Budnikova, A. | Search bioRxiv

bioRxiv2026

Genetic depletion in zebrafish uncovers requirement for septins in haematopoiesis

Haematopoiesis and differentiation of immune cells from haematopoietic stem and progenitor cells (HSPCs) are essential to core aspects of health and disease. A key player in haematopoiesis and HSPC differentiation is the cytoskeleton, which governs cell division and lineage bias. Despite insights using mouse models, regulation of haematopoiesis by the septin cytoskeleton is mostly unknown. Septins are unconventional filament forming proteins best known for roles in cell division and host defence. To investigate septin-mediated host defence in vivo, we generated septin-deficient zebrafish models for infection with Mycobacterium marinum. Unexpectedly, septin-deficient larvae were protected from mycobacterial infection due to significantly increased macrophage numbers, reduced cell death, and enhanced inflammatory responses. Underlying this, we found that septin-deficient larvae produce significantly more HSPCs and show myeloid lineage bias, establishing a requirement for septins in haematopoiesis. In agreement with classical HSPC hierarchy, increased myeloid production in septin-deficient larvae is at the expense of erythroid lineage production. Our findings that septins play a role in haematopoiesis is consistent with hallmarks of haematological disorders in which septin dysfunction has been implicated, including acute myeloid leukaemia, myelodysplastic syndrome, and platelet disorder Bernard-Soulier syndrome. These results highlight zebrafish as a new model to investigate septin-mediated haematopoiesis and application of septin-based medicines to treat blood disorders.

cell biology↗

bioRxiv2025

Learning a mechanical growth model of flower morphogenesis

Morphogenesis, the process by which organs take their shape, is a fundamental problem in biology and requires a complex combination of genetic, biochemical, and mechanical signals. The data that we collect for this process are usually multi-scale and multi-modal, typically image timeseries of tissue morphology and transcription data. As the data becomes larger and more diverse, the harder it becomes to gain meaningful understanding in terms of theoretical models. Here, and tackling this problem in the developing flower organ, we learn a mechanical model of growth starting from combined morphology and transcription data across the tissue by firstly learning and connecting independent representations for the two spaces and secondly refining the representation using the mechanical state of the tissue to learn a mechanical growth model. This approach can link multiple scales, in this case proposing the physical action of genes, and can act as a vehicle to accommodate diverse data and hypotheses in developmental biology of plants and beyond.

developmental biology↗