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.

Advanced image-free analysis of the nano-organization of chromatin and other biomolecules by Single Molecule Localization Microscopy (SMLM).

The cell as a system of many components, governed by the laws of physics and chemistry drives molecular functions having an impact on the spatial organization of these systems and vice versa. Since the relationship between structure and function is an almost universal rule not only in biology, appropriate methods are required to parameterize the relationship between the structure and function of biomolecules and their networks, the mechanisms of the processes in which they are involved, and the mechanisms of regulation of these processes. Single molecule localization microscopy (SMLM), which we focus on here, offers a significant advantage for the quantitative parametrization of molecular organization: it provides matrices of coordinates of fluorescently labeled biomolecules that can be directly subjected to advanced mathematical analytical procedures without the need for laborious and sometimes misleading image processing. Here, we propose mathematical tools for comprehensive quantitative computer data analysis of SMLM point patterns that include Ripley distance frequency analysis, persistent homology analysis, persistent 'imaging', principal component analysis and co-localization analysis. The application of these methods is explained using artificial datasets simulating different, potentially possible and interpretatively important situations. Illustrative analyses of real complex biological SMLM data are presented to emphasize the applicability of the proposed algorithms. This manuscript demonstrated the extraction of features and parameters quantifying the influence of chromatin (re)organization on genome function, offering a novel approach to study chromatin architecture at the nanoscale. However, the ability to adapt the proposed algorithms to analyze essentially any molecular organizations, e.g., membrane receptors or protein trafficking in the cytosol, offers broad flexibility of use.

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.

Near-infrared spectra dataset of milk composition in transmittance mode.

Monitoring of milk composition can support several dimensions of dairy management such as identification of the health status of individual dairy cows and the safeguarding of dairy quality. The quantification of milk composition has been traditionally executed employing destructive chemical or laboratory Fourier-transform infrared (FTIR) spectroscopy analyses which can incur high costs and prolonged waiting times for continuous monitoring. Therefore, modern technology for milk composition quantification relies on non-destructive near-infrared (NIR) spectroscopy which is not invasive and can be performed on-farm, in real-time. The current dataset contains NIR spectral measurements in transmittance mode in the wavelength range from 960 nm to 1690 nm of 1224 individual raw milk samples, collected on-farm over an eight-week span in 2017, at the experimental dairy farm of the province of Antwerp, 'Hooibeekhoeve' (Geel, Belgium). For these spectral measurements, laboratory reference values corresponding to the three main components of raw milk (fat, protein and lactose), urea and somatic cell count (SCC) are included. This data has been used to build multivariate calibration models to predict the three milk compounds, as well as develop strategies to monitor the prediction performance of the calibration models.

Clustered localization of EGFRvIII in glioblastoma cells as detected by high precision localization microscopy.

For receptor tyrosine kinases supramolecular organization on the cell membrane is critical for their function. Super-resolution fluorescence microscopy techniques have offered new opportunities for the analysis of single receptor localization. Here, we analysed the cluster formation of the epidermal growth factor receptor variant III (EGFRvIII), a deletion variant which is expressed in glioblastoma. The constitutively activated variant EGFRvIII is expressed in cells with an egfr gene amplification and is thought to enhance the tumorigenic potential especially of glioblastoma cells. Due to the lack of an adequate model system, it is still unclear how endogenous EGFRvIII expression alters cellular signalling and if it is organized in clusters like the wild type receptor. We have recently described the establishment of two pairs of iso-genetic cell lines (BS153 and DKMG), displaying endogenous EGFRvIII expression or not. Using these cell lines we investigated single receptor localization of EGFRvIII by high precision localization microscopy. Cluster analysis revealed that EGFRvIII is present in clusters on the surface of the cells, with about 60% or even more receptor molecules being assembled in clusters of approximately 100 nm in diameter whereby the cluster definition was iteratively determined. The signal to signal distance may indicate dimer formation while signal quantification indicates 1 × 106-5 × 106 EGFRvIII molecules per cell. Altogether, these data give unique insights into the membrane surface localization of EGFRvIII in glioblastoma cells. These insights will help to unveil the function of this tumour associated receptor variant which might lead to a better understanding of glioblastoma and therefore could lead to improved therapy approaches.