The future of our project


  ProCF as a prototyping platform

Given the current design of our project, we imagine that ProCF could work as a ‘breadboard’ to provide a low-cost and easy way for prototyping the effect of different fatty acid profiles on the proteome, metabolism, and growth of Saccharomyces cerevisiae. The term ‘breadboard’ comes from a solderless (and therefore reusable) board used in electronics to makes it easier for creating temporary prototypes and experimenting with circuit design. For this reason, breadboards are popular with students and in technological education. We feel that ‘breadboard’ is an apt way to refer to our system as it may be used to compete with the extensive genetic engineering and promotor swapping methods commonly used in these kinds of experiments.

Due to the toxicity of certain types of fatty acids (or their derivatives), a ‘breadboard’ approach to gene expression may prove especially useful in experiments where the overexpression of such types is required. Especially the increased levels of short chain fatty acids, alkanes, alcohols, and aldehydes have been proven to pose severe toxicity to the growth and metabolism of the S. cerevisiae (Besada‐Lombana et al., 2017; Borrull et al., 2015; Jayakody & Jin, 2021; Legras et al., 2010; Liu et al., 2013). For example, studies of transcriptome response to alkanes have helped to identify that efflux pumps are involved in alkane tolerance (Chen et al., 2013; Ling et al., 2013)

Analysis of the expression patterns, stress responses, and membrane modifications in strains subjected to varying levels of overexpression of target compounds, is of the outmost importance to increase their viability as cell factories. It is our belief that ProCF, and projects expanding upon this design, would help to make this process more efficient.

  Future prospects

Our team proposes that S. cerevisiae can be engineered in such a way as to allow the fine-tuning of enzymatic reaction pathways in vivo, by utilising more sophisticated signalling systems than we used for our current project. To this extent we have during our project identified a number of enzymes that target fatty acids to convert them to a number of high-value derivatives, such as aldehydes, alkanes, alpha-oleofins, alcohols and esters. These derivatives are themselves platform molecules, potentially allowing for large library of oleochemicals to be constructed (Biermann et al., 2011; Nikolau et al., 2008).
A table showing potential reactions & products.
Enzyme Species Substrate Product Reference
CAR Mycobacterium marinum Fatty acids Aldehydes Akhtar et al., 2013; Kaehne et al., 2011
α-Dioxygenase Oryza sativa    
ADC Prochlorococcus marinus Aldehydes Alkanes Jiménez‐Díaz et al., 2017
P450 decarboxylase Jeotgalicoccus sp. ATCC 8456 Aldehydes α-Oleofins Rude et al., 2011
AHR Escherichia coli Aldehydes Alcohols Cao et al., 2015
Lipase Rhizomucor miehei Fatty acids + Alcohols Esters Rodrigues & Fernandez-Lafuente, 2010b, 2010a
This is, of course, a simplistic depiction. There are many other steps needed to make such a system work. Introducing heterogenous biosynthesis pathways is often hampered by crosstalk between competing pathways, the production of undesirable and/or toxic side-products and cellular responses. Localization of pathway components and compartmentalization would be key to successfully implement this kind of design, and there is need for very specific metabolic channeling activities. While co-localising enzymes by using synthetic scaffolds has been proven to improve production titers (Dueber et al., 2009; Nygren & Skerra, 2004), concentrating and compartmentalisation of intermediates in cellular organelles (such as vesicles) can isolate the pathways from any competition and provide a more suitable environment for biosynthesis.

Luckily, this has been explored in the current literature (Herrero & Sentandreu, 1988; Reifenrath et al., 2020; Sheng et al., 2016; Wright & Bartel, 2020). We would like to highlight the excellent work previously conducted by iGEM 2017 Team:Cologne-Duesseldorf in their project ARTICO, who designed tools for customising cell compartments in yeast by regulating the import of enzymes into the peroxisomes. The stringent, precise and accurate regulation of gene expression may very well be described as the ‘Holy grail’ of synthetic biology, and the development of modular tools for programming genetic circuits is highly sought after (Benner & Sismour, 2005; Campos, 2009). Exciting new technologies utilising synthetic GPCR signalling transduction pathways (Billerbeck et al., 2018; Lengger & Jensen, 2020; Shaw et al., 2019) and dCas-protein fusions with various gene regulatory domains (Doudna & Charpentier, 2014; La Russa & Qi, 2015) enable fine tuning of expression in a very precise manner.

Ideally, such systems would not only work through ON/OFF states but would allow defined levels and dynamic regulation of gene expression (that ProCF accomplishes with combining different variable chemical induction systems). We believe this is a promising a route to generate high-value products through derivatisation of basic compounds (such as diversification through branching, cyclization, or the introduction of double bonds) that are currently difficult to introduce with conventional chemistry.


Akhtar, M. K., Turner, N. J., & Jones, P. R. (2013). Carboxylic acid reductase is a versatile enzyme for the conversion of fatty acids into fuels and chemical commodities. Proceedings of the National Academy of Sciences, 110(1), 87–92.

Benner, S. A., & Sismour, A. M. (2005). Synthetic biology. Nature Reviews Genetics, 6(7), 533–543.

Besada‐Lombana, P. B., Fernandez‐Moya, R., Fenster, J., & Da Silva, N. A. (2017). Engineering Saccharomyces cerevisiae fatty acid composition for increased tolerance to octanoic acid. Biotechnology and Bioengineering, 114(7), 1531–1538.

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.

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Borrull, A., López‐Martínez, G., Poblet, M., Cordero‐Otero, R., & Rozès, N. (2015). New insights into the toxicity mechanism of octanoic and decanoic acids on Saccharomyces cerevisiae. Yeast, 32(5), 451–460.

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Cao, Y.-X., Xiao, W.-H., Liu, D., Zhang, J.-L., Ding, M.-Z., & Yuan, Y.-J. (2015). Biosynthesis of odd-chain fatty alcohols in Escherichia coli. Metabolic Engineering, 29, 113–123.

Chen, B., Ling, H., & Chang, M. W. (2013). Transporter engineering for improved tolerance against alkane biofuels in Saccharomyces cerevisiae. Biotechnology for Biofuels, 6(1), 1–10.

Doudna, J. A., & Charpentier, E. (2014). The new frontier of genome engineering with CRISPR-Cas9. Science, 346(6213).

Dueber, J. E., Wu, G. C., Malmirchegini, G. R., Moon, T. S., Petzold, C. J., Ullal, A. V, Prather, K. L. J., & Keasling, J. D. (2009). Synthetic protein scaffolds provide modular control over metabolic flux. Nature Biotechnology, 27(8), 753–759.

Herrero, E., & Sentandreu, R. (1988). Protein secretion and compartmentalization in yeast. Microbiologia, 4(2), 73–85.

Jayakody, L. N., & Jin, Y.-S. (2021). In-depth understanding of molecular mechanisms of aldehyde toxicity to engineer robust Saccharomyces cerevisiae. Applied Microbiology and Biotechnology, 1–18.

Jiménez‐Díaz, L., Caballero, A., Pérez‐Hernández, N., & Segura, A. (2017). Microbial alkane production for jet fuel industry: motivation, state of the art and perspectives. Microbial Biotechnology, 10(1), 103–124.

Kaehne, F., Buchhaupt, M., & Schrader, J. (2011). A recombinant α-dioxygenase from rice to produce fatty aldehydes using E. coli. Applied Microbiology and Biotechnology, 90(3), 989–995.

La Russa, M. F., & Qi, L. S. (2015). The new state of the art: Cas9 for gene activation and repression. Molecular and Cellular Biology, 35(22), 3800–3809.

Legras, J. L., Erny, C., Le Jeune, C., Lollier, M., Adolphe, Y., Demuyter, C., Delobel, P., Blondin, B., & Karst, F. (2010). Activation of two different resistance mechanisms in Saccharomyces cerevisiae upon exposure to octanoic and decanoic acids. Applied and Environmental Microbiology, 76(22), 7526–7535.

Lengger, B., & Jensen, M. K. (2020). Engineering G protein-coupled receptor signalling in yeast for biotechnological and medical purposes. FEMS Yeast Research, 20(1), foz087.

Ling, H., Chen, B., Kang, A., Lee, J.-M., & Chang, M. W. (2013). Transcriptome response to alkane biofuels in Saccharomyces cerevisiae: identification of efflux pumps involved in alkane tolerance. Biotechnology for Biofuels, 6(1), 1–10.

Liu, P., Chernyshov, A., Najdi, T., Fu, Y., Dickerson, J., Sandmeyer, S., & Jarboe, L. (2013). Membrane stress caused by octanoic acid in Saccharomyces cerevisiae. Applied Microbiology and Biotechnology, 97(7), 3239–3251.

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.

Nygren, P.-Å., & Skerra, A. (2004). Binding proteins from alternative scaffolds. Journal of Immunological Methods, 290(1–2), 3–28.

Reifenrath, M., Oreb, M., Boles, E., & Tripp, J. (2020). Artificial ER-derived vesicles as synthetic organelles for in vivo compartmentalization of biochemical pathways. ACS Synthetic Biology, 9(11), 2909–2916.

Rodrigues, R. C., & Fernandez-Lafuente, R. (2010a). Lipase from Rhizomucor miehei as a biocatalyst in fats and oils modification. Journal of Molecular Catalysis B: Enzymatic, 66(1–2), 15–32.

Rodrigues, R. C., & Fernandez-Lafuente, R. (2010b). Lipase from Rhizomucor miehei as an industrial biocatalyst in chemical process. Journal of Molecular Catalysis B: Enzymatic, 64(1–2), 1–22.

Rude, M. A., Baron, T. S., Brubaker, S., Alibhai, M., Del Cardayre, S. B., & Schirmer, A. (2011). Terminal olefin (1-alkene) biosynthesis by a novel P450 fatty acid decarboxylase from Jeotgalicoccus species. Applied and Environmental Microbiology, 77(5), 1718–1727.

Shaw, W. M., Yamauchi, H., Mead, J., Gowers, G.-O. F., Bell, D. J., Öling, D., Larsson, N., Wigglesworth, M., Ladds, G., & Ellis, T. (2019). Engineering a model cell for rational tuning of GPCR signaling. Cell, 177(3), 782–796.

Sheng, J., Stevens, J., & Feng, X. (2016). Pathway compartmentalization in peroxisome of Saccharomyces cerevisiae to produce versatile medium chain fatty alcohols. Scientific Reports, 6(1), 1–11.

Wright, Z. J., & Bartel, B. (2020). Peroxisomes form intralumenal vesicles with roles in fatty acid catabolism and protein compartmentalization in Arabidopsis. Nature Communications, 11(1), 1–13.