Estermann, A. | bioRxiv Science

bioRxiv2026

Whole slide image analysis of the endometrial decidual reaction reveals multiscale perturbations associated with miscarriage

The inflammatory decidual reaction renders the cycling endometrium transiently permissive for embryo implantation before transforming it into the decidua, the maternal bed accommodating the fetal placenta during pregnancy. Disruptions in decidual tissue remodeling are linked to miscarriage and other pregnancy disorders. However, endometrial assessment is hampered by a lack of affordable technologies capable of mapping the spatiotemporal dysregulation of this dynamic and complex tissue. Employing a graph neural network on whole slide images of 493 CD56-immunostained endometrial samples, Endometronome was developed as a deep learning tool to spatially track the decidual reaction and provide accurate estimates of marker gene expression. When applied to 2,690 additional biopsies, this model consistently identified morphological correlates of prior miscarriage burden, a proxy for future risk. Further, a morphological signature indicative of metabolic glandular impairment discriminated between clinical miscarriage presentations. These findings illustrate how advanced imaging analysis of routine histology can transform miscarriage prevention strategies.

pathology↗

bioRxiv2026

Deconvolving the structural heterogeneity of alpha-Synuclein in vitro and in situ

The structural states of proteins in cells and tissues provide important insight into their functional states, but studying protein structures in situ remains challenging. Furthermore, a single protein can adopt multiple conformations in cells, which typically cannot be assessed by most structural approaches. Here we developed a novel approach, based on structural proteomics fingerprints, for the quantitative analysis of the distribution of structural states of a protein in vitro and in situ. We applied it to the Parkinsons disease hallmark protein alpha-synuclein (aSyn), for which various structural states (disordered, helical, oligomeric and amyloid fibrillar, among others) have been characterized in vitro, but for which the in vivo structural states remain hotly debated. We measured structure-specific proteolytic fingerprints from well-characterized aSyn in vitro conformations and used them to quantitatively determine the aSyn conformational composition in samples of interest. We first benchmarked our approach using ground truth datasets of known composition and showed that, during in vitro amyloid fibril formation, we could simultaneously detect a time-dependent decrease in disordered monomeric aSyn, an increase in {beta}-sheet-rich oligomers, and a delayed rise in amyloid fibrils. We then applied the method to complex, biologically relevant samples. In a S. cerevisiae aSyn overex-pression model, aSyn was predominantly helical, with an increased helical fraction accompanying its relocalization from the plasma membrane to cytosolic lipid droplets. This shift was linked to proteome-wide changes in lipid droplet homeostasis and fatty acid and ergosterol metabolism, underscoring the role of lipid metabolism and droplet formation in aSyn biology. Importantly, we also detected helical aSyn in human iPSC-derived cortical neurons, supporting the physiological relevance of this conformation. Finally, neurons differentiated from PD patient-derived iPSCs showed elevated levels of {beta}-sheet-rich aSyn compared to wild-type cells. Our approach allowed the in situ identification and quantification of different structural states of aSyn directly in cell lysates. Since several proteins can adopt multiple, functionally-relevant conformations in cells, our approach should be broadly applicable to in situ, quantitative structural and functional studies of proteins.

neuroscience↗