Biology subjects

Eberhardt, J.

Publications and source records attributed to Eberhardt, J..

7 recordsLinked to original sources

bioRxiv2026

A high-throughput compound screen identifies multiple druggable targets in Plasmodium falciparum transmission stages

Most antimalarials are ineffective against the sexual transmission stages, known as gametocytes, of the malaria parasite Plasmodium falciparum. Their low sensitivity to drugs is attributed to limited compound uptake and a poorly understood form of cellular quiescence. Our current understanding of druggable transmission-blocking processes is therefore limited. Based on genetically engineered parasites that facilitate the mass production of synchronous mature gametocytes, we developed a high throughput drug screening platform that allowed us to test more than 50,000 compounds for gametocytocidal effects in one day. By screening a diversity-oriented library, we identified over 40 molecules that kill mature gametocytes in the low nanomolar range. Using resistance selection coupled to whole genome sequencing and drug-target interaction modelling, we followed up on three chemically tractable compounds that are also highly active against asexual parasites and prevent gametocyte transmission to mosquitoes. We show that the compound ONX-0914, a specific inhibitor of the {beta}5i/LMP7 subunit of human immunoproteasomes, targets the parasite proteasomal {beta}5 subunit. In contrast, the compounds CR-1-31-B and brusatol interfere with translation by targeting eukaryotic initiation factor 4A (eIF4A) and the peptidyl transferase center (PTC) of the 80S ribosome, respectively. Interestingly, parasite resistance to brusatol, a broad-spectrum antitumor drug, is linked to the differential modification of specific rRNA bases near the ribosomal A-site, mediated by altered base specificity of a rRNA methyltransferase. In summary, we successfully combined high-throughput compound screening with drug target deconvolution to reveal the targets and mode-of-action for three potent gametocytocidal molecules and discover the mechanism of resistance to the anti-tumorigenic drug brusatol. In addition to critically advancing our understanding of mature gametocyte biology and druggable processes in P. falciparum transmission stages, our observations made with brusatol-resistant parasites may become relevant for anti-cancer drug research.

molecular biology↗

bioRxiv2025

Have protein-ligand co-folding methods moved beyond memorisation?

Deep learning has driven major breakthroughs in protein structure prediction, however the next critical advance is accurately predicting how proteins interact with small molecule ligands, to enable real-world applications such as drug discovery. Recent cofolding methods aim to address this challenge, but evaluating their performance has been inconclusive due to the lack of relevant bench-marking datasets. Here we present a comprehensive evaluation of four leading all-atom cofolding methods using our newly introduced benchmark dataset Runs N Poses, which comprises 2,600 high-resolution protein-ligand systems released after the training cutoff used by these methods. We demonstrate that current cofolding approaches largely memorise ligand poses from their training data, hindering their use for de novo drug design. With this assessment and benchmark dataset, we aim to accelerate progress in the field by allowing for a more realistic assessment of the current state-of-the-art deep learning methods for predicting protein-ligand interactions.

bioinformatics↗

bioRxiv2025

Detection of low pre-existing humoral immunity against influenza virus H5N1 clade 2.3.4.4b in unexposed individuals

The spill-over of Influenza A virus H5N1 clade 2.3.4.4b from cattle to humans highlights the risk of a human H5N1 pandemic. Given the impact of pre-existing immunity on the course and severity of viral infections, we comprehensively assessed the humoral immunity against the H5N1 A/Texas/37/2024 isolate in H5N1-naive individuals. To this end, we performed complementary binding and neutralization assays on 66 subjects and ranked activities among a panel of 76 influenza A virus isolates. We detected low but distinct cross-neutralizing titers against A/Texas/37/2024 with a 3.9 to 15.6-fold reduction compared to selected H1N1 or H3N2 strains. By cloning and evaluating 136 monoclonal antibodies from memory B cells, we identified potent A/Texas/37/2024-neutralizing monoclonal antibodies in five out of six investigated individuals. These antibodies cross-neutralize H1, compete with antibodies targeting the HA stem, and protect mice from lethal H5N1 challenge. Our findings demonstrate partial pre-existing humoral immunity to A/Texas/37/2024 in H5N1-naive individuals.

immunology↗

bioRxiv2024

Concepts and methods for predicting viral evolution

The seasonal human influenza virus undergoes rapid evolution, leading to significant changes in circulating viral strains from year to year. These changes are typically driven by adaptive mutations, particularly in the antigenic epitopes, the regions of the viral surface protein haemagglutinin targeted by human antibodies. Here we describe a consistent set of methods for data-driven predictive analysis of viral evolution. Our pipeline integrates four types of data: (1) sequence data of viral isolates collected on a worldwide scale, (2) epidemiological data on incidences, (3) antigenic characterization of circulating viruses, and (4) intrinsic viral phenotypes. From the combined analysis of these data, we obtain estimates of relative fitness for circulating strains and predictions of clade frequencies for periods of up to one year. Furthermore, we obtain comparative estimates of protection against future viral populations for candidate vaccine strains, providing a basis for pre-emptive vaccine strain selection. Continuously updated predictions obtained from the prediction pipeline for influenza and SARS-CoV-2 are available on the website previr.app.

biophysics↗

bioRxiv2023

ZeptoCTC - Sensitive Protein Analysis of True Single Cell Lysates using Reverse Phase Protein Arrays (RPPA)

Circulating Tumor Cells (CTCs) are commonly analyzed through genomic profiling, which does not capture posttranslational and functional alterations of encoded proteins. To address this limitation, we developed ZeptoCTC, a single-cell protein analysis workflow that combines established technologies for single-cell isolation and sensitive Reverse Phase Protein Array (RPPA) analysis to assess multiple protein expression and activation in individual CTCs. The workflow involves single cell labeling, isolation, lysis, and printing of the true single cell lysates onto a ZeptoChip using a modified micromanipulator CellCelectorTM. Subsequently, the printed lysates undergo fluorescence immunoassay RPPA protein detection using a ZeptoReader followed by signal quantification with Image J software. ZeptoCTC was successfully optimized, beginning with the measurement of EpCAM protein expression--a standard marker for CTC detection. As expected, mean fluorescence signals for EpCAM levels were significantly higher in single MCF-7 cells compared to MDA-MB-231 cells. Next, Capivasertib-treated MCF-7 cells exhibited an approximately 2-fold increase in the pAkt/Akt ratio compared to non-treated control cells. This finding was consistent with a co-performed western blot analysis of pooled MCF-7 cells. Application of ZeptoCTC to the analysis of single CTCs derived from a metastasized breast cancer (MBC) patient indicated a significantly higher level of pAkt, accompanied by a corresponding increase in pErk level when compared to patient-matched WBC. Finally, the current workflow successfully indicated the detectable pAkt and Akt signal difference in CTCs from two MBC patients: one with an Akt1 wild-type genotype, and the other harboring approximately 80% Akt1(E17K) mutated CTCs. The mutated CTCs revealed clearly elevated pAkt levels (1.8-fold), along with an even more strongly elevated total Akt (3.4-fold) when compared to the respective signals measured in wild-type CTCs. In conclusion, ZeptoCTC is a highly sensitive method for measuring the expression and phosphorylation of treatment-relevant proteins in key cancer-driving signaling pathways from true single cell samples.

molecular biology↗

bioRxiv2023

DanioCTC: Injection of circulating tumor cells from metastatic breast cancer patients in zebrafish xenografts for analysis of metastasis

Circulating tumor cells (CTCs) are considered as metastatic precursor cells, and zebrafish xenografts provide an in vivo model to study cancer cell spread. Currently, the low number of patient-derived CTCs limits their analysis in animal models. We present DanioCTC, a xenograft workflow for injecting CTCs from metastatic breast cancer (MBC) patients into zebrafish embryos to study cell dissemination in vivo. The study successfully adapts existing workflows and combines diagnostic leukapheresis (DLA), the Parsortix microfluidic system, flow cytometry, and the automated cell micromanipulator CellCelector setup to enrich and isolate MBC-derived CTCs and to finally inject them into Zebrafish embryos, where their dissemination was tracked up to 3 days post-injection. MDA-MB-231 cells were used as a standard xenotransplantation control, and these cells were frequently found in the head and blood-forming regions of the tail. Using DLA aliquots spiked with MBA-MB-231 cells, the newly established DanioCTC workflow confirmed the dissemination of MDA-MB-231 cells into these regions. CTCs from an MBC patient were then enriched by DLA, Parsortix, and flow cytometry, isolated with the CellCelectorTM and xenografted into zebrafish embryos. CTCs were mainly detected in the head and trunk, unlike MDA-MB-231 cells, which were present in the head and tail. DanioCTC presents a significant breakthrough in the use of zebrafish embryos as a model to study CTC dissemination in vivo, which can be used for patient-derived CTCs instead of cell culture-derived cancer cells as a crucial step towards understanding the biology of metastatic breast cancer. Statement of significanceDanioCTC is a novel workflow to inject patient-derived CTCs into zebrafish, enabling studies on CTC dissemination and personalized treatment in vivo, therefore advancing our toolkit to fight metastatic cancer.

cancer biology↗

bioRxiv2019

Integrative x-ray structure and molecular modeling for the rationalization of procaspase-8 inhibitor potency and selectivity

Caspases are a critical class of proteases involved in regulating programmed cell death and other biological processes. Selective inhibitors of individual caspases, however, are lacking, due in large part to the high structural similarity found in the active sites of these enzymes. We recently discovered a small-molecule inhibitor, 63-R, that covalently binds the zymogen, or inactive precursor (pro-form), of caspase-8, but not other caspases, pointing to an untapped potential of procaspases as targets for chemical probes. Realizing this goal would benefit from a structural understanding of how small molecules bind to and inhibit caspase zymogens. There have, however, been very few reported procaspase structures. Here, we employ x-ray crystallography to elucidate a procaspase-8 crystal structure in complex with 63-R, which reveals large conformational changes in active-site loops that accommodate the intramolecular cleavage events required for protease activation. Combining these structural insights with molecular modeling and mutagenesis-based biochemical assays, we elucidate key interactions required for 63-R inhibition of procaspase-8. Our findings inform the mechanism of caspase activation and its disruption by small molecules, and, more generally, have implications for the development of small molecule inhibitors and/or activators that target alternative (e.g., inactive precursor) protein states to ultimately expand the druggable proteome.

biochemistry↗