Actomyosin, vimentin and LINC complex pull on osteosarcoma nuclei to deform on micropillar topography.

Cell deformation occurs in many critical biological processes, including cell extravasation during immune response and cancer metastasis. These cells deform the nucleus, their largest and stiffest organelle, while passing through narrow constrictions in vivo and the underlying mechanisms still remain elusive. It is unclear which biochemical actors are responsible and whether the nucleus is pushed or pulled (or both) during deformation. Herein we use an easily-tunable poly-L-lactic acid micropillar topography, mimicking in vivo constrictions to determine the mechanisms responsible for nucleus deformation. Using biochemical tools, we determine that actomyosin contractility, vimentin and nucleo-cytoskeletal connections play essential roles in nuclear deformation, but not A-type lamins. We chemically tune the adhesiveness of the micropillars to show that pulling forces are predominantly responsible for the deformation of the nucleus. We confirm these results using an in silico cell model and propose a comprehensive mechanism for cellular and nuclear deformation during confinement. These results indicate that microstructured biomaterials are extremely versatile tools to understand how forces are exerted in biological systems and can be useful to dissect and mimic complex in vivo behaviour.

Glycerol metabolism of Pichia pastoris (Komagataella spp.) characterised by 13C-based metabolic flux analysis.

Metabolic flux analysis based on 13C-derived constraints has proved to be a powerful method for quantitative physiological characterisation of one of the most extensively used microbial cell factory platforms, Pichia pastoris (syn. Komagataella spp.). Nonetheless, the reduced number of carbon atoms and the symmetry of the glycerol molecule has hampered the comprehensive determination of metabolic fluxes when used as the labelled C-source. Moreover, metabolic models typically used for 13C-based flux balance analysis may be incomplete or misrepresent the actual metabolic network. To circumvent these limitations, we reduced the genome-scale metabolic model iMT1026-v3.0 into a core model and used it for the iterative fitting of metabolic fluxes to the measured mass isotope distribution of proteinogenic amino acids obtained after fractional 13C labelling of cells with [1,3-13C]-glycerol. This workflow allows reliable estimates to be obtained for in vivo fluxes in P. pastoris cells growing on glycerol as sole carbon source, as well as revising previous assumptions concerning its metabolic operation, such as alternative metabolic branches, calculation of energetic parameters and proposed specific cofactor utilisation.