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bioRxiv2017

Discovery and Evaluation of Biosynthetic Pathways for the Production of Five Methyl Ethyl Ketone Precursors

The limited supply of fossil fuels and the establishment of new environmental policies shifted research in industry and academia towards sustainable production of the 2nd generation of biofuels, with Methyl Ethyl Ketone (MEK) being one promising fuel candidate. MEK is a commercially valuable petrochemical with an extensive application as a solvent. However, as of today, a sustainable and economically viable production of MEK has not yet been achieved despite several attempts of introducing biosynthetic pathways in industrial microorganisms. We used BNICE.ch as a retrobiosynthesis tool to discover all novel pathways around MEK. Out of 1325 identified compounds connecting to MEK with one reaction step, we selected 3-oxopentanoate, but-3-en-2-one, but-1-en-2-olate, butylamine, and 2-hydroxy-2-methyl-butanenitrile for further study. We reconstructed 3679610 novel biosynthetic pathways towards these 5 compounds. We then embedded these pathways into the genome-scale model of E. coli, and a set of 18622 were found to be most biologically feasible ones based on thermodynamics and their yields. For each novel reaction in the viable pathways, we proposed the most similar KEGG reactions, with their gene and protein sequences, as candidates for either a direct experimental implementation or as a basis for enzyme engineering. Through pathway similarity analysis we classified the pathways and identified the enzymes and precursors that were indispensable for the production of the target molecules. These retrobiosynthesis studies demonstrate the potential of BNICE.ch for discovery, systematic evaluation, and analysis of novel pathways in synthetic biology and metabolic engineering studies.\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=76 SRC=\"FIGDIR/small/209569_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (27K):\norg.highwire.dtl.DTLVardef@15bb5corg.highwire.dtl.DTLVardef@bfc12borg.highwire.dtl.DTLVardef@1230500org.highwire.dtl.DTLVardef@1d74d2_HPS_FORMAT_FIGEXP M_FIG Graphical abstract C_FIG

synthetic biology↗

bioRxiv2018

Human 5′ UTR design and variant effect prediction from a massively parallel translation assay

Predicting the impact of cis-regulatory sequence on gene expression is a foundational challenge for biology. We combine polysome profiling of hundreds of thousands of randomized 5' UTRs with deep learning to build a predictive model that relates human 5' UTR sequence to translation. Together with a genetic algorithm, we use the model to engineer new 5' UTRs that accurately target specified levels of ribosome loading, providing the ability to tune sequences for optimal protein expression. We show that the same approach can be extended to chemically modified RNA, an important feature for applications in mRNA therapeutics and synthetic biology. We test 35,000 truncated human 5' UTRs and 3,577 naturally-occurring variants and show that the model accurately predicts ribosome loading of these sequences. Finally, we provide evidence of 47 SNVs associated with human diseases that cause a significant change in ribosome loading and thus a plausible molecular basis for disease.

synthetic biology↗

bioRxiv2017

Stringency of synthetic promoter sequences in Clostridium revealed and circumvented by tuning promoter library mutation rates

Collections of characterized promoters of different strengths are key resources for synthetic biology, but are not well established for many important organisms, including industrially-relevant Clostridium spp. When generating promoters, reporter constructs are used to measure expression, but classical fluorescent reporter proteins are oxygen-dependent and hence inactive in anaerobic bacteria like Clostridium. We directly compared oxygen-independent reporters of different types in Clostridium acetobutylicum and found that glucuronidase (GusA) from E. coli performed best. Using GusA, a library of synthetic promoters was first generated by a typical approach entailing complete randomization of a constitutive thiolase gene promoter (Pthl) except for the consensus -35 and -10 elements. In each synthetic promoter, the chance of each degenerate position matching Pthl was 25%. Surprisingly, none of the synthetic promoters from this library were functional in C. acetobutylicum, even though they functioned as expected in E. coli. Next, instead of complete randomization, we specified lower promoter mutation rates using oligonucleotide primers synthesized using custom mixtures of nucleotides. Using these primers, two promoter libraries were constructed in which the chance of each degenerate position matching Pthl was 79% or 58%, instead of 25% as before. Synthetic promoters from these stringent libraries functioned well in C. acetobutylicum, covering a wide range of strengths. The promoters functioned similarly in the distantly-related species Clostridium sporogenes, and allowed predictable metabolic engineering of C. acetobutylicum for acetoin production. Besides generating the desired promoters and demonstrating their useful properties, this work indicates an unexpected stringency of promoter sequences in Clostridium, not reported previously.\n\nGRAPHICAL ABSTRACT\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=94 SRC=\"FIGDIR/small/216853_ufig1.gif\" ALT=\"Figure 1000\">\nView larger version (28K):\norg.highwire.dtl.DTLVardef@52f2borg.highwire.dtl.DTLVardef@5be460org.highwire.dtl.DTLVardef@ee8b05org.highwire.dtl.DTLVardef@e92801_HPS_FORMAT_FIGEXP M_FIG C_FIG

synthetic biology↗

bioRxiv2015

Dynamic signal processing by ribozyme-mediated RNA circuits to control gene expression

Organisms have different circuitries that allow converting signal molecule levels to changes in gene expression. An important challenge in synthetic biology involves the de novo design of RNA modules enabling dynamic signal processing in live cells. This requires a scalable methodology for sensing, transmission, and actuation, which could be assembled into larger signaling networks. Here, we present a biochemical strategy to design RNA-mediated signal transduction cascades able to sense small molecules and small RNAs. We design switchable functional RNA domains by using strand-displacement techniques. We experimentally characterize the molecular mechanism underlying our synthetic RNA signaling cascades, show the ability to regulate gene expression with transduced RNA signals, and describe the signal processing response of our systems to periodic forcing in single live cells. The engineered systems integrate RNA-RNA interaction with available ribozyme and aptamer elements, providing new ways to engineer arbitrary complex gene circuits.

Synthetic Biology↗

bioRxiv2016

Biosynthesis of the Antibiotic Nonribosomal Peptide Penicillin in Baker’s Yeast

Fungi are a valuable source of enzymatic diversity and therapeutic natural products including antibiotics. By taking genes from a filamentous fungus and directing their efficient expression and subcellular localisation, we here engineer the bakers yeast Saccharomyces cerevisiae to produce and secrete the antibiotic penicillin, a beta-lactam nonribosomal peptide. Using synthetic biology tools combined with long-read DNA sequencing, we optimise productivity by 50-fold to produce bioactive yields that allow spent S. cerevisiae growth media to have antibacterial action against Streptococcus bacteria. This work demonstrates that S. cerevisiae can be engineered to perform the complex biosynthesis of multicellular fungi, opening up the possibility of using yeast to accelerate rational engineering of nonribosomal peptide antibiotics.

Synthetic Biology↗

bioRxiv2017

Tools for engineering coordinated system behaviour in synthetic microbial consortia

Advancing synthetic biology to the multicellular level requires the development of multiple orthogonal cell-to-cell communication channels to propagate information with minimal signal interference. The development of quorum sensing devices, the cornerstone technology for building microbial communities with coordinated system behaviour, has largely focused on reducing signal leakage between systems of cognate AHL/transcription factor pairs. However, the use of non-cognate signals as a design feature has received limited attention so far. Here, we demonstrate the largest library of AHL-receiver devices constructed to date with all cognate and non-cognate chemical signal interactions quantified and we develop a software tool that allows automated selection of orthogonal chemical channels. We use this approach to identify up to four orthogonal channels in silico and experimentally demonstrate the simultaneous use of three channels in co-culture. The development of multiple non-interfering cell-to-cell communication channels will facilitate the design of synthetic microbial consortia for novel applications including distributed bio-computation, increased bioprocess efficiency, cell specialisation, and spatial organisation.

synthetic biology↗

bioRxiv2017

Model reduction permits Turing instability analysis of arbitrary reaction-diffusion models

Synthesising a genetic network which generates stable Turing patterns is one of the great challenges of synthetic biology, but a significant obstacle is the disconnect between the mathematical theory and the biological reality. Current mathematical understanding of patterning is typically restricted to systems of 2 or 3 chemical species, for which equations are tractable, but plausible genetic networks typically consist of dozens of interacting species. In this article, we suggest a method for reducing large biochemical systems to systems with 2 or 3 species which can then be studied analytically. We provide conditions to guarantee that the full system forms patterns if the reduced system does, and vice-versa. We confirm our technique with 3 examples: the Brusselator, an example proposed by Turing, and a biochemically plausible patterning system consisting of 17 species. These examples show that our method significantly simplifies the study of pattern formation in large systems.

synthetic biology↗

bioRxiv2017

Accelerating Evolutionary Hill Climbs in Parallel Turbidostats

Evolution has been used to address many engineering problems. Within the context of metabolic engineering and synthetic biology, directed evolution has natural appli-cations. However, most research concerning optimizing microbial evolution has been focused on library generation and screening, while accelerating evolutionary hill climbs and been largely ignored. Here, we develop a model to explore how population struc-ture can accelerate evolutionary hill climbs. We show that by adjusting the population size, environmental challenge, and meta-population dynamics that the rate of evolution can be accelerated in parallel turbidostats. Our analyses leads to two surprising results: small populations are favored over conventionally large microbial populations, and propagating modest fitness improvements is favored over propagating mutants with large beneficial mutations. When combined with rational design and other optimization techniques our theory can accelerate strain development for applications such as consolidated bioprocessing, and bioremidation systems.

synthetic biology↗

bioRxiv2018

Synthetic mammalian pattern formation driven by differential diffusivity of Nodal and Lefty

Pattern formation is fundamental for embryonic development. Although synthetic biologists have created several patterns, a synthetic mammalian reaction-diffusion pattern has yet to be realized. TGF-{beta} family proteins Nodal and Lefty have been proposed to meet the conditions for reaction-diffusion patterning: Nodal is a short-range activator that enhances the expression of Nodal and Lefty whereas Lefty acts as a long-range inhibitor against Nodal. However, the pattern forming possibility of the Nodal-Lefty signaling has never been directly tested, and the underlying mechanisms of differential diffusivity of Nodal and Lefty remain unclear. Here, through a combination of synthetic biology and theoretical modeling, we show that a reconstituted minimal network of the Nodal-Lefty signaling spontaneously gives rise to a pattern in mammalian cell culture. Surprisingly, extracellular Nodal was confined underneath the cells as small clusters, resulting in a narrow distribution range compared with Lefty. We further found that the finger 1 domain of the Nodal protein is responsible for its short-range distribution. By transplanting the finger 1 domain of Nodal into Lefty, we converted the originally long-range distribution of Lefty to a short-range one, successfully preventing the pattern formation. These results indicate that the differences in the localization and domain structures between Nodal and Lefty, combined with the activator-inhibitor topology, are sufficient for reaction-diffusion pattern formation in mammalian cells.

synthetic biology↗

bioRxiv2017

Refactoring gene sequences for broad assembly standards compatibility

Four cloning standards in synthetic biology are BioBrick, BglBrick, MoClo and GoldenBraid, with each requiring their constitutive parts be compatible with the associated restriction enzymes. To standardize parts for the broadest usage, it would be useful to synthesize genes that are simultaneously compatible with all 4 popular assembly strategies. Here it is shown that using a defined set of rules, implemented in a computational program, any protein coding sequence can be made compatible with all four standards by silent mutations. Using a coding sequence as an input, all BioBrick, BglBrick, MoClo, and GoldenBraid restriction sites and chi recombination hot spots can be destroyed with silent mutations that approximate the codon usage of the organism. As an application, all open reading frames in the model organisms Escherichia Coli and Bacillus Subtilis are computationally refactored, showing the feasibility of implementing this umbrella strategy for synthesizing genes with the broadest compatibility.

synthetic biology↗

bioRxiv2016

Ribo-attenuators: novel elements for reliable and modular riboswitch engineering

Riboswitches are structural genetic regulatory elements that directly couple the sensing of small molecules to gene expression. They have considerable potential for applications throughout synthetic biology and bio-manufacturing as they are able to sense a wide range of small molecules and regulate gene expression in response. Despite over a decade of research they have yet to reach this considerable potential as they cannot yet be treated as modular components. This is due to several limitations including sensitivity to changes in genetic context, low tunability, and variability in performance. To overcome the associated difficulties with riboswitches, we have designed and introduced a novel genetic element called a Ribo-attenuator in Bacteria. This genetic element allows for predictable tuning, insulation from contextual changes, and a reduction in expression variation. Ribo-attenuators allow riboswitches to be treated as truly modular and tunable components, and thus increases their reliability for a wide range of applications.

synthetic biology↗

bioRxiv2017

Mobius Assembly: A Versatile Framework For Golden Gate Assembly

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=104 SRC=\"FIGDIR/small/140095_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (16K):\norg.highwire.dtl.DTLVardef@165d4e4org.highwire.dtl.DTLVardef@7bd8f1org.highwire.dtl.DTLVardef@dfbda4org.highwire.dtl.DTLVardef@11b8db9_HPS_FORMAT_FIGEXP M_FIG C_FIG Golden Gate Assembly is a powerful synthetic biology tool, which utilizes Type IIS enzymes for unidirectional assembly of multiple DNA fragments. The simplicity of its DNA assembly and the exchangeability of standard parts greatly facilitate the generation of combinatorial assembly libraries. Currently there are two popular Golden Gate Assembly frameworks that allow multigene augmentation (MoClo and Golden Braid); they render either high cloning capacity or vector toolkit simplicity. We have developed a new Golden Gate Assembly framework called Mobius Assembly, which combines vector toolkit simplicity with high cloning capacity. Mobius Assembly is based on a two-level approach and embraces the standard overhangs defined by MoClo and Golden Braid to confer exchangeability, but with reduced domestication requirement. Furthermore, we have implemented drop-out cassettes encoding chromogenic proteins for visible cloning screening. As proofs of concept, we have functionally assembled up to 16 transcriptional units of various pigmentation genes in both operon and multigene arrangements.

synthetic biology↗

bioRxiv2018

Activation of innate immune responses by a CpG oligonucleotide sequence composed entirely of threose nucleic acid.

Recent advances in synthetic biology have led to the development of nucleic acid polymers with backbone structures distinct from those found in nature, termed xeno-nucleic acids (XNAs). Several unique properties of XNAs make them attractive as nucleic acid therapeutics, most notably their high resistance to serum nucleases and ability to form Watson-Crick base-pairing with DNA and RNA. The ability of XNAs to induce immune responses has not been investigated. Threose nucleic acid (TNA), a type of XNA, is recalcitrant to nuclease digestion and capable of undergoing Darwinian evolution to produce high affinity aptamers; thus, TNA is an attractive candidate for diverse applications, including nucleic acid therapeutics. Here, we evaluated a TNA oligonucleotide derived from a CpG oligonucleotide sequence known to activate TLR9-dependent immune signaling in B cell lines. We observed a slight induction of relevant mRNA signals, robust B cell line activation, and negligible effects on cellular proliferation.

synthetic biology↗

bioRxiv2014

Selection of chromosomal DNA libraries using a multiplex CRISPR system in Saccharomyces cerevisiae

The directed evolution of biomolecules to improve or change their activity is central to many engineering and synthetic biology efforts. However, selecting improved variants from gene libraries in living cells requires plasmid expression systems that suffer from variable copy number effects, or the use of complex marker-dependent chromosomal integration strategies. We developed quantitative gene assembly and DNA library insertion into the Saccharomyces cerevisiae genome by optimizing an efficient single-step and marker-free genome editing system using CRISPR-Cas9. With this Multiplex CRISPR (CRISPRm) system, we selected an improved cellobiose utilization pathway in diploid yeast in a single round of mutagenesis and selection, which increased cellobiose fermentation rates by over ten-fold. Mutations recovered in the best cellodextrin transporters reveal synergy between substrate binding and transporter dynamics, and demonstrate the power of CRISPRm to accelerate selection experiments and discoveries of the molecular determinants that enhance biomolecule function.

Synthetic Biology↗

bioRxiv2015

Engineering Transcriptional Regulator Effector Specificity using Computational Design and In Vitro Rapid Prototyping: Developing a Vanillin Sensor

The pursuit of circuits and metabolic pathways of increasing complexity and ro-bustness in synthetic biology will require engineering new regulatory tools. Feedback control based on relevant molecules, including toxic intermediates and environmental signals, would enable genetic circuits to react appropriately to changing conditions. In this work, variants of qacR, a tetR family repressor, were generated by computational protein design and screened in a cell-free transcription-translation (TX-TL) system for responsiveness to a new targeted effector. The modified repressors target vanillin, a growth-inhibiting small molecule found in lignocellulosic hydrolysates and other industrial processes. Promising candidates from the in vitro screen were further characterized in vitro and in vivo in a gene circuit. The screen yielded two qacR mutants that respond to vanillin both in vitro and in vivo. We believe this process, a combination of the generation of variants coupled with in vitro screening, can serve as a framework for designing new sensors for other target compounds.

Synthetic Biology↗

bioRxiv2017

Modeling mechanical interactions in growing populations of rod-shaped bacteria

Advances in synthetic biology allow us to engineer bacterial collectives with pre-specified characteristics. However, the behavior of these collectives is difficult to understand, as cellular growth and division as well as extra-cellular fluid flow lead to complex, changing arrangements of cells within the population. To rationally engineer and control the behavior of cell collectives we need theoretical and computational tools to understand their emergent spatiotemporal dynamics. Here, we present an agent-based model that allows growing cells to detect and respond to mechanical interactions. Crucially, our model couples the dynamics of cell growth to the cells environment: Mechanical constraints can affect cellular growth rate and a cell may alter its behavior in response to these constraints. This coupling links the mechanical forces that influence cell growth and emergent behaviors in cell assemblies. We illustrate our approach by showing how mechanical interactions can impact the dynamics of bacterial collectives growing in microfluidic traps.

synthetic biology↗

bioRxiv2017

Deep learning of the regulatory grammar of yeast 5’ untranslated regions from 500,000 random sequences

Our ability to predict protein expression from DNA sequence alone remains poor, reflecting our limited understanding of cis-regulatory grammar and hampering the design of engineered genes for synthetic biology applications. Here, we generate a model that predicts the translational efficiency of the 5 untranslated region (UTR) of mRNAs in the yeast Saccharomyces cerevisiae. We constructed a library of half a million 50-nucleotide-long random 5 UTRs and assayed their activity in a massively parallel growth selection experiment. The resulting data allow us to quantify the impact on translation of Kozak sequence composition, upstream open reading frames (uORFs) and secondary structure. We trained a convolutional neural network (CNN) on the random library and showed that it performs well at predicting the translational efficiency of both a held-out set of the random 5 UTRs as well as native S. cerevisiae 5 UTRs. The model additionally was used to computationally evolve highly translating 5 UTRs. We confirmed experimentally that the great majority of the evolved sequences lead to higher translation rates than the starting sequences, demonstrating the predictive power of this model.

synthetic biology↗

bioRxiv2017

Computational design of Small Transcription Activating RNAs (STARs) for versatile and dynamic gene regulation

A longstanding goal of synthetic biology has been the programmable control of cellular functions. Central to this goal is the creation of versatile regulatory toolsets that allow for programmable control of gene expression. Of the many regulatory molecules available, RNA regulators offer the intriguing possibility of de novo design - allowing for the bottom-up molecular-level design of genetic control systems. Here we present a computational design approach for the creation of a bacterial regulator called Small Transcription Activating RNAs (STARs) and create a library of high-performing and orthogonal STARs that achieve up to [~]9000-fold gene activation. We then demonstrate the versatility of RNA-based transcription control by showing the broad utility of STARs - from acting synergistically with existing constitutive and inducible regulators, to reprogramming cellular phenotypes and controlling multigene metabolic pathway expression. Finally, we combine these new STARs with themselves and CRISPRi transcriptional repressors to deliver new types of RNA-based genetic circuitry that allow for sophisticated and temporal control of gene expression.

synthetic biology↗