Biology subjects

Maikranz, E.

Publications and source records attributed to Maikranz, E..

4 recordsLinked to original sources

bioRxiv2026

Cortical folding patterns are encoded in the geometry of the unfolded neocortex.

Cortical folding patterns are conserved across individuals of gyrencephalic species and are closely related to cytoarchitectural organisation, connectivity, and function. Early morphogen gradients have been proposed as the molecular source of positional information encoding these patterns - a gyral molecular protomap - but the contribution of neocortical geometry to this encoding has not been examined. Here we show that the geometry of the unfolded ferret brain guides the adult folding pattern before any folding has occurred. Using high-resolution MRI surface reconstructions from postnatal day (P) 0 to adults, we demonstrate that newborn neocortical curvature predicts mature curvature maps, sulcal-gyral fate, and fold orientation. Pre-folding curvature correlates with expression of key patterning genes, and a mediation analysis indicates that geometry at P0 is the principal predictor of sulcal-gyral fate at P6. Mechanical simulations show that regions of high curvature act as autonomous anchors that organise the folding pattern. These results suggest that neocortical geometry constitutes a form of positional information that complements molecular patterns in regulating cortical organisation, and that a complete account of cortical development requires the integration of geometric and mechanical processes alongside molecular signalling.

neuroscience↗

bioRxiv2025

Extending digital biology: bacterial survival and morphological heterogeneity under antibiotic stress

The morphology of bacteria is modified by antibiotic stress while also serving to survive the antibiotic. However associating morphological descriptors with quantitative measurements of cell survival remains elusive. Here we present a workflow to generate morphological signatures for the progeny of individual cells for 168 different antibiotic conditions. The workflow uses stationary microfluidic droplets, to encapsulate and grow bacteria, and confocal microscopy to image the contents of each droplet. A custom image analysis pipeline is developed to interact with the images in order to label of the morphologies within a subset of the images and train a neural network. The network yields a multidimensional morphological signature for 82000 droplets, showing the co-existence of different morphologies even for the progeny of individual cells. The morphological signatures are different for varying antibiotic type and concentration, thus providing a way to distinguish antibiotics by their mode of action. By combining these morphological signatures with the digital detection of survival within droplets, this workflow can serve to understand the emergence of antibiotic resistance or to identify antimicrobial activity of unknown substances.

bioengineering↗

bioRxiv2023

Cancer-on-a-chip model shows that the adenomatous polyposis coli mutation impairs T cell engagement and killing of cancer spheroids

Evaluating the ability of cytotoxic T lymphocytes (CTLs) to eliminate tumor cells is crucial, for instance to predict the efficiency of cell therapy in personalized medicine. However, the destruction of a tumor by CTLs involves CTL migration in the extra-tumoral environment, accumulation on the tumor, antigen recognition, and cooperation in killing the cancer cells. Therefore, identifying the limiting steps in this complex process requires spatio-temporal measurements of different cellular events over long periods. Here, we use a cancer-on-a-chip platform to evaluate the impact of adenomatous polyposis coli (APC) mutation on CTL migration and cytotoxicity against 3D tumor spheroids. The APC mutated CTLs are found to have a reduced ability to destroy tumor spheroids compared with control cells, even though APC mutants migrate in the extra-tumoral space and accumulate on the spheroids as efficiently as control cells. Once in contact with the tumor however, mutated CTLs display reduced engagement with the cancer cells, as measured by a new metric that distinguishes different modes of CTL migration. Realigning the CTL trajectories around localized killing cascades reveals that all CTLs transition to high engagement in the two hours preceding the cascades, which confirms that the low engagement is the cause of reduced cytotoxicity. Beyond the study of APC mutations, this platform offers a robust way to compare cytotoxic cell efficiency of even closely related cell types, by relying on a multiscale cytometry approach to disentangle complex interactions and to identify the steps that limit the tumor destruction.

bioengineering↗

bioRxiv2021

The adhesion capability of S. aureus cells is heterogeneously distributed over the cell envelope

Understanding and controlling microbial adhesion is an important biomedical problem. However, many properties of the adhesion process of bacteria are still unknown, for example the distribution of adhesive strength over the cell wall. While a patchy colloid model for adhesion has been developed recently for Gram-negative Escherichia coli cells, a comparable model for Grampositive cells is unknown. Here, we use single-cell force spectroscopy to measure the adhesion of Staphylococcus aureus at different positions on tailored surfaces. We find heterogeneous adhesion profiles with varying degrees of intensity. By comparing these results to simulations, we find that locally increased adhesion can be explained by several distinct spots of high adhesion capabilities, similar to the patchy colloid model. Only for the underlying profile without local adhesive spots simple geometric considerations are insufficient. Rather, strong angle-dependent molecule-substratum interactions are necessary to explain the bathtub-like adhesion profiles seen for Staphylococcus aureus on a sinusoidal surface. We discuss implications of our results for the development of new materials and the design and analysis of future studies.

biophysics↗