Synthetic and systems biology for microbial production of commodity chemicals

Fine-tuning ethanol oxidation pathway enzymes and cofactor PQQ coordinates the conflict between fitness and acetic acid production by Acetobacter pasteurianus

The very high concentrations required for industrial production of free acetic acid create toxicity and low pH values, which usually conflict with the host cell growth, leading to a poor productivity. Achieving a balance between cell fitness and product synthesis is the key challenge to improving acetic acid production efficiency in metabolic engineering. Here, we show that the synergistic regulation of alcohol/aldehyde dehydrogenase expression and cofactor PQQ level could not only efficiently relieve conflict between increased acetic acid production and compromised cell fitness, but also greatly enhance acetic acid tolerance of Acetobacter pasteurianus to a high initial concentration (3% v/v) of acetic acid. Combinatorial expression of adhA and pqqABCDE greatly shortens the duration of starting‐up process from 116 to 99 h, leading to a yield of 69 g l^‐1 acetic acid in semi‐continuous fermentation. As a final result, average acetic acid productivity has been raised to 0.99 g l^‐1 h^‐1, which was 32% higher than the parental A. pasteurianus. This study is of great significance for decreasing cost of semi‐continuous fermentation for producing high‐strength acetic acid industrially. We envisioned that this strategy will be useful for production of many other desired organic acids, especially those involving cofactor reactions.

Modelling co-translational dimerization for programmable nonlinearity in synthetic biology

Nonlinearity plays a fundamental role in the performance of both natural and synthetic biological networks. Key functional motifs in living microbial systems, such as the emergence of bistability or oscillations, rely on nonlinear molecular dynamics. Despite its core importance, the rational design of nonlinearity remains an unmet challenge. This is largely due to a lack of mathematical modelling that accounts for the mechanistic basis of nonlinearity. We introduce a model for gene regulatory circuits that explicitly simulates protein dimerization-a well-known source of nonlinear dynamics. Specifically, our approach focuses on modelling co-translational dimerization: the formation of protein dimers during-and not after-translation. This is in contrast to the prevailing assumption that dimer generation is only viable between freely diffusing monomers (i.e. post-translational dimerization). We provide a method for fine-tuning nonlinearity on demand by balancing the impact of co- versus post-translational dimerization. Furthermore, we suggest design rules, such as protein length or physical separation between genes, that may be used to adjust dimerization dynamics in vivo. The design, build and test of genetic circuits with on-demand nonlinear dynamics will greatly improve the programmability of synthetic biological systems.

Multiplex Design of the Metabolic Network for Production of l-Homoserine in Escherichia coli

In this study, the bottlenecks that sequentially limit l-homoserine biosynthesis were identified and resolved, based on rational and efficient metabolic-engineering strategies, coupled with CRISPR interference (CRISPRi)-based systematic analysis. The metabolomics data largely expanded our understanding of metabolic effects and revealed relevant targets for further modification to achieve better performance. The systematic analysis strategy, as well as metabolomics analysis, can be used to rationally design cell factories for the production of highly valuable chemicals.

l-Homoserine, which is one of the few amino acids that is not produced on a large scale by microbial fermentation, plays a significant role in the synthesis of a series of valuable chemicals. In this study, systematic metabolic engineering was applied to target Escherichia coli W3110 for the production of l-homoserine. Initially, a basic l-homoserine producer was engineered through the strategies of overexpressing thrA (encoding homoserine dehydrogenase), removing the degradative and competitive pathways by knocking out metA (encoding homoserine O-succinyltransferase) and thrB (encoding homoserine kinase), reinforcing the transport system, and redirecting the carbon flux by deleting iclR (encoding the isocitrate lyase regulator). The resulting strain constructed by these strategies yielded 3.21 g/liter of l-homoserine in batch cultures. Moreover, based on CRISPR-Cas9/dCas9 (nuclease-dead Cas9)-mediated gene repression for 50 genes, the iterative genetic modifications of biosynthesis pathways improved the l-homoserine yield in a stepwise manner. The rational integration of glucose uptake and recovery of l-glutamate increased l-homoserine production to 7.25 g/liter in shake flask cultivation. Furthermore, the intracellular metabolic analysis further provided targets for strain modification by introducing the anaplerotic route afforded by pyruvate carboxylase to oxaloacetate formation, which resulted in accumulating 8.54 g/liter l-homoserine (0.33 g/g glucose, 62.4% of the maximum theoretical yield) in shake flask cultivation. Finally, a rationally designed strain gave 37.57 g/liter l-homoserine under fed-batch fermentation, with a yield of 0.31 g/g glucose.

IMPORTANCE In this study, the bottlenecks that sequentially limit l-homoserine biosynthesis were identified and resolved, based on rational and efficient metabolic-engineering strategies, coupled with CRISPR interference (CRISPRi)-based systematic analysis. The metabolomics data largely expanded our understanding of metabolic effects and revealed relevant targets for further modification to achieve better performance. The systematic analysis strategy, as well as metabolomics analysis, can be used to rationally design cell factories for the production of highly valuable chemicals.

A model-driven approach towards rational microbial bioprocess optimization

Due to sustainability concerns, bio-based production capitalizing on microbes as cell factories is in demand to synthesize valuable products. Nevertheless, the nonhomogenous variations of the extracellular environment in bioprocesses often challenge the biomass growth and the bioproduction yield. To enable a more rational bioprocess optimization, we have established a model-driven approach that systematically integrates experiments with modeling, executed from flask to bioreactor scale, and using ferulic acid to vanillin bioconversion as a case study. The impacts of mass transfer and aeration on the biomass growth and bioproduction performances were examined using minimal small-scale experiments. An integrated model coupling the cell factory kinetics with the three-dimensional computational hydrodynamics of bioreactor was developed to better capture the spatiotemporal distributions of bioproduction. Full-factorial predictions were then performed to identify the desired operating conditions. A bioconversion yield of 94% was achieved, which is one of the highest for recombinant Escherichia coli using ferulic acid as the precursor.

Optimization and Molecular Characterization of Lipase Producing Bacillus subtilis Strain Rcps3 and Bacillus fumarioli Strain Rcps4 from Oil-contaminated Soils of Warangal

Microbial sources are regularly used as reliable biocatalysts sources which are often used in the process and production industry. Demands for such organisms with greater capacity of intended enzyme production are on the rise. Lipase is important enzyme used in the biotechnological process of hydrolysis of fats in almost all the relevant industries We have utilized the local oil-contaminated soil resources to search for efficacious bacterial strains that have excellent lipase activity. We were successful in identifying two such bacterial sources, namely, Bacillus subtilis strain RCPS3 and Bacillus fumarioli strain RCPS4, responsible for lipase production from oil effluent contaminated soil of Telangana. This is the first report of these two strains from this part of India that are involved in lipase production. The strains were isolated, optimized, and purified using standard microbiology protocols and were characterized at the molecular level using the biomarker 16s ribosomal RNA genes of the strains. The identified and isolated bacterial strains were confirmed as Bacillus subtilis strain RCPS3, and Bacillus fumarioli strain RCPS4 through molecular and computational characterization.

A machine learning Automated Recommendation Tool for synthetic biology

Synthetic biology allows us to bioengineer cells to synthesize novel valuable molecules such as renewable biofuels or anticancer drugs. However, traditional synthetic biology approaches involve ad-hoc engineering practices, which lead to long development times. Here, we present the Automated Recommendation Tool (ART), a tool that leverages machine learning and probabilistic modeling techniques to guide synthetic biology in a systematic fashion, without the need for a full mechanistic understanding of the biological system. Using sampling-based optimization, ART provides a set of recommended strains to be built in the next engineering cycle, alongside probabilistic predictions of their production levels. We demonstrate the capabilities of ART on simulated data sets, as well as experimental data from real metabolic engineering projects producing renewable biofuels, hoppy flavored beer without hops, fatty acids, and tryptophan. Finally, we discuss the limitations of this approach, and the practical consequences of the underlying assumptions failing.

Isobutanol production freed from biological limits using synthetic biochemistry

Cost competitive conversion of biomass-derived sugars into biofuel will require high yields, high volumetric productivities and high titers. Suitable production parameters are hard to achieve in cell-based systems because of the need to maintain life processes. As a result, next-generation biofuel production in engineered microbes has yet to match the stringent cost targets set by petroleum fuels. Removing the constraints imposed by having to maintain cell viability might facilitate improved production metrics. Here, we report a cell-free system in a bioreactor with continuous product removal that produces isobutanol from glucose at a maximum productivity of 4 g L⁻¹ h⁻¹, a titer of 275 g L⁻¹ and 95% yield over the course of nearly 5 days. These production metrics exceed even the highly developed ethanol fermentation process. Our results suggest that moving beyond cells has the potential to expand what is possible for bio-based chemical production.

A cell free or synthetic biochemistry approach offers a way to circumvent the many constraints of living cells. Here, the authors demonstrate, via enzyme and process enhancements, the production of isobutanol with the metrics exceeding highly developed ethanol fermentation.

The 3-ketoacyl-CoA thiolase: an engineered enzyme for carbon chain elongation of chemical compounds

Because of their function of catalyzing the rearrangement of the carbon chains, thiolases have attracted increasing attentions over the past decades. The 3-ketoacyl-CoA thiolase (KAT) is a member of the thiolase, which is capable of catalyzing the Claisen condensation reaction between the two acyl-CoAs, thereby achieving carbon chain elongation. In this way, diverse value-added compounds might be synthesized starting from simple small CoA thioesters. However, most KATs are hampered by low stability and poor substrate specificity, which has hindered the development of large-scale biosynthesis. In this review, the common characteristics in the three-dimensional structure of KATs from different sources are summarized. Moreover, structure-guided rational engineering is discussed as a strategy for enhancing the performance of KATs. Finally, we reviewed the metabolic engineering applications of KATs for producing various energy-storage molecules, such as n-butanol, fatty acids, dicarboxylic acids, and polyhydroxyalkanoates. KEY POINTS: • Summarize the structural characteristics and catalyzation mechanisms of KATs. • Review on the rational engineering to enhance the performance of KATs. • Discuss the applications of KATs for producing energy-storage molecules.

Lignin valorization using biological approach

Due to the structural complexity and recalcitrance nature of lignin, its depolymerization into monomeric units becomes one of the biggest challenges in the bioconversion of lignin into value-added products. Depolymerization of lignin produces a blend of many compounds that are problematic for isolating components in a cost-effective way. Lignin valorization using a biological approach facilitates sustainable and commercially viable biorefineries. The use of microbes for the conversion of depolymerized lignin compounds into target products can be a solution to the heterogeneity issue. Several studies have been carried out to develop robust strains that can utilize all relevant lignin-derived compounds, but constructing these strains is difficult. As an alternative, designing multiple microbes to convert a mixture of various compounds into the desired product seems realistic. This review provides an overview of lignin bioconversion using various approaches such as metabolic engineering and synthetic biology. Ligninolytic strains have a broad enzymatic machine for depolymerization of lignin and its conversion into intermediates such as catechol or protocatechuate. These intermediates can be further converted to metabolite products such as polyhydroxyalkanoates and triacylglycerol. Synthetic biology offers encouraging methodologies to construct pathways for lignin conversion and to engineer ligninolytic microbes as prospective strains for lignin bioconversion.

Saccharomyces cerevisiae (Baker's Yeast) as an Interfering RNA Expression and Delivery System

The broad application of RNA interference for disease prevention is dependent upon the production of dsRNA in an economically feasible, scalable, and sustainable fashion, as well as the identification of safe and effective methods for RNA delivery. Current research has sparked interest in the use of Saccharomyces cerevisiae for these applications. This review examines the potential for commercial development of yeast interfering RNA expression and delivery systems. S. cerevisiae is a genetic model organism that lacks a functional RNA interference system, which may make it an ideal system for expression and accumulation of high levels of recombinant interfering RNA. Moreover, recent studies in a variety of eukaryotic species suggest that this microbe may be an excellent and safe system for interfering RNA delivery. Key areas for further research and development include optimization of interfering RNA expression in S. cerevisiae, industrial-sized scaling of recombinant yeast cultures in which interfering RNA molecules are expressed, the development of methods for large-scale drying of yeast that preserve interfering RNA integrity, and identification of encapsulating agents that promote yeast stability in various environmental conditions. The genetic tractability of S. cerevisiae and a long history of using this microbe in both the food and pharmaceutical industry will facilitate further development of this promising new technology, which has many potential applications of medical importance.

The Role of Synthetic Biology in Atmospheric Greenhouse Gas Reduction: Prospects and Challenges

The long atmospheric residence time of CO2 creates an urgent need to add atmospheric carbon drawdown to CO2 regulatory strategies. Synthetic and systems biology (SSB), which enables manipulation of cellular phenotypes, offers a powerful approach to amplifying and adding new possibilities to current land management practices aimed at reducing atmospheric carbon. The participants (in attendance: Christina Agapakis, George Annas, Adam Arkin, George Church, Robert Cook-Deegan, Charles DeLisi, Dan Drell, Sheldon Glashow, Steve Hamburg, Henry Jacoby, Henry Kelly, Mark Kon, Todd Kuiken, Mary Lidstrom, Mike MacCracken, June Medford, Jerry Melillo, Ron Milo, Pilar Ossorio, Ari Patrinos, Keith Paustian, Kristala Jones Prather, Kent Redford, David Resnik, John Reilly, Richard J. Roberts, Daniel Segre, Susan Solomon, Elizabeth Strychalski, Chris Voigt, Dominic Woolf, Stan Wullschleger, and Xiaohan Yang) identified a range of possibilities by which SSB might help reduce greenhouse gas concentrations and which might also contribute to environmental sustainability and adaptation. These include, among other possibilities, engineering plants to convert CO2 produced by respiration into a stable carbonate, designing plants with an increased root-to-shoot ratio, and creating plants with the ability to self-fertilize. A number of serious ecological and societal challenges must, however, be confronted and resolved before any such application can be fully assessed, realized, and deployed.

Data-driven rational biosynthesis design: from molecules to cell factories

A proliferation of chemical, reaction and enzyme databases, new computational methods and software tools for data-driven rational biosynthesis design have emerged in recent years. With the coming of the era of big data, particularly in the bio-medical field, data-driven rational biosynthesis design could potentially be useful to construct target-oriented chassis organisms. Engineering the complicated metabolic systems of chassis organisms to biosynthesize target molecules from inexpensive biomass is the main goal of cell factory design. The process of data-driven cell factory design could be divided into several parts: (1) target molecule selection; (2) metabolic reaction and pathway design; (3) prediction of novel enzymes based on protein domain and structure transformation of biosynthetic reactions; (4) construction of large-scale DNA for metabolic pathways; and (5) DNA assembly methods and visualization tools. The construction of a one-stop cell factory system could achieve automated design from the molecule level to the chassis level. In this article, we outline data-driven rational biosynthesis design steps and provide an overview of related tools in individual steps.

Flux controlling technology for central carbon metabolism for efficient microbial bio-production

Syntheses of many commodities that are produced using microorganisms require cofactors such as ATP and NAD(P)H. Thus, optimization of the flux distribution in central carbon metabolism, which plays a key role in cofactor regeneration, is critical for enhancing the production of the target compounds. Since the intracellular and extracellular conditions change over time in the fermentation process, dynamic control of the metabolic system for maintaining the cellular state appropriately is necessary. Here, we review techniques for detecting the intracellular metabolic state with fluorescent sensors and controlling the flux of central carbon metabolism with optogenetic tools, as well as present a prospect of bio-production processes for fine-tuning the flux distribution.

Protein-based biorefining driven by nitrogen-responsive transcriptional machinery

BACKGROUND

Protein-based bioconversion has been demonstrated as a sustainable approach to produce higher alcohols and ammonia fertilizers. However, owing to the switchover from transcription mediated by the bacterial RNA polymerase σ⁷⁰ to that mediated by alternative σ factors, the biofuel production driven by σ⁷⁰-dependent promoters declines rapidly once cells enter the stationary phase or encounter stresses. To enhance biofuel production, in this study the growth phase-independent and nitrogen-responsive transcriptional machinery mediated by the σ⁵⁴ is exploited to drive robust protein-to-fuel conversion.

RESULTS

We demonstrated that disrupting the Escherichia coli ammonia assimilation pathways driven by glutamate dehydrogenase and glutamine synthetase could sustain the activity of σ⁵⁴-mediated transcription under ammonia-accumulating conditions. In addition, two σ⁵⁴-dependent promoters, argTp and glnAp2, were identified as suitable candidates for driving pathway expression. Using these promoters, biofuel production from proteins was shown to persist to the stationary phase, with the net production in the stationary phase being 1.7-fold higher than that derived from the optimal reported σ⁷⁰-dependent promoter P _LlacO₁. Biofuel production reaching levels 1.3- to 3.4-fold higher than those of the σ⁷⁰-dependent promoters was also achieved by argTp and glnAp2 under stressed conditions. Moreover, the σ⁵⁴-dependent promoters realized more rapid and stable production than that of σ⁷⁰-dependent promoters during fed-batch fermentation, producing up to 4.78 g L ^- 1 of total biofuels.

CONCLUSIONS

These results suggested that the nitrogen-responsive transcriptional machinery offers the potential to decouple production from growth, highlighting this system as a novel candidate to realize growth phase-independent and stress-resistant biofuel production.

Tackling Achilles' Heel in Synthetic Biology: Pairing Intracellular Synthesis of Noncanonical Amino Acids with Genetic-Code Expansion to Foster Biotechnological Applications

For the last two decades, synthetic biologists have been able to unlock and expand the genetic code, generating proteins with unique properties through the incorporation of noncanonical amino acids (ncAAs). These evolved biomaterials have shown great potential for applications in industrial biocatalysis, therapeutics, bioremediation, bioconjugation, and other areas. Our ability to continue developing such technologies depends on having relatively easy access to ncAAs. However, the synthesis of enantiomerically pure ncAAs in practical quantitates for large-scale processes remains a challenge. Biocatalytic ncAA production has emerged as an excellent alternative to traditional organic synthesis in terms of cost, enantioselectivity, and sustainability. Moreover, biocatalytic synthesis offers the opportunity of coupling the intracellular generation of ncAAs with genetic-code expansion to overcome the limitations of an external supply of amino acid. In this minireview, we examine some of the most relevant achievements of this approach and its implications for improving technological applications derived from synthetic biology.

Applications of stable isotope-based metabolomics and fluxomics toward synthetic biology of cyanobacteria

Unique features of cyanobacteria (e.g., photosynthesis and nitrogen fixation) make them potential candidates for production of biofuels and other value-added biochemicals. As prokaryotes, they can be readily engineered using synthetic and systems biology tools. Metabolic engineering of cyanobacteria for the synthesis of desired compounds requires in-depth knowledge of central carbon and nitrogen metabolism, pathway fluxes, and their regulation. Metabolomics and fluxomics offer the comprehensive analysis of metabolism by directly characterizing the biochemical activities of cells. This information is acquired by measuring the abundance of key metabolites and their rates of interconversion, which can be achieved by labeling cells with stable isotopes, quantifying metabolite pool sizes and isotope incorporation by gas chromatography/liquid chromatography-mass spectrometry GC/LC-MS or nuclear magnetic resonance (NMR), and mathematical modeling to estimate in vivo metabolic fluxes. Herein, we review progress that has been made to adapt metabolomics and fluxomics tools to examine model cyanobacterial species. We summarize the application of metabolic flux analysis (MFA) strategies to identify metabolic bottlenecks that can be targeted to boost cell growth, improve stress tolerance, or enhance biochemical production in cyanobacteria. Despite the advances in metabolomics, fluxomics, and other synthetic and systems biology tools during the past years, further efforts are required to increase our understanding of cyanobacterial metabolism in order to create efficient photosynthetic hosts for the production of value-added compounds. This article is categorized under: Laboratory Methods and Technologies > Metabolomics Biological Mechanisms > Metabolism Analytical and Computational Methods > Analytical Methods.

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.

Synthetic biology uses cells as its computing substrate, often based on the genetic circuit concept. In this Perspective, the authors argue that existing synthetic biology approaches based on classical models of computation limit the potential of biocomputing, and propose that living organisms have under-exploited capabilities.

Highly Efficient Preparation of Cyclic Dinucleotides via Engineering of Dinucleotide Cyclases in Escherichia coli

Cyclic dinucleotides (CDNs) are widely used secondary signaling molecules in bacterial and mammalian cells. The family of CDNs includes c-di-GMP, c-di-AMP and two distinct versions of hybrid cGAMPs. Studies related to these CDNs require large doses that are relatively expensive to generate by current methods. Here we report what to our knowledge is the first feasible microbial-based method to prepare these CDNs including c-di-GMP, 3′3′-cGAMP and 2′3′-cGAMP. The method mainly includes two parts: producing high yield of CDNs by engineering the overexpression of the proper dinucleotide cyclases (DNCs) and other related proteins in Escherichia coli, and purifying the bacteria-produced CDNs by a unified and simple process involving a STING affinity column, macroporous adsorption resin and C18 reverse-phase liquid chromatography. After purification, we obtained the diammonium salts of c-di-GMP, 3′3′-cGAMP and 2′3′-cGAMP with weight purity of >99, >96, >99% and in yields of >68, >26, and >82 milligrams per liter of culture, respectively. This technological platform enables the production of CDNs from cheaper material, provides a sustainable source of CDNs for scientific investigation, and can easily be further developed to prepare CDNs on a large scale for industry.

Engineering orthogonal synthetic timer circuits based on extracytoplasmic function σ factors

The rational design of synthetic regulatory circuits critically hinges on the availability of orthogonal and well-characterized building blocks. Here, we focus on extracytoplasmic function (ECF) σ factors, which are the largest group of alternative σ factors and hold extensive potential as synthetic orthogonal regulators. By assembling multiple ECF σ factors into regulatory cascades of varying length, we benchmark the scalability of the approach, showing that these ‘autonomous timer circuits’ feature a tuneable time delay between inducer addition and target gene activation. The implementation of similar timers in Escherichia coli and Bacillus subtilis shows strikingly convergent circuit behavior, which can be rationalized by a computational model. These findings not only reveal ECF σ factors as powerful building blocks for a rational, multi-layered circuit design, but also suggest that ECF σ factors are universally applicable as orthogonal regulators in a variety of bacterial species.

Identifying and engineering the ideal microbial terpenoid production host

More than 70,000 different terpenoid structures are known so far; many of them offer highly interesting applications as pharmaceuticals, flavors and fragrances, or biofuels. Extraction of these compounds from their natural sources or chemical synthesis is-in many cases-technically challenging with low or moderate yields while wasting valuable resources. Microbial production of terpenoids offers a sustainable and environment-friendly alternative starting from simple carbon sources and, frequently, safeguards high product specificity. Here, we provide an overview on employing recombinant bacteria and yeasts for heterologous de novo production of terpenoids. Currently, Escherichia coli and Saccharomyces cerevisiae are the two best-established production hosts for terpenoids. An increasing number of studies have been successful in engineering alternative microorganisms for terpenoid biosynthesis, which we intend to highlight in this review. Moreover, we discuss the specific engineering challenges as well as recent advances for microbial production of different classes of terpenoids. Rationalizing the current stages of development for different terpenoid production hosts as well as future prospects shall provide a valuable decision basis for the selection and engineering of the cell factory(ies) for industrial production of terpenoid target molecules.

The isoprenoid alcohol pathway, a synthetic route for isoprenoid biosynthesis

The more than 50,000 isoprenoids found in nature are all derived from the 5-carbon diphosphates isopentenyl pyrophosphate (IPP) and dimethylallyl pyrophosphate (DMAPP). Natively, IPP and DMAPP are generated by the mevalonate (MVA) and 2-C-methyl-d-erythritol-4-phosphate (MEP) pathways, which have been engineered to produce compounds with numerous applications. However, as these pathways are inherently constrained by carbon, energy inefficiencies, and their roles in native metabolism, engineering for isoprenoid biosynthesis at high flux, titer, and yield remains a challenge. To overcome these limitations, here we develop an alternative synthetic pathway termed the isoprenoid alcohol (IPA) pathway that centers around the synthesis and subsequent phosphorylation of IPAs. We first established a lower IPA pathway for the conversion of IPAs to isoprenoid pyrophosphate intermediates that enabled the production of greater than 2 g/L geraniol from prenol as well as limonene, farnesol, diaponeurosporene, and lycopene. We then designed upper IPA pathways for the generation of (iso)prenol from central carbon metabolites with the development of a route to prenol enabling its synthesis at more than 2 g/L. Using prenol as the linking intermediate further facilitated an integrated IPA pathway that resulted in the production of nearly 0.6 g/L total monoterpenoids from glycerol as the sole carbon source. The IPA pathway provides an alternative route to isoprenoids that is more energy efficient than native pathways and can serve as a platform for targeting a repertoire of isoprenoid compounds with application as high-value pharmaceuticals, commodity chemicals, and fuels.

Cell-Free Metabolic Engineering: Recent Developments and Future Prospects

Due to the ongoing crises of fossil fuel depletion, climate change, and environmental pollution, microbial processes are increasingly considered as a potential alternative for cleaner and more efficient production of the diverse chemicals required for modern civilization. However, many issues, including low efficiency of raw material conversion and unintended release of genetically modified microorganisms into the environment, have limited the use of bioprocesses that rely on recombinant microorganisms. Cell-free metabolic engineering is emerging as a new approach that overcomes the limitations of existing cell-based systems. Instead of relying on metabolic processes carried out by living cells, cell-free metabolic engineering harnesses the metabolic activities of cell lysates in vitro. Such approaches offer several potential benefits, including operational simplicity, high conversion yield and productivity, and prevention of environmental release of microorganisms. In this article, we review the recent progress in this field and discuss the prospects of this technique as a next-generation bioconversion platform for the chemical industry.

Organic waste as a sustainable feedstock for platform chemicals

Biorefineries have been established since the 1980s for biofuel production, and there has been a switch lately from first to second generation feedstocks in order to avoid the food versus fuel dilemma. To a lesser extent, many opportunities have been investigated for producing chemicals from biomass using by-products of the present biorefineries, simple waste streams. Current facilities apply intensive pre-treatments to deal with single substrate types such as carbohydrates. However, most organic streams such as municipal solid waste or algal blooms present a high complexity and variable mixture of molecules, which makes specific compound production and separation difficult. Here we focus on flexible anaerobic fermentation and hydrothermal processes that can treat complex biomass as a whole to obtain a range of products within an integrated biorefinery concept.

Approaches to Computational Strain Design in the Multiomics Era

Modern omics analyses are able to effectively characterize the genetic, regulatory, and metabolic phenotypes of engineered microbes, yet designing genetic interventions to achieve a desired phenotype remains challenging. With recent developments in genetic engineering techniques, timelines associated with building and testing strain designs have been greatly reduced, allowing for the first time an efficient closed loop iteration between experiment and analysis. However, the scale and complexity associated with multi-omics datasets complicates manual biological reasoning about the mechanisms driving phenotypic changes. Computational techniques therefore form a critical part of the Design-Build-Test-Learn (DBTL) cycle in metabolic engineering. Traditional statistical approaches can reduce the dimensionality of these datasets and identify common motifs among high-performing strains. While successful in many studies, these methods do not take full advantage of known connections between genes, proteins, and metabolic networks. There is therefore a growing interest in model-aided design, in which modeling frameworks from systems biology are used to integrate experimental data and generate effective and non-intuitive design predictions. In this mini-review, we discuss recent progress and challenges in this field. In particular, we compare methods augmenting flux balance analysis with additional constraints from fluxomic, genomic, and metabolomic datasets and methods employing kinetic representations of individual metabolic reactions, and machine learning. We conclude with a discussion of potential future directions for improving strain design predictions in the omics era and remaining experimental and computational hurdles.

Short term atmospheric pressure cold plasma treatment: A novel strategy for enhancing the substrate utilization in a thermophile, Geobacillus sp. strain WSUCF1

The aim of this study was to investigate the effect of atmospheric pressure cold plasma on the microbial substrate utilization and biomass yield in a thermophilic strain. Geobacillus sp. strain WSUCF1, a thermophile capable of producing cellulolytic enzymes with higher activity was used for this investigation. Treatment with cold plasma for 4 min increased the rates of glucose utilization by 74% and biomass yield by 60% when compared with the control. WSUCF1 treated with plasma also displayed enhanced biofilm formation. This study for the first time, reports the use of cold plasma for enhancing the substrate utilization and biofilm formation in a thermophile.

Engineering Strategies in Microorganisms for the Enhanced Production of Squalene: Advances, Challenges and Opportunities

The triterpene squalene is a natural compound that has demonstrated an extraordinary diversity of uses in pharmaceutical, nutraceutical, and personal care industries. Emboldened by this range of uses, novel applications that can gain profit from the benefits of squalene as an additive or supplement are expanding, resulting in its increasing demand. Ever since its discovery, the primary source has been the deep-sea shark liver, although recent declines in their populations and justified animal conservation and protection regulations have encouraged researchers to identify a novel route for squalene biosynthesis. This renewed scientific interest has profited from immense developments in synthetic biology, which now allows fine-tuning of a wider range of plants, fungi, and microorganisms for improved squalene production. There are numerous naturally squalene producing species and strains; although they generally do not make commercially viable yields as primary shark liver sources can deliver. The recent advances made toward improving squalene output from natural and engineered species have inspired this review. Accordingly, it will cover in-depth knowledge offered by the studies of the natural sources, and various engineering-based strategies that have been used to drive the improvements in the pathways toward large-scale production. The wide uses of squalene are also discussed, including the notable developments in anti-cancer applications and in augmenting influenza vaccines for greater efficacy.

Recent trends in integrated bioprocesses: aiding and expanding microbial biofuel/biochemical production

Microbial biosynthesis of fuels and chemicals represents a promising route for their renewable production. Product toxicity, however, represents a common challenge limiting the efficacy of this approach. Integrated bioprocesses incorporating in situ product separation are poised to help address this intrinsic problem, but suffer their own unique shortcomings. To improve and expand the utility of this versatile bioprocessing strategy, recent innovations have focused on developing more effective separation materials and novel process configurations, as well as adapting designs to accommodate semi-continuous modes of operation. As a result, integrated bioprocesses are finding new applications to aid the biosynthesis of an ever-growing list of bioproducts. Emerging applications, meanwhile, are exploring the further expansion of such designs to interface microbial and chemical catalysts, leading to new and versatile routes for the one-pot synthesis of an even greater diversity of renewable products.

Genomic and transcriptomic analysis of a coniferyl aldehyde-resistant Saccharomyces cerevisiae strain obtained by evolutionary engineering

Phenolic inhibitors in lignocellulosic hydrolysates interfere with the performance of fermenting microorganisms. Among these, coniferyl aldehyde is one of the most toxic inhibitors. In this study, genetically stable Saccharomyces cerevisiae mutants with high coniferyl aldehyde resistance were successfully obtained for the first time by using an evolutionary engineering strategy, based on the systematic application of increasing coniferyl aldehyde stress in batch cultures. Among the selected coniferyl aldehyde-resistant mutants, the highly resistant strain called BH13 was also cross-resistant to other phenolic inhibitors, vanillin, ferulic acid and 4-hydroxybenzaldehyde. In the presence of 1.2 mM coniferyl aldehyde stress, BH13 had a significantly reduced lag phase, which was less than 3 h and only about 25% of that of the reference strain and converted coniferyl aldehyde faster. Additionally, there was no reduction in its growth rate, either. Comparative transcriptomic analysis of a highly coniferyl aldehyde-resistant mutant revealed upregulation of the genes involved in energy pathways, response to oxidative stress and oxidoreductase activity in the mutant strain BH13, already under non-stress conditions. Transcripts associated with pleiotropic drug resistance were also identified as upregulated. Genome re-sequencing data generally supported transcriptomic results and identified gene targets that may have a potential role in coniferyl aldehyde resistance.

Engineering Robust Production Microbes for Large-Scale Cultivation

Systems biology and synthetic biology are increasingly used to examine and modulate complex biological systems. As such, many issues arising during scaling-up microbial production processes can be addressed using these approaches. We review differences between laboratory-scale cultures and larger-scale processes to provide a perspective on those strain characteristics that are especially important during scaling. Systems biology has been used to examine a range of microbial systems for their response in bioreactors to fluctuations in nutrients, dissolved gases, and other stresses. Synthetic biology has been used both to assess and modulate strain response, and to engineer strains to improve production. We discuss these approaches and tools in the context of their use in engineering robust microbes for applications in large-scale production.

Carboxylation of Hydroxyaromatic Compounds with HCO3− by Enzyme Catalysis: Recent Advances Open the Perspective for Valorization of Lignin-Derived Aromatics

This review focuses on recent advances in the field of enzymatic carboxylation reactions of hydroxyaromatic compounds using HCO3− (as a CO2 source) to produce hydroxybenzoic and other phenolic acids in mild conditions with high selectivity and moderate to excellent yield. Nature offers an extensive portfolio of enzymes catalysing reversible decarboxylation of hydroxyaromatic acids, whose equilibrium can be pushed towards the side of the carboxylated products. Extensive structural and mutagenesis studies have allowed recent advances in the understanding of the reaction mechanism of decarboxylase enzymes, ultimately enabling an improved yield and expansion of the scope of the reaction. The topic is of particular relevance today as the scope of the carboxylation reactions can be extended to include lignin-related compounds in view of developing lignin biorefinery technology.

Genome-Scale 13C Fluxomics Modeling for Metabolic Engineering of Saccharomyces cerevisiae

Synthetic biology is a rapidly developing field that pursues the application of engineering principles and development approaches to biological engineering. Synthetic biology is poised to change the way biology is practiced, and has important practical applications: for example, building genetically engineered organisms to produce biofuels, medicines, and other chemicals. Traditionally, synthetic biology has focused on manipulating a few genes (e.g., in a single pathway or genetic circuit), but its combination with systems biology holds the promise of creating new cellular architectures and constructing complex biological systems from the ground up. Enabling this merge of synthetic and systems biology will require greater predictive capability for modeling the behavior of cellular systems, and more comprehensive data sets for building and calibrating these models. The so-called "-omics" data sets can now be generated via high throughput techniques in the form of genomic, proteomic, transcriptomic, and metabolomic information on the engineered biological system. Of particular interest with respect to the engineering of microbes capable of producing biofuels and other chemicals economically and at scale are metabolomic datasets, and their insights into intracellular metabolic fluxes. Metabolic fluxes provide a rapid and easy to understand picture of how carbon and energy flow throughout the cell. Here, we present a detailed guide to performing metabolic flux analysis and modeling using the open source JBEI Quantitative Metabolic Modeling (jQMM) library. This library allows the user to transform metabolomics data in the form of isotope labeling data from a ¹³C labeling experiment into a determination of cellular fluxes that can be used to develop genetic engineering strategies for metabolic engineering.The jQMM library presents a complete toolbox for performing a range of different tasks of interest in metabolic engineering. Various different types of flux analysis and modeling can be performed such as flux balance analysis, ¹³C metabolic flux analysis, and two-scale ¹³C metabolic flux analysis (2S-¹³C MFA). 2S-¹³C MFA is a novel method that determines genome-scale fluxes without the need of every single carbon transition in the metabolic network. In addition to several other capabilities, the jQMM library can make model based predictions for how various genetic engineering strategies can be incorporated toward bioengineering goals: it can predict the effects of reaction knockouts on metabolism using both the MoMA and ROOM methodologies. In this chapter, we will illustrate the use of the jQMM library through a step-by-step demonstration of flux determination and knockout prediction in a complex eukaryotic model organism: Saccharomyces cerevisiae (S. cerevisiae). Included with this chapter is a digital Jupyter Notebook file that provides a computable appendix showing a self-contained example of jQMM usage, which can be changed to fit the user's specific needs. As an open source software project, users can modify and extend the code base to make improvements at will, allowing them to share their development work and contribute back to the jQMM modeling community.

Advancement of Metabolic Engineering Assisted by Synthetic Biology

Synthetic biology has undergone dramatic advancements for over a decade, during which it has expanded our understanding on the systems of life and opened new avenues for microbial engineering. Many biotechnological and computational methods have been developed for the construction of synthetic systems. Achievements in synthetic biology have been widely adopted in metabolic engineering, a field aimed at engineering micro-organisms to produce substances of interest. However, the engineering of metabolic systems requires dynamic redistribution of cellular resources, the creation of novel metabolic pathways, and optimal regulation of the pathways to achieve higher production titers. Thus, the design principles and tools developed in synthetic biology have been employed to create novel and flexible metabolic pathways and to optimize metabolic fluxes to increase the cells’ capability to act as production factories. In this review, we introduce synthetic biology tools and their applications to microbial cell factory constructions.

Identification of growth-coupled production strains considering protein costs and kinetic variability

Conversion of renewable biomass to useful molecules in microbial cell factories can be approached in a rational and systematic manner using constraint-based reconstruction and analysis. Filtering for high confidence in silico designs is critical because in vivo construction and testing of strains is expensive and time consuming. As such, a workflow was devised to analyze the robustness of growth-coupled production when considering the biosynthetic costs of the proteome and variability in enzyme kinetic parameters using a genome-scale model of metabolism and gene expression (ME-model). A collection of 2632 unfiltered knockout designs in Escherichia coli was evaluated by the workflow. A ME-model was used in the workflow to test the designs' growth-coupled production in addition to a less complex genome-scale metabolic model (M-model). The workflow identified 634 M-model growth-coupled designs which met the filtering criteria and 42 robust designs, which met growth-coupled production criteria using both M and ME-models. Knockouts were found to follow a pattern of controlling intermediate metabolite consumption such as pyruvate consumption and high flux subsystems such as glycolysis. Kinetic parameter sampling using the ME-model revealed how enzyme efficiency and pathway tradeoffs can affect growth-coupled production phenotypes.

A Post-translational Metabolic Switch Enables Complete Decoupling of Bacterial Growth from Biopolymer Production in Engineered Escherichia coli

Most of the current methods for controlling the formation rate of a key protein or enzyme in cell factories rely on the manipulation of target genes within the pathway. In this article, we present a novel synthetic system for post-translational regulation of protein levels, FENIX, which provides both independent control of the steady-state protein level and inducible accumulation of target proteins. The FENIX device is based on the constitutive, proteasome-dependent degradation of the target polypeptide by tagging with a short synthetic, hybrid NIa/SsrA amino acid sequence in the C-terminal domain. Protein production is triggered via addition of an orthogonal inducer ( i.e., 3-methylbenzoate) to the culture medium. The system was benchmarked in Escherichia coli by tagging two fluorescent proteins (GFP and mCherry), and further exploited to completely uncouple poly(3-hydroxybutyrate) (PHB) accumulation from bacterial growth. By tagging PhaA (3-ketoacyl-CoA thiolase, first step of the route), a dynamic metabolic switch at the acetyl-coenzyme A node was established in such a way that this metabolic precursor could be effectively redirected into PHB formation upon activation of the system. The engineered E. coli strain reached a very high specific rate of PHB accumulation (0.4 h^-1) with a polymer content of ca. 72% (w/w) in glucose cultures in a growth-independent mode. Thus, FENIX enables dynamic control of metabolic fluxes in bacterial cell factories by establishing post-translational synthetic switches in the pathway of interest.

Efficient production of 3-hydroxypropionate from fatty acids feedstock in Escherichia coli

The production of chemicals from renewable biomass resources is usually limited by factors including high-cost processes and low efficiency of biosynthetic pathways. Fatty acids (FAs) are an ideal alternative biomass. Their advantages include high-efficiently producing acetyl-CoA and reducing power, coupling chemical production with CO₂ fixation, and the fact that they are readily obtained from inexpensive feedstocks. The important platform chemical 3-hydroxypropionate (3HP) can be produced from FAs as the feedstock with a theoretical yield of 2.49 g/g, much higher than the theoretical yield from other feedstocks. In this study, we first systematically analyzed the limiting factors in FA-utilization pathways in Escherichia coli. Then, we optimized FA utilization in Escherichia coli by using a combination of metabolic engineering and optimization of fermentation conditions. The 3HP biosynthesis module was introduced into a FA-utilizing strain, and the flux balance was finely optimized to maximize 3HP production. The resulting strain was able to produce 3HP from FAs with a yield of 1.56 g/g, and was able to produce 3HP to a concentration of 52 g/L from FAs in a 5-L fermentation process. The strain also could produce 3HP from various type of FAs feedstock including gutter oil. This is the first report of a technique for the efficient production of the platform chemical 3HP from FAs.

Systems and Synthetic Biology Approaches to Engineer Fungi for Fine Chemical Production

Since the advent of systems and synthetic biology, many studies have sought to harness microbes as cell factories through genetic and metabolic engineering approaches. Yeast and filamentous fungi have been successfully harnessed to produce fine and high value-added chemical products. In this review, we present some of the most promising advances from recent years in the use of fungi for this purpose, focusing on the manipulation of fungal strains using systems and synthetic biology tools to improve metabolic flow and the flow of secondary metabolites by pathway redesign. We also review the roles of bioinformatics analysis and predictions in synthetic circuits, highlighting in silico systemic approaches to improve the efficiency of synthetic modules.

A Synthetic Microbial Operational Amplifier

Synthetic biology has created oscillators, latches, logic gates, logarithmically linear circuits, and load drivers that have electronic analogs in living cells. The ubiquitous operational amplifier, which allows circuits to operate robustly and precisely has not been built with biomolecular parts. As in electronics, a biological operational-amplifier could greatly improve the predictability of circuits despite noise and variability, a problem that all cellular circuits face. Here, we show how to create a synthetic three-stage inducer-input operational amplifier with a fast CRISPR-based differential-input push-pull stage, a slow transcription-and-translation amplification stage, and a fast-enzymatic output stage. Our "Bio-OpAmp" uses only 5 proteins including dCas9. It expands the toolkit of fundamental analog circuits in synthetic biology and provides a simple circuit motif for robust and precise molecular homeostasis.