Call for Biofuels, especially Alkanes

Biofuels which have a closed CO₂ cycle[1] and don’t require expensive, complex chemical processing, are recognized as promising replacements for diesel fuels in the fields of energy and environment. Among them, fatty-acid-derived alkanes have many advantages over other biofuel compounds, such as high caloric value and low carbon emission[2], which means that they could be an ideal replacement for diesel fuels.

Pathway of Alkane Biosynthesis

The pathway of alkane sythesis in microbes has been studied, and heterologous expression in E.coli of the two genes encoding the two key enzymes named NPDC and AAR has been reported, which successfully turns Fatty Acyl-ACP into alkane molecules of certain chain lengths, making it possible for microbes to produce alkanes. In the strain with the highest alkane productivity, alkane titers were over 300 mg/liter using a modified mineral medium, and more than 80% of the hydrocarbons were found outside the cells[3].

Limitations of Directed Evolution

Directed evolution through random mutagenesis, followed by high-throughput selection has made it possible to improve alkane yield or pathway efficiency. However, it can be a daunting task, because there remain many constraints on throughput imposed during the standard directed evolution workflow (library construction, transformation, and screening). We consider screening and selection as rate-limiting steps in directed evolution efforts for alkane overproduction. Therefore, in the production of large chain alkanes, it is crucial for there to be a sensitive and high-throughput screening device for comparing production rates in engineered strains of E. coli.

Difficulties of Selection

Conspicuous products can be accurately measured using standard high-throughput colorimetric and fluorometric assays. Alkanes, however, like many small molecules, have no smell or fluorescence, or essential for growth, and they cannot be readily transformed into compounds possessing these properties[4]. Furthermore, commonly used screening tools like chromatography-mass spectrometry methods are inherently low throughput, with screenable library sizes generally limited to less than 103 variants. Therefore, the improved strains are beyond the reach of a general screening tool and cannot be readily obtained[5].

Use of Transcription Factors

One strategy deserving special attention is the use of transcription factors which have long been used to construct whole-cell biosensors for the detection of environmental pollutants, but remain largely untranslated toward library screening and directed evolution purposes. Transcription factors regulate a promoter’s transcriptional output in response to a small-molecule ligand so it’s possible to report on in vivo small-molecule production.

Screening methods utilizing transcription factors possess many ideal characteristics.The transcription factor-promoter pair can be user-selected to encode for fluorescent or growth-coupled responses, and there’s no need for downstream synthetic chemistry or in vitro manipulation [4]. Therefore,with the design of biosensors, we can transform intracellular alkane molecules without a conspicuous phenotype into detectable signal outputs.

Application of High-throughput Selection

In conclusion, utilizing high-throughput screening to select out desirable mutations is an important step in directed evolution and pathway improvement, which largely increases the library and saves labour and time. In our project, we are designing a selection module for alkanes so that we can use irrational modification to optimize the pathway of alkane synthesis.

Reference

[1] Yan Kung et al. (2012) “From Fields to Fuels: Recent Advances in the Microbial Production of Biofuels.” ACS Synth. Biol. 1, 498−513

[2] Mathew A Rude, Andreas Schirmer et al.(2009) “New microbial fuels: a biotech perspective.” Current Opinion in Microbiology 12:274–281

[3] Andreas Schirmer, Mathew A. Rude et al.(2010) “Microbial Biosynthesis of Alkanes.” Science Vol. 329 no. 5991 pp. 559-562

[4] Jeffrey A. Dietrich, Adrienne E. McKee, Jay D. Keasling et al.(2010) “High-Throughput Metabolic Engineering: Advances in Small-Molecule Screening and Selection.” Annu. Rev. Biochem. 79:563–90

[5] Jina Yang1, Sang Woo Seo1, Sungho Jang et al.(2013) “Synthetic RNA devices to expedite the evolution of metabolite-producing microbes.” Nature Communications DOI: 10.1038/ncomms2404