Biology subjects

Opitz, T.

Publications and source records attributed to Opitz, T..

9 recordsLinked to original sources

bioRxiv2026

Targeting epilepsy with photopharmacology in human brain tissue

Photo-activatable drugs (PDs) are rapidly emerging as precision therapeutics across biomedical research, yet their potential in epilepsy treatment has remained understudied. Given that 30% of epilepsies are medically refractory, and anti-seizure medications often cause multi-organ side-effects, PDs could break new ground. Here, we evaluate light-switchable ion-channel blockers QAQ and CQAQ, and a newly developed caged propofol (CaP), in murine brain slices, and postsurgical brain tissue from patients with epilepsy or brain tumors. In mice, we show that QAQ/CQAQ reversibly suppress neuronal firing, while photo-activated CaP prolonged inhibitory post-synaptic currents and enhanced leak current. While QAQ caused identical effects in human tissue, CQAQ unexpectedly increased firing. Activated CaP robustly suppressed epileptiform activity across species. This work establishes CaP as a tool for neuroscience and disease-related studies. Our results highlight the necessity for early human model testing in biomedical research, and showcase photopharmacology as a potential powerful approach to control human epilepsy.

pharmacology and toxicology↗

bioRxiv2024

Region-specific spreading depolarization drives aberrant post-ictal behavior

Confusion, aphasia, and unaware wandering are prominent post-ictal symptoms regularly observed in temporal lobe epilepsy (TLE)1. Despite the potentially life-threatening nature of the immediate post-ictal state2, its neurobiological underpinnings remain understudied3. We provide evidence in mice and humans that seizure-associated focal spreading depolarization (sSD) is a pathoclinical key factor in epilepsy. Using two-photon or widefield imaging (hippocampus, neocortex), field potential and single unit recordings, and behavioral assessment in mice, we first studied seizures during viral encephalitis, and subsequently established an optogenetic approach to dissociate hippocampal seizures and SD. We find region-specific occurrence of sSD that displays distinct spatial trajectories to preceding seizures, and show that seizure-related and isolated hippocampal SD prompt post-ictal wandering. This clinically relevant locomotor phenotype occurred in the absence of hippocampal SD progression to the neocortex. Finally, we confirm sSD existence in human epilepsy, in a patient cohort with refractory focal epilepsy, via Behnke-Fried electrode recordings. In this cohort, sSD displayed a similar temporomesial propensity as in mice. This work uncovers sSD as a previously underrecognized pathoclinical entity underlying postictal behavioral abnormalities in epilepsy. Our results carry wide-reaching ramifications for epilepsy research and neurology, and challenge current EEG-standards.

neuroscience↗

bioRxiv2024

Spatio-temporal dynamics of attacks around deaths of wolves: A statistical assessment of lethal control efficiency in France

The lethal control of large carnivores is criticized regarding its efficiency to prevent hotspots of attacks on livestock. Previous studies, mainly focused on North America, provided mixed results. We evaluated the effects of wolf lethal removals on the distribution of attack intensities in the French Alps between 2011 and 2020, using a Before After Control-Impact approach with retrospective data. We built an original framework combining both continuous spatial and temporal scales and a 3D kernel estimation. We compared the attack intensities observed before and after the legal killings of wolves on a period of 90 days and on a range of 10 km, and with control situations where no removal occurred. The analysis was corrected for the presence of livestock. A moderate decrease of attack intensity was the most common outcome after the lethal removal of a single wolf. This reduction was greatly amplified when removing two or three wolves. The scale of analysis also modulated this general pattern, with decreases being generally amplified at a small spatio-temporal range. Contextual factors (e.g., geographical or seasonal variations) could also lead to deviations from this general pattern. Overall, between 2011 and 2020, lethal control of wolves in France generally contributed to reduce livestock attacks, but mainly locally and to a minor extent. Our results highlight the importance of accounting for scale in such assessments and suggest that the evaluation of the effectiveness of lethal removals in reducing livestock predation might be more relevant in a local context. As a next step, we recommend to move forward from patterns to mechanisms by linking the effects of lethal control on wolves to their effects on attacks through analysis of fine-scaled data on wolves and livestock.

ecology↗

bioRxiv2021

An astrocytic signaling loop for frequency-dependent control of dendritic integration and spatial learning

Dendrites of hippocampal CA1 pyramidal cells amplify clustered glutamatergic input by activation of voltage-gated sodium channels and N-methyl-D-aspartate receptors (NMDARs). NMDAR activity depends on the presence of NMDAR co-agonists such as D-serine, but how co-agonists influence dendritic integration is not well understood. Using combinations of whole-cell patch clamp, iontophoretic glutamate application, two-photon excitation fluorescence microscopy and glutamate uncaging we found that exogenous D-serine reduces the threshold of dendritic spikes and increases their amplitude. Triggering an astrocytic mechanism controlling endogenous D-serine supply via endocannabinoid receptors (CBRs) also increased dendritic spiking. Unexpectedly, this pathway was activated by pyramidal cell activity primarily in the theta range, which required HCN channels and astrocytic CB1Rs. Therefore, astrocytes close a positive and frequency-dependent feedback loop between pyramidal cell activity and their integration of dendritic input. Its disruption led to an impairment of spatial memory, which demonstrates its behavioral relevance.

neuroscience↗

bioRxiv2021

Spatio-temporal point processes as meta-models for population dynamics in heterogeneous landscapes

Landscape heterogeneity affects population dynamics, which determine species persistence, diversity and interactions. These relationships can be accurately represented by advanced spatially-explicit models (SEMs) allowing for high levels of detail and precision. However, such approaches are characterised by high computational complexity, high amount of data and memory requirements, and spatio-temporal outputs may be difficult to analyse. A possibility to deal with this complexity is to aggregate outputs over time or space, but then interesting information may be masked and lost, such as local spatio-temporal relationships or patterns. An alternative solution is given by meta-models and meta-analysis, where simplified mathematical relationships are used to structure and summarise the complex transformations from inputs to outputs. Here, we propose an original approach to analyse SEM outputs. By developing a meta-modelling approach based on spatio-temporal point processes (STPPs), we characterise spatio-temporal population dynamics and landscape heterogeneity relationships in agricultural contexts. A landscape generator and a spatially-explicit population model simulate hierarchically the pest-predator dynamics of codling moth and ground beetles in apple orchards over heterogeneous agricultural landscapes. Spatio-temporally explicit outputs are simplified to marked point patterns of key events, such as local proliferation or introduction events. Then, we construct and estimate regression equations for multi-type STPPs composed of event occurrence intensity and magnitudes. Results provide local insights into spatio-temporal dynamics of pest-predator systems. We are able to differentiate the contributions of different driver categories (i.e., spatio-temporal, spatial, population dynamics). We highlight changes in the effects on occurrence intensity and magnitude when considering drivers at global or local scale. This approach leads to novel findings in agroecology where the organisation of cultivated fields and semi-natural elements are known to play a crucial role for pest regulation. It aids to formulate guidelines for biological control strategies at global and local scale.

ecology↗

bioRxiv2021

More pests but less treatments: ambivalent effect of landscape complexity on Conservation Biological Control

In agricultural landscapes, the amount and organization of crops and semi-natural habitats (SNH) have the potential to promote a bundle of ecosystem services due to their influence on ecological community at multiple spatio-temporal scales. SNH are relatively undisturbed and are often source of complementary resources and refuges, supporting more diverse and abundant natural pest enemies. However, the nexus of SNH proportion and organization with pest suppression is not trivial. It is thus crucial to understand how the behavior of pest and auxiliary species, the underlying landscape structure, and their interaction may influence conservation biological control (CBC). Here, we develop a generative stochastic landscape model to simulate realistic agricultural landscape compositions and configurations of fields and linear elements. Generated landscapes are used as spatial support over which we simulate a spatially explicit predator-prey dynamic model. We find that SNH boost predator population, but predator movement from hedges to fields is fundamental for an efficient pest regulation by auxiliaries and to decrease pesticide treatments. Moreover landscape elements may lead to different effects on pest reduction depending on the considered scale. Integration of species behaviors and traits with landscape structure at multiple scales are needed to provide useful insights for CBC.

ecology↗

bioRxiv2020

Ste20-like kinase is critical for inhibitory synapse maintenance and its deficiency confers a developmental dendritopathy

The size and structure of the dendritic arbor play important roles in determining how synaptic inputs of neurons are converted to action potential output. The regulatory mechanisms governing the development of dendrites, however, are insufficiently understood. The evolutionary conserved Ste20/Hippo kinase pathway has been proposed to play an important role in regulating the formation and maintenance of dendritic architecture. A key element of this pathway, Ste20-like kinase (SLK), regulates cytoskeletal dynamics in non-neuronal cells and is strongly expressed throughout neuronal development. However, its function in neurons is unknown. We show that during development of mouse cortical neurons, SLK has a surprisingly specific role for proper elaboration of higher, [≥] 3rd, order dendrites. Moreover, we demonstrate that SLK is required to maintain excitation-inhibition balance. Specifically, SLK knockdown caused a selective loss of inhibitory synapses and functional inhibition after postnatal day 15, while excitatory neurotransmission was unaffected. Finally, we show that this mechanism may be relevant for human disease, as dysmorphic neurons within human cortical malformations revealed significant loss of SLK expression. Overall, the present data identify SLK as a key regulator of both dendritic complexity during development and of inhibitory synapse maintenance.

neuroscience↗

bioRxiv2020

Prediction of regional wildfire activity with a probabilistic Bayesian framework

O_LIModelling wildfire activity is crucial for informing science-based risk management and understanding fire-prone ecosystem functioning worldwide. Models also help to disentangle the relative roles of different factors, to understand wildfire predictability or to provide insights into specific events. C_LIO_LIHere, we develop a two-component Bayesian hierarchically-structured probabilistic model of daily fire activity, which are modelled as the outcome of a marked point process in which individual fires are the points (occurrence component) and the fire sizes are the marks (size component). The space-time Poisson model for occurrence is adjusted to gridded fire counts using the integrated nested Laplace approximation (INLA) combined with the Stochastic Partial Differential Equation (SPDE) approach. The size model is based on piecewise-estimated Pareto and Generalized-Pareto distributions, also adjusted with INLA. The Fire Weather Index (FWI) and Forest Area are the main explanatory variables. Seasonal and spatial residuals as well as a post-2003 effect are included to improve the consistency of the relationship between climate and fire occurrence, in accordance with parsimonious criteria. C_LIO_LIA set of 1000 simulations of the posterior model of fire activity is evaluated at various temporal and spatial scales in Mediterranean France. The number of escaped fires ([≥]1ha) across the region can be coarsely reproduced at the daily scale, and is more accurately predicted on a weekly basis or longer. The regional weekly total number of larger fires (10 to 100 ha) can be predicted as well, but the accuracy decays with size, as the model uncertainty increases with event rareness. Local predictions of fire numbers or burnt areas likewise require a longer aggregation period to maintain model accuracy. C_LIO_LIRegarding the year 2003 -which was characterized by an extreme burnt area in France associated with a heat wave-, the estimation of the number of escaped fires was consistent with observations, but the model systematically underrepresents larger fires and burnt areas, which suggests that the FWI does not consistently rate the danger of large fire occurrence during heat waves. C_LIO_LIOur study sheds new light on the stochastic processes underlying fire hazard, and is promising for predicting and projecting future fire hazard in the context of climate change. C_LI

bioengineering↗

bioRxiv2019

Unspecific expression in limited excitatory cell populations in interneuron-targeting Cre-driver lines can have large functional effects

1Transgenic Cre-recombinase expressing mouse lines are widely used to express fluorescent proteins and opto-/chemogenetic actuators, making them a cornerstone of modern neuroscience. Particularly, the investigation of interneurons has benefitted from the ability to target genetic constructs to defined cell types. However, the cell type specificity of some mouse lines has been called into questions. Here we show for the first time the functional consequences of unspecific expression in a somatostatin-Cre (SST-Cre) mouse line. We find large optogenetically evoked excitatory currents originating from unspecifically targeted CA3 pyramidal cells. We also used public Allen Brain Institute data to estimate expression specificity in other Cre lines. Another SST-Cre mouse lines shows comparable unspecificity, whereas a Parvalbumin-Cre mouse line shows much less unspecific expression. Finally, we make suggestions to ensure that the results from in-vivo use of Cre mouse lines are interpretable.

neuroscience↗