Accurate detection of dysmorphic nuclei using dynamic programming and supervised classification

A vast array of pathologies is typified by the presence of nuclei with an abnormal morphology. Dysmorphic nuclear phenotypes feature dramatic size changes or foldings, but also entail much subtler deviations such as nuclear protrusions called blebs. Due to their unpredictable size, shape and intensity, dysmorphic nuclei are often not accurately detected in standard image analysis routines. To enable accurate detection of dysmorphic nuclei in confocal and widefield fluorescence microscopy images, we have developed an automated segmentation algorithm, called Blebbed Nuclei Detector (BleND), which relies on two-pass thresholding for initial nuclear contour detection, and an optimal path finding algorithm, based on dynamic programming, for refining these contours. Using a robust error metric, we show that our method matches manual segmentation in terms of precision and outperforms state-of-the-art nuclear segmentation methods. Its high performance allowed for building and integrating a robust classifier that recognizes dysmorphic nuclei with an accuracy above 95%. The combined segmentation-classification routine is bound to facilitate nucleus-based diagnostics and enable real-time recognition of dysmorphic nuclei in intelligent microscopy workflows

Dysregulation of microtubule stability impairs morphofunctional connectivity in primary neuronal networks

Functionally related neurons assemble into connected networks that process and transmit electrochemical information. To do this in a coordinated manner, the number and strength of synaptic connections is tightly regulated. Synapse function relies on the microtubule (MT) cytoskeleton, the dynamics of which are in turn controlled by a plethora of MT-associated proteins, including the MT-stabilizing protein Tau. Although mutations in the Tau-encodingMAPT gene underlie a set of neurodegenerative disorders, termed tauopathies, the exact contribution of MT dynamics and the perturbation thereof to neuronal network connectivity has not yet been scrutinized. Therefore, we investigated the impact of targeted perturbations of MT stability on morphological (e.g., neurite- and synapse density) and functional (e.g., synchronous calcium bursting) correlates of connectivity in networks of primary hippocampal neurons. We found that treatment with MT-stabilizing or -destabilizing compounds impaired morphofunctional connectivity in a reversible manner. We also discovered that overexpression of MAPT induced significant connectivity defects, which were accompanied by alterations in MT dynamics and increased resistance to pharmacological MT depolymerization. Overexpression of a MAPT variant harboring the P301L point mutation in the MT-binding domain did far less, directly linking neuronal connectivity with Tau's MT binding affinity. Our results show that MT stability is a vulnerable node in tauopathies and that its precise pharmacological tuning may positively affect neuronal network connectivity. However, a critical balance in MT turnover causes it to be a difficult therapeutic target with a narrow operating window

Sustained synchronized neuronal network activity in a human astrocyte co-culture system

Impaired neuronal network function is a hallmark of neurodevelopmental and neurodegenerative disorders such as autism, schizophrenia, and Alzheimer's disease and is typically studied using genetically modified cellular and animal models. Weak predictive capacity and poor translational value of these models urge for better human derived in vitro models. The implementation of human induced pluripotent stem cells (hiPSCs) allows studying pathologies in differentiated disease-relevant and patient-derived neuronal cells. However, the differentiation process and growth conditions of hiPSC-derived neurons are non-trivial. In order to study neuronal network formation and (mal) function in a fully humanized system, we have established an in vitro co-culture model of hiPSC-derived cortical neurons and human primary astrocytes that recapitulates neuronal network synchronization and connectivity within three to four weeks after final plating. Live cell calcium imaging, electrophysiology and high content image analyses revealed an increased maturation of network functionality and synchronicity over time for co-cultures compared to neuronal monocultures. The cells express GABAergic and glutamatergic markers and respond to inhibitors of both neurotransmitter pathways in a functional assay. The combination of this co-culture model with quantitative imaging of network morphofunction is amenable to high throughput screening for lead discovery and drug optimization for neurological diseases

MYCN activation in hTERT immortalized RPE cells as a model for oncogene induced senescence

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Comprehensive pharmacological profiling in neuroblastoma cell lines using Deep Coverage Microscopy (DCM)

Chemoresistance is a major impediment to successful treatment of a growing number of cancer entities. This phenomenon can be circumvented through highly selective and efficient drugging of molecular targets and pathways implicated in the chemoresistance phenotype. We have recently discovered that MYC(N)-driven tumors show strong upregulation of genes involved in replicative stress (RS)-induced DNA damage repair (DDR). Thus, exploiting this pathway may offer a novel entry point for combinatorial chemotherapy. However, limited knowledge on drug-gene-phenotype interactions complicates rational selection of promising compounds. To address this topic in a systematic manner, we have established a high-content microscopy-based compound-screening assay that provides a holistic readout on DNA damage, cell morphology and cellular stress response. We have validated the approach using compounds that are known to induce DNA damage or replicative stress in a selected panel of neuroblastoma cell lines with different MYCN background. We are now applying it to assess interactions between these compounds and a selected gene set involved in RS/DDR. In doing so, we expect to reveal common modes of action between selected compounds and to infer putative synergies for combinatorial treatments modulating the genes involved in RS and/or DDR. Thus, with our work we aim at devising a more powerful, robust and integrative approach for assessing synthetic lethality. This will be a key strategy for more efficient killing of tumors and for use in patients in which conventional methods no longer show effect