Biology subjects

van Hugte, E. J. H.

Publications and source records attributed to van Hugte, E. J. H..

4 recordsLinked to original sources

bioRxiv2026

MEA-LINK identifies the CCL4-CCR5 axis in neuronal hyperactivity control by human microglia

Microglia, the resident immune cells of the brain, act along a spectrum to maintain CNS homeostasis, respond to perturbations, and control neuronal activity. Disentangling the molecular mechanisms of human microglia-neuron crosstalk remains challenging due to the context-dependent, dynamic nature of their interaction. We introduce MEA-LINK, a systems-approach leveraging natural variation to screen for immune modulators of neuronal activity. This multi-modal platform integrates human induced pluripotent stem cell (hiPSC) technology with micro-electrode array (MEA) recordings and proteomic analyses of secreted immune factors, allowing for longitudinal samples and correlations across modalities. We applied MEA-LINK to explore microglia-neuron interactions during development and hyperactivity challenges. We show that human microglia accelerate neuronal network development and rescue hyperactive network phenotypes. Linking the secretome adaptations to neuronal network activity variations, we identified CCL4 as a top candidate in microglia-mediated hyperactivity control. Then, we functionally validated the context-dependent role of microglial CCL4 to neuronal CCR5 signaling in human neuronal networks. Our findings support a neuron-specific function of chemokines and their receptors in the brain and provide a new perspective for immune signaling in neuronal hyperactivity control. The MEA-LINK platform thus offers a foundation for comprehensive, systematic studies of human microglia-neuron interactions. HighlightsO_LIMEA-LINK integrates micro-electrode array recordings with proteomics of longitudinal samples to identify immune modulators of neuronal activity. C_LIO_LIHuman microglia rescue neuronal hyperactivity induced by pharmacological and genetic challenges. C_LIO_LIMicroglial CCL4 dampens neuronal activity via CCR5 signaling in a context-dependent manner. C_LI Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=147 SRC="FIGDIR/small/703799v1_ufig1.gif" ALT="Figure 1"> View larger version (39K): org.highwire.dtl.DTLVardef@18e44f7org.highwire.dtl.DTLVardef@151c450org.highwire.dtl.DTLVardef@12f7b89org.highwire.dtl.DTLVardef@57651b_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2023

SCN1A-deficient hiPSC-derived excitatory neuronal networks display mutation-specific phenotypes

Dravet syndrome is a severe epileptic encephalopathy, characterized by (febrile) seizures, behavioral problems and developmental delay. 80% of Dravet syndrome patients have a mutation in SCN1A, encoding NaV1.1. Milder clinical phenotypes, such as GEFS+ (generalized epilepsy with febrile seizures plus), can also arise from SCN1A mutations. Predicting the clinical phenotypic outcome based on the type of mutation remains challenging, even when the same mutation is inherited within one family. Both this clinical and genetic heterogeneity add to the difficulties of predicting disease progression and tailored prescription of anti-seizure medication. A better understanding of the neuropathology of different SCN1A mutations, might give insight in differentiating the expected clinical phenotype and best fit treatment choice. Initially it was recognized that loss of Na+ -current in inhibitory neurons specifically resulted in disinhibition and consequently seizure generation. However, the extent to which excitatory neurons contribute to the pathophysiology is currently debated, and might depend on the patient clinical phenotype or the specific mutation in SCN1A. To examine the genotype-phenotype correlations of SCN1A mutations in relation to excitatory neurons, we investigated a panel of patient-derived excitatory neuronal networks differentiated on multi-electrode arrays. We included patients with different clinical phenotypes, harboring different mutations in SCN1A, plus a family where the same mutation leads to both GEFS+ and Dravet syndrome. We hitherto describe a previously unidentified functional excitatory neuronal network phenotype in the context of epilepsy, which corresponded to seizurogenic network prediction patterns elicited by proconvulsive compounds. We find that excitatory neuronal networks were differently affected, dependent on the type of SCN1A mutation, but not on clinical severity. Specifically, pore domain mutations could be distinguished from voltage sensing domain mutations. Furthermore, all patients showed aggravated neuronal network responses upon febrile temperatures. While the basal neuronal network phenotypes could not be distinguished based on patient clinical severity, retrospective drug screening revealed that anti-seizure medication only affected GEFS+ patient-, but not Dravet patient-derived neuronal networks in a patient specific and clinically relevant manner. In conclusion, our results indicate a mutation-specific excitatory neuronal network phenotype, which recapitulates the foremost clinically relevant features, providing future opportunities for precision therapies. HighlightsO_LIHuman stem cell derived excitatory neurons are affected by mutations in SCN1A and display mutation-specific, but not clinical phenotype specific, neuronal network phenotypes C_LIO_LIThe neuronal network phenotype we describe corresponds to seizurogenic network prediction patterns in vitro C_LIO_LIExcitatory neuronal networks respond to Dravet syndrome clinically relevant triggers, like febrile temperatures and Dravet-contraindicated ASM Carbamazepine C_LIO_LIRetrospective drug screening revealed that GEFS+ neuronal networks, but not Dravet neuronal networks respond to ASM in a patient-specific and clinical relevant manner C_LI

neuroscience↗

bioRxiv2021

Human neuronal networks on micro-electrode arrays are a highly robust tool to study disease-specific genotype-phenotype correlations in vitro

Micro-electrode arrays (MEAs) are increasingly used to characterize neuronal network activity of human induced pluripotent stem-cell (hiPSC)-derived neurons. Despite their gain in popularity, MEA recordings from hiPSC-derived neuronal networks are not always used to their full potential in respect to experimental design, execution and data analysis. Therefore, we benchmarked the robustness and sensitivity of MEA-derived neuronal activity patterns derived from ten healthy individual control lines. We provide recommendations on experimental design and analysis to achieve standardization. With such standardization, MEAs can be used as a reliable platform to distinguish (disease-specific) network phenotypes. In conclusion, we show that MEAs are a powerful and robust tool to uncover functional neuronal network phenotypes from hiPSC-derived neuronal networks, and provide an important resource to advance the hiPSC field towards the use of MEAs for disease-phenotyping and drug discovery.

neuroscience↗

bioRxiv2019

Mitochondrial dysfunction impairs human neuronal development and reduces neuronal network activity and synchronicity

Epilepsy, intellectual and cortical sensory deficits and psychiatric manifestations are among the most frequent manifestations of mitochondrial diseases. Yet, how mitochondrial dysfunction affects neural structure and function remains largely elusive. This is mostly due to the lack of a proper in vitro translational neuronal model system(s) with impaired energy metabolism. Leveraging the induced pluripotent stem cell technology, from a cohort of patients with the common pathogenic m.3243A>G variant of mitochondrial encephalomyopathy, lactic acidosis and stroke-like episodes (MELAS), we differentiated excitatory cortical neurons (iNeurons) with normal (low heteroplasmy) and impaired (high heteroplasmy) mitochondrial function on an isogenic nuclear DNA background. iNeurons with high levels of heteroplasmy exhibited mitochondrial dysfunction, delayed neural maturation, reduced dendritic complexity and fewer functional excitatory synapses. Micro-electrode array recordings of neuronal networks with high heteroplasmy displayed reduced network activity and decreased synchronous network bursting. The impaired neural energy metabolism of iNeurons compromising the structural and functional integrity of neurons and neural networks, could be the primary driver of increased susceptibility to neuropsychiatric manifestations of mitochondrial disease.

neuroscience↗