Biology subjects

Herice, C.

Publications and source records attributed to Herice, C..

3 recordsLinked to original sources

bioRxiv2025

Unveiling the molecular identity of plant autophagic compartments: A proteo-lipidomic study in Arabidopsis thaliana

Autophagy is an intracellular degradation and recycling pathway essential for cell quality control and plant tolerance to stress. The formation and maturation of autophagosomes, the cargo-packing vesicles, rely on extensive membrane remodeling, yet little is known about the nature, dynamics and functions of lipids in these events. Here, we established a method combing cell fractionation and immuno-isolation in native conditions to purify autophagic membranes from Arabidopsis thaliana. By integrating proteomic and lipidomic analyses, we defined their molecular footprint which, coupled to colocalization analyses, revealed potent actors involved in lipid metabolism, membrane trafficking and membrane remodeling, supporting a close interplay between lipid homeostasis and autophagosome biology. Characterization of the phagophore lipid composition showed low sterol and sphingolipid content, a predominance of glycerophospholipids, including phosphoinositides, and a particular enrichment in phosphatidylcholine and phosphatidylglycerol. Comparisons with other plant endomembranes and autophagic compartments from other organisms revealed the singularity of this lipid signature and notably identified phosphatidylglycerol as a plant-specific component of autophagic membranes. Analyses of inducible phosphatidylglycerol-deficient plants showed defects in autophagy activity thereby supporting the functional relevance of the phagophore lipid composition, particularly that of phosphatidylglycerol homeostasis. Together, our findings place lipids as fundamental components of the autophagy molecular landscape and provide a framework to further investigate their contribution to autophagosome biology and functions in plant acclimation to environmental changes. Significance StatementAutophagy is catabolic pathway critical for eukaryotic life and essential for plant acclimation to stress. It hinges on the remarkable plasticity of a specialized membrane, the phagophore, to orchestrate and support intense membrane remodeling events towards the formation of the autophagic vesicle containing cargo. To resolve their elusive molecular bases, we need to integrate inputs from both components of biological membranes: proteins and lipids, yet information regarding lipids is still very limited. Here, we isolated plant phagophores, established their protein and lipid molecular footprint, revealed its singularity and showed its physiological and functional relevance for autophagy activity. Our work highlights lipids as key regulators of plant autophagy and opens new doors for investigating how membrane dynamics shape cellular stress responses.

plant biology↗

bioRxiv2019

A mean-field approach to the dynamics of networks of complex neurons, from nonlinear Integrate-and-Fire to Hodgkin-Huxley models

We present a mean-field formalism able to predict the collective dynamics of large networks of conductance-based interacting spiking neurons. We apply this formalism to several neuronal models, from the simplest Adaptive Exponential Integrate-and-Fire model to the more complex Hodgkin-Huxley and Morris-Lecar models. We show that the resulting mean-field models are capable of predicting the correct spontaneous activity of both excitatory and inhibitory neurons in asynchronous irregular regimes, typical of cortical dynamics. Moreover, it is possible to quantitatively predict the populations response to external stimuli in the form of external spike trains. This mean-field formalism therefore provides a paradigm to bridge the scale between population dynamics and the microscopic complexity of the individual cells physiology. NEW & NOTEWORTHYPopulation models are a powerful mathematical tool to study the dynamics of neuronal networks and to simulate the brain at macroscopic scales. We present a mean-field model capable of quantitatively predicting the temporal dynamics of a network of complex spiking neuronal models, from Integrate-and-Fire to Hodgkin-Huxley, thus linking population models to neurons electrophysiology. This opens a perspective on generating biologically realistic mean-field models from electrophysiological recordings.

neuroscience↗

bioRxiv2019

Pathway-dependent regulation of sleep dynamics in a network model of the sleep-wake cycle

Sleep is a fundamental homeostatic process within the animal kingdom. Although various brain areas and cell types are involved in the regulation of the sleep-wake cycle, it is still unclear how different pathways between neural populations contribute to its regulation. Here we address this issue by investigating the behavior of a simplified network model upon synaptic weight manipulations. Our model consists of three neural populations connected by excitatory and inhibitory synapses. Activity in each population is described by a firing-rate model, which determines the state of the network. Namely wakefulness, rapid eye movement (REM) sleep or non-REM (NREM) sleep. By systematically manipulating the synaptic weight of every pathway, we show that even this simplified model exhibits non-trivial behaviors: for example, the wake-promoting population contributes not just to the induction and maintenance of wakefulness, but also to sleep induction. Although a recurrent excitatory connection of the REM-promoting population is essential for REM sleep genesis, this recurrent connection does not necessarily contribute to the maintenance of REM sleep. The duration of NREM sleep can be shortened or extended by changes in the synaptic strength of the pathways from the NREM-promoting population. In some cases, there is an optimal range of synaptic strengths that affect a particular state, implying that the amount of manipulations, not just direction (i.e., activation or inactivation), needs to be taken into account. These results demonstrate pathway-dependent regulation of sleep dynamics and highlight the importance of systems-level quantitative approaches for sleep-wake regulatory circuits.\n\nAuthor SummarySleep is essential and ubiquitous across animal species. Over the past half-century, various brain areas, cell types, neurotransmitters, and neuropeptides have been identified as part of a sleep-wake regulating circuitry in the brain. However, it is less explored how individual neural pathways contribute to the sleep-wake cycle. In the present study, we investigate the behavior of a computational model by altering the strength of connections between neuronal populations. This computational model is comprised of a simple network where three neuronal populations are connected together, and the activity of each population determines the current state of the model, that is, wakefulness, rapid-eye-movement (REM) sleep or non-REM (NREM) sleep. When we alter the connection strength of each pathway, we observe that the effect of such alterations on the sleep-wake cycle is highly pathway-dependent. Our results provide further insights into the mechanisms of sleep-wake regulation, and our computational approach can complement future biological experiments.

neuroscience↗