Biology subjects

Bonnet, J.

Publications and source records attributed to Bonnet, J..

25 records · Page 2Linked to original sources

bioRxiv2020

Structural basis for decoding active histone methylation marks by Polycomb Repressive Complex 2

Repression of genes by Polycomb requires that PRC2 modifies their chromatin by trimethylating lysine 27 on histone H3 (H3K27me3). At transcriptionally active genes, di- and trimethylated H3K36 inhibit PRC2. Here, the cryo-EM structure of PRC2 on dinucleosomes reveals how binding of its catalytic subunit EZH2 to nucleosomal DNA orients the H3 N-terminus via an extended network of interactions to place H3K27 into the active site. Unmodified H3K36 occupies a critical position in the EZH2-DNA interface. Mutation of H3K36 to arginine or alanine inhibits H3K27 methylation by PRC2 on nucleosomes in vitro. Accordingly, Drosophila H3K36A and H3K36R mutants show reduced levels of H3K27me3 and defective Polycomb repression of HOX genes. The relay of interactions between EZH2, the nucleosomal DNA and the H3 N-terminus therefore creates the geometry that permits allosteric inhibition of PRC2 by methylated H3K36 in transcriptionally active chromatin.

biochemistry↗

bioRxiv2019

Exploring the design space of recombinase logic circuits.

Logic circuits operating in living cells are generally built by mimicking electronic layouts, and scale-up is accomplished using additional layers of elementary logic gates like NOT and NOR gates. Recombinase-based logic, in which logic is implemented using DNA inversion or excision, allows for highly efficient, compact and single-layer design architectures. However, recombinase logic architectures depart from electronic design principles, and gate design performed empirically is challenging for an increasing number of inputs. Here we used a combinatorial approach to explore the design space of recombinase logic devices. We generated combinations and permutations of recombination sites, genes, and regulatory elements, for a total of ~19 million designs supporting the implementation of all 2- and 3-input logic functions and up to 92% of 4-input logic functions. We estimated the influence of different design constraints on the number of executable functions, and found that the use of DNA inversion and transcriptional terminators were key factors to implement the vast majority of logic functions. We provide a user-friendly interface, called RECOMBINATOR (http://recombinator.lirmm.fr/index.php), that enable users to navigate the design space of recombinase-based logic, find architectures implementing a specific logic function and sort them according to various biological criteria. Finally, we define a set of 16 architectures from which all 256 3-input logic functions can be derived. This work provides a theoretical foundation for the systematic exploration and design of single-layer recombinase logic devices.\n\n\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=55 SRC=\"FIGDIR/small/711374v2_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (14K):\norg.highwire.dtl.DTLVardef@799feborg.highwire.dtl.DTLVardef@f22dc2org.highwire.dtl.DTLVardef@19a1d10org.highwire.dtl.DTLVardef@ea3b9a_HPS_FORMAT_FIGEXP M_FIG C_FIG

synthetic biology↗

bioRxiv2019

Rational programming of history-dependent logic in cellular populations.

Genetic programs operating in an history-dependent fashion are ubiquitous in nature and govern sophisticated processes such as development and differentiation. The ability to systematically and predictably encode such programs would advance the engineering of synthetic organisms and ecosystems with rich signal processing abilities. Here we implement robust, scalable history-dependent programs by distributing the computational labor across a cellular population. Our design is based on recombinase-driven DNA scaffolds expressing different genes according to the order of occurrence of inputs. These multicellular computing systems are highly modular and any program can be built by differential composition of strains containing well-characterized logic scaffolds. We developed an automated workflow that researchers can use to streamline program design and optimization. We anticipate that the history-dependent programs presented here will support many applications using cellular populations for material engineering, biomanufacturing and healthcare.\n\nOne Sentence SummarySystematic and automated frameworks for implementing robust history-dependent genetic programs in cellular populations.

synthetic biology↗

bioRxiv2019

Metabolic Perceptrons for Neural Computing in Biological Systems

AbstractSynthetic biological circuits are promising tools for developing sophisticated systems for medical, industrial, and environmental applications. So far, circuit implementations commonly rely on gene expression regulation for information processing using digital logic. Here, we present a new approach for biological computation through metabolic circuits designed by computer-aided tools, implemented in both whole-cell and cell-free systems. We first combine metabolic transducers to build an analog adder, a device that sums up the concentrations of multiple input metabolites. Next, we build a weighted adder where the contributions of the different metabolites to the sum can be adjusted. Using a computational model trained on experimental data, we finally implement two four-input \"perceptrons\" for desired binary classification of metabolite combinations by applying model-predicted weights to the metabolic perceptron. The perceptron-mediated neural computing introduced here lays the groundwork for more advanced metabolic circuits for rapid and scalable multiplex sensing.

synthetic biology↗

bioRxiv2018

Plug-and-Play Metabolic Transducers Expand the Chemical Detection Space of Cell-Free Biosensors

Cell-free transcription-translation systems have great potential for biosensing, yet the range of detectable chemicals is limited. Here we provide a framework to expand the range of molecules detectable by cell-free biosensors by combining synthetic metabolic cascades with transcription factor-based networks. These hybrid cell-free biosensors are highly-sensitive and have a fast response and high-dynamic range. This work provides a foundation to engineer modular cell-free biosensors tailored for many applications.

synthetic biology↗

bioRxiv2018

Hierarchical composition of reliable recombinase logic devices.

We provide a systematic framework for engineering reliable recombinase logic devices by hierarchical composition of well-characterized, optimized recombinase switches. We apply this framework to build a recombinase logic device family supporting up to 4-input Boolean logic. This work will support the predictable engineering of several classes of recombinase devices to reliably control cellular behavior.

synthetic biology↗

bioRxiv2017

Scalable composition frameworks for multicellular logic

A major goal of synthetic biology is to reprogram living organisms to solve pressing challenges in manufacturing, environmental remediation, or healthcare. While many types of genetic logic gates have been engineered, their scalability remains limited. Previous work demonstrated that Distributed Multicellular Computation (DMC) enables the implementation of complex logic within cellular consortia. However, current DMC systems require spatial separation of cellular subpopulation to be scalable to N-inputs, and need cell-cell communication channels to operate. Here we present scalable composition frameworks for the systematic design of multicellular consortia performing recombinase-based Boolean or history-dependent logic, and integrating an arbitrary number of inputs. The theoretical designs for both Boolean and history-dependent logic are based on reduced sets of computational modules implemented into specific cellular subpopulations which can then be combined in various manners to implement all logic functions. Our systems mark a departure from previous DMC architectures as they do not require either cell-cell communication nor spatial separation, greatly facilitating their implementation and making them fully autonomous. Due to their scalability and composability, we anticipate that the design strategies presented here will help researchers and engineers to reprogram cellular behavior for various applications in a streamlined manner. We provide an online tool for automated design of DNA architectures allowing the implementation of multicellular N-inputs logic functions at: http://synbio.cbs.cnrs.fr/calin.

synthetic biology↗