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Why is it desirable to couple chemical production to growth?

Why is it desirable to couple chemical production to growth?


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I have the following question in systems biology: a) Draw a graph showing the relationship of growth (Vbio) and Vefni for the system here. (Let the horizontal axis represent Vbio and the vertical axis represent Vefni)

My first thought was that it would simply be straight line from (0.5,0.5) to (1,0). But now I'm thinking that I have to take V4 into account as well.

b) Determine one or more reactions that are such that if they are taken out the production of M4 is coupled to growth (growth-coupling). Draw a graph showing the relationship Vbio and Vefni for the mutant.

Here I thought it would be V1 and V4. I'm not sure though because I haven't found a good explanation for what growth-coupling is exactly.

c) Why is it desirable to couple chemical production to growth? i.e. what advantages do those systems have over the ones where no such coupling is present?

Here I have no idea.


Why is it desirable to couple chemical production to growth?

When designing new metabolic pathways for chemical production, one has to keep in mind that the purpose of it is to get scaled up (i.e. to reach industrial size).

From the industrial point of view, the faster/simpler a process is, the better. Growth coupled chemical production means that only one step is necessary in order to produce the desired product (before downstream processes). Otherwise, one would have to produce the biomass first (growth step) and then to proceed to the chemical production step. One step is cheaper and faster than two, not mentioning the intermediary steps that could be necessary (cells washing, centrifugation, filtration… ).

The main drawback of growth coupled chemical production is that the final yield ($mol_{final~product}/mol_{substrate}$) is hindered by biomass production. This can be a real issue if the substrate is expensive.


32.3: Asexual Reproduction

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  • Compare the mechanisms and methods of natural and artificial asexual reproduction
  • Describe the advantages and disadvantages of natural and artificial asexual reproduction
  • Discuss plant life spans

Many plants are able to propagate themselves using asexual reproduction. This method does not require the investment required to produce a flower, attract pollinators, or find a means of seed dispersal. Asexual reproduction produces plants that are genetically identical to the parent plant because no mixing of male and female gametes takes place. Traditionally, these plants survive well under stable environmental conditions when compared with plants produced from sexual reproduction because they carry genes identical to those of their parents.

Many different types of roots exhibit asexual reproduction Figure (PageIndex<1>). The corm is used by gladiolus and garlic. Bulbs, such as a scaly bulb in lilies and a tunicate bulb in daffodils, are other common examples. A potato is a stem tuber, while parsnip propagates from a taproot. Ginger and iris produce rhizomes, while ivy uses an adventitious root (a root arising from a plant part other than the main or primary root), and the strawberry plant has a stolon, which is also called a runner.

Figure (PageIndex<1>): Different types of stems allow for asexual reproduction. (a) The corm of a garlic plant looks similar to (b) a tulip bulb, but the corm is solid tissue, while the bulb consists of layers of modified leaves that surround an underground stem. Both corms and bulbs can self-propagate, giving rise to new plants. (c) Ginger forms masses of stems called rhizomes that can give rise to multiple plants. (d) Potato plants form fleshy stem tubers. Each eye in the stem tuber can give rise to a new plant. (e) Strawberry plants form stolons: stems that grow at the soil surface or just below ground and can give rise to new plants. (credit a: modification of work by Dwight Sipler credit c: modification of work by Albert Cahalan, USDA ARS credit d: modification of work by Richard North credit e: modification of work by Julie Magro)

Some plants can produce seeds without fertilization. Either the ovule or part of the ovary, which is diploid in nature, gives rise to a new seed. This method of reproduction is known as apomixis .

An advantage of asexual reproduction is that the resulting plant will reach maturity faster. Since the new plant is arising from an adult plant or plant parts, it will also be sturdier than a seedling. Asexual reproduction can take place by natural or artificial (assisted by humans) means.


2 Bioenergetics of Ecosystem Development

Attributes 1 through 5 in Table 1 represent the bioenergetics of the ecosystem. In the early stages of ecological succession, or in young nature, so to speak, the rate of primary production or total (gross) photosyntesis (P) exceeds the rae of community respiration (R), so that the P/R ratio is greater than 1. In the special case of organic pollution, the P/R ratio is typically less than 1. In both cases, however, the theory is that P/R approaches 1 as succession occurs. In other words, energy fixed tends to be balanced by the energy cost of maintenance (that is, total community respiration) in the mature or climax ecosystem. The P/R ratio, therefore, should be an excellent functional index of the relative maturity of the system.

So long as P exceeds R, organic matter and Biomass (B) will accumulate in the system (Table 1, item 6), with the result that ratio P/B will tend to decrease or, conversely, the B/P, B/R, or B/E ratios (where E=P/R) will increase (Table 1, items 2 and 3). Theoretically, then, the amount of standingcrop biomass supported by the available energy flow (E) increases to a maximum in the mature or climax stages (Table 1, item 3). As a consequence, the net community production, or yield, in an annual cycle is large in young nature and small or zero in mature nature (Table 1, item 4).


Life Cycle and Adaptability

Johnsongrass is an aggressive perennial. Either new shoots from rhizomes or new seedlings will sprout during early to mid-spring. Seeds start to germinate when soil temperatures reach 70 F however, new shoots from rhizomes will sprout when soil temperatures are 60 F. Sprouts from rhizomes develop faster than seedlings by taking advantage of rhizome carbohydrates accumulated during the winter. Plants start to produce new rhizomes after five to seven true leaves have developed. This occurs approximately three to six weeks after emergence. Flowering will commence six to nine weeks after emergence, and viable seeds will be produced two to three weeks after flowering. During the fall, Johnsongrass growth ceases when soil temperatures return to 60 F, turning the plant dormant. In Oklahoma, Johnsongrass will start to grow by the end of March, and new rhizomes will start to develop by the end of April. Flowering will start in early June and viable seeds will appear in late June. Additionally, new rhizomes, flowers and seeds will continue to be produced until early November, when plants turn dormant.

Johnsongrass is adapted to a wide range of soil types within a pH range of 5 to 7.5. Therefore, Johnsongrass is mainly found in arable lands, orchards, open waste grounds, roadsides, pastures, irrigated canals and ditches. It grows best in fertile lowland soils. It is not adapted to poorly drained clay soils, but it can tolerate short periods of flooding. Rhizome production also is affected by soil type. Greater rhizome production and depth will occur in lighter-textured soils. For instance, clay soils will allow only half of the rhizomes that are capable of being produced in sandy loam soils. In addition, most rhizomes in clay and sandy loam soils will reach depths of 3 and 5 inches, respectively.


Metabolic Engineering for Production of Biorenewable Fuels and Chemicals: Contributions of Synthetic Biology

Production of fuels and chemicals through microbial fermentation of plant material is a desirable alternative to petrochemical-based production. Fermentative production of biorenewable fuels and chemicals requires the engineering of biocatalysts that can quickly and efficiently convert sugars to target products at a cost that is competitive with existing petrochemical-based processes. It is also important that biocatalysts be robust to extreme fermentation conditions, biomass-derived inhibitors, and their target products. Traditional metabolic engineering has made great advances in this area, but synthetic biology has contributed and will continue to contribute to this field, particularly with next-generation biofuels. This work reviews the use of metabolic engineering and synthetic biology in biocatalyst engineering for biorenewable fuels and chemicals production, such as ethanol, butanol, acetate, lactate, succinate, alanine, and xylitol. We also examine the existing challenges in this area and discuss strategies for improving biocatalyst tolerance to chemical inhibitors.

1. Introduction

Human society has always depended on biomass-derived carbon and energy for nutrition and survival. In recent history, we have also become dependent on petroleum-derived carbon and energy for commodity chemicals and fuels. However, the nonrenewable nature of petroleum stands in stark contrast to the renewable carbon and energy present in biomass, where biomass is essentially a temporary storage unit for atmospheric carbon and sunlight-derived energy. Thus there is increasing demand to develop and implement strategies for production of commodity chemicals and fuels from biomass instead of petroleum. Specifically, in this work we are interested in the microbial fermentation of biomass-derived sugars to commodity fuels and chemicals.

In order for a fermentation process to compete with existing petroleum-based processes, the target chemical must be produced at a high yield, titer and productivity. Sometimes there are additional constraints on the fermentation process, such as the presence of potent inhibitors in biomass hydrolysate or the need to operate at an extreme pH or temperature [1]. These goals can be difficult to attain with naturally-occurring microbes. Therefore, microorganisms with these desired traits often must be developed, either by modification of existing microbes or by the de novo design of new microbes. While significant progress has been made towards de novo design [2, 3], this work focuses on the modification of existing microbes.

Humanity has long relied on microbial biocatalysts for production of fermented food and beverages and eukaryotic biocatalysts for food and textiles. We have slowly modified these biocatalysts by selecting for desirable traits without understanding the underlying biological mechanisms. But upon elucidation of the biological code and the development of recombinant DNA technology, we now have the tools to do more than just select for observable traits—we are now able to rationally modify and design metabolic pathways, proteins, and even whole organisms.

Much of this rational modification has been in the form of Metabolic Engineering. Metabolic Engineering was defined in 1991 [4, 5] and here we use the definition of “the directed improvement of production, formation, or cellular properties through the modification of specific biochemical reactions or the introduction of new ones with the use of recombinant DNA technology ” [6]. While Metabolic Engineering has enabled extraordinary advances in the production of commodity chemicals and fuels from biomass, some of which are discussed in this work, we have now reached the point where biological functions that do not exist in nature are desired. Synthetic biology aims to develop and provide these nonnatural biological functions.

For many years, the term Synthetic Biology was used to describe concepts that would be classified today as Metabolic Engineering [7]. However in the last 10 years, terms such as “unnatural organic molecules” [7], “unnatural chemical systems [8], “novel behaviors” [9], “artificial, biology-inspired systems” [10], and “functions that do not exist in nature” [11] have been used to describe Synthetic Biology. For the purpose of this review, we will apply the Synthetic Biology definition of “the design and construction of new biological components, such as enzymes, genetic circuits, and cells, or the redesign of existing biological systems” [12].

Synthetic biology has application to many fields, including cell-free synthesis [13], tissue and plant engineering [14] and drug discovery [15], but here we are interested in the modification of microbes for the biorenewable production of commodity chemicals and fuels. Other recent reviews have also dealt with this topic [16–18].

Synthetic biology for the production of a target compound can be expressed as a sequence of the following events, each of which will be discussed in more detail and demonstrated below.

Design the metabolic pathways and phenotypic properties of the desired system. What are the desired substrates and products? What are the expected environmental stressors?

Choose an appropriate host organism (chassis) based on the following criteria. Which organisms display at least some of the desired properties? How well characterized and annotated are these organisms? Are there molecular biology tools for modification of this chassis?

Formulate an implementation approach. What modifications are necessary to achieve the pathways and properties identified in step ? Do metabolic pathways need to be added, removed, or tuned? Does the desired pathway or phenotype exist in nature, or does it need to be designed de novo?

Optimize the redesigned system and assess the system properties relative to the ideal. Can the chassis be improved further?

Even a simple biocatalyst, such as the laboratory workhorse Escherichia coli, is a complex system of an estimated 4603 genes, 2077 reactions, and 1039 unique metabolites [19, 20], and while the steps outlined above are relatively straightforward, it is still difficult to quickly and reliably engineer a biocatalyst to perform desired behaviors [21]. Systems biology, the standardization of biological systems, and metabolic evolution are all vital to the compensation for this disconnect between the expected and actual biocatalyst behaviors. Through a combination of these powerful techniques, biocatalysts have been redesigned for the production of an astounding array of commodity fuels and chemicals, both natural and unnatural (Figure 1 and Table 1). Here we discuss successful examples involving the production of commodity fuels and chemicals, with a focus on D- and L-lactate, L-alanine, succinate, ethanol, and butanol.


2. Methods and Tools for Biocatalyst Redesign

2.1. Chassis

A robust and stable chassis enables efficient and economical production of fuels and chemicals at an industrial level. Since we are specifically interested in biocatalysts that can utilize biomass, a desirable chassis has the following characteristics: (1) growth in mineral salts medium with inexpensive carbon sources, (2) utilization of hexose and pentose sugars, so that all the sugar components in lignocellulosic biomass can be converted to the desired product, (3) high metabolic rate, essential for high rate of productivity, (4) simple fermentation process to reduce the manipulation cost and minimize failure risks in large-scale production, (5) robust organism (high temperature and low pH where possible) to reduce the requirement for external cellulase during cellulose degradation, as well as to reduce the required amount of base addition, (6) ease of genetic manipulation and genetic stability, (7) resistance to inhibitors produced during the biomass pretreatment process, and (8) tolerance to high substrate and product concentrations in order to obtain high titers of target compound.

Enteric bacteria, especially E. coli, have many of the above mentioned physiological characteristics and are, thus, an excellent chassis for synthetic biology. Most of the examples discussed here use E. coli, but other important microbial model systems have been redesigned, including Clostridium acetobutylicum [28], Corynebacterium glutamicum [29], Saccharomyces cerevisiae [30], and Aspergillus niger [31]. E. coli has been used as a model organism since the beginning of genetic engineering [32]. While K-12 strain MG1655 (ATCC# 47076) is one of the most commonly used E. coli strains [33], there are other lineages, such as B (ATCC# 11303), C (ATCC# 8739), and W (ATCC# 9637), that are also generally regarded as safe since they are unable to colonize the human gut [34]. Although K-12 is the most characterized and widely used strain, E. coli W (ATCC# 9637) and C (ATCC# 8739) have proven to be better chassis for synthesizing fuels and chemicals. For example, K-12-derived strains were unable to completely ferment 10% (w/v) glucose in either complex or mineral salts medium [1, 35], while derivatives of strains W or C can completely ferment more than 10% (w/v) of glucose with higher cell growth and sugar utilization rates than K-12. Additionally, E. coli W strains have the native ability to ferment sucrose [1, 36].

Foreign genes may be unstable in host cells due to recombination facilitated by mobile DNA elements, and thus the mobile DNA elements in E. coli K-12 strain have been deleted [37]. This minimal genome construction strategy is an excellent approach to improve this chassis for the production of fuels and chemicals.

2.2. Systems Biology Tools
2.2.1. Genome-Scale Models and In Silico Simulation

Given the rational basis of metabolic engineering and synthetic biology, models and simulations are critical predictive and tools. Genome sequencing and automatic annotation tools have enabled construction of genome-scale metabolic models of nearly 20 microorganisms [38]. These constraint-based models and in silico simulations can be used to predict metabolic flux redistribution after genetic manipulation, or to predict other cellular functions, such as substrate preference, outcomes of adaptive evolution and shifts in expression profiles [39]. They can also aid in pathway design to obtain desired phenotypes [40–42]. For example, the E. coli iJE660a GSM model was used to successfully simulate single- and multiple-gene knockouts to improve lycopene production [42]. The computational framework, Optknock, was developed to identify gene deletion targets for system optimization [41], and simulation results for gene deletions for succinate, lactate, and 1,3-propanediol production were in agreement with experimental data. Another simulation program, OptStrain, was developed to guide metabolic pathway modification for target compound production, through both the addition of heterologous metabolic reactions and deletion of native reactions [40]. However, most of the current models only have stoichiometric information, while kinetic and regulatory effects are not included [38, 39]. Integration of kinetic and regulatory information will improve the accuracy and predictive power of these models.

2.2.2. High-Throughput Omics Analysis

High-throughput omics analysis, such as transcriptome, proteome, metabolome, and fluxome [43–45], aids in characterization of cellular function on multiple levels, and therefore provide a “debugging” capability for system optimization [12, 45].

Genetic manipulations can disturb the metabolic balance or impair cell growth due to depletion of important precursors [46, 47], accumulation of toxic intermediates [48], or redox imbalance [1]. For example, high NADH levels in E. coli reengineered for ethanol production inhibited citrate synthase activity, thereby limiting cell growth by lowering production of the critical metabolite 2-ketoglutarate [49]. Metabolome and fluxome analysis can quickly identify the limiting metabolites or altered metabolic flux distribution, providing the basis for problem solving [45, 50]. For example, metabolite measurements of Aspergillus terreus were implemented in the rational metabolic redesign for increased production of lovastatin [45, 50]. Changes of mRNA and protein profiles can be identified by transcriptome and proteome analysis, providing gene targets for further engineering [46, 47]. The work of Choi et al. demonstrate this concept: transcriptome analysis of E. coli producing the human insulin-like growth factor I fusion protein aided in selection for targets for gene deletion. The resulting redesigned strain showed a greater than 2-fold increase in product titer and volumetric productivity [46, 47]. Additionally, comparative genome sequence analysis facilitates identification of mutated genes or regulators during evolution, and these mutations can be used to redesign the systems for better synthetic capability. For example, in an effort described as “genome-based strain reconstruction”, evolved strains of Corneybacterium glutamicum selected for L-lysine production were compared to the parental strain, and mutations were found that were proposed as beneficial to L-lysine production. Three of these mutations were introduced into the parent strain and enabled production of up to 3.0 g/L/hr L-lysine [51].

2.3. Genetic Manipulation Tools
2.3.1. Gene Deletion

Gene deletion can redistribute carbon flux toward the target product by deleting genes critical to competing metabolic pathways and, thus, is widely used in metabolic redesign strategies. Homologous recombination is the most frequently used strategy for gene-deletion (Figure 2). Historically, plasmids containing a selectable marker flanked by DNA fragments homologous to the target gene and either temperature sensitive or conditional replicons were needed for efficient gene deletion in bacteria [52] (Figure 2(a)). In contrast, genes can be directly disrupted in yeast by linear PCR fragments with short flanking DNA fragments homologous to chromosomal DNA. Linear DNA is not as easy to transform into E. coli because of the intracellular exonuclease system and low recombination efficiency. Gene deletion systems based on bacteriophage

Red recombinase facilitate chromosomal gene deletion using a linear PCR fragment [53]. In this method, the chromosomal gene is replaced by the selectable marker flanked by two FRT (FLP recognition target) fragments (Figure 2(b)) and then the marker can be removed by the FLP recombinase [54]. However, this method leaves a 68bp-FRT scar on the chromosome after each excision [52], reducing further gene deletion efficiency. Repeated use of this FRT/FLP system for specific gene deletions has the potential to generate large unintended chromosomal deletions.


(a)
(b)
(c)
(a)
(b)
(c) Comparison of three-gene deletion methods in E. coli. These methods can also be used in other enteric bacteria. The first and third methods can also be used for gene integration into the chromosome and promoter replacement for tuning gene expression. 2(a) plasmid-based method. Step

is construction of the deletion plasmid containing DNA fragments homologous to the target gene (h1 and h2), a selectable marker, and either a temperature sensitive or conditional replicon. Step

is double-crossover recombination the plasmid cannot replicate in the host strain, and antibiotic-resistant colonies are selected. In step

, the FRT, replicon, and antibiotic resistance marker are removed by FLP. 2(b) Linear DNA-based method. Step

is construction of the linear DNA fragment by PCR (H1-P1 and H2-P2 as primers). H1 and H2 refer to short DNA fragments homologous to target gene. Step

is replacement of the target gene with the antibiotic resistance gene through crossover recombination with the help of Red recombinase. Step

is removal of FRT and antibiotic marker by FLP. 2(c) Two-stage recombination-based method developed in our lab. Steps

, 2, 3, and 5 describe construction of the plasmids and linear DNA fragments for the two-stage recombinations. Step

describes the first recombination step, in which the cat, sacB cassette is inserted into the target gene. Step

To facilitate sequential gene deletions, our lab has developed a two-stage recombination strategy (Figure 2(c)), using the sensitivity of E. coli to sucrose when Bacillus subtilis levansucrase (sacB) is expressed [24, 27, 55]. Gene deletions created by this method do not leave foreign DNA, antibiotic resistance markers, or scar sequences at the site of deletion. In the first recombination, part of the target gene is replaced by a DNA cassette containing a chloramphenicol resistance gene (cat) and levansucrase gene (sacB). In the second recombination, the cat, sacB cassette is removed by selection for resistance to sucrose. Cells containing the sacB gene accumulate levan during incubation with sucrose and are killed [55]. Surviving recombinants are highly enriched for loss of the cat, sacB cassette [24, 27].

2.3.2. Gene Expression Tuning

Like gene deletions, plasmid-based expression systems are ubiquitous to metabolic redesign. However, plasmid-based systems have several disadvantages. (1) Plasmid maintenance is a metabolic burden on the host cell, especially for high-copy number plasmids [56]. Note that high copy numbers are not essential, considering that most central metabolic enzymes are encoded by a single gene (2) plasmid-based expression is dependent on plasmid stability, with only few natural unit-copy plasmids having the desired stability [12] (3) only low-copy number plasmids have replication that is timed with the cell cycle, and thus maintaining a consistent copy number in all cells is challenging [12] (4) metabolic redesign can require construction of a complex heterologous pathway, and thus several genes, encoded in large pieces of DNA, need to be incorporated. Most commercial plasmids have difficulties carrying large DNA fragments.

Chromosomal integration of the target genes followed by fine-tuning their expression could eliminate these plasmid-associated problems. The abovementioned two-step recombination strategy for gene deletion can also be used for gene integration or promoter replacement (Figure 2).

Gene expression in prokaryotes is mainly controlled at the transcriptional level, and therefore the promoter is the most tunable element. While inducible promoters, such as lac and ara, have been traditionally used to modulate gene expression, large-scale inducer use is cost prohibitive for production of fuels and bulk chemicals. However, several strategies have been developed to construct constitutive promoter libraries for fine-tuning gene expression. Some methods rely on the use of natural promoters. For example, Zymomonas mobilis genomic DNA was used to construct a promoter library for screening optimal expression of Erwinia chrysanthemi endoglucanase genes (celY and celZ) in Klebsiella oxytoca P2 in order to improve ethanol production from cellulose [57]. Other methods rely on random modification of existing promoters, such as the randomization of the spacer sequences between the consensus sequences [58], or mutagenesis of a constitutive promoter [59]. This promoter modification method was used to assess the impact of phosphoenolpyruvate carboxylase levels on cell yield and deoxy-xylulose-P synthase levels on lycopene production, and the optimal expression levels of these genes were identified for maximal desired phenotype [59]. These synthetic promoter libraries could also be integrated into the chromosome directly, which could facilitate expression modulation of chromosomal genes [60, 61].

The fine-tuning methods described above rely on the selection of the best natural promoter or random alteration of existing promoters. One of the goals of synthetic biology is construction of standard parts, and posttranscriptional processes, such as transcriptional termination, mRNA degradation, and translation initiation, have been engineered with this goal in mind. Examples include construction of a synthetic library of 5’ secondary structures to successfully manipulate mRNA stability [62], and modulation of the ribosome binding site (RBS) as well as Shine-Dalgarno (SD) and AU-rich sequences to tune gene expression at the translation initiation process [60, 63]. Riboregulators were also developed to tune gene expression via RNA-RNA interactions [64]. A final method of fine-tuning gene expression is codon optimization, which can improve translation of foreign genes [65]. These optimized gene sequences often do not exist in nature and must be generated using DNA synthesis techniques.

In many cases, more than one gene needs to be introduced into the chassis and expression of these genes needs to be coordinated to attain desired biocatalyst performance. One such method is modulation of the expression of each individual gene via its own promoter. However, it is difficult to predict the appropriate expression level of each gene. Another option is to combine multiple genes into a synthetic operon with a single promoter, and fine-tune expression of each gene through posttranscriptional processes [12] with tunable control elements (such as mRNA secondary structure, RNase cleavage sites, ribosome binding sites, and sequestering sequences) at intergenic regions. Libraries of tunable intergenic regions (TIGRs) were generated and screened to tune expression of several genes in an operon [48]. This method was used to coordinate expression of three genes in an operon that encodes a heterologous mevalonate biosynthetic pathway, improving mevalonate production by 7-fold [48]. Another method to control expression of more than one gene is to engineer global transcription machinery by random mutagenesis of transcription factors [66, 67]. This method was shown to efficiently improve tolerance to toxic compounds and production of metabolites, and to alter phenotypes [66, 67].

2.3.3. Protein Engineering

Natural proteins may not meet the required criteria for specific and efficient system performance, and thus alteration for a specific application may be needed. Directed evolution of proteins offers a way to rapidly optimize enzymes, even in the absence of structural or mechanistic information [68]. For directed evolution, a protein library is usually generated by random mutagenesis [68], recombination of a target gene [69], or a family of related genes [70] and then the library is analyzed by high-throughput screening. This method has been used to successfully increase enzyme activity [71, 72], increase protein solubility and expression, invert enantioselectivity, and increase stability and activity in unusual environments [68]. For example, a mutation library of the gene-encoding geranylgeranyl diphosphate synthase of Archaeoglobus fulgidus was generated to screen for mutants with higher activity, enabling lycopene production in E. coli. Screening of more than 2,000 variants identified eight with increased activity one of which increased lycopene production by 100% [71].

Of particular relevance to the field of synthetic biology is the creation of novel enzymatic activity through protein engineering [73, 74]. For example, the unnatural isomerization of α-alanine to β-alanine was attained by evolving a lysine 2,3-aminomutase to expand its substrate specificity to include α-alanine [73].

Rational design is another powerful tool to increase protein properties, especially with the aid of computational analysis [75, 76]. Based on knowledge of protein structure and function, one can predict which amino acid(s) to change in order to obtain the desired function. In the redesign of Lactobacillus brevis for the production of secondary alcohols, it was desired to change the cofactor preference of the R-specific alcohol dehydrogenase from NADPH to NADH. A structure-based computational model was used to identify potentially beneficial amino acid substitutions and one of these changes increased NADH-dependent activity four-fold [77].

While these examples demonstrate the power of rational enzyme (re-)design, this approach requires detailed information about the protein structure and mechanism, while random mutagenesis does not. Recent advances have combined directed evolution and rational design in a so-called “semi-rational” approach to successfully improve enzyme activity when only limited information is available [78, 79]. When the mutagenesis is limited to specific residues, as chosen from existing structural or functional knowledge, these “smart” libraries are more likely to yield positive results [79]. For example, the catalytic activity of pyranose-2-oxidase was improved by mutagenesis of the known active site [80].

While the 20 natural amino acids supply enzymes with a wide range of possible activity, this range can be expanded even further by the use of unnatural amino acids (UAAs). There are more than 40 UAAs available at this time and they have been used to probe protein function, photocage critical residues, and alter metalloprotein properties [81, 82]. While this technology is still in the developmental stage, at least one study has shown an improvement in enzyme activity following insertion of UAAs. Site 124 of E. coli’s nitroreductase was replaced with a variety of natural and unnatural amino acids and certain UAA variants had a greater than 2-fold increase in activity over the best natural amino acid variant [83]. This biomimetic approach has been expanded to other metabolites, such as carbohydrates [84] and lipids [85].

2.4. Evolution

As described above, a robust biocatalyst with high yield, titer, and productivity is critical for a fermentation process to compete with petrochemical-based production. Current models and simulation tools provide a framework given the constraints of known protein functions. But the many reactions and enzymes that remain uncharacterized cannot be included in this theoretical analysis. Therefore rational design methods often result in a biocatalyst that performs poorly relative to the model. Metabolic evolution provides a complementary approach to improve biocatalyst productivity and robustness, dependent upon the design of an appropriate selection pressure. Where feasible, synthesis of the target compound can be coupled to the production of ATP, redox balance, or key metabolites that are essential for growth, and selection for improvements in growth during metabolic evolution (serial transfers) can be used to coselect for higher rates or titers of target compounds (Figure 3). Both redox balance and net ATP production in such a synthetic system are requisites for successful evolution.


(a)
(b)
(c)
(a)
(b)
(c) Metabolic evolution for improving L-alanine production in E. coli [27]. 3(a) Redesigned metabolic pathway for L-alanine production: ATP production and cell growth is coupled to NADH oxidation and L-alanine production. 3(b) Directed evolution improves cell growth. Parental strain XZ112 reaches a maximum cell mass of 0.7 gL -1 after 48 hours of fermentation evolved strain XZ113 attains 0.7 gL -1 after 24 hours and a maximum of 0.9 gL -1 after 48 hours 3(c) metabolic evolution to improve cell growth also improves alanine production. Parental strain XZ112 produces 355 mM alanine after 72 hours of fermentation evolved strain XZ113 produces 484 mM in 48 hours.

We have used this metabolic evolution strategy to optimize biocatalysts redesigned for production of several fermentation products [1], including ethanol, D-lactate, L-lactate, L-alanine (Figure 3), and succinate, as described in more detail below. A frequently-used design scheme is to couple synthesis of the target product to growth by inactivating competing NADH-consuming pathways. Thus, the only way for cells to regenerate NAD + for glycolysis is to produce the target compound. Increased cell growth, supported by higher ATP production rate during glycolysis, is coupled with higher NADH oxidization rate, and thus tightly coupled with synthesis of target product. This evolution strategy has been shown to increase productivity by up to two orders of magnitude.

Computational frameworks based on genome-scale metabolic models have been used to construct biocatalysts that couple biomass formation with chemical production [40, 41], and therefore provide a basis for selective pressure for high productivity. For example, Optknock identified gene deletion targets for the construction of lactate-producing E. coli, and then directed evolution improved production capability [86]. Although rational design of metabolic pathways based on current metabolic models is a common method for maximizing yield of the target compound, this method is not always the best strategy, due to our limited understanding of the complicated metabolic network and dynamic kinetics of each reaction. Metabolic evolution provides an excellent alternative method for strain improvement, through which reactions that are not currently predictable would be selected to improve biocatalyst performance [87]. As our knowledge of biocatalyst behavior and metabolism improves, predictive models will become even more powerful.

3. Redesign through Modification of Existing Pathways

In this section, we highlight projects that have redesigned a chassis to produce target compounds at high yield and titer without the introduction of foreign pathways. In the next section, we describe biocatalyst redesigns which used foreign or nonnatural pathways.

3.1. Succinate

Succinate, a four-carbon dicarboxylic acid, is currently used as a specialty chemical in food, agricultural, and pharmaceutical industries [88] but can also serve as a starting point for the synthesis of commodity chemicals used in plastics and solvents, with a potential global market of $15 billion [89]. Succinate is primarily produced from petroleum and there is considerable interest in the fermentative production of succinate from sugars [89].

Several rumen bacteria can produce succinate from sugars with a high yield and productivity [90–92], but require complex nutrients. Alternatively, native strains of E. coli ferment glucose effectively in simple mineral salts medium but produce succinate only as a minor product [93]. Therefore E. coli strain C (ATCC 8739) was redesigned for succinate production at high yield, titer, and productivity [94].

The initial redesign strategy focused on inactivation of competitive pathways, specifically deletion of lactate dehydrogenase (ldhA), alcohol/aldehyde dehydrogenase (adhE), and acetate kinase (ackA). However, the resulting strain grew poorly in mineral salts medium under anaerobic condition and accumulated only trace amounts of succinate. Because NADH oxidization is coupled to succinate synthesis in this strain, metabolic evolution was used to improve both the cell growth and succinate production. After inactivation of pyruvate formate-lyase and methylglyoxal synthase to eliminate formate and lactate production, the final strain, KJ073, produced near 670 mM succinate (80 g/L) in mineral salts medium with a high yield (1.2 mol/mol glucose) and high productivity (0.82 g/L/h) [94]. Inactivation of threonine decarboxylase (tdcD), 2-ketobutyrate formate-lyase (tdcE), and aspartate aminotransferase (aspC) further increased succinate yield (1.5 mol/mol glucose), titer (700 mM), and productivity (0.9 g/L/h) [24].

Despite its power in improving biocatalyst performance, metabolic evolution has the undesirable property of being a black box evolved strains show the desired biocatalyst properties, but the metabolic evolution process does not improve our understanding of the biocatalyst. Therefore, reverse engineering of evolved strains can help us identify key mutations that can then be rationally applied to other biocatalysts. Reverse engineering of the succinate-producing strain revealed two significant changes in cellular metabolism that increased energy efficiency [87]. The first change is that PEP carboxykinase (pck), which normally functions in gluconeogenesis during the oxidative metabolism of organic acids [90, 95, 96], became the major carboxylation pathway for succinate production. High-level expression of PCK dominated CO2 fixation and increased ATP yield (1 ATP per oxaloacetate produced). The second change is that the native phosphoenolpyruvate- (PEP-) dependent phosphotransferase system for glucose uptake was inactivated and replaced by an alternative glucose uptake pathway: GalP permease (galP) and glucokinase (glk). These changes increased the pool of PEP available for maintaining redox balance, as well as increasing energy efficiency by eliminating the need to produce additional PEP from pyruvate, a reaction that requires two ATP equivalents [97].

While rational design based on current metabolic understanding is a key component of metabolic engineering and synthetic biology, our limited understanding of the complicated metabolic network and dynamic kinetics of each reaction can lead to failure of predictive models. In this example, metabolic evolution was demonstrated as an excellent alternative method for strain improvement, through which currently unpredictable reactions would be selected to expand cellular metabolic capability [87]. By understanding the mutations that enabled desirable performance of the succinate-producing strain, we have more options available for the redesign of future systems. To demonstrate this, E. coli was again redesigned based on the findings from the evolved strain [98]. This time, the design strategy shifted from inactivating competitive fermentation pathways to recruiting energy conserving pathways for efficient succinate production (Figure 4(e)). After increasing pck gene expression and inactivating the native glucose PTS system, the native E. coli metabolic system was converted to an efficient succinate synthetic system, equivalent to the native pathway of succinate-producing rumen bacteria [98].


(a)
(b)
(c)
(d)
(e)
(a)
(b)
(c)
(d)
(e) Synthetic pathways of E. coli for production of fuels and chemicals in our lab: 4(a) Native metabolic pathways of glucose fermentation in E. coli 4(b) synthetic pathways for production of D-lactate, ethanol, L-lactate and L-alanine 4(c) synthetic pathways for production of pyruvate and acetate 4(d) synthetic pathway for production of xylitol, 4(e) synthetic pathway for production of succinate. ★ indicate gene deletion. Genes and enzymes: ackA, acetate kinase adhAB, alcohol dehydrogenase (Z. mobilis) adhE, alcohol/aldehyde dehydrogenase alaD, L-alanine dehydrogenase (G. stearothermophilus) crr, glucose-specific phosphotransferase enzyme IIA component frd, fumarate reductase fum, fumarase galP, galactose-proton symporter (glucose permease) glk, glucokinase ldhA, D-lactate dehydrogenase ldhL, L-lactate dehydrogenase (P. acidilactici) mdh, malate dehydrogenase pdc, pyruvate decarboxylase pflB, pyruvate formate-lyase ppc, phosphoenolpyruvate carboxylase pta, phosphate acetyltransferase ptsG, PTS system glucose-specific EIICB component ptsH, phosphocarrier protein HPr ptsI, phosphoenolpyruvate-protein phosphotransferase (Phosphotransferase system, enzyme I) pyk, pyruvate kinase xrd, xylose reductase (C. boidinii) xylB, xylulokinase. Metabolites: G6P, glucose-6-phosphate G3P, glycerol-3-phosphate PEP, phosphoenol pyruvate X5P, D-xylulose-5-phosphate.
3.2. D-Lactate

D-lactate is widely used as a specialty chemical in the food and pharmaceutical industry. It can also be combined with L-lactate for the production of polylactic acid (PLA), an increasingly popular biorenewable and biodegradable plastic [99, 100] whose commercial success obviously depends on the production cost. Although glucose is the current substrate for fermentative production of lactate, it is desirable to produce this commodity chemical from lignocellulosic feedstock, which contains a mixture of sugars. Some lactic acid bacteria have the desirable native ability to produce large amount of D-lactate under low pH condition, where the low pH reduces the process cost [101, 102]. However, these lactic acid bacteria require complex nutrients, and many of them lack the ability to ferment pentose sugars. The lactic acid bacteria that do ferment pentose sugars unfortunately produce a mixture of lactate and acetate and, thus, are not a good chassis for commercial production of D-lactate. While E. coli can ferment many sugars effectively in a simple mineral salts medium, inherent D-lactate productivity is low and other undesirable metabolites are also produced [103]. Therefore, the E. coli metabolic system was redesigned to attain the desired properties of high yield and productivity of D-lactate.

E. coli strain W3110 was used as the chassis for D-lactate production with a redesign strategy that focused on inactivation of competitive fermentation pathways [104]. After deleting the genes encoding fumarate reductase (frdABCD), alcohol/aldehyde dehydrogenase (adhE), pyruvate formate lyase (pflB), and acetate kinase (ackA), the resulting strain, SZ63, can only oxidize NADH via D-lactate synthesis (Figure 4(b)). Although this strain could completely utilize 5% (w/v) glucose in a mineral salts medium with a yield near theoretical maximum (96%), the volumetric D-lactate productivity of 0.42 g/L/h was relatively low compared with lactic acid bacteria [35]. In addition, this strain can neither utilize sucrose nor completely utilize 10% (w/v) sugar [35]. Therefore, an E. coli W derivative strain was chosen as chassis for more robust D-lactate production [35, 105]. After redesigning central metabolism so that D-lactate production was the sole means of oxidizing NADH, metabolic evolution was used to further improve cell growth and D-lactate productivity. The resulting strain, SZ194, efficiently consumed 12% (w/v) glucose in mineral salts medium and produced 110 g/L D-lactate [105] with a volumetric productivity of 2.14 g/L/h, a 5-fold increase over the W3110 derivative. The biocatalyst was further optimized by deleting methylglyoxal synthase gene (mgsA) to eliminate L-lactate production, and by metabolic evolution to increase yield and productivity. The final D-lactate producing strain, TG114, could convert 12% (w/v) glucose to 118 g/L D-lactate with an excellent yield (98%) and productivity (2.88 g/L/h) [22].

3.3. Acetate

Acetate is a commodity chemical with 2001 worldwide production estimated at 6.8 million metric tons [23]. Biological production of acetate accounts for only 10% of world production, mainly in the form of vinegar, with the remainder of production through petrochemical routes [106–108]. Biological production of commodity chemicals has historically focused on anaerobic production of reduced products, since substrate loss as cell mass and CO2 is minimal and product yields are high. Contrastingly, acetate is an oxidized chemical, and traditional biological production involves a complex two-stage process: fermentation of sugars to ethanol by Saccharomyces, followed by aerobic oxidation of ethanol to acetate by Acetobacter [106–108]. To enable microbial production of redox-neutral or oxidized products at high yield, the biocatalyst metabolism needs to be redesigned to combine attributes of both fermentative and oxidative metabolisms.

Redesign of E. coli W3110 metabolism for acetate production focused on three major pathways: fermentative metabolism, oxidative metabolism, and energy supply (Figure 4(c)) [23]. The competitive fermentation pathways (pflB, ldhA, frd, adhE) were inactivated to prevent the consumption of common precursor pyruvate, and the oxidative tricarboxylic acid (TCA) cycle was interrupted to reduce the carbon loss as CO2. Finally, oxidative phosphorylation was disrupted (atpFH) to reduce ATP production while maintaining the ability to oxidize NADH by the electron transport system, thus increasing the glycolytic flux for more ATP production through substrate-level phosphorylation. Although rationally designed, the resulting strain, TC32, had an undesirable auxotrophic requirement for succinate during growth in glucose-minimal medium. Evolution was used to eliminate this auxotrophy and the final strain, TC36, produced 878 mM acetate (53 g/L) in mineral salts medium with 75% of the maximal theoretical yield. Although this is a lower titer than acetate produced from ethanol oxidation by Acetobacter, TC36 has a two-fold higher production rate, requires only mineral salts medium, and can metabolize a wide range of carbon sources in a simple one-step process [23].

3.4. Others

Butanol is an excellent alternative transportation fuel with several advantages compared to ethanol, including higher-energy content, lower volatility, less hydroscopicity, and less corrosivity [109]. Redesign of E. coli for butanol production is discussed below. C. acetobutylicum ATCC 824 naturally produces butanol and was redesigned to increase butanol production and decrease coproduct accumulation. Metabolic engineering-type modifications, such as overexpression of the acetone formation pathway to increase formation of butanol precursor butyryl-CoA, inactivation of the transcriptional repressor SolR, and overexpression of alcohol/aldehyde dehydrogenase all increased butanol production [110–112]. In an excellent example of synthetic biology-type applications, expression of the butyrate kinase gene was fine-tuned by a rationally designed antisense RNA to increase butanol production [113].

1,2-propanediol (1,2-PD) is a major commodity chemical currently derived from propylene. E. coli naturally produces low amounts of 1,2-PD, and therefore its metabolism was redesigned to produce 1,2-PD at high yield and titer from glucose this was achieved by inactivation of competing pathways (lactate dehydrogenase and glyoxalase I), and overexpression of essential genes of 1,2-PD synthetic pathway (methylglyoxal synthase, glycerol dehydrogenase, and 1,2-PD oxidoreductase) [114]. Evolution was also used in combination with rational design for increased 1,2-PD production [115].

L-valine, an essential hydrophobic and branched-chain amino acid, is used in cosmetics, pharmaceuticals, and animal feed additives [116]. E. coli was redesigned for L-valine production at high yield and titer from glucose through a combination of traditional metabolic engineering and synthetic biology. Traditional metabolic engineering was used to inactivate competing pathways and overexpress acetohydroxy acid synthase I (ilvBN), part of the valine biosynthesis pathway. Unfortunately, the E. coli chassis has regulatory elements that tightly control L-valine biosynthesis, making production of valine at high yield and titer difficult. Feedback inhibition was eliminated by rational site-directed mutagenesis of acetohydroxy acid synthase III. In an excellent demonstration of the gene expression tuning techniques discussed above, transcriptional attenuation of valine biosynthesis genes ilvGMEDA was eliminated by replacing the attenuator leader region with the constitutive tac promoter. Transcriptome analysis and in silico simulation guided selection of additional target genes for amplification and deletion, and the final biocatalyst produced 0.378 g L-valine per g glucose, giving a titer of 7.55 g/L valine from 20%(w/v) glucose [116]. A similar strategy was also used for L-threonine production [117].

4. Redesign through Introduction of Foreign or Nonnatural Pathways

4.1. Foreign Pathways
4.1.1. Ethanol

Ethanol is a renewable transportation fuel. Replacement of gasoline with ethanol would significantly reduce US import oil dependency, increase the national security, and reduce environmental pollution [118]. However, only 9 billion gallons of ethanol were produced in 2008, and all were from corn-based production. Lignocellulose is generally regarded as an excellent source of sugars for conversion into fuel ethanol. It is, thus, desirable to design or obtain biocatalysts that can utilize all the sugar components in lignocellulose and convert them to ethanol with high yield and productivity in mineral salts medium. Native S. cerevisiae and Z. mobilis strains can efficiently convert glucose to ethanol, but cannot utilize pentose sugars. In contrast, E. coli strains can utilize all the sugar components of lignocelluloses but ethanol is only a minor fermentation product, with mixed acids accumulating as the major fermentation product [103]. While recent advances have been made engineering the native E. coli metabolic pathways for ethanol production [119], the most successful example used a foreign metabolic pathway to enable ethanol production from E. coli strain W (ATCC# 9637) [1].

Redesign for ethanol production was decoupled to three parts: construction of a metabolic pathway for production of ethanol as the major fermentation product, elimination of competitive NADH oxidization pathways, and disruption of side-product formation. The Z. mobilis homoethanol pathway (pyruvate decarboxylase and alcohol dehydrogenase) was introduced as a foreign pathway, enabling redox-balanced production of ethanol at high yield [120] (Figure 4(b)). Then fumarate reductase (frd) was disrupted to increase ethanol yield. The resulting strain, KO11, produced ethanol at a yield of 95% in a complex medium [121]. This strain was developed at the dawn of metabolic engineering and has been used to produce ethanol from a variety of lignocellulosic materials, as reviewed in [1].

Although the ethanol production rate of KO11 was as high as yeast, the ethanol tolerance and performance in minimal medium did not meet the desired standards. Therefore strain SZ110, a derivative of KO11 modified for lactate production in mineral salts media [35], was redesigned for ethanol production [122]. As with the design of KO11, redesign of SZ110 was decoupled to construction of an ethanol synthetic pathway, elimination of competitive NADH oxidization pathways, and blockage of side-product formation. However, this redesign strategy also included the acceleration of mixed sugar co-utilization. The lactate producing pathway was disrupted and the Z. mobilis homoethanol pathway was integrated into the chromosome by random insertion to select for optimal expression. The Pseudomonas putida short-chain esterase (estZ) [123] was introduced to decrease ethyl acetate levels in the fermentation broth and decrease the downstream purification cost. In addition, methylglyoxal synthase (mgsA) was inactivated, resulting in co-metabolism of glucose and xylose, and accelerated the metabolism of a 5-sugar mixture (mannose, glucose, arabinose, xylose, and galactose) to ethanol [25]. After using evolution to increase cell growth and production, the final strain, LY168, could concurrently metabolize a complex combination of the five principal sugars present in lignocellulosic biomass with a high yield and productivity in mineral salts medium [25].

4.1.2. L-Lactate

As described above, L-lactate is the major component of the biodegradable plastic PLA. Although many lactic acid bacteria produce L-lactate with high yield and productivity [124], they usually require complex nutrients. E. coli does not have a native pathway for L-lactate production, and therefore introduction of a foreign pathway was necessary.

The strategy for redesigning E. coli W3110 for L-lactate production was to eliminate competitive NADH oxidization pathways and then construct the desired L-lactate synthetic pathway (Figure 4(b)) [125]. The L-lactate production pathway, L-lactate dehydrogenase (ldhL) from Pediococcus acidilactici, was used and its coding region and terminator were integrated into the E. coli chromosome at the ldhA site, so that ldhL could be expressed under the native ldhA promoter. In addition, since the ldhL gene contains a weak ribosomal-binding region, this region was rationally replaced with ldhA’s RBS [125]. Following a period of metabolic evolution, the resulting strain, SZ85, synthesized 45 g/L L-lactate in a mineral salts medium with yield near theoretical maximum (94%). However, this strain was a K-12 derivative and displayed the same problems seen with the K12-based D-lactate-producing strain described above, meaning that it was unable to completely ferment high sugar concentrations and had a low productivity (0.65 g/L/h). Therefore, the same design strategy was implemented in an E. coli W (ATCC# 9637) derivative. After further deleting mgsA gene to improve chiral purity and using metabolic evolution to improve cell growth and productivity, the final L-lactate-producing strain, TG108, could convert 12% glucose to 116 g/L L-lactate with an excellent yield (98%) and productivity (2.29 g/L/h) [22].

4.1.3. Xylitol

The pentahydroxy sugar alcohol xylitol is commonly used to replace sucrose in food and as a natural, non-nutritive sweetener that inhibits dental caries [126]. Xylitol can also be used as a building block for synthesizing new polymers [127]. Current xylitol commercial production involves hydrogenation of hemicellulose-derived xylose with an active metal catalyst [127]. Biological-based processes have also recently been developed, but although high xylitol titer was achieved by some yeast, the process requires complex medium with numerous expensive vitamin supplements [128]. While E. coli does not have the native capability to synthesize xylitol, a redesign strategy for strain W3110 was proposed involving a foreign metabolic pathway [26]. In the proposed redesign, glucose would support cell growth and provide reducing equivalents, while xylose would be used as substrate for xylitol synthesis (Figure 4(d)). The design strategy consisted of three major components: enabling co-utilization of glucose and xylose, separation of xylose metabolism from central metabolism, and construction of a xylitol production pathway (Figure 4(d)). In order to enable co-utilization of glucose and xylose, glucose-mediated repression of xylose metabolism was eliminated by replacing the native crp gene with a cAMP-independent mutant (CRP*). Xylose metabolism was separated from central metabolism by deleting the xylulokinase (xylB) gene, preventing the loss of xylose carbon to central metabolism. Finally, xylose reductase and xylitol dehydrogenase from several microorganisms were tested for xylitol synthetic capability, and the NADPH-dependent xylose reductase from C. boidinii (CbXR) was found to support optimal xylitol production. The final strain, PC09 (CbXR), could produce 250 mM (38 g/L) xylitol in mineral salts medium. The yield was 1.7 mol xylitol per mol glucose consumed, which was improved to 4.7 mol/mol by using resting cells. It was proposed that xylitol production could be further improved by increasing supply of reducing equivalents [129].

4.1.4. L-Alanine

L-alanine can be used with other L-amino acids as a pre- and postoperative nutrition therapy in pharmaceutical and veterinary applications [130]. It is also used as a food additive because of its sweet taste. The annual worldwide production of L-alanine is around 500 tons [131], and this market is currently limited by production costs. The current commercial production process converts aspartate to alanine via aspartate decarboxylase, where aspartate is produced from fumarate by aspartate ammonia-lyase catalysis [27]. An efficient fermentative process with a renewable feedstock such as glucose offers the potential to reduce L-alanine cost and facilitate a broad expansion of the alanine market into other products.

SZ194, a derivative of E. coli W (ATCC# 9637) that was previously engineered for D-lactate production, was used as the chassis for L-alanine production [27] (Figure 4(b)). Alanine production in the native strain uses glutamate- and NADPH-dependent glutamate-pyruvate aminotransferase. It is preferable to produce L-alanine directly from pyruvate and ammonia using an NADH-dependent enzyme, and therefore L-alanine dehydrogenase (alaD) of Geobacillus stearothermophilus was employed. The native ribosome binding site, coding region, and terminator of alaD gene were integrated into the E. coli chromosome at the ldhA site, so that expression of alaD could be controlled by the native promoter of ldhA, a promoter that has worked well for production of D- and L-lactate, as described above. Further redesign focused on elimination of trace amounts of lactate and increasing the L-alanine chiral purity by deleting mgsA and the major alanine racemase gene (dadX). Metabolic evolution increased the final titer and productivity by 15- and 30-fold, respectively (Figure 3). The latest L-alanine producing strain, XZ132, converted 12% glucose to 114 g/L L-alanine with a 95% yield and the excellent volumetric productivity of 2.38 g/L/h [27].

4.1.5. Combining Multiple Foreign Pathways in a Single Chassis

Although the work described above relied on the introduction of a single foreign pathway, there are other excellent examples that employ pathways from more than one organism in a single host.

E. coli was redesigned for 1,3-propanediol production using S. cerevisiae pathway to convert glucose to glycerol and a K. pneumonia pathway to convert glycerol to 1,3-propanediol [132]. E. coli was also redesigned for isopropanol production by combining acetyl CoA acetyltransferase (thl) and acetoacetate decarboxylase (adc) from C. acetobutylicum with the second alcohol dehydrogenase (adh) from C. beijerinckii and E. coli’s own acetoacetyl-CoA transferase (atoAD) [133]. Artemisinic acid, a precursor of antimalarial drug artemisin, was produced by E. coli following the combination of a mevalonate pathway from S. cerevisiae and E. coli, amorphadiene synthase, and a novel cytochrome P450 monooxygenase (CYP71AV1) from Artemisia annua [12, 134].

S. cerevisiae was redesigned for flavanone production by combining Arabidopsis thaliana cinnamate 4-hydroxylase (C4H), Petroselinum crispum 4-coumaroyl: CoA-ligase (4CL), and Petunia chalcone synthase (CHS), Petunia chalcone isomerase (CHI) [135]. A similar synthetic system producing hydroxylated flavonols was also constructed in E. coli with additional amplification of C. roseus P450 flavonoid

-hydroxylase (F H) fused with P450 reductase, Malus domestica flavanone 3β-hydroxylase (FHT), and Arabidopsis thaliana flavonol synthase (FLS) [136]. The flavonoid production was significantly increased through further redesigning of the central metabolic system of E. coli to increase precursor (Malonyl-CoA) supply [137].

4.2. Modification of Natural Pathways for Production of Unnatural Compounds

One of the goals of synthetic biology is to design or construct new genetic circuits. In the examples given thus far, existing biological parts have been reassembled to engineer a biocatalyst that efficiently produces a product that already exists in nature. However, metabolic pathways can also be constructed to produce unnatural compounds.

As discussed above, directed evolution of proteins can modify their activity such that new substrates are recognized or new products are formed [138]. For example, novel carotenoid compounds were generated by evolution of two key carotenoid synthetic enzymes, phytoene desaturase, and lycopene cyclase [139]. Additionally, combinatorial biosynthesis, which combines genes from different organisms into a heterologous host, can also generate new products [140]. For example, four previously unknown carotenoids were produced by combinatorial biosynthesis in E. coli [141].

4.3. De Novo Pathway Design

In order to broaden the available biosynthesis space, it is essential to go beyond the natural pathways and design pathways de novo [142]. Although this exciting design strategy still has many challenges, several successful examples have been reported.

For example, a synthetic pathway for 3-hydroxypropionic acid (3-HP) production was designed involving the unnatural isomerization of α-alanine to β-alanine, as mentioned above. In this example the researchers used directed evolution to expand the substrate specificity of lysine 2,3-aminomutase to include α-alanine [73]. The resulting β-alanine can then be converted to 3-HP through existing metabolic pathways.

Unnatural pathways for higher alcohol production in E. coli were designed by combining the native amino acid synthetic pathways with a 2-keto acid decarboxylase from Lactococcus lactis and alcohol dehydrogenase from S. cerevisiae [143]. The 2-keto acid intermediates in amino acid biosynthesis pathways were redirected from amino acid production to alcohol production, enabling production of 3-methyl-1-pentanol. This pathway was then expanded for production of unnatural alcohols by rational redesign of two enzymes, with the resulting biocatalysts having the ability to synthesize various unnatural alcohols ranging in length from five to eight carbons [144].

4.4. Engineering Tolerance to Inhibitory Compounds

As our repertoire of biologically-produced compounds increases, tolerance to high product titers becomes more important. Biofuels, such as ethanol and butanol, can inhibit biocatalyst growth, and therefore the tolerance of the biocatalyst needs to be improved [145–147]. As described above, our goal is to use lignocellulosic biomass as a substrate for production of commodity fuels and chemicals. Unfortunately, the processes used to convert biomass to soluble sugars also produce a mixture of minor products, such as furfural and acetic acid, that inhibit biocatalyst metabolism [148]. Although most of these inhibitors could be removed by detoxification [149], this additional process would increase operational cost. It is, thus, desirable to obtain microorganisms that are tolerant to these inhibitors and can directly ferment hemicellulose hydrolysate.

One approach to increasing tolerance is to understand the mechanism of inhibition. Transcriptome analysis has been used to probe the response to ethanol [145, 150], furfural [151], and butanol [147]. Another approach is to use directed evolution, as highlighted by the following example. Ethanologenic E. coli strain LY180 (a derivative of LY168 with restored lactose utilization and integration of an endoglucanase, and cellobiose utilization) was used as the chassis to select for furfural resistance through evolution [148]. The evolved strain, EMFR9, had significantly increased furfural resistance. Reverse engineering efforts, including transcriptome analysis, attributed furfural resistance to the silencing expression of several oxidoreductases. These oxidoreductases use NADPH for furfural reduction, depleting the available pools for biosynthesis. Thus furfural-mediated growth inhibition can be attributed to NADPH depletion [148], an insight that can be applied to other biocatalyst design projects.

5. Perspectives

Although many biocatalysts have been successfully redesigned for production of industrially important fuels and chemicals through traditional metabolic engineering, we are just beginning to see the potential of synthetic biology in this area. One of the foremost goals in our lab is the improvement of biocatalysts for biomass utilization. To attain this goal, tolerance to hydrolysate-derived inhibitors needs to be improved. For all applications, tolerance to high substrate and product titers is also important. This goal of redesigning a biocatalyst’s phenotype, that is, tolerance, is not as clear as redesigning metabolism and a rational redesign strategy is particularly difficult when the mechanism of inhibition is not known.

As the understanding of our biocatalysts improves, particularly through reverse engineering of evolved strains, genome-scale models can be improved. Inclusion of kinetic and regulatory effects will also improve the accuracy and predictive power of these models. Note that some models have recently been developed that bypass the need for kinetic data, though [152]. Since enzymes are the major functional part performing the metabolic synthesis, improved protein engineering tools and new protein catalytic capability will aid in advancement of this field. It is important to generate high-quality protein mutagenesis libraries (relatively small libraries with a high diversity of enzymes) to facilitate efficient screening efforts [138]. Direct screening from metagenomic libraries of environmental samples can aid in isolation of enzymes with new functions, which cannot be obtained by the traditional strain isolation methods [153]. Enzymes can even be synthesized from scratch by a rational design strategy with computational aid [154]. Finally, new tools for better de novo design of synthetic pathways need to be developed. Several databases, such as BNICE (Biochemical Network Integrated Computational Explorer) [155] and ReBiT (Retro-Biosynthesis Tool) [142], have already been established to facilitate identification of enzymes to construct a complete synthetic pathway for producing target compounds. It is important to establish guidelines, such as redox balance, energy production, and thermodynamic feasibility, to screen among these enormous pathways for the optimal routes.

By including synthetic biology tools in metabolic engineering projects, and vice versa, these two fields can significantly advance the replacement of petroleum-derived commodity products with those produced from biorenewable carbon and energy.

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Copyright

Copyright © 2010 Laura R. Jarboe et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Future Height Control Techniques

Mechanical Conditioning. It has been known for a long time that mechanical stresses such as repeated brushing, shaking, or bending caused by air movement or contact with animate or inanimate objects can reduce plant growth. Recent research conducted by Dr. Joyce Latimer at the University of Georgia has demonstrated the commercial potential of this technique for controlling the height of vegetable transplants, particularly tomato. This work was stimulated, in part, by the fact that B- Nine is no longer registered for use on edible crops. One system of mechanical conditioning adapted to commercial greenhouses involves drawing a bar across the

Figure 2. Growth of marigold is affected by when fertilizer is withheld for short periods at different times during the crop.

tops of the plants once or twice a day. The bar is set low enough to contact the plants, but not so low that the plants are injured or uprooted. Thirty to 40% reductions in height have been reported with this system. Other systems involve periodic shaking, blowing air treatments, or water sprays. For this to become useful to flower growers research is needed to determine the response of flower crops.

Light filters. Plant physiologists have found that changing the ratio of red to far-red light can influence stem elongation and branching. Red light inhibits stem elongation compared to far-red light which promotes stem elongation. Red light also promotes branching by stimulating lateral bud growth. In nature there are daily and seasonal changes in the red:far-red ratio. Natural light in the middle of the day and in the summer has a higher proportion of red than sunrise and sunset and the winter. The shading effect of plant canopies also changes the ratio increasing the proportion of far-red light. This is an important factor in why plants stretch when they are spaced too closely. Current research is being directed at developing greenhouse coverings which alter the red:far-red balance to control plant height and branching.


Why is it desirable to couple chemical production to growth? - Biology

Living things grow and they reproduce. Growth is a way to generate the materials for reproduction. Reproduction is a way to make new organisms that can grow. Thus, the apparent "goal" of every organism is to fill the available world with its offspring, that is, with "self". It has been suggested that each unit of inheritance itself, each gene, is selfish in this way. It acts in such a way as to increase its chances to spread to all available individuals of a population. If other genes are helpful in this, good. If not, don't collaborate.

The mindless drive toward expansion that is the hallmark of living things is a program invented early in life history. It has proven very successful. (It was reinvented by the free market as a successful program for organizations living in the economic world.) The goal of the program can never be achieved, because organisms depend on each other for their existence. Thus, there is a "negative feedback" on the growth of every organism which keeps things in balance, sort of. Humans, lately, have been especially successful in avoiding or neutralizing negative feedback on population growth (such as disease or lack of food). As a result, they have discovered that the environment loses desirable properties as it is filled with people, and that resources become scarce. This discovery has given rise to the notion of "sustainable development", which may be translated as "growth without the negative consequences." It remains to be seen whether the mindless drive toward expansion that we share with all other organisms can be checked by intelligent internal feedback before it is halted by lack of resources.

All growth depends on the appropriation of outside matter, that is, on "eating" in some fashion. Ecologists have classified the various ways organisms eat (all in Greek, for style):

Organisms eating others (other-eaters) are called "hetero-trophs". If this happens in an oxygenated environment and oxygen is used to "burn" the food, we speak of "aerobic respiration." We humans are heterotrophs and we use aerobic respiration to maintain our bodies. (We breathe oxygen in and carbon dioxide out.) Other heterotrophs may use anaerobic respiration to process food (they strip the oxygen from molecules such as nitrate or sulfate) or they may use fermentation (they chop up the organic molecules and rearrange the parts, as does yeast). Organisms that feed themselves using sunlight to build new organic matter (self-feeders) are called photo-auto-trophs. Normally, oxygen is produced when doing this ("oxygenic photosynthesis") as described by the photosynthetic equation. A third way of making a living, other than eating others or feeding oneself using sunlight, is by using chemical gradients as an energy source for synthesis (rather than sunlight). Such organisms are called "chemo-auto-trophs". They are all microbes of a special class of bacteria in the broad sense ("archea") and have special adaptations to cope with chemically unusual environments (highly acidic, sulfur-rich, etc.). There are those that are "anaerobic" (that is, there is no molecular oxygen available) and those that are "aerobic" (that is, they use available molecular oxygen to change the local chemistry and produce energy). Among the anaerobic forms are methane and sulfide producers, for example. (Methane is formed in the guts of cattle sulfide produces the rotten-egg smell). Among the aerobic forms are sulfide oxidizers and iron oxidizers. (The former produce the acidic runoff from mines. The latter produce rust on wet rocks.)


Tired of Seeing Buttercup in Your Pasture?

Tired of looking out across your pastures/hay fields and seeing that “sea of yellow” every spring? One of the signs that spring has arrived is when the yellow flowers of buttercup begin to appear, but it’s during the winter months that the vegetative growth of buttercup takes place. As a cool season weed, this plant often flourishes in over grazed pasture fields with poor stands of desirable forages. In fact, many fields that have dense buttercup populations are fields heavily grazed by animals during the fall through the early spring months. Buttercups are sometimes classified as short-lived perennials, but often grow as winter annuals.

Buttercup is toxic to all species of livestock. The toxin protanemonin is released when the plant is chewed or otherwise wounded and is present in all parts of the plant. Animals that eat buttercup may suffer from blistering of the mouth and internal parts of the gastrointestinal tract, diarrhea, colic, and, in severe cases, death. Fortunately, most animals will not eat buttercup because it is unpalatable. The toxin become inactivated when dried so buttercup is not a concern in hay.

Most buttercup plants emerge from seed during the fall or late winter months. Therefore, pasture management practices that improve and promote growth of desirable plants during these months is one of the best methods to help compete against the emergence and growth of this plant. Mowing fields or clipping plants close to the ground in the early spring before buttercup plants can produce flowers may help reduce the amount of new seed produced, but mowing alone will not totally eliminate seed production.

For chemical control, herbicides registered for use on grass pastures that contain 2,4-D will effectively control buttercup. Depending on other weeds present products that contain dicamba+2,4-D (eg. Weedmaster), aminopyralid (eg. ForeFront, Milestone), triclopyr (eg. PastureGard, Crossbow), or metsulfuron (eg. Cimarron) can also be used. However, legumes such as clovers interseeded with grass pastures can be severely injured or killed by these herbicide products. For optimum results, apply a herbicide in the early spring (February – April) before flowers are observed, when buttercup plants are still small and actively growing. For best herbicide activity, wait until daytime air temperatures are greater than 50 F for two to three consecutive days. When determining which product is best for your operation, be sure to read product labels to find out the details about grazing and haying restrictions as they vary widely between these products

An effective weed control program is essential to establishing and maintaining highly productive pastures and animal performance. We need to remember that “An ounce of prevention is worth a pound of cure.” Select well-adapted grass and/or legume species that will grow and establish rapidly. This will minimize the length of time for weeds to invade easily. Lime and fertilize according to soil test recommendations. Proper pH and nutrient status will help insure that the forage will grow rapidly and be more competitive with weeds. Manage grazing properly. Overgrazing is a common cause of weed problems. Heavy grazing pressure may favor weed growth over grass. Identify weed problems and location and select which option or combination of options you plan to use for weed control (mechanical, chemical, or grazing management), but the most important is to put it in practice and evaluate the outcome.

Mississippi State Cooperative Extension

Maryland Cooperative Extension


Sucrose Molecule

Click image to enlarge

Figure 1. Sucrose is produced from the chemical reaction between two simple sugars called glucose and fructose.

Anthony Fernandez

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Figure 2. Space-filling model of a sucrose molecule

Shutterstock

In a sugar crystal, the sucrose molecules are arranged in a repeating pattern that extends in all three dimensions, and all of these molecules are attracted to each other by intermolecular forces—a type of interaction that binds molecules together and is weaker than the bonds between atoms in a molecule.

When you add granulated sugar to water, some of the sucrose molecules start separating from one another because they are attracted to the water molecules (Fig. 3). When water and sucrose molecules are close to each other, they interact through intermolecular forces that are similar to the intermolecular forces between sucrose molecules.

Click image to enlarge

Figure 3. When granulated sugar is added to water, it breaks apart because the water molecules are attracted to the sucrose molecules through intermolecular forces. As a result, each sucrose molecule is surrounded by water molecules and is carried off into the solution.

The dissolving process involves two steps: First, the water molecules bind to the sucrose molecules and second, the water molecules pull the sucrose molecules away from the crystal and into the solution.

In general, only a certain amount of a solid can be dissolved in water at a given volume and temperature. If we add more than that amount, no more of that solid will dissolve. At this stage, we say that the solution is saturated. The additional solid just falls to the bottom of the container.

Why is that so? If you were able to see the molecules of sucrose and water, you would notice that, in the beginning, when you add a small amount of granulated sugar to the water, most of the sucrose molecules are leaving the sugar crystals, pulled away by the water molecules. You would also notice that some of the dissolved sucrose molecules are also crystallizing, that is, not only are sucrose molecules leaving the sugar crystals but other sucrose molecules are rejoining the sugar crystals, as well (Fig. 4). The reason is that sucrose molecules are constantly moving in the solution, so nothing prevents some of them from binding again to sucrose molecules in the sugar crystals. However, the rate of dissolving is greater than the rate of crystallization—at least until the solution is saturated—so, overall, the sugar crystals remain dissolved in the water.

Click image to enlarge

Figure 4. When a sugar crystal is added to a cup of water, some sucrose molecules separate from the crystal while others join the crystal. Whether the crystal dissolves in water or grows in size is determined by comparing the relative number of sucrose molecules dissolving and leaving the crystal with the number of sucrose molecules leaving the solution and joining the crystal.

As we add more granulated sugar to the solution, the rate of dissolving decreases and the rate of crystallization increases, so at some point, both rates are equal. In other words, the number of sucrose molecules leaving the crystals is the same as the number of sucrose molecules joining the crystals. This is what happens when the solution is saturated.

As a result, past that point, if we add more sugar crystals, the process of dissolving will continue, but it will be exactly balanced by the process of recrystallization. So the sugar crystals cannot dissolve in the water anymore. In this case, the crystals and the solution are in dynamic equilibrium. This means that the size of the crystals stays the same, even though the sucrose molecules are constantly trading places between the solution and the crystals.

To make rock candy, we initially used more sugar than could dissolve in water at room temperature (three cups of sugar for one cup of water). The only way to get all of that sugar to dissolve is to heat up the water, because increasing the temperature causes more sugar to dissolve in water. In other words, the dynamic equilibrium is affected by a change in temperature. If we increase the temperature, we increase the dissolving process, and if we reduce the temperature, we decrease the dissolving process.

The crystallization process is explained by Le Châtelier’s principle, which states that a system that is shifted away from equilibrium acts to restore equilibrium by reacting in opposition to the shift. So an increase in temperature causes the system to decrease energy, in an attempt to bring the temperature down. Because the breakup of chemical bonds always absorbs energy, it cools the system down, so more sucrose molecules break apart and dissolve in the solution.

What happens when the solution cools down? At this point, we see sugar crystals form. This is also explained by Le Châtelier’s principle: A decrease in temperature causes a system to generate energy, in an attempt to bring the temperature up. Because the formation of chemical bonds always releases energy, more sucrose molecules will join the crystal in an attempt to increase the temperature. This explains why crystals form when the temperature decreases.

Once the saturated solution starts to cool down, it becomes supersaturated. A supersaturated solution is unstable—it contains more solute (in this case, sugar) than can stay in solution—so as the temperature decreases, the sugar comes out of the solution, forming crystals. The lower the temperature, the more molecules join the sugar crystals, and that is how rock candy is created.


What does it mean for investors?

If you take a step back and evaluate each claim Intrexon has made about its gas fermentation platform, the promised game-changing status of the technology begins to lose its luster. The company makes poor comparisons to existing technologies and doesn't seem to have any real advantage for making at least three of the four chemicals it's currently developing.

By the time the company is at production scale for 1,4-BDO and 2,3-BDO -- years from now -- it's likely that existing processes using traditional fermentation will have already gained significant market share and driven down their process costs below that of conventional petrochemical processes. Other chemicals in the crosshairs are already mass produced at healthy margins and don't come with the technical risk of a novel gas fermentation process. So although Intrexon's vision sounds great on paper, there are quite a few obstacles investors, management, and Wall Street analysts seem to be overlooking.


Watch the video: Im Positive 2019. An open discussion with school students on HIV (July 2022).


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