Biology subjects

Geissen, E.-M.

Publications and source records attributed to Geissen, E.-M..

4 recordsLinked to original sources

bioRxiv2026

ProPER: Programmable, multiplexed detection of molecular proximities and RNA life-cycle stages in situ

Proximity detection methods facilitate contextual analysis of biomolecules by reporting their microenvironment, spatial organization and molecular interactions. To expand these detection capabilities towards highly sensitive, quantitative, and multiplexed interaction mapping, we introduce Proximity Primer Exchange Reaction (ProPER). ProPER is a novel ligation-free proximity extension and controlled DNA amplification strategy that enables spatially resolved in situ detection of molecular proximities. In ProPER, extension of DNA barcodes into linear concatemers is made conditional on the spatial proximity of primer and hairpin pairs split across two targets, thereby enabling efficient coincidence or proximity detection with isothermal signal amplification for high-sensitivity imaging. The method is readily integrated with mainstream in situ assays such as immunofluorescence, FISH and metabolic labeling, and supports high-resolution visualization of diverse molecular modalities, including RNA-RNA or protein-protein interactions, even at dense labeling sites. Leveraging pre-validated orthogonal sequence pairs, ProPER allows simultaneous multiplexed detection of molecular proximities within the same cell and on the same target molecule. We applied multiplexed ProPER to resolve the life-cycle stages of individual RNA molecules. Quantitative tracking of transcriptional, splicing and translational states enabled construction of a kinetic model that identifies key regulatory steps driving differential expression kinetics of two inflammatory response genes. Overall, we establish ProPER as a versatile and efficient framework for in situ multiplexed proximity detection, overcoming key limitations of existing approaches. The programmable DNA encoding scheme enables advanced capabilities, such as proximity cascades and multivalent interaction detection, and provides a basis for integrating molecular proximity measurements into future combinatorial barcoding or spatial omics workflows.

molecular biology↗

bioRxiv2025

Real-time tracking of mRNP complex assembly reveals various mechanisms that synergistically enhance translation repression

Protein biosynthesis must be highly regulated to ensure proper spatiotemporal gene expression and thus cellular viability. Translation is often modulated at the initiation stage by RNA binding proteins through either promotion or repression of ribosome recruitment to the mRNA. However, it largely remains unknown how the kinetics of mRNA ribonucleoprotein (mRNP) assembly on untranslated regions (UTRs) relates to its translation regulation activity. Using Sex-lethal (Sxl)-mediated translation repression of msl-2 in female fly dosage compensation as a model system, we show that different mechanisms in mRNP assembly synergistically achieve tight translation repression. Using multi-color single-molecule fluorescence microscopy we show that 1) Sxl targets its binding sites via sliding and double-binding, 2) that Unr recruitment is accelerated over 500-fold by RNA-bound Sxl and 3) that Hrp48 further stabilizes RNA-bound Sxl indirectly via ATP-independent RNA remodeling. Overall, we provide a framework to study how multiple RBPs dynamically cooperate with RNA to achieve function.

biophysics↗

bioRxiv2024

Origins of de novo chromosome rearrangements unveiled by coupled imaging and genomics

Chromosomal instability results in widespread structural and numerical chromosomal abnormalities (CAs) during cancer evolution1-3. While CAs have been linked to mitotic errors resulting in the emergence of nuclear atypias4-7, the underlying processes and basal rates of spontaneous CA formation in human cells remain under-explored. Here we introduce machine learning-assisted genomics-and-imaging convergence (MAGIC), an autonomously operated platform that integrates automated live-cell imaging of micronucleated cells, machine learning in real-time, and single-cell genomics to investigate de novo CA formation at scale. Applying MAGIC to near-diploid, non-transformed cell lines, we track CA events over successive cell cycles, highlighting the common role of dicentric chromosomes as an initiating event. We determine the baseline CA rate, which approximately doubles in TP53-deficient cells, and show that chromosome losses arise more rapidly than gains. The targeted induction of DNA double-strand breaks along chromosomes triggers distinct CA processes, revealing stable isochromosomes, amplification and coordinated segregation of isoacentric segments in multiples of two, and complex CA outcomes, depending on the break location. Our data contrast de novo CA spectra from somatic mutational landscapes after selection occurred. The large-scale experimentation enabled by MAGIC provides insights into de novo CA formation, paving the way to unravel fundamental determinants of chromosome instability.

genomics↗

bioRxiv2022

Protein-Peptide Turnover Profiling reveals wiring of phosphorylation during protein maturation

Post-translational modifications (PTMs) regulate various aspects of protein function, including degradation. Mass spectrometric methods that rely on pulsed metabolic labeling are very popular to quantify turnover rates on a proteome-wide scale. Such data have often been interpreted in the context of protein proteolytic stability. Here, we combine theoretical kinetic modeling with experimental pulsed stable isotope labeling of amino acids in cell culture (pSILAC) for the study of protein phosphorylation. We demonstrate that metabolic labeling combined with PTM-specific enrichment does not measure effects of PTMs on protein stability. Rather, it reveals the relative order of PTM addition and removal along a proteins lifetime--a fundamentally different metric. We use this framework to identify temporal phosphorylation sites on cell cycle-specific factors and protein complex assembly intermediates. Our results open up an entirely new aspect in the study of PTMs, by tying them into the context of a proteins lifetime.

biochemistry↗