Biology subjects

Francois, P.

Publications and source records attributed to Francois, P..

4 recordsLinked to original sources

bioRxiv2018

Bipolar spindle formation is a fast, irreversible process requiring Kinesin-5 crosslinking and sliding modalities

GRAPHICAL ABSTRACT\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=128 SRC=\"FIGDIR/small/452821_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (30K):\norg.highwire.dtl.DTLVardef@ad6c3corg.highwire.dtl.DTLVardef@19cf957org.highwire.dtl.DTLVardef@b5c2a8org.highwire.dtl.DTLVardef@fece04_HPS_FORMAT_FIGEXP M_FIG C_FIG Separation of duplicated spindle poles is the first step in forming the mitotic spindle. Kinesin-5 crosslinks and slides anti-parallel microtubules, but it is unclear how these two activities contribute to the first steps in spindle formation. In this study we report that in monopolar spindles, the duplicated spindle poles snap apart in a fast and irreversible step that produces a nascent bipolar spindle. Using mutations in Kinesin-5 that inhibit microtubule sliding, we show crosslinking alone drives the fast, irreversible pole separation. Electron tomography revealed microtubule pairs in monopolar spindles have short overlaps that intersect at high angles and are unsuited for ensemble Kinesin-5 sliding. However, maximal extension of a subset of microtubule pairs approaches the length of nascent bipolar spindles and is consistent with a Kinesin-5 crosslinking driven transition. Finally, stochastic microtubule sliding by Kinesin-5 stabilizes the nascent spindle and sets a stereotyped equilibrium length.

biophysics↗

bioRxiv2018

Fooling the classifier: Ligand antagonism and adversarial examples

Machine learning algorithms can be fooled by small well-designed adversarial perturbations. This is reminiscent of cellular decision-making where ligands (called antagonists) prevent correct signalling, like in early immune recognition. We draw a formal analogy between neural networks used in machine learning and models of cellular decision-making (adaptive proofreading). We apply attacks from machine learning to simple decision-making models, and show explicitly the correspondence to antagonism by weakly bound ligands. Such antagonism is absent in more nonlinear models, which inspired us to implement a biomimetic defence in neural networks filtering out adversarial perturbations. We then apply a gradient-descent approach from machine learning to different cellular decision-making models, and we reveal the existence of two regimes characterized by the presence or absence of a critical point for the gradient. This critical point causes the strongest antagonists to lie close to the decision boundary. This is validated in the loss landscapes of robust neural networks and cellular decision-making models, and observed experimentally for immune cells. For both regimes, we explain how associated defence mechanisms shape the geometry of the loss landscape, and why different adversarial attacks are effective in different regimes. Our work connects evolved cellular decision-making to machine learning, and motivates the design of a general theory of adversarial perturbations, both for in vivo and in silico systems.

biophysics↗

bioRxiv2018

A dual sRNA in Staphylococcus aureus induces a metabolic switch responding to glucose consumption

Pathogenic bacteria must rapidly adapt to ever-changing environmental signals or nutrient availability resulting in metabolism remodeling. The carbon catabolite repression represents a global regulatory system, allowing the bacteria to express genes involved in carbon utilization and metabolization of the preferred carbon source. In Staphylococcus aureus, regulation of catabolite repressing genes is mediated by the carbon catabolite protein A (CcpA). Here, we have identified a CcpA-dependent small non-coding RNA, RsaI that is inhibited by high glucose concentrations. RsaI represses the translation of mRNAs encoding a major permease of glucose uptake, the FN3K enzyme that protects proteins against damages caused by high glucose concentrations, and IcaR, the transcriptional repressor of exopolysaccharide production. Besides, RsaI regulates the activities of other sRNAs responding to the uptake of glucose-6 phosphate or NO. Finally, RsaI inhibits the expression of several enzymes involved in carbon catabolism pathway, and activates genes involved in energy production, fermentation and NO detoxification when the glucose concentration decreases. This multifunctional RNA provides a signature for a metabolic switch when glucose is scarce and growth is arrested.

microbiology↗

bioRxiv2017

Endocytosis caused by liquid-liquid phase separation of proteins

Membrane invagination and vesicle formation are key steps in endocytosis and cellular trafficking. Here, we show that endocytic coat proteins with prion-like domains (PLDs) form hemispherical puncta in the budding yeast, S. cerevisiae. These puncta have the hallmarks of biomolecular condensates and enable membrane remodeling to drive actin-independent endocytosis. The puncta, which we refer to as endocytic condensates, form and dissolve reversibly in response to changes in temperature and solution conditions. The condensates are organized around dynamic protein-protein interaction networks, which involve interactions among PLDs with high glutamine contents. The endocytic coat protein Sla1 is at the hub of the protein-protein interaction network. Using active rheology, we indirectly characterized the material properties of endocytic condensates. These experiments show that endocytic condensates are viscoelastic materials and allow us to estimate the interfacial tension between endocytic condensates and their surroundings. We then adapt the physics of contact mechanics, specifically the contact theory of Hertz, to develop a quantitative framework for describing how interfacial tensions among condensates, the membrane, and the cytosol can deform the plasma membrane to enable actin independent endocytosis.

cell biology↗