Iterative algorithm-guided design of massive strain libraries, applied to itaconic acid production in yeast

In silico analysis of design of experiment methods for metabolic pathway optimization

Microbial cell factories allow the production of chemicals presenting an alternative to traditional fossil fuel-dependent production. However, finding the optimal expression of production pathway genes is crucial for the development of efficient production strains. Unlike sequential experimentation, combinatorial optimization captures the relationships between pathway genes and production, albeit at the cost of conducting multiple experiments. Fractional factorial designs followed by linear modeling and statistical analysis reduce the experimental workload while maximizing the information gained during experimentation. Although tools to perform and analyze these designs are available, guidelines for selecting appropriate factorial designs for pathway optimization are missing. In this study, we leverage a kinetic model of a seven-genes pathway to simulate the performance of a full factorial strain library. We compare this approach to resolution V, IV, III, and Plackett Burman (PB) designs. Additionally, we evaluate the performance of these designs as training sets for a random forest algorithm aimed at identifying best-producing strains. Evaluating the robustness of these designs to noise and missing data, traits inherent to biological datasets, we find that while resolution V designs capture most information present in full factorial data, they necessitate the construction of a large number of strains. On the other hand, resolution III and PB designs fall short in identifying optimal strains and miss relevant information. Besides, given the small number of experiments required for the optimization of a pathway with seven genes, linear models outperform random forest. Consequently, we propose the use of resolution IV designs followed by linear modeling in Design-Build-Test-Learn (DBTL) cycles targeting the screening of multiple factors. These designs enable the identification of optimal strains and provide valuable guidance for subsequent optimization cycles.

An Eclectic Review on Dicarboxylic Acid Production Through Yeast Cell Factories and Its Industrial Prominence

Dicarboxylic acid (DCA) is a multifaceted chemical intermediate, recoursed to produce many industrially important products such as adhesives, plasticizers, lubricants, polymers, etc. To bypass the shortcomings of the chemical methods of synthesis of DCA and to reduce fossil fuel footprints, bio-based synthesis is gaining attention. In pursuit of an eco-friendly sustainable alternative method of DCA production, microbial cell factories, and renewable organic resources are gaining popularity. Among the plethora of microbial communities, yeast is being favored industrially compared to bacterial fermentation due to its hyperosmotic and low pH tolerance and flexibility for gene manipulations. By application of rapidly evolving genetic manipulation techniques, the bio-based DCA production could be made more precise and economical. To bridge the gap between supply and demand of DCA, many strategies are employed to improve the fermentation. This review briefly outlines the advancements in DCA production using yeast cell factories with the exemplification of strain improvement strategies.

Machine Learning-Guided Optimization of p-Coumaric Acid Production in Yeast

Industrial biotechnology uses Design-Build-Test-Learn (DBTL) cycles to accelerate the development of microbial cell factories, required for the transition to a biobased economy. To use them effectively, appropriate connections between the phases of the cycle are crucial. Using p-coumaric acid (pCA) production in Saccharomyces cerevisiae as a case study, we propose the use of one-pot library generation, random screening, targeted sequencing, and machine learning (ML) as links during DBTL cycles. We showed that the robustness and flexibility of the ML models strongly enable pathway optimization and propose feature importance and Shapley additive explanation values as a guide to expand the design space of original libraries. This approach allowed a 68% increased production of pCA within two DBTL cycles, leading to a 0.52 g/L titer and a 0.03 g/g yield on glucose.

Combinatorial optimization of pathway, process and media for the production of p-coumaric acid by Saccharomyces cerevisiae

Microbial cell factories are instrumental in transitioning towards a sustainable bio-based economy, offering alternatives to conventional chemical processes. However, fulfilling their potential requires simultaneous screening for optimal media composition, process and genetic factors, acknowledging the complex interplay between the organism's genotype and its environment. This study employs statistical design of experiments to systematically explore these relationships and optimize the production of p-coumaric acid (pCA) in Saccharomyces cerevisiae. Two rounds of fractional factorial designs were used to identify factors with a significant effect on pCA production, which resulted in a 168-fold variation in pCA titre. Moreover, a significant interaction between the culture temperature and expression of ARO4 highlighted the importance of simultaneous process and strain optimization. The presented approach leverages the strengths of experimental design and statistical analysis and could be systematically applied during strain and bioprocess design efforts to unlock the full potential of microbial cell factories.

Enabling pathway design by multiplex experimentation and machine learning

The remarkable metabolic diversity observed in nature has provided a foundation for sustainable production of a wide array of valuable molecules. However, transferring the biosynthetic pathway to the desired host often runs into inherent failures that arise from intermediate accumulation and reduced flux resulting from competing pathways within the host cell. Moreover, the conventional trial and error methods utilized in pathway optimization struggle to fully grasp the intricacies of installed pathways, leading to time-consuming and labor-intensive experiments, ultimately resulting in suboptimal yields. Considering these obstacles, there is a pressing need to explore the enzyme expression landscape and identify the optimal pathway configuration for enhanced production of molecules. This review delves into recent advancements in pathway engineering, with a focus on multiplex experimentation and machine learning techniques. These approaches play a pivotal role in overcoming the limitations of traditional methods, enabling exploration of a broader design space and increasing the likelihood of discovering optimal pathway configurations for enhanced production of molecules. We discuss several tools and strategies for pathway design, construction, and optimization for sustainable and cost-effective microbial production of molecules ranging from bulk to fine chemicals. We also highlight major successes in academia and industry through compelling case studies.

A Rapid Antibody Enhancement Platform in Saccharomyces cerevisiae Using an Improved, Diversifying CRISPR Base Editor

The yeast Saccharomyces cerevisiae is commonly used to interrogate and screen protein variants and to perform directed evolution studies to develop proteins with enhanced features. While several techniques have been described that help enable the use of yeast for directed evolution, there remains a need to increase their speed and ease of use. Here we present yDBE, a yeast diversifying base editor that functions in vivo and employs a CRISPR-dCas9-directed cytidine deaminase base editor to diversify DNA in a targeted, rapid, and high-breadth manner. To develop yDBE, we enhanced the mutation rate of an initial base editor by employing improved deaminase variants and characterizing several scaffolded guide constructs. We then demonstrate the ability of the yDBE platform to improve the affinity of a displayed antibody scFv, rapidly generating diversified libraries and isolating improved binders via cell sorting. By performing high-throughput sequencing analysis of the high-activity yDBE, we show that it enables a mutation rate of 2.13 × 10-4 substitutions/bp/generation over a window of 100 bp. As yDBE functions entirely in vivo and can be easily programmed to diversify nearly any such window of DNA, we posit that it can be a powerful tool for facilitating a variety of directed evolution experiments.

Simulated Design-Build-Test-Learn Cycles for Consistent Comparison of Machine Learning Methods in Metabolic Engineering

Combinatorial pathway optimization is an important tool in metabolic flux optimization. Simultaneous optimization of a large number of pathway genes often leads to combinatorial explosions. Strain optimization is therefore often performed using iterative design-build-test-learn (DBTL) cycles. The aim of these cycles is to develop a product strain iteratively, every time incorporating learning from the previous cycle. Machine learning methods provide a potentially powerful tool to learn from data and propose new designs for the next DBTL cycle. However, due to the lack of a framework for consistently testing the performance of machine learning methods over multiple DBTL cycles, evaluating the effectiveness of these methods remains a challenge. In this work, we propose a mechanistic kinetic model-based framework to test and optimize machine learning for iterative combinatorial pathway optimization. Using this framework, we show that gradient boosting and random forest models outperform the other tested methods in the low-data regime. We demonstrate that these methods are robust for training set biases and experimental noise. Finally, we introduce an algorithm for recommending new designs using machine learning model predictions. We show that when the number of strains to be built is limited, starting with a large initial DBTL cycle is favorable over building the same number of strains for every cycle.

Design of Four Small-Molecule-Inducible Systems in the Yeast Chromosome, Applied to Optimize Terpene Biosynthesis

The optimization of cellular functions often requires the balancing of gene expression, but the physical construction and screening of alternative designs are costly and time-consuming. Here, we construct a strain of Saccharomyces cerevisiae that contains a "sensor array" containing bacterial regulators that respond to four small-molecule inducers (vanillic acid, xylose, aTc, IPTG). Four promoters can be independently controlled with low background and a 40- to 5000-fold dynamic range. These systems can be used to study the impact of changing the level and timing of gene expression without requiring the construction of multiple strains. We apply this approach to the optimization of a four-gene heterologous pathway to the terpene linalool, which is a flavor and precursor to energetic materials. Using this approach, we identify bottlenecks in the metabolic pathway. This work can aid the rapid automated strain development of yeasts for the bio-manufacturing of diverse products, including chemicals, materials, fuels, and food ingredients.

Rational search of genetic design space for a heterologous terpene metabolic pathway in Streptomyces

Modern tools in DNA synthesis and assembly give genetic engineers control over the nucleotide-level design of complex, multi-gene systems. Systematic approaches to explore genetic design space and optimize the performance of genetic constructs are lacking. Here we explore the application of a five-level Plackett-Burman fractional factorial design to improve the titer of a heterologous terpene biosynthetic pathway in Streptomyces. A library of 125 engineered gene clusters encoding the production of diterpenoid ent-atiserenoic acid (eAA) via the methylerythritol phosphate pathway was constructed and introduced into Streptomyces albidoflavus J1047 for heterologous expression. The eAA production titer varied within the library by over two orders of magnitude and host strains showed unexpected and reproducible colony morphology phenotypes. Analysis of Plackett-Burman design identified expression of dxs, the gene encoding the first and the flux-controlling enzyme, having the strongest impact on eAA titer, but with a counter-intuitive negative correlation between dxs expression and eAA production. Finally, simulation modeling was performed to determine how several plausible sources of experimental error/noise and non-linearity impact the utility of Plackett-Burman analyses.

Alleviating glucose repression and enhancing respiratory capacity to increase itaconic acid production

The Crabtree effect products ethanol and acetic acid can be used for itaconic acid (IA) production in Saccharomyces cerevisiae. However, both the IA synthesis and oxidative phosphorylation pathways were hampered by glucose repression when glucose was used as the substrate. This study aimed to improve IA titer by increasing gene expressions related to glucose derepression without impairing yeast growth on glucose. Engineering the acetyl-CoA synthesis pathway increased the titer of IA to 257 mg/L in a urea-based medium. Instead of entire pathway overexpression, we found that some signaling pathways regulating glucose repression were effective targets to improve IA production and respiratory capacity. As a consequence of the reduced inhibition, IA titer was further increased by knocking out a negative regulator of the mitochondrial retrograde signaling MKS1. SNF1/MIG1 signaling was disturbed by deleting the hexokinase HXK2 or an endoplasmic reticulum membrane protein GSF2. The shaking results showed that XYY286 (BY4741, HO::cadA, Y::Dz.ada, 208a::Mt.acs, Δhxk2, pRS415-cadA, pRS423-aac2) accumulated 535 mg/L IA in 168 h in the YSCGLU medium. qRT-PCR results verified that deletion of MKS1 or HXK2 upregulated the gene expressions of the IA synthesis and respiratory pathways during the growth on glucose.

Metabolic engineering of Schizosaccharomyces pombe for itaconic acid production

The economical production of value-added chemicals from renewable biomass is a promising aspect of producing a sustainable economy. Itaconic acid (IA) is a high value-added compound that is expected to be an alternative to petroleum-based chemicals. In this study, we developed a metabolic engineering strategy for the large-scale production of IA from glucose using the fission yeast Schizosaccharomyces pombe. Heterologous expression of the cis-aconitic acid decarboxylase (CAD) gene from Aspergillus terreus, which encodes cis-aconitate decarboxylase in the cytosol, led to the production of 0.132 g/L of IA. We demonstrated that mitochondrial localization of CAD enhanced the production of IA. To prevent the leakage of carbon flux from the TCA cycle, we generated a strain in which the endogenous malate exporter, citrate lyase, and citrate transporter genes were disrupted. A titer of 1.110 g/L of IA was obtained from a culture of this strain started with 50 g/L of glucose. By culturing the multiple mutant strain at increased cell density, we succeeded in enhancing the IA production to 1.555 g/L. The metabolic engineering strategies presented in this study have the potential to improve the titer of the biosynthesis of derivatives of intermediates of the TCA cycle.

Designing Microbial Cell Factories for the Production of Chemicals

The sustainable production of chemicals from renewable, nonedible biomass has emerged as an essential alternative to address pressing environmental issues arising from our heavy dependence on fossil resources. Microbial cell factories are engineered microorganisms harboring biosynthetic pathways streamlined to produce chemicals of interests from renewable carbon sources. The biosynthetic pathways for the production of chemicals can be defined into three categories with reference to the microbial host selected for engineering: native-existing pathways, nonnative-existing pathways, and nonnative-created pathways. Recent trends in leveraging native-existing pathways, discovering nonnative-existing pathways, and designing de novo pathways (as nonnative-created pathways) are discussed in this Perspective. We highlight key approaches and successful case studies that exemplify these concepts. Once these pathways are designed and constructed in the microbial cell factory, systems metabolic engineering strategies can be used to improve the performance of the strain to meet industrial production standards. In the second part of the Perspective, current trends in design tools and strategies for systems metabolic engineering are discussed with an eye toward the future. Finally, we survey current and future challenges that need to be addressed to advance microbial cell factories for the sustainable production of chemicals.

Synergistic effects on itaconic acid production in engineered Aspergillus niger expressing the two distinct biosynthesis clusters from Aspergillus terreus and Ustilago maydis

BACKGROUND

Itaconic acid (IA) is a versatile platform chemical widely used for the synthesis of various polymers and current methods for IA production based on Aspergillus terreus fermentation are limited in terms of process efficiency and productivity. To construct more efficient IA production strains, A. niger was used as a chassis for engineering IA production by assembling the key components of IA biosynthesis pathways from both A. terreus and Ustilago maydis.

RESULTS

Recombinant A. niger S1596 overexpressing the A. terreus IA biosynthesis genes cadA, mttA, mfsA produced IA of 4.32 g/L, while A. niger S2120 overexpressing the U. maydis IA gene cluster adi1, tad1, mtt1, itp1 achieved IA of 3.02 g/L. Integration of the two IA production pathways led to the construction of A. niger S2083 with IA titers of 5.58 g/L. Increasing cadA copy number in strain S2083 created strain S2209 with titers of 7.99 g/L and deleting ictA to block IA degradation in S2209 created strain S2288 with IA titers of 8.70 g/L. Overexpressing acoA to enhance the supply of IA precursor in strain S2288 generated strain S2444 with IA titers of 9.08 g/L in shake flask.

CONCLUSION

Recombinant A. niger overexpressing the U. maydis IA biosynthesis pathway was capable of IA accumulation. Combined expression of the two IA biosynthesis pathways from A. terreus and U. maydis in A. niger resulted in much higher IA titers. Furthermore, increasing cadA copy number, deleting ictA to block IA degradation and overexpressing acoA to enhance IA precursor supply all showed beneficial effects on IA accumulation.

Advances and trends in microbial production of polyhydroxyalkanoates and their building blocks

With the rapid development of synthetic biology, a variety of biopolymers can be obtained by recombinant microorganisms. Polyhydroxyalkanoates (PHA) is one of the most popular one with promising material properties, such as biodegradability and biocompatibility against the petrol-based plastics. This study reviews the recent studies focusing on the microbial synthesis of PHA, including chassis engineering, pathways engineering for various substrates utilization and PHA monomer synthesis, and PHA synthase modification. In particular, advances in metabolic engineering of dominant workhorses, for example Halomonas, Ralstonia eutropha, Escherichia coli and Pseudomonas, with outstanding PHA accumulation capability, were summarized and discussed, providing a full landscape of diverse PHA biosynthesis. Meanwhile, we also introduced the recent efforts focusing on structural analysis and mutagenesis of PHA synthase, which significantly determines the polymerization activity of varied monomer structures and PHA molecular weight. Besides, perspectives and solutions were thus proposed for achieving scale-up PHA of low cost with customized material property in the coming future.

A review on contemporary approaches in enhancing the innate lipid content of yeast cell

For the past few decades, industrialization has made a huge environmental hazard to the world with its waste. The approach of waste to wealth in the recent era has made many Eco-economical suggestions for the industries. The valuable products in biorefinery aspects of the eco-economical suggestions include; energy products, high-value drugs and novel materials. Bio-lipids are found to be the major influencing eco-economical products in the process. Production of bio-lipid from microbial sources has paved the way for future research on lipid-bioproducts. The yeast cell is a unique organism with a large unicellular structure capable of accumulating a high amount of lipids. It constitutes 90% of neutral lipids. Various strategies enhance the lipid profile of yeast cells: usage of oleaginous yeast, usage of low cost (or) alternative substrates, developing stress conditions in the growth medium, using genetically modified yeast, altering metabolic pathways of yeast and by using the symbiotic cultures of yeast with other microbes. The metabolic alterations of lipid pathways such as lipid biosynthesis, lipid elongation, lipid accumulation and lipid degradation have been a striking feature of research in lipid-based microbial work. The lipid-bioproducts have also made a strong footprint in the history of alternative energy products. It includes partial acyl glycerol, oleochemicals, phospholipids and biofuels. This report comprises the recent approaches carried out in the yeast cell for enhancing its lipid content. The limitations, challenges and future scope of individual strategies were also highlighted in this article.

Overcoming glutamate auxotrophy in Escherichia coli itaconate overproducer by the Weimberg pathway

Biosynthesis of itaconic acid occurs through decarboxylation of the TCA cycle intermediate cis-aconitate. Engineering of efficient itaconate producers often requires elimination of the highly active isocitrate dehydrogenase to conserve cis-aconitate, leading to 2-ketoglutarate auxotrophy in the producing strains. Supplementation of glutamate or complex protein hydrolysate then becomes necessary, often in large quantities, to support the high cell density desired during itaconate fermentation and adds to the production cost. Here, we present an alternative approach to overcome the glutamate auxotrophy in itaconate producers by synthetically introducing the Weimberg pathway from Burkholderia xenovorans for 2-ketoglutarate biosynthesis. Because of its independence from natural carbohydrate assimilation pathways in Escherichia coli, the Weimberg pathway is able to provide 2-ketoglutarate using xylose without compromising the carbon flux toward itaconate. With xylose concentration carefully tuned to minimize excess 2-ketoglutarate flux in the stationary phase, the final strain accumulated 20 g/L of itaconate in minimal medium from 18 g/L of xylose and 45 g/L of glycerol. Necessity of the recombinant Weimberg pathway for growth also allowed us to maintain multi-copy plasmids carrying in operon the itaconate-producing genes without addition of antibiotics. Use of the Weimberg pathway for growth restoration is applicable to other production systems with disrupted 2-ketoglutarate synthesis.

Curation Principles Derived from the Analysis of the SBOL iGEM Data Set

As an engineering endeavor, synthetic biology requires effective sharing of genetic design information that can be reused in the construction of new designs. While there are a number of large community repositories of design information, curation of this information has been limited. This in turn limits the ways in which design information can be put to use. The aim of this work was to improve this situation by creating a curated library of parts from the International Genetically Engineered Machines (iGEM) registry data set. To this end, an analysis of the Synthetic Biology Open Language (SBOL) version of the iGEM registry was carried out using four different approaches-simple statistics, SnapGene autoannotation, SYNBICT autoannotation, and expert analysis-the results of which are presented herein. Key challenges encountered include the use of free text, insufficient part provenance, part duplication, lack of part removal, and insufficient continuous curation. On the basis of these analyses, the focus has shifted from the creation of a curated iGEM part library to instead the extraction of a set of lessons, which are presented here. These lessons can be exploited to facilitate the creation and curation of other part libraries using a simpler and less labor intensive process.

The challenges and prospects of Escherichia coli as an organic acid production host under acid stress

OBJECTIVE

Organic acids have a wide range of applications and have attracted the attention of many industries, and their large-scale applications have led fermentation production to low-cost development. Among them, the microbial fermentation method, especially using Escherichia coli as the production host, has the advantages of fast growth and low energy consumption, and has gradually shown better advantages and prospects in organic acid fermentation production.

IMPORTANCE

However, when the opportunity comes, the acidified environment caused by the acid products accumulated during the fermentation process also challenges E. coli. The acid sensitivity of E. coli is a core problem that needs to be solved urgently. The addition of neutralizers in traditional operations led to the emergence of osmotic stress inadvertently, the addition of strong acid substances to recover products in the salt state not only increases production costs, but the discharged sewage is also harmful to the environment.

ELABORATION

This article summarizes the current status of the application of E. coli in the production of organic acids, and based on the impact of acid stress on the physiological state of cells and the impact of industrial production profits, put forward some new conjectures that can make up for the deficiencies in existing research and application.

IMPLICATION

At this point, the diversified transformation of E. coli has become a chassis microbe that is more suitable for industrial fermentation, enhancing industrial application value.

KEY POINTS

• E. coli is a potential host for high value-added organic acids production. • Classify the damage mechanism and coping strategies of E. coli when stimulated by acid molecules. • Multi-dimensional expansion tools are needed to create acid-resistant E. coli chassis.

Synthetic Biology Knowledge System

The Synthetic Biology Knowledge System (SBKS) is an instance of the SynBioHub repository that includes text and data information that has been mined from papers published in ACS Synthetic Biology. This paper describes the SBKS curation framework that is being developed to construct the knowledge stored in this repository. The text mining pipeline performs automatic annotation of the articles using natural language processing techniques to identify salient content such as key terms, relationships between terms, and main topics. The data mining pipeline performs automatic annotation of the sequences extracted from the supplemental documents with the genetic parts used in them. Together these two pipelines link genetic parts to papers describing the context in which they are used. Ultimately, SBKS will reduce the time necessary for synthetic biologists to find the information necessary to complete their designs.

Utilization of ethanol for itaconic acid biosynthesis by engineered Saccharomyces cerevisiae

In Saccharomyces cerevisiae, ethanol can serve as both a carbon source and NADH donor for the production of acetyl-CoA derivatives. Here we investigated the metabolic regulation of ethanol utilization for itaconic acid production by S. cerevisiae. To understand the interconnection between the TCA cycle and the glyoxylate pathway, mitochondrial membrane transporter proteins SFC1, YHM2, CTP1, DIC1, and MPC1 were knocked out and results showed that SFC1 functions as an important entrance of the glyoxylate pathway into the TCA cycle, and YHM2 is helpful to IA production but not the primary pathway for citric acid supply. To decrease the accumulation of acetic acid, the major ADP/ATP carrier of the mitochondrial inner membrane, AAC2, was upregulated and determined to accelerate ethanol utilization and itaconic acid production. RNA sequencing results showed that AAC2 overexpression enhanced IA titer by upregulating the ethanol-acetyl-CoA pathway and NADH oxidase in the mitochondrial membrane. RNA-seq analysis also suggested that aconitase ACO1 may be a rate-limiting step of IA production. However, the expression of exogenous aconitase didn't increase IA production but enhanced the rate of ethanol utilization and decreased cell growth.

A systematic framework for using membrane metrics for strain engineering

The cell membrane plays a central role in the fitness and performance of microbial cell factories and therefore it is an attractive engineering target. The goal of this work is to develop a systematic framework for identifying membrane features for use as engineering targets. The metrics that describe the composition of the membrane can be visualized as "knobs" that modulate various "outcomes", such as physical properties of the membrane and metabolic activity in the form of growth and productivity, with these relationships varying depending on the condition. We generated a set of strains with altered membrane lipid composition via expression of des, fabA and fabB and performed a rigorous characterization of these knobs and outcomes across several individual inhibitory conditions. Here, the knobs are the relative abundance of unsaturated lipids and lipids containing cyclic rings; the average lipid length, and the ratio of linear and non-linear lipids (L/nL ratio). The outcomes are membrane permeability, hydrophobicity, fluidity, and specific growth rate. This characterization identified significant correlations between knobs and outcomes that were specific to individual inhibitors, but also were significant across all tested conditions. For example, across all conditions, the L/nL ratio is positively correlated with the cell surface hydrophobicity, and the average lipid length is positively correlated with specific growth rate. A subsequent analysis of the data with the individual inhibitors identified pairs of lipid metrics and membrane properties that were predicted to impact cell growth in seven modeled scenarios with two or more inhibitors. The L/nL ratio and the membrane hydrophobicity were predicted to impact cell growth with the highest frequency. We experimentally validated this prediction in the combined condition of 42 °C, 2.5 mM furfural and 2% v/v ethanol in minimal media. Membrane hydrophobicity was confirmed to be a significant predictor of ethanol production. This work demonstrates that membrane physical properties can be used to predict the performance of biocatalysts in single and multiple inhibitory conditions, and possibly as an engineering target. In this manner, membrane properties can possibly be used as screening or selection metrics for library- or evolution-based strain engineering.

Engineered yeast genomes accurately assembled from pure and mixed samples

Yeast whole genome sequencing (WGS) lacks end-to-end workflows that identify genetic engineering. Here we present Prymetime, a tool that assembles yeast plasmids and chromosomes and annotates genetic engineering sequences. It is a hybrid workflow-it uses short and long reads as inputs to perform separate linear and circular assembly steps. This structure is necessary to accurately resolve genetic engineering sequences in plasmids and the genome. We show this by assembling diverse engineered yeasts, in some cases revealing unintended deletions and integrations. Furthermore, the resulting whole genomes are high quality, although the underlying assembly software does not consistently resolve highly repetitive genome features. Finally, we assemble plasmids and genome integrations from metagenomic sequencing, even with 1 engineered cell in 1000. This work is a blueprint for building WGS workflows and establishes WGS-based identification of yeast genetic engineering.

Statistical Design of Experiments for Synthetic Biology

The design and optimization of biological systems is an inherently complex undertaking that requires careful balancing of myriad synergistic and antagonistic variables. However, despite this complexity, much synthetic biology research is predicated on One Factor at A Time (OFAT) experimentation; the genetic and environmental variables affecting the activity of a system of interest are sequentially altered while all other variables are held constant. Beyond being time and resource intensive, OFAT experimentation crucially ignores the effect of interactions between factors. Given the ubiquity of interacting genetic and environmental factors in biology this failure to account for interaction effects in OFAT experimentation can result in the development of suboptimal systems. To address these limitations, an increasing number of studies have turned to Design of Experiments (DoE), a suite of methods that enable efficient, systematic exploration and exploitation of complex design spaces. This review provides an overview of DoE for synthetic biologists. Key concepts and commonly used experimental designs are introduced, and we discuss the advantages of DoE as compared to OFAT experimentation. We dissect the applicability of DoE in the context of synthetic biology and review studies which have successfully employed these methods, illustrating the potential of statistical experimental design to guide the design, characterization, and optimization of biological protocols, pathways, and processes.

CRISPR-mediated multigene integration enables Shikimate pathway refactoring for enhanced 2-phenylethanol biosynthesis in Kluyveromyces marxianus

BACKGROUND

2-phenylethanol (2-PE) is a rose-scented flavor and fragrance compound that is used in food, beverages, and personal care products. Compatibility with gasoline also makes it a potential biofuel or fuel additive. A biochemical process converting glucose or other fermentable sugars to 2-PE can potentially provide a more sustainable and economical production route than current methods that use chemical synthesis and/or isolation from plant material.

RESULTS

We work toward this goal by engineering the Shikimate and Ehrlich pathways in the stress-tolerant yeast Kluyveromyces marxianus. First, we develop a multigene integration tool that uses CRISPR-Cas9 induced breaks on the genome as a selection for the one-step integration of an insert that encodes one, two, or three gene expression cassettes. Integration of a 5-kbp insert containing three overexpression cassettes successfully occurs with an efficiency of 51 ± 9% at the ABZ1 locus and was used to create a library of K. marxianus CBS 6556 strains with refactored Shikimate pathway genes. The 3³-factorial library includes all combinations of KmARO4, KmARO7, and KmPHA2, each driven by three different promoters that span a wide expression range. Analysis of the refactored pathway library reveals that high expression of the tyrosine-deregulated KmARO4^K221L and native KmPHA2, with the medium expression of feedback insensitive KmARO7^G141S, results in the highest increase in 2-PE biosynthesis, producing 684 ± 73 mg/L. Ehrlich pathway engineering by overexpression of KmARO10 and disruption of KmEAT1 further increases 2-PE production to 766 ± 6 mg/L. The best strain achieves 1943 ± 63 mg/L 2-PE after 120 h fed-batch operation in shake flask cultures.

CONCLUSIONS

The CRISPR-mediated multigene integration system expands the genome-editing toolset for K. marxianus, a promising multi-stress tolerant host for the biosynthesis of 2-PE and other aromatic compounds derived from the Shikimate pathway.

Combinatorial metabolic pathway assembly approaches and toolkits for modular assembly

Synthetic Biology is a rapidly growing interdisciplinary field that is primarily built upon foundational advances in molecular biology combined with engineering design principles such as modularity and interoperability. The field considers living systems as programmable at the genetic level and has been defined by the development of new platform technologies and methodological advances. A key concept driving the field is the Design-Build-Test-Learn cycle which provides a systematic framework for building new biological systems. One major application area for synthetic biology is biosynthetic pathway engineering that requires the modular assembly of different genetic regulatory elements and biosynthetic enzymes. In this review we provide an overview of modular DNA assembly and describe and compare the plethora of in vitro and in vivo assembly methods for combinatorial pathway engineering. Considerations for part design and methods for enzyme balancing are also presented, and we briefly discuss alternatives to intracellular pathway assembly including microbial consortia and cell-free systems for biosynthesis. Finally, we describe computational tools and automation for pathway design and assembly and argue that a deeper understanding of the many different variables of genetic design, pathway regulation and cellular metabolism will allow more predictive pathway design and engineering.

Metabolic Engineering of Saccharomyces cerevisiae for Rosmarinic Acid Production

Rosmarinic acid is a hydroxycinnamic acid ester commonly found in the Boraginaceae and Lamiaceae plant families. It exhibits various biological activities, including antioxidant, anti-inflammatory, antibacterial, antiallergic, and antiviral properties. Rosmarinic acid is used as a food and cosmetic ingredient, and several pharmaceutical applications have been suggested as well. Rosmarinic acid is currently produced by extraction from plants or chemical synthesis; however, due to limited availability of the plant sources and the complexity of the chemical synthesis method, there is an increasing interest in producing this compound by microbial fermentation. In this study, we aimed to produce rosmarinic acid by engineered baker's yeast Saccharomyces cerevisiae. Multiple biosynthetic pathway variants, carrying only plant genes or a combination of plant and Escherichia coli genes, were implemented using a full factorial design of experiment. Through analysis of variances, the effect of each enzyme variant (factors), together with possible interactions between these factors, was assessed. The best pathway variant produced 2.95 ± 0.08 mg/L rosmarinic acid in mineral medium with glucose as the sole carbon source. Increasing the copy number of rosmarinic acid biosynthetic genes increased the titer to 5.93 ± 0.06 mg/L. The study shows the feasibility of producing rosmarinic acid by yeast fermentation.

Yeast Intracellular Staining (yICS): Enabling High-Throughput, Quantitative Detection of Intracellular Proteins via Flow Cytometry for Pathway Engineering

The complexities of pathway engineering necessitate screening libraries to discover phenotypes of interest. However, this approach is challenging when desirable phenotypes cannot be directly linked to growth advantages or fluorescence. In these cases, the ability to rapidly quantify intracellular proteins in the pathway of interest is critical to expedite the clonal selection process. While Saccharomyces cerevisiae remains a common host for pathway engineering, current approaches for intracellular protein detection in yeast either have low throughput, can interfere with protein function, or lack the ability to detect multiple proteins simultaneously. To fill this need, we developed yeast intracellular staining (yICS) that enables fluorescent antibodies to access intracellular compartments of yeast cells while maintaining their cellular integrity for analysis by flow cytometry. Using the housekeeping proteins β actin and glyceraldehyde 3-phophate dehydrogenase (GAPDH) as targets for yICS, we demonstrated for the first time successful antibody-based flow cytometric detection of yeast intracellular proteins with no modification. Further, yICS characterization of a recombinant d-xylose assimilation pathway showed 3-plexed, quantitative detection of the xylose reductase (XR), xylitol dehydrogenase (XDH), and xylulokinase (XK) enzymes each fused with a small (6-10 amino acids) tag, revealing distinct enzyme expression profiles between plasmid-based and genome-integrated expression approaches. As a result of its high-throughput and quantitative capability, yICS enabled rapid screening of a library created from CRISPR-mediated XDH integration into the yeast δ site, identifying rare (1%) clones that led to an 8.4-fold increase in XDH activity. These results demonstrate the utility of yICS for greatly accelerating pathway engineering efforts, as well as any application where the high-throughput and quantitative detection of intracellular proteins is desired.

Rational flux-tuning of Halomonas bluephagenesis for co-production of bioplastic PHB and ectoine

Ectoine, a compatible solute synthesized by many halophiles for hypersalinity resistance, has been successfully produced by metabolically engineered Halomonas bluephagenesis, which is a bioplastic poly(3-hydroxybutyrate) producer allowing open unsterile and continuous conditions. Here we report a de novo synthesis pathway for ectoine constructed into the chromosome of H. bluephagenesis utilizing two inducible systems, which serve to fine-tune the transcription levels of three clusters related to ectoine synthesis, including ectABC, lysC and asd based on a GFP-mediated transcriptional tuning approach. Combined with bypasses deletion, the resulting recombinant H. bluephagenesis TD-ADEL-58 is able to produce 28 g L⁻¹ ectoine during a 28 h fed-batch growth process. Co-production of ectoine and PHB is achieved to 8 g L⁻¹ ectoine and 32 g L⁻¹ dry cell mass containing 75% PHB after a 44 h growth. H. bluephagenesis demonstrates to be a suitable co-production chassis for polyhydroxyalkanoates and non-polymer chemicals such as ectoine.

Halomonas bluephagenesis is a halophilic platform bacterium for next generation industrial biotechnology. Here, the authors employ a stimulus response-based flux-tuning method for coproduction of bioplastic PHB and ectoine under open unsterile and continuous growth conditions.

Recent progress on bio-based production of dicarboxylic acids in yeast

Dicarboxylic acids are widely used in fine chemical and food industries as well as the monomer for polymerisation of high molecular material. Given the problems of environmental contamination and sustainable development faced by traditional production of dicarboxylic acids based on petrol, new approaches such as bio-based production of dicarboxylic acids drew more attentions. The yeast, Saccharomyces cerevisiae, was regarded as an ideal organism for bio-based production of dicarboxylic acids with high tolerance to acidic and hyperosmotic environments, robust growth using a broad range of substrates, great convenience for genetic manipulation, stable inheritance via sub-cultivation, and food compatibility. In this review, the production of major dicarboxylates via S. cerevisiae was concluded and the challenges and opportunities facing were discussed.Key Points• Summary of current production of major dicarboxylic acids by Saccharomyces cerevisiae.• Discussion of influence factors on four-carbon dicarboxylic acids production by Saccharomyces cerevisiae.• Outlook of potential production of five- and six-carbon dicarboxylic acids by Saccharomyces cerevisiae.

Metabolic engineering of an acid-tolerant yeast strain Pichia kudriavzevii for itaconic acid production

Itaconic acid (IA), or 2-methylenesuccinic acid, has a broad spectrum of applications in the biopolymer industry owing to the presence of one vinyl bond and two acid groups in the structure. Its polymerization can follow a similar mechanism as acrylic acid but additional functionality can be incorporated into the extra beta acid group. Currently, the bio-based production of IA in industry relies on the fermentation of the filamentous fungus Aspergillus terreus. However, the difficulties associated with the fermentation undertaken by filamentous fungi together with the pathogenic potential of A. terreus pose a serious challenge for industrial-scale production. In recent years, there has been increasing interest in developing alternative production hosts for fermentation processes that are more homogenous in the production of organic acids.

Pichia kudriavzevii is a non-conventional yeast with high acid tolerance to organic acids at low pH, which is a highly desirable trait by easing downstream processing. We introduced cis-aconitic acid decarboxylase gene (cad) from A. terreus (designated At_cad) into this yeast and established the initial titer of IA at 135 ​± ​5 ​mg/L. Subsequent overexpression of a native mitochondrial tricarboxylate transporter (herein designated Pk_mttA) presumably delivered cis-aconitate efficiently to the cytosol and doubled the IA production. By introducing the newly invented CRISPR-Cas9 system into P. kudriavzevii, we successfully knocked out both copies of the gene encoding isocitrate dehydrogenase (ICD), aiming to increase the availability of cis-aconitate. The resulting P. kudriavzevii strain, devoid of ICD and overexpressing Pk_mttA and At_cad on its genome produced IA at 505 ​± ​17.7 ​mg/L in shake flasks, and 1232 ​± ​64 ​mg/L in fed-batch fermentation. Because the usage of an acid-tolerant species does not require pH adjustment during fermentation, this work demonstrates the great potential of engineering P. kudriavzevii as an industrial chassis for the production of organic acid.

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Pichia kudriavzevii is a non-conventional yeast with high acid tolerance to organic acids at low pH.

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Engineering P. kudriavzevii to produce itaconic acid, a highly sought after biopolymer precursor.

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First description of a cis-aconitic acid transporter identified from a host besides the native producer of itaconic acid.

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Discussion on the potential of P. kudriavzevii as an industrial chassis for the production of organic acids.

Biosynthesis of the nitrogenase active-site cofactor precursor NifB-co in Saccharomyces cerevisiae

The radical S-adenosylmethionine (SAM) enzyme NifB occupies a central and essential position in nitrogenase biogenesis. NifB catalyzes the formation of an [8Fe-9S-C] cluster, called NifB-co, which constitutes the core of the active-site cofactors for all 3 nitrogenase types. Here, we produce functional NifB in aerobically cultured Saccharomyces cerevisiae Combinatorial pathway design was employed to construct 62 strains in which transcription units driving different expression levels of mitochondria-targeted nif genes (nifUSXB and fdxN) were integrated into the chromosome. Two combinatorial libraries totaling 0.7 Mb were constructed: An expression library of 6 partial clusters, including nifUSX and fdxN, and a library consisting of 28 different nifB genes mined from the Structure-Function Linkage Database and expressed at different levels according to a factorial design. We show that coexpression in yeast of the nitrogenase maturation proteins NifU, NifS, and FdxN from Azotobacter vinelandii with NifB from the archaea Methanocaldococcus infernus or Methanothermobacter thermautotrophicus yields NifB proteins equipped with [Fe-S] clusters that, as purified, support in vitro formation of NifB-co. Proof of in vivo NifB-co formation was additionally obtained. NifX as purified from aerobically cultured S. cerevisiae coexpressing M. thermautotrophicus NifB with A. vinelandii NifU, NifS, and FdxN, and engineered yeast SAM synthase supported FeMo-co synthesis, indicative of NifX carrying in vivo-formed NifB-co. This study defines the minimal genetic determinants for the formation of the key precursor in the nitrogenase cofactor biosynthetic pathway in a eukaryotic organism.

Stimulus response-based fine-tuning of polyhydroxyalkanoate pathway in Halomonas

Optimization of intracellular biosynthesis process involving regulation of multiple gene expressions is dependent on the efficient and accurate expression of each expression unit independently. However, challenges of analyzing intermediate products seriously hinder the application of high throughput assays. This study aimed to develop an engineering approach for unsterile production of poly(3-hydroxybutyrate-co-4-hydroxybutyrate) or (P3HB4HB) by recombinant Halomonas bluephagenesis (H. bluephagenesis) constructed via coupling the design of GFP-mediated transcriptional mapping and high-resolution control of gene expressions (HRCGE), which consists of two inducible systems with high- and low-dynamic ranges employed to search the exquisite transcription level of each expression module in the presence of γ-butyrolactone, the intermediate for 4-hydroxybutyrate (4HB) synthesis. It has been successful to generate a recombinant H. bluephagenesis, namely TD68-194, able to produce over 36 g/L P3HB4HB consisting of 16 mol% 4HB during a 7-L lab-scale fed-batch growth process, of which cell dry weight and PHA content reached up to 48.22 g/L and 74.67%, respectively, in 36 h cultivation. HRCGE has been found useful for metabolic pathway construction.

Start-Stop Assembly: a functionally scarless DNA assembly system optimized for metabolic engineering

DNA assembly allows individual DNA constructs or libraries to be assembled quickly and reliably. Most methods are either: (i) Modular, easily scalable and suitable for combinatorial assembly, but leave undesirable 'scar' sequences; or (ii) bespoke (non-modular), scarless but less suitable for construction of combinatorial libraries. Both have limitations for metabolic engineering. To overcome this trade-off we devised Start-Stop Assembly, a multi-part, modular DNA assembly method which is both functionally scarless and suitable for combinatorial assembly. Crucially, 3 bp overhangs corresponding to start and stop codons are used to assemble coding sequences into expression units, avoiding scars at sensitive coding sequence boundaries. Building on this concept, a complete DNA assembly framework was designed and implemented, allowing assembly of up to 15 genes from up to 60 parts (or mixtures); monocistronic, operon-based or hybrid configurations; and a new streamlined assembly hierarchy minimizing the number of vectors. Only one destination vector is required per organism, reflecting our optimization of the system for metabolic engineering in diverse organisms. Metabolic engineering using Start-Stop Assembly was demonstrated by combinatorial assembly of carotenoid pathways in Escherichia coli resulting in a wide range of carotenoid production and colony size phenotypes indicating the intended exploration of design space.

Recent developments in terminator technology in Saccharomyces cerevisiae

Metabolically engineered microorganisms that produce useful organic compounds will be helpful for realizing a sustainable society. The budding yeast Saccharomyces cerevisiae has high utility as a metabolic engineering platform because of its high fermentation ability, non-pathogenicity, and ease of handling. When producing yeast strains that produce exogenous compounds, it is a prerequisite to control the expression of exogenous enzyme-encoding genes. Terminator region in a gene expression cassette, as well as promoter region, could be used to improve metabolically engineered yeasts by increasing or decreasing the expression of the target enzyme-encoding genes. The findings on terminators have grown rapidly in the last decade, so an overview of these findings should provide a foothold for new developments.

Efficient Itaconic acid production via protein-protein scaffold introduction between GltA, AcnA, and CadA in recombinant Escherichia coli

Itaconic acid, which is a promising organic acid in synthetic polymers and some base-material production, has been produced by Aspergillus terreus fermentation at a high cost. The recombinant Escherichia coli that contained the cadA gene from A. terreus can produce itaconic acid but with low yield. By introducing the protein-protein scaffold between citrate synthesis, aconitase, and cis-aconitase decarboxylase, 5.7 g/L of itaconic acid was produced, which is 3.8-fold higher than that obtained with the strain without scaffold. The optimum pH and temperature for itaconic acid production were 8.5 and 30°C, respectively. When the competing metabolic network was inactivated by knock-out mutation, the itaconic acid concentration further increased, to 6.57 g/L.

Synthetic Biology of Yeast

With the rapid development of DNA synthesis and next-generation sequencing, synthetic biology that aims to standardize, modularize, and innovate cellular functions, has achieved vast progress. Here we review key advances in synthetic biology of the yeast Saccharomyces cerevisiae, which serves as an important eukaryal model organism and widely applied cell factory. This covers the development of new building blocks, i.e., promoters, terminators and enzymes, pathway engineering, tools developments, and gene circuits utilization. We will also summarize impacts of synthetic biology on both basic and applied biology, and end with further directions for advancing synthetic biology in yeast.

Utilising datasheets for the informed automated design and build of a synthetic metabolic pathway

BACKGROUND

The automation of modular cloning methodologies permits the assembly of many genetic designs. Utilising characterised biological parts aids in the design and redesign of genetic pathways. The characterisation information held on datasheets can be used to determine whether a biological part meets the design requirements. To manage the design of genetic pathways, researchers have turned to modelling-based computer aided design software tools.

RESULT

An automated workflow has been developed for the design and build of heterologous metabolic pathways. In addition, to demonstrate the powers of electronic datasheets we have developed software which can transfer part information from a datasheet to the Design of Experiment software JMP. To this end we were able to use Design of Experiment software to rationally design and test randomised samples from the design space of a lycopene pathway in E. coli. This pathway was optimised by individually modulating the promoter strength, RBS strength, and gene order targets.

CONCLUSION

The use of standardised and characterised biological parts will empower a design-oriented synthetic biology for the forward engineering of heterologous expression systems. A Design of Experiment approach streamlines the design-build-test cycle to achieve optimised solutions in biodesign. Developed automated workflows provide effective transfer of information between characterised information (in the form of datasheets) and DoE software.

Controlled intracellular trafficking alleviates an expression bottleneck in S. cerevisiae ester biosynthesis

In metabolic engineering, most available pathway engineering strategies aim to control enzyme expression by making changes at the transcriptional level with an underlying assumption that translation and functional expression follow suit. In this work, we engineer expression of a key reaction step in medium chain ester biosynthesis that does not follow this common assumption. The native Saccharomyces cerevisiae alcohol acyltransferses Eeb1 and Eht1 condense acyl-CoAs with ethanol to produce the corresponding ester, a reaction that is rate limiting in engineering ester biosynthesis pathways. By changing the N- and C-termini of Eeb1 to those of Eht1, Eeb1 localization is changed from the mitochondria to lipid droplets. The change has no significant effect on transcription, but increases protein expression by 23-fold thus enabling a 3-fold increase in enzyme activity. This system demonstrates one example of the impact of protein trafficking on functional pathway expression, and will guide future metabolic engineering of ester biosynthesis and, potentially, other pathways with critical membrane-bound enzymes.

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Intracellular localization can control membrane-associated enzyme expression.

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Terminal domain swapping of Eht1 and Eeb1 alters intracellular localization.

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Eeb1 expression and activity are increased with lipid droplet targeting.

Dynamic control of endogenous metabolism with combinatorial logic circuits

Controlling gene expression during a bioprocess enables real-time metabolic control, coordinated cellular responses, and staging order-of-operations. Achieving this with small molecule inducers is impractical at scale and dynamic circuits are difficult to design. Here, we show that the same set of sensors can be integrated by different combinatorial logic circuits to vary when genes are turned on and off during growth. Three Escherichia coli sensors that respond to the consumption of feedstock (glucose), dissolved oxygen, and by-product accumulation (acetate) are constructed and optimized. By integrating these sensors, logic circuits implement temporal control over an 18-h period. The circuit outputs are used to regulate endogenous enzymes at the transcriptional and post-translational level using CRISPRi and targeted proteolysis, respectively. As a demonstration, two circuits are designed to control acetate production by matching their dynamics to when endogenous genes are expressed (pta or poxB) and respond by turning off the corresponding gene. This work demonstrates how simple circuits can be implemented to enable customizable dynamic gene regulation.