Generation of ordered protein assemblies using rigid three-body fusion

Protein nanomaterial design is an emerging discipline with applications in medicine and beyond. A longstanding design approach uses genetic fusion to join protein homo-oligomer subunits via α-helical linkers to form more complex symmetric assemblies, but this method is hampered by linker flexibility and a dearth of geometric solutions. Here, we describe a general computational method that performs rigid three-body fusion of homo-oligomer and spacer building blocks to generate user-defined architectures, while at the same time significantly increasing the number of geometric solutions over typical symmetric fusion. The fusion junctions are then optimized using Rosetta to minimize flexibility. We apply this method to design and test 92 dihedral symmetric protein assemblies from a set of designed homo-dimers and repeat protein building blocks. Experimental validation by native mass spectrometry, small angle X-ray scattering, and negative-stain single-particle electron microscopy confirms the assembly states for 11 designs. Most of these assemblies are constructed from DARPins (designed ankyrin repeat proteins), anchored on one end by α-helical fusion and on the other by a designed homo-dimer interface, and we explored their use for cryo-EM structure determination by incorporating DARPin variants selected to bind targets of interest. Although the target resolution was limited by preferred orientation effects, small scaffold size, and the low-order symmetry of these dihedral scaffolds, we found that the dual anchoring strategy reduced the flexibility of the target-DARPIN complex with respect to the overall assembly, suggesting that multipoint anchoring of binding domains could contribute to cryo-EM structure determination of small proteins

Generation of ordered protein assemblies using rigid three-body fusion

Protein nanomaterial design is an emerging discipline with applications in medicine and beyond. A longstanding design approach uses genetic fusion to join protein homo-oligomer subunits via α-helical linkers to form more complex symmetric assemblies, but this method is hampered by linker flexibility and a dearth of geometric solutions. Here, we describe a general computational method that performs rigid three-body fusion of homo-oligomer and spacer building blocks to generate user-defined architectures, while at the same time significantly increasing the number of geometric solutions over typical symmetric fusion. The fusion junctions are then optimized using Rosetta to minimize flexibility. We apply this method to design and test 92 dihedral symmetric protein assemblies from a set of designed homo-dimers and repeat protein building blocks. Experimental validation by native mass spectrometry, small angle X-ray scattering, and negative-stain single-particle electron microscopy confirms the assembly states for 11 designs. Most of these assemblies are constructed from DARPins (designed ankyrin repeat proteins), anchored on one end by α-helical fusion and on the other by a designed homo-dimer interface, and we explored their use for cryo-EM structure determination by incorporating DARPin variants selected to bind targets of interest. Although the target resolution was limited by preferred orientation effects, small scaffold size, and the low-order symmetry of these dihedral scaffolds, we found that the dual anchoring strategy reduced the flexibility of the target-DARPIN complex with respect to the overall assembly, suggesting that multipoint anchoring of binding domains could contribute to cryo-EM structure determination of small proteins

On Chemical Reaction Network Design by a Nested Evolution Algorithm

International audienceOne goal of synthetic biology is to implement useful functions with biochemical reactions, either by reprogramming living cells or programming artificial vesicles. In this perspective, we consider Chemical Reaction Networks (CRN) as a programming language, and investigate the CRN program synthesis problem. Recent work has shown that CRN interpreted by differential equations are Turing-complete and can be seen as analog computers where the molecular concentrations play the role of information carriers. Any real function that is computable by a Turing machine in arbitrary precision can thus be computed by a CRN over a finite set of molecular species. The proof of this result gives a numerical method to generate a finite CRN for implementing a real function presented as the solution of a Polynomial Initial Values Problem (PIVP). In this paper, we study an alternative method based on artificial evolution to build a CRN that approximates a real function given on finite sets of input values. We present a nested search algorithm that evolves the structure of the CRN and optimizes the kinetic parameters at each generation. We evaluate this algorithm on the Heaviside and Cosine functions both as functions of time and functions of input molecular species. We then compare the CRN obtained by artificial evolution both to the CRN generated by the numerical method from a PIVP definition of the function, and to the natural CRN found in the BioModels repository for switches and oscillators

Ingéniérie de biosenseurs autonomes et programmables via une approche de biologie synthétique : détection multiplexée de biomarqueurs et traitement de signal biomoléculaire intégrés dans des outils diagnostiques de nouvelle génération

The promise for real precision medicine is contingent on innovative technological solutions to diagnosis. In the postgenomicera, synthetic biology approaches to medicine provide new ways to probe, monitor and interface humanpathophysiology. Emerging as a mature field increasingly transitioning to the clinics, synthetic biology can be used toapply engineering principles to design and build biological systems with clinical specifications. A particularlytantalizing application is to develop versatile, programmable and intelligent diagnostic devices closely interconnectedwith therapy. This thesis presents novel engineering concepts and approaches to design synthetic biological devicesinterfacing human diseases in clinical samples through biomolecular digital signal processing, in light of a need fordramatic improvements in capabilities and robustness. It addresses primarily the engineering of synthetic genecircuits through integrase based digital genetic amplifiers and logic gates, to integrate modular and programmablebiosensing of biomarkers and diagnostic decision algorithms into bacteria. It then investigates systematic bottom-upmethodologies to program microscale synthetic protocells performing medical biosensing and biocomputingoperations. We demonstrate streamlined microfluidic fabrication methods and solutions to implement complexBoolean operation using integrated synthetic biochemical circuits. This contribution also extends to thecharacterization of protocell design space through novel computer assisted design frameworks, as well as the analysisof mathematical and biological evidence for universal protocellular biocomputing devices. The articulation ofbiological governing principles and medical implications for the synthetic devices developed in this work was furthervalidated in the clinic, and initiates new models towards next-generation diagnostics. This work envisions thatsynthetic biology is preparing the future of medicine, supporting and speeding up the development of diagnosticswith novel capabilities to bring direct improvement in biotechnologies from the clinical lab to the patient.Les promesses de la médecine de précision dépendent de nouvelles solutions technologiques pour le diagnostic.Dans l’ère post-génomique, les approches de biologie synthétique pour la médecine apportent de nouvelles façons desonder, monitorer et interfacer la physiopathologie humaine. Emergeant en tant que champ scientifique mature dontla transition clinique s’accélère, la biologie synthétique peut être utilisée pour appliquer des principes d’ingénierie afinde concevoir et construire des systèmes biologiques comprenant des spécifications cliniques. Une applicationparticulièrement intéressante est de développer des outils diagnostiques polyvalents, programmables et intelligentsétroitement interconnectés avec la thérapie. Cette thèse présente de nouveaux concepts et approches d’ingénieriepour concevoir des dispositifs biosynthétiques capables d’interfacer les maladies humaines dans des échantillonscliniques en exploitant du traitement de signal au niveau biomoléculaire, à la lumière d’un besoin croissant en termesde capacités et de robustesse. Cette thèse s’intéresse en premier lieu à l’ingénierie de circuits synthétiques de gènes,reposant sur les portes logiques à integrases, pour intégrer des opérations modulaires et programmables debiodétection de biomarqueur associées à des algorithmes de décisions au sein de population de bactéries. Elles’intéresse ensuite à des méthodologies systématiques dites bottom-up, pour programmer des protocellulessynthétiques microscopiques, capables d’exécuter des opérations de biodétection médicale et de biocomputation.Nous décrivons le développement de méthodes simples de fabrications microfluidiques associées à des solutionspour implémenter des opérations booléennes complexes en utilisant des circuits biochimiques synthétiques. Cettecontribution s’élargit aussi à la caractérisation de l’espace de conception de protocellules à l’aide d’approches dedesign assisté par ordinateur, ainsi qu’à l’analyse de preuves mathématiques et biologiques pour l’utilisation deprotocellules comme des dispositifs universels de calcul. L’articulation des principes biologiques fondamentaux avecles implications médicales concernant les dispositifs biosynthétiques développés dans ce travail, a été jusqu’à lavalidation clinique et initie de nouveaux modèles pour le developpement de diagnostics de nouvelle génération. Cetravail prévoit que la biologie synthétique est en train de préparer le futur de la médecine, en supportant et accélérantle développement de diagnostics avec de nouvelles capacités, apportant un progrès biotechnologique direct depuis lelaboratoire de biologie clinique jusqu’au patient

Bringing next‐generation diagnostics to the clinic through synthetic biology

International audienceThe promise for real precision medicine is contingent on innovative technological solutions to diagnosis and therapy. In the post-genomic era, rational and systematic approaches to biological design could provide new ways to dynamically probe, monitor, and interface human pathophysiology. Emerging as a mature field increasingly transitioning to the clinics, synthetic biology integrates engineering principles to build sensors, control circuits, and actuators within the biological substrate according to clinical specifications. A particularly tantalizing goal is to develop novel versatile, programmable and autonomous diagnostic devices intertwined with therapy and personalized for the patient to get closest, finest, and most comprehensive diagnostic information and medical procedures. Here, we discuss how synthetic biology could be preparing the future of medicine, supporting and speeding up the development of diagnostics with novel capabilities to bring direct improvement from the clinical laboratory to the patient, while addressing healthcare evolution and global health concern

Computing with Synthetic Protocells

International audienceIn this article we present a new kind of computing device that uses biochemical reactions networks as building blocks to implement logic gates. The architecture of a computing machine relies on these generic and composable building blocks, computation units, that can be used in multiple instances to perform complex boolean functions. Standard logical operations are implemented by biochemical networks, encapsulated and insulated within synthetic vesicles called protocells. These protocells are capable of exchanging energy and information with each other through transmembrane electron transfer.In the paradigm of computation we propose, protoputing, a machine can solve only one problem and therefore has to be built specifically. Thus, the programming phase in the standard computing paradigm is represented in our approach by the set of assembly instructions (specific attachments) that directs the wiring of the protocells that constitute the machine itself. To demonstrate the computing power of protocellular machines, we apply it to solve a NP-complete problem, known to be very demanding in computing power, the 3-SAT problem. We show how to program the assembly of a machine that can verify the satisfiability of a given boolean formula. Then we show how to use the massive parallelism of these machines to verify in less than twenty minutes all the valuations of the input variables and output a fluorescent signal when the formula is satisfiable or no signal at all otherwise

Computer‐aided biochemical programming of synthetic microreactors as diagnostic devices

International audienceBiological systems have evolved efficient sensing and decision-making mechanisms to maximize fitness in changing molecular environments. Synthetic biologists have exploited these capabilities to engineer control on information and energy processing in living cells. While engineered organisms pose important technological and ethical challenges, de novo assembly of non-living biomolecular devices could offer promising avenues toward various real-world applications. However, assembling biochemical parts into functional information processing systems has remained challenging due to extensive multidimensional parameter spaces that must be sampled comprehensively in order to identify robust, specification compliant molecular implementations. We introduce a systematic methodology based on automated computational design and microfluidics enabling the programming of synthetic cell-like microreactors embedding biochemical logic circuits, or protosensors, to perform accurate biosensing and biocomputing operations in vitro according to temporal logic specifications. We show that proof-of-concept protosensors integrating diagnostic algorithms detect specific patterns of biomarkers in human clinical samples. Protosensors may enable novel approaches to medicine and represent a step toward autonomous micromachines capable of precise interfacing of human physiology or other complex biological environments, ecosystems, or industrial bioprocesses

Imidazoquinoxaline anticancer derivatives and imiquimod interact with tubulin: Characterization of molecular microtubule inhibiting mechanisms in correlation with cytotoxicity

International audienceDisplaying a strong antiproliferative activity on a wide variety of cancer cells, EAPB0203 and EAPB0503 belong to the imidazo[1,2-a]quinoxalines family of imiquimod structural analogues. EAPB0503 has been shown to inhibit tubulin polymerization. The aim of the present study is to characterize the interaction of EAPB0203 and EAPB0503 with tubulin. We combine experimental approaches at the cellular and the molecular level both in vitro and in silico in order to evaluate the interaction of EAPB0203 and EAPB0503 with tubulin. We examine the influence of EAPB0203 and EAPB0503 on the cell cycle and fate, explore the binding interaction with purified tubulin, and use a computational molecular docking model to determine the binding modes to the microtubule. We then use a drug combination study with other anti-microtubule agents to compare the binding site of EAPB0203 and EAPB0503 to known potent tubulin inhibitors. We demonstrate that EAPB0203 and EAPB0503 are capable of blocking human melanoma cells in G2 and M phases and inducing cell death and apoptosis. Second, we show that EAPB0203 and EAPB0503, but also unexpectedly imiquimod, bind directly to purified tubulin and inhibit tubulin polymerization. As suggested by molecular docking and binding competition studies, we identify the colchicine binding site on β-tubulin as the interaction pocket. Furthermore, we find that EAPB0203, EAPB0503 and imiquimod display antagonistic cytotoxic effect when combined with colchicine, and disrupt tubulin network in human melanoma cells. We conclude that EAPB0203, EAPB0503, as well as imiquimod, interact with tubulin through the colchicine binding site, and that the cytotoxic activity of EAPB0203, EAPB0503 and imiquimod is correlated to their tubulin inhibiting effect. These compounds appear as interesting anticancer drug candidates as suggested by their activity and mechanism of action, and deserve further investigation for their use in the clinic