Biology subjects

Rouches, M.

Publications and source records attributed to Rouches, M..

5 recordsLinked to original sources

bioRxiv2025

Trainable computation in molecular networks

Reports of learning in single cells without genetic change span decades yet remain controversial, in part because there is no accepted general molecular mechanism for training comparable to gradient-based training or Hebbian learning in neural circuits. Here we identify a minimal set of ingredients sufficient to realize non-genetic learning, drawing inspiration from Boltzmann neural networks. First, dense reversible interaction networks provide an expressive substrate in which modulating the concentrations of a small set of mediator species can reprogram function without altering the underlying interaction parameters. Second, a simple rate-sensitive autoregulatory scheme that adjusts these mediator levels provides a local Hebbian-like training rule that can train the same network for diverse tasks, including Pavlovian conditioning, supervised classification, and generative tuning of bet-hedging ratios to match environmental statistics. We show that this autoregulatory training rule is model free and applies to reversible multimerization networks of arbitrary complexity, so training can compensate for unknown or unmodeled interactions present in vivo. These results suggest design principles for trainable synthetic cellular circuits and indicate how molecular systems could learn statistical features of their environments through experience.

systems biology↗

bioRxiv2024

Prewetting couples membrane and protein phase transitions to greatly enhance coexistence in models and cells.

Biopolymers that separate into condensed and dilute phases in solution also prewet membranes when one or more components couple to membrane lipids. Here we demonstrate that this prewetting transition becomes exquisitely sensitive to lipid composition when membranes have compositions near the boundary of liquid-ordered/liquid-disordered phase coexistence. In simulation and reconstitution, we couple polyelectrolytes to membranes of saturated lipids, unsaturated lipids, and cholesterol, and find that the coexistence of prewet and dry surface phases is dramatically potentiated by proximity to the membrane phase transition. In cells, we employ an optogenetic tool to characterize prewetting both at the plasma membranes (PM) and the endoplasmic reticulum (ER), and find that prewetting is potentiated or inhibited by perturbations of membrane composition. Prewetting can also mediate membrane adhesion, with avidity dependent on membrane composition. This effect is demonstrated in cells through the potentiation or inhibition of ER-PM contact sites. The strong correspondence between results in simulation, reconstitution, and cells demonstrates a new role for membrane lipids in regulating the recruitment and assembly of soluble proteins.

biophysics↗

bioRxiv2021

Rapid propagation of membrane tension at a presynaptic terminal

Many cellular activities, such as cell migration1, cell division2,3, signaling4,5, infection6, phagocytosis7 and exo-endocytosis8-11, generate membrane tension gradients that in turn regulate them12. Moreover, membrane flows, which are driven by tension gradients, can limit exo-endocytosis coupling in space and time, as net membrane flow from exocytic to endocytic sites is required to maintain membrane homeostasis13. However, there is controversy over how rapidly plasma membrane flows can relax tension gradients; contrary to the common view12,14,15, recent work showed membrane tension does not equilibrate in several cell types16. Here we show membrane tension can propagate rapidly or slowly, spanning orders of magnitude in speed, depending on cell type. In a neuronal terminal specialized for rapid synaptic vesicle turnover and where exo-endocytosis events occur at distinct loci, membrane tension equilibrates within seconds. By contrast, membrane tension does not propagate in neuroendocrine adrenal chromaffin cells secreting catecholamines. Thus, slow membrane flow and tension equilibration may confine exo- and exocytosis to the same loci17. Stimulation of exocytosis causes a rapid, global decrease in the synaptic terminal membrane tension, which recovers slowly due to endocytosis. Our results demonstrate membrane tension propagates rapidly at neuronal terminals and varies during synaptic activity, likely contributing to exo-endocytosis coupling.

biophysics↗

bioRxiv2021

Surface Densities Prewet a Near-Critical Membrane

Recent work has highlighted roles for thermodynamic phase behavior in diverse cellular processes. Proteins and nucleic acids can phase separate into three-dimensional liquid droplets in the cytoplasm and nucleus and the plasma membrane of animal cells appears tuned close to a two-dimensional liquid-liquid critical point. In some examples, cytoplasmic proteins aggregate at plasma membrane domains, forming structures such as the post-synaptic density and diverse signaling clusters. Here we examine the physics of these surface densities, employing minimal simulations of co-acervating polymers coupled to an Ising membrane surface in conjunction with a complementary Landau theory. We argue that these surface densities are a novel phase reminiscent of pre-wetting, in which a molecularly thin three-dimensional liquid forms on a usually solid surface. However, in surface densities the solid surface is replaced by a membrane with an independent propensity to phase separate. We show that proximity to criticality in the membrane dramatically increases the parameter regime in which a pre-wetting-like transition occurs, leading to a broad region where coexisting surface phases can form even when a bulk phase is unstable. Our simulations naturally exhibit three surface phase coexistence even though both the membrane and the polymer bulk can only display two phase coexistence on their own. We argue that the physics of these surface densities enables diverse functions seen in Eukaryotic cells.

biophysics↗

bioRxiv2018

bpRNA: Large-scale Automated Annotation and Analysis of RNA Secondary Structure

While RNA secondary structure prediction from sequence data has made remarkable progress, there is a need for improved strategies for annotating the features of RNA secondary structures. Here we present bpRNA, a novel annotation tool capable of parsing RNA structures, including complex pseudoknot-containing RNAs, to yield an objective, precise, compact, unambiguous, easily-interpretable description of all loops, stems, and pseudoknots, along with the positions, sequence, and flanking base pairs of each such structural feature. We also introduce several new informative representations of RNA structure types to improve structure visualization and interpretation. We have further used bpRNA to generate a web-accessible meta-database, \"bpRNA-1m\", of over 100,000 single-molecule, known secondary structures; this is both more fully and accurately annotated and over 20-times larger than existing databases. We use a subset of the database with highly similar ([≥]90% identical) sequences filtered out to report on statistical trends in sequence, flanking base pairs, and length. Both the bpRNA method and the bpRNA-1m database will be valuable resources both for specific analysis of individual RNA molecules and large-scale analyses such as are useful for updating RNA energy parameters for computational thermodynamic predictions, improving machine learning models for structure prediction, and for benchmarking structure-prediction algorithms.

bioinformatics↗