Biology subjects

Jenster, G.

Publications and source records attributed to Jenster, G..

5 recordsLinked to original sources

bioRxiv2025

Cell-Based Immunization Combined with Single-Round Cell Panning Enables Discovery of PSMA-Targeting Nanobodies from Phage Display Libraries

There is a strong need for nanobodies targeting novel cancer-associated antigens to advance radioligand imaging and antibody-based therapeutics. In this study, we investigated whether non-targeted Llama immunization using tumor cells, combined with non-targeted phage display panning on human cell lines, could yield nanobodies specific to Prostate Specific Membrane Antigen (PSMA). Nanobody selection using both classical three round PSMA negative-positive panning and single round panning of cell lines positive or negative for PSMA showed clear enrichment for PSMA binders in both strategies. Using shRNA knockdown, flow cytometry, cell-ELISA, immunohistochemistry and structural modeling and docking, we confirmed the PSMA targeting of selected nanobodies. Two distinct epitopes were predicted to be bound by nanobodies PSMANb9 and A7 (JVZ-007), corroborated by epitope competition assays. These findings support the feasibility of non-targeted immunization and panning strategies for isolating clinically relevant cancer nanobodies.

cancer biology↗

bioRxiv2024

CD81-guided heterologous EVs present heterogeneous interactions with breast cancer cells

Extracellular vesicles (EVs) are cell-secreted particles conceived as natural vehicles for intercellular communication. The intrinsic biocompatibility, stability in biofluids, and heterogeneous molecular cargo of EVs promise advancements in targeted therapy applications. However, predicting cell-targeting spectrum and cargo delivery are fundamental challenges for exploiting EVs or hybrid formulations. In this work, we combined cell-based and biochemical approaches to understand if secreted EVs show predictable EV-cell interactions and consequent cargo delivery. We exploited the tetraspanin CD81 to encode full-length recombinant proteins with a C-terminal GFP reporter encompassing or not Trastuzumab light chains targeting the HER2 receptor. These fusion proteins participated in vesicular trafficking dynamics and accumulated on secreted EVs when transiently over-expressed in HEK293T cells. Despite the presence of GFP, secreted EV populations retained a HER2 receptor-binding capacity and were used in EV-cell interaction assays. In time-frames where the global GFP spot distribution did not change between HER2-positive (SK-BR-3) or -negative (MDA-MB-231) breast cancer cell lines, the HER2 manipulation in isogenic cells remarkably affected the tropism of heterologous EVs. In this line, secreted doxorubicin-EVs, which showed improved efficacy compared to the free drug, had a reduced cell-killing activity on SK-BR-3 with a knocked-out HER2 receptor. Interestingly, the fusion protein-corresponding transcripts also present as full-length mRNAs in recombinant EVs could reach orthotopic breast tumors in JIMT-1-xenografted mice, as detected by ddPCR in tissue biopsies, improving our sensitivity in detecting bioavailable cargoes. These data show multiple mechanisms underlying EV-cell interactions and prioritize the profiling of surfaceomes for better comprehension of cell engagement and design new generations of EV-based nanovehicles.

molecular biology↗

bioRxiv2021

Detection of fusion transcripts and their genomic breakpoints from RNA sequencing data

Spliced fusion-transcripts are typically identified by RNA-seq without elucidating the causal genomic breakpoints. However, non poly(A)-enriched RNA-seq contains large proportions of intronic reads spanning also genomic breakpoints. Using 1.274 RNA-seq samples, we investigated what additional information is embedded in non poly(A)-enriched RNA-seq data. Here, we present our novel, graph-based, Dr. Disco algorithm that makes use of both intronic and exonic RNA-seq reads to identify not only fusion transcripts but also genomic breakpoints in gene but also in intergenic regions. Dr. Disco identified TMPRSS2-ERG fusions with genomic breakpoints and other transcribed rearrangements from multiple RNA-sequencing cohorts. In breast cancer and glioma samples Dr. Disco identified rearrangement hotspots near CCND1 and MDM2 and could directly associate this with increased expression. A comparison with matched DNA-sequencing revealed that most genomic breakpoints are not, or minimally, transcribed while also revealing highly expressed translocations missed by DNA-seq. By using the full potential of non poly(A)-enriched RNA-seq data, Dr. Disco can reliably identify expressed genomic breakpoints and their transcriptional effects.

bioinformatics↗

bioRxiv2020

FASTAFS: file system virtualisation of random access compressed FASTA files

BackgroundThe FASTA file format used to store polymeric sequence data has become a bioinformatics file standard used for decades. The relatively large files require additional files beyond the scope of the original format, to identify sequences and provide random access. Currently, multiple compressors have been developed to archive FASTA files back and forth, but these lack direct access to targeted content or metadata of the archive. Moreover, these solutions are not directly backwards compatible to FASTA files, resulting in limited software integration. ResultsWe designed linux based a toolkit using Filesystem in Userspace (FUSE) that virtualises the content of DNA, RNA and protein FASTA archives into the filesystem. This guarantees in-sync virtualised metadata files and offers fast random-access decompression using Zstandard (zstd). The toolkit, FASTAFS, can track all system wide running instances, allows file integrity verification and can provide, instantly, scriptable access to sequence files and is easy to use and deploy. ConclusionsFASTAFS is a user-friendly and easy to deploy backwards compatible generic purpose solution to store and access compressed FASTA files, since it offers file system access to FASTA files as well as in-sync metadata files through file virtualisation. Using virtual filesystems as in-between layer offers the possibility to design format conversion without the need to rewrite code into different languages while preserving compatibility. Code Availabilityhttps://github.com/yhoogstrate/fastafs

bioinformatics↗

bioRxiv2020

EVQuant; high-throughput quantification and characterization of extracellular vesicle (sub)populations

Extracellular vesicles (EVs) reflect the cell of origin in terms of nucleic acids and protein content. They are found in biofluids and represent an ideal liquid biopsy biomarker source for many diseases. Unfortunately, clinical implementation is limited by available technologies for EV analysis. We have developed a simple, robust and sensitive microscopy-based high-throughput assay (EVQuant) to overcome these limitations and allow widespread use in the EV community. The EVQuant assay can detect individual immobilized EVs as small as 35 nm and determine their concentration in biofluids without extensive EV isolation or purification procedures. It can also identify specific EV subpopulations based on combinations of biomarkers and is used here to identify prostate-derived urinary EVs as CD9-/CD63+. Moreover, characterization of individual EVs allows analysis of their size distribution. The ability to identify, quantify and characterize EV (sub-)populations in high-throughput substantially extents the applicability of the EVQuant assay over most current EV quantification assays.

bioengineering↗