An algal photoenzyme converts fatty acids to hydrocarbons

Sorigué, Damien; Légeret, Bertrand; Cuiné, Stéphan; Blangy, Stéphanie; Moulin, Solène; Billon, Emmanuelle; Richaud, Pierre; Brugière, Sabine; Couté, Yohann; Nurizzo, Didier; Müller, Pavel; Brettel, Klaus; Pignol, David; Arnoux, Pascal; Li‐Beisson, Yonghua; Peltier, Gilles; Beisson, Fred

doi:10.1126/science.aan6349

Cited by 347 publications

(497 citation statements)

References 44 publications

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“…In accordance with previous observations,7a Cv FAP showed the highest activity with long‐chain fatty acids (C>14). Interestingly, the conversions of oleic acid and linoleic acid were significantly lower than of the fully saturated counterpart (stearic acid).…”

supporting

confidence: 93%

“…For the production of the Cv FAP in E. coli , two constructs were designed based on a previously reported construct 7a. The constructs both consist of sequentially a 6× His‐tag, thioredoxin (TrxA) tag, tobacco etch virus (TEV) protease cleavage site, and the gene coding for Cv FAP (GenBank: KY511411.1).…”

Section: Methodsmentioning

confidence: 99%

“…Interestingly, the conversions of oleic acid and linoleic acid were significantly lower than of the fully saturated counterpart (stearic acid). We therefore investigated the relative activity of Cv FAP towards some oleic acid isomers ( cis / trans and regioisomers, Table S3) and docked these isomers into the crystal structure of Cv FAP (PDB: 5NCC; Figures S14–17) 7a. A good correlation was found between the initial decarboxylation rate and the distance of the substrate carboxylate group from the flavin cofactor (Table S3).…”

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confidence: 99%

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Light‐Driven Enzymatic Decarboxylation of Fatty Acids

et al. 2018

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The photoenzymatic decarboxylation of fatty acids to alkanes is proposed as an alternative approach for the synthesis of biodiesel. By using a recently discovered photodecarboxylase from Chlorella variabilis NC64A (CvFAP) we demonstrate the irreversible preparation of alkanes from fatty acids and triglycerides. Several fatty acids and their triglycerides are converted by CvFAP in near‐quantitative yield and exclusive selectivity upon illumination with blue light. Very promising turnover numbers of up to 8000 were achieved in this proof‐of‐concept study.

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confidence: 93%

Section: Methodsmentioning

confidence: 99%

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Light‐Driven Enzymatic Decarboxylation of Fatty Acids

et al. 2018

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“…4). While these proof-of-concept examples have led to the production of a rather simple small molecule, so far, algal photoenzymes have been shown to convert fatty acids to hydrocarbons by direct light activation 54 . Hence, these examples may be regarded as door-openers for yet-to-be-expected next steps in this highly vibrant field of research.…”

Section: Review Articlementioning

confidence: 99%

Opportunities and challenges for combining chemo- and biocatalysis

et al. 2018

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N ature has evolved highly efficient systems in the form of cascade reactions, which assemble the metabolic networks that support life (growth and survival). The basic principle of cascade reactions is also frequently used in biocatalysis, using enzymes in isolation, as well as in combination with chemocatalysts (see Fig. 1 and Box 1 for definition of terms) [1][2][3][4][5][6][7] . As there is no need for purification and isolation of intermediates, operating time, production costs and waste are reduced, and concomitantly, overall yields are improved. In addition, the problem of unstable or difficult to handle intermediates can be overcome, and reactivity as well as selectivity can be enhanced by avoiding unfavourable reaction equilibria through the cooperative effects of multiple catalysts 8 . Starting in the 1980s, the early examples of the combination of chemo-and biocatalysts were reported by the van Bekkum group, who pioneered the development of a process to make the sugar substitute d-mannitol from readily available d-glucose through the combination of a heterogeneous metal-catalysed hydrogenation and an enzyme-catalysed isomerization 9 . The first broadly applied technology for the combination of enzyme and metalcatalysts, which was the research subject of many academic groups as well as industry, emerged in the 1990s from the Williams group 10,11 and aimed to achieve higher yields than classical kinetic resolution of racemates, thus overcoming the limitation of a maximum yield of 50% in the latter case. A prominent example of work that developed this theme is the combination of lipase-catalysed kinetic resolution via acylation of secondary alcohols with Pd-or Rh-catalysed racemization via reversible transfer hydrogenation to achieve a dynamic kinetic resolution (DKR) [12][13][14] . This example was facilitated in part because lipases are active and stable in organic solvents. Later, for instance, Turner's group combined a monoamine oxidase-catalysed imine formation with a chemical reduction 15 to achieve the 100% theoretical yield through a deracemization process. In addition to the combination of metalcatalysis with enzymes, organocatalysis, electrochemistry and light-induced reaction couples have since then been studied extensively, going far beyond the scope of a DKR.The challenges to combining chemo-and biocatalysis in cascades (see Box 1 for definitions and Table 1) can be daunting, not least the requirement for the chemical step to occur in the presence of water, the preferred solvent for enzymes 3 . This Review therefore highlights recent examples of the combination of chemo-and biocatalysts in aqueous multistep syntheses, and looks at how to overcome limitations by, for example, design of appropriate reaction conditions, protein engineering and advanced reactor concepts. Furthermore, trends such as the integration of transition metalcatalysis into microorganisms and the introduction of novel chemistry into engineered enzymes are discussed, and a critical assessment of the impact of this research ...

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“…This opened full automation to any sample presented in any mount and has provided a new tool to structural biologists, allowing the process of collecting hundreds of data sets or screening hundreds of crystals to be 'outsourced', freeing their time and often collecting better data . At the time of writing, the beamline has processed more than 39,000 samples representing a wide range of projects, from those that require extensive screening to find the best diffracting crystal (Na et al, 2017;Sorigué et al, 2017;Naschberger et al 2017) to small molecule fragment screening (Cheeseman et al, 2017;Hiruma et al, 2017) and experimental phasing at high and low resolutions (Kharde et al, 2015;Muir et al, 2016). The beamline is able to deal with a wide range of samples by combining parameters provided by the user with information gathered during processing.…”

Section: Introductionmentioning

confidence: 99%

Recent improvements to the automatic characterization and data collection algorithms on MASSIF-1

Svensson

Gilski

Nurizzo

et al. 2017

Preprint

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SynopsisSignificant improvements in the sample location, characterisation and data collection algorithms on the autonomous ESRF beamline MASSIF-1 are described. The workflows now include dynamic beam diameter adjustment and multi-position and multi-crystal data collections.. CC-BY-ND 4.0 International license peer-reviewed) is the author/funder. It is made available under a The copyright holder for this preprint (which was not . http://dx.doi.org/10.1101/236596 doi: bioRxiv preprint first posted online 2 Abstract Macromolecular crystallography (MX) is now a mature and widely used technique essential in the understanding of biology and medicine. Increases in computing power combined with robotics have enabled not only large numbers of samples to be screened and characterised but also for better decisions to be taken on data collection itself. This led to the development of MASSIF-1 at the ESRF, the world's first beamline to run fully automatically while making intelligent decisions taking user requirements into account. Since opening in late 2014 the beamline has now processed over 39,000 samples. Improvements have been made to the speed of the sample handling robotics and error management within the software routines.The workflows initially put in place, while highly innovative at the time, have been expanded to include increased complexity and additional intelligence using the information gathered during characterisation, this includes adapting the beam diameter dynamically to match the diffraction volume within the crystal. Complex multi-position and multi-crystal data collections are now also integrated into the selection of experiments available. This has led to increased data quality and throughput allowing even the most challenging samples to be treated automatically.Key words: X-ray centring; synchrotron instrumentation; macromolecular crystallography; automation; helical data collection; multiple crystal data collection . CC-BY-ND 4.0 International license peer-reviewed) is the author/funder. It is made available under a The copyright holder for this preprint (which was not . http://dx.doi.org/10.1101/236596 doi: bioRxiv preprint first posted online 3 IntroductionAutomation is transforming the way scientific data are collected, allowing large amounts of high quality data to be gathered in a consistent manner (Quintana & Plätzer, 2015;Foster, 2005). Advances in robotics and software have been key in these developments and have had a particular impact on structural biology, allowing multiple constructs to be screened and purified (Camper & Viola, 2009;Hart & Waldo, 2013;Vijayachandran et al., 2011); huge numbers of crystallisation experiments to be performed (Elsliger et al., 2010;Ferrer et al., 2013;Heinemann et al., 2003;Joachimiak, 2009;Calero et al., 2014), samples to be mounted at synchrotrons (Cipriani et al., 2006; Cohen et al., 2002;Jacquamet et al., 2009;Papp et al., 2017;Snell et al., 2004), data to be analysed and processed (Bourenkov & Popov, 2010;Holton & Alber, 2004;Incardona et al., ...

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An algal photoenzyme converts fatty acids to hydrocarbons

Cited by 347 publications

References 44 publications

Light‐Driven Enzymatic Decarboxylation of Fatty Acids

Light‐Driven Enzymatic Decarboxylation of Fatty Acids

Opportunities and challenges for combining chemo- and biocatalysis

Recent improvements to the automatic characterization and data collection algorithms on MASSIF-1

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