Quantitative Metabolome Analysis Using Capillary Electrophoresis Mass Spectrometry

Soga, Tomoyoshi; Ohashi, Yoshiaki; Ueno, Yuki; Naraoka, Hisako; Tomita, Masaru; Nishi­oka, Takaaki

doi:10.1021/pr034020m

Cited by 904 publications

(697 citation statements)

References 28 publications

Supporting

Mentioning

683

Contrasting

Unclassified

Order By: Relevance

“…In this study, the Biolog phenotyping dataset could be used effectively for the metabolic reconstruction of B. subtilis, and furthermore the latter could enhance the quality and utility of the former (see above). However, the in silico model could only predict 46% (160 in 350) of the experimental metabolomic compounds reported from the literature (5). At the present time, the annotation of the B. subtilis genome is incomplete, and ϳ40% of its ORFs do not have a functional assignment (2).…”

Section: Discussionmentioning

confidence: 99%

“…It should also be noticed that subtle differences in the experimental conditions and the strain background could induce the difference between lethal and a very slow growth mutation (22). The in silico metabolites of the metabolic network were also compared with experimental metabolomic data for B. subtilis grown in a moderately rich medium (5). 350 of 1692 compounds separated have been positively identified using standards (see supplemental Table 1 of Ref.…”

Section: Table 2 Impact Of Single-gene Deletions On Growth In B Subtmentioning

confidence: 99%

See 1 more Smart Citation

Genome-scale Reconstruction of Metabolic Network in Bacillus subtilis Based on High-throughput Phenotyping and Gene Essentiality Data

Oh¹,

Palsson²,

Park

et al. 2007

Journal of Biological Chemistry

402

356

View full text Add to dashboard Cite

In this report, a genome-scale reconstruction of Bacillus subtilis metabolism and its iterative development based on the combination of genomic, biochemical, and physiological information and high-throughput phenotyping experiments is presented. The initial reconstruction was converted into an in silico model and expanded in a four-step iterative fashion. First, network gap analysis was used to identify 48 missing reactions that are needed for growth but were not found in the genome annotation. Second, the computed growth rates under aerobic conditions were compared with high-throughput phenotypic screen data, and the initial in silico model could predict the outcomes qualitatively in 140 of 271 cases considered. Detailed analysis of the incorrect predictions resulted in the addition of 75 reactions to the initial reconstruction, and 200 of 271 cases were correctly computed. Third, in silico computations of the growth phenotypes of knock-out strains were found to be consistent with experimental observations in 720 of 766 cases evaluated. Fourth, the integrated analysis of the large-scale substrate utilization and gene essentiality data with the genomescale metabolic model revealed the requirement of 80 specific enzymes (transport, 53; intracellular reactions, 27) that were not in the genome annotation. Subsequent sequence analysis resulted in the identification of genes that could be putatively assigned to 13 intracellular enzymes. The final reconstruction accounted for 844 open reading frames and consisted of 1020 metabolic reactions and 988 metabolites. Hence, the in silico model can be used to obtain experimentally verifiable hypothesis on the metabolic functions of various genes.Bacillus subtilis has been the organism of choice for the production of several important industrial products, including antibiotics, enzymes, nucleosides, and vitamins. Several aspects of the biochemistry, genetics, and physiology of B. subtilis have been studied extensively making B. subtilis the best characterized prokaryote second only to Escherichia coli (1, 2). In addition various "-omics" data sets such as transcriptomic (3), proteomic (4), and metabolomic (5) are available for B. subtilis. This wealth of experimental data enables the development of a genome-scale metabolic in silico model that can be used not only for quantitative interpretation and structured integration of such extensive data sets but also as a tool for hypothesis generation and engineering of B. subtilis metabolism.To date, constraint-based reconstruction and analysis (COBRA) 4 of cellular metabolism has been employed successfully to develop organism-specific genome-scale in silico models that have enabled numerous applications (6). Unlike other modeling strategies such as kinetic (7), stochastic (8), and cybernetic (9) methods, the COBRA approach does not attempt to compute precisely what a biochemical network does; rather, it seeks to distinguish between the network states that are achievable from those that are not, based on a detailed reconstruction of...

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Table 2 Impact Of Single-gene Deletions On Growth In B Subtmentioning

confidence: 99%

Genome-scale Reconstruction of Metabolic Network in Bacillus subtilis Based on High-throughput Phenotyping and Gene Essentiality Data

Oh¹,

Palsson²,

Park

et al. 2007

Journal of Biological Chemistry

402

356

View full text Add to dashboard Cite

show abstract

“…After the centrifugation, the supernatant was filtered (M r cutoff of 5,000) and lyophilized, and the resulting dried extract was dissolved in 20 l of water. Capillary electrophoresis electrospray ionization time-of-flight mass spectrometry (CE-TOFMS) measurements were performed as described previously (27,28,29). In this procedure, the recovery rates of nucleotides ranged from 60 to 90%, for example, 76, 81, 82, 63, 84, 76, 89, 57, and 66% for AMP, ADP, ATP, dATP, UDP, GDP, CDP, dTDP, and ppGpp, respectively.…”

Section: Methodsmentioning

confidence: 99%

Degradation of ppGpp by Nudix Pyrophosphatase Modulates the Transition of Growth Phase in the Bacterium Thermus thermophilus

Ooga

Ohashi

Kuramitsu

et al. 2009

Journal of Biological Chemistry

Self Cite

View full text Add to dashboard Cite

A major bacterial alarmone, guanosine 3,5-bispyrophosphate (ppGpp), controls cellular growth under conditions of nutritional starvation. For most bacteria, intracellular ppGpp levels are tightly controlled by the synthesis/degradation cycle of RelA and SpoT activities. This study shows a novel ppGpp regulatory protein governing the cellular growth of Thermus thermophilus, Ndx8, a member of the Nudix pyrophosphatase family that degrades ppGpp to yield guanosine 3,5-bisphosphate. The ndx8-null mutant strain exhibited early stage growth arrest accompanied by the stationary phase-specific morphologies and global transcriptional modulation under nutritionally defined conditions. Several possible substrate compounds of Ndx8, which specifically accumulated in the ndx8 mutant cells, were identified by employing a capillary electrophoresis time-of-flight mass spectrometry-based metabolomics approach. Among them, the hydrolytic activity of Ndx8 for ppGpp was significant not only in vitro but also in vivo. Finally, the elimination of ppGpp synthetic activity suppressed the observed phenotype of the ndx8 mutation, suggesting that the function of Ndx8 as a growth regulator is involved in ppGpp accumulation, which is thought to act as a trigger of the growth phase transition. These results suggest a novel mechanism of ppGpp-mediated growth control by the functional relay between Ndx8 and SpoT activity as ppGpp scavengers.The stringent response, which is a pleiotropic adaptation to nutritional starvation and stress, is broadly conserved in bacteria and plant chloroplasts (1, 2). This physiological control is dominated by a rapid synthesis/degradation cycle of the stringent alarmones guanosine 3Ј-pyrophosphate 5Ј-triphosphate (pppGpp) 4 or guanosine 3Ј,5Ј-bispyrophosphate (ppGpp) ( Fig. 1) (3). In Escherichia coli grown under amino acid depletion, pppGpp is synthesized from ATP and GTP by ribosome-associated RelA activity and subsequently converted to ppGpp by the activity of 5Ј-nucleotidase (4). Besides this pathway, ppGpp is also directly synthesized from GDP by the activity of RelA. Thereafter, ppGpp is degraded to GDP and pyrophosphate by the activity of SpoT, which is a RelA homolog with reciprocal activities for ppGpp degradation and synthesis (5, 6). For several bacteria, SpoT physiologically acts as both the ppGpp synthetase and hydrolase and is known as the Rel/Spo homolog. The metabolism of these alarmone nucleotides is understood based on the function of these two enzymes, whereas recent studies have identified alternative players acting as ppGpp synthetase in bacteria (7,8). On the other hand, for the degradation of ppGpp, previous studies reported that SpoT-independent (p)ppGpp degradation activity exists in bacteria, whereas the biological meaning(s) and enzymatic mechanism(s) of these alternative pathways have not been characterized in any organisms (9 -12).The Nudix hydrolases constitute a large family of proteins that share a highly conserved amino acid sequence, the so-called "Nudix motif," which is distribut...

show abstract

“…Application of metabolomic analyses using capillary electrophoresis/electrospray ionization/mass spectrometry (CE/ESI/MS; refs. 21,22) allows us to determine fluxes of multiple metabolic pathways during cell-cycle progression in vitro (20,23,24). MALDI-IMS analyses of metastatic tumors have shown that the cancer cells in G 1 phase were more active in glycolysis than those in the other phases.…”

Section: Introductionmentioning

confidence: 99%

Energy Management by Enhanced Glycolysis in G1-phase in Human Colon Cancer Cells In Vitro and In Vivo

Bao

Mukai

Hishiki

et al. 2013

Molecular Cancer Research

View full text Add to dashboard Cite

Activation of aerobic glycolysis in cancer cells is well known as the Warburg effect, although its relation to cellcycle progression remains unknown. In this study, human colon cancer cells were labeled with a cell-cycle phasedependent fluorescent marker Fucci to distinguish cells in G 1 -phase and those in S þ G 2 /M phases. Fucci-labeled cells served as splenic xenograft transplants in super-immunodeficient NOG mice and exhibited multiple metastases in the livers, frozen sections of which were analyzed by semiquantitative microscopic imaging mass spectrometry. Results showed that cells in G 1 -phase exhibited higher concentrations of ATP, NADH, and UDP-N-acetylglucosamine than those in S and G 2 -M phases, suggesting accelerated glycolysis in G 1 -phase cells in vivo. Quantitative determination of metabolites in cells synchronized in S, G 2 -M, and G 1 phases suggested that efflux of lactate was elevated significantly in G 1 -phase. By contrast, ATP production in G 2 -M was highly dependent on mitochondrial respiration, whereas cells in S-phase mostly exhibited an intermediary energy metabolism between G 1 and G 2 -M phases. Isogenic cells carrying a p53-null mutation appeared more active in glycolysis throughout the cell cycle than wild-type cells. Thus, as the cell cycle progressed from G 2 -M to G 1 phases, the dependency of energy production on glycolysis was increased while the mitochondrial energy production was reciprocally decreased.Implications: These results shed light on distinct features of the phase-specific phenotypes of metabolic systems in cancer cells. Mol Cancer Res; 11(9); 973-85. Ó2013 AACR.

show abstract

Quantitative Metabolome Analysis Using Capillary Electrophoresis Mass Spectrometry

Cited by 904 publications

References 28 publications

Genome-scale Reconstruction of Metabolic Network in Bacillus subtilis Based on High-throughput Phenotyping and Gene Essentiality Data

Genome-scale Reconstruction of Metabolic Network in Bacillus subtilis Based on High-throughput Phenotyping and Gene Essentiality Data

Degradation of ppGpp by Nudix Pyrophosphatase Modulates the Transition of Growth Phase in the Bacterium Thermus thermophilus

Energy Management by Enhanced Glycolysis in G1-phase in Human Colon Cancer Cells In Vitro and In Vivo

Contact Info

Product

Resources

About