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SUMMARY: Synechococcus elongatus PCC 11801 and 11802 are closely related cyanobacterial strains that are fast‐growing and tolerant to high light and temperature. These strains hold significant promise as chassis for photosynthetic production of chemicals from carbon dioxide. A detailed quantitative understanding of the central carbon pathways would be a reference for future metabolic engineering studies with these strains. We conducted isotopic non‐stationary 13C metabolic flux analysis to quantitively assess the metabolic potential of these two strains. This study highlights key similarities and differences in the central carbon flux distribution between these and other model/non‐model strains. The two strains demonstrated a higher Calvin–Benson–Bassham (CBB) cycle flux coupled with negligible flux through the oxidative pentose phosphate pathway and the photorespiratory pathway and lower anaplerosis fluxes under photoautotrophic conditions. Interestingly, PCC 11802 shows the highest CBB cycle and pyruvate kinase flux values among those reported in cyanobacteria. The unique tricarboxylic acid (TCA) cycle diversion in PCC 11801 makes it ideal for the large‐scale production of TCA cycle‐derived chemicals. Additionally, dynamic labeling transients were measured for intermediates of amino acid, nucleotide, and nucleotide sugar metabolism. Overall, this study provides the first detailed metabolic flux maps of S. elongatus PCC 11801 and 11802, which may aid metabolic engineering efforts in these strains. Significance Statement: We conducted 13C metabolic flux analysis of Synechococcus elongatus PCC 11801 and 11802, providing information on pathway fluxes and turnover rates of various metabolic intermediates. Both strains demonstrate a higher Calvin–Benson–Bassham (CBB) flux and lower oxidative pentose phosphate pathway, photorespiration, and anaplerosis pathway fluxes; S. elongatus PCC 11802 has the highest CBB cycle flux reported for any cyanobacteria. [ABSTRACT FROM AUTHOR]

SUMMARY: Cyanobacteria are attractive model organisms for the study of photosynthesis and diurnal metabolism and as hosts for photoautotrophic production of chemicals. Exposure to bright light or environmental pollutants and a diurnal lifestyle of these prokaryotes may result in significant oxidative stress. Glutathione is a widely studied γ‐glutamyl peptide that plays a key role in managing oxidative stress and detoxification of xenobiotics in cyanobacteria. The functional role and biosynthesis pathways of this tripeptide have been studied in detail in various phyla, including cyanobacteria. However, other γ‐glutamyl peptides remain largely unexplored. We use an integrated approach to identify a number of γ‐glutamyl peptides based on signature mass fragments and mass shifts in them in 13C and 15N enriched metabolite extracts. The newly identified compounds include γ‐glutamyl dipeptides and derivatives of glutathione. Carbon backbones of the former turn over much faster than that of glutathione, suggesting that they follow a distinct biosynthesis pathway. Further, transients of isotopic 13C enrichment show positional labeling in these peptides, which allows us to delineate the alternative biosynthesis pathways. Importantly, the amino acid of γ‐glutamyl dipeptides shows much faster turnover compared to the glutamate moiety. The significant accumulation of γ‐glutamyl dipeptides under slow‐growth conditions combined with the results from dynamic 13C labeling suggests that these compounds may act as reservoirs of amino acids in cyanobacteria. Significance Statement: The role of γ‐glutamyl peptides other than glutathione is largely unexplored in cyanobacterial metabolism. In this study, stable isotope‐assisted identification and quantification of γ‐glutamyl peptides in cyanobacteria has been performed and potential routes of their formation have been proposed based on dynamic 13C labeling. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Accurate quantification of mass isotopologue distribution (MID) of metabolites is a prerequisite for [sup 13]C-metabolic flux analysis. Currently used mass spectrometric (MS) techniques based on multiple reaction monitoring (MRM) place limitations on the number of MIDs that can be analyzed in a single run. Moreover, the deconvolution step results in amplification of error. Here, we demonstrate that SWATH MS/ MS, a data independent acquisition (DIA) technique allows quantification of a large number of precursor and product MIDs in a single run. SWATH sequentially fragments all precursor ions in stacked mass isolation windows. Co-fragmentation of all precursor isotopologues in a single SWATH window yields higher sensitivity enabling quantification of MIDs of fragments with low abundance and lower systematic and random errors. We quantify the MIDs of 53 precursor and product ions corresponding to 19 intracellular metabolites from a dynamic 13C-labeling of a model cyanobacterium, Synechococcus sp. PCC 7002. The use of product MIDs resulted in an improved precision of many measured fluxes compared to when only precursor MIDs were used for flux analysis. The approach is truly untargeted and allows additional metabolites to be quantified from the same data. [ABSTRACT FROM AUTHOR]

ABSTRACT Cyanobacteria, which constitute a quantitatively dominant phylum, have attracted attention in biofuel applications due to favorable physiological characteristics, high photosynthetic efficiency and amenability to genetic manipulations. However, quantitative aspects of cyanobacterial metabolism have received limited attention. In the present study, we have performed isotopically non-stationary 13C metabolic flux analysis (INST-13C-MFA) to analyze rerouting of carbon in a glycogen synthase deficient mutant strain ( glgA-I glgA-II) of the model cyanobacterium Synechococcus sp. PCC 7002. During balanced photoautotrophic growth, 10-20% of the fixed carbon is stored in the form of glycogen via a pathway that is conserved across the cyanobacterial phylum. Our results show that deletion of glycogen synthase gene orchestrates cascading effects on carbon distribution in various parts of the metabolic network. Carbon that was originally destined to be incorporated into glycogen gets partially diverted toward alternate storage molecules such as glucosylglycerol and sucrose. The rest is partitioned within the metabolic network, primarily via glycolysis and tricarboxylic acid cycle. A lowered flux toward carbohydrate synthesis and an altered distribution at the glucose-1-phosphate node indicate flexibility in the network. Further, reversibility of glycogen biosynthesis reactions points toward the presence of futile cycles. Similar redistribution of carbon was also predicted by Flux Balance Analysis. The results are significant to metabolic engineering efforts with cyanobacteria where fixed carbon needs to be re-routed to products of interest. Biotechnol. Bioeng. 2017;114: 2298-2308. © 2017 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

Synechococcus elongatus PCC 11801 and 11802 are closely related cyanobacterial strains that are fast-growing and tolerant to high light and temperature. These strains hold significant promise as chassis for photosynthetic production of chemicals from carbon dioxide. A detailed quantitative understanding of the central carbon pathways would be a reference for future metabolic engineering studies with these strains. We conducted isotopic non-stationary 13 C metabolic flux analysis to quantitively assess the metabolic potential of these two strains. This study highlights key similarities and differences in the central carbon flux distribution between these and other model/non-model strains. The two strains demonstrated a higher Calvin-Benson-Bassham (CBB) cycle flux coupled with negligible flux through the oxidative pentose phosphate pathway and the photorespiratory pathway and lower anaplerosis fluxes under photoautotrophic conditions. Interestingly, PCC 11802 shows the highest CBB cycle and pyruvate kinase flux values among those reported in cyanobacteria. The unique tricarboxylic acid (TCA) cycle diversion in PCC 11801 makes it ideal for the large-scale production of TCA cycle-derived chemicals. Additionally, dynamic labeling transients were measured for intermediates of amino acid, nucleotide, and nucleotide sugar metabolism. Overall, this study provides the first detailed metabolic flux maps of S. elongatus PCC 11801 and 11802, which may aid metabolic engineering efforts in these strains., (© 2023 Society for Experimental Biology and John Wiley & Sons Ltd.)

Cyanobacteria are attractive model organisms for the study of photosynthesis and diurnal metabolism and as hosts for photoautotrophic production of chemicals. Exposure to bright light or environmental pollutants and a diurnal lifestyle of these prokaryotes may result in significant oxidative stress. Glutathione is a widely studied γ-glutamyl peptide that plays a key role in managing oxidative stress and detoxification of xenobiotics in cyanobacteria. The functional role and biosynthesis pathways of this tripeptide have been studied in detail in various phyla, including cyanobacteria. However, other γ-glutamyl peptides remain largely unexplored. We use an integrated approach to identify a number of γ-glutamyl peptides based on signature mass fragments and mass shifts in them in 13 C and 15 N enriched metabolite extracts. The newly identified compounds include γ-glutamyl dipeptides and derivatives of glutathione. Carbon backbones of the former turn over much faster than that of glutathione, suggesting that they follow a distinct biosynthesis pathway. Further, transients of isotopic 13 C enrichment show positional labeling in these peptides, which allows us to delineate the alternative biosynthesis pathways. Importantly, the amino acid of γ-glutamyl dipeptides shows much faster turnover compared to the glutamate moiety. The significant accumulation of γ-glutamyl dipeptides under slow-growth conditions combined with the results from dynamic 13 C labeling suggests that these compounds may act as reservoirs of amino acids in cyanobacteria., (© 2021 Society for Experimental Biology and John Wiley & Sons Ltd.)

Recently, the sequential windowed acquisition of all theoretical fragment ion mass spectra (SWATH) method coupled with liquid chromatography has been demonstrated for the quantification of isotopic 13 C enrichment in a large number of cellular metabolites and fragments. SWATH, a data-independent acquisition (DIA) method, alleviates the need for data deconvolution and shows greater accuracy in the quantification of low abundance isotopologs of fragments thereby resulting in a lower systematic error. Here we provide a detailed protocol for the design of Q1 mass isolation windows and the post-acquisition data analysis with emphasis on the untargeted nature of SWATH.

Accurate quantification of mass isotopolog distribution (MID) of intracellular metabolites is a key requirement for 13 C metabolic flux analysis ( 13 C-MFA). Liquid chromatography coupled with mass spectrometry (LC/MS) has emerged as a frontrunner technique that combines two orthogonal separation strategies. While metabolomics requires separation of monoisotopic peaks, 13 C-MFA imposes additional demands for chromatographic separation as isotopologs of metabolites significantly add to the number of analytes. In this protocol chapter, we discuss two liquid chromatography methods, namely, reverse phase ion-pairing and hydrophilic interaction chromatography (HILIC) that together can separate a wide variety of metabolites that are typically used for 13 C metabolic flux analysis.

13 C Metabolic Flux Analysis ( 13 C-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 13 C enrichment can be quantified accurately. Experimental techniques for tracking 13 C 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 13 C-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 X 13 CMS, DynaMet, geoRge, and HiResTEC with three diverse datasets. The tools provided a global, untargeted view of 13 C 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., (© 2019 The Authors.)

Cyanobacteria, which constitute a quantitatively dominant phylum, have attracted attention in biofuel applications due to favorable physiological characteristics, high photosynthetic efficiency and amenability to genetic manipulations. However, quantitative aspects of cyanobacterial metabolism have received limited attention. In the present study, we have performed isotopically non-stationary 13 C metabolic flux analysis (INST- 13 C-MFA) to analyze rerouting of carbon in a glycogen synthase deficient mutant strain (glgA-I glgA-II) of the model cyanobacterium Synechococcus sp. PCC 7002. During balanced photoautotrophic growth, 10-20% of the fixed carbon is stored in the form of glycogen via a pathway that is conserved across the cyanobacterial phylum. Our results show that deletion of glycogen synthase gene orchestrates cascading effects on carbon distribution in various parts of the metabolic network. Carbon that was originally destined to be incorporated into glycogen gets partially diverted toward alternate storage molecules such as glucosylglycerol and sucrose. The rest is partitioned within the metabolic network, primarily via glycolysis and tricarboxylic acid cycle. A lowered flux toward carbohydrate synthesis and an altered distribution at the glucose-1-phosphate node indicate flexibility in the network. Further, reversibility of glycogen biosynthesis reactions points toward the presence of futile cycles. Similar redistribution of carbon was also predicted by Flux Balance Analysis. The results are significant to metabolic engineering efforts with cyanobacteria where fixed carbon needs to be re-routed to products of interest. Biotechnol. Bioeng. 2017;114: 2298-2308. © 2017 Wiley Periodicals, Inc., (© 2017 Wiley Periodicals, Inc.)