Septins are a family of GTP-binding proteins, which are essential for active membrane movement such as cytokinesis and vesicle trafficking. In non-dividing cells (such as platelets and neurons) septins are implicated in exocytosis. Platelets from a SEPT5 knockout mouse showed an altered serotonin secretion and platelet aggregation, suggesting that SEPT5 is involved in secretion in platelets. Septins form complexes consisting of multiple septin polypeptides. Using the yeast two-hybrid system we had demonstrated that SEPT5 partners with SEPT8. The aim of this study was to identify other interaction partners of the human platelet septin SEPT8. Using the yeast two-hybrid system with SEPT8 as bait protein we identified the human septin SEPT4 as an interaction partner of SEPT8. The interaction between SEPT4 and SEPT8 was confirmed by immunoprecipitation. Expression analysis revealed that SEPT4 is also expressed in human platelets. Thus, SEPT4 is the third described platelet septin besides SEPT5 and SEPT8. Transmission electron microscopy of platelets revealed that SEPT8 and SEPT4 are localized surrounding alpha-granules (as it had been shown for the septin SEPT5) suggesting that the three septins may be components of the septin complex in platelets and contribute in such a way to platelet biology. Activation of platelets by agonists resulted in the translocation of SEPT4 and SEPT8 to the platelet surface indicating a possible functional role of these proteins in platelet granular secretion.

Septins are cytoskeletal GTPases forming heteropolymeric complexes involved in processes characterised by active membrane movement such as cytokinesis, vesicle trafficking, and exocytosis. Septins are expressed in non-mitotic cells such as neurons and platelets. SEPT11 belongs to the SEPT6 group and was identified as interaction partner of SEPT5. We cloned and characterised novel SEPT11 variants and investigated interaction partners of SEPT11 in platelets and human umbilical vein endothelial cells. An endothelial cell library was used for cloning novel SEPT11 variants. Using Northern analysis the different SEPT11 transcripts were illustrated. Interaction studies were performed using yeast two-hybrid system, precipitation, FRET, and immunofluorescence microscopy. We demonstrate that SEPT11 partners with SEPT2, SEPT4 and SEPT7 using yeast two-hybrid system and precipitation. The interaction of SEPT11 with SEPT7 is also demonstrated by FRET. In addition to the known SEPT11 transcript (SEPT11_v1) we identified a novel SEPT11 variant (SEPT11_v2) as interaction partner of SEPT4 and SEPT7. Library screening of an endothelial cell library also revealed the presence of this novel SEPT11_v2 transcript. In addition, a third SEPT11 variant (SEPT11_v3) was identified. Expression of SEPT11_v1 and of SEPT11_v2 and SEPT11_v3 in human brain regions was investigated by Northern analysis. Further interaction partners of SEPT11 are characterised using immunofluorescence. Co-localisation of SEPT2, SEPT4, SEPT7 and SEPT11 with tubulin and transferrin receptor (endocytotic marker) is demonstrated. In addition, co-localisation of SEPT4 and SEPT11 with the vesicle-associated protein synaptobrevin 1 (VAMP1), but not clearly with actin, was shown. Only SEPT2 and SEPT7 definitely co-localised with actin, but not clearly with VAMP1.

Mesenchymal stem cells (MSCs) gain an increasing focus in the field of regenerative medicine due to their differentiation abilities into chondrocytes, adipocytes, and osteoblastic cells. However, it is apparent that the transformation processes are extremely complex and cause cellular heterogeneity. The study aimed to characterize differences between MSCs and cells after adipogenic (AD) or osteoblastic (OB) differentiation at the proteome level. Comparative proteomic profiling was performed using tandem mass spectrometry in data-independent acquisition mode. Proteins were quantified by deep neural networks in library-free mode and correlated to the Molecular Signature Database (MSigDB) hallmark gene set collections for functional annotation. We analyzed 4108 proteins across all samples, which revealed a distinct clustering between MSCs and cell differentiation states. Protein expression profiling identified activation of the Peroxisome proliferator-activated receptors (PPARs) signaling pathway after AD. In addition, two distinct protein marker panels could be defined for osteoblastic and adipocytic cell lineages. Hereby, overexpression of AEBP1 and MCM4 for OB as well as of FABP4 for AD was detected as the most promising molecular markers. Combination of deep neural network and machine-learning algorithms with data-independent mass spectrometry distinguish MSCs and cell lineages after adipogenic or osteoblastic differentiation. We identified specific proteins as the molecular basis for bone formation, which could be used for regenerative medicine in the future.

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