Highlighting the potential of Synechococcus elongatus PCC 7942 as platform to produce α-linolenic acid through an updated genome-scale metabolic modeling

Abstract

Cyanobacteria are prokaryotic organisms that capture energy from sunlight using oxygenic photosynthesis and transform CO2 into products of interest such as fatty acids. Synechococcus elongatus PCC 7942 is a model cyanobacterium efficiently engineered to accumulate high levels of omega-3 fatty acids. However, its exploitation as a microbial cell factory requires a better knowledge of its metabolism, which can be approached by using systems biology tools. To fulfill this objective, we worked out an updated, more comprehensive, and functional genome-scale model of this freshwater cyanobacterium, which was termed iMS837. The model includes 837 genes, 887 reactions, and 801 metabolites. When compared with previous models of S. elongatus PCC 7942, iMS837 is more complete in key physiological and biotechnologically relevant metabolic hubs, such as fatty acid biosynthesis, oxidative phosphorylation, photosynthesis, and transport, among others. iMS837 shows high accuracy when predicting growth performance and gene essentiality. The validated model was further used as a test-bed for the assessment of suitable metabolic engineering strategies, yielding superior production of non-native omega-3 fatty acids such as α-linolenic acid (ALA). As previously reported, the computational analysis demonstrated that fabF overexpression is a feasible metabolic target to increase ALA production, whereas deletion and overexpression of fabH cannot be used for this purpose. Flux scanning based on enforced objective flux, a strain-design algorithm, allowed us to identify not only previously known gene overexpression targets that improve fatty acid synthesis, such as Acetyl-CoA carboxylase and β-ketoacyl-ACP synthase I, but also novel potential targets that might lead to higher ALA yields. Systematic sampling of the metabolic space contained in iMS837 identified a set of ten additional knockout metabolic targets that resulted in higher ALA productions. In silico simulations under photomixotrophic conditions with acetate or glucose as a carbon source boosted ALA production levels, indicating that photomixotrophic nutritional regimens could be potentially exploited in vivo to improve fatty acid production in cyanobacteria. Overall, we show that iMS837 is a powerful computational platform that proposes new metabolic engineering strategies to produce biotechnologically relevant compounds, using S. elongatus PCC 7942 as non-conventional microbial cell factory.

Model validation and selection in metabolic flux analysis and flux balance analysis

“…Collecting the true positive, true negative, false positive, and false negative predictions from the in silico versus in vivo lethality predictions into a confusion matrix allows for an at-a-glance evaluation of overall model accuracy and for the comparison of alternative model architectures. 68 Researchers sometimes use algorithms to identify knockouts that couple biomass accumulation to flux through a reaction for biotechnological applications. [63][64][65] This requires that models accurately predict growth/no-growth phenotypes for gene knockouts, but previous work in a model of Saccharomyces cerevisiae, for example, shows that FBA performs poorly at predicting the synthetic lethality of double-knockouts, making this a serious concern.…”

“…Conversely, in silico lethality predictions not confirmed by experiment suggest the model is missing isoforms or alternative reaction routes. Collecting the true positive, true negative, false positive, and false negative predictions from the in silico versus in vivo lethality predictions into a confusion matrix allows for an at‐a‐glance evaluation of overall model accuracy and for the comparison of alternative model architectures 68 . Researchers sometimes use algorithms to identify knockouts that couple biomass accumulation to flux through a reaction for biotechnological applications 63–65 .…”

The Specificities of Lysophosphatidic Acid Acyltransferase and Fatty Acid Desaturase Determine the High Content of Myristic and Myristoleic Acids in Cyanobacterium sp. IPPAS B-1200

“…IPPAS B-1200, a cyanobacterium isolated from samples obtained from the saline lake Balkhash, contains 30-40% C14 saturated myristic and monounsaturated myristoleic acids [5]. An even more simple FA profile is characteristic for the cyanobacterium Synechococcus elongatus PCC 7942-14:0 (<1%), 16:0 (45%), 16:1 (50%), 18:0 (1%), and 18:1∆9 (3%) [9]. S. elongatus PCC 7942 has been widely used as a model to study the process of FA desaturation [9,10] and the properties of FADs [11,12].…”

“…An even more simple FA profile is characteristic for the cyanobacterium Synechococcus elongatus PCC 7942-14:0 (<1%), 16:0 (45%), 16:1 (50%), 18:0 (1%), and 18:1∆9 (3%) [9]. S. elongatus PCC 7942 has been widely used as a model to study the process of FA desaturation [9,10] and the properties of FADs [11,12].…”