bioRxiv Science⌕ Search

Biology subjects

Diakova, M.

Publications and source records attributed to Diakova, M..

2 recordsLinked to original sources

Whole-Embryo 3D Quantification Reveals Conserved Topological Design and Scaling of Germ Layers in Xenopus

How embryos with markedly different absolute sizes and cell numbers establish comparable tissue organization during development remains a fundamental question in developmental biology. To address this question, we compared two closely related Xenopus species that differ substantially in embryonic size, Xenopus laevis and Xenopus tropicalis. We generated a whole-embryo quantitative 3D atlas of cell allocation, spatial organization, and mitotic dynamics at key time points between gastrulation to tailbud stages. Using tissue clearing, and 3D imaging we tracked single-nucleus coordinates across developmental milestones to resolve how body plans adapt to organismal scale. We show that embryonic scaling is not achieved through simple proportional changes in cell number. Instead, the smaller X. tropicalis embryo is characterized by a distinct high-density tissue organization associated with a persistently higher mitotic index (~1.4-fold higher than in X. laevis at both gastrula and tailbud stages). Across development, this is accompanied by a near-doubling of cell number in X. tropicalis without a proportional increase in embryo volume. We quantify tissue organization and find species-specific cellular architectures during gastrulation that largely converge by the tailbud stage. At this stage, homologous tissues display broadly similar structural profiles despite persistent differences in embryo size, cell number, and density. Together, our findings reveal that closely related vertebrate embryos can follow distinct cellular organization trajectories while converging toward comparable tissue architecture, providing a quantitative framework for understanding robust body plan formation across divergent physical scales.

Developmental Biology↗

Normalized Raman Imaging for Studies of Tissue Physiology of the Kidney

Conventional histological relies on fixation, embedding, sectioning, and staining methods that distort cellular architecture, extract lipids, and introduces variability, limiting reproducibility. We present Normalized Stimulated Raman Imaging (NoRI) that enables quantitative, label-free protein and lipid measurements at high-spatial resolution. NoRI computationally corrects protein, lipid, and water Raman signals, allowing quantitative biomass measurements while preserving tissue architecture, facilitating analysis by convolutional neural networks. Applied to mouse kidney, NoRI accurately classified tubule types (F1-[harmonic mean of precision and recall against manual annotation]=0.93), anatomical regions (F1=0.91), and biological sex (F1=0.97), revealing greater cytoplasmic lipid (+6.9mg/mL; p=0.028) and nuclear protein (+26.3mg/mL; p<0.001) in female tubules. In acute kidney injury, NoRI captured dynamic lipid and protein organization and quantified brush border remodelling and lipid droplet changes over 25 days. Spatial lipid quantification was central for feature classification in AKI (F1=1.0). These results establish NoRI as a reproducible, quantitative method for diagnostics, histopathology, and feature discovery.

physiology↗