecipitation liquid chromatography tandem mass spectrometry under control and stress conditions (isoxaben induced cell wall damage and sorbitol induced hyperosmotic stress) to identify the THE1 interactome. The interactome of THE1 changed in a context dependent manner, linking THE1 to known signaling components in CWI maintenance and phytohormone response (such as proton pumps, calcium pumps, other receptor kinases or cellulose synthesis regulators). Moreover, we identified novel interactors, associating THE1 with hitherto unexplored signaling pathways in response to CWI impairment. Our results also suggest that the THE1G37D protein (corresponding to the the1 1 allele) is retained in the endoplasmic reticulum, explaining its loss of function phenotype. The THE1 interactome and localization data provide the foundation to build a mechanistic understanding of THE1 mediated CWI maintenance.

plant biology↗

bioRxiv2026

Prostaglandin E2 facilitates reciprocal crosstalk between intestinal smooth muscle tissue and epithelium in tumor development

Colorectal cancer arises from intestinal epithelial cells and is driven by the accumulation of aberrant signaling events that disrupt intestinal stem cell (ISC) homeostasis. While stromal regulation of the ISC niche is increasingly recognized, the contribution of the underlying/adjacent smooth muscle tissue (SMT) remains poorly characterized. In particular, the potential crosstalk between normal or tumoral epithelium and the SMT is largely unexplored. Here, we investigate the ability of the SMT in modulating normal and tumorigenic epithelial biology, and the impact of the tumoral epithelium on the underlying SMT. Mechanistically, by using imaging analyses, transcriptomics, and mass spectrometry, we identify the SMT-derived factor Prostaglandin E2 (PGE2) as the key driver of epithelial dedifferentiation, promoting YAP transcriptional activation, organoid enlargement, and spheroid morphology in intestinal epithelial organoids following SMT supernatant exposure. Conversely, we show that non-invasive tumoral epithelium induces significant changes in the underlying SMT. Tumor-associated SMT shows structural remodeling, inflammation, and reduced muscle fitness. Furthermore, we detected increased prostaglandin signaling, including upregulation of PGE2 synthase Ptgs1 (COX1), in the SMT underneath the epithelial tumor. Our results reveal a communication between the tumoral epithelium and the underlying SMT prior to metastasis, which could be a facilitating step for tumoral extramural progression. Taken together, these findings highlight a novel tumor-stroma interaction.

Molecular Biology↗

bioRxiv2025

FHIR as a Unifying Format for Genomic Research Data Tracking, Aggregation, and Integration

The increasing complexity of genomic research demands standardized data sharing and integration. The Fast Healthcare Interoperability Resources (FHIR) specification has become a well-established standard for exchanging data among health data systems. While designed primarily for clinical and patient data in health care environments, it also has applicability to represent genomic research data and offers a path for aggregating and integrating extremely rich datasets that have traditionally remained siloed and disparate. To study this potential, we developed FHIR Aggregator, an integration of seven major biomedical repositories, including the Genomic Data Commons, GTEx, HTAN, and DepMap, that covered 142334 patients, 819251 specimens, 1096491 observations and 711166 documents. We explore the various ways the FHIR standard can be applied to structure genomic research data and enable new possibilities. We demonstrate how FHIR can be used, where it succeeds or falls short, and which concepts must be extended to better support large-scale clinical and genomics research projects.

bioinformatics↗

bioRxiv2025

Knowledge Discovery in Datasets of Proteomics by Systems Modeling in Translational Research on Pancreatic Cancer

Knowledge discovery in databases (KDD) can contribute to translational research, also known as translational medicine, by bridging the gap between in vitro and in vivo studies and clinical applications. Here, we propose a systems modeling workflow for KDD. This framework includes data collection of composition model (various research models) and processing model (proteomics) and analytical model (bioinformatics, artificial intelligence/machine leaning and pattern evaluation), knowledge presentation, and feedback loops for hypothesis generation and validation. We applied this workflow to study pancreatic ductal adenocarcinoma (PDAC). Through this approach, we identified the common proteins between human PDAC and various research models in vitro (cells, spheroids and organoids) and in vivo (mouse mice). Accordingly, we hypothesized potential translational targets on hub proteins and the related signaling pathways, PDAC specific proteins and signature pathways, and high topological proteins. Thus, we suggest that this systems modeling workflow can be a valuable method for KDD, facilitating knowledge discovery in translational targets in general and in particular to PADA in this case.

systems biology↗

bioRxiv2023

Mutation Patterns Predict Drug Sensitivity in Acute Myeloid Leukemia

Acute myeloid leukemia (AML) is an aggressive malignancy of myeloid progenitor cells characterized by successive acquisition of genetic alterations. This inherent heterogeneity poses challenges in the development of precise and effective therapies. To gain insights into the genetic influence on drug response and optimize treatment selection, we performed targeted sequencing, ex vivo drug screening, and single-cell genomic profiling on leukemia cell samples derived from AML patients. We detected genetic signatures associated with sensitivity or resistance to specific agents. By integrating large public datasets, we discovered statistical patterns of co-occurring and mutually exclusive mutations in AML. The application of single-cell genomic sequencing unveiled the co-occurrence of variants at the individual cell level, highlighting the presence of distinct sub- clones within AML patients. Machine learning models were built to predict ex vivo drug sensitivity using the genetic variants. Notably, these models demonstrated high accuracy in predicting sensitivity to some drugs, such as MEK inhibitors. Our study provides valuable resources for characterizing AML patients and predicting drug sensitivity, emphasizing the significance of considering subclonal distribution in drug response prediction. These findings provide a foundation for advancing precision medicine in AML. By tailoring treatment based on individual genetic profiles and functional testing, as well as accounting for the presence of subclones, we envision a future of improved therapeutic strategies for AML patients. One Sentence SummaryIntegrative computational and experimental analysis of mutation patterns and drug responses provide biologic insight and therapeutic guidance for patients with adult AML.

cell biology↗

bioRxiv2022

MultiOMICs landscape of SARS-CoV-2-induced host responses in human lung epithelial cells

Despite the availability of vaccines and approved therapeutics, the COVID-19 pandemic continues to rise owing to the emergence of newer variants. Several multi-omics studies have made available extensive evidence on host-pathogen interactions and potential therapeutic targets. Nonetheless, an increased understanding of host signaling networks regulated by post-translational modifications and their ensuing effect on the biochemical and cellular dynamics is critical to expanding the current knowledge on the host response to SARS-CoV-2 infections. Here, employing unbiased global transcriptomics, proteomics, acetylomics, phosphoproteomics, and exometabolome analysis of a lung-derived human cell line, we show that SARS-CoV-2 Norway/Trondheim-S15 strain induces time-dependent alterations in the induction of type I IFN response, activation of DNA damage response, dysregulated Hippo signaling, among others. We provide evidence for the interplay of phosphorylation and acetylation dynamics on host proteins and its effect on the altered release of metabolites, especially organic acids and ketone bodies. Together, our findings serve as a resource of potential targets that can aid in designing novel host-directed therapeutic strategies.

systems biology↗

bioRxiv2020

Antiviral options against SARS-CoV-2 infection

As of June 2020, the number of people infected with severe acute respiratory coronavirus 2 (SARS-CoV-2) continues to skyrocket, with more than 6,5 million cases worldwide. Both the World Health Organization (WHO) and United Nations (UN) has highlighted the need for better control of SARS-CoV-2 infections. However, developing novel virus-specific vaccines, monoclonal antibodies and antiviral drugs against SARS-CoV-2 can be time-consuming and costly. Convalescent sera and safe-in-man broad-spectrum antivirals (BSAAs) are readily available treatment options. Here we developed a neutralization assay using SARS-CoV-2 strain and Vero-E6 cells. We identified most potent sera from recovered patients for treatment of SARS-CoV-2-infected patients. We also screened 136 safe-in-man broad-spectrum antivirals against SARS-CoV-2 infection in Vero-E6 cells and identified nelfinavir, salinomycin, amodiaquine, obatoclax, emetine and homoharringtonine. We found that combinations of virus-directed nelfinavir along with host-directed amodiaquine exhibited the highest synergy. Finally, we developed a website to disseminate the knowledge on available and emerging treatments of COVID-19.

microbiology↗