SWATH Tandem Mass Spectrometry Workflow for Quantification of Mass Isotopologue Distribution of Intracellular Metabolites and Fragments Labeled with Isotopic 13C Carbon

KETCHUP: Parameterizing of large-scale kinetic models using multiple datasets with different reference states

Large-scale kinetic models provide the computational means to dynamically link metabolic reaction fluxes to metabolite concentrations and enzyme levels while also conforming to substrate level regulation. However, the development of broadly applicable frameworks for efficiently and robustly parameterizing models remains a challenge. Challenges arise due to both the heterogeneity, paucity, and difficulty in obtaining flux and/or concentration data but also due to the computational difficulties of the underlying parameter identification problem. Both the computational demands for parameterization, degeneracy of obtained parameter solutions and interpretability of results has so far limited widespread adoption of large-scale kinetic models despite their potential. Herein, we introduce the Kinetic Estimation Tool Capturing Heterogeneous Datasets Using Pyomo (KETCHUP), a flexible parameter estimation tool that leverages a primal-dual interior-point algorithm to solve a nonlinear programming (NLP) problem that identifies a set of parameters capable of recapitulating the (non)steady-state fluxes and concentrations in wild-type and perturbed metabolic networks. KETCHUP is benchmarked against previously parameterized large-scale kinetic models demonstrating an at least an order of magnitude faster convergence than the tool K-FIT while at the same time attaining better data fits. This versatile toolbox accepts different kinetic descriptions, metabolic fluxes, enzyme levels and metabolite concentrations, under either steady-state or instationary conditions to enable robust kinetic model construction and parameterization. KETCHUP supports the SBML format and can be accessed at https://github.com/maranasgroup/KETCHUP.

Isotopically non-stationary 13 C metabolic flux analysis of two closely related fast-growing cyanobacteria, Synechococcus elongatus PCC 11801 and 11802

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.

Metabolomics in drug research and development: The recent advances in technologies and applications

Emerging evidence has demonstrated the vital role of metabolism in various diseases or disorders. Metabolomics provides a comprehensive understanding of metabolism in biological systems. With advanced analytical techniques, metabolomics exhibits unprecedented significant value in basic drug research, including understanding disease mechanisms, identifying drug targets, and elucidating the mode of action of drugs. More importantly, metabolomics greatly accelerates the drug development process by predicting pharmacokinetics, pharmacodynamics, and drug response. In addition, metabolomics facilitates the exploration of drug repurposing and drug-drug interactions, as well as the development of personalized treatment strategies. Here, we briefly review the recent advances in technologies in metabolomics and update our knowledge of the applications of metabolomics in drug research and development.

Reconstruction of Glutathione Metabolism in the Neuronal Model of Rotenone-Induced Neurodegeneration Using Mass Isotopologue Analysis with Hydrophilic Interaction Liquid Chromatography-Zeno High-Resolution Multiple Reaction Monitoring

Accurate reconstruction of metabolic pathways is an important prerequisite for interpreting metabolomics changes and understanding the diverse biological processes in disease models. A tracer-based metabolomics strategy utilizes stable isotope-labeled precursors to resolve complex pathways by tracing the labeled atom(s) to downstream metabolites through enzymatic reactions. Isotope enrichment analysis is informative and achieved by counting total labeled atoms and acquiring the mass isotopologue distribution (MID) of the intact metabolite. However, quantitative analysis of labeled metabolite substructures/moieties (MS² fragments) can offer more valuable insights into the reaction connections through measuring metabolite transformation. In order to acquire the isotopic labeling information at the intact metabolite and moiety level simultaneously, we developed a method that couples hydrophilic interaction liquid chromatography (HILIC) with Zeno trap-enabled high-resolution multiple reaction monitoring (MRM^HR). The method enabled accurate and reproducible MID quantification for intact metabolites as well as their fragmented moieties, with notably high sensitivity in the MS² fragmentation mode based on the measurement of ¹³C- or ¹⁵N-labeled cellular samples. The method was applied to human-induced pluripotent stem cell-derived neurons to trace the fate of ¹³C/¹⁵N atoms from D-¹³C₆-glucose/L-¹⁵N₂-glutamine added to the media. With the MID analysis of both intact metabolites and fragmented moieties, we validated the pathway reconstruction of de novo glutathione synthesis in mid-brain neurons. We discovered increased glutathione oxidization from both basal and newly synthesized glutathione pools under neuronal oxidative stress. Furthermore, the significantly decreased de novo glutathione synthesis was investigated and associated with altered activities of several key enzymes, as evidenced by suppressed glutamate supply via glucose metabolism and a diminished flux of glutathione synthetic reaction in the neuronal model of rotenone-induced neurodegeneration.

13C-Isotope-Assisted Assessment of Metabolic Quenching During Sample Collection from Suspension Cell Cultures

Metabolomics and fluxomics are core approaches to directly profile and interrogate cellular metabolism in response to various genetic or environmental perturbations. In order to accurately measure the abundance and isotope enrichment of intracellular metabolites, cell culture samples must be rapidly harvested and cold quenched to preserve the in vivo metabolic state of the cells at the time of sample collection. When dealing with suspension cultures, this process is complicated by the need to separate the liquid culture media from cellular biomass prior to metabolite extraction. Here, we examine the efficacy of several commonly used metabolic quenching methods, using the model cyanobacterium Synechocystis sp. PCC 6803 as an example. Multiple ¹³C-labeled compounds, including ¹³C-bicarbonate, ¹³C-glucose, and ¹³C-glutamine, were used as tracers during the sample collection and the cold-quenching process to assess the extent of metabolic turnover after cells were harvested from culture flasks. We show that the combination of rapid filtration followed by 100% cold (-80 °C) methanol quenching exhibits the highest quenching efficiency, while mixing cell samples with a partially frozen 30% methanol slurry (-24 °C) followed by centrifugation is slightly less effective at quenching metabolism but enables less laborious sample processing. By contrast, rapidly mixing the cells with a saline ice slurry (∼0 °C) is less effective, as indicated by high isotope-labeling rates after sample harvest, while mixing the cells with 60% cold methanol (-65 °C) prior to centrifugation causes significant metabolite loss. This study demonstrates a rigorous, quantitative, and broadly applicable method for assessing the metabolic quenching efficacy of protocols used for sample collection in metabolomics and fluxomics studies.

An efficient LC-MS method for isomer separation and detection of sugars, phosphorylated sugars, and organic acids

Assessing central carbon metabolism in plants can be challenging due to the dynamic range in pool sizes, with low levels of important phosphorylated sugars relative to more abundant sugars and organic acids. Here, we report a sensitive liquid chromatography-mass spectrometry method for analysing central metabolites on a hybrid column, where both anion-exchange and hydrophilic interaction chromatography (HILIC) ligands are embedded in the stationary phase. The liquid chromatography method was developed for enhanced selectivity of 27 central metabolites in a single run with sensitivity at femtomole levels observed for most phosphorylated sugars. The method resolved phosphorylated hexose, pentose, and triose isomers that are otherwise challenging. Compared with a standard HILIC approach, these metabolites had improved peak areas using our approach due to ion enhancement or low ion suppression in the biological sample matrix. The approach was applied to investigate metabolism in high lipid-producing tobacco leaves that exhibited increased levels of acetyl-CoA, a precursor for oil biosynthesis. The application of the method to isotopologue detection and quantification was considered through evaluating 13C-labeled seeds from Camelina sativa. The method provides a means to analyse intermediates more comprehensively in central metabolism of plant tissues.

Probing the metabolism of γ-glutamyl peptides in cyanobacteria via metabolite profiling and 13 C labeling

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.

Metabolic systems biology and multi-omics of cyanobacteria: Perspectives and future directions

Cyanobacteria are oxygenic photoautotrophs whose metabolism contains key biochemical pathways to fix atmospheric CO₂ and synthesize various metabolites. The development of bioengineering tools has enabled the manipulation of cyanobacterial chassis to produce various valuable bioproducts photosynthetically. However, effective utilization of cyanobacteria as photosynthetic cell factories needs a detailed understanding of their metabolism and its interaction with other cellular processes. Implementing systems and synthetic biology tools has generated a wealth of information on various metabolic pathways. However, to design effective engineering strategies for further improvement in growth, photosynthetic efficiency, and enhanced production of target biochemicals, in-depth knowledge of their carbon/nitrogen metabolism, pathway fluxe distribution, genetic regulation and integrative analyses are necessary. In this review, we discuss the recent advances in the development of genome-scale metabolic models (GSMMs), omics analyses (metabolomics, transcriptomics, proteomics, fluxomics), and integrative modeling approaches to showcase the current understanding of cyanobacterial metabolism.

Cyanobacteria as cell factories: the roles of host and pathway engineering and translational research

Cyanobacteria, a group of photoautotrophic prokaryotes, are attractive hosts for the sustainable production of chemicals from carbon dioxide and sunlight. However, the rates, yields, and titers have remained well below those needed for commercial deployment. We argue that the following areas will be central to the development of cyanobacterial cell factories: engineered and well-characterized host strains, model-guided pathway design, and advanced synthetic biology tools. Although several foundational studies report improved strain properties, translational research will be needed to develop engineered hosts and deploy them for metabolic engineering. Further, the recent developments in metabolic modeling and synthetic biology of cyanobacteria will enable nimble strategies for strain improvement with the complete cycle of design, build, test, and learn.

Characterization and Determination of 13C-Labeled Nonessential Amino Acids in a 13C5-Glutamine Isotope Tracer Experiment with a Mass Spectrometry Strategy Combining Parallel Reaction Monitoring and Multiple Reaction Monitoring

Isotopic tracer, a powerful technique for metabolic pathway analysis, is currently widely applied in metabolic flux analysis. However, the qualitative and quantitative analyses of ¹³C-labeled metabolites pose great challenges, especially in complex biological sample matrices. Here, we present an integrated method for the qualitative and quantitative analyses of various isotopologues and isotopomers of ¹³C-labeled nonessential amino acids (NEAAs) in HepG2 cells incubated with ¹³C₅-glutamine (Gln) based on ultra-high-performance liquid chromatography (UHPLC) coupled with tandem mass spectrometry (MS). First, accurate mass-to-charge (m/z) values of protonated isotopologues and elution time of standards were simultaneously analyzed to characterize ¹³C-labeled NEAAs by high-resolution Orbitrap MS in the parallel reaction monitoring (PRM) mode. Second, isotopologues and isotopomers of ¹³C-labeled NEAAs were investigated in HepG2 cells incubated with ¹³C₅-Gln at different time points. Ultimately, a total of 66 multiple reaction monitoring (MRM) transitions were performed by UHPLC coupled with triple quadrupole MS. Among them, 29 MRM transitions were monitored for pure metabolites (unambiguously identified). The other 37 MRM transitions were monitored for mixtures with exactly identical MRM transitions and retention time. The application of targeted profiling of ¹³C-labeled NEAAs in the dynamic ¹³C-labeling experiment indicated that the concentration-time profiles of NEAAs were different from each other. The concentrations of most ¹³C-labeled Gln, Glu, Pro, and Asp altered after ¹³C₅-Gln incubation, indicating that Gln plays a fundamental role in the biosynthesis of Glu, Pro, and Asp. The proposed PRM-MRM combination mode LC-MS approach is expected to provide valuable insights into analyses of isotope-labeled metabolites in isotope tracer experiments.

Adaptive laboratory evolution of the fast-growing cyanobacterium Synechococcus elongatus PCC 11801 for improved solvent tolerance

Cyanobacteria hold promise as cell factories for the photoautotrophic conversion of carbon dioxide to useful chemicals. For the eventual commercial viability of such processes, cyanobacteria need to be engineered for (i) efficient channeling of carbon flux toward the product of interest and (ii) improved product tolerance, the latter being the focus of this study. We chose the recently reported, fast-growing, high light and CO₂ tolerant cyanobacterium Synechococcus elongatus PCC 11801 for adaptive laboratory evolution. In two parallel experiments that lasted over 8400 h of culturing and 100 serial passages, S. elongatus PCC 11801 was evolved to tolerate 5 g/L n-butanol or 30 g/L 2,3-butanediol representing a 100% improvement in concentrations tolerated. The evolved strains retained alcohol tolerance even after being passaged several times without the alcohol stress suggesting that the changes were permanent. Whole genome sequencing of the n-butanol evolved strains revealed mutations in a number of stress responsive genes encoding translation initiation factors, RpoB and an ABC transporter. In 2,3-butanediol evolved strains, genes for ClpC, a different ABC transporter, glyceraldehyde-3-phosphate dehydrogenase and phosphoribulokinase were found to be mutated. Furthermore, the evolved strains showed significant improvement in tolerance toward several other alcohols. Notably, the n-butanol evolved strain could tolerate up to 32 g/L ethanol, thereby making it a promising host for photosynthetic production of biofuels via metabolic engineering.

Liquid Chromatography Methods for Separation of Polar and Charged Intracellular Metabolites for 13C Metabolic Flux Analysis

Accurate quantification of mass isotopolog distribution (MID) of intracellular metabolites is a key requirement for ¹³C metabolic flux analysis (¹³C-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, ¹³C-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 ¹³C metabolic flux analysis.

Dynamic Inventory of Intermediate Metabolites of Cyanobacteria in a Diurnal Cycle

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.

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We identify and quantify 67 polar intermediate metabolites in cyanobacteria via LC-MS

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A number of metabolites show large variations during the diurnal cycle

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Intermediates of the CBB cycle peak at midday, coinciding with peak in growth rate

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Gamma-glutamyl dipeptides identified as new storage compounds that peak at dawn

Use of information dependent acquisition mass spectra and sequential window acquisition of all theoretical fragment-ion mass spectra for fruit juices metabolomics and authentication

INTRODUCTION

LC-MS based untargeted metabolomics are the main untargeted methods used for juice metabolomics to solve the authentication problem faced in fruit juice industry.

OBJECTIVES

To evaluate the performances of different untargeted metabolomics methods on fruit juices metabolomics and authentication, orange and apple fruit juices were selected for this study.

METHODS

IDA-MS and SWATH-MS based on UHPLC-QTOF were used for the metabolomics and authenticity determination of apple and orange juices, including the lab-made samples of oranges (Citrus sinensis Osb.) from Jiangxi Province, apples (Malus domestica Borkh) from Shandong Province, and different brands of commercial orange and apple juice samples from markets.

RESULTS

IDA-MS and SWATH-MS could both acquire numerous MS1 features and MS2 information of juice components, while SWATH-MS excels at the acquisition rate of MS2. Distinctive separation between authentic orange juice and not authentic orange juice could be seen from principal component analysis and hierarchical clustering analysis based on both IDA-MS and SWATH-MS. After analysis of variance, fold change analysis and orthogonal projection to latent structures discriminant mode, 53 and 46 potential markers were defined by IDA-MS and SWATH-MS (with 77.4% and 100% MS2 acquisition rate) separately. Subsequently, these potential markers were putatively annotated using general chemical databases with 6 more annotated by SWATH-MS. Furthermore, 7 of the potential markers, l-asparagine, umbelliferone, glucosamine, phlorin, epicatechin, phytosphingosine and chlorogenic acid, were identified with standards. For the consideration of model simplicity, two determined makers (umbelliferone and chlorogenic acid) were selected to construct the DD-SIMCA model in commercial samples because of their good correlation with apple adulteration proportion, and the sensitivity and specificity of the model were 100% and 95%.

CONCLUSION

SWATH-MS excels at the MS2 acquisition of juice components and potential markers. This study provides an overall performance comparison between IDA-MS and SWATH-MS, and guidance for the method selection on fruit juice metabolomics and juice authenticity determination. Two of the potential markers determined, umbelliferone and chlorogenic acid, could be used as apple juice indicators in orange juice.

Systematic identification and elimination of flux bottlenecks in the aldehyde production pathway of Synechococcus elongatus PCC 7942

Isotopically nonstationary metabolic flux analysis (INST-MFA) provides a versatile platform to quantitatively assess in vivo metabolic activities of autotrophic systems. By applying INST-MFA to recombinant aldehyde-producing cyanobacteria, we identified metabolic alterations that correlated with increased strain performance in order to guide rational metabolic engineering. We identified four reactions adjacent to the pyruvate node that varied significantly with increasing aldehyde production: pyruvate kinase (PK) and acetolactate synthase (ALS) fluxes were directly correlated with product formation, while pyruvate dehydrogenase (PDH) and phosphoenolpyruvate carboxylase (PPC) fluxes were inversely correlated. Overexpression of enzymes for PK or ALS did not result in further improvements to the previous best-performing strain, while downregulation of PDH expression (through antisense RNA expression) or PPC flux (through expression of the reverse reaction, phosphoenolpyruvate carboxykinase) provided significant improvements. These results illustrate the potential of INST-MFA to enable a systematic approach for iterative identification and removal of pathway bottlenecks in autotrophic host cells.

Photosynthetic Co-Production of Succinate and Ethylene in A Fast-Growing Cyanobacterium, Synechococcus elongatus PCC 11801

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 P_cpcB, 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.

Evaluation of quenching methods for metabolite recovery in photoautotrophic Synechococcus sp. PCC 7002

The first step of many metabolomics studies is quenching, a technique vital for rapidly halting metabolism and ensuring that the metabolite profile remains unchanging during sample processing. The most widely used approach is to plunge the sample into prechilled cold methanol; however, this led to significant metabolite loss in Synecheococcus sp. PCC 7002. Here we describe our analysis of the impacts of cold methanol quenching on the model marine cyanobacterium Synechococcus sp. PCC 7002, as well as our brief investigation of alternative quenching methods. We tested several methods including cold methanol, cold saline, and two filtration approaches. Targeted central metabolites were extracted and metabolomic profiles were generated using liquid chromatography-tandem mass spectrometry (LC-MS/MS). The results indicate that cold methanol quenching induces dramatic metabolite leakage in Synechococcus, resulting in a majority of central metabolites being lost prior to extraction. Alternatively, usage of a chilled saline quenching solution mitigates metabolite leakage and improves sample recovery without sacrificing rapid quenching of cellular metabolism. Finally, we illustrate that metabolite leakage can be assessed, and subsequently accounted for, in order to determine absolute metabolite pool sizes; however, our results show that metabolite leakage is inconsistent across various metabolite pools and therefore must be determined for each individually measured metabolite.

Applications of Chromatography-Ultra High-Resolution MS for Stable Isotope-Resolved Metabolomics (SIRM) Reconstruction of Metabolic Networks

Metabolism is a complex network of compartmentalized and coupled chemical reactions, which often involve transfers of substructures of biomolecules, thus requiring metabolite substructures to be tracked. Stable isotope resolved metabolomics (SIRM) enables pathways reconstruction, even among chemically identical metabolites, by tracking the provenance of stable isotope-labeled substructures using NMR and ultrahigh resolution (UHR) MS. The latter can resolve and count isotopic labels in metabolites and can identify isotopic enrichment in substructures when operated in tandem MS mode. However, MS2 is difficult to implement with chromatography-based UHR-MS due to lengthy MS1 acquisition time that is required to obtain the molecular isotopologue count, which is further exacerbated by the numerous isotopologue source ions to fragment. We review here recent developments in tandem MS applications of SIRM to obtain more detailed information about isotopologue distributions in metabolites and their substructures.

A Novel Cyanobacterium Synechococcus elongatus PCC 11802 has Distinct Genomic and Metabolomic Characteristics Compared to its Neighbor PCC 11801

Cyanobacteria, a group of photosynthetic prokaryotes, are attractive hosts for biotechnological applications. It is envisaged that future biorefineries will deploy engineered cyanobacteria for the conversion of carbon dioxide to useful chemicals via light-driven, endergonic reactions. Fast-growing, genetically amenable, and stress-tolerant cyanobacteria are desirable as chassis for such applications. The recently reported strains such as Synechococcus elongatus UTEX 2973 and PCC 11801 hold promise, but additional strains may be needed for the ongoing efforts of metabolic engineering. Here, we report a novel, fast-growing, and naturally transformable cyanobacterium, S. elongatus PCC 11802, that shares 97% genome identity with its closest neighbor S. elongatus PCC 11801. The new isolate has a doubling time of 2.8 h at 1% CO2, 1000 µmole photons.m-2.s-1 and grows faster under high CO2 and temperature compared to PCC 11801 thus making it an attractive host for outdoor cultivations and eventual applications in the biorefinery. Furthermore, S. elongatus PCC 11802 shows higher levels of key intermediate metabolites suggesting that this strain might be better suited for achieving high metabolic flux in engineered pathways. Importantly, metabolite profiles suggest that the key enzymes of the Calvin cycle are not repressed under elevated CO2 in the new isolate, unlike its closest neighbor.

SWATH: A Data-Independent Tandem Mass Spectrometry Method to Quantify 13C Enrichment in Cellular Metabolites and Fragments

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 ¹³C 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.

Metabolic engineering of a fast-growing cyanobacterium Synechococcus elongatus PCC 11801 for photoautotrophic production of succinic acid

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.

Evaluation of freely available software tools for untargeted quantification of 13C isotopic enrichment in cellular metabolome from HR-LC/MS data

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.

Mass Isotopologue Distribution of dimer ion adducts of intracellular metabolites for potential applications in 13C Metabolic Flux Analysis

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.

High-throughput mass spectrometry scheme for screening and quantification of flavonoids in antioxidant nutraceuticals

Antioxidant nutraceuticals functional characteristic science is a challenging field for combining sensitivity and comprehensiveness. A untargeted screening and quantification method based on ultra-high performance liquid chromatography coupled to Quadrupole-Orbitrap high resolution mass spectrometry has been developed for determination of multiple classes of flavonoids in eight-three nutraceuticals samples. The data acquisition is based on a non-target approach of sequential full scan and variable data independent acquisition of twenty consecutive fragmentation events. The flavonoids include flavanols, flavones, flavanones, anthocyanidins, flavonols and isoflavones. A processing strategy is introduced to implementing filtering methods based on data feature extraction, common ion selection, shoulder peak removal, response threshold adjustment, mass shift and characteristic structural fragments evaluation. Confirmation is based on both accurate mass and isotopic assignment of standards, and further quantification is achieved by fragmentation. This scheme allows in depth characterization of flavonoids with the entire fragments.

Genome Features and Biochemical Characteristics of a Robust, Fast Growing and Naturally Transformable Cyanobacterium Synechococcus elongatus PCC 11801 Isolated from India

Cyanobacteria provide an interesting platform for biotechnological applications due to their efficient photoautotrophic growth, amenability to genetic engineering and the ability to grow on non-arable land. An ideal industrial strain of cyanobacteria would need to be fast growing and tolerant to high levels of temperature, light, carbon dioxide, salt and be naturally transformable. In this study, we report Synechococcus elongatus PCC 11801, a strain isolated from India that fulfills these requirements. The physiological and biochemical characteristics of PCC 11801 under carbon and light-limiting conditions were investigated. PCC 11801 shows a doubling time of 2.3 h, that is the fastest growth for any cyanobacteria reported so far under ambient CO₂ conditions. Genome sequence of PCC 11801 shows genome identity of ~83% with its closest neighbors Synechococcus elongatus PCC 7942 and Synechococcus elongatus UTEX 2973. The unique attributes of PCC 11801 genome are discussed in light of the physiological characteristics that are needed in an industrial strain. The genome of PCC 11801 shows several genes that do not have homologs in neighbor strains PCC 7942 and UTEX 2973, some of which may be responsible for adaptation to various abiotic stresses. The remarkably fast growth rate of PCC 11801 coupled with its robustness and ease of genetic transformation makes it an ideal candidate for the photosynthetic production of fuels and chemicals.

Automated Vision-Based Detection of Cracks on Concrete Surfaces Using a Deep Learning Technique

At present, a number of computer vision-based crack detection techniques have been developed to efficiently inspect and manage a large number of structures. However, these techniques have not replaced visual inspection, as they have been developed under near-ideal conditions and not in an on-site environment. This article proposes an automated detection technique for crack morphology on concrete surface under an on-site environment based on convolutional neural networks (CNNs). A well-known CNN, AlexNet is trained for crack detection with images scraped from the Internet. The training set is divided into five classes involving cracks, intact surfaces, two types of similar patterns of cracks, and plants. A comparative study evaluates the successfulness of the detailed surface categorization. A probability map is developed using a softmax layer value to add robustness to sliding window detection and a parametric study was carried out to determine its threshold. The applicability of the proposed method is evaluated on images taken from the field and real-time video frames taken using an unmanned aerial vehicle. The evaluation results confirm the high adoptability of the proposed method for crack inspection in an on-site environment.

An improved method for extraction of polar and charged metabolites from cyanobacteria

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.