A fast genetically encoded fluorescent sensor for faithful in vivo acetylcholine detection in mice, fish, worms and flies

Here we design and optimize a genetically encoded fluorescent indicator, iAChSnFR, for the ubiquitous neurotransmitter acetylcholine, based on a bacterial periplasmic binding protein. iAChSnFR shows large fluorescence changes, rapid rise and decay kinetics, and insensitivity to most cholinergic drugs. iAChSnFR revealed large transients in a variety of slice and in vivo preparations in mouse, fish, fly and worm. iAChSnFR will be useful for the study of acetylcholine in all organisms

A fast genetically encoded fluorescent sensor for faithful in vivo acetylcholine detection in mice, fish, worms and flies

Here we design and optimize a genetically encoded fluorescent indicator, iAChSnFR, for the ubiquitous neurotransmitter acetylcholine, based on a bacterial periplasmic binding protein. iAChSnFR shows large fluorescence changes, rapid rise and decay kinetics, and insensitivity to most cholinergic drugs. iAChSnFR revealed large transients in a variety of slice and in vivo preparations in mouse, fish, fly and worm. iAChSnFR will be useful for the study of acetylcholine in all organisms

Nicotine in the Endoplasmic Reticulum

Nicotine activates plasma membrane (PM) nicotinic receptors (nAChRs), but also permeates into the endoplasmic reticulum (ER) and cis-Golgi, and there binds to nascent nAChRs. Other psychiatric and abused drugs may also enter the ER and bind their classical targets. Further progress requires direct proof, quantification, and time resolution of these processes in live cells and in the brain of animals. Therefore, we are developing genetically encoded fluorescent biosensors to study the subcellular pharmacokinetics of neural drugs

Nicotine in the Endoplasmic Reticulum

Nicotine activates plasma membrane (PM) nicotinic receptors (nAChRs), but also permeates into the endoplasmic reticulum (ER) and cis-Golgi, and there binds to nascent nAChRs. Other psychiatric and abused drugs may also enter the ER and bind their classical targets. Further progress requires direct proof, quantification, and time resolution of these processes in live cells and in the brain of animals. Therefore, we are developing genetically encoded fluorescent biosensors to study the subcellular pharmacokinetics of neural drugs

Determining the pharmacokinetics of nicotinic drugs in the endoplasmic reticulum using biosensors

Nicotine dependence is thought to arise in part because nicotine permeates into the endoplasmic reticulum (ER), where it binds to nicotinic receptors (nAChRs) and begins an “inside-out” pathway that leads to up-regulation of nAChRs on the plasma membrane. However, the dynamics of nicotine entry into the ER are unquantified. Here, we develop a family of genetically encoded fluorescent biosensors for nicotine, termed iNicSnFRs. The iNicSnFRs are fusions between two proteins: a circularly permutated GFP and a periplasmic choline-/betaine-binding protein engineered to bind nicotine. The biosensors iNicSnFR3a and iNicSnFR3b respond to nicotine by increasing fluorescence at [nicotine] 75%. Reducing nicotine intake by 10-fold decreases activation to ∼20%. iNicSnFR3a and iNicSnFR3b also sense the smoking cessation drug varenicline, revealing that varenicline also permeates into the ER within seconds. Our iNicSnFRs enable optical subcellular pharmacokinetics for nicotine and varenicline during an early event in the inside-out pathway

Débat avec les responsables scientifiques de l’axe 3

Valérie Carayol : Vous avez dit que « dans la mêlée du direct, nous participons plutôt que nous symbolisons » et que « l’induction se vit au présent ». Hier, avec Wolfgang Settekorn qui nous a parlé de métaphorisations mutuelles avec des exemples visuels et avec Philippe Breton qui nous a parlé d’amalgame, on avait déjà esquissé un rapprochement entre l’induction et les dynamiques spatiales, pas obligatoirement une dynamique temporelle. Est-ce que vous pourriez préciser cette idée du direct, ..

Directed Evolution of a Selective and Sensitive Serotonin Sensor via Machine Learning

Serotonin plays a central role in cognition and is the target of most pharmaceuticals for psychiatric disorders. Existing drugs have limited efficacy; creation of improved versions will require better understanding of serotonergic circuitry, which has been hampered by our inability to monitor serotonin release and transport with high spatial and temporal resolution. We developed and applied a binding-pocket redesign strategy, guided by machine learning, to create a high-performance, soluble, fluorescent serotonin sensor (iSeroSnFR), enabling optical detection of millisecond-scale serotonin transients. We demonstrate that iSeroSnFR can be used to detect serotonin release in freely behaving mice during fear conditioning, social interaction, and sleep/wake transitions. We also developed a robust assay of serotonin transporter function and modulation by drugs. We expect that both machine-learning-guided binding-pocket redesign and iSeroSnFR will have broad utility for the development of other sensors and in vitro and in vivo serotonin detection, respectively

Recent Advances in Directed Phytase Evolution and Rational Phytase Engineering

Phytases are hydrolytic enzymes that initiate stepwise removal of phosphate from phytate. Phytate is the major phosphorous storage compound in cereal gains, oilseeds, and legumes and is indigestible by monogastric animals such as poultry and swine. Supplementation of phytase in animal feed proved to improve animal nutrition and decrease phosphorous pollution. Several phytases were discovered in the last century, and today a highly competitive market situation emerged the demands for phytases that are redesigned to excellently match industrial demands. Phytase engineering by directed evolution and rational design has offered a robust approach to tailor-made phytases with high specific activity, broad thermal and pH profile, and protease resistance. In this chapter, we summarized challenges and successful approaches employed in phytase engineering. Factors influencing phytase thermostability, pH stability, pH optima, and protease resistance have been discussed with respect to structural perspective and potential molecular mechanism for improvement. Importance of cooperative substitutions and a way to identify these interactions are discussed. Recent development in screening technology and molecular insights in combining key beneficial substitutions are detailed. In addition, strategies and approaches for rapid and efficient evolution of phytases and to understand structure function relationships on a molecular level have been proposed