Biology subjects

Frey, D.

Publications and source records attributed to Frey, D..

9 recordsLinked to original sources

bioRxiv2026

EWSR1::ATF1 hyperactivation via TRIM11 depletion triggers lethal metabolic rewiring in clear cell sarcoma

Clear cell sarcoma (CCS) is an ultra-rare and aggressive soft tissue sarcoma driven by the EWSR1::ATF1 fusion oncoprotein. Currently, no effective and well-tolerated treatment options are available to CCS patients. Direct inhibition of fusion transcription factors is precluded by the absence of defined ligand-binding pockets, whereas their abundance is under the control of the ubiquitin-proteasome system (UPS), offering an alternative avenue for biology-guided treatment. Here we show the abundance of EWSR1::ATF1 is tightly regulated by the UPS, and that release of this constraint is lethal to CCS cells. A reporter-based CRISPR/Cas9 knockout screen of UPS components identified TRIM11 as an E3 ligase that regulates turnover of EWSR1::ATF1, which it recognises as a neosubstrate without altering wild-type EWSR1 or ATF1. Depletion of TRIM11 increased nuclear fusion protein abundance, amplified the fusion-driven transcriptional programs and reduced viability. Proteomic analysis identified the cataplerotic enzyme phosphoenolpyruvate carboxykinase 1 (PCK1), a direct EWSR1::ATF1 target, as the key mediator of lethal effects of fusion hyperactivation. Extracellular flux analysis, isotope tracing and quantitative metabolomics revealed excessive cataplerotic carbon withdrawal and impaired oxidative phosphorylation as the underlying mechanism. In patient tumors, high PCK1 expression associated with metastatic transcriptome programs and disease presentation, as well as shorter survival. Taken together, we report that hyperactivation of EWSR1::ATF1 opens a metabolic vulnerability, establishing TRIM11 as an actionable dependency and PCK1 as a candidate prognostic biomarker in CCS.

cancer biology↗

bioRxiv2026

BAF complex-independent gene activation by SS18::SSX

In synovial sarcoma, the BAF subunit SS18 is fused to SSX, a transcriptional repressor, generating the oncogenic SS18::SSX fusion protein. Incorporation of SS18::SSX into BAF complexes leads to their aberrant retargeting to Polycomb-repressed genes via SSX, while simultaneously altering their composition and activity. The presence of BAF at Polycomb target sites is widely assumed to be essential for gene activation. Here, we directly tested the requirement for BAF activity in synovial sarcoma cell survival and SS18::SSX-driven transcription. Using targeted degradation of BAF ATPase subunits and deletion of core components, we show that BAF loss has modest effects on sarcoma cell viability and does not impede SS18::SSX target gene expression. Consistently, deletion of the BAF ATPase subunit Smarca4 does not impair SS18::SSX-driven tumor formation in vivo. Using domain-specific SS18::SSX mutants, we further demonstrate that the fusion can activate oncogenic transcription independently of BAF interaction, and that this activity depends on the C-terminal QPGY-rich domain of SS18. Mechanistically, SS18::SSX promotes transcription by engaging the histone acetyltransferase EP300, independently of BAF. Accordingly, pharmacologic degradation of EP300/CREBBP suppresses SS18::SSX-driven transcriptional programs and impairs synovial sarcoma cell survival. Together, these findings challenge the view that BAF activity is required for SS18::SSX-mediated transcriptional activation and demonstrate that aberrant Polycomb target gene expression is sustained through recruitment of transcriptional coactivators in the absence of BAF. Our work reveals new therapeutic vulnerabilities in synovial sarcoma and suggests broader relevance for targeting coactivator-dependent transcription in fusion-driven cancers. HighlightsO_LIBAF degradation does not alter SS18::SSX-activated transcriptional programs C_LIO_LIDirect SS18::SSX transcriptional activation is independent of BAF interaction C_LIO_LIThe SS18 C-terminus engages the co-activator EP300 to promote gene expression C_LIO_LISmall molecule degraders of EP300/CREBBP abolish SS18::SSX-mediated transcription C_LI

cancer biology↗

bioRxiv2025

Internally twin-Strep tagged CD63 for rapid and efficient isolation of engineered extracellular vesicles encapsulating functional proteins

Extracellular vesicles (EVs) are important mediators of intercellular communication. Achieving high purity of intact engineered EVs through separation from the overwhelming background of unmodified vesicles and cellular or serum-derived contaminants remains a major challenge, yet is critical for fundamental studies of EV biology and EV-based therapeutics. To address this unmet need, we applied structure-guided engineering to canonical EV tetraspanins. Focusing on CD63 and CD9, we identified sites for internal insertion of the twin-Strep tag via flexible linkers into unstructured regions of their large extracellular loops. This design retains functional properties of the scaffolds while providing a robust molecular handle enabling rapid, efficient, and selective antibody-free affinity-based isolation of intact EVs using advanced Strep technology. Fusing proteins of interest (POIs) to the C-terminus of these scaffolds, either directly or via a photoactivatable protein, allowed POI loading into the lumen of twin-Strep tagged EVs with optional optogenetic control of POI release. Proteomic analysis confirmed the high purity of captured engineered EVs with >96% of contaminants removed, enabling sensitive detection of numerous EV-associated proteins. We also report the efficient removal of contaminating virus particles resembling EVs in size and density. Purified engineered EVs successfully delivered an encapsulated fluorescent reporter into target cells, bypassing dye labeling commonly used to track EVs. We demonstrate endosomal escape of the reporter, facilitated by EV decoration with vesicular stomatitis virus glycoprotein, and cytoplasmic release upon optogenetic activation. Our toolbox may serve as a broadly applicable strategy for the efficient production of intact and highly pure engineered EVs to support potential fundamental or translational EV studies.

molecular biology↗

bioRxiv2025

Generating Synthetic MR Perfusion Maps from DWI and FLAIR in Acute Ischemic Stroke using Deep Learning

BackgroundMagnetic resonance imaging (MRI) is critical for acute stroke triage, but time-consuming, and often requires contrast injection for perfusion imaging. This study aimed to synthesize T-map perfusion maps from routinely available, non-contrast DWI and FLAIR using deep generative models. We hypothesized that relevant perfusion information could be inferred from these modalities to streamline imaging and reduce reliance on dynamic susceptibility contrast perfusion. MethodsAcute MRI data from 355 patients with anterior circulation stroke, including dynamic susceptibility contrast perfusion, were retrospectively collected from two European centers (Heidelberg: 2010-2018; Bordeaux: 2021-2022). Six versions of a denoising diffusion probabilistic model (DDPM) and a GAN architecture were trained to generate synthetic T-max perfusion maps from DWI, FLAIR, and infarct core mask as inputs. Performance was assessed by comparing synthetic and ground truth T-max maps using image similarity metrics. Regions with T-max >6s were compared using Dice coefficients, and mismatch volume distributions were analyzed. An ablation study quantified the contribution of each input. ResultsThe best performance was achieved by a DDPM with a 2.5D architecture using DWI, FLAIR, infarct core mask, and a perfusion-weighted loss function. It produced synthetic perfusion T-max maps with high similarity to ground truth under 110 seconds. The model showed strong spatial overlap for T-max >6s regions in internal validation (average Dice = 0.82, SD = 0.08), and external validation average (Dice 0.59, SD = 0.13), respectively. Synthetic maps closely matched ground-truth mismatch distributions, capturing key perfusion patterns. The infarct core mask played a critical role in model performance, alongside DWI and FLAIR inputs. ConclusionsWe propose a non-invasive, scalable framework to generate synthetic T-max perfusion maps from non-contrast MRI. This approach could expand access to perfusion data in acute stroke, shorten imaging protocols, and accelerate treatment decisions by eliminating the need for contrast-enhanced acquisition. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/684079v2_ufig1.gif" ALT="Figure 1"> View larger version (94K): org.highwire.dtl.DTLVardef@164235forg.highwire.dtl.DTLVardef@14e5489org.highwire.dtl.DTLVardef@190214eorg.highwire.dtl.DTLVardef@17a9e3a_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2024

Lysis buffer selection guidance for mass spectrometry-based global proteomics including studies on the intersection of signal transduction and metabolism

Prerequisite for a successful proteomics experiment is a high-quality lysis of the sample of interest, resulting in a large number of identified proteins as well as a high coverage of protein sequences. Therefore, the choice of suitable lysis conditions is crucial. Many buffers were previously employed in proteomics studies, yet a comprehensive comparison of lysate preparation conditions was so far missing. In this study, we compared the efficiency of four commonly used lysis buffers, containing the agents NP40, SDS, urea or GdnHCl, in four different types of biological samples (suspension and adherent cell lines, primary mouse cells and mouse liver tissue). After liquid chromatography-mass spectrometry (LC-MS) measurement and MaxQuant analysis, we compared chromatograms, intensities, number of identified proteins and the localization of the identified proteins. Overall, SDS emerged as the most reliable reagent, ensuring stable performance and reproducibility across diverse samples. Furthermore, our data advocated for a dual-sample lysis approach, including that the resulting pellet is lysed again after the initial lysis with a urea lysis buffer and subsequently both lysates are combined for a single LC-MS run to maximize the proteome coverage. However, none of the investigated lysis buffers proved to be superior in every category, indicating that the lysis buffer of choice depends on the proteins of interest and on the biological question. Further, we demonstrated with our systematic studies the establishment of conditions that allows to perform global proteomics and affinity purification-based interactome characterization from the same lysate. In sum our results provide guidance for the best-suited lysis buffer for mass spectrometry-based proteomics depending on the question of interest.

systems biology↗

bioRxiv2023

Distribution of the invasive Anisandrus maiche (Coleoptera: Scolytinae) in Switzerland, first record in Europe of its ambrosia fungus Ambrosiella cleistominuta, and its new association with Xylosandrus crassiusculus

In 2022, two independent insect surveys in canton Ticino (southern Switzerland) revealed the widespread occurrence of the invasive ambrosia beetle Anisandrus maiche from southern to central-upper Ticino. This species is native to east Asia and has previously been found as a non-native invasive species in the United States, Canada, western Russia, Ukraine and, in 2021, in northern Italy. Here, we present the results of several trapping studies using different trap types (bottle traps, funnel traps and Polytrap intercept traps) and attractants and a map of the distribution of the species. In total, 685 specimens of A. maiche, all female, were trapped, and the identity of selected individuals was confirmed by morphological and molecular identification based on three mitochondrial and nuclear markers (COI, 28S and CAD). Traps checked from early April to early September 2022 in intervals of two to four weeks showed that flights of A. maiche occurred mainly from June to mid-August. Isolation of fungal associates of A. maiche from beetles trapped alive revealed the presence of four fungal species, including the ambrosia fungus Ambrosiella cleistominuta, the known mutualists of A. maiche. The identity of A. cleistominuta was confirmed by comparing DNA sequences of its nuclear, internal transcribed spacer (ITS) gene with reference sequences in NCBI and BOLDSYSTEMS. This represents the first record of A. cleistominuta in Europe. Ambrosiella cleistominuta was also found in association with another non-native invasive ambrosia beetle, Xylosandrus crassiusculus, at a botanic garden in central Ticino. As ambrosia beetles usually show a high degree of fidelity with only one mutualistic fungus (in the case of X. crassiusculus normally Ambrosiella roeperi), this association is highly unusual and probably the result of lateral transfer among these non-native invasive species. Of the other fungal associates isolated from A. maiche in Ticino, Fusarium lateritium is of note as there is a possibility that A. maiche could act as a vector of this plant pathogen. We highlight several research needs that should be addressed to gain insight into the potential impact of these non-native species and to overcome problems with heteroplasmy in COI sequences in studies of invasion and population genetics of ambrosia beetles.

ecology↗

bioRxiv2022

An approach to rapid distributed manufacturing of broad spectrum anti-viral griffithsin using cell-free systems to mitigate pandemics

This study describes the cell-free biomanufacturing of a broad-spectrum antiviral protein, griffithsin (GRFT) such that it can be produced with consistent purity and potency in less than 24 hours. We demonstrate GRFT production using two independent cell-free systems, one plant and one microbial. Griffithsin purity and quality were verified using standard regulatory metrics. Efficacy was demonstrated in vitro against SARS-CoV-2 and HIV-1 and was nearly identical to that of GRFT expressed in vivo. The proposed production process is efficient and can be readily scaled up and deployed anywhere in the world where a viral pathogen might emerge. The current emergence of viral variants has resulted in frequent updating of existing vaccines and loss of efficacy for front-line monoclonal antibody therapies. Proteins such as GRFT with its efficacious and broad virus neutralizing capability provide a compelling pandemic mitigation strategy to promptly suppress viral emergence at the source of an outbreak.

bioengineering↗

bioRxiv2022

A Coiled-Coil-Based Design Strategy for the Thermostabilization of G-Protein-Coupled Receptors

The most common methods for generating crystallizable GPCRs are scanning alanine mutagenesis and fusion to crystallization-facilitating partner proteins. The major goal of our work was to create a new GPCR tool that would provide receptor stability and additional soluble surface for crystallization. Towards this aim, we selected the two-stranded antiparallel coiled coil as a domain fold that satisfies both criteria. A selection of antiparallel coiled coils was used for structure-guided substitution of intracellular loop of the {beta}3 adrenergic receptor. Unexpectedly, only the two GPCR variants containing thermostable coiled coils were expressed. We showed that one GPCR chimera is stable upon purification in detergent, retains ligand-binding properties, and can be crystallized. However, the quality of the crystals was not suitable for structure determination. To supply additional surface for promoting crystal contacts, we replaced in a structure-based approach the loop of the antiparallel coiled coil by T4L. Although expression is currently not suitable for structural work, we found that the engineered GPCR is even more stable than the coiled-coil variant. Our approach should be of interest for applications that benefit from stable GPCRs.

biophysics↗

bioRxiv2019

A framework for testing different imputation methods for tabular datasets

Background and purposeHandling missing values is a prevalent challenge in the analysis of clinical data. The rise of data-driven models demands an efficient use of the available data. Methods to impute missing values are thus crucial. Here, we developed a publicly available framework to test different imputation methods and compared their impact in a typical stroke clinical dataset as a use case.\n\nMethodsA clinical dataset based on the 1000Plus stroke study with 380 completed-entries patients was used. 13 common clinical parameters including numerical and categorical values were selected. Missing values in a missing-at-random (MAR) and missing-completely-at-random (MCAR) fashion from 0% to 60% were simulated and consequently imputed using the mean, hot-deck, multiple imputation by chained equations, expectation maximization method and listwise deletion. The performance was assessed by the root mean squared error, the absolute bias and the performance of a linear model for discharge mRS prediction.\n\nResultsListwise deletion was the worst performing method and started to be significantly worse than any imputation method from 2% (MAR) and 3% (MCAR) missing values on. The underlying missing value mechanism seemed to have a crucial influence on the identified best performing imputation method. Consequently no single imputation method outperformed all others. A significant performance drop of the linear model started from 11% (MAR+MCAR) and 18% (MCAR) missing values.\n\nConclusionsIn the presented case study of a typical clinical stroke dataset we confirmed that listwise deletion should be avoided for dealing with missing values. Our findings indicate that the underlying missing value mechanism and other dataset characteristics strongly influence the best choice of imputation method. For future studies with similar data structure, we thus suggest to use the developed framework in this study to select the most suitable imputation method for a given dataset prior to analysis.

neuroscience↗