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Abstract Background Cyanobacteria, a group of photosynthetic prokaryotes, are being increasingly explored for direct conversion of carbon dioxide to useful chemicals. However, efforts to engineer these photoautotrophs have resulted in low product titers. This may be ascribed to the bottlenecks in metabolic pathways, which need to be identified for rational engineering. We engineered the recently reported, fast-growing and robust cyanobacterium, Synechococcus elongatus PCC 11801 to produce succinate, an important platform chemical. Previously, engineering of the model cyanobacterium S. elongatus PCC 7942 has resulted in succinate titer of 0.43 g l−1 in 8 days. Results Building on the previous report, expression of α-ketoglutarate decarboxylase, succinate semialdehyde dehydrogenase and phosphoenolpyruvate carboxylase yielded a succinate titer of 0.6 g l−1 in 5 days suggesting that PCC 11801 is better suited as host for production. Profiling of the engineered strains for 57 intermediate metabolites, a number of enzymes and qualitative analysis of key transcripts revealed potential flux control points. Based on this, we evaluated the effects of overexpression of sedoheptulose-1,7-bisphosphatase, citrate synthase and succinate transporters and knockout of succinate dehydrogenase and glycogen synthase A. The final construct with seven genes overexpressed and two genes knocked out resulted in photoautotrophic production of 0.93 g l−1 succinate in 5 days. Conclusion While the fast-growing strain PCC 11801 yielded a much higher titer than the model strain, the efficient photoautotrophy of this novel isolate needs to be harnessed further for the production of desired chemicals. Engineered strains of S. elongatus PCC 11801 showed dramatic alterations in the levels of several metabolites suggesting far reaching effects of pathway engineering. Attempts to overexpress enzymes deemed to be flux controlling led to the emergence of other potential rate-limiting steps. Thus, this process of debottlenecking of the pathway needs to be repeated several times to obtain a significantly superior succinate titer.

Summary: Cyanobacteria are gaining importance both as hosts for photoautotrophic production of chemicals and as model systems for studies of diurnal lifestyle. The proteome and transcriptome of cyanobacteria have been closely examined under diurnal growth, whereas the downstream effects on the intermediary metabolism have not received sufficient attention. The present study focuses on identifying the cellular metabolites whose inventories undergo dramatic changes in a fast-growing cyanobacterium, Synechococcus elongatus PCC 11801. We identified and quantified 67 polar metabolites, whose inventory changes significantly during diurnal growth, with some metabolites changing by 100-fold. The Calvin-Benson-Bassham cycle intermediates peak at midday to support fast growth. The hitherto unexplored γ-glutamyl peptides act as reservoirs of amino acids. Interestingly, several storage molecules or their precursors accumulate during the dark phase, dispelling the notion that all biosynthetic activity takes place in the light phase. Our results will guide metabolic modeling and strain engineering of cyanobacteria.

13C Metabolic Flux Analysis (13C-MFA) involves the quantification of isotopic enrichment in cellular metabolites and fitting the resultant data to the metabolic network model of the organism. Coverage and resolution of the resultant flux map depends on the total number of metabolites and fragments in which 13C enrichment can be quantified accurately. Experimental techniques for tracking 13C enrichment are evolving rapidly and large volumes of data are now routinely generated through the use of Liquid Chromatography coupled with High-Resolution Mass Spectrometry (HR-LC/MS). Therefore, the current manuscript is focused on the challenges in high-throughput analyses of such large datasets. Current 13C-MFA studies often have to rely on the targeted quantification of a small subset of metabolites, thereby leaving a large fraction of the data unexplored. A number of public domain software tools have been reported in recent years for the untargeted quantitation of isotopic enrichment. However, the suitability of their application across diverse datasets has not been investigated. Here, we test the software tools X13CMS, DynaMet, geoRge, and HiResTEC with three diverse datasets. The tools provided a global, untargeted view of 13C enrichment in metabolites in all three datasets and a much-needed automation in data analysis. Some inconsistencies were observed in results obtained from the different tools, which could be partially ascribed to the lack of baseline separation and potential mass conflicts. After removing the false positives manually, isotopic enrichment could be quantified reliably in a large repertoire of metabolites. Of the software tools explored, geoRge and HiResTEC consistently performed well for the untargeted analysis of all datasets tested.

13C Metabolic Flux Analysis (13C-MFA) is a powerful tool for quantification of carbon flux distribution in metabolic pathways. However, the requirement to obtain accurate labeling patterns, especially for compounds with low abundance, poses a challenge. Chromatographic separation and high sensitivity of the modern mass spectrometers (MS) alleviate this problem to a certain extent. However, the presence of derivatives such as in-source fragments, multimer ion adducts, and multiply charged ions result in reduced intensity of the molecular ion. While multimer ion adducts have been reported in the field of metabolomics, their presence is considered undesirable in quantitative studies. Here, we demonstrate a novel application of dimer ion adducts in calculating the mass isotopologue distribution (MIDs) of the corresponding monomer ions for public domain and in-house generated datasets comprising of 13C-labeling time-course experiments. Out of the 100 standard compounds analyzed, we could detect multimer ion adducts in 24 of the intermediate metabolites. Further, a subset of these multimer ions were detected in all the biological samples analyzed. Majority of these ion adducts were either not detected in the original study or labeled as a putative features. Regression analysis was performed to estimate the monomer MIDs from those of the dimer. This resulted in accurate estimation regardless of the biological system, chromatographic method, the MS hardware, or the relative abundance of the dimer ion. We argue that this analysis may be useful in cases where satisfactory data cannot be extracted from the chromatographic peaks of the monomer ions.

Cyanobacteria are emerging as hosts for photoautotrophic production of chemicals. Recent studies have attempted to stretch the limits of photosynthetic production, typically focusing on one product at a time, possibly to minimise the additional burden of product separation. Here, we explore the simultaneous production of two products that can be easily separated: ethylene, a gaseous product, and succinate, an organic acid that accumulates in the culture medium. This was achieved by expressing a single copy of the ethylene forming enzyme (efe) under the control of PcpcB, the inducer-free super-strong promoter of phycocyanin β subunit. We chose the recently reported, fast-growing and robust cyanobacterium, Synechococcus elongatus PCC 11801, as the host strain. A stable recombinant strain was constructed using CRISPR-Cpf1 in a first report of markerless genome editing of this cyanobacterium. Under photoautotrophic conditions, the recombinant strain shows specific productivities of 338.26 and 1044.18 μmole/g dry cell weight/h for ethylene and succinate, respectively. These results compare favourably with the reported productivities for individual products in cyanobacteria that are highly engineered. Metabolome profiling and 13C labelling studies indicate carbon flux redistribution and suggest avenues for further improvement. Our results show that S. elongatus PCC 11801 is a promising candidate for metabolic engineering.

A key requirement for 13C Metabolic flux analysis (13C-MFA), a widely used technique to estimate intracellular metabolic fluxes, is an efficient method for the extraction of intermediate metabolites for analysis via liquid chromatography mass spectrometry (LC/MS). The 13C isotopic labeling results in further distribution of an already sparse pool of intermediate metabolites into isotopologues, each appearing as a separate chromatographic feature. We examined some of the reported solvent systems for the extraction of polar intracellular metabolites from three strains of cyanobacteria of the genus Synechococcus, viz., Synechococcus sp. PCC 7002, Synechococcus elongatus PCC 7942, and a newly isolated Synechococcus elongatus PCC 11801 (manuscript under review). High resolution-LC/MS was used to assess the relative abundance of the extracted metabolites. The different solvent systems used for extraction led to statistically significant changes in the extraction efficiency for a large number of metabolites. While a few hundred m/z features or potential metabolites were detected with different solvent systems, the abundance of over a quarter of all metabolites varied significantly from one solvent system to another. Further, the extraction methods were evaluated for a targeted set of metabolites that are important in 13C-MFA studies of photosynthetic organisms. While for the strain PCC 7002, the reported method using methanol-chloroform-water system gave satisfactory results, a mild base in the form of NH4OH had to be used in place of water to achieve adequate levels of extraction for PCC 7942 and PCC 11801. While minor changes in extraction solvent resulted in dramatic changes in the extraction efficiency of a number of compounds, certain metabolites such as amino acids and organic acids were adequately extracted in all the solvent systems tested. Overall, we present a new improved method for extraction using a methanol-chloroform-NH4OH system. Our method improves the extraction of polar compounds such as sugar phosphates, bisphosphates, that are central to 13C-MFA studies.