Fluxome analysis using GC-MS

Ex Vivo 13C-Metabolic Flux Analysis of Porcine Circulating Immune Cells Reveals Cell Type-Specific Metabolic Patterns and Sex Differences in the Pentose Phosphate Pathway

In general, females present with stronger immune responses than males, but scarce data are available on sex-specific differences in immunometabolism. In this study, we characterized porcine peripheral blood mononuclear cell (PBMC) and granulocyte energy metabolism using a Bayesian 13C-metabolic flux analysis, which allowed precise determination of the glycolytic, pentose phosphate pathway (PPP), and tricarboxylic acid cycle (TCA) fluxes, together with an assessment of the superoxide anion radical (O2•-) production and mitochondrial O2 consumption. A principal component analysis allowed for identifying the cell type-specific patterns of metabolic plasticity. PBMCs displayed higher TCA cycle activity, especially glutamine-derived aspartate biosynthesis, which was directly related to mitochondrial respiratory activity and inversely related to O2•- production. In contrast, the granulocytes mainly utilized glucose via glycolysis, which was coupled to oxidative PPP utilization and O2•- production rates. The granulocytes of the males had higher oxidative PPP fluxes compared to the females, while the PBMCs of the females displayed higher non-oxidative PPP fluxes compared to the males associated with the T helper cell (CD3+CD4+) subpopulation of PBMCs. The observed sex-specific differences were not directly attributable to sex steroid plasma levels, but we detected an inverse correlation between testosterone and aldosterone plasma levels and showed that aldosterone levels were related with non-oxidative PPP fluxes of both cell types.

Multi-omics view of recombinant Yarrowia lipolytica: Enhanced ketogenic amino acid catabolism increases polyketide-synthase-driven docosahexaenoic production to high selectivity at the gram scale

DHA is a marine PUFA of commercial value, given its multiple health benefits. The worldwide emerging shortage in DHA supply has increased interest in microbial cell factories that can provide the compound de novo. In this regard, the present work aimed to improve DHA production in the oleaginous yeast strain Y. lipolytica Af4, which synthetized the PUFA via a heterologous myxobacterial polyketide synthase (PKS)-like gene cluster. As starting point, we used transcriptomics, metabolomics, and 13C-based metabolic pathway profiling to study the cellular dynamics of Y. lipolytica Af4. The shift from the growth to the stationary DHA-production phase was associated with fundamental changes in carbon core metabolism, including a strong upregulation of the PUFA gene cluster, as well as an increase in citrate and fatty acid degradation. At the same time, the intracellular levels of the two DHA precursors acetyl-CoA and malonyl-CoA dropped by up to 98% into the picomolar range. Interestingly, the degradation pathways for the ketogenic amino acids l-lysine, l-leucine, and l-isoleucine were transcriptionally activated, presumably to provide extra acetyl-CoA. Supplementation with small amounts of these amino acids at the beginning of the DHA production phase beneficially increased the intracellular CoA-ester pools and boosted the DHA titer by almost 40%. Isotopic 13C-tracer studies revealed that the supplements were efficiently directed toward intracellular CoA-esters and DHA. Hereby, l-lysine was found to be most efficient, as it enabled long-term activation, due to storage within the vacuole and continuous breakdown. The novel strategy enabled DHA production in Y. lipolytica at the gram scale for the first time. DHA was produced at a high selectivity (27% of total fatty acids) and free of the structurally similar PUFA DPA, which facilitates purification for high-value medical applications that require API-grade DHA. The assembled multi-omics picture of the central metabolism of Y. lipolytica provides valuable insights into this important yeast. Beyond our work, the enhanced catabolism of ketogenic amino acids seems promising for the overproduction of other compounds in Y. lipolytica, whose synthesis is limited by the availability of CoA ester precursors.

The Y-ome Conundrum: Insights into Uncharacterized Genes and Approaches for Functional Annotation

The ever-increasing availability of genome sequencing data has revealed a substantial number of uncharacterized genes without known functions across various organisms. The first comprehensive genome sequencing of E. coli K12 revealed that more than 50% of its open reading frames corresponded to transcripts with no known functions. The group of protein-coding genes without a functional description and/or a recognized pathway, beginning with the letter "Y", is classified as the "y-ome". Several efforts have been made to elucidate the functions of these genes and to recognize their role in biological processes. This review provides a brief update on various strategies employed when studying the y-ome, such as high-throughput experimental approaches, comparative omics, metabolic engineering, gene expression analysis, and data integration techniques. Additionally, we highlight recent advancements in functional annotation methods, including the use of machine learning, network analysis, and functional genomics approaches. Novel approaches are required to produce more precise functional annotations across the genome to reduce the number of genes with unknown functions.

A combined pig model to determine the net absorption of volatile fatty acids in the large intestine under different levels of crude fiber

BACKGROUND

This study aimed to develop a combined model to quantify the net absorption of volatile fatty acids (VFA) in the large intestine (LI) of pigs.

METHODS

Fifteen female growing pigs (Duroc × Large White × Landrace) were ranked by body weight (30 ± 2.1 kg) on day 0 and assigned to one of three treatments, namely the basal diet containing different crude fiber (CF) levels (LCF: 3.0% CF, MCF: 4.5% CF, and HCF: 6.0% CF). The pigs were implanted with the terminal ileum fistula and the cannulation of the ileal mesenteric vein (IMV), portal vein (PV), and left femoral artery (LFA) from days 6 to 7. [13 C]-Labeled VFA and P-aminohippuric acid were constantly perfused into the terminal ileum fistula and the cannulation of the IMV (day 15), respectively. Blood samples were collected from the PV and the LFA during perfusion (5 h), and LI samples were collected.

RESULTS

The net flux of [12 C]-acetic acid in the PV was greater for LCF versus MCF (p = 0.045), but no difference was observed in the net flux of [12 C]-propionic acid (p = 0.505) and [12 C]-butyric acid (p = 0.35) in the PV among treatments. The deposition of [12 C]-acetic acid in the LI was greater for LCF versus MCF (p = 0.014), whereas the deposition of [12 C]-propionic acid (p = 0.007) and [12 C]-butyric acid (p = 0.037) in the LI was greater for LCF versus HCF.

CONCLUSIONS

In conclusion, this pig model was found conducive to study the net absorption of VFAs in the LI, and LCF had more net absorption of VFAs in the LI than MCF and HCF.

Systems-Wide Dissection of Organic Acid Assimilation in Pseudomonas aeruginosa Reveals a Novel Path To Underground Metabolism

The human pathogen Pseudomonas aeruginosa (Pa) is one of the most frequent and severe causes of nosocomial infection. This organism is also a major cause of airway infections in people with cystic fibrosis (CF). Pa is known to have a remarkable metabolic plasticity, allowing it to thrive under diverse environmental conditions and ecological niches; yet, little is known about the central metabolic pathways that sustain its growth during infection or precisely how these pathways operate. In this work, we used a combination of 'omics approaches (transcriptomics, proteomics, metabolomics, and ¹³C-fluxomics) and reverse genetics to provide systems-level insight into how the infection-relevant organic acids succinate and propionate are metabolized by Pa. Moreover, through structural and kinetic analysis of the 2-methylcitrate synthase (2-MCS; PrpC) and its paralogue citrate (CIT) synthase (GltA), we show how these two crucial enzymatic steps are interconnected in Pa organic acid assimilation. We found that Pa can rapidly adapt to the loss of GltA function by acquiring mutations in a transcriptional repressor, which then derepresses prpC expression. Our findings provide a clear example of how "underground metabolism," facilitated by enzyme substrate promiscuity, "rewires" Pa metabolism, allowing it to overcome the loss of a crucial enzyme. This pathogen-specific knowledge is critical for the advancement of a model-driven framework to target bacterial central metabolism. IMPORTANCE Pseudomonas aeruginosa is an opportunistic human pathogen that, due to its unrivalled resistance to antibiotics, ubiquity in the built environment, and aggressiveness in infection scenarios, has acquired the somewhat dubious accolade of being designated a "critical priority pathogen" by the WHO. In this work, we uncover the pathways and mechanisms used by P. aeruginosa to grow on a substrate that is abundant at many infection sites: propionate. We found that if the organism is prevented from metabolizing propionate, the substrate turns from being a convenient nutrient source into a potent poison, preventing bacterial growth. We further show that one of the enzymes involved in these reactions, 2-methylcitrate synthase (PrpC), is promiscuous and can moonlight for another essential enzyme in the cell (citrate synthase). Indeed, mutations that abolish citrate synthase activity (which would normally prevent the cell from growing) can be readily overcome if the cell acquires additional mutations that increase the expression of PrpC. This is a nice example of the evolutionary utility of so-called "underground metabolism."

Follicular Fluid: A Powerful Tool for the Understanding and Diagnosis of Polycystic Ovary Syndrome

Polycystic ovary syndrome (PCOS) represents one of the leading causes of anovulatory infertility and affects 5% to 20% of women worldwide. Until today, both the subsequent etiology and pathophysiology of PCOS remain unclear, and patients with PCOS that undergo assisted reproductive techniques (ART) might present a poor to exaggerated response, low oocyte quality, ovarian hyperstimulation syndrome, as well as changes in the follicular fluid metabolites pattern. These abnormalities originate a decrease of Metaphase II (MII) oocytes and decreased rates for fertilization, cleavage, implantation, blastocyst conversion, poor egg to follicle ratio, and increased miscarriages. Focus on obtaining high-quality embryos has been taken into more consideration over the years. Nowadays, the use of metabolomic analysis in the quantification of proteins and peptides in biological matrices might predict, with more accuracy, the success in assisted reproductive technology. In this article, we review the use of human follicular fluid as the matrix in metabolomic analysis for diagnostic and ART predictor of success for PCOS patients.

GC/MS-based 13C metabolic flux analysis resolves the parallel and cyclic photomixotrophic metabolism of Synechocystis sp. PCC 6803 and selected deletion mutants including the Entner-Doudoroff and phosphoketolase pathways

BACKGROUND

Cyanobacteria receive huge interest as green catalysts. While exploiting energy from sunlight, they co-utilize sugar and CO₂. This photomixotrophic mode enables fast growth and high cell densities, opening perspectives for sustainable biomanufacturing. The model cyanobacterium Synechocystis sp. PCC 6803 possesses a complex architecture of glycolytic routes for glucose breakdown that are intertwined with the CO₂-fixing Calvin-Benson-Bassham (CBB) cycle. To date, the contribution of these pathways to photomixotrophic metabolism has remained unclear.

RESULTS

Here, we developed a comprehensive approach for ¹³C metabolic flux analysis of Synechocystis sp. PCC 6803 during steady state photomixotrophic growth. Under these conditions, the Entner-Doudoroff (ED) and phosphoketolase (PK) pathways were found inactive but the microbe used the phosphoglucoisomerase (PGI) (63.1%) and the oxidative pentose phosphate pathway (OPP) shunts (9.3%) to fuel the CBB cycle. Mutants that lacked the ED pathway, the PK pathway, or phosphofructokinases were not affected in growth under metabolic steady-state. An ED pathway-deficient mutant (Δeda) exhibited an enhanced CBB cycle flux and increased glycogen formation, while the OPP shunt was almost inactive (1.3%). Under fluctuating light, ∆eda showed a growth defect, different to wild type and the other deletion strains.

CONCLUSIONS

The developed approach, based on parallel ¹³C tracer studies with GC-MS analysis of amino acids, sugars, and sugar derivatives, optionally adding NMR data from amino acids, is valuable to study fluxes in photomixotrophic microbes to detail. In photomixotrophic cells, PGI and OPP form glycolytic shunts that merge at switch points and result in synergistic fueling of the CBB cycle for maximized CO₂ fixation. However, redirected fluxes in an ED shunt-deficient mutant and the impossibility to delete this shunt in a GAPDH2 knockout mutant, indicate that either minor fluxes (below the resolution limit of ¹³C flux analysis) might exist that could provide catalytic amounts of regulatory intermediates or alternatively, that EDA possesses additional so far unknown functions. These ideas require further experiments.

Co-cultures of Propionibacterium freudenreichii and Bacillus amyloliquefaciens cooperatively upgrade sunflower seed milk to high levels of vitamin B12 and multiple co-benefits

Background

Sunflower seeds (Helianthus annuus) display an attractive source for the rapidly increasing market of plant-based human nutrition. Of particular interest are press cakes of the seeds, cheap residuals from sunflower oil manufacturing that offer attractive sustainability and economic benefits. Admittedly, sunflower seed milk, derived therefrom, suffers from limited nutritional value, undesired flavor, and the presence of indigestible sugars. Of specific relevance is the absence of vitamin B₁₂. This vitamin is required for development and function of the central nervous system, healthy red blood cell formation, and DNA synthesis, and displays the most important micronutrient for vegans to be aware of. Here we evaluated the power of microbes to enrich sunflower seed milk nutritionally as well as in flavor.

Results

Propionibacterium freudenreichii NCC 1177 showed highest vitamin B₁₂ production in sunflower seed milk out of a range of food-grade propionibacteria. Its growth and B₁₂ production capacity, however, were limited by a lack of accessible carbon sources and stimulants of B₁₂ biosynthesis in the plant milk. This was overcome by co-cultivation with Bacillus amyloliquefaciens NCC 156, which supplied lactate, amino acids, and vitamin B₇ for growth of NCC 1177 plus vitamins B₂ and B₃, potentially supporting vitamin B₁₂ production by the Propionibacterium. After several rounds of optimization, co-fermentation of ultra-high-temperature pre-treated sunflower seed milk by the two microbes, enabled the production of 17 µg (100 g)⁻¹ vitamin B₁₂ within four days without any further supplementation. The fermented milk further revealed significantly enriched levels of l-lysine, the most limiting essential amino acid, vitamin B₃, vitamin B₆, improved protein quality and flavor, and largely eliminated indigestible sugars.

Conclusion

The fermented sunflower seed milk, obtained by using two food-grade microbes without further supplementation, displays an attractive, clean-label product with a high level of vitamin B₁₂ and multiple co-benefits. The secret of the successfully upgraded plant milk lies in the multifunctional cooperation of the two microbes, which were combined, based on their genetic potential and metabolic signatures found in mono-culture fermentations. This design by knowledge approach appears valuable for future development of plant-based milk products.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12934-022-01773-w.

mfapy: An open-source Python package for 13C-based metabolic flux analysis

¹³C-based metabolic flux analysis (¹³C-MFA) is an essential tool for estimating intracellular metabolic flux levels in metabolic engineering and biology. In ¹³C-MFA, a metabolic flux distribution that explains the observed isotope labeling data was computationally estimated using a non-linear optimization method. Herein, we report the development of mfapy, an open-source Python package developed for more flexibility and extensibility for ¹³C-MFA. mfapy compels users to write a customized Python code by describing each step in the data analysis procedures of the isotope labeling experiments. The flexibility and extensibility provided by mfapy can support trial-and-error performance in the routine estimation of metabolic flux distributions, experimental design by computer simulations of ¹³C-MFA experiments, and development of new data analysis techniques for stable isotope labeling experiments. mfapy is available to the public from the Github repository (https://github.com/fumiomatsuda/mfapy).

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An open-source Python package, mfapy, is developed for ¹³C-MFA.

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mfapy enables users to write Python codes for data analysis procedures of ¹³C-MFA.

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mfapy has a flexibility and extensibility to support various data analysis procedures.

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Computer simulations of ¹³C-MFA experiments is supported for experimental design.

Cascaded valorization of brown seaweed to produce l-lysine and value-added products using Corynebacterium glutamicum streamlined by systems metabolic engineering

Seaweeds emerge as promising third-generation renewable for sustainable bioproduction. In the present work, we valorized brown seaweed to produce l-lysine, the world's leading feed amino acid, using Corynebacterium glutamicum, which was streamlined by systems metabolic engineering. The mutant C. glutamicum SEA-1 served as a starting point for development because it produced small amounts of l-lysine from mannitol, a major seaweed sugar, because of the deletion of its arabitol repressor AtlR and its engineered l-lysine pathway. Starting from SEA-1, we systematically optimized the microbe to redirect excess NADH, formed on the sugar alcohol, towards NADPH, required for l-lysine synthesis. The mannitol dehydrogenase variant MtlD D75A, inspired by 3D protein homology modelling, partly generated NADPH during the oxidation of mannitol to fructose, leading to a 70% increased l-lysine yield in strain SEA-2C. Several rounds of strain engineering further increased NADPH supply and l-lysine production. The best strain, SEA-7, overexpressed the membrane-bound transhydrogenase pntAB together with codon-optimized gapN, encoding NADPH-dependent glyceraldehyde 3-phosphate dehydrogenase, and mak, encoding fructokinase. In a fed-batch process, SEA-7 produced 76 g L^-1l-lysine from mannitol at a yield of 0.26 mol mol^-1 and a maximum productivity of 2.1 g L^-1 h^-1. Finally, SEA-7 was integrated into seaweed valorization cascades. Aqua-cultured Laminaria digitata, a major seaweed for commercial alginate, was extracted and hydrolyzed enzymatically, followed by recovery and clean-up of pure alginate gum. The residual sugar-based mixture was converted to l-lysine at a yield of 0.27 C-mol C-mol^-1 using SEA-7. Second, stems of the wild-harvested seaweed Durvillaea antarctica, obtained as waste during commercial processing of the blades for human consumption, were extracted using acid treatment. Fermentation of the hydrolysate using SEA-7 provided l-lysine at a yield of 0.40 C-mol C-mol^-1. Our findings enable improvement of the efficiency of seaweed biorefineries using tailor-made C. glutamicum strains.

IsoSolve: An Integrative Framework to Improve Isotopic Coverage and Consolidate Isotopic Measurements by Mass Spectrometry and/or Nuclear Magnetic Resonance

Stable-isotope labeling experiments are widely used to investigate the topology and functioning of metabolic networks. Label incorporation into metabolites can be quantified using a broad range of mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy methods, but in general, no single approach can completely cover isotopic space, even for small metabolites. The number of quantifiable isotopic species could be increased and the coverage of isotopic space improved by integrating measurements obtained by different methods; however, this approach has remained largely unexplored because no framework able to deal with partial, heterogeneous isotopic measurements has yet been developed. Here, we present a generic computational framework based on symbolic calculus that can integrate any isotopic data set by connecting measurements to the chemical structure of the molecules. As a test case, we apply this framework to isotopic analyses of amino acids, which are ubiquitous to life, central to many biological questions, and can be analyzed by a broad range of MS and NMR methods. We demonstrate how this integrative framework helps to (i) clarify and improve the coverage of isotopic space, (ii) evaluate the complementarity and redundancy of different techniques, (iii) consolidate isotopic data sets, (iv) design experiments, and (v) guide future analytical developments. This framework, which can be applied to any labeled element, isotopic tracer, metabolite, and analytical platform, has been implemented in IsoSolve (available at https://github.com/MetaSys-LISBP/IsoSolve and https://pypi.org/project/IsoSolve), an open-source software that can be readily integrated into data analysis pipelines.

Genome-based selection and application of food-grade microbes for chickpea milk fermentation towards increased L-lysine content, elimination of indigestible sugars, and improved flavour

Background

Plant-based milk alternatives are more popular than ever, and chickpea-based milks are among the most commercially relevant products. Unfortunately, limited nutritional value because of low levels of the essential amino acid l-lysine, low digestibility and unpleasant taste are challenges that must be addressed to improve product quality and meet consumer expectations.

Results

Using in-silico screening and food safety classifications, 31 strains were selected as potential l-lysine producers from approximately 2,500 potential candidates. Beneficially, 30% of the isolates significantly accumulated amino acids (up to 1.4 mM) during chickpea milk fermentation, increasing the natural level by up to 43%. The best-performing strains, B. amyloliquefaciens NCC 156 and L. paracasei subsp. paracasei NCC 2511, were tested further. De novo lysine biosynthesis was demonstrated in both strains by ¹³C metabolic pathway analysis. Spiking small amounts of citrate into the fermentation significantly activated l-lysine biosynthesis in NCC 156 and stimulated growth. Both microbes revealed additional benefits in eliminating indigestible sugars such as stachyose and raffinose and converting off-flavour aldehydes into the corresponding alcohols and acids with fruity and sweet notes.

Conclusions

B. amyloliquefaciens NCC 156 and L. paracasei subsp. paracasei NCC 2511 emerged as multi-benefit microbes for chickpea milk fermentation with strong potential for industrial processing of the plant material. Given the high number of l-lysine-producing isolates identified in silico, this concept appears promising to support strain selection for food fermentation.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12934-021-01595-2.

Convergent evolution of zoonotic Brucella species toward the selective use of the pentose phosphate pathway

Mechanistic understanding of the factors that govern host tropism remains incompletely understood for most pathogens. Brucella species, which are capable of infecting a wide range of hosts, offer a useful avenue to address this question. We hypothesized that metabolic fine-tuning to intrahost niches is likely an underappreciated axis underlying pathogens' ability to infect new hosts and tropism. In this work, we compared the central metabolism of seven Brucella species by stable isotopic labeling and genetics. We identified two functionally distinct groups, one overlapping with the classical zoonotic species of domestic livestock that exclusively use the pentose phosphate pathway (PPP) for hexose catabolism, whereas species from the second group use mostly the Entner-Doudoroff pathway (EDP). We demonstrated that the metabolic dichotomy among Brucellae emerged after the acquisition of two independent EDP-inactivating mutations in all classical zoonotic species. We then examined the pathogenicity of key metabolic mutants in mice and confirmed that this trait is tied to virulence. Altogether, our data are consistent with the hypothesis that the PPP has been incrementally selected over the EDP in parallel to Brucella adaptation to domestic livestock.

Validity of natural isotope abundance correction for metabolic flux analysis

A pervasive issue in stable isotope tracing and metabolic flux analysis is the presence of naturally occurring isotopes such as ¹³C. For mass isotopomer distributions (MIDs) measured by mass spectrometry, it is common practice to correct for natural occurrence of isotopes within metabolites of interest using a linear transform based on binomial distributions. The resulting corrected MIDs are often used to fit metabolic network models and infer metabolic fluxes, which implicitly assumes that corrected MIDs will yield the same flux solution as the actual observed MIDs. Although this assumption can be empirically verified in special cases by simulation studies, there seems to be no published proof of this important property for the general case. In this paper, we prove that this property holds for the case of noise-free MID data obtained at steady state. On the other hand, for noisy MID data, the flux solution will generally differ between the two representations. These results provide a theoretical foundation for the common practice of MID correction in metabolic flux analysis.

A common approach for absolute quantification of short chain CoA thioesters in prokaryotic and eukaryotic microbes

BACKGROUND

Thioesters of coenzyme A participate in 5% of all enzymatic reactions. In microbial cell factories, they function as building blocks for products of recognized commercial value, including natural products such as polyketides, polyunsaturated fatty acids, biofuels, and biopolymers. A core spectrum of approximately 5-10 short chain thioesters is present in many microbes, as inferred from their genomic repertoire. The relevance of these metabolites explains the high interest to trace and quantify them in microbial cells.

RESULTS

Here, we describe a common workflow for extraction and absolute quantification of short chain CoA thioesters in different gram-positive and gram-negative bacteria and eukaryotic yeast, i.e. Corynebacterium glutamicum, Streptomyces albus, Pseudomonas putida, and Yarrowia lipolytica. The approach assessed intracellular CoA thioesters down to the picomolar level and exhibited high precision and reproducibility for all microbes, as shown by principal component analysis. Furthermore, it provided interesting insights into microbial CoA metabolism. A succinyl-CoA synthase defective mutant of C. glutamicum exhibited an unaffected level of succinyl-CoA that indicated a complete compensation by the L-lysine pathway to bypass the disrupted TCA cycle. Methylmalonyl-CoA, an important building block of high-value polyketides, was identified as dominant CoA thioester in the actinomycete S. albus. The microbe revealed a more than 10,000-fold difference in the abundance of intracellular CoA thioesters. A recombinant strain of S. albus, which produced different derivatives of the antituberculosis polyketide pamamycin, revealed a significant depletion of CoA thioesters of the ethylmalonyl CoA pathway, influencing product level and spectrum.

CONCLUSIONS

The high relevance of short chain CoA thioesters to synthetize industrial products and the interesting insights gained from the examples shown in this work, suggest analyzing these metabolites in microbial cell factories more routinely than done so far. Due to its broad application range, the developed approach appears useful to be applied this purpose. Hereby, the possibility to use one single protocol promises to facilitate automatized efforts, which rely on standardized workflows.

ScalaFlux: A scalable approach to quantify fluxes in metabolic subnetworks

13C-metabolic flux analysis (13C-MFA) allows metabolic fluxes to be quantified in living organisms and is a major tool in biotechnology and systems biology. Current 13C-MFA approaches model label propagation starting from the extracellular 13C-labeled nutrient(s), which limits their applicability to the analysis of pathways close to this metabolic entry point. Here, we propose a new approach to quantify fluxes through any metabolic subnetwork of interest by modeling label propagation directly from the metabolic precursor(s) of this subnetwork. The flux calculations are thus purely based on information from within the subnetwork of interest, and no additional knowledge about the surrounding network (such as atom transitions in upstream reactions or the labeling of the extracellular nutrient) is required. This approach, termed ScalaFlux for SCALAble metabolic FLUX analysis, can be scaled up from individual reactions to pathways to sets of pathways. ScalaFlux has several benefits compared with current 13C-MFA approaches: greater network coverage, lower data requirements, independence from cell physiology, robustness to gaps in data and network information, better computational efficiency, applicability to rich media, and enhanced flux identifiability. We validated ScalaFlux using a theoretical network and simulated data. We also used the approach to quantify fluxes through the prenyl pyrophosphate pathway of Saccharomyces cerevisiae mutants engineered to produce phytoene, using a dataset for which fluxes could not be calculated using existing approaches. A broad range of metabolic systems can be targeted with minimal cost and effort, making ScalaFlux a valuable tool for the analysis of metabolic fluxes.

Contextual Flexibility in Pseudomonas aeruginosa Central Carbon Metabolism during Growth in Single Carbon Sources

Pseudomonas aeruginosa is an opportunistic human pathogen that is well known for causing infections in the airways of people with cystic fibrosis. Although it is clear that P. aeruginosa is metabolically well adapted to life in the CF lung, little is currently known about how the organism metabolizes the nutrients available in the airways. In this work, we used a combination of gene expression and isotope tracer (“fluxomic”) analyses to find out exactly where the input carbon goes during growth on two CF-relevant carbon sources, acetate and glycerol (derived from the breakdown of lung surfactant). We found that carbon is routed (“fluxed”) through very different pathways during growth on these substrates and that this is accompanied by an unexpected remodeling of the cell’s electron transfer pathways. Having access to this “blueprint” is important because the metabolism of P. aeruginosa is increasingly being recognized as a target for the development of much-needed antimicrobial agents.

Pseudomonas aeruginosa is an opportunistic human pathogen, particularly noted for causing infections in the lungs of people with cystic fibrosis (CF). Previous studies have shown that the gene expression profile of P. aeruginosa appears to converge toward a common metabolic program as the organism adapts to the CF airway environment. However, we still have only a limited understanding of how these transcriptional changes impact metabolic flux at the systems level. To address this, we analyzed the transcriptome, proteome, and fluxome of P. aeruginosa grown on glycerol or acetate. These carbon sources were chosen because they are the primary breakdown products of an airway surfactant, phosphatidylcholine, which is known to be a major carbon source for P. aeruginosa in CF airways. We show that the fluxes of carbon throughout central metabolism are radically different among carbon sources. For example, the newly recognized “EDEMP cycle” (which incorporates elements of the Entner-Doudoroff [ED] pathway, the Embden-Meyerhof-Parnas [EMP] pathway, and the pentose phosphate [PP] pathway) plays an important role in supplying NADPH during growth on glycerol. In contrast, the EDEMP cycle is attenuated during growth on acetate, and instead, NADPH is primarily supplied by the reaction catalyzed by isocitrate dehydrogenase(s). Perhaps more importantly, our proteomic and transcriptomic analyses revealed a global remodeling of gene expression during growth on the different carbon sources, with unanticipated impacts on aerobic denitrification, electron transport chain architecture, and the redox economy of the cell. Collectively, these data highlight the remarkable metabolic plasticity of P. aeruginosa; that plasticity allows the organism to seamlessly segue between different carbon sources, maximizing the energetic yield from each.

Integration of flux measurements and pharmacological controls to optimize stable isotope-resolved metabolomics workflows and interpretation

Stable isotope-resolved metabolomics (SIRM) provides information regarding the relative activity of numerous metabolic pathways and the contribution of nutrients to specific metabolite pools; however, SIRM experiments can be difficult to execute, and data interpretation is challenging. Furthermore, standardization of analytical procedures and workflows remain significant obstacles for widespread reproducibility. Here, we demonstrate the workflow of a typical SIRM experiment and suggest experimental controls and measures of cross-validation that improve data interpretation. Inhibitors of glycolysis and oxidative phosphorylation as well as mitochondrial uncouplers serve as pharmacological controls, which help define metabolic flux configurations that occur under well-controlled metabolic states. We demonstrate how such controls and time course labeling experiments improve confidence in metabolite assignments as well as delineate metabolic pathway relationships. Moreover, we demonstrate how radiolabeled tracers and extracellular flux analyses integrate with SIRM to improve data interpretation. Collectively, these results show how integration of flux methodologies and use of pharmacological controls increase confidence in SIRM data and provide new biological insights.

Advances in Chemical and Biological Methods to Identify Microorganisms-From Past to Present

Fast detection and identification of microorganisms is a challenging and significant feature from industry to medicine. Standard approaches are known to be very time-consuming and labor-intensive (e.g., culture media and biochemical tests). Conversely, screening techniques demand a quick and low-cost grouping of bacterial/fungal isolates and current analysis call for broad reports of microorganisms, involving the application of molecular techniques (e.g., 16S ribosomal RNA gene sequencing based on polymerase chain reaction). The goal of this review is to present the past and the present methods of detection and identification of microorganisms, and to discuss their advantages and their limitations.

13C-Metabolic Flux Analysis Reveals Effect of Phenol on Central Carbon Metabolism in Escherichia coli

Phenol is an important chemical product that can be used in a wide variety of applications, and it is currently produced from fossil resources. Fermentation production of phenol from renewable biomass resources by microorganisms is highly desirable for sustainable development. However, phenol toxicity hampers phenol production in industrial microorganisms such as Escherichia coli. In the present study, it was revealed that culturing E. coli in the presence of phenol not only decreased growth rate, but also biomass yield. This suggests that phenol affects the carbon flow of the metabolism, but the mechanism is unknown. To investigate the effect of phenol on the flux distribution of central carbon metabolism, ¹³C-metabolic flux analysis (¹³C-MFA) was performed on cells grown under different phenol concentrations (0, 0.1, and 0.15%). ¹³C-MFA revealed that the TCA cycle flux reduced by 25% increased acetate production from acetyl-CoA by 30% in the presence of 0.1% phenol. This trend of flux changes was emphasized at a phenol concentration of 0.15%. Although the expression level of citrate synthase, which catalyzes the first reaction of the TCA cycle, does not change regardless of phenol concentrations, the in vitro enzyme activity assay shows that the reaction was inhibited by phenol. These results suggest that the TCA cycle flux decreased due to phenol inhibition of citrate synthase; therefore, ATP could not be sufficiently produced by respiration, and growth rate decreased. Furthermore, since carbon was lost as acetate due to overflow metabolism, the biomass yield became low in the presence of phenol.

Mapping Salmonella typhimurium pathways using 13C metabolic flux analysis

In the last years, Salmonella has been extensively studied not only due to its importance as a pathogen, but also as a host to produce pharmaceutical compounds. However, the full exploitation of Salmonella as a platform for bioproduct delivery has been hampered by the lack of information about its metabolism. Genome-scale metabolic models can be valuable tools to delineate metabolic engineering strategies as long as they closely represent the actual metabolism of the target organism. In the present study, a ¹³C-MFA approach was applied to map the fluxes at the central carbon pathways of S. typhimurium LT2 growing at glucose-limited chemostat cultures. The experiments were carried out in a 2L bioreactor, using defined medium enriched with 20% ¹³C-labeled glucose. Metabolic flux distributions in central carbon pathways of S. typhimurium LT2 were estimated using OpenFLUX2 based on the labeling pattern of biomass protein hydrolysates together with biomass composition. The results suggested that pentose phosphate is used to catabolize glucose, with minor fluxes through glycolysis. In silico simulations, using Optflux and pFBA as simulation method, allowed to study the performance of the genome-scale metabolic model. In general, the accuracy of in silico simulations was improved by the superimposition of estimated intracellular fluxes to the existing genome-scale metabolic model, showing a better fitting to the experimental extracellular fluxes, whereas the intracellular fluxes of pentose phosphate and anaplerotic reactions were poorly described.

Transcriptomic and fluxomic changes in Streptomyces lividans producing heterologous protein

BACKGROUND

The Gram-positive Streptomyces lividans TK24 is an attractive host for heterologous protein production because of its high capability to secrete proteins-which favors correct folding and facilitates downstream processing-as well as its acceptance of methylated DNA and its low endogeneous protease activity. However, current inconsistencies in protein yields urge for a deeper understanding of the burden of heterologous protein production on the cell. In the current study, transcriptomics and [Formula: see text]-based fluxomics were exploited to uncover gene expression and metabolic flux changes associated with heterologous protein production. The Rhodothermus marinus thermostable cellulase A (CelA)-previously shown to be successfully overexpressed in S. lividans-was taken as an example protein.

RESULTS

RNA-seq and [Formula: see text]-based metabolic flux analysis were performed on a CelA-producing and an empty-plasmid strain under the same conditions. Differential gene expression, followed by cluster analysis based on co-expression and co-localization, identified transcriptomic responses related to secretion-induced stress and DNA damage. Furthermore, the OsdR regulon (previously associated with hypoxia, oxidative stress, intercellular signaling, and morphological development) was consistently upregulated in the CelA-producing strain and exhibited co-expression with isoenzymes from the pentose phosphate pathway linked to secondary metabolism. Increased expression of these isoenzymes matches to increased fluxes in the pentose phosphate pathway. Additionally, flux maps of the central carbon metabolism show increased flux through the tricarboxylic acid cycle in the CelA-producing strain. Redirection of fluxes in the CelA-producing strain leads to higher production of NADPH, which can only partly be attributed to increased secretion.

CONCLUSIONS

Transcriptomic and fluxomic changes uncover potential new leads for targeted strain improvement strategies which may ease the secretion stress and metabolic burden associated with heterologous protein synthesis and secretion, and may help create a more consistently performing S. lividans strain. Yet, links to secondary metabolism and redox balancing should be further investigated to fully understand the S. lividans metabolome under heterologous protein production.

Metabolic flux analysis in Ashbya gossypii using 13C-labeled yeast extract: industrial riboflavin production under complex nutrient conditions

Background

The fungus Ashbya gossypii is an important industrial producer of the vitamin riboflavin. Using this microbe, riboflavin is manufactured in a two-stage process based on a rich medium with vegetable oil, yeast extract and different precursors: an initial growth and a subsequent riboflavin production phase. So far, our knowledge on the intracellular metabolic fluxes of the fungus in this complex process is limited, but appears highly relevant to better understand and rationally engineer the underlying metabolism. To quantify intracellular fluxes of growing and riboflavin producing A. gossypii, studies with different ¹³C tracers were embedded into a framework of experimental design, isotopic labeling analysis by MS and NMR techniques, and model-based data processing. The studies included the use ¹³C of yeast extract, a key component used in the process.

Results

During growth, the TCA cycle was found highly active, whereas the cells exhibited a low flux through gluconeogenesis as well as pentose phosphate pathway. Yeast extract was the main carbon donor for anabolism,  while vegetable oil selectively contributed to the proteinogenic amino acids glutamate, aspartate, and alanine. During the subsequent riboflavin biosynthetic phase, the carbon flux through the TCA cycle remained high. Regarding riboflavin formation, most of the vitamin’s carbon originated from rapeseed oil (81 ± 1%), however extracellular glycine and yeast extract also contributed with 9 ± 0% and 8 ± 0%, respectively. In addition, advanced yeast extract-based building blocks such as guanine and GTP were directly incorporated into the vitamin.

Conclusion

Intracellular carbon fluxes for growth and riboflavin production on vegetable oil provide the first flux insight into a  fungus on complex industrial medium. The knowledge gained therefrom is valuable for further strain and process improvement. Yeast extract, while being the main carbon source during growth, contributes valuable building blocks to the synthesis of vitamin B₂. This highlights the importance of careful selection of the right yeast extract for a process based on its unique composition.

Electronic supplementary material

The online version of this article (10.1186/s12934-018-1003-y) contains supplementary material, which is available to authorized users.

Thiazolidine Peracetates: Carbohydrate Derivatives that Readily Assign cis-, trans-2,3-Monosaccharides by Gas Chromatography-Mass Spectrometry Analysis

A novel group of carbohydrate derivatives is described that uniquely assign cis/ trans-2,3-aldose stereoisomers at low nanomolar concentrations. Aldopentoses, aldohexoses, or component aldoses from hydrolysis of polysaccharides or oligosaccharides react with cysteamine in pyridine to give quantitative formation of thiazolidines, which are subsequently peracetylated in a one-pot reaction. The nonpolar thiazolidines peracetate (TPA) derivatives are analyzed by gas chromatography and electron impact mass spectrometry (GC/EI-MS), each aldose giving rise to two TPA geometric isomers. The quantitative ratio of these diastereomers is dependent upon whether the parent monosaccharide is cis-2,3-(Rib, Lyx, Man, All, Gul, and Tal), or trans-2,3-aldose (Xyl, Ara, Glc, Gal, Ido, and Alt). TPAs generate observed EI-MS fragment ions characteristic of C1-C2 and C3-C4 bond cleavage of the parent sugars. This has been used to estimate the extent of metabolic labeling of microbial cell-wall carbohydrates, especially into the defining anomeric carbons and during aldolase / ketolase -catalyzed rearrangements.

Mass Spectrometry-Based Method to Study Inhibitor-Induced Metabolic Redirection in the Central Metabolism of Cancer Cells

Cancer cells often respond to chemotherapeutic inhibitors by redirecting carbon flow in the central metabolism. To understand the metabolic redirections of inhibitor treatment on cancer cells, this study established a 13C-metabolic flux analysis (13C-MFA)-based method to evaluate metabolic redirection in MCF-7 breast cancer cells using mass spectrometry. A metabolic stationary state necessary for accurate 13C-MFA was confirmed during an 8-24 h window using low-dose treatments of various metabolic inhibitors. Further 13C-labeling experiments using [1-13C]glucose and [U-13C]glutamine, combined with gas chromatography-mass spectrometry (GC-MS) analysis of mass isotopomer distributions (MIDs), confirmed that an isotopic stationary state of intracellular metabolites was reached 24 h after treatment with paclitaxel (Taxol), an inhibitor of mitosis used for cancer treatment. Based on these metabolic and isotopic stationary states, metabolic flux distribution in the central metabolism of paclitaxel-treated MCF-7 cells was determined by 13C-MFA. Finally, estimations of the 95% confidence intervals showed that tricarboxylic acid cycle metabolic flux increased after paclitaxel treatment. Conversely, anaerobic glycolysis metabolic flux decreased, revealing metabolic redirections by paclitaxel inhibition. The gap between total regeneration and consumption of ATP in paclitaxel-treated cells was also found to be 1.2 times greater than controls, suggesting ATP demand was increased by paclitaxel treatment, likely due to increased microtubule polymerization. These data confirm that 13C-MFA can be used to investigate inhibitor-induced metabolic redirection in cancer cells. This will contribute to future pharmaceutical developments and understanding variable patient response to treatment.

Improved riboflavin production with Ashbya gossypii from vegetable oil based on 13C metabolic network analysis with combined labeling analysis by GC/MS, LC/MS, 1D, and 2D NMR

The fungus Ashbya gossypii is an important industrial producer of riboflavin, i.e. vitamin B₂. In order to meet the constantly increasing demands for improved production processes, it appears essential to better understand the underlying metabolic pathways of the vitamin. Here, we used a highly sophisticated set-up of parallel ¹³C tracer studies with labeling analysis by GC/MS, LC/MS, 1D, and 2D NMR to resolve carbon fluxes in the overproducing strain A. gossypii B2 during growth and subsequent riboflavin production from vegetable oil as carbon source, yeast extract, and supplemented glycine. The studies provided a detailed picture of the underlying metabolism. Glycine was exclusively used as carbon-two donor of the vitamin's pyrimidine ring, which is part of its isoalloxazine ring structure, but did not contribute to the carbon-one metabolism due to the proven absence of a functional glycine cleavage system. The pools of serine and glycine were closely connected due to a highly reversible serine hydroxymethyltransferase. Transmembrane formate flux simulations revealed that the one-carbon metabolism displayed a severe bottleneck during initial riboflavin production, which was overcome in later phases of the cultivation by intrinsic formate accumulation. The transiently limiting carbon-one pool was successfully replenished by time-resolved feeding of small amounts of formate and serine, respectively. This increased the intracellular availability of glycine, serine, and formate and resulted in a final riboflavin titer increase of 45%.

Characterization of an easy-to-use method for the routine analysis of the central metabolism using an affordable low-resolution GC-MS system: application to Arthrospira platensis

We developed an easy-to-use method for the routine analysis of the central metabolism using an affordable low-resolution GC-MS system run in SIM mode. The profiling approach was optimized for the derivatization protocol of some 60 targeted metabolites. The performance of two silylation reagents (MSTFA and BSTFA) that allowed the comprehensive derivatization of 42 key intermediary metabolites of the 60 initially targeted (organic acids, phosphate derivatives, monosaccharides and amino acids) was measured. The experimental results unequivocally showed that the MSTFA reagent met mandatory criteria including ease of handling (a very simple one-step protocol was developed), comprehensiveness of derivatization (the 42 compounds covered the extended metabolic pathways of the central carbon metabolism, with a coverage percentage ranging from 17% for the worst to 90% for the best result), optimized response coefficient of the whole derivatives (median value greater than the others by one order of magnitude) and repeatability of the protocol (RSD value below 25% for the whole procedure). When tested in real conditions (cyanobacteria polar extract), the experimental results showed that the profiling methodology was adequately repeatable (RSD = 35%) to ensure quantification results comparable with much more sensitive analytical techniques (capillary electrophoresis/mass spectrometry and liquid chromatography/triple quadrupole mass spectrometry system), while needing only about twice the quantity of biomass. Graphical abstract Schematic overview of an easy-to-use profiling method for the routine analysis of the central metabolism using a low-resolution GC-MS system.

Enabling the valorization of guaiacol-based lignin: Integrated chemical and biochemical production of cis,cis-muconic acid using metabolically engineered Amycolatopsis sp ATCC 39116

Lignin is nature's second most abundant polymer and displays a largely unexploited renewable resource for value-added bio-production. None of the lignin-based fermentation processes so far managed to use guaiacol (2-methoxy phenol), the predominant aromatic monomer in depolymerized lignin. In this work, we describe metabolic engineering of Amycolatopsis sp. ATCC 39116 to produce cis,cis-muconic acid (MA), a precursor of recognized industrial value for commercial plastics, from guaiacol. The microbe utilized a very broad spectrum of lignin-based aromatics, such as catechol, guaiacol, phenol, toluene, p-coumarate, and benzoate, tolerated them in elevated amounts and even preferred them over sugars. As a next step, we developed a novel approach for genomic engineering of this challenging, GC-rich actinomycete. The successful introduction of conjugation and blue-white screening, using β-glucuronidase, enabled tailored genomic modifications within ten days. Successive deletion of two putative muconate cycloisomerases from the genome provided the mutant Amycolatopsis sp. ATCC 39116 MA-2, which accumulated 3.1gL^-1 MA from guaiacol within 24h, achieving a yield of 96%. The mutant was found also capable to produce MA from a guaiacol-rich true lignin hydrolysate, obtained from pine through hydrothermal conversion. This provides an important proof-of-concept to successfully coupling chemical and biochemical process steps into a value chain from the lignin polymer to an industrial chemical. In addition, Amycolatopsis sp. ATCC 39116 MA-2 was able to produce 2-methyl MA from o-cresol (2-methyl phenol), which opens possibilities towards polymers with novel architecture and properties.

13C-assisted metabolic flux analysis to investigate heterotrophic and mixotrophic metabolism in Cupriavidus necator H16

INTRODUCTION

Cupriavidus necator H16 is a gram-negative bacterium, capable of lithoautotrophic growth by utilizing hydrogen as an energy source and fixing carbon dioxide (CO2) through Calvin-Benson-Bassham (CBB) cycle. The potential to utilize synthesis gas (Syngas) and the prospects of rerouting carbon from polyhydroxybutyrate synthesis to value-added compounds makes C. necator an excellent chassis for industrial application.

OBJECTIVES

In the context of lack of sufficient quantitative information of the metabolic pathways and to advance in rational metabolic engineering for optimized product synthesis in C. necator H16, we carried out a metabolic flux analysis based on steady-state 13C-labelling.

METHODS

In this study, steady-state carbon labelling experiments, using either d-[1-13C]fructose or [1,2-13C]glycerol, were undertaken to investigate the carbon flux through the central carbon metabolism in C. necator H16 under heterotrophic and mixotrophic growth conditions, respectively.

RESULTS

We found that the CBB cycle is active even under heterotrophic condition, and growth is indeed mixotrophic. While Entner-Doudoroff (ED) pathway is shown to be the major route for sugar degradation, tricarboxylic acid (TCA) cycle is highly active in mixotrophic condition. Enhanced flux is observed in reductive pentose phosphate pathway (redPPP) under the mixotrophic condition to supplement the precursor requirement for CBB cycle. The flux distribution was compared to the mRNA abundance of genes encoding enzymes involved in key enzymatic reactions of the central carbon metabolism.

CONCLUSION

This study leads the way to establishing 13C-based quantitative fluxomics for rational pathway engineering in C. necator H16.

Cell-Type Specific Metabolic Flux Analysis: A Challenge for Metabolic Phenotyping and a Potential Solution in Plants

Stable isotope labelling experiments are used routinely in metabolic flux analysis (MFA) to determine the metabolic phenotype of cells and tissues. A complication arises in multicellular systems because single cell measurements of transcriptomes, proteomes and metabolomes in multicellular organisms suggest that the metabolic phenotype will differ between cell types. In silico analysis of simulated metabolite isotopomer datasets shows that cellular heterogeneity confounds conventional MFA because labelling data averaged over multiple cell types does not necessarily yield averaged flux values. A potential solution to this problem—the use of cell-type specific reporter proteins as a source of cell-type specific labelling data—is proposed and the practicality of implementing this strategy in the roots of Arabidopsis thaliana seedlings is explored. A protocol for the immunopurification of ectopically expressed green fluorescent protein (GFP) from Arabidopsis thaliana seedlings using a GFP-binding nanobody is developed, and through GC-MS analysis of protein hydrolysates it is established that constitutively expressed GFP reports accurately on the labelling of total protein in root tissues. It is also demonstrated that the constitutive expression of GFP does not perturb metabolism. The principal obstacle to the implementation of the method in tissues with cell-type specific GFP expression is the sensitivity of the GC-MS system.

Optimal 13C-labeling of glycerol carbon source for precise flux estimation in Escherichia coli

Glycerol is a promising carbon source for bio-production and is particularly attractive because it is produced in excess as a biodiesel byproduct. Elucidating the flux distribution of glycerol catabolism would greatly aid metabolic engineering, but ¹³C-labeling of glycerol has not yet been optimized for precise flux estimations. In this study, an Escherichia coli wild type strain was aerobically cultured using glycerol as the sole carbon source. [1,3-¹³C], [2-¹³C], and [U-¹³C] glycerols were independently mixed with an equal amount of naturally labeled glycerol; these mixtures were used as ¹³C-labeled substrates, and flux distributions during exponential growth were estimated based on ¹³C-enrichment of proteinogenic amino acids. The glycerol catabolism pathway in E. coli has four branches: the oxidative pentose phosphate pathway (PP), Entner-Doudoroff pathway (ED), and malic enzyme (ME) pathways, and the glyoxylate shunt (GX). The 95% confidence intervals of these fluxes were compared across the ¹³C-labeling experiments. The [2-¹³C] and [U-¹³C] glycerols, but not [1,3-¹³C] glycerol allowed precise characterization of the PP, ED, and ME pathway fluxes. All three types of ¹³C-labeling aided in successfully determining the GX flux. Based on the above estimated flux distribution, various patterns of ¹³C-labeling of glycerol were computationally generated. These in silico experiments revealed that the sole use of [2-¹³C] glycerol or [1,3-¹³C] glycerol is optimal for precise flux estimation, where simultaneous using glycerols with different types of ¹³C-labeling failed to improve flux estimation as assessed by confidence intervals.

Bio-based succinate from sucrose: High-resolution 13C metabolic flux analysis and metabolic engineering of the rumen bacterium Basfia succiniciproducens

Succinic acid is a platform chemical of recognized industrial value and accordingly faces a continuous challenge to enable manufacturing from most attractive raw materials. It is mainly produced from glucose, using microbial fermentation. Here, we explore and optimize succinate production from sucrose, a globally applied substrate in biotechnology, using the rumen bacterium Basfia succiniciproducens DD1. As basis of the strain optimization, the yet unknown sucrose metabolism of the microbe was studied, using ¹³C metabolic flux analyses. When grown in batch culture on sucrose, the bacterium exhibited a high succinate yield of 1molmol^-1 and a by-product spectrum, which did not match the expected PTS-mediated sucrose catabolism. This led to the discovery of a fructokinase, involved in sucrose catabolism. The flux approach unraveled that the fructokinase and the fructose PTS both contribute to phosphorylation of the fructose part of sucrose. The contribution of the fructokinase reduces the undesired loss of the succinate precursor PEP into pyruvate and into pyruvate-derived by-products and enables increased succinate production, exclusively via the reductive TCA cycle branch. These findings were used to design superior producers. Mutants, which (i) overexpress the beneficial fructokinase, (II) lack the competing fructose PTS, and (iii) combine both traits, produce significantly more succinate. In a fed-batch process, B. succiniciproducens ΔfruA achieved a titer of 71gL^-1 succinate and a yield of 2.5molmol^-1 from sucrose.

Genome-wide association studies dissect the genetic networks underlying agronomical traits in soybean

BACKGROUND

Soybean (Glycine max [L.] Merr.) is one of the most important oil and protein crops. Ever-increasing soybean consumption necessitates the improvement of varieties for more efficient production. However, both correlations among different traits and genetic interactions among genes that affect a single trait pose a challenge to soybean breeding.

RESULTS

To understand the genetic networks underlying phenotypic correlations, we collected 809 soybean accessions worldwide and phenotyped them for two years at three locations for 84 agronomic traits. Genome-wide association studies identified 245 significant genetic loci, among which 95 genetically interacted with other loci. We determined that 14 oil synthesis-related genes are responsible for fatty acid accumulation in soybean and function in line with an additive model. Network analyses demonstrated that 51 traits could be linked through the linkage disequilibrium of 115 associated loci and these links reflect phenotypic correlations. We revealed that 23 loci, including the known Dt1, E2, E1, Ln, Dt2, Fan, and Fap loci, as well as 16 undefined associated loci, have pleiotropic effects on different traits.

CONCLUSIONS

This study provides insights into the genetic correlation among complex traits and will facilitate future soybean functional studies and breeding through molecular design.

The importance of accurately correcting for the natural abundance of stable isotopes

The use of isotopically labeled tracer substrates is an experimental approach for measuring in vivo and in vitro intracellular metabolic dynamics. Stable isotopes that alter the mass but not the chemical behavior of a molecule are commonly used in isotope tracer studies. Because stable isotopes of some atoms naturally occur at non-negligible abundances, it is important to account for the natural abundance of these isotopes when analyzing data from isotope labeling experiments. Specifically, a distinction must be made between isotopes introduced experimentally via an isotopically labeled tracer and the isotopes naturally present at the start of an experiment. In this tutorial review, we explain the underlying theory of natural abundance correction of stable isotopes, a concept not always understood by metabolic researchers. We also provide a comparison of distinct methods for performing this correction and discuss natural abundance correction in the context of steady state 13C metabolic flux, a method increasingly used to infer intracellular metabolic flux from isotope experiments.