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Ohno, Satoshi, Saori Uematsu i Shinya Kuroda. "Quantitative metabolic fluxes regulated by trans-omic networks". Biochemical Journal 479, nr 6 (31.03.2022): 787–804. http://dx.doi.org/10.1042/bcj20210596.
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Cells change their metabolism in response to internal and external conditions by regulating the trans-omic network, which is a global biochemical network with multiple omic layers. Metabolic flux is a direct measure of the activity of a metabolic reaction that provides valuable information for understanding complex trans-omic networks. Over the past decades, techniques to determine metabolic fluxes, including 13C-metabolic flux analysis (13C-MFA), flux balance analysis (FBA), and kinetic modeling, have been developed. Recent studies that acquire quantitative metabolic flux and multi-omic data have greatly advanced the quantitative understanding and prediction of metabolism-centric trans-omic networks. In this review, we present an overview of 13C-MFA, FBA, and kinetic modeling as the main techniques to determine quantitative metabolic fluxes, and discuss their advantages and disadvantages. We also introduce case studies with the aim of understanding complex metabolism-centric trans-omic networks based on the determination of metabolic fluxes.
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Schramm, Thorben, i Hannes Link. "Von der Stöchiometrie zur Kontrolle metabolischer Netzwerke". BIOspektrum 27, nr 1 (luty 2021): 34–36. http://dx.doi.org/10.1007/s12268-021-1538-0.
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AbstractCellular metabolism is very complex and extensively regulated. For many organisms we know almost the complete set of biochemical reactions in their metabolic network. However, it is not well understood how these reactions are regulated and how they interact in order to enable cellular functions. In this review, we describe recent methodological advances to study metabolic networks with a focus on bacterial metabolism.
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Davis, Jacob D., i Eberhard O. Voit. "Metrics for regulated biochemical pathway systems". Bioinformatics 35, nr 12 (14.11.2018): 2118–24. http://dx.doi.org/10.1093/bioinformatics/bty942.
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Abstract Motivation The assessment of graphs through crisp numerical metrics has long been a hallmark of biological network analysis. However, typical graph metrics ignore regulatory signals that are crucially important for optimal pathway operation, for instance, in biochemical or metabolic studies. Here we introduce adjusted metrics that are applicable to both static networks and dynamic systems. Results The metrics permit quantitative characterizations of the importance of regulation in biochemical pathway systems, including systems designed for applications in synthetic biology or metabolic engineering. They may also become criteria for effective model reduction. Availability and implementation The source code is available at https://gitlab.com/tienbien44/metrics-bsa
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Mosca, Ettore, Matteo Barcella, Roberta Alfieri, Annamaria Bevilacqua, Gianfranco Canti i Luciano Milanesi. "Systems biology of the metabolic network regulated by the Akt pathway". Biotechnology Advances 30, nr 1 (styczeń 2012): 131–41. http://dx.doi.org/10.1016/j.biotechadv.2011.08.004.
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Peplow, Andrew W., Andrew G. Tag, Gulnara F. Garifullina i Marian N. Beremand. "Identification of New Genes Positively Regulated by Tri10 and a Regulatory Network for Trichothecene Mycotoxin Production". Applied and Environmental Microbiology 69, nr 5 (maj 2003): 2731–36. http://dx.doi.org/10.1128/aem.69.5.2731-2736.2003.
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ABSTRACT Tri10, a regulatory gene in trichothecene mycotoxin-producing Fusarium species, is required for trichothecene biosynthesis and the coordinated expression of four trichothecene pathway-specific genes (Tri4, Tri5, Tri6, and Tri101) and the isoprenoid biosynthetic gene for farnesyl pyrophosphate synthetase (FPPS). We showed that six more trichothecene genes (Tri3, Tri7, Tri8, Tri9, Tri11, and Tri12) are regulated by Tri10. We also constructed a cDNA library from a strain of Fusarium sporotrichioides that overexpresses Tri10 (↑Tri10) and used cDNA derived from the ↑Tri10 strain and a non-Tri10-expressing strain (ΔTri10) to differentially screen macroarrays prepared from the cDNA library. This screen identified 15 additional Tri10-regulated transcripts. Four of these transcripts represent Tri1, Tri13, and Tri14 and a gene designated Tri15. Three other sequences are putative orthologs of genes for isoprenoid biosynthesis, the primary metabolic pathway preceding trichothecene biosynthesis. The remaining eight sequences have been designated Ibt (influenced by Tri10) genes. Of the 26 transcripts now known to be positively regulated by Tri10, 22 are positively coregulated by Tri6, a gene that encodes a previously characterized trichothecene pathway-specific transcription factor. These 22 Tri10- and Tri6-coregulated sequences include all of the known Tri genes (except for Tri10), the FPPS gene, and the other three putative isoprenoid biosynthetic genes. Tri6 also regulates a transcript that is not regulated by Tri10. Thus, Tri10 and Tri6 regulate overlapping sets of genes that include a common group of multiple genes for both primary and secondary metabolism.
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Heo, Ji-Won, i Sung-Eun Kim. "Comparative Transcriptomic Profiling of Organs Associated With Metabolic Dysfunction in Cancer-Induced Cachexia". Current Developments in Nutrition 5, Supplement_2 (czerwiec 2021): 501. http://dx.doi.org/10.1093/cdn/nzab041_016.
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Abstract Objectives Approximately 50–80% of cancer patients suffer from cachexia represented by weight loss mainly due to loss of skeletal muscle. Cancer-induced cachexia is a complex metabolic syndrome associated with not only systemic inflammation but also perturbations to energy metabolism. In this study, we profiled gene expression patterns of different organs in CT-26 tumor bearing mice in order to understand metabolic dysfunction in cancer cachexia. Methods The transcriptomic profiles of skeletal muscle, adipose tissue, and liver of CT26-tumor bearing mice were generated using SurePrint G3 Mouse Gene Expression 8 × 60 K v2 (Agilent, Inc.). Functional and network analyses were performed using Gene Set Enrichment Analysis and Ingenuity Pathway Analysis (QIAGEN). Results We identified 299, 508, and 1,311 genes differentially regulated in skeletal muscle, adipose tissue, and liver, respectively. In the skeletal muscle, lipid biosynthetic process and mitochondrial electron transport were negatively regulated and network involved in glutamine metabolism was up-regulated. In adipose tissue, tricarboxylic acid cycle was down-regulated and lipid metabolism was associated with several genes including Thrsp, Plvap, and Sphk1. In the liver, regulation of gluconeogenesis was down-regulated, while production of lactic acid and uptake of D-glucose were related with H6pd and Pkm whose expression was up-regulated during cancer cachexia. Furthermore, the top network matched by genes commonly up-regulated in all organs included Bcl3, Csf2rb, Fcgr2a, and Lilrb3, which are known to be associated with inflammation and muscle wasting. Conclusions Our data suggest that skeletal muscle, adipose tissue, and liver present distinct gene expression profiles associated with inflammation and energy metabolism and several genes up-regulated in all organs might be candidate biomarkers for the prevention and early detection of cancer cachexia. Funding Sources This work was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education.
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Yang, Xiguang, Xiaopeng Duan, Zhenglin Xia, Rui Huang, Ke He i Guoan Xiang. "The Regulation Network of Glycerolipid Metabolism as Coregulators of Immunotherapy-Related Myocarditis". Cardiovascular Therapeutics 2023 (21.06.2023): 1–23. http://dx.doi.org/10.1155/2023/8774971.
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Background. To date, immunotherapy for patients with malignant tumors has shown a significant association with myocarditis. However, the mechanism of metabolic reprogramming changes for immunotherapy-related cardiotoxicity is still not well understood. Methods. The CD45+ single-cell RNA sequencing (scRNA-seq) of the Pdcd1-/-Ctla4+/- and wild-type mouse heart in GSE213486 was downloaded to demonstrate the heterogeneity of immunocyte atlas in immunotherapy-related myocarditis. The liquid chromatography–tandem mass spectrometry (LC-MS/MS) spectrum metabolomics analysis detects the metabolic network differences. The drug prediction, organelle level interaction, mitochondrial level regulatory network, and phosphorylation site prediction for key regulators have also been screened via multibioinformatics analysis methods. Results. The scRNA analysis shows that the T cell is the main regulatory cell subpopulation in the pathological progress of immunotherapy-related myocarditis. Mitochondrial regulation pathway significantly participated in pseudotime trajectory- (PTT-) related differential expressed genes (DEGs) in the T cell subpopulation. Additionally, both the gene set enrichment analysis (GSEA) of PTT-related DEGs and LC-MS/MS metabolomics analysis showed that mitochondrial-regulated glycerolipid metabolism plays a central role in metabolic reprogramming changes for immunotherapy-related cardiotoxicity. Finally, the hub-regulated protease of diacylglycerol kinase zeta (Dgkz) was significantly identified and widely played various roles in glycerolipid metabolism, oxidative phosphorylation, and lipid kinase activation. Conclusion. Mitochondrial-regulated glycerolipid metabolism, especially the DGKZ protein, plays a key role in the metabolic reprogramming of immunotherapy-related myocarditis.
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Ramana, Chilakamarti V. "Regulation of a Metabolic Gene Signature in Response to Respiratory Viruses and Type I Interferon Signaling". Journal of Molecular Pathology 5, nr 1 (7.03.2024): 133–52. http://dx.doi.org/10.3390/jmp5010009.
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Respiratory viruses are the causative agents responsible for seasonal epidemics and occasional pandemic outbreaks and are a leading cause of death worldwide. Type I interferon (IFNα/β) signaling in the lung epithelial cells plays a major role in the innate immunity to respiratory viruses. Gene signatures are a set of differentially expressed genes in a particular disease or condition and are used to diagnose, monitor, and predict disease progression. These signatures can be used to identify regulatory modules and gene regulatory networks (GRNs) in mammalian signal transduction pathways. Considerable progress has been made in the identification of type I interferon-regulated gene signatures in the host response to respiratory viruses, including antiviral, immunomodulatory, apoptosis, and transcription factor signatures. Respiratory virus infections and host defenses require a dramatic change in the metabolic flux of macromolecules involved in nucleotide, lipid, and protein metabolism. The profiling of IFN-stimulated metabolic genes induced in the host response to several respiratory viruses led to the identification of a common gene signature in human lung epithelial cells and in the lungs of mouse models of respiratory virus infection. The regulation of the metabolic gene signature was correlated with the induction of IFN-beta (IFN-β) and IFN-inducible transcription factors at the RNA level in lung epithelial cells. Furthermore, the gene signature was also detected in response to bacterial lipopolysaccharide-induced acute lung injury. A protein interaction network analysis revealed that metabolic enzymes interact with IFN-regulated transcription factors and members of the unfolded protein response (UPR) to form a module and potentially regulate type I interferon signaling, constituting a feedback loop. In addition, components of the metabolic gene expression signature were differentially regulated in the lung tissues of COVID-19 patients compared with healthy controls. These results suggest that the metabolic gene signature is a potential therapeutic target for the treatment of respiratory virus infections and inflammatory diseases.
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Lai, Liang-Chuan, Alexander L. Kosorukoff, Patricia V. Burke i Kurt E. Kwast. "Metabolic-State-Dependent Remodeling of the Transcriptome in Response to Anoxia and Subsequent Reoxygenation in Saccharomyces cerevisiae". Eukaryotic Cell 5, nr 9 (wrzesień 2006): 1468–89. http://dx.doi.org/10.1128/ec.00107-06.
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ABSTRACT We conducted a comprehensive genomic analysis of the temporal response of yeast to anaerobiosis (six generations) and subsequent aerobic recovery (≈2 generations) to reveal metabolic-state (galactose versus glucose)-dependent differences in gene network activity and function. Analysis of variance showed that far fewer genes responded (raw P value of ≤10−8) to the O2 shifts in glucose (1,603 genes) than in galactose (2,388 genes). Gene network analysis reveals that this difference is due largely to the failure of “stress”-activated networks controlled by Msn2/4, Fhl1, MCB, SCB, PAC, and RRPE to transiently respond to the shift to anaerobiosis in glucose as they did in galactose. After ≈1 generation of anaerobiosis, the response was similar in both media, beginning with the deactivation of Hap1 and Hap2/3/4/5 networks involved in mitochondrial functions and the concomitant derepression of Rox1-regulated networks for carbohydrate catabolism and redox regulation and ending (≥2 generations) with the activation of Upc2- and Mot3-regulated networks involved in sterol and cell wall homeostasis. The response to reoxygenation was rapid (<5 min) and similar in both media, dominated by Yap1 networks involved in oxidative stress/redox regulation and the concomitant activation of heme-regulated ones. Our analyses revealed extensive networks of genes subject to combinatorial regulation by both heme-dependent (e.g., Hap1, Hap2/3/4/5, Rox1, Mot3, and Upc2) and heme-independent (e.g., Yap1, Skn7, and Puf3) factors under these conditions. We also uncover novel functions for several cis-regulatory sites and trans-acting factors and define functional regulons involved in the physiological acclimatization to changes in oxygen availability.
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Gholizadeh, Maryam, Jamal Fayazi, Yazdan Asgari, Hakimeh Zali i Lars Kaderali. "Reconstruction and Analysis of Cattle Metabolic Networks in Normal and Acidosis Rumen Tissue". Animals 10, nr 3 (11.03.2020): 469. http://dx.doi.org/10.3390/ani10030469.
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The objective of this study was to develop a system-level understanding of acidosis biology. Therefore, the genes expression differences between the normal and acidosis rumen epithelial tissues were first examined using the RNA-seq data in order to understand the molecular mechanisms involved in the disease and then their corresponding metabolic networks constructed. A number of 1074 genes, 978 isoforms, 1049 transcription start sites (TSS), 998 coding DNA sequence (CDS) and 2 promoters were identified being differentially expressed in the rumen tissue between the normal and acidosis samples (p < 0.05). The functional analysis of 627 up-regulated genes revealed their involvement in ion transmembrane transport, filament organization, regulation of cell adhesion, regulation of the actin cytoskeleton, ATP binding, glucose transmembrane transporter activity, carbohydrate binding, growth factor binding and cAMP metabolic process. Additionally, 111 differentially expressed enzymes were identified between the rumen epithelial tissue of the normal and acidosis steers with 46 up-regulated and 65 down-regulated ones in the acidosis group. The pathways and reactions analyses associated with the up-regulated enzymes indicate that most of these enzymes are involved in the fatty acid metabolism, biosynthesis of amino acids, pyruvate and carbon metabolism while most of the down-regulated ones are involved in purine and pyrimidine, vitamin B6 and antibiotics metabolisms. The degree distribution of both metabolic networks follows a power-law one, hence displaying a scale-free property. The top 15 hub metabolites were determined in the acidosis metabolic network with most of them involved in the fatty acid oxidation, VFA biosynthesis, amino acid biogenesis and glutathione metabolism which plays an important role in the stress condition. The limitations of this study were low number of animals and using only epithelial tissue (ventral sac) for RNA-seq.
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Kang, Qi, Mengyi Hu, Jianxin Jia, Xuanxuan Bai, Chengdong Liu, Zhiqiang Wu, Wenbiao Chen i Mingyu Li. "Global Transcriptomic Analysis of Zebrafish Glucagon Receptor Mutant Reveals Its Regulated Metabolic Network". International Journal of Molecular Sciences 21, nr 3 (22.01.2020): 724. http://dx.doi.org/10.3390/ijms21030724.
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The glucagon receptor (GCGR) is a G-protein-coupled receptor (GPCR) that mediates the activity of glucagon. Disruption of GCGR results in many metabolic alterations, including increased glucose tolerance, decreased adiposity, hypoglycemia, and pancreatic α-cell hyperplasia. To better understand the global transcriptomic changes resulting from GCGR deficiency, we performed whole-organism RNA sequencing analysis in wild type and gcgr-deficient zebrafish. We found that the expression of 1645 genes changes more than two-fold among mutants. Most of these genes are related to metabolism of carbohydrates, lipids, and amino acids. Genes related to fatty acid β-oxidation, amino acid catabolism, and ureagenesis are often downregulated. Among gcrgr-deficient zebrafish, we experimentally confirmed increases in lipid accumulation in the liver and whole-body glucose uptake, as well as a modest decrease in total amino acid content. These results provide new information about the global metabolic network that GCGR signaling regulates in addition to a better understanding of the receptor’s physiological functions.
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Huberman, Lori B., Vincent W. Wu, David J. Kowbel, Juna Lee, Chris Daum, Igor V. Grigoriev, Ronan C. O’Malley i N. Louise Glass. "DNA affinity purification sequencing and transcriptional profiling reveal new aspects of nitrogen regulation in a filamentous fungus". Proceedings of the National Academy of Sciences 118, nr 13 (22.03.2021): e2009501118. http://dx.doi.org/10.1073/pnas.2009501118.
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Sensing available nutrients and efficiently utilizing them is a challenge common to all organisms. The model filamentous fungus Neurospora crassa is capable of utilizing a variety of inorganic and organic nitrogen sources. Nitrogen utilization in N. crassa is regulated by a network of pathway-specific transcription factors that activate genes necessary to utilize specific nitrogen sources in combination with nitrogen catabolite repression regulatory proteins. We identified an uncharacterized pathway-specific transcription factor, amn-1, that is required for utilization of the nonpreferred nitrogen sources proline, branched-chain amino acids, and aromatic amino acids. AMN-1 also plays a role in regulating genes involved in responding to the simple sugar mannose, suggesting an integration of nitrogen and carbon metabolism. The utilization of nonpreferred nitrogen sources, which require metabolic processing before being used as a nitrogen source, is also regulated by the nitrogen catabolite regulator NIT-2. Using RNA sequencing combined with DNA affinity purification sequencing, we performed a survey of the role of NIT-2 and the pathway-specific transcription factors NIT-4 and AMN-1 in directly regulating genes involved in nitrogen utilization. Although previous studies suggested promoter binding by both a pathway-specific transcription factor and NIT-2 may be necessary for activation of nitrogen-responsive genes, our data show that pathway-specific transcription factors regulate genes involved in the catabolism of specific nitrogen sources, while NIT-2 regulates genes involved in utilization of all nonpreferred nitrogen sources, such as nitrogen transporters. Together, these transcription factors form a nutrient sensing network that allows N. crassa cells to regulate nitrogen utilization.
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Obata, Toshihiro, Peter Geigenberger i Alisdair R. Fernie. "Redox control of plant energy metabolism: The complex intertwined regulation of redox and metabolism in plant cells". Biochemist 37, nr 1 (1.02.2015): 14–18. http://dx.doi.org/10.1042/bio03701014.
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Maintenance of the cellular redox status is crucial both to keep metabolic processes running and to prevent oxidation of cellular components by reactive oxygen species under fluctuating environments. The plastid is a plant-specific organelle in which considerable redox-active reactions occur and therefore the redox status in this energy organelle, as well as that of the mitochondria, must be tightly regulated. Plants employ multiple mechanisms to actively regulate energy metabolism in response to the redox status and to integrate subcellular redox signals to orchestrate redox status at the cellular level. In this article, we describe the redox regulation of the major flux bearing reactions in these two energy organelles and survey recent advances concerning interorganellar redox communication. The sum action of this complex regulatory network allows both the fine-tuning of metabolic activities for cellular redox homoeostasis and that of redox to allow optimal metabolic function.
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Kharadi, Roshni R., Kayla Selbmann i George W. Sundin. "A complete twelve-gene deletion null mutant reveals that cyclic di-GMP is a global regulator of phase-transition and host colonization in Erwinia amylovora". PLOS Pathogens 18, nr 8 (1.08.2022): e1010737. http://dx.doi.org/10.1371/journal.ppat.1010737.
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Cyclic-di-GMP (c-di-GMP) is an essential bacterial second messenger that regulates biofilm formation and pathogenicity. To study the global regulatory effect of individual components of the c-di-GMP metabolic system, we deleted all 12 diguanylate cyclase (dgc) and phosphodiesterase (pde)-encoding genes in E. amylovora Ea1189 (Ea1189Δ12). Ea1189Δ12 was impaired in surface attachment due to a transcriptional dysregulation of the type IV pilus and the flagellar filament. A transcriptomic analysis of surface-exposed WT Ea1189 and Ea1189Δ12 cells indicated that genes involved in metabolism, appendage generation and global transcriptional/post-transcriptional regulation were differentially regulated in Ea1189Δ12. Biofilm formation was regulated by all 5 Dgcs, whereas type III secretion and disease development were differentially regulated by specific Dgcs. A comparative transcriptomic analysis of Ea1189Δ8 (lacks all five enzymatically active dgc and 3 pde genes) against Ea1189Δ8 expressing specific dgcs, revealed the presence of a dual modality of spatial and global regulatory frameworks in the c-di-GMP signaling network.
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Yang, S. H., C. S. He, C. H. Li i G. Q. Liu. "RNA-Seq Reveals Differentially Expressed Genes and Pathways Affecting Intramuscular Fat Metabolism in Huangshan Black Chicken Population". Journal of Agricultural Science 12, nr 3 (15.02.2020): 117. http://dx.doi.org/10.5539/jas.v12n3p117.
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Intramuscular fat (IMF) plays an important role in meat quality due to its positive correlation with juiciness, tenderness, and flavor. However, for chickens, the molecular mechanisms underlying IMF deposition in thigh muscle have not yet been determined. Here, to identify candidate genes and signaling pathways related to IMF deposition, we deeply explored the chicken transcriptome from thigh muscles of Huangshan Black Chickens with extremely high and low phenotypic values for intramuscular fat content. A total of 128 genes differentially expressed genes (DEGs) were detected, of which 94 were up-regulated and 34 were down-regulated. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways revealed these DEGs (including FABP4, G0S2, PLIN1, SCD1, LFABP, SLC1A6, SLC45A3, ACSBG1, LY86, ST8SIA5, SNAI2, HPGD, EDN2, and THRSP) were significantly enriched in lipid biosynthetic process, steroid biosynthetic and metabolic process, fatty acid metabolic process, and regulation of unsaturated fatty acid metabolic pathways. Additionally, we concluded an interaction network related to lipid metabolism, which might be contributed to the IMF deposition in chicken. Overall, we proposed some new candidate genes and interaction networks that can be associated with IMF deposition and used as biomarkers in meat quality improvement.
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Prochownik, Edward V. "Regulation of Normal and Neoplastic Proliferation and Metabolism by the Extended Myc Network". Cells 11, nr 24 (8.12.2022): 3974. http://dx.doi.org/10.3390/cells11243974.
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The Myc Network, comprising a small assemblage of bHLH-ZIP transcription factors, regulates many hundreds to thousands of genes involved in proliferation, energy metabolism, translation and other activities. A structurally and functionally related set of factors known as the Mlx Network also supervises some of these same functions via the regulation of a more limited but overlapping transcriptional repertoire. Target gene co-regulation by these two Networks is the result of their sharing of three members that suppress target gene expression as well as by the ability of both Network’s members to cross-bind one another’s consensus DNA sites. The two Networks also differ in that the Mlx Network’s control over transcription is positively regulated by several glycolytic pathway intermediates and other metabolites. These distinctive properties, functions and tissue expression patterns potentially allow for sensitive control of gene regulation in ways that are differentially responsive to environmental and metabolic cues while allowing for them to be both rapid and of limited duration. This review explores how such control might occur. It further discusses how the actual functional dependencies of the Myc and Mlx Networks rely upon cellular context and how they may differ between normal and neoplastic cells. Finally, consideration is given to how future studies may permit a more refined understanding of the functional interrelationships between the two Networks.
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Basu, Anamika, Anasua Sarkar i Piyali Basak. "Analysis of microRNA Regulated Seed Biology Networks in Arabidopsis". International Journal of Knowledge Discovery in Bioinformatics 4, nr 2 (lipiec 2014): 11–20. http://dx.doi.org/10.4018/ijkdb.2014070102.
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Seed maturation and embryogenesis in plants are crucial event for food production of all human beings. Delayed seed maturation and abnormal embryo formation of food crops degrade the quality and quantity of food grains. By performing comparative gene analysis of different microarray experiments in different stages of embryogenesis in Arabidopsis thaliana, using as model plant, here the authors identified a gene coexpression module in preglobular stage. In this module, different genes have been studied which are over-expressed during embryogenesis related with several KEGG metabolic pathways. Analysing the gene cluster evolved from network we concluded that microRNA regulates gene expression of two genes. One of them NRMP6, a metal ion transporter protein gene and second one SKS8, has copper ion binding activity, are regulated by miR167A/B. Since these two genes are also expressed during embryogenesis of other food crops e.g. rice tomato etc, so the microRNAs regulation on gene expression during embryogenesis can be extrapolated for other economically important seeds.
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Lu, Meng, Francesca W. van Tartwijk, Julie Qiaojin Lin, Wilco Nijenhuis, Pierre Parutto, Marcus Fantham, Charles N. Christensen i in. "The structure and global distribution of the endoplasmic reticulum network are actively regulated by lysosomes". Science Advances 6, nr 51 (grudzień 2020): eabc7209. http://dx.doi.org/10.1126/sciadv.abc7209.
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The endoplasmic reticulum (ER) comprises morphologically and functionally distinct domains: sheets and interconnected tubules. These domains undergo dynamic reshaping in response to changes in the cellular environment. However, the mechanisms behind this rapid remodeling are largely unknown. Here, we report that ER remodeling is actively driven by lysosomes, following lysosome repositioning in response to changes in nutritional status: The anchorage of lysosomes to ER growth tips is critical for ER tubule elongation and connection. We validate this causal link via the chemo- and optogenetically driven repositioning of lysosomes, which leads to both a redistribution of the ER tubules and a change of its global morphology. Therefore, lysosomes sense metabolic change in the cell and regulate ER tubule distribution accordingly. Dysfunction in this mechanism during axonal extension may lead to axonal growth defects. Our results demonstrate a critical role of lysosome-regulated ER dynamics and reshaping in nutrient responses and neuronal development.
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Yun, Hye-Young. "Leucine rich repeat LGI family member 3: Integrative analyses support its prognostic association with pancreatic adenocarcinoma". Medicine 103, nr 8 (23.02.2024): e37183. http://dx.doi.org/10.1097/md.0000000000037183.
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Leucine rich repeat LGI family member 3 (LGI3) is a member of the LGI protein family. Previous studies of our group have reported that LGI3 is expressed in adipose tissue, skin and brain, and serves as a multifunctional cytokine. LGI3 may also be involved in cytokine networks in various cancers. This study aimed to analyze differentially expressed genes in pancreatic adenocarcinoma (PAC) tissues and PAC cohort data in order to evaluate the prognostic role of LGI3. The expression microarray and the PAC cohort data were analyzed by bioinformatic methods for differential expression, protein-protein interactions, functional enrichment and pathway analyses, gene co-expression network analysis, and prognostic association analysis. Results showed that LGI3 expression was significantly reduced in PAC tissues. Nineteen upregulated genes and 31 downregulated genes in PAC tissues were identified as LGI3-regulated genes. Protein-protein interaction network analysis demonstrated that 92% (46/50) of the LGI3-regulated genes that were altered in PACs belonged to a protein-protein interaction network cluster. Functional enrichment and gene co-expression network analyses demonstrated that these genes in the network cluster were associated with various processes including inflammatory and immune responses, metabolic processes, cell differentiation, and angiogenesis. PAC cohort analyses revealed that low expression levels of LGI3 were significantly associated with poor PAC prognosis. Analysis of favorable or unfavorable prognostic gene products in PAC showed that 93 LGI3-regulated genes were differentially associated with PAC prognosis. LGI3 expression was correlated with the tumor-infiltration levels of various immune cells. Taken together, these results suggested that LGI3 may be a potential prognostic marker of PAC.
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Reed, Jordan N., Jiansheng Huang, Yong Li, Lijiang Ma, Dhanush Banka, Martin Wabitsch, Tianfang Wang, Wen Ding, Johan LM Björkegren i Mete Civelek. "Systems genetics analysis of human body fat distribution genes identifies adipocyte processes". Life Science Alliance 7, nr 7 (3.05.2024): e202402603. http://dx.doi.org/10.26508/lsa.202402603.
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Excess abdominal fat is a sexually dimorphic risk factor for cardio-metabolic disease and is approximated by the waist-to-hip ratio adjusted for body mass index (WHRadjBMI). Whereas this trait is highly heritable, few causal genes are known. We aimed to identify novel drivers of WHRadjBMIusing systems genetics. We used two independent cohorts of adipose tissue gene expression and constructed sex- and depot-specific Bayesian networks to model gene-gene interactions from 8,492 genes. Using key driver analysis, we identified genes that, in silico and putatively in vitro, regulate many others. 51–119 key drivers in each network were replicated in both cohorts. In other cell types, 23 of these genes are found in crucial adipocyte pathways: Wnt signaling or mitochondrial function. We overexpressed or down-regulated seven key driver genes in human subcutaneous pre-adipocytes. Key driver genesANAPC2andRSPO1inhibited adipogenesis, whereasPSME3increased adipogenesis.RSPO1increased Wnt signaling activity. In differentiated adipocytes, MIGA1 and UBR1 down-regulation led to mitochondrial dysfunction. These five genes regulate adipocyte function, and we hypothesize that they regulate fat distribution.
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Clavijo-Buriticá, Diana Carolina, Catalina Arévalo-Ferro i Andrés Fernando González Barrios. "A Holistic Approach from Systems Biology Reveals the Direct Influence of the Quorum-Sensing Phenomenon on Pseudomonas aeruginosa Metabolism to Pyoverdine Biosynthesis". Metabolites 13, nr 5 (16.05.2023): 659. http://dx.doi.org/10.3390/metabo13050659.
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Computational modeling and simulation of biological systems have become valuable tools for understanding and predicting cellular performance and phenotype generation. This work aimed to construct, model, and dynamically simulate the virulence factor pyoverdine (PVD) biosynthesis in Pseudomonas aeruginosa through a systemic approach, considering that the metabolic pathway of PVD synthesis is regulated by the quorum-sensing (QS) phenomenon. The methodology comprised three main stages: (i) Construction, modeling, and validation of the QS gene regulatory network that controls PVD synthesis in P. aeruginosa strain PAO1; (ii) construction, curating, and modeling of the metabolic network of P. aeruginosa using the flux balance analysis (FBA) approach; (iii) integration and modeling of these two networks into an integrative model using the dynamic flux balance analysis (DFBA) approximation, followed, finally, by an in vitro validation of the integrated model for PVD synthesis in P. aeruginosa as a function of QS signaling. The QS gene network, constructed using the standard System Biology Markup Language, comprised 114 chemical species and 103 reactions and was modeled as a deterministic system following the kinetic based on mass action law. This model showed that the higher the bacterial growth, the higher the extracellular concentration of QS signal molecules, thus emulating the natural behavior of P. aeruginosa PAO1. The P. aeruginosa metabolic network model was constructed based on the iMO1056 model, the P. aeruginosa PAO1 strain genomic annotation, and the metabolic pathway of PVD synthesis. The metabolic network model included the PVD synthesis, transport, exchange reactions, and the QS signal molecules. This metabolic network model was curated and then modeled under the FBA approximation, using biomass maximization as the objective function (optimization problem, a term borrowed from the engineering field). Next, chemical reactions shared by both network models were chosen to combine them into an integrative model. To this end, the fluxes of these reactions, obtained from the QS network model, were fixed in the metabolic network model as constraints of the optimization problem using the DFBA approximation. Finally, simulations of the integrative model (CCBM1146, comprising 1123 reactions and 880 metabolites) were run using the DFBA approximation to get (i) the flux profile for each reaction, (ii) the bacterial growth profile, (iii) the biomass profile, and (iv) the concentration profiles of metabolites of interest such as glucose, PVD, and QS signal molecules. The CCBM1146 model showed that the QS phenomenon directly influences the P. aeruginosa metabolism to PVD biosynthesis as a function of the change in QS signal intensity. The CCBM1146 model made it possible to characterize and explain the complex and emergent behavior generated by the interactions between the two networks, which would have been impossible to do by studying each system’s individual components or scales separately. This work is the first in silico report of an integrative model comprising the QS gene regulatory network and the metabolic network of P. aeruginosa.
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Feng, Xiaoxu, Shang Liu, Hailiang Cheng, Dongyun Zuo, Youping Zhang, Qiaolian Wang, Limin Lv i Guoli Song. "Weighted Gene Co-Expression Network Analysis Reveals Hub Genes Contributing to Fuzz Development in Gossypium arboreum". Genes 12, nr 5 (17.05.2021): 753. http://dx.doi.org/10.3390/genes12050753.
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Fuzzless mutants are ideal materials to decipher the regulatory network and mechanism underlying fuzz initiation and formation. In this study, we utilized two Gossypium arboreum accessions differing in fuzz characteristics to explore expression pattern differences and discriminate genes involved in fuzz development using RNA sequencing. Gene ontology (GO) analysis was conducted and found that DEGs were mainly enriched in the regulation of transcription, metabolic processes and oxidation–reduction-related processes. Weighted gene co-expression network analysis discerned the MEmagenta module highly associated with a fuzz/fuzzless trait, which included a total of 50 hub genes differentially expressed between two materials. GaFZ, which negatively regulates trichome and fuzz formation, was found involved in MEmagenta cluster1. In addition, twenty-eight hub genes in MEmagenta cluster1 were significantly up-regulated and expressed in fuzzless mutant DPL972. It is noteworthy that Ga04G1219 and Ga04G1240, which, respectively, encode Fasciclin-like arabinogalactan protein 18(FLA18) and transport protein, showed remarkable differences of expression level and implied that they may be involved in protein glycosylation to regulate fuzz formation and development. This module and hub genes identified in this study will provide new insights on fiber and fuzz formation and be useful for the molecular design breeding of cotton genetic improvement.
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Morita, Masahiro, Nadeem Siddiqui, Sakie Katsumura, Christopher Rouya, Ola Larsson, Takeshi Nagashima, Bahareh Hekmatnejad i in. "Hepatic posttranscriptional network comprised of CCR4–NOT deadenylase and FGF21 maintains systemic metabolic homeostasis". Proceedings of the National Academy of Sciences 116, nr 16 (29.03.2019): 7973–81. http://dx.doi.org/10.1073/pnas.1816023116.
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Whole-body metabolic homeostasis is tightly controlled by hormone-like factors with systemic or paracrine effects that are derived from nonendocrine organs, including adipose tissue (adipokines) and liver (hepatokines). Fibroblast growth factor 21 (FGF21) is a hormone-like protein, which is emerging as a major regulator of whole-body metabolism and has therapeutic potential for treating metabolic syndrome. However, the mechanisms that control FGF21 levels are not fully understood. Herein, we demonstrate that FGF21 production in the liver is regulated via a posttranscriptional network consisting of the CCR4–NOT deadenylase complex and RNA-binding protein tristetraprolin (TTP). In response to nutrient uptake, CCR4–NOT cooperates with TTP to degrade AU-rich mRNAs that encode pivotal metabolic regulators, including FGF21. Disruption of CCR4–NOT activity in the liver, by deletion of the catalytic subunit CNOT6L, increases serum FGF21 levels, which ameliorates diet-induced metabolic disorders and enhances energy expenditure without disrupting bone homeostasis. Taken together, our study describes a hepatic CCR4–NOT/FGF21 axis as a hitherto unrecognized systemic regulator of metabolism and suggests that hepatic CCR4–NOT may serve as a target for devising therapeutic strategies in metabolic syndrome and related morbidities.
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Ivanova, Anna A., Jon C. Rees, Bryan A. Parks, Michael Andrews, Michael Gardner, Eunice Grigorutsa, Zsuzsanna Kuklenyik, James L. Pirkle i John R. Barr. "Integrated Quantitative Targeted Lipidomics and Proteomics Reveal Unique Fingerprints of Multiple Metabolic Conditions". Biomolecules 12, nr 10 (8.10.2022): 1439. http://dx.doi.org/10.3390/biom12101439.
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Aberrations in lipid and lipoprotein metabolic pathways can lead to numerous diseases, including cardiovascular disease, diabetes, neurological disorders, and cancer. The integration of quantitative lipid and lipoprotein profiling of human plasma may provide a powerful approach to inform early disease diagnosis and prevention. In this study, we leveraged data-driven quantitative targeted lipidomics and proteomics to identify specific molecular changes associated with different metabolic risk categories, including hyperlipidemic, hypercholesterolemic, hypertriglyceridemic, hyperglycemic, and normolipidemic conditions. Based on the quantitative characterization of serum samples from 146 individuals, we have determined individual lipid species and proteins that were significantly up- or down-regulated relative to the normolipidemic group. Then, we established protein–lipid topological networks for each metabolic category and linked dysregulated proteins and lipids with defined metabolic pathways. To evaluate the differentiating power of integrated lipidomics and proteomics data, we have built an artificial neural network model that simultaneously and accurately categorized the samples from each metabolic risk category based on the determined lipidomics and proteomics profiles. Together, our findings provide new insights into molecular changes associated with metabolic risk conditions, suggest new condition-specific associations between apolipoproteins and lipids, and may inform new biomarker discovery in lipid metabolism-associated disorders.
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Lee, Yu-Gyeong, Ji-in Yoon, Yoo-ree Kang i Mi-kyung Sung. "Sex Differences in Diet-induced Obesity: Identification of Key Genes in Association With Phenotypes". Current Developments in Nutrition 6, Supplement_1 (czerwiec 2022): 1117. http://dx.doi.org/10.1093/cdn/nzac078.011.
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Abstract Objectives Obesity is associated with many metabolic disorders requiring personalized management. In this study, we examined sex-dependent metabolic changes in diet-induced fat accumulation and tissue-specific transcriptomics to identify responsible genes. Estrogen-dependency was also evaluated. Methods Male, female and ovariectomized female C57BL/6J mice fed with high fat diet were maintained for 10wks. At sacrifice, body weight, tissue weight, fasting blood glucose and insulin, leptin and adiponectin were measured. Adipose tissue histology and the quantification of major proteins involved in fat synthesis and oxidation were carried out. Key genes in major tissues were identified based on microarray analyses followed by network analyses using protein-protein network and STRING programs. Results Female animals showed significantly lower body weight, adipocyte size, and the macrophage infiltration in white adipose tissue, which are increased by ovariectomy. Not like leptin, adiponectin concentration is significantly higher in female animals, which is maintained even after the ovariectomy. The expressions of proteins related to the regulation of lipid metabolism in adipose tissue show sex differences with or without estrogen depletion. Microarray analyses reveal that ovariectomized female group-specific genes up-regulated in fat, liver and muscle tissue are 251,148, and 49 in numbers, respectively. The number of down-regulated genes are 329, 86, and 37, respectively. PPI network analysis identified Cxcr3, Il2ra, Il2rg, Lck, and Ccl5 as top five up-regulated genes showing highest interaction score, while Cyc1, Uqcrc1, Atp5d, Ndufa9, and Ndufs8 are down-regulated with highest scores. Similarly, the top 5 genes up-regulated in liver tissue are Emr1, Itgb2, Igsf6, Clec4a3, and Aif1, while Eed, Myh11, and Tjp2 are down-regulated with highest scores. Cd4, Slco2b1, Fbxw11, Tub, Wnt5b, U2af2, and Cd38 are up-regulated and the Egfr is down-regulated with highest score in muscle tissue. Conclusions This study suggests that biochemical alterations in abdominal obesity in females are different from males, and a part of mechanisms are estrogen-independent. Several key genes associated with these changes are suggested. Funding Sources This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT).
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Dong, Lidan, Yanfei Zheng, Dan Liu, Fuhong He, Kaiki Lee, Lingru Li i Qi Wang. "Analyses of Long Noncoding RNA and mRNA Profiles in Subjects with the Phlegm-Dampness Constitution". BioMed Research International 2021 (10.12.2021): 1–14. http://dx.doi.org/10.1155/2021/4896282.
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Background. Constitution in traditional Chinese medicine (TCM) plays a key role in the genesis, development, and prognosis of diseases. Phlegm-dampness constitution (PDC) is one of the nine constitutions in TCM, susceptible to metabolic disorders, which is mainly manifested by profuse phlegm, loose abdomen, and greasy face. Epidemiologic, genomic, and epigenetic studies have been carried out in previous works, confirming that PDC represents a distinctive population with microcosmic changes related to metabolic disorders. However, whether long noncoding RNAs (lncRNAs) play a regulatory role in metabolic disease in subjects with PDC remains largely unknown. We aimed to investigate distinct lncRNA and mRNA expression signatures and lncRNA-mRNA regulatory networks in the phlegm-dampness constitution (PDC). Methods. The peripheral blood mononuclear cells (PBMCs) were isolated from the subjects with PDC ( n = 13 ) and balanced constitution (BC) ( n = 9 ). The profiles of lncRNAs and mRNAs in PBMCs were analyzed using microarray and further validated with RT-qPCR. Subsequently, pathway analysis was performed to investigate the function of differentially expressed mRNAs by using Ingenuity Pathway Analysis (IPA). Results. Results suggested that some mRNAs, which were regulated by the differentially expressed lncRNAs, were mainly enriched in lipid metabolism and immune inflammation-related pathways. This was consistent with the molecular characteristics of previous studies, indicating that the clinical characteristics of metabolic disorders in PDC might be regulated by lncRNAs. Furthermore, by making coexpression network construction as well as cis-regulated target gene analysis, several lncRNA-mRNA pairs with potential regulatory relationships were identified by bioinformatic analyses, including RP11-317J10.2-CA3, RP11-809C18.3-PIP4K2A, LINC0069-RFTN1, TTTY15-ARHGEF9, and AC135048.13-ORAI3. Conclusions. This study first revealed that the expression characteristics of lncRNAs/mRNAs may be potential biomarkers, indicating that the distinctive physical and clinical characteristics of PDC might be partially attributed to the specific expression signatures of lncRNAs/mRNAs.
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Pan, Rongbin, Kok Suen Cheng, Yanjuan Chen, Xingwang Zhu, Wenting Zhao, Changhong Xiao i Yong Chen. "Effects of Gancao Nourish-Yin Decoction on Liver Metabolic Profiles in hTNF-α Transgenic Arthritic Model Mice". Chinese medicine and natural products 02, nr 01 (marzec 2022): e19-e27. http://dx.doi.org/10.1055/s-0042-1747916.
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Abstract Objective Gancao Nourish-Yin Decoction (GNYD) has been applied to clinical rheumatoid arthritis (RA) patients, and it had shown effectiveness not only in disease activity controlling but also in improving patients' physical status. However, its mechanism of function has not been investigated. Metabolic perturbations have been associated with RA, and targeting the metabolic profile is one of the ways to manage the disease. The aim of this study is to observe the effect of GNYD on metabolic changes of human tumor necrosis factor α (hTNF-α) transgenic arthritic model mice. Methods hTNF-α transgenic arthritic model mice were divided into the control group and the GNYD group with six mice in each group. After 8 weeks of treatment, liver tissues of mice in both groups were obtained for liquid chromatography-mass spectrometry analysis. Significantly regulated metabolites by GNYD treatment were first identified, followed by Kyoto Encyclopedia of Genes and Genomes pathway and network analysis. Results A total of 126 metabolites were detected in the liver. Compared with the control group, 17 metabolites in the GNYD group were significantly altered. Specifically, thiamine, gamma-L-glutamyl-L-valine, pantothenic acid, pyridoxal (vitamin B6), succinic acid, uridine 5′-diphospho-glucuronic acid, uridine, allantoic acid, N-acetyl-D-glucosamine, nicotinamide ribotide, and N2, N2-dimethylguanosine were down-regulated by GNYD treatment, whereas isobutyrylglycine, N-acetylcadaverine, N-carbamoyl-L-aspartic acid, L-anserine, creatinine, and cis-4-hydroxy-D-proline were up-regulated. Six metabolic pathways were significantly altered including the alanine, aspartate, and glutamate metabolism; pyrimidine metabolism; thiamine metabolism; amino sugar and nucleotide sugar metabolism; pantothenate and CoA biosynthesis; and citrate cycle. Integrative metabolic network analysis suggested the possibility of GNYD having both positive and negative effects on RA through the suppression of angiogenesis and the promotion of leukocyte extravasation into the synovium, respectively. Conclusions GNYD can modulate the hepatic metabolism of hTNF-α transgenic arthritic model mice. Further optimization of this decoction may lead to better therapeutic effects on RA patients.
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Li, Tianyou, Le Wang, Luting Wu, Yingquan Xie, Mengyun Chang, Dawei Wang, Long Yi, Xiaohui Zhu i Mantian Mi. "Integrated Metabolomics and Network Pharmacology Investigation of Cardioprotective Effects of Myricetin after 1-Week High-Intensity Exercise". Nutrients 15, nr 6 (9.03.2023): 1336. http://dx.doi.org/10.3390/nu15061336.
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Cardiovascular adverse effects caused by high-intensity exercise (HIE) have become a public health problem of widespread concern. The therapeutic effect and metabolic regulation mechanism of myricetin, a phytochemical with potential therapeutic effects, have rarely been studied. In this study, we established mice models of different doses of myricetin intervention with 1 week of HIE after intervention. Cardiac function tests, serology, and pathological examinations were used to evaluate the protective effect of myricetin on the myocardium. The possible therapeutic targets of myricetin were obtained using an integrated analysis of metabolomics and network pharmacology and verified using molecular docking and RT-qPCR experiments. Different concentrations of myricetin improved cardiac function, significantly reduced the levels of myocardial injury markers, alleviated myocardial ultrastructural damage, reduced the area of ischemia/hypoxia, and increased the content of CX43. We obtained the potential targets and regulated metabolic network of myricetin by combined network pharmacology and metabolomics analysis and validated them by molecular docking and RT-PCR. In conclusion, our findings suggest that myricetin exerts anti-cardiac injury effects of HIE through the downregulation of PTGS2 and MAOB and the upregulation of MAP2K1 and EGFR while regulating the complicated myocardial metabolic network.
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Martin, D. Brand, i R. Keira Curtis. "Simplifying metabolic complexity". Biochemical Society Transactions 30, nr 2 (1.04.2002): 25–30. http://dx.doi.org/10.1042/bst0300025.
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A complete description of the regulation of metabolism in even a single cell will be very hard to achieve, enormous and indigestible. However, there are two powerful ways to simplify the complexity. Firstly, related processes and intermediates can be grouped into a small number of modules, and the regulation of the simplified system can be studied. Secondly, control analysis can be used. With these simplifications to illuminate the important regulatory features, even a full description could be made intellectually and experimentally accessible without distorting the essential regulatory features. Modular control analysis is powerful because it can quantify the relative importance of different flows of regulatory information through any metabolic, physiological, signalling or transcriptional network. It can answer global questions about the importance of different pathways mediating any change to a system. It has been used to analyse how cadmium, a poison with multiple effects, changes oxidative phosphorylation in isolated mitochondria, and to quantify the regulation of energy metabolism in hepatocytes. It has been used to measure how energy metabolism is regulated during mitogen stimulation of thymocytes, quantifying the relative importance of different signalling pathways and how each pathway contributes to the activation of energy metabolism. Recently, we have applied modular control analysis to modern DNA micro-array expression profiling to measure the importance of different groups of mRNA transcripts in mediating physiological responses.
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Sakharkar, Meena K., Babita Shashni, Karun Sharma, Sarinder K. Dhillon, Prabhakar R. Ranjekar i Kishore R. Sakharkar. "Therapeutic Implications of Targeting Energy Metabolism in Breast Cancer". PPAR Research 2013 (2013): 1–11. http://dx.doi.org/10.1155/2013/109285.
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PPARs are ligand activated transcription factors. PPARγagonists have been reported as a new and potentially efficacious treatment of inflammation, diabetes, obesity, cancer, AD, and schizophrenia. Since cancer cells show dysregulation of glycolysis they are potentially manageable through changes in metabolic environment. Interestingly, several of the genes involved in maintaining the metabolic environment and the central energy generation pathway are regulated or predicted to be regulated by PPARγ. The use of synthetic PPARγligands as drugs and their recent withdrawal/restricted usage highlight the lack of understanding of the molecular basis of these drugs, their off-target effects, and their network. These data further underscores the complexity of nuclear receptor signalling mechanisms. This paper will discuss the function and role of PPARγin energy metabolism and cancer biology in general and its emergence as a promising therapeutic target in breast cancer.
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Liu, Heyu, Lirong Li, Yuan Fan, Yaping Lu, Changhong Zhu i Wei Xia. "Construction of Potential Gene Expression and Regulation Networks in Prostate Cancer Using Bioinformatics Tools". Oxidative Medicine and Cellular Longevity 2021 (31.08.2021): 1–11. http://dx.doi.org/10.1155/2021/8846951.
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Objective. To identify the key genes involved in prostate cancer and their regulatory network. Methods. The dataset of mRNA/miRNA transcriptome sequencing was downloaded from The Cancer Genome Atlas/the Gene Expression Omnibus database for analysis. The “edgeR” package in the R environment was used to normalize and analyze differentially expressed genes (DEGs) and miRNAs (DEmiRNAs). First, the PANTHER online tool was used to analyze the function enrichment of DEGs. Next, a protein-protein interaction (PPI) network was constructed using STRING and Cytoscape tools. Finally, miRNA-gene regulatory networks were constructed using the miRTarBase. Results. We identified 4339 important DEGs, of which 2145 were upregulated (Up-DEGs) and 2194 were downregulated (Down-DEGs). Functional enrichment analysis showed that the Up-DEGs were related to the immune system and the cell cycle in prostate cancer, whereas the Down-DEGs were related to the nucleic acid metabolic process and metabolism pathways. Twelve core protein clusters were found in the PPI network. Further, the constructed miRNA-gene interaction network showed that 11 downregulated miRNAs regulated 16 Up-DEGs and 22 upregulated miRNAs regulated 22 Down-DEGs. Conclusion. We identified 4339 genes and 70 miRNAs that may be involved in immune response, cell cycle, and other key pathways of the prostate cancer regulatory network. Genes such as BUB1B, ANX1A1, F5, HTR4, and MUC4 can be used as biomarkers to assist in the diagnosis and prognosis of prostate cancer.
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Namani, Ravi, Ghassan S. Kassab i Yoram Lanir. "Integrative model of coronary flow in anatomically based vasculature under myogenic, shear, and metabolic regulation". Journal of General Physiology 150, nr 1 (1.12.2017): 145–68. http://dx.doi.org/10.1085/jgp.201711795.
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Coronary blood flow is regulated to match the oxygen demand of myocytes in the heart wall. Flow regulation is essential to meet the wide range of cardiac workload. The blood flows through a complex coronary vasculature of elastic vessels having nonlinear wall properties, under transmural heterogeneous myocardial extravascular loading. To date, there is no fully integrative flow analysis that incorporates global and local passive and flow control determinants. Here, we provide an integrative model of coronary flow regulation that considers the realistic asymmetric morphology of the coronary network, the dynamic myocardial loading on the vessels embedded in it, and the combined effects of local myogenic effect, local shear regulation, and conducted metabolic control driven by venous O2 saturation level. The model predicts autoregulation (approximately constant flow over a wide range of coronary perfusion pressures), reduced heterogeneity of regulated flow, and presence of flow reserve, in agreement with experimental observations. Furthermore, the model shows that the metabolic and myogenic regulations play a primary role, whereas shear has a secondary one. Regulation was found to have a significant effect on the flow except under extreme (high and low) inlet pressures and metabolic demand. Novel outcomes of the model are that cyclic myocardial loading on coronary vessels enhances the coronary flow reserve except under low inlet perfusion pressure, increases the pressure range of effective autoregulation, and reduces the network flow in the absence of metabolic regulation. Collectively, these findings demonstrate the utility of the present biophysical model, which can be used to unravel the underlying mechanisms of coronary physiopathology.
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Tang, Hong-Wen, Yanhui Hu, Chiao-Lin Chen, Baolong Xia, Jonathan Zirin, Min Yuan, John M. Asara, Leonard Rabinow i Norbert Perrimon. "The TORC1-Regulated CPA Complex Rewires an RNA Processing Network to Drive Autophagy and Metabolic Reprogramming". Cell Metabolism 27, nr 5 (maj 2018): 1040–54. http://dx.doi.org/10.1016/j.cmet.2018.02.023.
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Taub, Mary. "Salt Inducible Kinase Signaling Networks: Implications for Acute Kidney Injury and Therapeutic Potential". International Journal of Molecular Sciences 20, nr 13 (30.06.2019): 3219. http://dx.doi.org/10.3390/ijms20133219.
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A number of signal transduction pathways are activated during Acute Kidney Injury (AKI). Of particular interest is the Salt Inducible Kinase (SIK) signaling network, and its effects on the Renal Proximal Tubule (RPT), one of the primary targets of injury in AKI. The SIK1 network is activated in the RPT following an increase in intracellular Na+ (Na+in), resulting in an increase in Na,K-ATPase activity, in addition to the phosphorylation of Class IIa Histone Deacetylases (HDACs). In addition, activated SIKs repress transcriptional regulation mediated by the interaction between cAMP Regulatory Element Binding Protein (CREB) and CREB Regulated Transcriptional Coactivators (CRTCs). Through their transcriptional effects, members of the SIK family regulate a number of metabolic processes, including such cellular processes regulated during AKI as fatty acid metabolism and mitochondrial biogenesis. SIKs are involved in regulating a number of other cellular events which occur during AKI, including apoptosis, the Epithelial to Mesenchymal Transition (EMT), and cell division. Recently, the different SIK kinase isoforms have emerged as promising drug targets, more than 20 new SIK2 inhibitors and activators having been identified by MALDI-TOF screening assays. Their implementation in the future should prove to be important in such renal disease states as AKI.
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Alur, Varun, Varshita Raju, Basavaraj Vastrad, Chanabasayya Vastrad, Satish Kavatagimath i Shivakumar Kotturshetti. "Bioinformatics Analysis of Next Generation Sequencing Data Identifies Molecular Biomarkers Associated With Type 2 Diabetes Mellitus". Clinical Medicine Insights: Endocrinology and Diabetes 16 (styczeń 2023): 117955142311556. http://dx.doi.org/10.1177/11795514231155635.
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Background: Type 2 diabetes mellitus (T2DM) is the most common metabolic disorder. The aim of the present investigation was to identify gene signature specific to T2DM. Methods: The next generation sequencing (NGS) dataset GSE81608 was retrieved from the gene expression omnibus (GEO) database and analyzed to identify the differentially expressed genes (DEGs) between T2DM and normal controls. Then, Gene Ontology (GO) and pathway enrichment analysis, protein-protein interaction (PPI) network, modules, miRNA (micro RNA)-hub gene regulatory network construction and TF (transcription factor)-hub gene regulatory network construction, and topological analysis were performed. Receiver operating characteristic curve (ROC) analysis was also performed to verify the prognostic value of hub genes. Results: A total of 927 DEGs (461 were up regulated and 466 down regulated genes) were identified in T2DM. GO and REACTOME results showed that DEGs mainly enriched in protein metabolic process, establishment of localization, metabolism of proteins, and metabolism. The top centrality hub genes APP, MYH9, TCTN2, USP7, SYNPO, GRB2, HSP90AB1, UBC, HSPA5, and SQSTM1 were screened out as the critical genes. ROC analysis provides prognostic value of hub genes. Conclusion: The potential crucial genes, especially APP, MYH9, TCTN2, USP7, SYNPO, GRB2, HSP90AB1, UBC, HSPA5, and SQSTM1, might be linked with risk of T2DM. Our study provided novel insights of T2DM into genetics, molecular pathogenesis, and novel therapeutic targets.
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He, Feng, Xiaoli Ru i Tao Wen. "NRF2, a Transcription Factor for Stress Response and Beyond". International Journal of Molecular Sciences 21, nr 13 (6.07.2020): 4777. http://dx.doi.org/10.3390/ijms21134777.
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Nuclear factor erythroid 2-related factor 2 (NRF2) is a transcription factor that regulates the cellular defense against toxic and oxidative insults through the expression of genes involved in oxidative stress response and drug detoxification. NRF2 activation renders cells resistant to chemical carcinogens and inflammatory challenges. In addition to antioxidant responses, NRF2 is involved in many other cellular processes, including metabolism and inflammation, and its functions are beyond the originally envisioned. NRF2 activity is tightly regulated through a complex transcriptional and post-translational network that enables it to orchestrate the cell’s response and adaptation to various pathological stressors for the homeostasis maintenance. Elevated or decreased NRF2 activity by pharmacological and genetic manipulations of NRF2 activation is associated with many metabolism- or inflammation-related diseases. Emerging evidence shows that NRF2 lies at the center of a complex regulatory network and establishes NRF2 as a truly pleiotropic transcription factor. Here we summarize the complex regulatory network of NRF2 activity and its roles in metabolic reprogramming, unfolded protein response, proteostasis, autophagy, mitochondrial biogenesis, inflammation, and immunity.
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Yue, Muxin, Yunsong Liu, Ping Zhang, Zheng Li i Yongsheng Zhou. "Integrative Analysis Reveals the Diverse Effects of 3D Stiffness upon Stem Cell Fate". International Journal of Molecular Sciences 24, nr 11 (26.05.2023): 9311. http://dx.doi.org/10.3390/ijms24119311.
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The origin of life and native tissue development are dependent on the heterogeneity of pluripotent stem cells. Bone marrow mesenchymal stem cells (BMMSCs) are located in a complicated niche with variable matrix stiffnesses, resulting in divergent stem cell fates. However, how stiffness drives stem cell fate remains unknown. For this study, we performed whole-gene transcriptomics and precise untargeted metabolomics sequencing to elucidate the complex interaction network of stem cell transcriptional and metabolic signals in extracellular matrices (ECMs) with different stiffnesses, and we propose a potential mechanism involved in stem cell fate decision. In a stiff (39~45 kPa) ECM, biosynthesis of aminoacyl-tRNA was up-regulated, and increased osteogenesis was also observed. In a soft (7~10 kPa) ECM, biosynthesis of unsaturated fatty acids and deposition of glycosaminoglycans were increased, accompanied by enhanced adipogenic/chondrogenic differentiation of BMMSCs. In addition, a panel of genes responding to the stiffness of the ECM were validated in vitro, mapping out the key signaling network that regulates stem cells’ fate decisions. This finding of “stiffness-dependent manipulation of stem cell fate” provides a novel molecular biological basis for development of potential therapeutic targets within tissue engineering, from both a cellular metabolic and a biomechanical perspective.
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Kokaji, Toshiya, Atsushi Hatano, Yuki Ito, Katsuyuki Yugi, Miki Eto, Keigo Morita, Satoshi Ohno i in. "Transomics analysis reveals allosteric and gene regulation axes for altered hepatic glucose-responsive metabolism in obesity". Science Signaling 13, nr 660 (1.12.2020): eaaz1236. http://dx.doi.org/10.1126/scisignal.aaz1236.
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Impaired glucose tolerance associated with obesity causes postprandial hyperglycemia and can lead to type 2 diabetes. To study the differences in liver metabolism in healthy and obese states, we constructed and analyzed transomics glucose-responsive metabolic networks with layers for metabolites, expression data for metabolic enzyme genes, transcription factors, and insulin signaling proteins from the livers of healthy and obese mice. We integrated multiomics time course data from wild-type and leptin-deficient obese (ob/ob) mice after orally administered glucose. In wild-type mice, metabolic reactions were rapidly regulated within 10 min of oral glucose administration by glucose-responsive metabolites, which functioned as allosteric regulators and substrates of metabolic enzymes, and by Akt-induced changes in the expression of glucose-responsive genes encoding metabolic enzymes. In ob/ob mice, the majority of rapid regulation by glucose-responsive metabolites was absent. Instead, glucose administration produced slow changes in the expression of carbohydrate, lipid, and amino acid metabolic enzyme–encoding genes to alter metabolic reactions on a time scale of hours. Few regulatory events occurred in both healthy and obese mice. Thus, our transomics network analysis revealed that regulation of glucose-responsive liver metabolism is mediated through different mechanisms in healthy and obese states. Rapid changes in allosteric regulators and substrates and in gene expression dominate the healthy state, whereas slow changes in gene expression dominate the obese state.
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Volkova, Svetlana, Marta R. A. Matos, Matthias Mattanovich i Igor Marín de Mas. "Metabolic Modelling as a Framework for Metabolomics Data Integration and Analysis". Metabolites 10, nr 8 (24.07.2020): 303. http://dx.doi.org/10.3390/metabo10080303.
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Metabolic networks are regulated to ensure the dynamic adaptation of biochemical reaction fluxes to maintain cell homeostasis and optimal metabolic fitness in response to endogenous and exogenous perturbations. To this end, metabolism is tightly controlled by dynamic and intricate regulatory mechanisms involving allostery, enzyme abundance and post-translational modifications. The study of the molecular entities involved in these complex mechanisms has been boosted by the advent of high-throughput technologies. The so-called omics enable the quantification of the different molecular entities at different system layers, connecting the genotype with the phenotype. Therefore, the study of the overall behavior of a metabolic network and the omics data integration and analysis must be approached from a holistic perspective. Due to the close relationship between metabolism and cellular phenotype, metabolic modelling has emerged as a valuable tool to decipher the underlying mechanisms governing cell phenotype. Constraint-based modelling and kinetic modelling are among the most widely used methods to study cell metabolism at different scales, ranging from cells to tissues and organisms. These approaches enable integrating metabolomic data, among others, to enhance model predictive capabilities. In this review, we describe the current state of the art in metabolic modelling and discuss future perspectives and current challenges in the field.
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Gujar, Amit D., Son Le, Diane D. Mao, David Y. A. Dadey, Alice Turski, Yo Sasaki, Diane Aum i in. "An NAD+-dependent transcriptional program governs self-renewal and radiation resistance in glioblastoma". Proceedings of the National Academy of Sciences 113, nr 51 (7.12.2016): E8247—E8256. http://dx.doi.org/10.1073/pnas.1610921114.
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Accumulating evidence suggests cancer cells exhibit a dependency on metabolic pathways regulated by nicotinamide adenine dinucleotide (NAD+). Nevertheless, how the regulation of this metabolic cofactor interfaces with signal transduction networks remains poorly understood in glioblastoma. Here, we report nicotinamide phosphoribosyltransferase (NAMPT), the rate-limiting step in NAD+synthesis, is highly expressed in glioblastoma tumors and patient-derived glioblastoma stem-like cells (GSCs). High NAMPT expression in tumors correlates with decreased patient survival. Pharmacological and genetic inhibition of NAMPT decreased NAD+levels and GSC self-renewal capacity, and NAMPT knockdown inhibited the in vivo tumorigenicity of GSCs. Regulatory network analysis of RNA sequencing data using GSCs treated with NAMPT inhibitor identified transcription factor E2F2 as the center of a transcriptional hub in the NAD+-dependent network. Accordingly, we demonstrate E2F2 is required for GSC self-renewal. Downstream, E2F2 drives the transcription of members of the inhibitor of differentiation (ID) helix–loop–helix gene family. Finally, we find NAMPT mediates GSC radiation resistance. The identification of a NAMPT-E2F2-ID axis establishes a link between NAD+metabolism and a self-renewal transcriptional program in glioblastoma, with therapeutic implications for this formidable cancer.
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Piao, Mingxin, Jinpeng Zou, Zhifang Li, Junchuan Zhang, Liang Yang, Nan Yao, Yuhong Li i in. "The Arabidopsis HY2 Gene Acts as a Positive Regulator of NaCl Signaling during Seed Germination". International Journal of Molecular Sciences 22, nr 16 (20.08.2021): 9009. http://dx.doi.org/10.3390/ijms22169009.
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Phytochromobilin (PΦB) participates in the regulation of plant growth and development as an important synthetase of photoreceptor phytochromes (phy). In addition, Arabidopsis long hypocotyl 2 (HY2) appropriately works as a key PΦB synthetase. However, whether HY2 takes part in the plant stress response signal network remains unknown. Here, we described the function of HY2 in NaCl signaling. The hy2 mutant was NaCl-insensitive, whereas HY2-overexpressing lines showed NaCl-hypersensitive phenotypes during seed germination. The exogenous NaCl induced the transcription and the protein level of HY2, which positively mediated the expression of downstream stress-related genes of RD29A, RD29B, and DREB2A. Further quantitative proteomics showed the patterns of 7391 proteins under salt stress. HY2 was then found to specifically mediate 215 differentially regulated proteins (DRPs), which, according to GO enrichment analysis, were mainly involved in ion homeostasis, flavonoid biosynthetic and metabolic pathways, hormone response (SA, JA, ABA, ethylene), the reactive oxygen species (ROS) metabolic pathway, photosynthesis, and detoxification pathways to respond to salt stress. More importantly, ANNAT1–ANNAT2–ANNAT3–ANNAT4 and GSTU19–GSTF10–RPL5A–RPL5B–AT2G32060, two protein interaction networks specifically regulated by HY2, jointly participated in the salt stress response. These results direct the pathway of HY2 participating in salt stress, and provide new insights for the plant to resist salt stress.
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Thomas, Dylan D., Barbara E. Corkey, Nawfal W. Istfan i Caroline M. Apovian. "Hyperinsulinemia: An Early Indicator of Metabolic Dysfunction". Journal of the Endocrine Society 3, nr 9 (24.07.2019): 1727–47. http://dx.doi.org/10.1210/js.2019-00065.
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Abstract Hyperinsulinemia is strongly associated with type 2 diabetes. Racial and ethnic minority populations are disproportionately affected by diabetes and obesity-related complications. This mini-review provides an overview of the genetic and environmental factors associated with hyperinsulinemia with a focus on racial and ethnic differences and its metabolic consequences. The data used in this narrative review were collected through research in PubMed and reference review of relevant retrieved articles. Insulin secretion and clearance are regulated processes that influence the development and progression of hyperinsulinemia. Environmental, genetic, and dietary factors are associated with hyperinsulinemia. Certain pharmacotherapies for obesity and bariatric surgery are effective at mitigating hyperinsulinemia and are associated with improved metabolic health. Hyperinsulinemia is associated with many environmental and genetic factors that interact with a wide network of hormones. Recent studies have advanced our understanding of the factors affecting insulin secretion and clearance. Further basic and translational work on hyperinsulinemia may allow for earlier and more personalized treatments for obesity and metabolic diseases.
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Aoh, Quyen L., Chao-wei Hung i Mara C. Duncan. "Energy metabolism regulates clathrin adaptors at the trans-Golgi network and endosomes". Molecular Biology of the Cell 24, nr 6 (15.03.2013): 832–47. http://dx.doi.org/10.1091/mbc.e12-10-0750.
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Glucose is a master regulator of cell behavior in the yeast Saccharomyces cerevisiae. It acts as both a metabolic substrate and a potent regulator of intracellular signaling cascades. Glucose starvation induces the transient delocalization and then partial relocalization of clathrin adaptors at the trans-Golgi network and endosomes. Although these localization responses are known to depend on the protein kinase A (PKA) signaling pathway, the molecular mechanism of this regulation is unknown. Here we demonstrate that PKA and the AMP-regulated kinase regulate adaptor localization through changes in energy metabolism. We show that genetic and chemical manipulation of intracellular ATP levels cause corresponding changes in adaptor localization. In permeabilized cells, exogenous ATP is sufficient to induce adaptor localization. Furthermore, we reveal distinct energy-dependent steps in adaptor localization: a step that requires the ADP-ribosylation factor ARF, an ATP-dependent step that requires the phosphatidyl-inositol-4 kinase Pik1, and third ATP-dependent step for which we provide evidence but for which the mechanism is unknown. We propose that these energy-dependent mechanisms precisely synchronize membrane traffic with overall proliferation rates and contribute a crucial aspect of energy conservation during acute glucose starvation.
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Huang, Yan, Rong Chen, Shuci Yang, Ye Chen i Xiaoying Lü. "The Mechanism of Interaction Between Gold Nanoparticles and Human Dermal Fibroblasts Based on Integrative Analysis of Transcriptomics and Metabolomics Data". Journal of Biomedical Nanotechnology 18, nr 6 (1.06.2022): 1562–76. http://dx.doi.org/10.1166/jbn.2022.3365.
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The aim of this paper was to combine transcriptomics and metabolomics to analyze the mechanism of gold nanoparticles (GNPs) on human dermal fibroblasts (HDFs). First, 20-nm GNPs were prepared, and the differentially expressed genes in HDFs were subsequently screened by transcriptome sequencing technology after 4, 8, and 24 h of treatment with GNPs. By comparing the metabolic pathways in which the metabolites obtained in a previous study were involved, the pathways involving both genes and metabolites were filtered, and the differentially expressed genes and metabolites with upstream and downstream relationships were screened out. The gene–metabolite–metabolic pathway network was further constructed, and the functions of metabolic pathways, genes and metabolites in the important network were analyzed and experimentally verified. The results of transcriptome sequencing experiments showed that 1904, 1216 and 489 genes were differentially expressed in HDFs after 4, 8 and 24 h of treatment with GNPs, and these genes were involved in 270, 235 and 163 biological pathways, respectively. Through the comparison and analysis of the metabolic pathways affected by the metabolites, 7, 3 and 2 metabolic pathways with genes and metabolites exhibiting upstream and downstream relationships were identified. Through analysis of the gene–metabolite–metabolic pathway network, 4 important metabolic pathways, 9 genes and 7 metabolites were identified. Combined with the results of verification experiments on oxidative stress, apoptosis, the cell cycle, the cytoskeleton and cell adhesion, it was found that GNPs regulated the synthesis of downstream metabolites through upstream genes in important metabolic pathways. GNPs inhibited oxidative stress and thus did not induce significant apoptosis, but they exerted effects on several cellular functions, including arresting the cell cycle and affecting the cytoskeleton and cell adhesion.
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Ramser, Alison, Rachel Hawken, Elizabeth Greene, Ron Okimoto, Brenda Flack, Courtney J. Christopher, Shawn R. Campagna i Sami Dridi. "Bone Metabolite Profile Differs between Normal and Femur Head Necrosis (FHN/BCO)-Affected Broilers: Implications for Dysregulated Metabolic Cascades in FHN Pathophysiology". Metabolites 13, nr 5 (16.05.2023): 662. http://dx.doi.org/10.3390/metabo13050662.
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Femur head necrosis (FHN), also known as bacterial chondronecrosis with osteomyelitis (BCO), has remained an animal welfare and production concern for modern broilers regardless of efforts to select against it in primary breeder flocks. Characterized by the bacterial infection of weak bone, FHN has been found in birds without clinical lameness and remains only detectable via necropsy. This presents an opportunity to utilize untargeted metabolomics to elucidate potential non-invasive biomarkers and key causative pathways involved in FHN pathology. The current study used ultra-performance liquid chromatography coupled with high-resolution mass spectrometry (UPLC–HRMS) and identified a total of 152 metabolites. Mean intensity differences at p < 0.05 were found in 44 metabolites, with 3 significantly down-regulated and 41 up-regulated in FHN-affected bone. Multivariate analysis and a partial least squares discriminant analysis (PLS-DA) scores plot showed the distinct clustering of metabolite profiles from FHN-affected vs. normal bone. Biologically related molecular networks were predicted using an ingenuity pathway analysis (IPA) knowledge base. Using a fold-change cut off of −1.5 and 1.5, top canonical pathways, networks, diseases, molecular functions, and upstream regulators were generated using the 44 differentially abundant metabolites. The results showed the metabolites NAD+, NADP+, and NADH to be downregulated, while 5-Aminoimidazole-4-carboxamide ribonucleotide (AICAR) and histamine were significantly increased in FHN. Ascorbate recycling and purine nucleotides degradation were the top canonical pathways, indicating the potential dysregulation of redox homeostasis and osteogenesis. Lipid metabolism and cellular growth and proliferation were some of the top molecular functions predicted based on the metabolite profile in FHN-affected bone. Network analysis showed significant overlap across metabolites and predicted upstream and downstream complexes, including AMP-activated protein kinase (AMPK), insulin, collagen type IV, mitochondrial complex, c-Jun N-terminal kinase (Jnk), extracellular signal-regulated kinase (ERK), and 3β-hydroxysteroid dehydrogenase (3β HSD). The qPCR analysis of relevant factors showed a significant decrease in AMPKα2 mRNA expression in FHN-affected bone, supporting the predicted downregulation found in the IPA network analysis. Taken as a whole, these results demonstrate a shift in energy production, bone homeostasis, and bone cell differentiation that is distinct in FHN-affected bone, with implications for how metabolites drive the pathology of FHN.
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Markby, Greg Robert, i Kei Sakamoto. "Transcription factor EB and TFE3: new metabolic coordinators mediating adaptive responses to exercise in skeletal muscle?" American Journal of Physiology-Endocrinology and Metabolism 319, nr 4 (1.10.2020): E763—E768. http://dx.doi.org/10.1152/ajpendo.00339.2020.
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In response to the increased energy demands of contractions, skeletal muscle adapts remarkably well through acutely regulating metabolic pathways to maintain energy balance and in the longer term by regulating metabolic reprogramming, such as remodeling and expanding the mitochondrial network. This long-term adaptive response involves modulation of gene expression at least partly through the regulation of specific transcription factors and transcriptional coactivators. The AMPK-peroxisome proliferator-activated receptor γ coactivator 1α (PGC1α) pathway has long been known to orchestrate contraction-mediated adaptive responses, although AMPK- and PGC1α-independent pathways have also been proposed. Transcription factor EB (TFEB) and TFE3, known as important regulators of lysosomal biogenesis and autophagic processes, have emerged as new metabolic coordinators. The activity of TFEB/TFE3 is regulated through posttranslational modifications (i.e., phosphorylation) and spatial organization. Under nutrient and energy stress, TFEB and TFE3 are dephosphorylated and translocate to the nucleus, where they activate transcription of their target genes. It has recently been reported that exercise promotes nuclear translocation and activation of TFEB/TFE3 in mouse skeletal muscle through the Ca2+-stimulated protein phosphatase calcineurin. Skeletal muscle-specific ablation of TFEB exhibits impaired glucose homeostasis and mitochondrial biogenesis with reduced metabolic flexibility during exercise, and global TFE3 depletion results in diminished endurance and abolished exercise-induced metabolic benefits. Transcriptomic analysis of the muscle-specific TFEB-null mice has demonstrated that TFEB regulates the expression of genes involved in glucose metabolism and mitochondrial homeostasis. This review aims to summarize and discuss emerging roles for TFEB/TFE3 in metabolic and adaptive responses to exercise and contractile activity in skeletal muscle.
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Gruszka, Damian. "Crosstalk of the Brassinosteroid Signalosome with Phytohormonal and Stress Signaling Components Maintains a Balance between the Processes of Growth and Stress Tolerance". International Journal of Molecular Sciences 19, nr 9 (9.09.2018): 2675. http://dx.doi.org/10.3390/ijms19092675.
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Brassinosteroids (BRs) are a class of phytohormones, which regulate various processes during plant life cycle. Intensive studies conducted with genetic, physiological and molecular approaches allowed identification of various components participating in the BR signaling—from the ligand perception, through cytoplasmic signal transduction, up to the BR-dependent gene expression, which is regulated by transcription factors and chromatin modifying enzymes. The identification of new components of the BR signaling is an ongoing process, however an emerging view of the BR signalosome indicates that this process is interconnected at various stages with other metabolic pathways. The signaling crosstalk is mediated by the BR signaling proteins, which function as components of the transmembrane BR receptor, by a cytoplasmic kinase playing a role of the major negative regulator of the BR signaling, and by the transcription factors, which regulate the BR-dependent gene expression and form a complicated regulatory system. This molecular network of interdependencies allows a balance in homeostasis of various phytohormones to be maintained. Moreover, the components of the BR signalosome interact with factors regulating plant reactions to environmental cues and stress conditions. This intricate network of interactions enables a rapid adaptation of plant metabolism to constantly changing environmental conditions.
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Feng, Tieshan, Ping Lin, Jiao Gong, Dong Cheng, Xi Yang, Quan Zhang i Tingcai Cheng. "Gene Expression Pattern and Regulatory Network of α-Toxin Treatment in Bombyx mori". International Journal of Genomics 2019 (5.03.2019): 1–11. http://dx.doi.org/10.1155/2019/7859121.
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Bacillus bombyseptieus is a pathogen of Bombyx mori; it can cause bacterial septicemia in silkworm. One of the components of the parasporal crystal toxin of B. bombyseptieus, α-toxin, plays an important role in the process of infection in silkworm. In this study, we investigated the immune response of silkworm induced by α-toxin by using RNA-seq. We compared the changes in gene expression in the midgut, fatbody, and hemocytes of silkworm and in the B. mori embryonic cell line (BmE) after treatment with α-toxin and identified 952 differentially expressed genes and 353 differentially expressed long noncoding RNAs (lncRNAs). These regulated genes in different tissues were found to be enriched in different pathways. The upregulated genes in the midgut were mainly involved in peptidoglycan catabolic process and tyrosine kinase signaling pathway, whereas the downregulated genes were mainly involved in chitin metabolic pathways. The upregulated genes in fatbody were also involved in peptidoglycan catabolic process, but they were for a different peptidoglycan subtype. Further, genes encoding cecropins were enriched in the fatbody. The downregulated genes were mainly involved in the metabolic pathways of fundamental substances such as cellular protein metabolic process and nucleobase-containing compound metabolic process. These results suggest that α-toxin can induce various immune responses in silkworm, and further studies are warranted to understand the mechanism of α-toxin action in silkworm. Further, lncRNAs and differentially expressed genes were correlated using coexpression network analysis. Our findings revealed potential candidate genes and lncRNAs that might play important physiological functions in the immune response to α-toxins in silkworm.
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Kawamura, Genki, Toshiya Kokaji, Kentaro Kawata, Yuka Sekine, Yutaka Suzuki, Tomoyoshi Soga, Yoshibumi Ueda, Mizuki Endo, Shinya Kuroda i Takeaki Ozawa. "Optogenetic decoding of Akt2-regulated metabolic signaling pathways in skeletal muscle cells using transomics analysis". Science Signaling 16, nr 773 (21.02.2023). http://dx.doi.org/10.1126/scisignal.abn0782.
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Insulin regulates various cellular metabolic processes by activating specific isoforms of the Akt family of kinases. Here, we elucidated metabolic pathways that are regulated in an Akt2-dependent manner. We constructed a transomics network by quantifying phosphorylated Akt substrates, metabolites, and transcripts in C2C12 skeletal muscle cells with acute, optogenetically induced activation of Akt2. We found that Akt2-specific activation predominantly affected Akt substrate phosphorylation and metabolite regulation rather than transcript regulation. The transomics network revealed that Akt2 regulated the lower glycolysis pathway and nucleotide metabolism and cooperated with Akt2-independent signaling to promote the rate-limiting steps in these processes, such as the first step of glycolysis, glucose uptake, and the activation of the pyrimidine metabolic enzyme CAD. Together, our findings reveal the mechanism of Akt2-dependent metabolic pathway regulation, paving the way for Akt2-targeting therapeutics in diabetes and metabolic disorders.
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Sugimoto, Hikaru, Keigo Morita, Dongzi Li, Yunfan Bai, Matthias Mattanovich i Shinya Kuroda. "iTraNet: A Web-Based Platform for integrated Trans-Omics Network Visualization and Analysis". Bioinformatics Advances, 30.09.2024. http://dx.doi.org/10.1093/bioadv/vbae141.
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Abstract Motivation Visualization and analysis of biological networks play crucial roles in understanding living systems. Biological networks include diverse types, from gene regulatory networks and protein–protein interactions to metabolic networks. Metabolic networks include substrates, products, and enzymes, which are regulated by allosteric mechanisms and gene expression. However, the analysis of these diverse omics types is challenging due to the diversity of databases and the complexity of network analysis. Results We developed iTraNet, a web application that visualizes and analyzes trans-omics networks involving four types of networks: gene regulatory networks; protein–protein interactions; metabolic networks; and metabolite exchange networks. Using iTraNet, we found that in wild-type mice, hub molecules within the network tended to respond to glucose administration, whereas in ob/ob mice, this tendency disappeared. With its ability to facilitate network analysis, we anticipate that iTraNet will help researchers gain insights into living systems. Availability iTraNet is available at https://itranet.streamlit.app/. Supplementary information Supplementary data are available at Bioinformatics Advances online.