Formation of EGFRwt/EGFRvIII homo- and hetero-dimers in glioblastoma cells as detected by single molecule localization microscopy.

Super-resolution microscopy has been used to show the formation of receptor clusters and adapted lipid organization of cell membranes for many members of the ErbB receptor family. The clustering behaviour depends on the receptor size and shape, possibly ligand binding or expression activity. Using single molecule localization microscopy (SMLM), we also showed this typical clustering for the epidermal growth factor receptor variant III (EGFRvIII) in glioblastoma multiforme (GBM) cells. EGFRvIII is co-expressed with the wild type (EGFRwt) and both receptors are assumed to preferentially form hetero-dimers leading to transactivation and elevated oncogenic EGFR-signalling in GBM cells. Here, we analysed EGFRvIII and EGFRwt co-localization using our already described model system of the glioblastoma cell line DKMG, displaying endogenous EGFRvIII expression. Using EGFRvIII and EGFRwt specific antibodies, EGFR localization and their potential for dimerization in a given membrane cluster were analysed by dual colour SMLM supported by novel approaches of mathematic evaluations including Ripley statistics, persistent homology and similarity algorithms. Surprisingly, cluster analysis, Ripley point-to-point distance statistics for cluster geometry and persistent homology comparing cluster topology, revealed that both EGFRvIII and EGFRwt do primarily not form hetero-dimers but the results support the hypothesis that they tend to form homo-dimers. The ratio of homo-dimers obtained by this calculation was significantly higher (>5σ, standard deviation) than expected from randomly arranged points. In comparison, hetero-dimer formation was only slightly increased. We confirmed these data by immunoprecipitation, which show no co-precipitation of EGFRvIII and EGFRwt. Furthermore, we showed that the topology of the clusters was more similar among the same type than among the different types of receptors. Taken together, these data indicate that EGFRvIII does induce oncogenic signalling by homo-dimerisation and not preferentially by hetero-dimer formation with EGFRwt. These data offer a new perspective on EGFRvIII signalling which will lead to a better understanding of this tumour associated receptor variant in GBM.

Association between management practices and estimated mastitis incidence and milk losses on robotic dairy farms.

This study aims to describe the relation between farm-level management factors and estimated farm-level mastitis incidence and milk loss traits (MIMLT) at dairy farms with automated milking systems. In this observational study, 43 commercial dairy farms in Belgium and the Netherlands were included and 148 'management and udder health related variables' were obtained during a farm visit through a farm audit and survey. The MIMLT were estimated from milk yield data. Quarter-level milk yield perturbations that were caused by presumable mastitis cases (PMC) were selected based on quarter-level milk yield and electrical conductivity. On average, 57.6 ± 5.4% of the identified milk yield perturbations complied with our criteria. From these PMC, 3 farm-level MIMLT were calculated over a one-year period around the farm visit date: (1) the 'average number of PMC per cow per year', (2) the 'absolute milk loss per cow per day', calculated as the farm-level sum of all milk losses during PMC in one year, divided by the average number of lactating cows and the number of days, and (3) the 'relative milk loss', calculated as the farm-level sum of milk losses during PMC in one year, divided by the estimated total production in the absence of PMC. The 'average number of PMC per cow per year' was on average 1.81 ± 0.47. The PMC caused an average milk loss of 0.77 ± 0.26 kg per lactating cow per day, which corresponded to an average production loss of 2.38 ± 0.82% of the expected production in the absence of PMC. We performed a principal component regression (PCR) analysis to link the 3 MIMLT to the 'management and udder health related variables', whilst reducing the multicollinearity and the number of dimensions. The first principal component was mainly related to 'milking system brand, maintenance and settings'. The second component mainly linked to average productivity and somatic cell counts, whereas the third component mainly contained variables linked with mastitis management, treatment, and biosecurity. The 3 PCR models had R² ranging from 0.46 (for absolute milk loss per cow per day) to 0.57 (for relative milk loss). For all models, the second PC had the largest effect size. This analysis raises awareness of the impact of management factors on a factual basis and provides handles to take management actions to improve udder health.