Biology subjects

Masson, J.-B.

Publications and source records attributed to Masson, J.-B..

4 recordsLinked to original sources

bioRxiv2018

Live single molecule microscopy of HIV-1 assembly in host T cells reveals a spatio-temporal effect of the viral genome.

Monitoring virus assembly dynamic at the nanoscale level in host cells remains a major challenge. Human Immunodeficiency Virus type 1 (HIV-1) components are addressed to the plasma membrane where they assemble to form spherical particles of 100nm in diameter. HIV-1 Gag protein expression alone is sufficient to produce virus-like particles (VLPs) that resemble immature virus. Here, we monitored Gag assembly in host CD4 T lymphocytes using single molecule dynamics microscopy and energy mapping. A workflow allowing long time recordings of single Gag molecule localization, diffusion and effective energy maps was developed for robust quantitative analysis of HIV assembly and budding. Comparison of numerous cell plasma membrane assembling platforms in cells expressing wild type or assembly-defective Gag proteins showed that VLP formation last 15 minutes, with an assembly time of 5 minutes, and that the nucleocapsid domain is mandatory. Importantly, it reveals that the viral genome coordinates spatio-temporally HIV-1 assembly.

biophysics↗

bioRxiv2017

Mapping neurons and brain regions underlying sensorimotor decisions and sequences

A fundamental property of the nervous systems across the animal kingdom is the ability to select appropriate actions and sequences of actions in response to sensory cues. Many behaviors are physically mutually exclusive so commitment to one requires complete suppression of others. Further, because many behaviors are serially organized into sequences of actions, mechanisms must also exist that control transitions from one action to the next. The circuit mechanisms by which nervous systems achieve behavioral choice, stability and transitions are still incompletely understood. A key step in understanding these functions is to identify neurons and brain areas involved in controlling behavioral choice, stability and transitions. To do this, we developed an approach where we combined a large-scale neuronal inactivation screen with an automated action detection of sensorimotor decisions and sequences in response to a sensory cue. We characterized the response of wild-type larvae to a mechanosensory stimulus and found they can respond to the stimulus with a probabilistic sequence of 4 possible actions (head-cast, head-retraction, back-up and stop). We analyzed behaviors from around three hundred thousand larvae (N=2.9x105) where we selectively silenced small numbers of neuron types and individual neuron types systematically across the nervous system using a library of Drosophila GAL4 lines and determined the effect of these manipulations on larval mechanosensory responses. We identified neurons and brain-regions that when inactivated affected Drosophila larval sensorimotor decisions and sequence transitions between the different actions. Specifically, we identified 51 candidate lines for sensory processing and 24 candidate lines for competitive interactions. We also detected phenotype categories for sequence transitions consistent with a model of sequence generation where transitions and reversals are independently controlled. These findings provide the basis for understanding how sensorimotor decisions and sequence transition are controlled by the nervous system.

neuroscience↗

bioRxiv2017

Olfactory coding in the turbulent realm

Long-distance olfactory search behaviors depend on odor detection dynamics. Due to turbulence, olfactory signals travel as bursts of variable concentration and spacing and are characterized by long-tail distributions of odor/no-odor events, challenging the computing capacities of olfactory systems. How animals encode complex olfactory scenes to track the plume far from the source remains unclear. Here we focus on the coding of the plume temporal dynamics in moths. We compare responses of olfactory receptor neurons (ORNs) and antennal lobe projection neurons (PNs) to sequences of pheromone stimuli either with white-noise patterns or with realistic turbulent temporal structures simulating a large range of distances (8 to 64 m) from the odor source. For the first time, we analyze what information is extracted by the olfactory system at large distances from the source. Neuronal responses are analyzed using linear-nonlinear models fitted with white-noise stimuli and used for predicting responses to turbulent stimuli. We found that neuronal firing rate is less correlated with the dynamic odor time course when distance to the source increases because of improper coding during long odor and no-odor events that characterize large distances. Rapid adaptation during long puffs does not preclude however the detection of puff transitions in PNs. Individual PNs but not individual ORNs encode the onset and offset of odor puffs for any temporal structure of stimuli. A higher spontaneous firing rate coupled to an inhibition phase at the end of PN responses contributes to this coding property. This allows PNs to decode the temporal structure of the odor plume at any distance to the source, an essential piece of information moths can use in their tracking behavior.\n\nAuthor SummaryLong-distance olfactory search is a difficult task because atmospheric turbulence erases global gradients and makes the plume discontinuous. The dynamics of odor detections is the sole information about the position of the source. Male moths successfully track female pheromone plumes at large distances. Here we show that the moth olfactory system encodes olfactory scenes simulating variable distances from the odor source by characterizing puff onsets and offsets. A single projection neuron is sufficient to provide an accurate representation of the dynamic pheromone time course at any distance to the source while this information seems to be encoded at the population level in olfactory receptor neurons.

neuroscience↗

bioRxiv2017

Gradients Of Rac1 Nanoclusters Support Spatial Patterns Of Rac1 Signaling

The dynamics of the cytoskeleton and cell shape relies on the coordinated activation of RhoGTPase molecular switches. Among them, Rac1 participates to the orchestration in space and time of actin branching and protrusion/retraction cycles of the lamellipodia at the cell front during mesenchymal migration. Biosensor imaging has revealed a graded concentration of active GTP-loaded Rac1 in protruding regions of the cell. Here, using single molecule imaging and super-resolution microscopy, we reveal an additional supramolecular organization of Rac1. We find that, similarly to H-Ras, Rac1 partitions and is immobilized into nanoclusters of 50-100 molecules each. These nanoclusters assemble due to the interaction of the polybasic tail of Rac1 with the phosphoinositide lipids PIP2 and PIP3. The additional interactions with GEFs, GAPs, downstream effectors, and possibly other partners are responsible for an enrichment of Rac1 nanoclusters in protruding regions of the cell. Using optogenetics and micropatterning tools, we find that activation of Rac1 leads to its immobilization in nanoclusters and that the local level of Rac1 activity matches the local density of nanoclusters. Altogether, our results show that subcellular patterns of Rac1 activity are supported by gradients of signaling nanodomains of heterogeneous molecular composition, which presumably act as discrete signaling platforms. This finding implies that graded distributions of nanoclusters might encode spatial information.\n\nSignificance statementThe plasma membrane of eukaryotic cells is a highly organized surface where hundreds of incoming signals are transduced to the intracellular space. How cells encode faithfully this myriad of signals is a fundamental question. Here we show that Rac1, a critical membrane-bound protein involved in the regulation of cytoskeletal dynamics, forms small aggregates together with other regulating proteins. These supramolecular assemblies, called nanoclusters, are the \"quantal\" units of signaling. By increasing the local concentration, nanoclusters set thresholds for downstream signaling and ensure the fidelity of information transduction. We found that Rac1 nanoclusters are distributed as spatial gradients matching the patterns of Rac1 activity. We propose that cells can encode positional information through distributed signaling quanta, hereby ensuring spatial fidelity.

biophysics↗