Détection, caractérisation et visualisation des structures transitoires de protéines par sondage au tryptophane

Thèse numérisée par la Division de la gestion de documents et des archives de l'Université de Montréal

Allosterically Tunable, DNA-Based Switches Triggered by Heavy Metals

Here we demonstrate the rational design of allosterically controllable, metal-ion-triggered molecular switches. Specifically, we designed DNA sequences that adopt two low energy conformations, one of which does not bind to the target ion and the other of which contains mismatch sites serving as specific recognition elements for mercury(II) or silver(I) ions. Both switches contain multiple metal binding sites and thus exhibit homotropic allosteric (cooperative) responses. As heterotropic allosteric effectors we employ single-stranded DNA sequences that either stabilize or destabilize the nonbinding state, enabling dynamic range tuning over several orders of magnitude. The ability to rationally introduce these effects into target-responsive switches could be of value in improving the functionality of DNA-based nanomachines

Bimodal brush-functionalized nanoparticles selective to receptor surface density.

Nanoparticles or drug carriers which can selectively bind to cells expressing receptors above a certain threshold surface density are very promising for targeting cells overexpressing specific receptors under pathological conditions. Simulations and theoretical studies have suggested that such selectivity can be enhanced by functionalizing nanoparticles with a bimodal polymer monolayer (BM) containing shorter ligated chains and longer inert protective chains. However, a systematic study of the effect of these parameters under tightly controlled conditions is still missing. Here, we develop well-defined and highly specific platforms mimicking particle-cell interface using surface chemistry to provide a experimental proof of such selectivity. Using surface plasmon resonance and atomic force microscopy, we report the selective adsorption of BM-functionalized nanoparticles, and especially, a significant enhanced selective behavior by using a BM with longer protective chains. Furthermore, a model is also developed to describe the repulsive contribution of the protective brush to nanoparticle adsorption. This model is combined with super-selectivity theory to support experimental findings and shows that the observed selectivity is due to the steric energy barrier which requires a high number of ligand-receptor bonds to allow nanoparticle adsorption. Finally, the results show how the relative length and molar ratio of two chains can be tuned to target a threshold surface density of receptors and thus lay the foundation for the rational design of BM-functionalized nanoparticles for selective targeting

Optimizing the specificity window of biomolecular receptors using structure-switching and allostery

To ensure maximum specificity (i.e., minimize cross -reactivity with structurally similar analogues of the desired target), most bioassays invoke "stringency", the careful tuning of the conditions employed (e.g., pH, ionic strength, or temperature). Willingness to control assay conditions will fall, however, as quantitative, single-step biosensors begin to replace multistep analytical processes. This is especially true for sensors deployed in vivo, where the tuning of such parameters is not just inconvenient but impossible. In response, we describe here the rational adaptation of two strategies employed by nature to tune the affinity of biomolecular receptors so as to optimize the placement of their specificity "windows" without the need to alter measurement conditions: structure-switching and allosteric control. We quantitatively validate these approaches using two distinct, DNA-based receptors: a simple, linear-chain DNA suitable for detecting a complementary DNA strand and a structurally complex DNA aptamer used for the detection of a small-molecuIe drug. Using these models, we show that, without altering assay conditions, structure -switching and allostery can tune the concentration range over which a receptor achieves optimal specificity over orders of magnitude, thus optimally matching the specificity window with the range of target concentrations expected to be seen in a given application

High-Precision, In Vitro Validation of the Sequestration Mechanism for Generating Ultrasensitive Dose-Response Curves in Regulatory Networks

Our ability to recreate complex biochemical mechanisms in designed, artificial systems provides a stringent test of our understanding of these mechanisms and opens the door to their exploitation in artificial biotechnologies. Motivated by this philosophy, here we have recapitulated in vitro the “target sequestration” mechanism used by nature to improve the sensitivity (the steepness of the input/output curve) of many regulatory cascades. Specifically, we have employed molecular beacons, a commonly employed optical DNA sensor, to recreate the sequestration mechanism and performed an exhaustive, quantitative study of its key determinants (e.g., the relative concentrations and affinities of probe and depletant). We show that, using sequestration, we can narrow the pseudo-linear range of a traditional molecular beacon from 81-fold (i.e., the transition from 10% to 90% target occupancy spans an 81-fold change in target concentration) to just 1.5-fold. This narrowing of the dynamic range improves the sensitivity of molecular beacons to that equivalent of an oligomeric, allosteric receptor with a Hill coefficient greater than 9. Following this we have adapted the sequestration mechanism to steepen the binding-site occupancy curve of a common transcription factor by an order of magnitude over the sensitivity observed in the absence of sequestration. Given the success with which the sequestration mechanism has been employed by nature, we believe that this strategy could dramatically improve the performance of synthetic biological systems and artificial biosensors

Employing the Metabolic “Branch Point Effect” to Generate an All-or-None, Digital-like Response in Enzymatic Outputs and Enzyme-Based Sensors

Here, we demonstrate a strategy to convert the graded Michaelis−Menten response typical of unregulated enzymes into a sharp, effectively all-or-none response. We do so using an approach analogous to the “branch point effect”, a mechanism observed in naturally occurring metabolic networks in which two or more enzymes compete for the same substrate. As a model system, we used the enzymatic reaction of glucose oxidase (GOx) and coupled it to a second, nonsignaling reaction catalyzed by the higher affinity enzyme hexokinase (HK) such that, at low substrate concentrations, the second enzyme outcompetes the first, turning off the latter’s response. Above an arbitrarily selected “threshold” substrate concentration, the nonsignaling HK enzyme saturates leading to a “sudden” activation of the first signaling GOx enzyme and a far steeper dose−response curve than that observed for simple Michaelis−Menten kinetics. Using the well-known GOx-based amperometric glucose sensor to validate our strategy, we have steepen the normally graded response of this enzymatic sensor into a discrete yes/no output similar to that of a multimeric cooperative enzyme with a Hill coefficient above 13. We have also shown that, by controlling the HK reaction we can precisely tune the threshold target concentration at which we observe the enzyme output. Finally, we demonstrate the utility of this strategy for achieving effective noise attenuation in enzyme logic gates. In addition to supporting the development of biosensors with digital-like output, we envisage that the use of all-or-none enzymatic responses will also improve our ability to engineer efficient enzyme-based catalysis reactions in synthetic biology applications