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Biology subjects

Maurer, S. J.

Publications and source records attributed to Maurer, S. J..

4 recordsLinked to original sources

Buoyancy-driven sorting of synthetic cells for nanopore activity

The development of sorting strategies that directly report on functional activity remains a bottleneck in synthetic cell research. Current methodologies typically rely on sequential label-dependent probing, which limits throughput. Here, we introduce a label-free, buoyancy-driven selection strategy in which the mode of separation and the mode of decision-making are intrinsically linked, coupling pore activity directly to the synthetic vesicles internal density in a one-pot assay. In this system, sorting emerges intrinsically: Giant unilamellar vesicles (GUVs) that contain a dense medium sediment by default, while only those with functional transmembrane pores undergo solute exchange, leading to density equilibration and flotation. We exploit this principle to separate pore-active from non-functional GUVs without external markers or imaging-based readouts. Using protein pores and DNA origami and DNA tile nanopores, we demonstrate that buoyancy-driven separation enables parallel functional assessment of heterogeneous populations and supports flow-based enrichment of highly active synthetic cells. By directly linking molecular transport performance to GUV buoyancy, this approach collapses decision-making into the physical separation process itself, providing a scalable platform for screening, sorting, and evolving membrane pores in synthetic cell systems.

biophysics↗

Automated Image-Based Cell Sorting by Targeted Photopolymerization

We present an automated image-based cell sorting method capable of a through-put of hundreds of cells per second. Our microscopy platform integrates automated image acquisition, machine-learning based classification and sub-sequent depletion of up to 99.98 % of negative cells by spatially controlled photo-encapsulation, preserving target cells for collection. Applied to peripheral blood mononuclear cells, the method achieves the label-free, morphology-based enrichment of activated T cells for downstream applications in biomedicine.

cell biology↗

Growth, dissolution and segregation of genetically encoded RNA droplets by ribozyme catalysis

Active droplets, membraneless compartments driven by internal chemical reactions, are compelling models for protocells and synthetic life. A central challenge is to program their dynamic behaviors using heritable genetic information, which would grant them the capacity to evolve. Here, we create transiently active RNA droplets by integrating sites for ribozyme catalysis directly into the sequence of self-assembling, four-arm RNA nanostars. To enable perfusion and observe the resulting dynamics over time, we develop a method for trapping individual droplets in hydrogel cages by targeted in situ photopolymerization. This enables us to quantify the sequence-programmable droplet dissolution and to control the degradation kinetics by choosing between fast (hammerhead) and slow (hairpin) ribozymes. Furthermore, we trigger the segregation of mixed droplet populations via the sequence-specific cleavage of a chimeric linker RNA. The droplet-encapsulated DNA templates code for the regrowth of new droplets, establishing the proof-of-principle for a minimal, genetically encoded cycle of dissolution and regrowth. By directly linking RNA sequence to droplet stability, composition, and life-cycle dynamics, our work provides a robust platform for engineering evolvable materials and advancing the bottom-up construction of synthetic cells.

synthetic biology↗

Fast Single-Cell MALDI Imaging of Low-Mass Metabolites Reveals Cellular Activation Markers

Single-cell MALDI mass spectrometry imaging (MSI) of lipids and metabolites >200 Da has recently come to the forefront of biomedical research and chemical biology, but fast metabolome-preserving methods without paraformaldehyde fixation for analysis of low mass, hydrophilic metabolites (<200 Da) in large cell populations are lacking. Introducing giant unilamellar vesicles (GUVs) as MSI ground truth for cell-sized objects and Monte Carlo reference-based consensus clustering for data-dependent identification of cell subpopulations. The PRISM-MS (PRescan Imaging for Small Molecule - Mass Spectrometry) dual-scan MSI workflow is presented, enabling space-efficient and therefore faster lipid analysis in single GUVs and cells. Beyond lipids, PRISM-MS enables MSI and on-cell MS2-based identification of low-mass metabolites like amino acids or Krebs cycle intermediates involved in stimulus-dependent cell activation. The utility of PRISM-MS is demonstrated through the characterization of complex metabolome changes in lipopolysaccharide (LPS)-stimulated microglial cells and human-induced pluripotent stem cell-derived microglia. Translation of single cell results to endogenous microglia in organotypic hippocampal slice cultures indicates that LPS-activation involves changes of the itaconate-to-taurine ratio and alterations in neuron-to-glia glutamine-glutamate shuttling. The data suggests that PRISM-MS could serve as a standard method in single cell metabolomics, given its capability to characterize larger cell populations and low-mass metabolites.

bioinformatics↗