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PubMed2006

Mass spectrometry-based glycomics strategy for exploring N-linked glycosylation in eukaryotes and bacteria.

N-Glycosylation of proteins is recognized as one of the most common posttranslational modifications in eukaryotes. To date, most glycomics techniques are limited to examining eukaryotic pathways. Technologies capable of characterizing newly described N-linked glycosylation systems in bacteria from biologically relevant samples in an accurate, rapid, and cost-effective manner are needed. In this paper, a new glycomics strategy, based on the combination of nonspecific proteolytic digestion and permethylation, was devised that can be used for both eukaryotic and bacterial glycoproteins. Eukaryotic glycoproteins were digested with Pronase E with a higher ratio (enzyme/protein, 2:1-3:1) and a longer reaction time (48-72 h). The Asn-glycans were then purified using porous graphitic carbon cartridges followed by permethylation. The mass spectrometric data indicated that hydroxyl groups were methylated, while the amino group in asparagine underwent beta-elimination. Both modifications were evident from an increase of 111 Da in the molecular masses of permethylated Asn-glycans compared to the corresponding free oligosaccharides. NMR spectroscopy corroborated these results by showing that the mass difference resulted from beta-elimination of the free amino group in the asparagine residue. The method was validated with the characterization of the N-linked glycoproteins in total protein extracts from the bacterium Campylobacter jejuni 11168H. In addition to detecting the Asn-linked bacterial heptasaccharide, we also observed an unexpected free heptasaccharide intermediate that required a functional glycosylation pathway. These results demonstrate the usefulness of this method for screening N-linked glycans expressed by eukaryotes and bacteria and for detecting novel intermediates of N-linked glycosylation pathways.

Animals↗
PubMed2026

Metab8D: a metabolic regulome network from multiomics and machine learning.

To explore multiomic regulation of the metabolome, we used machine learning to predict metabolomic variation across ~1000 different cancer cell lines with matched omics data from eight biomolecular classes: genomic copy number variation, mutations, DNA methylation, histone post-translational modifications (PTMs), transcriptomics and RNA splice variants, non-coding transcriptomics (miRNA and lncRNA), proteomics, and phosphoproteomics. Overall, the metabolome is tightly associated with the transcriptome, with coding and non-coding RNAs emerging as top predictors. Peripheral metabolites are predictable via levels of corresponding enzymes, while those in central metabolism require combinatorial predictors in signaling and redox pathways, and may not reflect corresponding pathway expression. We reconstruct multiomic interaction subnetworks for highly predictable metabolites, and YAP1 signaling emerged as a top global predictor across four omic layers. We prioritize predictive multiomic features for single-cell and spatial metabolomics assays. Top predictors were enriched for synthetic-lethal interactions and synergistic combination therapies that target compensatory metabolic modulators.

Machine Learning↗
PubMed2006

Metabolic engineering of carotenoid biosynthesis in Escherichia coli by ordered gene assembly in Bacillus subtilis.

We attempted to optimize the production of zeaxanthin in Escherichia coli by reordering five biosynthetic genes in the natural carotenoid cluster of Pantoea ananatis. Newly designed operons for zeaxanthin production were constructed by the ordered gene assembly in Bacillus subtilis (OGAB) method, which can assemble multiple genes in one step using an intrinsic B. subtilis plasmid transformation system. The highest level of production of zeaxanthin in E. coli (820 microg/g [dry weight]) was observed in the transformant with a plasmid in which the gene order corresponds to the order of the zeaxanthin metabolic pathway (crtE-crtB-crtI-crtY-crtZ), among a series of plasmids with circularly permuted gene orders. Although two of five operons using intrinsic zeaxanthin promoters failed to assemble in B. subtilis, the full set of operons was obtained by repressing operon expression during OGAB assembly with a p(R) promoter-cI repressor system. This result suggests that repressing the expression of foreign genes in B. subtilis is important for their assembly by the OGAB method. For all tested operons, the abundance of mRNA decreased monotonically with the increasing distance of the gene from the promoter in E. coli, and this may influence the yield of zeaxanthin. Our results suggest that rearrangement of biosynthetic genes in the order of the metabolic pathway by the OGAB method could be a useful approach for metabolic engineering.

Bacillus subtilis↗
PubMed2026

Proteins as Regulators of Metabolic Changes in Sepsis: Alterations in Body Fluids, Immune Cells, and Organs through the Eyes of Proteomics.

Sepsis is a life-threatening syndrome characterized by a dysregulated host response to infection and profound metabolic alterations that contribute to immune dysfunction and organ failure. This Review synthesizes proteomic evidence on sepsis-associated alterations in proteins involved in metabolic pathways across circulating biofluids, immune cells, and organs. Across plasma and urine, proteomic studies identify disturbances in lipoprotein-associated pathways, redox homeostasis, mitochondrial function, and substrate metabolism, indicating that protein signatures of metabolic dysregulation are systemic and detectable across biofluids. In immune cells, monocytes and neutrophils, proteomic analyses reveal a shift toward glycolysis with concurrent impairment of mitochondrial pathways alongside phenotype-dependent differences in lipid and redox-related programs. Organ-level studies further show that metabolic responses are heterogeneous, with distinct trajectories in the kidney, heart, liver, lung, skeletal muscle, and brain. These observations support the concept that sepsis involves compartment-specific remodeling of metabolism-associated protein networks rather than a single convergent metabolic state. Proteomics also highlights potential translational opportunities by identifying metabolism-associated proteins linked to disease severity, clinical phenotypes, and biologically distinct patient subgroups, although the current evidence remains largely exploratory and context-dependent. Overall, proteomics provides a complementary framework for understanding the molecular regulation of sepsis-associated metabolic dysfunction and may refine biological stratification and therapeutic targeting, particularly when integrated with longitudinal sampling and multiomic data.

Humans↗
PubMed2006

Selective degradation of transcripts during meiotic maturation of mouse oocytes.

There is massive destruction of transcripts during the maturation of mouse oocytes. The objective of this project was to identify and characterize the transcripts that are degraded versus those that are stable during the transcriptionally silent germinal vesicle (GV)-stage to metaphase II (MII)-stage transition using a microarray approach. A system for oocyte transcript amplification using both internal and 3'-poly(A) priming was utilized to minimize the impact of complex variations in transcript polyadenylation prevalent during this transition. Transcripts were identified and quantified using the Affymetrix Mouse Genome 430 v2.0 GeneChip. The significantly changed and stable transcripts were analyzed using Ingenuity Pathways Analysis and GenMAPP/MAPPFinder to characterize the biological themes underlying global changes in oocyte transcripts during maturation. It was concluded that the destruction of transcripts during the GV to MII transition is a selective rather than promiscuous process in mouse oocytes. In general, transcripts involved in processes that are associated with meiotic arrest at the GV-stage and the progression of oocyte maturation, such as oxidative phosphorylation, energy production, and protein synthesis and metabolism, were dramatically degraded. In contrast, transcripts encoding participants in signaling pathways essential for maintaining the unique characteristics of the MII-arrested oocyte, such as those involved in protein kinase pathways, were the most prominent among the stable transcripts.

Animals↗
PubMed2006

The trifecta of aging in Caenorhabditis elegans.

Insulin signaling, mitochondrial respiration, and dietary restriction share conserved roles not only in the regulation of lifespan, but also in the timing and control of diverse functions such as reproduction, stress resistance and metabolism. These autonomous pathways differ in their dependence on known transcription factors and in their temporal requirements, but converge to manipulate the core set of physiological systems necessary for extended lifespan in worms. Recent work suggests that components of these pleiotrophic pathways might be manipulated specifically for their effects on aging without affecting additional downstream functions. Examination of these findings will help us to understand how the molecular mechanisms of distinct pathways can unite in the regulation of longevity.

Aging↗
PubMed2006

The effects of time delays in a phosphorylation-dephosphorylation pathway.

Complex signaling cascades involve many interlocked positive and negative feedback loops which have inherent delays. Modeling these complex cascades often requires a large number of variables and parameters. Delay differential equation models have been helpful in describing inherent time lags and also in reducing the number of governing equations. However the consequences of model reduction via delay differential equations have not been fully explored. In this paper we systematically examine the effect of delays in a complex network of phosphorylation-dephosphorylation cycles (described by Gonze and Goldbeter, J. Theor. Biol., 210, (2001) 167-186), which commonly occur in many biochemical pathways. By introducing delays in the positive and negative regulatory interactions, we show that a delay differential model can indeed reduce the number of cycles actually required to describe the phosphorylation-dephosphorylation pathway. In addition, we find some of the unique properties of the network and a quantitative measure of the minimum number of delay variables required to model the network. These results can be extended for modeling complex signalling cascades.

Feedback, Physiological↗
PubMed2006

The thiol-based redox networks of pathogens: unexploited targets in the search for new drugs.

Hydroperoxide metabolism in diverse pathogens is reviewed under consideration of involved enzymes as potential drug targets. The common denominator of the peroxidase systems of Trypanosoma, Leishmania, Plasmodium, and Mycobacterium species is the use of NAD(P)H to reduce hydroperoxides including peroxynitrite via a flavin-containing disulfide reductase, a thioredoxin (Trx)-related protein and a peroxidase that operates with thiol catalysis. In Plasmodium falciparum, thioredoxin- and glutathione dependent systems appear to be linked via glutaredoxin and plasmoredoxin to terminal thioredoxin peroxidases belonging to both, the peroxiredoxin (Prx) and glutathione peroxidase (GPx) family. In Mycobacterium tuberculosis, a catalase-type peroxidase is complemented by the typical 2-C-Prx AhpC that, in contrast to most bacteria, is reduced by TrxC, and an atypical 2-C-Prx reduced by TrxB or C. A most complex variation of the scheme is found in trypanosomatids, where the unique redox metabolite trypanothione reduces the thioredoxin-related tryparedoxin, which fuels Prx- and GPx-type peroxidases as well as ribonucleotide reductase. In Trypanosoma brucei and Leishmania donovani the system has been shown to be essential for viability and virulence by inversed genetics. It is concluded that optimum efficacy can be expected from inhibitors of the most upstream components of the redox cascades. For trypanosomatids attractive validated drug targets are trypanothione reductase and trypanothione synthetase; for mycobacteria thioredoxin reductase appears most appealing, while in Plasmodium simultaneous inhibition of both the thioredoxin and the glutathione pathway appears advisable to avoid mutual substitution in co-substrate supply to the peroxidases. Financial and organisational needs to translate the scientific progress into applicable drugs are discussed under consideration of the socio-economic impact of the addressed diseases.

Animals↗
PubMed2006

Biosynthesis and engineering of isoprenoid small molecules.

Isoprenoid secondary metabolites are a rich source of commercial products that have not been fully explored. At present, there are isoprenoid products used in cancer therapy, the treatment of infectious diseases, and crop protection. All isoprenoids share universal prenyl diphosphate precursors synthesized via two distinct pathways. From these universal precursors, the biosynthetic pathways to specific isoprenoids diverge resulting in a staggering array of products. Taking advantage of this diversity has been the focus of much effort in metabolic engineering heterologous hosts. In addition, the engineering of the mevalonate pathway has increased levels of the universal precursors available for heterologous production. Finally, we will describe the efforts to produce to commercial terpenoids, paclitaxel and artemisinin.

Artemisinins↗
PubMed2026

Enzyme-Metabolite Network Analysis of Endometrial Cancer-Derived Extracellular Vesicles Through Integrated Proteomics and Metabolomics.

Endometrial cancer (EC) is the most common gynecological malignancy in high-income countries. Extracellular vesicles (EVs) are key mediators of intercellular communication and metabolic reprogramming, but their molecular cargo in EC remains poorly characterized. EVs were isolated from four EC cell lines representing Type I and Type II subtypes (AN3CA, ISHIKAWA, HEC1A, and KLE). Untargeted metabolomics was performed by HILIC-LC-MS/MS, proteomics by data-independent acquisition (DIA) mass spectrometry, and multi-omics integration using MetaboAnalyst and OmicsNet. Metabolomic profiling identified 1463 annotated features and revealed significant differences among EC cell lines (PERMANOVA, p = 0.002). Twenty-eight differentially abundant metabolites, including lactic acid, succinic acid, and uric acid, were identified. Proteomic analysis quantified 8513 proteins with subtype-specific expression patterns. Integrated analysis revealed seven significantly enriched pathways, including glycolysis/gluconeogenesis, central carbon metabolism in cancer, and the pentose phosphate pathway. Increased LDHA abundance in metastatic AN3CA-derived EVs was confirmed by Western blot (p = 0.047). EC-derived EVs display subtype- and metastatic-status-specific metabolo-proteomic signatures, with glycolysis, TCA cycle remodeling, and central carbon metabolism as convergent pathway signatures of molecular reprogramming. These findings establish a multi-omics framework for characterizing EV cargo in EC and identify candidate enzyme-metabolite nodes for future biomarker validation in patient-derived specimens.

Female↗
PubMed2007

alpha-ketoglutaric semialdehyde dehydrogenase isozymes involved in metabolic pathways of D-glucarate, D-galactarate, and hydroxy-L-proline. Molecular and metabolic convergent evolution.

Azospirillum brasilense possesses an alternative pathway of l-arabinose metabolism in which alpha-ketoglutaric semialdehyde (alphaKGSA) dehydrogenase (KGSADH) is involved in the last step, the conversion of alphaKGSA to alpha-ketoglutarate. In the preceding studies, we identified a set of metabolic genes of the l-arabinose pathway including the KGSADH gene (Watanabe, S., Kodaki, T., and Makino, K. (2006) J. Biol. Chem. 281, 2612-2623; Watanabe, S., Kodaki, T., and Makino, K. (2006) J. Biol. Chem. 281, 28876-28888; Watanabe, S., Shimada, N., Tajima, K., Kodaki, T., and Makino, K. (2006) J. Biol. Chem. 281, 33521-33536). Here, we describe that A. brasilense possesses two different KGSADH isozymes from l-arabinose-related enzyme (KGSADH-I); that is, d-glucarate/d-galactarate-inducible KGSADH-II and hydroxy-l-proline-inducible KGSADH-III. They were purified homogeneously from A. brasilense cells grown on d-galactarate or hydroxy-l-proline, respectively. When compared with KGSADH-I, amino acid sequences of KGSADH-II and KGSADH-III were significantly similar but not totally identical. Physiological characterization using recombinant enzymes revealed that KGSADH-II and KGSADH-III showed similar high substrate specificity for alphaKGSA and different coenzyme specificity; that is, NAD(+)-dependent KGSADH-II and NADP(+)-dependent KGSADH-III. In the phylogenetic tree of the aldehyde dehydrogenase (ALDH) superfamily, KGSADH-II and KGSADH-III were poorly related to the known ALDH subclasses including KGSADH-I. On the other hand, ALDH-like ycbD protein involved in d-glucarate/d-galactarate operon from Bacillus subtilis is closely related to the methylmalonyl semialdehyde dehydrogenase subclass but not A. brasilense KGSADH isozymes. To estimate the correct function, the corresponding gene was expressed, purified, and characterized. Kinetic analysis revealed the physiological role as NADP(+)-dependent KGSADH. We conclude that three different types of KGSADH appeared in the bacterial evolutional stage convergently. Furthermore, even the same pathway such as l-arabinose and d-glucarate/d-galactarate metabolism also evolved by the independent involvement of KGSADH.

Aldehyde Oxidoreductases↗
PubMed1959

Drug metabolism in the newborn rabbit.

A number of drugs that are metabolized through the action of enzymes present in liver microsomes in the adult rabbit are not metabolized in livers of newborn rabbits. The development of metabolic pathways during a period of 4 weeks is presented. Evidence is given for the presence in livers of baby rabbits of inhibitors of some of these drug-enzyme systems.

Animals↗
PubMed2006

Mitochondrial retrograde signaling.

Mitochondrial retrograde signaling is a pathway of communication from mitochondria to the nucleus under normal and pathophysiological conditions. The best understood of such pathways is retrograde signaling in the budding yeast Saccharomyces cerevisiae. It involves multiple factors that sense and transmit mitochondrial signals to effect changes in nuclear gene expression; these changes lead to a reconfiguration of metabolism to accommodate cells to defects in mitochondria. Analysis of regulatory factors has provided us with a mechanistic view of regulation of retrograde signaling. Here we review advances in the yeast retrograde signaling pathway and highlight its regulatory factors and regulatory mechanisms, its physiological functions, and its connection to nutrient sensing, TOR signaling, and aging.

Cell Nucleus↗
PubMed2025

Metabolic network reconstruction as a resource for analyzing Salmonella Typhimurium SL1344 growth in the mouse intestine.

Nontyphoidal Salmonella strains (NTS) are among the most common foodborne enteropathogens and constitute a major cause of global morbidity and mortality, imposing a substantial burden on global health. The increasing antibiotic resistance of NTS bacteria has attracted a lot of research on understanding their modus operandi during infection. Growth in the gut lumen is a critical phase of the NTS infection. This might offer opportunities for intervention. However, the metabolic richness of the gut lumen environment and the inherent complexity and robustness of the metabolism of NTS bacteria call for modeling approaches to guide research efforts. In this study, we reconstructed a thermodynamically constrained and context-specific genome-scale metabolic model (GEM) for S. Typhimurium SL1344, a model strain well-studied in infection research. We combined sequence annotation, optimization methods and in vitro and in vivo experimental data. We used GEM to explore the nutritional requirements, the growth limiting metabolic genes, and the metabolic pathway usage of NTS bacteria in a rich environment simulating the murine gut. This work provides insight and hypotheses on the biochemical capabilities and requirements of SL1344 beyond the knowledge acquired through conventional sequence annotation and can inform future research aimed at better understanding NTS metabolism and identifying potential targets for infection prevention.

Salmonella typhimurium↗
PubMed2006

Monte Carlo sampling and principal component analysis of flux distributions yield topological and modular information on metabolic networks.

The work presented here uses Monte Carlo random sampling combined with flux balance analysis and linear programming to analyse the steady-state flux distributions on the surface of the glucose-ammonia phenotypic phase plane of an Escherichia coli system grown on glucose-minimal medium. The distribution of allowable glucose and ammonia uptake rates showed a triangular shape, the apex corresponding to maximum growth rate. The exact shape, e.g. the diagonal boundary is determined by the relative amounts of nutrients required for growth. The logarithm of flux values has a normal distribution, e.g. there is a log normal distribution, and most of the reactions have an order of magnitude between 10(-1) and 1. The increase in the number of blocked reactions as growth switched from aerobic to micro-aerobic phase and the presence of alternate networks for a single optimal solution were both reflections of the variability of pathway utilization for survival and growth. Principal component analysis (PCA) provided us with significant clues on the correlations between individual reactions and correlations between sets of reactions. Furthermore, PCA identified the most influential reactions of the system. The PCA score plots clearly distinguish two different growth phases, micro-aerobic and aerobic. The loading plots for each growth phase showed both the impact of the reactions on the model and the clustering of reactions that are highly correlated. These results have proved that PCA is a promising way to analyse correlations in high-dimensional solution spaces and to detect modular patterns among reactions in a network.

Ammonia↗