30 research outputs found

    Engineering microbial consortia to enhance biomining and bioremediation

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    In natural environments microorganisms commonly exist as communities of multiple species that are capable of performing more varied and complicated tasks than clonal populations. Synthetic biologists have engineered clonal populations with characteristics such as differentiation, memory, and pattern formation, which are usually associated with more complex multicellular organisms. The prospect of designing microbial communities has alluring possibilities for environmental, biomedical, and energy applications, and is likely to reveal insight into how natural microbial consortia function. Cell signaling and communication pathways between different species are likely to be key processes for designing novel functions in synthetic and natural consortia. Recent efforts to engineer synthetic microbial interactions will be reviewed here, with particular emphasis given to research with significance for industrial applications in the field of biomining and bioremediation of acid mine drainage

    Model-guided design of ligand-regulated RNAi for programmable control of gene expression

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    Progress in constructing biological networks will rely on the development of more advanced components that can be predictably modified to yield optimal system performance. We have engineered an RNA-based platform, which we call an shRNA switch, that provides for integrated ligand control of RNA interference (RNAi) by modular coupling of an aptamer, competing strand, and small hairpin (sh) RNA stem into a single component that links ligand concentration and target gene expression levels. A combined experimental and mathematical modelling approach identified multiple tuning strategies and moves towards a predictable framework for the forward design of shRNA switches. The utility of our platform is highlighted by the demonstration of fine-tuning, multi-input control, and model-guided design of shRNA switches with an optimized dynamic range. Thus, shRNA switches can serve as an advanced component for the construction of complex biological systems and offer a controlled means of activating RNAi in disease therapeutics

    Engineering stochasticity in gene expression

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    Stochastic fluctuations (noise) in gene expression can cause members of otherwise genetically identical populations to display drastically different phenotypes. An understanding of the sources of noise and the strategies cells employ to function reliably despite noise is proving to be increasingly important in describing the behavior of natural organisms and will be essential for the engineering of synthetic biological systems. Here we describe the design of synthetic constructs, termed ribosome competing RNAs (rcRNAs), as a means to rationally perturb noise in cellular gene expression. We find that noise in gene expression increases in a manner proportional to the ability of an rcRNA to compete for the cellular ribosome pool. We then demonstrate that operons significantly buffer noise between coexpressed genes in a natural cellular background and can even reduce the level of rcRNA enhanced noise. These results demonstrate that synthetic genetic constructs can significantly affect the noise profile of a living cell and, importantly, that operons are a facile genetic strategy for buffering against noise

    Synthetic control of a fitness tradeoff in yeast nitrogen metabolism

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    Background: Microbial communities are involved in many processes relevant to industrial and medical biotechnology, such as the formation of biofilms, lignocellulosic degradation, and hydrogen production. The manipulation of synthetic and natural microbial communities and their underlying ecological parameters, such as fitness, evolvability, and variation, is an increasingly important area of research for synthetic biology. Results: Here, we explored how synthetic control of an endogenous circuit can be used to regulate a tradeoff between fitness in resource abundant and resource limited environments in a population of Saccharomyces cerevisiae. We found that noise in the expression of a key enzyme in ammonia assimilation, Gdh1p, mediated a tradeoff between growth in low nitrogen environments and stress resistance in high ammonia environments. We implemented synthetic control of an endogenous Gdh1p regulatory network to construct an engineered strain in which the fitness of the population was tunable in response to an exogenously-added small molecule across a range of ammonia environments. Conclusion: The ability to tune fitness and biological tradeoffs will be important components of future efforts to engineer microbial communities

    Cytoskeletal Signaling: Is Memory Encoded in Microtubule Lattices by CaMKII Phosphorylation?

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    Memory is attributed to strengthened synaptic connections among particular brain neurons, yet synaptic membrane components are transient, whereas memories can endure. This suggests synaptic information is encoded and ‘hard-wired’ elsewhere, e.g. at molecular levels within the post-synaptic neuron. In long-term potentiation (LTP), a cellular and molecular model for memory, post-synaptic calcium ion (Ca2+) flux activates the hexagonal Ca2+-calmodulin dependent kinase II (CaMKII), a dodacameric holoenzyme containing 2 hexagonal sets of 6 kinase domains. Each kinase domain can either phosphorylate substrate proteins, or not (i.e. encoding one bit). Thus each set of extended CaMKII kinases can potentially encode synaptic Ca2+ information via phosphorylation as ordered arrays of binary ‘bits’. Candidate sites for CaMKII phosphorylation-encoded molecular memory include microtubules (MTs), cylindrical organelles whose surfaces represent a regular lattice with a pattern of hexagonal polymers of the protein tubulin. Using molecular mechanics modeling and electrostatic profiling, we find that spatial dimensions and geometry of the extended CaMKII kinase domains precisely match those of MT hexagonal lattices. This suggests sets of six CaMKII kinase domains phosphorylate hexagonal MT lattice neighborhoods collectively, e.g. conveying synaptic information as ordered arrays of six “bits”, and thus “bytes”, with 64 to 5,281 possible bit states per CaMKII-MT byte. Signaling and encoding in MTs and other cytoskeletal structures offer rapid, robust solid-state information processing which may reflect a general code for MT-based memory and information processing within neurons and other eukaryotic cells

    Programmable ligand-controlled riboregulators of eukaryotic gene expression

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    Recent studies have demonstrated the importance of noncoding RNA elements in regulating gene expression networks. We describe the design of a class of small trans-acting RNAs that directly regulate gene expression in a ligand-dependent manner. These allosteric riboregulators, which we call antiswitches, are made fully tunable and modular by rational design. They offer flexible control strategies by adopting active or inactive forms in response to ligand binding, depending on their design. They can be tailor-made to regulate the expression of target transcripts in response to different cellular effectors. Coupled with in vitro selection technologies for generating nucleic acid ligand-binding species, antiswitches present a platform for programming cellular behavior and genetic networks with respect to cellular state and environmental stimuli

    Arginine-rich motifs present multiple interfaces for specific binding by RNA

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    A number of proteins containing arginine-rich motifs (ARMs) are known to bind RNA and are involved in regulating RNA processing in viruses and cells. Using automated selection methods we have generated a number of aptamers against ARM peptides from various natural proteins. Aptamers bind tightly to their cognate ARMs, with K(d) values in the nanomolar range, and frequently show no propensity to bind to other ARMs or even to single amino acid variants of the cognate ARM. However, at least some anti-ARM aptamers can cross-recognize a limited set of other ARMs, just as natural RNA-binding sites have been shown to exhibit so-called “chameleonism.” We expand upon the number of examples of cross-recognition and, using mutational and circular dichroism (CD) analyses, demonstrate that there are multiple mechanisms by which RNA ligands can cross-recognize ARMs. These studies support a model in which individual arginine residues govern binding to an RNA ligand, and the inherent flexibility of the peptide backbone may make it possible for “semi-specific” recognition of a discrete set of RNAs by a discrete set of ARM peptides and proteins

    Automated selection of aptamers against protein targets translated in vitro: from gene to aptamer

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    Reagents for proteome research must of necessity be generated by high throughput methods. Apta mers are potentially useful as reagents to identify and quantitate individual proteins, yet are currently produced for the most part by manual selection procedures. We have developed automated selection methods, but must still individually purify protein targets. Therefore, we have attempted to select aptamers against protein targets generated by in vitro transcription and translation of individual genes. In order to specifically immobilize the protein targets for selection, they are also biotinylated in vitro. As a proof of this method, we have selected aptamers against translated human U1A, a component of the nuclear spliceosome. Selected sequences demonstrated exquisite mimicry of natural binding sequences and structures. These results not only reveal a potential path to the high throughput generation of aptamers, but also yield insights into the incredible specificity of the U1A protein for its natural RNA ligands
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