Search bioRxiv⌕ Search

bioRxiv · 10.1101/381913

Synthetic metabolic pathways for photobiological conversion of CO2 into hydrocarbon fuel

Abstract

Liquid fuels sourced from fossil sources are the dominant energy form for mobile transport today. The consumption of fossil fuels is still increasing, resulting in a continued search for more sustainable methods to renew our supply of liquid fuel. Photosynthetic microorganisms naturally accumulate hydrocarbons that could serve as a replacement for fossil fuel, however productivities remain low. We report successful introduction of five synthetic metabolic pathways in two green cell factories, prokaryotic cyanobacteria and eukaryotic algae. Heterologous thioesterase expression enabled high-yield conversion of native acyl-ACP into free fatty acids (FFA) in Synechocystis sp. PCC 6803 but not in Chlamydomonas reinhardtii where the polar lipid fraction instead was enhanced. Despite no increase in measurable FFA in Chlamydomonas, genetic recoding and over-production of the native fatty acid photodecarboxylase (FAP) resulted in increased accumulation of 7-heptadecene. Implementation of a carboxylic acid reductase (CAR) and aldehyde deformylating oxygenase (ADO) dependent synthetic pathway in Synechocystis resulted in the accumulation of fatty alcohols and a decrease in the native saturated alkanes. In contrast, the replacement of CAR and ADO with Pseudomonas mendocina UndB (so named as it is responsible for 1-undecene biosynthesis in Pseudomonas) or Chlorella variabilis FAP resulted in high-yield conversion of thioesterase-liberated FFAs into corresponding alkenes and alkanes, respectively. At best, the engineering resulted in an increase in hydrocarbon accumulation of 8- (from 1 to 8.5 mg/g dell dry weight) and 19-fold (from 4 to 77 mg/g cell dry weight) for Chlamydomonas and Synechocystis, respectively. In conclusion, reconstitution of the eukaryotic algae pathway in the prokaryotic cyanobacteria host generated the most effective system, highlighting opportunities for mix-and-match synthetic metabolism. These studies describe functioning synthetic metabolic pathways for hydrocarbon fuel synthesis in photosynthetic microorganisms for the first time, moving us closer to the commercial implementation of photobiocatalytic systems that directly convert CO2 into infrastructure-compatible fuels.\n\nHighlightsO_LISynthetic metabolic pathways for hydrocarbon fuels were engineered in algae\nC_LIO_LIFree fatty acids were effectively converted into alkenes and alkanes\nC_LIO_LITransfer of algal pathway into cyanobacteria was the most effective\nC_LIO_LIAlkane yield was enhanced 19-fold in Synechocystis spp. PCC 6803\nC_LIO_LIAlkene yield was enhanced 8-fold in Chlamydomonas reinhardtii\nC_LI

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Yunus, I. S., Wichmann, J., Woerdenweber, R., Lauersen, K. J., Kruse, O., Jones, P.. 2018-08-01. Synthetic metabolic pathways for photobiological conversion of CO2 into hydrocarbon fuel. https://doi.org/10.1101/381913

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

Machine learning guided design of strong transcriptional activation domains

Artificial intelligence has accelerated the design of structured proteins, but it remains difficult to design functional intrinsically disordered proteins because of weak structural constraints and poorly defined sequence-to-function relationships1. Activation domains (ADs), transcription factor regions that recruit coactivators, are an excellent test case for the de novo design of intrinsically disordered sequences. ADs are one of the oldest groups of functional intrinsically disordered sequences2 and designed ADs have applications in synthetic biology, biotechnology, and agriculture. We computationally generated 500,000 candidate sequences that resembled known ADs and predicted AD function with extant machine learning models, including three neural networks. From high-scoring sequences, we selected 18,750 for experimental validation in yeast. Surprisingly, >90% of the 16,770 well-measured sequences function as ADs. Sequences predicted to be active by multiple models were stronger, motivating development of a fast and accurate consensus AD predictor, MADRIGAL. A number of our designed ADs retain functionality across fungi, plants, and human cells. This work illustrates a generalizable paradigm for incorporating sequence-to-function models into the design loop to efficiently generate functional intrinsically disordered sequences.

synthetic biology↗

E. coli-produced nanobody fusions as a pan-serotype platform for AAV purification, quantification, and detection

Research, production and application of the recombinant adeno-associated virus (rAAV) require versatile tools for rapid and cost-effective advances. We developed fusion constructs with the pan-serotype, AAV-binding VHH-antibody-fragment named nanobody AAVX and devised procedures for AAV purification, quantification, and detection. Starting from an amino acid sequence, we cytosolically expressed in E. coli nanobody AAVX carrying various tags and fusion partners. Very efficient soluble production followed by a one-step immobilized metal-ion affinity chromatography (IMAC) yielded mostly >90% pure protein. Crosslinking AAVX with an agarose matrix enabled efficient purification of intact AAV2 and AAV5 capsids from cell lysates, as assessed by qPCR and ELISA. AAVX also supported effective AAV quantification by ELISA, as capture reagent and, when fused to luciferase, as detection reagent. Using tagged AAVX and streptavidin biosensors, we developed a rapid and label-free quantification assay of AAV capsids by biolayer interferometry (BLI). Finally, immunostaining with an AAVX-eGFP fusion visualized AAV capsids in fixed HEK-293 cells by fluorescence microscopy. Collectively, these results establish nanobody AAVX fusion proteins as versatile and readily customizable tools for AAV research and bioprocessing.

synthetic biology↗

Duality Vaccination through Nanodesign of Click-Ligated B-Cell Inhibitory Receptor Bridging

Synthesis of precise and robust molecular architectures is critical to harness the power of the immune system. The dimensions, rigidity and multivalency of nanoparticles contribute to eliciting high levels of antibodies from vaccination. However, antibodies vary hugely in quality: some antibodies are highly effective at neutralizing pathogens, while others provide little or no benefit. Here we establish switchable and modular platforms for protein and nanoparticle assembly that program the target of antibody responses. We introduce Duality vaccination: the simultaneous delivery of activating and inhibitory stimuli for focusing immune responses. To construct activatory immunogens, we employ click biology with spontaneous amidation to functionalize plug-and-display self-assembling porous dodecahedral nanocages. We construct inhibitory immunogens using SpyMask protease-gated bispecific assembly, ligating the antigen to binders that bridge the B cell receptor to immune checkpoint receptors. This dual immunogen architecture tailors the elicited antibodies to down-modulate undesired B cell responses. We establish the effect of temporal and spatial separation of activatory and inhibitory immunogen delivery. We further explore sensitivity to valency, linker flexibility and adjuvant delivery, employing model targets and coronavirus antigens. Dual programmable functionalization identifies key nanodesign features to control in vivo outputs, providing logic-gating towards urgent challenges in the creation of protective vaccines.

synthetic biology↗