New Applications of Synthetic Biology Tools for Cyanobacterial Metabolic Engineering

Abstract

Cyanobacteria are promising microorganisms for sustainable biotechnologies, yet unlocking their potential requires radical re-engineering and application of cutting-edge synthetic biology techniques. In recent years, the available devices and strategies for modifying cyanobacteria have been increasing, including advances in the design of genetic promoters, ribosome binding sites, riboswitches, reporter proteins, modular vector systems, and markerless selection systems. Because of these new toolkits, cyanobacteria have been successfully engineered to express heterologous pathways for the production of a wide variety of valuable compounds. Cyanobacterial strains with the potential to be used in real-world applications will require the refinement of genetic circuits used to express the heterologous pathways and development of accurate models that predict how these pathways can be best integrated into the larger cellular metabolic network. Herein, we review advances that have been made to translate synthetic biology tools into cyanobacterial model organisms and summarize experimental and in silico strategies that have been employed to increase their bioproduction potential. Despite the advances in synthetic biology and metabolic engineering during the last years, it is clear that still further improvements are required if cyanobacteria are to be competitive with heterotrophic microorganisms for the bioproduction of added-value compounds.

Keywords: cyanobacteria; genome scale models; metabolic engineering; photosynthesis; synthetic biology.

Figure 1

Regulatory mechanisms of inducible promoters recently introduced into cyanobacteria. (A) Arabinose-inducible gene expression from P_BAD, which is both positively and negatively regulated by the transcriptional regulator AraC. In the absence of arabinose, an AraC dimer contacts the O₂ and I₁ half sites of the promoter favoring the formation of a DNA loop that is unfavorable for RNA polymerase binding. When arabinose is present, AraC undergoes a structural change that releases the DNA loop, and ideally positions an AraC activation domain that promotes gene transcription. (B) Rhamnose-inducible gene expression from P_rhaBAD. In the absence of rhamnose RhaS is unable to dimerize, limiting its capacity to bind to promoter elements. In the presence of rhamnose, a dimer of RhaS binds to the I₁ and I₂ repeat half-sites of the rhaBAD promoter, recruiting RNA polymerase and activating the transcription of the target gene. (C) The vanillate-inducible promoter, P_van, is repressed by a dimer of VanR bound to its operator. When vanillate is present, two molecules bind the VanR dimer, resulting in a conformation change and release of transcriptional repression. I₁, binding site 1 in P_BAD and P_rhaBAD; I₂, binding site 2 in P_BAD and P_rhaBAD; GOI, gene of interest; mRNA, messenger RNA; O₂, operator of P_BAD; O_vanR, operator in P_van; RNA pol, RNA polymerase. In all cases, left and right panel represent uninduced and induced promoters, respectively.

Figure 2

CRISPR-cas technologies used for genome editing of cyanobacterial genome. (A) CRISPR-cas systems used in cyanobacteria: Cas9 (left) and Cas12a (right). In type II systems, Cas9 (green) forms a complex with the crRNA (red) and tracrRNA (brown), whereas in type V systems, Cas12a (blue) forms a complex with its crRNA (red). Both nucleases identify their target sites on the basis of complementarity of the guide sequence (blue) by heteroduplex formation, as well as the presence of a neighboring protospacer-adjacent motif (PAM; purple), although the positioning of the PAM is distinct between systems Cas9 cleaves the complementary DNA strand using its HNH domain, and a second RuvC domain to cleave the non-complementary strand. Cas12a cleaves target DNA using one RuvC endonuclease domain, and a second endonuclease activity is attributed to a novel nuclease domain. (B) Example application of CRISPR/Cas12a in Synechococcus elongatus PCC 7942. This system is based on the use of a single plasmid that contains: the cas12a gene under the lac promoter and a crRNA-encoding array (from Francisella novicida) under a constitutive (J23119) promoter. This plasmid allows for inducible, transient expression of cas12a. This crRNA-encoding array contains a leader sequence (1) followed by direct repeat (2) and spacer (3, 4, 5) sequences, and a terminator (6). In most cyanobacterial CRISPR-Cas reports a single spacer region (e.g., number 3) acts as the genome target spacer, while other spacers are not utilized. Multiple genomic regions can be targeted by encoding other spacers with complementary sequences, or the efficiency of modifying a single genomic loci can be improved by utilizing multiple spacers (Niu et al., 2018). Homology regions designed to promote recombination-mediated repair can also be encoded in the plasmid (represented by orange and green rectangles). Once inside the cell, an active and mature Cas12a-crRNA complex forms and is directed to the target sequence. After the introduction of the 5-nt staggered double-stranded break, the homology regions in the plasmid serve as a repair template to introduce the intended genomic changes. The transconjugants are selected on BG11 agar plates supplemented with kanamycin. The positive colonies are streaked on BG11 agar plates to cure the plasmid and they are assayed to check the loss by the inability to grow on kanamycin-containing media. Depicted system is modeled after the one described by Ungerer and Pakrasi (2016).

Figure 3

Schematic representation of engineering strategies that increase photosynthetic activity in cyanobacteria. Using ATP and NADPH produced by the light reactions (inset), the CBB acts to assimilate inorganic carbon via a RuBisCO—mediated reaction in the carboxysome (yellow icosahedron) lumen. Upregulation of multiple steps of the carbon concentration mechanism or CBB cycle enzymes has been shown to increase total carbon uptake rates by cyanobacteria (blue arrowheads). Additionally, the regeneration of RuBisCO substrate, ribulose 1,5-bisphosphate, by feeding external carbohydrates has been used to increase CO₂ assimilation rates. Multiple metabolic pathways (red arrows) that have been heterologously expressed in cyanobacteria have also been demonstrated to increase the effective rate of carbon fixation, perhaps by relieving sink inhibition of photosynthesis. 2AL, 2-acetolactate; 2 OIV, 2-ketoisovalerate; 2OG, 2-oxoglutarate; 3PGA, 3-phosphoglycerate; 6PG, 6-phosphoglycerate; AcALD, acetaldehyde; Ctb₆f, cytochrome b₆f; E4P, erythrose 4-phosphate; EtOH, ethanol; F1,6BP, fructose-1,6-bisphosphate; F6P, fructose-6-phosphate; Fd, ferredoxin; G6P, glucose 6-phosphate; Glu-ADP, Glucose-ADP; OAA, oxalacetate; P450, cytochrome P450; PC, plastocyanin; PEP, phosphoenolpyruvate; PQ, plastoquinone pool; PSI, photosystem I; PSII, photosystem II; Ru5P, ribulose-5-phosphate; S1,7BP, sedoheptulose-1,7-bisphosphate; S7P, sedoheptulose-7-phosphate; TCA, tricarboxylic acid; X5P, xylulose-5-phosphate.

Figure 4

Development of cyanobacterial GSMs. Early cyanobacterial GSMs were developed based on biochemical data and were focused mainly on central carbon metabolism and linked to basic representations of photosynthetic pathways (Cogne et al., ; Shastri and Morgan, ; Hong and Lee, 2007). Numerous advances have accelerated the reconstruction of GSMs, including improved quantity and quality of data described in public databases (e.g., CyanoBase, TransportDB, KEGG, and MetaCyc) and the development of tools for rapid generation of drafts and for gap-filling. The quality of GSMs has been substantially improved with the inclusion of gene-protein-reaction (GPR) associations, which has been assessed by essential gene prediction based on the availability of experimental data. This methodology allows identify four different kind of predictions: true positives, true negatives, false positives, and false negatives. True positives and true negatives are obtained when both prediction and experimental data indicate a gene is essential and non-essential, respectively (the first and the second case). False positives occur when the model says a gene is essential, but experiments suggest otherwise (the third case). False negatives are generated when a gene is predicted to be non-essential but in reality, it is essential (the fourth case). However, new improvements could further improve GSM predictive ability, including the integration of—omics datasets and the improvement of photosynthesis and photorespiration modeling. A long-term goal would be the development of genome-scale kinetic models, which might be expected to provide more accurate metabolic predictions. Logos for MetaCyc, TransportDB, and CyanoBase are used with permission.