A FAIR-compliant parts catalogue for genome engineering and expression control in Saccharomyces cerevisiae.

The synthetic biology toolkit for baker's yeast, Saccharomyces cerevisiae, includes extensive genome engineering toolkits and parts repositories. However, with the increasing complexity of engineering tasks and versatile applications of this model eukaryote, there is a continued interest to expand and diversify the rational engineering capabilities in this chassis by FAIR (findable, accessible, interoperable, and reproducible) compliance. In this study, we designed and characterised 41 synthetic guide RNA sequences to expand the CRISPR-based genome engineering capabilities for easy and efficient replacement of genomically encoded elements. Moreover, we characterize in high temporal resolution 20 native promoters and 18 terminators using fluorescein and LUDOX CL-X as references for GFP expression and OD600 measurements, respectively. Additionally, all data and reported analysis is provided in a publicly accessible jupyter notebook providing a tool for researchers with low-coding skills to further explore the generated data as well as a template for researchers to write their own scripts. We expect the data, parts, and databases associated with this study to support a FAIR-compliant resource for further advancing the engineering of yeasts.

Synthetic biology approaches to actinomycete strain improvement.

Their biochemical versatility and biotechnological importance make actinomycete bacteria attractive targets for ambitious genetic engineering using the toolkit of synthetic biology. But their complex biology also poses unique challenges. This mini review discusses some of the recent advances in synthetic biology approaches from an actinomycete perspective and presents examples of their application to the rational improvement of industrially relevant strains.

SEVA 3.0: an update of the Standard European Vector Architecture for enabling portability of genetic constructs among diverse bacterial hosts.

The Standard European Vector Architecture 3.0 database (SEVA-DB 3.0, http://seva.cnb.csic.es) is the update of the platform launched in 2013 both as a web-based resource and as a material repository of formatted genetic tools (mostly plasmids) for analysis, construction and deployment of complex bacterial phenotypes. The period between the first version of SEVA-DB and the present time has witnessed several technical, computational and conceptual advances in genetic/genomic engineering of prokaryotes that have enabled upgrading of the utilities of the updated database. Novelties include not only a more user-friendly web interface and many more plasmid vectors, but also new links of the plasmids to advanced bioinformatic tools. These provide an intuitive visualization of the constructs at stake and a range of virtual manipulations of DNA segments that were not possible before. Finally, the list of canonical SEVA plasmids is available in machine-readable SBOL (Synthetic Biology Open Language) format. This ensures interoperability with other platforms and affords simulations of their behaviour under different in vivo conditions. We argue that the SEVA-DB will remain a useful resource for extending Synthetic Biology approaches towards non-standard bacterial species as well as genetically programming new prokaryotic chassis for a suite of fundamental and biotechnological endeavours.

Optimization of thermophilic trans-isoprenyl diphosphate synthase expression in Escherichia coli by response surface methodology.

We optimized the heterologous expression of trans-isoprenyl diphosphate synthase (IDS), the key enzyme involved in the biosynthesis of trans-polyisoprene. trans-Polyisoprene is a particularly valuable compound due to its superior stiffness, excellent insulation, and low thermal expansion coefficient. Currently, trans-polyisoprene is mainly produced through chemical synthesis and no biotechnological processes have been established so far for its large-scale production. In this work, we employed D-optimal design and response surface methodology to optimize the expression of thermophilic enzymes IDS from Thermococcus kodakaraensis. The design of experiment took into account of six factors (preinduction cell density, inducer concentration, postinduction temperature, salt concentration, alternative carbon source, and protein inhibitor) and seven culture media (LB, NZCYM, TB, M9, Ec, Ac, and EDAVIS) at five different pH points. By screening only 109 experimental points, we were able to improve IDS production by 48% in close-batch fermentation.

Defined DNA-mediated assemblies of gene-expressing giant unilamellar vesicles.

The technological aspects of artificial vesicles as prominent cell mimics are evolving toward higher-order assemblies of functional vesicles with tissuelike architectures. Here, we demonstrate the spatially controlled DNA-directed bottom-up synthesis of complex microassemblies and macroassemblies of giant unilamellar vesicles functionalized with a basic cellular machinery to express green fluorescent protein and specified neighbor-to-neighbor interactions. We show both that the local and programmable DNA pairing rules on the nanoscale are able to direct the microscale vesicles into macroscale soft matter assemblies and that the highly sensitive gene-expression machinery remains intact and active during multiple experimental steps. An in silico model recapitulates the experiments performed in vitro and covers additional experimental setups highlighting the parameters that control the DNA-directed bottom-up synthesis of higher-order self-assembled structures. The controlled assembly of a functional vesicle matrix may be useful not only as simplified natural tissue mimics but also as artificial scaffolds that could interact and support living cells.

Do natural proteins differ from random sequences polypeptides? Natural vs. random proteins classification using an evolutionary neural network.

Are extant proteins the exquisite result of natural selection or are they random sequences slightly edited by evolution? This question has puzzled biochemists for long time and several groups have addressed this issue comparing natural protein sequences to completely random ones coming to contradicting conclusions. Previous works in literature focused on the analysis of primary structure in an attempt to identify possible signature of evolutionary editing. Conversely, in this work we compare a set of 762 natural proteins with an average length of 70 amino acids and an equal number of completely random ones of comparable length on the basis of their structural features. We use an ad hoc Evolutionary Neural Network Algorithm (ENNA) in order to assess whether and to what extent natural proteins are edited from random polypeptides employing 11 different structure-related variables (i.e. net charge, volume, surface area, coil, alpha helix, beta sheet, percentage of coil, percentage of alpha helix, percentage of beta sheet, percentage of secondary structure and surface hydrophobicity). The ENNA algorithm is capable to correctly distinguish natural proteins from random ones with an accuracy of 94.36%. Furthermore, we study the structural features of 32 random polypeptides misclassified as natural ones to unveil any structural similarity to natural proteins. Results show that random proteins misclassified by the ENNA algorithm exhibit a significant fold similarity to portions or subdomains of extant proteins at atomic resolution. Altogether, our results suggest that natural proteins are significantly edited from random polypeptides and evolutionary editing can be readily detected analyzing structural features. Furthermore, we also show that the ENNA, employing simple structural descriptors, can predict whether a protein chain is natural or random.

Coping with complexity: machine learning optimization of cell-free protein synthesis.

Biological systems contain complex metabolic pathways with many nonlinearities and synergies that make them difficult to predict from first principles. Protein synthesis is a canonical example of such a pathway. Here we show how cell-free protein synthesis may be improved through a series of iterated high-throughput experiments guided by a machine-learning algorithm implementing a form of evolutionary design of experiments (Evo-DoE). The algorithm predicts fruitful experiments from statistical models of the previous experimental results, combined with stochastic exploration of the experimental space. The desired experimental response, or evolutionary fitness, was defined as the yield of the target product, and new experimental conditions were discovered to have ∼ 350% greater yield than the standard. An analysis of the best experimental conditions discovered indicates that there are two distinct classes of kinetics, thus showing how our evolutionary design of experiments is capable of significant innovation, as well as gradual improvement.

Selection dynamic of Escherichia coli host in M13 combinatorial peptide phage display libraries.

Phage display relies on an iterative cycle of selection and amplification of random combinatorial libraries to enrich the initial population of those peptides that satisfy a priori chosen criteria. The effectiveness of any phage display protocol depends directly on library amino acid sequence diversity and the strength of the selection procedure. In this study we monitored the dynamics of the selective pressure exerted by the host organism on a random peptide library in the absence of any additional selection pressure. The results indicate that sequence censorship exerted by Escherichia coli dramatically reduces library diversity and can significantly impair phage display effectiveness.

Design and dynamic simulation of minimal metallo-proteins.

Ab initio in silico design of proteins and enzymes has emerged as a powerful tool to design application-tailored proteins and catalysts for a wide range of applications. Several enzymes exploit the unique features of metal cofactors to achieve catalytic activity otherwise unattainable through the use of only natural amino acid residues. One of the major bottlenecks in ab initio design of novel proteins relies on long-range and epistatic effects that severely limit the possibility of a rational design. Within this framework there is an ongoing effort to reduce protein length and complexity to unlock the full potential of in silico protein design. In this work we specifically address this problem designing and investigating the dynamic features of 10 in silico designed minimal metallo-proteins. In particular, in this paper we investigate whether and to what extent it is possible to design a minimal metallo-enzyme made of only residues involved in metal binding. In this research we address these questions by investigating the ability of 10 different "mini-proteins" with a length shorter than 15 residues. Molecular dynamics studies clearly show that it is possible to design a minimal protein able to bind a metal atom with the correct geometry. It is noteworthy that designed mini-proteins cannot achieve the formation of a canonical hydrophobic core, rather the metal ion provides a "metal core" around which the entire protein is organized. This opens the possibility of designing synthetic enzymes composed of only functional residues organized around a "metal core" which acts as both structural and functional determinat.

Massive non-natural proteins structure prediction using grid technologies.

BACKGROUND: The number of natural proteins represents a small fraction of all the possible protein sequences and there is an enormous number of proteins never sampled by nature, the so called "never born proteins" (NBPs). A fundamental question in this regard is if the ensemble of natural proteins possesses peculiar chemical and physical properties or if it is just the product of contingency coupled to functional selection. A key feature of natural proteins is their ability to form a well defined three-dimensional structure. Thus, the structural study of NBPs can help to understand if natural protein sequences were selected for their peculiar properties or if they are just one of the possible stable and functional ensembles. METHODS: The structural characterization of a huge number of random proteins cannot be approached experimentally, thus the problem has been tackled using a computational approach. A large random protein sequences library (2 x 10(4) sequences) was generated, discarding amino acid sequences with significant similarity to natural proteins, and the corresponding structures were predicted using Rosetta. Given the highly computational demanding problem, Rosetta was ported in grid and a user friendly job submission environment was developed within the GENIUS Grid Portal. Protein structures generated were analysed in terms of net charge, secondary structure content, surface/volume ratio, hydrophobic core composition, etc. RESULTS: The vast majority of NBPs, according to the Rosetta model, are characterized by a compact three-dimensional structure with a high secondary structure content. Structure compactness and surface polarity are comparable to those of natural proteins, suggesting similar stability and solubility. Deviations are observed in alpha helix-beta strands relative content and in hydrophobic core composition, as NBPs appear to be richer in helical structure and aromatic amino acids with respect to natural proteins. CONCLUSION: The results obtained suggest that the ability to form a compact, ordered and water-soluble structure is an intrinsic property of polypeptides. The tendency of random sequences to adopt alpha helical folds indicate that all-alpha proteins may have emerged early in pre-biotic evolution. Further, the lower percentage of aromatic residues observed in natural proteins has important evolutionary implications as far as tolerance to mutations is concerned.

Question 3: the worlds of the prebiotic and never born proteins.

Starting from the statement that no reliable methods are known to produce high molecular weight polypeptides under prebiotic conditions, a possible approach, at least to understand the differences between extant proteins and the possible large number of never born proteins, could be biological. Using the phage display method a large library of totally random amino acidic sequences was obtained. Consequently, different experiments to directly consider the frequency of stable folds were performed, and the interesting results obtained from such new approach are discussed in terms of contingency, contributing to the discussion on the selection mechanism of extant proteins.

Question 5: on the chemical reality of the RNA world.

The discovery of catalytic RNA has revolutionised modern molecular biology and bears important implications for the origin of Life research. Catalytic RNA, in particular self-replicating RNA, prompted the hypothesis of an early "RNA world" where RNA molecules played all major roles such information storage and catalysis. The actual role of RNA as primary actor in the origin of life has been under debate for a long time, with a particular emphasis on possible pathways to the prebiotic synthesis of mononucleotides; their polymerization and the possibility of spontaneous emergence of catalytic RNAs synthesised under plausible prebiotic conditions. However, little emphasis has been put on the chemical reality of an RNA world; in particular concerning the chemical constrains that such scenario should have met to be feasible. This paper intends to address those concerns with regard to the achievement of high local RNA molecules concentration and the aetiology of unique sequence under plausible prebiotic conditions.

Investigation of de novo totally random biosequences, Part II: On the folding frequency in a totally random library of de novo proteins obtained by phage display.

We present an investigation on theoretically possible protein structures which have not been selected by evolution and are, therefore, not present on our Earth ('Never Born Proteins' (NBP)). In particular, we attempt to assess whether and to what extent such polypeptides might be folded, thus acquiring a globular protein status. A library (ca. 10(9) clones) of totally random polypeptides, with a length of 50 amino acids, has been produced by phage display. The only structural bias in these sequences is a tripeptide substrate for thrombin: PRG, chosen according to the criteria described in the preceding Part I of this series. The presence of this substrate in an otherwise totally random sequence forms the basis for a qualitative experimental criterion which distinguishes unfolded from folded proteins, as folded proteins are more protected from protease digestion than unfolded ones. The investigation of 79 sequences, randomly selected from the initially large library, shows that over 20% of this population is thrombin-resistant, likely due to folding. Analysis of the amino acid sequences of these clones shows no significant homology to extant proteins, which indicates that they are indeed totally de novo. A few of these sequences have been expressed, and here we describe the structural properties of two thrombin-resistant randomly selected ones. These two de novo proteins have been characterized by spectroscopic methods and, in particular, by circular dichroism. The data show a stable three-dimensional folding, which is temperature-resistant and can be reversibly denatured by urea. The consequences of this finding within a library of 'Never Born Proteins' are discussed in terms of molecular evolution.

Investigation of de novo totally random biosequences, Part III: RNA Foster: A novel assay to investigate RNA folding structural properties.

Fold is essential to RNA properties, and, in particular, its thermodynamic stability can be used to monitor RNA-protein or RNA-ligand interactions, and to engineer RNA with novel or improved properties. While clearly valuable, experimental determination of RNA folding stability by traditional biophysical techniques requires substantial amounts of pure sample and rather expensive equipment. In this paper, we report a new, simple approach to the determination of RNA folding stability by coupling enzymatic digestion and temperature denaturation. The assay, named RNA folding stability Test (RNA Foster), is designed to probe the fraction of folded RNA (f(fold)) in an equilibrium mixture of folded and unfolded ones as a function of temperature. The simplicity of RNA Foster suggests that it can easily be scaled up for high-throughput studies of RNA folding stability both in basic and applied research.

Investigation of de novo totally random biosequences, Part IV: Folding Properties of de novo, totally random RNAs.

This work lies within the framework of a broader project aimed at exploring the realm of all possible folded polypeptides; the main question addressed here is whether the corresponding RNAs also assume a folded conformation. We present an investigation on the structural properties of de novo, totally random RNAs by means of the 'RNA Foster' assay. Experimental results show that all RNAs studied are folded at 37 degrees , so that fold seems to be a common feature of RNAs. Random RNAs' fold shows a surprising thermal stability with an average T(m) value at ca. 50 degrees which prompts the idea that thermo-stable structures might not be as rare as they are commonly thought to be. The results are discussed within the general framework of random RNA properties such as those that might have been produced in a prebiotic scenario.