Biology subjects

Brustlein, S.

Publications and source records attributed to Brustlein, S..

4 recordsLinked to original sources

bioRxiv2025

GABAergic neurons are major contributors of network inhibition in the neonatal hippocampus in-vivo

During development, neural network maturation is activity dependent. During the neonatal period, activity is provided by intermittent, spontaneous network activity patterns (SNAP) that occur independently of environment stimuli. Among the neurotransmitters that take part in neonatal development, the Gamma-amino-butyric acid (GABA) plays a pivotal role. GABAergic cells are the first to emerge the first to form functional synapses. GABA antagonists block hippocampal SNAPs in-vitro and alterations of GABAergic function dramatically impact cortical maturation. Based on these data, the traditional view is that the depolarizing action of GABA, a hallmark of immature networks in slice preparations, is at the core of developmental processes. However, in-vivo evidence for such depolarizing role is not clear, raising questions about the contribution of GABAergic neurons in-vivo. To address this issue we developed an in-vivo approach combining optogenetics and single-unit electrophysiology in non-anesthetized mice. This allowed us to both identify and manipulate hippocampal GABAergic cells while examining their influence on hippocampal SNAP. We found that, even during the first post-natal days, the net action of GABA is inhibitory, but not excitatory. This inhibitory action of GABA drastically increases after the second post-natal week.

neuroscience↗

bioRxiv2023

Functional networks of inhibitory neurons orchestrate synchrony in the hippocampus

Inhibitory interneurons are pivotal components of cortical circuits. Beyond providing inhibition, they have been proposed to coordinate the firing of excitatory neurons within cell assemblies. While the roles of specific interneuron subtypes have been extensively studied, their influence on pyramidal cell synchrony in vivo remains elusive. Employing an all-optical approach, we simultaneously recorded hippocampal interneurons and pyramidal cells and probed the network influence of individual interneurons using optogenetics. We demonstrate that CA1 interneurons form a functionally interconnected network that promotes synchrony through disinhibition during awake immobility, while preserving endogenous cell assemblies. Our network model underscores the importance of both cell assemblies and dense, unspecific interneuron connectivity in explaining our experimental findings, suggesting that interneurons may operate not only via division of labor but also through concerted activity.

neuroscience↗

bioRxiv2022

Light-inducible T cell engagers trigger, tune and shape the activation of primary T cells

To mount appropriate responses, T cells integrate complex sequences of receptor stimuli perceived during transient interactions with antigen presenting cells. Although it has been hypothesized that the dynamics of these interactions influence the outcome of T cell activation, methodological limitations have hindered its formal demonstration. Here, we have engineered the Light-inducible T cell engager (LiTe) system, a recombinant optogenetics-based molecular tool targeting the T Cell Receptor (TCR). The LiTe system constitutes a reversible molecular switch displaying exquisite reactivity. As proof of concept, we dissect how specific temporal patterns of TCR stimulation shape T cell activation patterns. We established that CD4+ T cells respond to intermittent TCR stimulation more efficiently than their CD8+ T cells counterparts and provide evidence that distinct sequences of TCR stimulation encode different cytokine programs. Finally, we show that the LiTe system could be exploited to create light-activated bispecific T cell engagers and manipulate tumor cell killing. Overall, the LiTe system provides new opportunities to understand how T cells integrate TCR stimulations and to trigger T cell cytotoxicity with a high spatiotemporal control.

immunology↗

bioRxiv2018

A theoretical high-density nanoscopy study leads to the design of UNLOC, an unsupervised algorithm

Among the superresolution microscopy techniques, the ones based on serially imaging sparse fluorescent particles enable the reconstruction of high-resolution images by localizing single molecules. Although challenging, single-molecule localization microscopy (SMLM) methods aim at listing the position of individual molecules leading a proper quantification of the stoichiometry and spatial organization of molecular actors. However, reaching the precision requested to localize accurately single molecules is mainly constrained by the signal-to-noise ratio (SNR) but also the density (Dframe), i.e., the number of fluorescent particles per m2 per frame. Of central interest, we establish here a comprehensive theoretical study relying on both SNR and Dframe to delineate the achievable limits for accurate SMLM observations. We demonstrate that, for low-density hypothesis (i.e. one-Gaussian fitting hypothesis), any fluorescent particle biases the localization of a particle of interest when they are distant by less than {approx} 600 nm. Unexpectedly, we also report that even dim fluorescent particles should be taken into account to ascertain unbiased localization of any surrounding particles. Therefore, increased Dframe quickly deteriorates the localization precision, the image reconstruction and more generally the quantification accuracy. The first outcome is a standardized density-SNR space diagram to determine the achievable SMLM resolution expected with experimental data. Additionally, this study leads to the identification of the essential requirements for implementing UNLOC (UNsupervised particle LOCalization), an unsupervised and fast computing algorithm approaching the Cramer-Rao bound for particles at high-density per frame and without any prior on their intensity. UNLOC is available as an ImageJ plugin.

biophysics↗