Gateway vectors for efficient artificial gene assembly in vitro and expression in yeast Saccharomyces cerevisiae

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Ask yeast how to burn your fats: lessons learned from the metabolic adaptation to salt stress

[EN] Here, we review and update the recent advances in the metabolic control during the adaptive response of budding yeast to hyperosmotic and salt stress, which is one of the best understood signaling events at the molecular level. This environmental stress can be easily applied and hence has been exploited in the past to generate an impressively detailed and comprehensive model of cellular adaptation. It is clear now that this stress modulates a great number of different physiological functions of the cell, which altogether contribute to cellular survival and adaptation. Primary defense mechanisms are the massive induction of stress tolerance genes in the nucleus, the activation of cation transport at the plasma membrane, or the production and intracellular accumulation of osmolytes. At the same time and in a coordinated manner, the cell shuts down the expression of housekeeping genes, delays the progression of the cell cycle, inhibits genomic replication, and modulates translation efficiency to optimize the response and to avoid cellular damage. To this fascinating interplay of cellular functions directly regulated by the stress, we have to add yet another layer of control, which is physiologically relevant for stress tolerance. Salt stress induces an immediate metabolic readjustment, which includes the up-regulation of peroxisomal biomass and activity in a coordinated manner with the reinforcement of mitochondrial respiratory metabolism. Our recent findings are consistent with a model, where salt stress triggers a metabolic shift from fermentation to respiration fueled by the enhanced peroxisomal oxidation of fatty acids. We discuss here the regulatory details of this stress-induced metabolic shift and its possible roles in the context of the previously known adaptive functions.The work of the authors was supported by grants from Ministerio de Economía y Competitividad (BFU2011- 23326 and BFU2016-75792-R).Pascual-Ahuir Giner, MD.; Manzanares-Estreder, S.; Timón Gómez, A.; Proft ., MH. (2017). Ask yeast how to burn your fats: lessons learned from the metabolic adaptation to salt stress. Current Genetics. 64(1):63-69. https://doi.org/10.1007/s00294-017-0724-5S6369641Aguilera J, Prieto JA (2001) The Saccharomyces cerevisiae aldose reductase is implied in the metabolism of methylglyoxal in response to stress conditions. Curr Genet 39:273–283Albertyn J, Hohmann S, Thevelein JM, Prior BA (1994) GPD1, which encodes glycerol-3-phosphate dehydrogenase, is essential for growth under osmotic stress in Saccharomyces cerevisiae, and its expression is regulated by the high-osmolarity glycerol response pathway. 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The HOG Pathway Dictates the Short-Term Translational Response after Hyperosmotic Shock

In the global osmoshock translational response in yeast, some gene products were translationally mobilized without transcriptional up-regulation. Conversely, other transcriptionally up-regulated mRNAs were translationally inhibited. Analogous changes occurred on the protein level. These translational responses were strongly dependent on Hog1 and Rck2

Multicellular Computing Using Conjugation for Wiring

Recent efforts in synthetic biology have focussed on the implementation of logical functions within living cells. One aim is to facilitate both internal ‘‘re-programming’’ and external control of cells, with potential applications in a wide range of domains. However, fundamental limitations on the degree to which single cells may be re-engineered have led to a growth of interest in multicellular systems, in which a ‘‘computation’’ is distributed over a number of different cell types, in a manner analogous to modern computer networks. Within this model, individual cell type perform specific sub-tasks, the results of which are then communicated to other cell types for further processing. The manner in which outputs are communicated is therefore of great significance to the overall success of such a scheme. Previous experiments in distributed cellular computation have used global communication schemes, such as quorum sensing (QS), to implement the ‘‘wiring’’ between cell types. While useful, this method lacks specificity, and limits the amount of information that may be transferred at any one time. We propose an alternative scheme, based on specific cell-cell conjugation. This mechanism allows for the direct transfer of genetic information between bacteria, via circular DNA strands known as plasmids. We design a multicellular population that is able to compute, in a distributed fashion, a Boolean XOR function. Through this, we describe a general scheme for distributed logic that works by mixing different strains in a single population; this constitutes an important advantage of our novel approach. Importantly, the amount of genetic information exchanged through conjugation is significantly higher than the amount possible through QS-based communication. We provide full computational modelling and simulation results, using deterministic, stochastic and spatially-explicit methods. These simulations explore the behaviour of one possible conjugation-wired cellular computing system under different conditions, and provide baseline information for future laboratory implementations

Principles of genetic circuit design

Cells navigate environments, communicate and build complex patterns by initiating gene expression in response to specific signals. Engineers seek to harness this capability to program cells to perform tasks or create chemicals and materials that match the complexity seen in nature. This Review describes new tools that aid the construction of genetic circuits. Circuit dynamics can be influenced by the choice of regulators and changed with expression 'tuning knobs'. We collate the failure modes encountered when assembling circuits, quantify their impact on performance and review mitigation efforts. Finally, we discuss the constraints that arise from circuits having to operate within a living cell. Collectively, better tools, well-characterized parts and a comprehensive understanding of how to compose circuits are leading to a breakthrough in the ability to program living cells for advanced applications, from living therapeutics to the atomic manufacturing of functional materials.National Institute of General Medical Sciences (U.S.) (Grant P50 GM098792)National Institute of General Medical Sciences (U.S.) (Grant R01 GM095765)National Science Foundation (U.S.). Synthetic Biology Engineering Research Center (EEC0540879)Life Technologies, Inc. (A114510)National Science Foundation (U.S.). Graduate Research FellowshipUnited States. Office of Naval Research. Multidisciplinary University Research Initiative (Grant 4500000552

Pathways to cellular supremacy in biocomputing

Synthetic biology uses living cells as the substrate for performing human-defined computations. Many current implementations of cellular computing are based on the “genetic circuit” metaphor, an approximation of the operation of silicon-based computers. Although this conceptual mapping has been relatively successful, we argue that it fundamentally limits the types of computation that may be engineered inside the cell, and fails to exploit the rich and diverse functionality available in natural living systems. We propose the notion of “cellular supremacy” to focus attention on domains in which biocomputing might offer superior performance over traditional computers. We consider potential pathways toward cellular supremacy, and suggest application areas in which it may be found.A.G.-M. was supported by the SynBio3D project of the UK Engineering and Physical Sciences Research Council (EP/R019002/1) and the European CSA on biological standardization BIOROBOOST (EU grant number 820699). T.E.G. was supported by a Royal Society University Research Fellowship (grant UF160357) and BrisSynBio, a BBSRC/ EPSRC Synthetic Biology Research Centre (grant BB/L01386X/1). P.Z. was supported by the EPSRC Portabolomics project (grant EP/N031962/1). P.C. was supported by SynBioChem, a BBSRC/EPSRC Centre for Synthetic Biology of Fine and Specialty Chemicals (grant BB/M017702/1) and the ShikiFactory100 project of the European Union’s Horizon 2020 research and innovation programme under grant agreement 814408

GUBS a language for synthetic biology: Specification and compilation

International audienceThe field of synthetic biology is looking forward principles and tools to make the biological devices inter-operable and programmable with, as long-term goal, the design of de-novo synthetic genome [14]. In this endeavour, computer-aided-design (CAD) environments play a central role by providing the required features to engineer systems: specification, analysis, and tuning [9,17,20,12]. Scaling up the complexity of devices necessitates to harness the development of CAD environments based on an automatic conversion of the design specification into DNA sequences, like compilers for programming languages. Currently, domain specific languages for synthetic biology mainly address the design of structure, namely the biological component assembly, where programming relates to DNA sequence description. Although the structural description is an indispensable step in the design-to-manufacture chain and provide an accurate description of devices, the required size of program for sequence description likely makes the task error-prone and infeasible. In this context, high level programming language for synthetic biology is announced as a key milestone for the second wave of synthetic biology to overcome the complexity of such large synthetic system design. We have proposed a domain specific language, Gubs [5] (Genomic Unified Behaviour Specification), dedicated to the behavioural specification of synthetic biological devices, viewed as discrete open dynamical systems. Gubs is a rule-based declarative language. In contrast to a closed system, a program is always a partial description of the behaviour of the system. The semantics of the language accounts the existence of some hidden non-specified actions (trigged by the environment for example) that possibly alter the behaviour of the programmed devices. Here we describe in detail the compilation framework,Ggc(Gubs Genetic Compiler), an automated compiler translating a program into biological components usable in living cells. The compilation process assemble biological components from a database to behaviourally cover the behaviour described by a program