Assessing the effect of dynamics on the closed-loop protein-folding hypothesis

The closed-loop (loop-n-lock) hypothesis of protein folding suggests that loops of about 25 residues, closed through interactions between the loop ends (locks), play an important role in protein structure. Coarse-grain elastic network simulations, and examination of loop lengths in a diverse set of proteins, each supports a bias towards loops of close to 25 residues in length between residues of high stability. Previous studies have established a correlation between total contact distance (TCD), a metric of sequence distances between contacting residues (cf. contact order), and the log-folding rate of a protein. In a set of 43 proteins, we identify an improved correlation ( r 2 = 0.76), when the metric is restricted to residues contacting the locks, compared to the equivalent result when all residues are considered ( r 2 = 0.65). This provides qualified support for the hypothesis, albeit with an increased emphasis upon the importance of a much larger set of residues surrounding the locks. Evidence of a similar-sized protein core/extended nucleus (with significant overlap) was obtained from TCD calculations in which residues were successively eliminated according to their hydrophobicity and connectivity, and from molecular dynamics simulations. Our results suggest that while folding is determined by a subset of residues that can be predicted by application of the closed-loop hypothesis, the original hypothesis is too simplistic; efficient protein folding is dependent on a considerably larger subset of residues than those involved in lock formation. </jats:p

Predictability of evolutionary trajectories in fitness landscapes

Experimental studies on enzyme evolution show that only a small fraction of all possible mutation trajectories are accessible to evolution. However, these experiments deal with individual enzymes and explore a tiny part of the fitness landscape. We report an exhaustive analysis of fitness landscapes constructed with an off-lattice model of protein folding where fitness is equated with robustness to misfolding. This model mimics the essential features of the interactions between amino acids, is consistent with the key paradigms of protein folding and reproduces the universal distribution of evolutionary rates among orthologous proteins. We introduce mean path divergence as a quantitative measure of the degree to which the starting and ending points determine the path of evolution in fitness landscapes. Global measures of landscape roughness are good predictors of path divergence in all studied landscapes: the mean path divergence is greater in smooth landscapes than in rough ones. The model-derived and experimental landscapes are significantly smoother than random landscapes and resemble additive landscapes perturbed with moderate amounts of noise; thus, these landscapes are substantially robust to mutation. The model landscapes show a deficit of suboptimal peaks even compared with noisy additive landscapes with similar overall roughness. We suggest that smoothness and the substantial deficit of peaks in the fitness landscapes of protein evolution are fundamental consequences of the physics of protein folding.Comment: 14 pages, 7 figure

Designing libraries of chimeric proteins using SCHEMA recombination and RASPP

SCHEMA is a method for designing libraries of novel proteins by recombination of homologous sequences. The goal is to maximize the number of folded proteins while simultaneously generating significant sequence diversity. Here, we use the RASPP algorithm to identify optimal SCHEMA designs for shuffling contiguous elements of sequence. To exemplify the method, SCHEMA is used to recombine five fungal cellobiohydrolases (CBH1s) to produce a library of more than 390,000 novel CBH1 sequences

Design principles for riboswitch function

Scientific and technological advances that enable the tuning of integrated regulatory components to match network and system requirements are critical to reliably control the function of biological systems. RNA provides a promising building block for the construction of tunable regulatory components based on its rich regulatory capacity and our current understanding of the sequence–function relationship. One prominent example of RNA-based regulatory components is riboswitches, genetic elements that mediate ligand control of gene expression through diverse regulatory mechanisms. While characterization of natural and synthetic riboswitches has revealed that riboswitch function can be modulated through sequence alteration, no quantitative frameworks exist to investigate or guide riboswitch tuning. Here, we combined mathematical modeling and experimental approaches to investigate the relationship between riboswitch function and performance. Model results demonstrated that the competition between reversible and irreversible rate constants dictates performance for different regulatory mechanisms. We also found that practical system restrictions, such as an upper limit on ligand concentration, can significantly alter the requirements for riboswitch performance, necessitating alternative tuning strategies. Previous experimental data for natural and synthetic riboswitches as well as experiments conducted in this work support model predictions. From our results, we developed a set of general design principles for synthetic riboswitches. Our results also provide a foundation from which to investigate how natural riboswitches are tuned to meet systems-level regulatory demands

Ribozyme-based insulator parts buffer synthetic circuits from genetic context

Synthetic genetic programs are built from circuits that integrate sensors and implement temporal control of gene expression. Transcriptional circuits are layered by using promoters to carry the signal between circuits. In other words, the output promoter of one circuit serves as the input promoter to the next. Thus, connecting circuits requires physically connecting a promoter to the next circuit. We show that the sequence at the junction between the input promoter and circuit can affect the input-output response (transfer function) of the circuit. A library of putative sequences that might reduce (or buffer) such context effects, which we refer to as 'insulator parts', is screened in Escherichia coli. We find that ribozymes that cleave the 5′ untranslated region (5′-UTR) of the mRNA are effective insulators. They generate quantitatively identical transfer functions, irrespective of the identity of the input promoter. When these insulators are used to join synthetic gene circuits, the behavior of layered circuits can be predicted using a mathematical model. The inclusion of insulators will be critical in reliably permuting circuits to build different programs.Life Technologies, Inc.United States. Defense Advanced Research Projects Agency (DARPA CLIO N66001-12-C-4018)United States. Office of Naval Research (N00014-10-1-0245)National Science Foundation (U.S.) (CCF-0943385)National Institutes of Health (U.S.) (AI067699)National Science Foundation (U.S.). Synthetic Biology Engineering Research Center (SynBERC, SA5284-11210

Glucanocellulosic ethanol: The undiscovered biofuel potential in energy crops and marine biomass

Converting biomass to biofuels is a key strategy in substituting fossil fuels to mitigate climate change. Conventional strategies to convert lignocellulosic biomass to ethanol address the fermentation of cellulose-derived glucose. Here we used super-resolution fluorescence microscopy to uncover the nanoscale structure of cell walls in the energy crops maize and Miscanthus where the typical polymer cellulose forms an unconventional layered architecture with the atypical (1, 3)-β-glucan polymer callose. This raised the question about an unused potential of (1, 3)-β-glucan in the fermentation of lignocellulosic biomass. Engineering biomass conversion for optimized (1, 3)-β-glucan utilization, we increased the ethanol yield from both energy crops. The generation of transgenic Miscanthus lines with an elevated (1, 3)-β-glucan content further increased ethanol yield providing a new strategy in energy crop breeding. Applying the (1, 3)-β-glucan-optimized conversion method on marine biomass from brown macroalgae with a naturally high (1, 3)-β-glucan content, we not only substantially increased ethanol yield but also demonstrated an effective co-fermentation of plant and marine biomass. This opens new perspectives in combining different kinds of feedstock for sustainable and efficient biofuel production, especially in coastal regions

Dual requirement of cytokine and activation receptor triggering for cytotoxic control of murine cytomegalovirus by NK cells

Natural killer (NK) cells play a critical role in controlling murine cytomegalovirus (MCMV) and can mediate both cytokine production and direct cytotoxicity. The NK cell activation receptor, Ly49H, is responsible for genetic resistance to MCMV in C57BL/6 mice. Recognition of the viral m157 protein by Ly49H is sufficient for effective control of MCMV infection. Additionally, during the host response to infection, distinct immune and non-immune cells elaborate a variety of pleiotropic cytokines which have the potential to impact viral pathogenesis, NK cells, and other immune functions, both directly and indirectly. While the effects of various immune deficiencies have been examined for general antiviral phenotypes, their direct effects on Ly49H-dependent MCMV control are poorly understood. To specifically interrogate Ly49H-dependent functions, herein we employed an in vivo viral competition approach to show Ly49H-dependent MCMV control is specifically mediated through cytotoxicity but not IFNγ production. Whereas m157 induced Ly49H-dependent degranulation, efficient cytotoxicity also required either IL-12 or type I interferon (IFN-I) which acted directly on NK cells to produce granzyme B. These studies demonstrate that both of these distinct NK cell-intrinsic mechanisms are integrated for optimal viral control by NK cells

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

Relative effects of sensory modalities and importance of fatty acid sensitivity on fat perception in a real food model

Fat can be perceived through mouthfeel, odour and taste, but the influence of these modalities on fat perception remains undefined. Fatty acids are stimuli. Individual’s sensitivity to fatty acids varies. Studies show association between fatty acid sensitivity, dietary intake and BMI, but results are conflicting. Therefore, this study examined this association, and the effects of modalities on fat perception. Two sub-studies conducted. In Study 1 (n=46), fat intensity was assessed by milk/cream mixtures varying by five fat levels. Fat intensity was rated under four conditions: mouthfeel-odour masked, mouthfeel masked, odour masking and no masking. Mouthfeel masking was achieved using thickener and paraffin, odour masking using nose-clips. Fatty acid sensitivity was measured by 3-AFC-staircase method using milk containing oleic acid (0.31-31.4mM). In Study 2 (n=51), more fat levels were added in fat intensity rating. A 2-AFC discrimination test was used to confirm whether fat levels could be distinguished. In the sensitivity test, a wider range of oleic acid was included. Fat intensity was rated higher without nose-clips (p<0.0001), implying that odour increased fat perception. Samples with mouthfeel-masked were rated higher, showing that increased viscosity and lubricity enhanced fat perception (p<0.0001). Participants could distinguish fat levels based on “taste” in rating tests and 2-AFC-tests. Participants were divided into high/medium/low-sensitivity groups. No significant difference found in fat intensity between groups, however, high-sensitivity group discriminated more fat levels. No association between sensitivity groups, nutrient intake or BMI found

Synthetic biology to access and expand nature's chemical diversity

Bacterial genomes encode the biosynthetic potential to produce hundreds of thousands of complex molecules with diverse applications, from medicine to agriculture and materials. Accessing these natural products promises to reinvigorate drug discovery pipelines and provide novel routes to synthesize complex chemicals. The pathways leading to the production of these molecules often comprise dozens of genes spanning large areas of the genome and are controlled by complex regulatory networks with some of the most interesting molecules being produced by non-model organisms. In this Review, we discuss how advances in synthetic biology — including novel DNA construction technologies, the use of genetic parts for the precise control of expression and for synthetic regulatory circuits — and multiplexed genome engineering can be used to optimize the design and synthesis of pathways that produce natural products