SHORT PROJECT SUMMARY
We designed...
-
Fatty acid-based compounds (oleochemicals) are important building blocks in the manufacturing of a wide range of industrial products
-
The physicochemical properties of oleochemicals are heavily dependent on the fatty acid chain length.
-
In our system design, the native fatty acid synthase of Saccharomyces cerevisiae is functionally replaced with a bacterial fatty acids synthase pathway from Escherichia coli.
-
This facilitates the tunable regulation of the length of the fatty acid acyl chains by tuning the expression of three thioesterases (the enzymes responsible for terminating the growth of the chain).
- Tunable gene expression is accomplished using a combination of three transcription factor-based chemical induction systems based on copper ions, tetracycline, and estradiol.
Our progress and results...
-
We successfully integrated 6 out of 8 genes of required genes (but unfortunately did not succeed in integrating the remaining 2), preventing us from testing the fully functional system.
-
All three transcription factor-based induction systems were benchmarked individually, and in combination, using fluorescent proteins. Results indicating that the system is tunable as intended.
- All parts we designed have been uploaded to the iGEM Parts Registry.
BACKGROUND
Why fatty acids?
Fatty acids (FA) and their derived compounds (also referred to as oleochemicals) are important building blocks in the manufacturing of a wide range of industrial products including plastics, fuels, paints, detergents, lubricants, personal care-, and pharmaceutical compounds. Their usefulness as base chemicals stems from their versatile chemistry that allows a myriad of derivatizations (Desroches et al., 2012; Dyer et al., 2008; Maisonneuve et al., 2013). The physiochemical properties of oleochemicals are heavily dependent on chain-length and can be influenced by incorporation of branches and other chemical modifications. Control of chain length would allow us to obtain a number of high-value products (Carlsson, 2009; Nosal et al., 2021; Ramos et al., 2009). In the section below we summarize several key oleochemicals and highlight their application areas.
Environmental impact and the increasing demand for oleochemicals
In the context of an uncertain supply and the environmental impact of using petroleum resources there is an urgent need to find alternative manufacturing processes for oleochemicals. While renewable plant oils have largely replaced petroleum a source for many types of oleochemicals, these are often major drivers of deforestation and biodiversity loss and compete with traditional food-crops for arable land (Carlsson, 2009; Gibbs et al., 2010; Shukla et al., 2019). The majority of plant oils are produced from just four crops: oil palm, soybeans, rapeseed and sunflower, which together account for approximately 79% of the total world production (Ritchie & Roser, 2021). Palm oil (mainly produced in Indonesia and Malaysia) accounts for 30 % of the world total (and is expected to grow by about 4% annually) and is a controversial feedstock material due to high levels of deforestation, and allegations of human rights violations among growers (Gilbert, 2012; Rival & Levang, 2014; Saxon & Roquemore, 2011). Soybean oil is the second-most-widely produced oil in the world (made and used extensively in the United States, Brazil, Argentina, and China). Its rapid market growth has been supported by its use as a feedstock in biodiesel production (Cavalett & Ortega, 2010). The total greenhouse gas emissions from Brazilian soy exports between 2010-2015 was estimated at 223.46 Mt and directly linked to the conversion of natural vegetation into arable land (Escobar et al., 2020; Zalles et al., 2019). The global FAs market is forecast to reach 48.46 billion USD by 2027 and the increasing demand for plant oils urgently promotes the need to find manufacturing methods that are both renewable and sustainable (Reports and Data, 2020). This would significant further the efforts towards a sustainable bio-based economy.
Challenges using plant oil as a source of oleochemicals
Plant oils consist almost entirely of triglycerides (TAG) esters, containing three FAs with varying chain lengths depending on the source (with 16 and 18 carbons being the most common). The value and application of an oil are determined largely by its FA composition. Due to their natural composition and limitations of current processing methods, the number of FA types that can be separated from plant oil is limited. The specific plant source can greatly affect the properties of the final product, due to it containing a mix of different chain lengths. Most vegetable oils contain just five basic FA structures; palmitic-, stearic-, oleic-, linoleic- and linolenic acid (Dyer et al., 2008).
Mixed with these are minor variants with chain lengths ranging between 8 and 24 carbons, containing varying numbers of double bonds, conjugated systems and other functional groups (Carlsson, 2009). Economically viable grades of FAs in many applications are composed of a ranged mixture of different chain lengths, resulting in a problem for their use in more specific applications. In many areas of industry and commercial products, broad cuts of FAs mixtures are employed, rather than chemically pure individual FAs.
Developing an effective, environmentally responsible, and economically viable extraction procedure for FAs with specific chain lengths is critical to ensure the success of subsequent derivatization and processing steps, and the sustainability of the entire production procedure.
FA composition based on chain length
Crop | 14:0 | 16:0 | 18:0 | 18:1 | 18:2 | 18:3 | 20:1 |
---|---|---|---|---|---|---|---|
Palm oil (Elaeis oleifera) | 5 | 36 | 2 | 50 | 8 | ||
Soybean oil (Glycine max) | 11 | 4 | 23 | 54 | 8 | ||
Canola oil (Brassica napus, Brassica rapa, or Brassica juncea) | 4 | 2 | 60 | 21 | 10 | 1 | |
Sunflower oil (Helianthus annuus) | 7 | 5 | 19 | 68 | |||
Linseed oil (Linum usitatissimum) | 6 | 2 | 19 | 24 | 47 |
Conventional manufacturing processes of oleochemicals from plant oils tend to be energy inefficient (requiring high temperatures and pressures), involve high acidity or alkalinity, and utilize a variety of hazardous solvent systems (including hexane, ethanol, methanol, chloroform, and butanol). Further, derivatization of FAs tends to rely on heavy metal catalysts. The current preferred technology for FA production is continuous high-pressure hydrolysis of fats and oils with superheated steam and has been in continuous use since the early 20th century. The process is usually carried out at around 250 °C at 3000–5000 kN/m2 pressure with sulfide or noble metal catalyst. This is a costly process due to the high energy input requirements in combination with the corrosive nature of the acids produced at these temperatures and pressures (Anneken et al., 2000; Guczi & Erdôhelyi, 2012). Methods using lipase enzymes as catalysts at mild conditions became available in the 1980s and are well suited for small-scale production of FAs, but are challenging for large-scale production due to problems of catalyst recovery and the low rate of attaining equilibrium in the reaction vessels (Daiha et al., 2015; Gandhi, 1997; Kubička, 2008). Another challenge in the production of FAs (which plant oils happen to share with petroleum) is the wide range of products made by the processes involved, with as many as 8-10 products being made at the same time with most of them sold into different markets, with different dynamics. While possibly supplying added value, this makes it difficult to balance the supply and the demand for all, or even most of the products by the frequently changing market demands. Given the tremendous industrial importance of oleochemicals, there is a need to decrease the world’s reliance on oleochemicals sourced from plant oil by finding alternative manufacturing methods for these types of compounds.
The future of oleochemicals from cell factories
The development of cell factories for the sustainable manufacturing of oleochemical is an enticing prospect. Using cell factories, it may be possible to produce a narrower range of FAs and oleochemicals from unspecific biomass as the feedstock, rather than unsustainable plant- or petroleum materials. Cell factories have the potential to address many of the challenges associated with plant-based supply chains. Cultivation of many microorganisms occurs over days and in closed environmental systems such as bioreactors, whereas plant production is often annually and regionally limited, and potentially allows more localized production, limiting the need for extensive transportation to maintain supply chains. In comparison with oleochemicals based on plant oils, cell factories allow greater consistency in product composition and purity profiles. Where plant-based production results in a mix of different acyl chain lengths (Carlsson, 2009), cell factories can be made compatible with renewable plant-based materials that can be grown on land not suitable for the cultivation of food crops. As previously noted, the use of edible oil in biochemical production has an influence on the global imbalance to the market demand and the food supply by their high prices, the reduction of food sources and the growth of commercial plant capacities. Thus, focus should be shifted to non-edible resources, which are not used in the human nutrition and could be grown in barren lands (Bozell & Petersen, 2010).
While the low abundance or yield of oleochemicals in wild microorganisms have rendered their isolation from such sources in many cases non-economically viable on an industrial scale, significant efforts have been put into finding genetic- and metabolic engineering strategies to increase production yields (Cravens et al., 2019; Ko et al., 2020; Nielsen & Keasling, 2016; T. Yu et al., 2018). The challenge is not only to design cell factories that can produce high yields, rates, and product titers of oleochemicals, but also to shorten the development time of each metabolic- and biosynthesis engineering design cycle, allowing cell factories to compete effectively with current petroleum-, and plant-based manufacturing processes as new markets develop.
The metabolism of natural producers with specific FA compositions are usually poorly understood, and they often lack immediate available tools for genetic modification available for model organism such as Saccharomyces cerevisiae and Escherichia coli. This makes them more difficult targets for engineering. Consequently, many new technologies depend on these well-known organisms by modifying existing biosynthesis pathways or introducing new ones (Calero & Nikel, 2019; Navarrete et al., 2020), showing great success in producing many highly-valuable target compounds such as complex opioids and vitamins (Galanie et al., 2015; Sun et al., 2019). Even as methods to produce and extract oleochemicals from microorganisms have been extensively explored (Marella et al., 2018; A.-Q. Yu et al., 2014) much of the current research has been focused on metabolic engineering to yield high-producing strains of one, or a few, number of structurally simple, low-molecular weight products such as such as aromatics, amines, terpenoids, terpenes, and esters (Calero & Nikel, 2019; Navarrete et al., 2020; Nielsen & Keasling, 2016). Although some natural products can be chemically synthesized - for example tunable synthesis of oleochemicals has been attempted using metal catalysts (Gollwitzer et al., 2017) - the complex structures of many of these compounds makes chemical synthesis either difficult or commercially infeasible (De Luca et al., 2012). The nature of biosynthesis in cell factories provide a promising route to generate a vast library of oleochemicals, even those difficult to extract, or not found in nature (Biermann et al., 2011; Nikolau et al., 2008).
While the low abundance or yield of oleochemicals in wild microorganisms have rendered their isolation from such sources in many cases non-economically viable on an industrial scale, significant efforts have been put into finding genetic- and metabolic engineering strategies to increase production yields (Cravens et al., 2019; Ko et al., 2020; Nielsen & Keasling, 2016; T. Yu et al., 2018). The challenge is not only to design cell factories that can produce high yields, rates, and product titers of oleochemicals, but also to shorten the development time of each metabolic- and biosynthesis engineering design cycle, allowing cell factories to compete effectively with current petroleum-, and plant-based manufacturing processes as new markets develop.
The metabolism of natural producers with specific FA compositions are usually poorly understood, and they often lack immediate available tools for genetic modification available for model organism such as Saccharomyces cerevisiae and Escherichia coli. This makes them more difficult targets for engineering. Consequently, many new technologies depend on these well-known organisms by modifying existing biosynthesis pathways or introducing new ones (Calero & Nikel, 2019; Navarrete et al., 2020), showing great success in producing many highly-valuable target compounds such as complex opioids and vitamins (Galanie et al., 2015; Sun et al., 2019). Even as methods to produce and extract oleochemicals from microorganisms have been extensively explored (Marella et al., 2018; A.-Q. Yu et al., 2014) much of the current research has been focused on metabolic engineering to yield high-producing strains of one, or a few, number of structurally simple, low-molecular weight products such as such as aromatics, amines, terpenoids, terpenes, and esters (Calero & Nikel, 2019; Navarrete et al., 2020; Nielsen & Keasling, 2016). Although some natural products can be chemically synthesized - for example tunable synthesis of oleochemicals has been attempted using metal catalysts (Gollwitzer et al., 2017) - the complex structures of many of these compounds makes chemical synthesis either difficult or commercially infeasible (De Luca et al., 2012). The nature of biosynthesis in cell factories provide a promising route to generate a vast library of oleochemicals, even those difficult to extract, or not found in nature (Biermann et al., 2011; Nikolau et al., 2008).
OUR PROJECT
Inspired by previous research from Fernandez‐Moya and colleagues in 2015 and the work conducted in collaboration with the Siewers Lab concerning yeast metabolism (Marella et al., 2018; Zhou et al., 2014, 2016), we decided to design a system that would allow us to regulate the chain lengths of FAs produced by S. cerevisiae (a large group that includes both laboratory and industrial strains).
The decision to use S. cerevisiae as a chassis instead of other well studied model organisms such as E. coli was based on its proven record as a reliable platform for industrial large-scale production of various compounds due to its robustness, genetic malleability, and tolerance towards harsh fermentation conditions (Parapouli et al., 2020), and some of the highest production titres of FAs in microbial fermentation have been reported for this organism (Fernandez-Moya & Da Silva, 2017; T. Yu et al., 2018). Being a model organism, substantial knowledge has been accumulated concerning the metabolism, genetics, and physiology of S. cerevisiae, with several well-established tools for genome engineering and fermentation technologies (Besada-Lombana et al., 2018; Lian, HamediRad, et al., 2018; Lian, Mishra, et al., 2018; Nevoigt, 2008). Working in a yeast lab with d irect access to knowledgeable experts who had worked with S. cerevisiae also played a part in our decision. To further explore the potential of this kind of system, we wanted to make it programmable by using a combination of different signaling agents.
Replacement of the native FA acid synthase system allows the chain lengths to be regulated
Fernandez‐Moya and colleagues in 2015 showed that the functional replacement of the S. cerevisiae FA synthase (FAS) with a bacterial type II system (eFAS) from E. coli allows the FA product profiles to be controlled by regulating the expression of different thioesterase (TE) enzymes.
S. cerevisiae produces cytosolic FAs de novo using a large barrel-shaped protein complex (2.6 MDa), consisting of two main subunits (α- and β) expressed by separate genes (FAS1 and FAS2, respectively). The process is iterative, and the reactions are catalyzed using acetyl coenzyme A as the initial active donor of two carbon atoms and extended two carbons at a time by the addition of an acetyl group from malonyl coenzyme A. Throughout this process the growing FA remains tethered to an acyl carrier protein (ACP) (Sztain et al., 2019). When the final length is achieved, FA synthesis is terminated by the TEs hydrolyzing a thioester bond, releasing a fully formed FA. The complexity and rigidity of native S. cerevisiae FAS makes it a challenging enzyme to target for protein engineering efforts. In comparison, the bacterial type II FAS consists of eight dissociated and mono-functional enzymes expressed from separate genes that can be manipulated individually and have been extensively reviewed (Chan & Vogel, 2010; Dodge et al., 2019; White et al., 2005).
The sequence for all eFAS genes (including the tesA) used in our project was retrieved from the NCBI database and originate from E. coli strain K-12 MG1655 (NCBI:txid511145). All genes were sequence optimized for yeast using Integrated DNA Technologies online codon optimization tool.
S. cerevisiae produces cytosolic FAs de novo using a large barrel-shaped protein complex (2.6 MDa), consisting of two main subunits (α- and β) expressed by separate genes (FAS1 and FAS2, respectively). The process is iterative, and the reactions are catalyzed using acetyl coenzyme A as the initial active donor of two carbon atoms and extended two carbons at a time by the addition of an acetyl group from malonyl coenzyme A. Throughout this process the growing FA remains tethered to an acyl carrier protein (ACP) (Sztain et al., 2019). When the final length is achieved, FA synthesis is terminated by the TEs hydrolyzing a thioester bond, releasing a fully formed FA. The complexity and rigidity of native S. cerevisiae FAS makes it a challenging enzyme to target for protein engineering efforts. In comparison, the bacterial type II FAS consists of eight dissociated and mono-functional enzymes expressed from separate genes that can be manipulated individually and have been extensively reviewed (Chan & Vogel, 2010; Dodge et al., 2019; White et al., 2005).
The sequence for all eFAS genes (including the tesA) used in our project was retrieved from the NCBI database and originate from E. coli strain K-12 MG1655 (NCBI:txid511145). All genes were sequence optimized for yeast using Integrated DNA Technologies online codon optimization tool.
Gene | Protein | Substrate(s) | Product(s) | |
---|---|---|---|---|
acpP | Acyl Carrier Protein | Apo-ACP + 4'-Phosphopantetheine Group | ACPSH | |
acpS | ACP Synthase | AcpS activates apo-ACP (encoded by acpP), transferring to it the 4’- phosphopantetheine from coenzyme A, resulting in holo-ACP | ||
fabB* | β-Ketoacyl-ACP Synthase I | (1) (n)Acyl-ACP + Malonyl-ACP | (n+2)β-Ketoacyl-ACP | |
(2) Acetoacetyl-ACP + Malonyl-ACP | β-Ketobutyryl-ACP + CO2 + ACPSH | |||
fabG | β-Ketoacyl-ACP Reductase | β-Ketoacyl-ACP + NADPH + H+ | β-Hydroxyacyl-ACP + NADP+ | |
fabZ** | β-Hydroxyacyl dehydratase | β-Hydroxyacyl-ACP | Anoyl-ACP + H2O | |
fabI | Enoyl-ACP Reductase | Anoyl-ACP + NADH + H+ | Acyl-ACP + NAD+ | |
fabD | Malonyl-CoA:ACP Transacylase | Transfers a malonyl group from coenzyme A to ACP, providing the primary carbon source for the formation of the fatty acid chain. | ||
fabH | β-Ketoacyl-ACP Synthase III | Start to initiate cycles of elongation by condensing acetyl-CoA with malonyl-ACP to form acetoacetyl-ACP. | ||
tesA | Thioesterase I | Acyl-ACP | Free fatty acid + ACPSH |
Expression of different thioesterases is key for the formation of FA with specific chain lengths
TEs (or thiolester hydrolases) (E.C.3.1.2) are enzymes which belong to the esterase family. Enzymes in this group exhibit esterase activity (splitting of an ester into acid and alcohol, in the presence of water) specifically at a thiol group. TEs tend to have strong sequence similarity, tertiary structures, and they share general mechanisms, as well as catalytic residues. TEs tend to be promiscuous and have been shown to display specificity for a broad range of different chain lengths, but some are more specific than others (Cantu et al., 2010; Jing et al., 2011).
When designing our system, we decided to use TesA (E. coli), as a part of the native eFAS system, and two heterologous thioesterases (FatB and TesBT), with substrate specificity for different target chain lengths. TesA is located in the periplasm of E. coli and has been shown to exhibits substrate preference for C14 (Steen et al., 2010), although other studies have reported a preference for C16 and C18 (Cho & Cronan Jr, 1993). FatB (Ricinus communis) overexpressed in E. coli was shown to lead to the accumulation of C14 and C16 at levels about 40 % and 55 %, respectively (Zhang et al., 2011). TesBT (Bacteroides thetaiotaomicron VPI-5482) expressed in E. coli has been shown to have a preference for C6 and C8, and significantly increased the yield of butyric acid (C4) (Jawed et al., 2016). Unfortunately, we managed to find very little data on these proteins when expressed in yeast. The overlap in substrate specificity between TesA and TesBT reported in the literature was deemed to not pose a problem for our design, as a proof-of-concept needed to show a tuneable shift between short-, medium-, and long FA production profiles in the final strain, not a preference for a very specific number of carbons. We expect more narrow ranges will be accomplished by future protein engineering efforts (Zhu et al., 2020).
The amino acid sequences for FatB and TesBT was retrieved from the NCBI database (ref. NM_001323748.1 and AAO77182.1, respectively) and converted to a DNA sequence using the Sequence Manipulation Suite. We optimized all gene sequences for S. cerevisiae using the IDT Codon Optimization tool.
When designing our system, we decided to use TesA (E. coli), as a part of the native eFAS system, and two heterologous thioesterases (FatB and TesBT), with substrate specificity for different target chain lengths. TesA is located in the periplasm of E. coli and has been shown to exhibits substrate preference for C14 (Steen et al., 2010), although other studies have reported a preference for C16 and C18 (Cho & Cronan Jr, 1993). FatB (Ricinus communis) overexpressed in E. coli was shown to lead to the accumulation of C14 and C16 at levels about 40 % and 55 %, respectively (Zhang et al., 2011). TesBT (Bacteroides thetaiotaomicron VPI-5482) expressed in E. coli has been shown to have a preference for C6 and C8, and significantly increased the yield of butyric acid (C4) (Jawed et al., 2016). Unfortunately, we managed to find very little data on these proteins when expressed in yeast. The overlap in substrate specificity between TesA and TesBT reported in the literature was deemed to not pose a problem for our design, as a proof-of-concept needed to show a tuneable shift between short-, medium-, and long FA production profiles in the final strain, not a preference for a very specific number of carbons. We expect more narrow ranges will be accomplished by future protein engineering efforts (Zhu et al., 2020).
The amino acid sequences for FatB and TesBT was retrieved from the NCBI database (ref. NM_001323748.1 and AAO77182.1, respectively) and converted to a DNA sequence using the Sequence Manipulation Suite. We optimized all gene sequences for S. cerevisiae using the IDT Codon Optimization tool.
A combination of different chemical induction systems facilitates tunable FAs profiles
Regulation of gene expression is crucial in synthetic biology research and applications and can be accomplished by means of inducible promotor systems. Most induction agents are transcription-factor based, meaning they bind to proteins that either directly target a particular promoter, or an activation and/or repression domain that regulate the transcription.
Inducible gene expression systems are sometimes favored over systems that facilitate a stable expression due to being reversible, and thus more flexible to use. Promoters have been identified that respond to many different types of stimuli, including small-molecules, metal ions, light, and temperature. Chemical approaches to control gene expression have extensively been explored in literature both concerning synthetic biology (Ford & Silver, 2015; Hanczyc, 2020) and medical science, as the ability to switch genes ‘on’ and ‘off’ is of great importance for the developing field of gene therapy (Goverdhana et al., 2005; Kallunki et al., 2019).
In our system, tunable gene expression is accomplished using a combination three chemical induction systems based on copper ions (Etcheverry, 1990; Labbé & Thiele, 1999), tetracycline (Gossen et al., 1995; Gossen & Bujard, 1992), and estradiol (Kumar et al., 1986; Pratt, 1990). Each system is carried on a separate plasmid and linked to the expression of the TEs by placing the genes downstream of the regulatory elements and promotors belonging to each system. Apart from the CUP1 promotor, the tetracycline- and estradiol systems utilized the Scpho5- and GAL1 promotors, respectively. Scpho5 and GAL1 are naturally phosphate- and galactose-sensitive promoters that have been frequently used and engineered to control gene expression in S. cerevisiae (Da Silva & Srikrishnan, 2012).
To find optimal concentration ranges, we benchmarked each system individually, in pairs, and as combination of all three systems, by replacing the TE genes with different fluorescent proteins (GFP, RFP and BFP, respectively).
Many synthetic induction systems are hybrid constructs, utilizing parts from both eukaryotic- and prokaryotic organisms, and often require the combined action of many different proteins to work. When this has been the case, as with the tetracycline- and the estradiol-based systems, these proteins were carried on the same plasmids as the TEs and constitutively expressed.
In our system, tunable gene expression is accomplished using a combination three chemical induction systems based on copper ions (Etcheverry, 1990; Labbé & Thiele, 1999), tetracycline (Gossen et al., 1995; Gossen & Bujard, 1992), and estradiol (Kumar et al., 1986; Pratt, 1990). Each system is carried on a separate plasmid and linked to the expression of the TEs by placing the genes downstream of the regulatory elements and promotors belonging to each system. Apart from the CUP1 promotor, the tetracycline- and estradiol systems utilized the Scpho5- and GAL1 promotors, respectively. Scpho5 and GAL1 are naturally phosphate- and galactose-sensitive promoters that have been frequently used and engineered to control gene expression in S. cerevisiae (Da Silva & Srikrishnan, 2012).
To find optimal concentration ranges, we benchmarked each system individually, in pairs, and as combination of all three systems, by replacing the TE genes with different fluorescent proteins (GFP, RFP and BFP, respectively).
Many synthetic induction systems are hybrid constructs, utilizing parts from both eukaryotic- and prokaryotic organisms, and often require the combined action of many different proteins to work. When this has been the case, as with the tetracycline- and the estradiol-based systems, these proteins were carried on the same plasmids as the TEs and constitutively expressed.
The CUP1, TET and Estradiole induction systems
The copper-based induction system (CUP1) is native to yeast where it responds to copper ions by producing metallothioneins and help to protect the cell from toxic levels. Yeast naturally expresses Ace1, a copper-dependent transcription factor (Gralla et al., 1991). The transcription factor is activated by binding to copper ions, and in turn activates the CUP1 promoter containing four metal regulatory elements. By inserting the CUP1 promoter upstream from a desired gene we can use the same system to stimulate expression. Since the system is native to yeast, no additional associated proteins need be included to make it work.
In the tetracycline-based induction system (TET), gene expression is induced by the presence, or absence, of the antibiotic tetracyline (or one of its derivatives such as doxycycline). There are two commonly used variants of this system, TetON and TetOFF. The TetON system is based on a reverse tetracycline-controlled transactivator (rtTA) composed of the TetR repressor binding protein from the tetracycline resistance operon of E. coli transposon Tn10. In the original version of the system, TetR is fused to the strong transactivating domain of VP16 (alternatively referred to as vmw65 or α-TIF in the literature) from Herpes simplex virus (Hirai et al., 2010). TetON is a variation of TetOFF in which four amino acids have been modified in the TetR DNA binding moiety which alters its binding characteristics to the promotors. The difference between the two systems is not whether the transactivator turns a gene on or off (as both proteins activate expression). Rather, TetON activates expression in the presence of tetracycline, while and TetOFF activates expression in the absence of tetracyline. The promotor contains Tet operator (TetO) sequences derived from the human cytomegalovirus immediate-early promoter and multiple TetO repeats can be placed in sequence to increases induction efficiency.
In our project we replaced VP16 with the yeast Gal4 activation domain (Traven et al., 2006), and rtTA is linked to a nuclear localization signal sequence. We also utilized seven TetO sequence repeats in the Scpho5 promoter.
In the tetracycline-based induction system (TET), gene expression is induced by the presence, or absence, of the antibiotic tetracyline (or one of its derivatives such as doxycycline). There are two commonly used variants of this system, TetON and TetOFF. The TetON system is based on a reverse tetracycline-controlled transactivator (rtTA) composed of the TetR repressor binding protein from the tetracycline resistance operon of E. coli transposon Tn10. In the original version of the system, TetR is fused to the strong transactivating domain of VP16 (alternatively referred to as vmw65 or α-TIF in the literature) from Herpes simplex virus (Hirai et al., 2010). TetON is a variation of TetOFF in which four amino acids have been modified in the TetR DNA binding moiety which alters its binding characteristics to the promotors. The difference between the two systems is not whether the transactivator turns a gene on or off (as both proteins activate expression). Rather, TetON activates expression in the presence of tetracycline, while and TetOFF activates expression in the absence of tetracyline. The promotor contains Tet operator (TetO) sequences derived from the human cytomegalovirus immediate-early promoter and multiple TetO repeats can be placed in sequence to increases induction efficiency.
In our project we replaced VP16 with the yeast Gal4 activation domain (Traven et al., 2006), and rtTA is linked to a nuclear localization signal sequence. We also utilized seven TetO sequence repeats in the Scpho5 promoter.
The estradiol-inducible system (also given to us by the Tom Ellis lab) induced by the mammalian hormone β-estradiol.
Similar to TET, several parts are required in order to make this system function properly. An estradiol ligand recognizing domain (ER) alters conformation upon binding to estradiol. This leads to the exposure of a nuclear localization signal, and thus to a transfer of the transcription factor from the cytosol to the nucleus. ER has further been fused to a human zinc finger protein native to neurons (Zif268). Zif268 recognizes a short DNA sequence known as Z3BS. ER-Zif268 is further fused with VP16 to ensure strong activation, and multiple repeats of Z3BS are used to increasing binding efficiency.
The variant of this system we decided to use for our project is an improvement of the original system more optimized for induction in yeast. In the original system, ER was fused with the yeast Gal4 binding domain, making it bind to the endogenous GAL promoters and thereby unwanted influenced the cells metabolism. As other Gal4 regulators could also bind to the promoter, this system could not be used in media containing galactose, unless GAL4 was knocked out. By substituting the Gal4 binding domain with Zif268, the variant system allows tightly regulated and growth condition-independent transcription (McIsaac et al., 2011, 2013, 2014; Ottoz et al., 2014).
The variant of this system we decided to use for our project is an improvement of the original system more optimized for induction in yeast. In the original system, ER was fused with the yeast Gal4 binding domain, making it bind to the endogenous GAL promoters and thereby unwanted influenced the cells metabolism. As other Gal4 regulators could also bind to the promoter, this system could not be used in media containing galactose, unless GAL4 was knocked out. By substituting the Gal4 binding domain with Zif268, the variant system allows tightly regulated and growth condition-independent transcription (McIsaac et al., 2011, 2013, 2014; Ottoz et al., 2014).
While not optimal for large-scale manufacturing processes, these induction systems were chosen for their availability and being well-characterized in the current literature to provide a basis for a proof-of-concept of our design. The use of small-molecule inducers is mainly limited to the diffusion of the agent in the growth media, the sensitivity of the system and the cost of the compounds used. Background expression (‘leakiness’) is common for many types of induction systems. In addition, specific responses by the chassis used add an extra level of complexity when trying to design and optimize the induction system, especially when several systems are combined and made to work in parallel as on our project (Da Silva & Srikrishnan, 2012).
With our project we aim to illustrate that the use of multiple signals can allow programmability and fine-tuning of gene expression involved in biosynthesis pathways, and that there is a potential for using this kind of systems as platform technologies for large-scale manufacturing purposes.
With our project we aim to illustrate that the use of multiple signals can allow programmability and fine-tuning of gene expression involved in biosynthesis pathways, and that there is a potential for using this kind of systems as platform technologies for large-scale manufacturing purposes.
Reference
Åkerman, C. O., Hagström, A. E. V, Mollaahmad, M. A., Karlsson, S., & Hatti-Kaul, R. (2011). Biolubricant synthesis using immobilised lipase: Process optimisation of trimethylolpropane oleate production. Process Biochemistry, 46(12), 2225–2231.
Anneken, D. J., Both, S., Christoph, R., Fieg, G., Steinberner, U., & Westfechtel, A. (2000). Fatty acids. Ullmann’s Encyclopedia of Industrial Chemistry.
Banat, I. M., Franzetti, A., Gandolfi, I., Bestetti, G., Martinotti, M. G., Fracchia, L., Smyth, T. J., & Marchant, R. (2010). Microbial biosurfactants production, applications and future potential. Applied Microbiology and Biotechnology, 87(2), 427–444.
Banković-Ilić, I. B., Stamenković, O. S., & Veljković, V. B. (2012). Biodiesel production from non-edible plant oils. Renewable and Sustainable Energy Reviews, 16(6), 3621–3647.
Bednarski, W., Adamczak, M., Tomasik, J., & Płaszczyk, M. (2004). Application of oil refinery waste in the biosynthesis of glycolipids by yeast. Bioresource Technology, 95(1), 15–18.
Besada-Lombana, P. B., McTaggart, T. L., & Da Silva, N. A. (2018). Molecular tools for pathway engineering in Saccharomyces cerevisiae. Current Opinion in Biotechnology, 53, 39–49.
Biermann, U., Bornscheuer, U., Meier, M. A. R., Metzger, J. O., & Schäfer, H. J. (2011). Oils and fats as renewable raw materials in chemistry. Angewandte Chemie International Edition, 50(17), 3854–3871.
Bozell, J. J., & Petersen, G. R. (2010). Technology development for the production of biobased products from biorefinery carbohydrates—the US Department of Energy’s “Top 10” revisited. Green Chemistry, 12(4), 539–554.
BP p.l.c. (2021). Statistical Review of World Energy 2021 | 70th edition. https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html
Bremmer, B. J., & Plonsker, L. (2008). Bio-based lubricants: a market opportunity study update. Omni-Tech International, Midland.
Calero, P., & Nikel, P. I. (2019). Chasing bacterial chassis for metabolic engineering: a perspective review from classical to non‐traditional microorganisms. Microbial Biotechnology, 12(1), 98–124.
Cantu, D. C., Chen, Y., Lemons, M. L., & Reilly, P. J. (2010). ThYme: a database for thioester-active enzymes. Nucleic Acids Research, 39(suppl_1), D342–D346.
Carlsson, A. S. (2009). Plant oils as feedstock alternatives to petroleum–A short survey of potential oil crop platforms. Biochimie, 91(6), 665–670.
Cavalett, O., & Ortega, E. (2010). Integrated environmental assessment of biodiesel production from soybean in Brazil. Journal of Cleaner Production, 18(1), 55–70.
Cecilia, J. A., Ballesteros Plata, D., Alves Saboya, R. M., Tavares de Luna, F. M., Cavalcante, C. L., & Rodríguez-Castellón, E. (2020). An overview of the biolubricant production process: challenges and future perspectives. Processes, 8(3), 257.
Ceresa, C., Fracchia, L., Fedeli, E., Porta, C., & Banat, I. M. (2021). Recent advances in biomedical, therapeutic and pharmaceutical applications of microbial surfactants. Pharmaceutics, 13(4), 466.
Chan, D. I., & Vogel, H. J. (2010). Current understanding of fatty acid biosynthesis and the acyl carrier protein. Biochemical Journal, 430(1), 1–19.
Chatterjee, A., Eliasson, S. H. H., & Jensen, V. R. (2018). Selective production of linear α-olefins via catalytic deoxygenation of fatty acids and derivatives. Catalysis Science & Technology, 8(6), 1487–1499.
Cho, H., & Cronan Jr, J. E. (1993). Escherichia coli thioesterase I, molecular cloning and sequencing of the structural gene and identification as a periplasmic enzyme. Journal of Biological Chemistry, 268(13), 9238–9245.
Cochrane, S. A., & Vederas, J. C. (2016). Lipopeptides from Bacillus and Paenibacillus spp.: a gold mine of antibiotic candidates. Medicinal Research Reviews, 36(1), 4–31.
Cravens, A., Payne, J., & Smolke, C. D. (2019). Synthetic biology strategies for microbial biosynthesis of plant natural products. Nature Communications, 10(1), 1–12.
Da Silva, N. A., & Srikrishnan, S. (2012). Introduction and expression of genes for metabolic engineering applications in Saccharomyces cerevisiae. FEMS Yeast Research, 12(2), 197–214.
Daiha, K. de G., Angeli, R., de Oliveira, S. D., & Almeida, R. V. (2015). Are lipases still important biocatalysts? A study of scientific publications and patents for technological forecasting. PloS One, 10(6), e0131624.
Das, U. N. (2006). Essential fatty acids: biochemistry, physiology and pathology. Biotechnology Journal: Healthcare Nutrition Technology, 1(4), 420–439.
De Luca, V., Salim, V., Atsumi, S. M., & Yu, F. (2012). Mining the biodiversity of plants: a revolution in the making. Science, 336(6089), 1658–1661.
Desroches, M., Escouvois, M., Auvergne, R., Caillol, S., & Boutevin, B. (2012). From vegetable oils to polyurethanes: synthetic routes to polyols and main industrial products. Polymer Reviews, 52(1), 38–79.
Dodge, G. J., Patel, A., Jaremko, K. L., McCammon, J. A., Smith, J. L., & Burkart, M. D. (2019). Structural and dynamical rationale for fatty acid unsaturation in Escherichia coli. Proceedings of the National Academy of Sciences, 116(14), 6775–6783.
Dyer, J. M., Stymne, S., Green, A. G., & Carlsson, A. S. (2008). High‐value oils from plants. The Plant Journal, 54(4), 640–655.
Escobar, N., Tizado, E. J., zu Ermgassen, E. K. H. J., Löfgren, P., Börner, J., & Godar, J. (2020). Spatially-explicit footprints of agricultural commodities: Mapping carbon emissions embodied in Brazil’s soy exports. Global Environmental Change, 62, 102067.
Etcheverry, T. (1990). [26] Induced expression using yeast copper metallothionein promoter. Methods in Enzymology, 185, 319–329.
Felse, P. A., Shah, V., Chan, J., Rao, K. J., & Gross, R. A. (2007). Sophorolipid biosynthesis by Candida bombicola from industrial fatty acid residues. Enzyme and Microbial Technology, 40(2), 316–323.
Fernandez-Moya, R., & Da Silva, N. A. (2017). Engineering Saccharomyces cerevisiae for high-level synthesis of fatty acids and derived products. FEMS Yeast Research, 17(7), fox071.
Fernandez‐Moya, R., Leber, C., Cardenas, J., & Da Silva, N. A. (2015). Functional replacement of the Saccharomyces cerevisiae fatty acid synthase with a bacterial type II system allows flexible product profiles. Biotechnology and Bioengineering, 112(12), 2618–2623.
Florini, A. (2011). The International Energy Agency in global energy governance. Global Policy, 2, 40–50.
Ford, T. J., & Silver, P. A. (2015). Synthetic biology expands chemical control of microorganisms. Current Opinion in Chemical Biology, 28, 20–28.
Free, C. M., Thorson, J. T., Pinsky, M. L., Oken, K. L., Wiedenmann, J., & Jensen, O. P. (2019). Impacts of historical warming on marine fisheries production. Science, 363(6430), 979–983.
Galanie, S., Thodey, K., Trenchard, I. J., Interrante, M. F., & Smolke, C. D. (2015). Complete biosynthesis of opioids in yeast. Science, 349(6252), 1095–1100.
Gandhi, N. N. (1997). Applications of lipase. Journal of the American Oil Chemists’ Society, 74(6), 621–634.
Gibbs, H. K., Ruesch, A. S., Achard, F., Clayton, M. K., Holmgren, P., Ramankutty, N., & Foley, J. A. (2010). Tropical forests were the primary sources of new agricultural land in the 1980s and 1990s. Proceedings of the National Academy of Sciences, 107(38), 16732–16737.
Gilbert, N. (2012). Palm-oil boom raises conservation concerns. Nature News, 487(7405), 14.
Gollwitzer, A., Dietel, T., Kretschmer, W. P., & Kempe, R. (2017). A broadly tunable synthesis of linear α-olefins. Nature Communications, 8(1), 1–6.
Gossen, M., & Bujard, H. (1992). Tight control of gene expression in mammalian cells by tetracycline-responsive promoters. Proceedings of the National Academy of Sciences, 89(12), 5547–5551.
Gossen, M., Freundlieb, S., Bender, G., Muller, G., Hillen, W., & Bujard, H. (1995). Transcriptional activation by tetracyclines in mammalian cells. Science, 268(5218), 1766–1769.
Goverdhana, S., Puntel, M., Xiong, W., Zirger, J. M., Barcia, C., Curtin, J. F., Soffer, E. B., Mondkar, S., King, G. D., & Hu, J. (2005). Regulatable gene expression systems for gene therapy applications: progress and future challenges. Molecular Therapy, 12(2), 189–211.
Gralla, E. B., Thiele, D. J., Silar, P., & Valentine, J. S. (1991). ACE1, a copper-dependent transcription factor, activates expression of the yeast copper, zinc superoxide dismutase gene. Proceedings of the National Academy of Sciences, 88(19), 8558–8562.
Guczi, L., & Erdôhelyi, A. (2012). Catalysis for alternative energy generation. Springer Science & Business Media.
Gui, M. M., Lee, K. T., & Bhatia, S. (2008). Feasibility of edible oil vs. non-edible oil vs. waste edible oil as biodiesel feedstock. Energy, 33(11), 1646–1653.
Hanczyc, M. M. (2020). Engineering Life: A Review of Synthetic Biology. Artificial Life, 26(2), 260–273.
Hirai, H., Tani, T., & Kikyo, N. (2010). Structure and functions of powerful transactivators: VP16, MyoD and FoxA. The International Journal of Developmental Biology, 54(11–12), 1589.
Hollenbach, R., Bindereif, B., van der Schaaf, U. S., Ochsenreither, K., & Syldatk, C. (2020). Optimization of glycolipid synthesis in hydrophilic deep eutectic solvents. Frontiers in Bioengineering and Biotechnology, 8, 382.
Howard, T. P., Middelhaufe, S., Moore, K., Edner, C., Kolak, D. M., Taylor, G. N., Parker, D. A., Lee, R., Smirnoff, N., & Aves, S. J. (2013). Synthesis of customized petroleum-replica fuel molecules by targeted modification of free fatty acid pools in Escherichia coli. Proceedings of the National Academy of Sciences, 110(19), 7636–7641.
IHS Markit. (2009). Chemical Economics Handbook. https://ihsmarkit.com/products/linear-alpha-olefins-chemical-economics-handbook.html
Jawed, K., Mattam, A. J., Fatma, Z., Wajid, S., Abdin, M. Z., & Yazdani, S. S. (2016). Engineered production of short chain fatty acid in Escherichia coli using fatty acid synthesis pathway. PLoS One, 11(7), e0160035.
Jing, F., Cantu, D. C., Tvaruzkova, J., Chipman, J. P., Nikolau, B. J., Yandeau-Nelson, M. D., & Reilly, P. J. (2011). Phylogenetic and experimental characterization of an acyl-ACP thioesterase family reveals significant diversity in enzymatic specificity and activity. BMC Biochemistry, 12(1), 1–16.
Jollands, N. (2008). International Energy Agency. Competitive Cities and Climate Change, 136.
Kallunki, T., Barisic, M., Jäättelä, M., & Liu, B. (2019). How to choose the right inducible gene expression system for mammalian studies? Cells, 8(8), 796.
Knepper, T. P., & Berna, J. L. (2003). Surfactants: properties, production, and environmental aspects. Comprehensive Analytical Chemistry, 40, 1–49.
Ko, Y.-S., Kim, J. W., Lee, J. A., Han, T., Kim, G. B., Park, J. E., & Lee, S. Y. (2020). Tools and strategies of systems metabolic engineering for the development of microbial cell factories for chemical production. Chemical Society Reviews, 49(14), 4615–4636.
Kubička, D. (2008). Future refining catalysis-introduction of biomass feedstocks. Collection of Czechoslovak Chemical Communications, 73(8), 1015–1044.
Kumar, V., Green, S., Staub, A., & Chambon, P. (1986). Localisation of the oestradiol‐binding and putative DNA‐binding domains of the human oestrogen receptor. The EMBO Journal, 5(9), 2231–2236.
Labbé, S., & Thiele, D. J. (1999). [8] Copper ion inducible and repressible promoter systems in yeast. Methods in Enzymology, 306, 145–153.
Leung, D. Y. C., Wu, X., & Leung, M. K. H. (2010). A review on biodiesel production using catalyzed transesterification. Applied Energy, 87(4), 1083–1095.
Lian, J., HamediRad, M., & Zhao, H. (2018). Advancing metabolic engineering of Saccharomyces cerevisiae using the CRISPR/Cas system. Biotechnology Journal, 13(9), 1700601.
Lian, J., Mishra, S., & Zhao, H. (2018). Recent advances in metabolic engineering of Saccharomyces cerevisiae: new tools and their applications. Metabolic Engineering, 50, 85–108.
Lipinski, C. A., Lombardo, F., Dominy, B. W., & Feeney, P. J. (1997). Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Advanced Drug Delivery Reviews, 23(1–3), 3–25.
Liu, Y., Kim, K. E., Herbert, M. B., Fedorov, A., Grubbs, R. H., & Stoltz, B. M. (2014). Palladium‐catalyzed decarbonylative dehydration of fatty acids for the production of linear alpha olefins. Advanced Synthesis & Catalysis, 356(1), 130–136.
Maisonneuve, L., Lebarbé, T., Grau, E., & Cramail, H. (2013). Structure–properties relationship of fatty acid-based thermoplastics as synthetic polymer mimics. Polymer Chemistry, 4(22), 5472–5517.
Mäki-Arvela, P., Kubickova, I., Snåre, M., Eränen, K., & Murzin, D. Y. (2007). Catalytic deoxygenation of fatty acids and their derivatives. Energy & Fuels, 21(1), 30–41.
Marchant, R., & Banat, I. M. (2012). Microbial biosurfactants: challenges and opportunities for future exploitation. Trends in Biotechnology, 30(11), 558–565.
Marella, E. R., Holkenbrink, C., Siewers, V., & Borodina, I. (2018). Engineering microbial fatty acid metabolism for biofuels and biochemicals. Current Opinion in Biotechnology, 50, 39–46.
MarketsandMarkets. (2020). Surfactants Market (CH3464) | Global Forecast to 2025. https://www.marketsandmarkets.com/Market-Reports/biosurfactants-market-493.html
Markovic, M., Ben-Shabat, S., Aponick, A., Zimmermann, E. M., & Dahan, A. (2020). Lipids and lipid-processing pathways in drug delivery and therapeutics. International Journal of Molecular Sciences, 21(9), 3248.
McIsaac, R. S., Gibney, P. A., Chandran, S. S., Benjamin, K. R., & Botstein, D. (2014). Synthetic biology tools for programming gene expression without nutritional perturbations in Saccharomyces cerevisiae. Nucleic Acids Research, 42(6), e48–e48.
McIsaac, R. S., Oakes, B. L., Wang, X., Dummit, K. A., Botstein, D., & Noyes, M. B. (2013). Synthetic gene expression perturbation systems with rapid, tunable, single-gene specificity in yeast. Nucleic Acids Research, 41(4), e57–e57.
McIsaac, R. S., Silverman, S. J., McClean, M. N., Gibney, P. A., Macinskas, J., Hickman, M. J., Petti, A. A., & Botstein, D. (2011). Fast-acting and nearly gratuitous induction of gene expression and protein depletion in Saccharomyces cerevisiae. Molecular Biology of the Cell, 22(22), 4447–4459.
Meyers, W. H., & Kalaitzandonakes, N. (2015). World population, food growth, and food security challenges. In Food Security in an Uncertain World. Emerald Group Publishing Limited.
Navarrete, C., Jacobsen, I. H., Martínez, J. L., & Procentese, A. (2020). Cell factories for industrial production processes: Current issues and emerging solutions. Processes, 8(7), 768.
Nevoigt, E. (2008). Progress in metabolic engineering of Saccharomyces cerevisiae. Microbiology and Molecular Biology Reviews, 72(3), 379–412.
Nielsen, J., & Keasling, J. D. (2016). Engineering cellular metabolism. Cell, 164(6), 1185–1197.
Nikolau, B. J., Perera, M. A. D. N., Brachova, L., & Shanks, B. (2008). Platform biochemicals for a biorenewable chemical industry. The Plant Journal, 54(4), 536–545.
Nosal, H., Moser, K., Warzała, M., Holzer, A., Stańczyk, D., & Sabura, E. (2021). Selected Fatty Acids Esters as Potential PHB-V Bioplasticizers: Effect on Mechanical Properties of the Polymer. Journal of Polymers and the Environment, 29(1), 38–53.
Olkowska, E., Polkowska, Z., & Namiesnik, J. (2011). Analytics of surfactants in the environment: problems and challenges. Chemical Reviews, 111(9), 5667–5700.
Ostroumov, S. A. (2005). Biological effects of surfactants. CRC Press.
Ottoz, D. S. M., Rudolf, F., & Stelling, J. (2014). Inducible, tightly regulated and growth condition-independent transcription factor in Saccharomyces cerevisiae. Nucleic Acids Research, 42(17), e130–e130.
Parapouli, M., Vasileiadis, A., Afendra, A.-S., & Hatziloukas, E. (2020). Saccharomyces cerevisiae and its industrial applications. AIMS Microbiology, 6(1), 1.
Pardi, N., Hogan, M. J., Porter, F. W., & Weissman, D. (2018). mRNA vaccines—a new era in vaccinology. Nature Reviews Drug Discovery, 17(4), 261–279.
Pratt, W. B. (1990). Interaction of hsp90 with steroid receptors: organizing some diverse observations and presenting the newest concepts.
Ramos, M. J., Fernández, C. M., Casas, A., Rodríguez, L., & Pérez, Á. (2009). Influence of fatty acid composition of raw materials on biodiesel properties. Bioresource Technology, 100(1), 261–268.
Reports and Data. (2020). Fatty Acid Market Size, Trends & Growth, By Form (Oil, Capsule, Syrup, Powder), By Product (Omega-3, Omega-6, Omega-7, Omega-9), By Source and By Application (Oilfield, Food and Beverage, Animal Feed, Dietary Supplements, Lubricants and Cosmetics), Foreca.
Ritchie, H., & Roser, M. (2021). Forests and Deforestation. Our World in Data. https://ourworldindata.org/forests-and-deforestation
Rival, A., & Levang, P. (2014). Palms of controversies: Oil palm and development challenges. CIFOR.
Santillan‐Jimenez, E., & Crocker, M. (2012). Catalytic deoxygenation of fatty acids and their derivatives to hydrocarbon fuels via decarboxylation/decarbonylation. Journal of Chemical Technology & Biotechnology, 87(8), 1041–1050.
Saxon, E., & Roquemore, S. (2011). Palm oil. The Root of the Problem: What’s Driving Tropical Deforestation Today, 51–63.
Schneider, M. P. (2006). Plant‐oil‐based lubricants and hydraulic fluids. Journal of the Science of Food and Agriculture, 86(12), 1769–1780.
Shukla, P. R., Skea, J., Calvo Buendia, E., Masson-Delmotte, V., Pörtner, H. O., Roberts, D. C., Zhai, P., Slade, R., Connors, S., & Van Diemen, R. (2019). IPCC, 2019: Climate Change and Land: an IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems.
Smith, G. A. (2019). Fatty acid, methyl ester, and vegetable oil ethoxylates. In Biobased Surfactants (pp. 287–301). Elsevier.
Steen, E. J., Kang, Y., Bokinsky, G., Hu, Z., Schirmer, A., McClure, A., Del Cardayre, S. B., & Keasling, J. D. (2010). Microbial production of fatty-acid-derived fuels and chemicals from plant biomass. Nature, 463(7280), 559–562.
Sun, L., Kwak, S., & Jin, Y.-S. (2019). Vitamin A production by engineered Saccharomyces cerevisiae from xylose via two-phase in situ extraction. ACS Synthetic Biology, 8(9), 2131–2140.
Sztain, T., Patel, A., Lee, D. J., Davis, T. D., McCammon, J. A., & Burkart, M. D. (2019). Modifying the thioester linkage affects the structure of the acyl carrier protein. Angewandte Chemie International Edition, 58(32), 10888–10892.
Traven, A., Jelicic, B., & Sopta, M. (2006). Yeast Gal4: a transcriptional paradigm revisited. EMBO Reports, 7(5), 496–499.
Uemura, H. (2012). Synthesis and production of unsaturated and polyunsaturated fatty acids in yeast: current state and perspectives. Applied Microbiology and Biotechnology, 95(1), 1–12.
Van De Waterbeemd, H., Smith, D. A., Beaumont, K., & Walker, D. K. (2001). Property-based design: optimization of drug absorption and pharmacokinetics. Journal of Medicinal Chemistry, 44(9), 1313–1333.
van der Klis, F., Le Nôtre, J., Blaauw, R., van Haveren, J., & van Es, D. S. (2012). Renewable linear alpha olefins by selective ethenolysis of decarboxylated unsaturated fatty acids. European Journal of Lipid Science and Technology, 114(8), 911–918.
White, S. W., Zheng, J., Zhang, Y.-M., & Rock, C. O. (2005). The structural biology of type II fatty acid biosynthesis. Annu. Rev. Biochem., 74, 791–831.
Willing, A. (2001). Lubricants based on renewable resources–an environmentally compatible alternative to mineral oil products. Chemosphere, 43(1), 89–98.
Willis, W. M., & Marangoni, A. G. (1999). Biotechnological strategies for the modification of food lipids. Biotechnology and Genetic Engineering Reviews, 16(1), 141–176.
Yew, H.-C., & Misran, M. (2019). Characterization of fatty acid based nanostructured lipid carrier (NLC) and their sustained release properties. Progress in Drug Discovery & Biomedical Science, 2(1).
Yu, A.-Q., Pratomo Juwono, N. K., Leong, S. S. J., & Chang, M. W. (2014). Production of fatty acid-derived valuable chemicals in synthetic microbes. Frontiers in Bioengineering and Biotechnology, 2, 78.
Yu, T., Zhou, Y. J., Huang, M., Liu, Q., Pereira, R., David, F., & Nielsen, J. (2018). Reprogramming yeast metabolism from alcoholic fermentation to lipogenesis. Cell, 174(6), 1549–1558.
Zaccheria, F., Mariani, M., Psaro, R., Bondioli, P., & Ravasio, N. (2016). Environmentally friendly lubricants through a zero waste process. Applied Catalysis B: Environmental, 181, 581–586.
Zalles, V., Hansen, M. C., Potapov, P. V, Stehman, S. V, Tyukavina, A., Pickens, A., Song, X.-P., Adusei, B., Okpa, C., & Aguilar, R. (2019). Near doubling of Brazil’s intensive row crop area since 2000. Proceedings of the National Academy of Sciences, 116(2), 428–435.
Zhang, X., Li, M., Agrawal, A., & San, K.-Y. (2011). Efficient free fatty acid production in Escherichia coli using plant acyl-ACP thioesterases. Metabolic Engineering, 13(6), 713–722.
Zhou, Y. J., Buijs, N. A., Siewers, V., & Nielsen, J. (2014). Fatty acid-derived biofuels and chemicals production in Saccharomyces cerevisiae. Frontiers in Bioengineering and Biotechnology, 2, 32.
Zhou, Y. J., Buijs, N. A., Zhu, Z., Gómez, D. O., Boonsombuti, A., Siewers, V., & Nielsen, J. (2016). Harnessing yeast peroxisomes for biosynthesis of fatty-acid-derived biofuels and chemicals with relieved side-pathway competition. Journal of the American Chemical Society, 138(47), 15368–15377.
Zhu, Z., Hu, Y., Teixeira, P. G., Pereira, R., Chen, Y., Siewers, V., & Nielsen, J. (2020). Multidimensional engineering of Saccharomyces cerevisiae for efficient synthesis of medium-chain fatty acids. Nature Catalysis, 3(1), 64–74.
Anneken, D. J., Both, S., Christoph, R., Fieg, G., Steinberner, U., & Westfechtel, A. (2000). Fatty acids. Ullmann’s Encyclopedia of Industrial Chemistry.
Banat, I. M., Franzetti, A., Gandolfi, I., Bestetti, G., Martinotti, M. G., Fracchia, L., Smyth, T. J., & Marchant, R. (2010). Microbial biosurfactants production, applications and future potential. Applied Microbiology and Biotechnology, 87(2), 427–444.
Banković-Ilić, I. B., Stamenković, O. S., & Veljković, V. B. (2012). Biodiesel production from non-edible plant oils. Renewable and Sustainable Energy Reviews, 16(6), 3621–3647.
Bednarski, W., Adamczak, M., Tomasik, J., & Płaszczyk, M. (2004). Application of oil refinery waste in the biosynthesis of glycolipids by yeast. Bioresource Technology, 95(1), 15–18.
Besada-Lombana, P. B., McTaggart, T. L., & Da Silva, N. A. (2018). Molecular tools for pathway engineering in Saccharomyces cerevisiae. Current Opinion in Biotechnology, 53, 39–49.
Biermann, U., Bornscheuer, U., Meier, M. A. R., Metzger, J. O., & Schäfer, H. J. (2011). Oils and fats as renewable raw materials in chemistry. Angewandte Chemie International Edition, 50(17), 3854–3871.
Bozell, J. J., & Petersen, G. R. (2010). Technology development for the production of biobased products from biorefinery carbohydrates—the US Department of Energy’s “Top 10” revisited. Green Chemistry, 12(4), 539–554.
BP p.l.c. (2021). Statistical Review of World Energy 2021 | 70th edition. https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html
Bremmer, B. J., & Plonsker, L. (2008). Bio-based lubricants: a market opportunity study update. Omni-Tech International, Midland.
Calero, P., & Nikel, P. I. (2019). Chasing bacterial chassis for metabolic engineering: a perspective review from classical to non‐traditional microorganisms. Microbial Biotechnology, 12(1), 98–124.
Cantu, D. C., Chen, Y., Lemons, M. L., & Reilly, P. J. (2010). ThYme: a database for thioester-active enzymes. Nucleic Acids Research, 39(suppl_1), D342–D346.
Carlsson, A. S. (2009). Plant oils as feedstock alternatives to petroleum–A short survey of potential oil crop platforms. Biochimie, 91(6), 665–670.
Cavalett, O., & Ortega, E. (2010). Integrated environmental assessment of biodiesel production from soybean in Brazil. Journal of Cleaner Production, 18(1), 55–70.
Cecilia, J. A., Ballesteros Plata, D., Alves Saboya, R. M., Tavares de Luna, F. M., Cavalcante, C. L., & Rodríguez-Castellón, E. (2020). An overview of the biolubricant production process: challenges and future perspectives. Processes, 8(3), 257.
Ceresa, C., Fracchia, L., Fedeli, E., Porta, C., & Banat, I. M. (2021). Recent advances in biomedical, therapeutic and pharmaceutical applications of microbial surfactants. Pharmaceutics, 13(4), 466.
Chan, D. I., & Vogel, H. J. (2010). Current understanding of fatty acid biosynthesis and the acyl carrier protein. Biochemical Journal, 430(1), 1–19.
Chatterjee, A., Eliasson, S. H. H., & Jensen, V. R. (2018). Selective production of linear α-olefins via catalytic deoxygenation of fatty acids and derivatives. Catalysis Science & Technology, 8(6), 1487–1499.
Cho, H., & Cronan Jr, J. E. (1993). Escherichia coli thioesterase I, molecular cloning and sequencing of the structural gene and identification as a periplasmic enzyme. Journal of Biological Chemistry, 268(13), 9238–9245.
Cochrane, S. A., & Vederas, J. C. (2016). Lipopeptides from Bacillus and Paenibacillus spp.: a gold mine of antibiotic candidates. Medicinal Research Reviews, 36(1), 4–31.
Cravens, A., Payne, J., & Smolke, C. D. (2019). Synthetic biology strategies for microbial biosynthesis of plant natural products. Nature Communications, 10(1), 1–12.
Da Silva, N. A., & Srikrishnan, S. (2012). Introduction and expression of genes for metabolic engineering applications in Saccharomyces cerevisiae. FEMS Yeast Research, 12(2), 197–214.
Daiha, K. de G., Angeli, R., de Oliveira, S. D., & Almeida, R. V. (2015). Are lipases still important biocatalysts? A study of scientific publications and patents for technological forecasting. PloS One, 10(6), e0131624.
Das, U. N. (2006). Essential fatty acids: biochemistry, physiology and pathology. Biotechnology Journal: Healthcare Nutrition Technology, 1(4), 420–439.
De Luca, V., Salim, V., Atsumi, S. M., & Yu, F. (2012). Mining the biodiversity of plants: a revolution in the making. Science, 336(6089), 1658–1661.
Desroches, M., Escouvois, M., Auvergne, R., Caillol, S., & Boutevin, B. (2012). From vegetable oils to polyurethanes: synthetic routes to polyols and main industrial products. Polymer Reviews, 52(1), 38–79.
Dodge, G. J., Patel, A., Jaremko, K. L., McCammon, J. A., Smith, J. L., & Burkart, M. D. (2019). Structural and dynamical rationale for fatty acid unsaturation in Escherichia coli. Proceedings of the National Academy of Sciences, 116(14), 6775–6783.
Dyer, J. M., Stymne, S., Green, A. G., & Carlsson, A. S. (2008). High‐value oils from plants. The Plant Journal, 54(4), 640–655.
Escobar, N., Tizado, E. J., zu Ermgassen, E. K. H. J., Löfgren, P., Börner, J., & Godar, J. (2020). Spatially-explicit footprints of agricultural commodities: Mapping carbon emissions embodied in Brazil’s soy exports. Global Environmental Change, 62, 102067.
Etcheverry, T. (1990). [26] Induced expression using yeast copper metallothionein promoter. Methods in Enzymology, 185, 319–329.
Felse, P. A., Shah, V., Chan, J., Rao, K. J., & Gross, R. A. (2007). Sophorolipid biosynthesis by Candida bombicola from industrial fatty acid residues. Enzyme and Microbial Technology, 40(2), 316–323.
Fernandez-Moya, R., & Da Silva, N. A. (2017). Engineering Saccharomyces cerevisiae for high-level synthesis of fatty acids and derived products. FEMS Yeast Research, 17(7), fox071.
Fernandez‐Moya, R., Leber, C., Cardenas, J., & Da Silva, N. A. (2015). Functional replacement of the Saccharomyces cerevisiae fatty acid synthase with a bacterial type II system allows flexible product profiles. Biotechnology and Bioengineering, 112(12), 2618–2623.
Florini, A. (2011). The International Energy Agency in global energy governance. Global Policy, 2, 40–50.
Ford, T. J., & Silver, P. A. (2015). Synthetic biology expands chemical control of microorganisms. Current Opinion in Chemical Biology, 28, 20–28.
Free, C. M., Thorson, J. T., Pinsky, M. L., Oken, K. L., Wiedenmann, J., & Jensen, O. P. (2019). Impacts of historical warming on marine fisheries production. Science, 363(6430), 979–983.
Galanie, S., Thodey, K., Trenchard, I. J., Interrante, M. F., & Smolke, C. D. (2015). Complete biosynthesis of opioids in yeast. Science, 349(6252), 1095–1100.
Gandhi, N. N. (1997). Applications of lipase. Journal of the American Oil Chemists’ Society, 74(6), 621–634.
Gibbs, H. K., Ruesch, A. S., Achard, F., Clayton, M. K., Holmgren, P., Ramankutty, N., & Foley, J. A. (2010). Tropical forests were the primary sources of new agricultural land in the 1980s and 1990s. Proceedings of the National Academy of Sciences, 107(38), 16732–16737.
Gilbert, N. (2012). Palm-oil boom raises conservation concerns. Nature News, 487(7405), 14.
Gollwitzer, A., Dietel, T., Kretschmer, W. P., & Kempe, R. (2017). A broadly tunable synthesis of linear α-olefins. Nature Communications, 8(1), 1–6.
Gossen, M., & Bujard, H. (1992). Tight control of gene expression in mammalian cells by tetracycline-responsive promoters. Proceedings of the National Academy of Sciences, 89(12), 5547–5551.
Gossen, M., Freundlieb, S., Bender, G., Muller, G., Hillen, W., & Bujard, H. (1995). Transcriptional activation by tetracyclines in mammalian cells. Science, 268(5218), 1766–1769.
Goverdhana, S., Puntel, M., Xiong, W., Zirger, J. M., Barcia, C., Curtin, J. F., Soffer, E. B., Mondkar, S., King, G. D., & Hu, J. (2005). Regulatable gene expression systems for gene therapy applications: progress and future challenges. Molecular Therapy, 12(2), 189–211.
Gralla, E. B., Thiele, D. J., Silar, P., & Valentine, J. S. (1991). ACE1, a copper-dependent transcription factor, activates expression of the yeast copper, zinc superoxide dismutase gene. Proceedings of the National Academy of Sciences, 88(19), 8558–8562.
Guczi, L., & Erdôhelyi, A. (2012). Catalysis for alternative energy generation. Springer Science & Business Media.
Gui, M. M., Lee, K. T., & Bhatia, S. (2008). Feasibility of edible oil vs. non-edible oil vs. waste edible oil as biodiesel feedstock. Energy, 33(11), 1646–1653.
Hanczyc, M. M. (2020). Engineering Life: A Review of Synthetic Biology. Artificial Life, 26(2), 260–273.
Hirai, H., Tani, T., & Kikyo, N. (2010). Structure and functions of powerful transactivators: VP16, MyoD and FoxA. The International Journal of Developmental Biology, 54(11–12), 1589.
Hollenbach, R., Bindereif, B., van der Schaaf, U. S., Ochsenreither, K., & Syldatk, C. (2020). Optimization of glycolipid synthesis in hydrophilic deep eutectic solvents. Frontiers in Bioengineering and Biotechnology, 8, 382.
Howard, T. P., Middelhaufe, S., Moore, K., Edner, C., Kolak, D. M., Taylor, G. N., Parker, D. A., Lee, R., Smirnoff, N., & Aves, S. J. (2013). Synthesis of customized petroleum-replica fuel molecules by targeted modification of free fatty acid pools in Escherichia coli. Proceedings of the National Academy of Sciences, 110(19), 7636–7641.
IHS Markit. (2009). Chemical Economics Handbook. https://ihsmarkit.com/products/linear-alpha-olefins-chemical-economics-handbook.html
Jawed, K., Mattam, A. J., Fatma, Z., Wajid, S., Abdin, M. Z., & Yazdani, S. S. (2016). Engineered production of short chain fatty acid in Escherichia coli using fatty acid synthesis pathway. PLoS One, 11(7), e0160035.
Jing, F., Cantu, D. C., Tvaruzkova, J., Chipman, J. P., Nikolau, B. J., Yandeau-Nelson, M. D., & Reilly, P. J. (2011). Phylogenetic and experimental characterization of an acyl-ACP thioesterase family reveals significant diversity in enzymatic specificity and activity. BMC Biochemistry, 12(1), 1–16.
Jollands, N. (2008). International Energy Agency. Competitive Cities and Climate Change, 136.
Kallunki, T., Barisic, M., Jäättelä, M., & Liu, B. (2019). How to choose the right inducible gene expression system for mammalian studies? Cells, 8(8), 796.
Knepper, T. P., & Berna, J. L. (2003). Surfactants: properties, production, and environmental aspects. Comprehensive Analytical Chemistry, 40, 1–49.
Ko, Y.-S., Kim, J. W., Lee, J. A., Han, T., Kim, G. B., Park, J. E., & Lee, S. Y. (2020). Tools and strategies of systems metabolic engineering for the development of microbial cell factories for chemical production. Chemical Society Reviews, 49(14), 4615–4636.
Kubička, D. (2008). Future refining catalysis-introduction of biomass feedstocks. Collection of Czechoslovak Chemical Communications, 73(8), 1015–1044.
Kumar, V., Green, S., Staub, A., & Chambon, P. (1986). Localisation of the oestradiol‐binding and putative DNA‐binding domains of the human oestrogen receptor. The EMBO Journal, 5(9), 2231–2236.
Labbé, S., & Thiele, D. J. (1999). [8] Copper ion inducible and repressible promoter systems in yeast. Methods in Enzymology, 306, 145–153.
Leung, D. Y. C., Wu, X., & Leung, M. K. H. (2010). A review on biodiesel production using catalyzed transesterification. Applied Energy, 87(4), 1083–1095.
Lian, J., HamediRad, M., & Zhao, H. (2018). Advancing metabolic engineering of Saccharomyces cerevisiae using the CRISPR/Cas system. Biotechnology Journal, 13(9), 1700601.
Lian, J., Mishra, S., & Zhao, H. (2018). Recent advances in metabolic engineering of Saccharomyces cerevisiae: new tools and their applications. Metabolic Engineering, 50, 85–108.
Lipinski, C. A., Lombardo, F., Dominy, B. W., & Feeney, P. J. (1997). Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Advanced Drug Delivery Reviews, 23(1–3), 3–25.
Liu, Y., Kim, K. E., Herbert, M. B., Fedorov, A., Grubbs, R. H., & Stoltz, B. M. (2014). Palladium‐catalyzed decarbonylative dehydration of fatty acids for the production of linear alpha olefins. Advanced Synthesis & Catalysis, 356(1), 130–136.
Maisonneuve, L., Lebarbé, T., Grau, E., & Cramail, H. (2013). Structure–properties relationship of fatty acid-based thermoplastics as synthetic polymer mimics. Polymer Chemistry, 4(22), 5472–5517.
Mäki-Arvela, P., Kubickova, I., Snåre, M., Eränen, K., & Murzin, D. Y. (2007). Catalytic deoxygenation of fatty acids and their derivatives. Energy & Fuels, 21(1), 30–41.
Marchant, R., & Banat, I. M. (2012). Microbial biosurfactants: challenges and opportunities for future exploitation. Trends in Biotechnology, 30(11), 558–565.
Marella, E. R., Holkenbrink, C., Siewers, V., & Borodina, I. (2018). Engineering microbial fatty acid metabolism for biofuels and biochemicals. Current Opinion in Biotechnology, 50, 39–46.
MarketsandMarkets. (2020). Surfactants Market (CH3464) | Global Forecast to 2025. https://www.marketsandmarkets.com/Market-Reports/biosurfactants-market-493.html
Markovic, M., Ben-Shabat, S., Aponick, A., Zimmermann, E. M., & Dahan, A. (2020). Lipids and lipid-processing pathways in drug delivery and therapeutics. International Journal of Molecular Sciences, 21(9), 3248.
McIsaac, R. S., Gibney, P. A., Chandran, S. S., Benjamin, K. R., & Botstein, D. (2014). Synthetic biology tools for programming gene expression without nutritional perturbations in Saccharomyces cerevisiae. Nucleic Acids Research, 42(6), e48–e48.
McIsaac, R. S., Oakes, B. L., Wang, X., Dummit, K. A., Botstein, D., & Noyes, M. B. (2013). Synthetic gene expression perturbation systems with rapid, tunable, single-gene specificity in yeast. Nucleic Acids Research, 41(4), e57–e57.
McIsaac, R. S., Silverman, S. J., McClean, M. N., Gibney, P. A., Macinskas, J., Hickman, M. J., Petti, A. A., & Botstein, D. (2011). Fast-acting and nearly gratuitous induction of gene expression and protein depletion in Saccharomyces cerevisiae. Molecular Biology of the Cell, 22(22), 4447–4459.
Meyers, W. H., & Kalaitzandonakes, N. (2015). World population, food growth, and food security challenges. In Food Security in an Uncertain World. Emerald Group Publishing Limited.
Navarrete, C., Jacobsen, I. H., Martínez, J. L., & Procentese, A. (2020). Cell factories for industrial production processes: Current issues and emerging solutions. Processes, 8(7), 768.
Nevoigt, E. (2008). Progress in metabolic engineering of Saccharomyces cerevisiae. Microbiology and Molecular Biology Reviews, 72(3), 379–412.
Nielsen, J., & Keasling, J. D. (2016). Engineering cellular metabolism. Cell, 164(6), 1185–1197.
Nikolau, B. J., Perera, M. A. D. N., Brachova, L., & Shanks, B. (2008). Platform biochemicals for a biorenewable chemical industry. The Plant Journal, 54(4), 536–545.
Nosal, H., Moser, K., Warzała, M., Holzer, A., Stańczyk, D., & Sabura, E. (2021). Selected Fatty Acids Esters as Potential PHB-V Bioplasticizers: Effect on Mechanical Properties of the Polymer. Journal of Polymers and the Environment, 29(1), 38–53.
Olkowska, E., Polkowska, Z., & Namiesnik, J. (2011). Analytics of surfactants in the environment: problems and challenges. Chemical Reviews, 111(9), 5667–5700.
Ostroumov, S. A. (2005). Biological effects of surfactants. CRC Press.
Ottoz, D. S. M., Rudolf, F., & Stelling, J. (2014). Inducible, tightly regulated and growth condition-independent transcription factor in Saccharomyces cerevisiae. Nucleic Acids Research, 42(17), e130–e130.
Parapouli, M., Vasileiadis, A., Afendra, A.-S., & Hatziloukas, E. (2020). Saccharomyces cerevisiae and its industrial applications. AIMS Microbiology, 6(1), 1.
Pardi, N., Hogan, M. J., Porter, F. W., & Weissman, D. (2018). mRNA vaccines—a new era in vaccinology. Nature Reviews Drug Discovery, 17(4), 261–279.
Pratt, W. B. (1990). Interaction of hsp90 with steroid receptors: organizing some diverse observations and presenting the newest concepts.
Ramos, M. J., Fernández, C. M., Casas, A., Rodríguez, L., & Pérez, Á. (2009). Influence of fatty acid composition of raw materials on biodiesel properties. Bioresource Technology, 100(1), 261–268.
Reports and Data. (2020). Fatty Acid Market Size, Trends & Growth, By Form (Oil, Capsule, Syrup, Powder), By Product (Omega-3, Omega-6, Omega-7, Omega-9), By Source and By Application (Oilfield, Food and Beverage, Animal Feed, Dietary Supplements, Lubricants and Cosmetics), Foreca.
Ritchie, H., & Roser, M. (2021). Forests and Deforestation. Our World in Data. https://ourworldindata.org/forests-and-deforestation
Rival, A., & Levang, P. (2014). Palms of controversies: Oil palm and development challenges. CIFOR.
Santillan‐Jimenez, E., & Crocker, M. (2012). Catalytic deoxygenation of fatty acids and their derivatives to hydrocarbon fuels via decarboxylation/decarbonylation. Journal of Chemical Technology & Biotechnology, 87(8), 1041–1050.
Saxon, E., & Roquemore, S. (2011). Palm oil. The Root of the Problem: What’s Driving Tropical Deforestation Today, 51–63.
Schneider, M. P. (2006). Plant‐oil‐based lubricants and hydraulic fluids. Journal of the Science of Food and Agriculture, 86(12), 1769–1780.
Shukla, P. R., Skea, J., Calvo Buendia, E., Masson-Delmotte, V., Pörtner, H. O., Roberts, D. C., Zhai, P., Slade, R., Connors, S., & Van Diemen, R. (2019). IPCC, 2019: Climate Change and Land: an IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems.
Smith, G. A. (2019). Fatty acid, methyl ester, and vegetable oil ethoxylates. In Biobased Surfactants (pp. 287–301). Elsevier.
Steen, E. J., Kang, Y., Bokinsky, G., Hu, Z., Schirmer, A., McClure, A., Del Cardayre, S. B., & Keasling, J. D. (2010). Microbial production of fatty-acid-derived fuels and chemicals from plant biomass. Nature, 463(7280), 559–562.
Sun, L., Kwak, S., & Jin, Y.-S. (2019). Vitamin A production by engineered Saccharomyces cerevisiae from xylose via two-phase in situ extraction. ACS Synthetic Biology, 8(9), 2131–2140.
Sztain, T., Patel, A., Lee, D. J., Davis, T. D., McCammon, J. A., & Burkart, M. D. (2019). Modifying the thioester linkage affects the structure of the acyl carrier protein. Angewandte Chemie International Edition, 58(32), 10888–10892.
Traven, A., Jelicic, B., & Sopta, M. (2006). Yeast Gal4: a transcriptional paradigm revisited. EMBO Reports, 7(5), 496–499.
Uemura, H. (2012). Synthesis and production of unsaturated and polyunsaturated fatty acids in yeast: current state and perspectives. Applied Microbiology and Biotechnology, 95(1), 1–12.
Van De Waterbeemd, H., Smith, D. A., Beaumont, K., & Walker, D. K. (2001). Property-based design: optimization of drug absorption and pharmacokinetics. Journal of Medicinal Chemistry, 44(9), 1313–1333.
van der Klis, F., Le Nôtre, J., Blaauw, R., van Haveren, J., & van Es, D. S. (2012). Renewable linear alpha olefins by selective ethenolysis of decarboxylated unsaturated fatty acids. European Journal of Lipid Science and Technology, 114(8), 911–918.
White, S. W., Zheng, J., Zhang, Y.-M., & Rock, C. O. (2005). The structural biology of type II fatty acid biosynthesis. Annu. Rev. Biochem., 74, 791–831.
Willing, A. (2001). Lubricants based on renewable resources–an environmentally compatible alternative to mineral oil products. Chemosphere, 43(1), 89–98.
Willis, W. M., & Marangoni, A. G. (1999). Biotechnological strategies for the modification of food lipids. Biotechnology and Genetic Engineering Reviews, 16(1), 141–176.
Yew, H.-C., & Misran, M. (2019). Characterization of fatty acid based nanostructured lipid carrier (NLC) and their sustained release properties. Progress in Drug Discovery & Biomedical Science, 2(1).
Yu, A.-Q., Pratomo Juwono, N. K., Leong, S. S. J., & Chang, M. W. (2014). Production of fatty acid-derived valuable chemicals in synthetic microbes. Frontiers in Bioengineering and Biotechnology, 2, 78.
Yu, T., Zhou, Y. J., Huang, M., Liu, Q., Pereira, R., David, F., & Nielsen, J. (2018). Reprogramming yeast metabolism from alcoholic fermentation to lipogenesis. Cell, 174(6), 1549–1558.
Zaccheria, F., Mariani, M., Psaro, R., Bondioli, P., & Ravasio, N. (2016). Environmentally friendly lubricants through a zero waste process. Applied Catalysis B: Environmental, 181, 581–586.
Zalles, V., Hansen, M. C., Potapov, P. V, Stehman, S. V, Tyukavina, A., Pickens, A., Song, X.-P., Adusei, B., Okpa, C., & Aguilar, R. (2019). Near doubling of Brazil’s intensive row crop area since 2000. Proceedings of the National Academy of Sciences, 116(2), 428–435.
Zhang, X., Li, M., Agrawal, A., & San, K.-Y. (2011). Efficient free fatty acid production in Escherichia coli using plant acyl-ACP thioesterases. Metabolic Engineering, 13(6), 713–722.
Zhou, Y. J., Buijs, N. A., Siewers, V., & Nielsen, J. (2014). Fatty acid-derived biofuels and chemicals production in Saccharomyces cerevisiae. Frontiers in Bioengineering and Biotechnology, 2, 32.
Zhou, Y. J., Buijs, N. A., Zhu, Z., Gómez, D. O., Boonsombuti, A., Siewers, V., & Nielsen, J. (2016). Harnessing yeast peroxisomes for biosynthesis of fatty-acid-derived biofuels and chemicals with relieved side-pathway competition. Journal of the American Chemical Society, 138(47), 15368–15377.
Zhu, Z., Hu, Y., Teixeira, P. G., Pereira, R., Chen, Y., Siewers, V., & Nielsen, J. (2020). Multidimensional engineering of Saccharomyces cerevisiae for efficient synthesis of medium-chain fatty acids. Nature Catalysis, 3(1), 64–74.