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Pritz, C. O.

Publications and source records attributed to Pritz, C. O..

2 recordsLinked to original sources

The plant specific VPS2.2/HYADE of the ESCRT-III protein sorting machinery localizes to a secretory compartment and is required for cell division plane determination in Arabidopsis

Positioning of the division plane is a critical step during cellular development. While in animal cells the plane of cell division is defined during metaphase, in plants this decision is made before mitosis and includes the formation of a cytoskeletal structure termed the preprophase band (PPB). Although not essential, the PPB constitutes the earliest mark for the plane of cell division and coincides with the sites where the cell plate fuses with the parental plasma membrane during cytokinesis. Recent studies indicate that endo- and exocytosis are involved in remodelling of the cortical division zone. Here we show that PPBs, phragmoplasts, cell plates and cell walls are misplaced in Arabidopsis mutants of Atvps2.2/hyade (hya), a plant-specific component of the Endosomal Sorting Complex Required for Transport (ESCRT)-III. We demonstrate that the amino acid substitution Q71P of the hya-3 allele abolishes the homo- and heteromerization with other ESCRT-III components. Functional HYA-GFP fusion proteins are excluded from the canonical location of ESCRT-III complexes at multivesicular bodies (MVBs) and are absent from Brefeldin A (BFA) and Wortmannin (WM) sensitive compartments in Arabidopsis. HYA-GFP neither localize to early nor late endosomes but colocalizes with markers of secretory compartments such as the Qc-SNARE, SYP61 and with trans-Golgi-network (TGN) derived secretory Rab-A3 vesicles. Moreover, HYA-GFP locates to the extracellular space indicating that VPS2.2/HYA is involved in secretion. These results are consistent with a novel, non-canonical function of ESCRT-III in the establishment and maintenance of the cortical division zone via secretion.

plant biology↗

Paw posture is a robust indicator for injury, pain, and age.

Inferring biological states from animal behavior is a crucial but challenging step in biomedical discovery that is constrained by variability and labour-intensive assays, even with AI-powered tools. Here, we show that simple images of static paws, analyzed by our custom keypoint segmentation AI-tool provide accurate read-outs for a wide array of physiological states. Without invasive testing, our method detects postural changes associated with nerve injury, acute pain, aging, and the genetic loss of kpna4, a regulator of paw innervation. Leveraging the toe-spread-reflex, a spinal-circuit driven response, the approach requires no habituation and shows low behavioral variability. Individual digits emerge as biomarkers for internal states with digit V indicating neuropathic pain during nerve damage and digit I reflecting loss of kpna4. Our model is freely available and can readily be adapted to other tasks or species. These findings establish unstimulated paw posture as a scaleable, low-cost, readout for biological states.

neuroscience↗