Reporter pathway analysis from transcriptome data: Metabolite-centric versus Reaction-centric approach

Çakır, Tunahan

doi:10.1038/srep14563

Cited by 15 publications

(12 citation statements)

References 60 publications

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“…Further, reporter pathways were also identified by aggregating the score of n metabolites (Eq. 3) of a pathway 19 . We identified the direction of change of reporter pathways by performing the analysis with only upregulated or downregulated genes in each subtype.…”

Section: Methodsmentioning

confidence: 99%

“…The FOXM1 expression level was higher in late stage samples of KIRP and KICH while the E2F 1 expression level was higher in RCC (data not shown). We characterized the metabolic network-based alterations of RCC by mapping the gene expression changes to the reactions in HMR2 and identified reporter metabolites and pathways 18,19 . Figure 2 shows the reporter pathways of KICH, KIRC, and KIRP (Data S1).…”

Section: Reporter Metabolic Pathways In Rcc Subtypes the Differentiamentioning

confidence: 99%

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Network-based metabolic characterization of renal cell carcinoma

Pandey

Lanke

Vinod

2020

Sci Rep

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An emerging hallmark of cancer is metabolic reprogramming, which presents opportunities for cancer diagnosis and treatment based on metabolism. We performed a comprehensive metabolic network analysis of major renal cell carcinoma (Rcc) subtypes including clear cell, papillary and chromophobe by integrating transcriptomic data with the human genome-scale metabolic model to understand the coordination of metabolic pathways in cancer cells. We identified metabolic alterations of each subtype with respect to tumor-adjacent normal samples and compared them to understand the differences between subtypes. We found that genes of amino acid metabolism and redox homeostasis are significantly altered in RCC subtypes. Chromophobe showed metabolic divergence compared to other subtypes with upregulation of genes involved in glutamine anaplerosis and aspartate biosynthesis. A difference in transcriptional regulation involving HIF1A is observed between subtypes. We identified E2F1 and FOXM1 as other major transcriptional activators of metabolic genes in RCC. Further, the co-expression pattern of metabolic genes in each patient showed the variations in metabolism within RCC subtypes. We also found that co-expression modules of each subtype have tumor stage-specific behavior, which may have clinical implications. Major biological processes namely reproduction, development, wound healing and tissue regeneration require cell proliferation. Cells proliferate in response to growth-promoting stimulus however, under adverse conditions they move into a reversible, non-proliferating state termed quiescence. Cells gauge the strength of proliferative and anti-proliferative signals through multiple molecular players to make cellular decisions. Cancer is a proliferative disease that arises when the regulatory control of quiescence-proliferation reversible transition is lost. An emerging hallmark of cancer is metabolic reprogramming, which helps to meet the energy demand for cell growth and division. Initial studies by Otto Warburg pointed to aerobic glycolysis, however recent advances have started to reveal other metabolic alterations and plasticity of cancer metabolism 1,2. Understanding the differences in metabolism between normal and cancer cells can shed light on the adaptations that promote disease progression and may also facilitate the identification of therapeutic metabolic targets. Mutations or epigenetic alterations in cancer can influence the expression of metabolic genes. Studies have explored transcriptome data of different cancers to understand the transcriptional dysregulation of metabolic genes. These studies are based on data generated by The Cancer Genome Atlas (TCGA) program. A pan-cancer analysis of different cancer types found a convergent metabolic landscape with upregulated nucleotide synthesis and downregulated mitochondrial metabolism as the main features 3. Rosario et al. 4 analyzed the gene expression of metabolic pathways in Kyoto Encyclopedia of Genes and Genomes (KEGG) and found that pentose and glucuronate inter...

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Section: Methodsmentioning

confidence: 99%

Section: Reporter Metabolic Pathways In Rcc Subtypes the Differentiamentioning

confidence: 99%

Network-based metabolic characterization of renal cell carcinoma

Pandey

Lanke

Vinod

2020

Sci Rep

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“…It would also be desirable to confirm adequate differentiation by measuring a few metabolites before attempting implantation. The reporter metabolites algorithm (Çakır, 2015;Schultz and Qutub, 2016) applied to a model of well-differentiated MSCs would determine exometabolomic biomarkers that are indicative of successful levels of differentiation.…”

Section: Experimental Cost Reduction Via In Silico Results Predictionmentioning

confidence: 99%

Current Status and Future Prospects of Genome-Scale Metabolic Modeling to Optimize the Use of Mesenchymal Stem Cells in Regenerative Medicine

Sigmarsdóttir

McGarrity

Rolfsson

et al. 2020

Front. Bioeng. Biotechnol.

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Mesenchymal stem cells are a promising source for externally grown tissue replacements and patient-specific immunomodulatory treatments. This promise has not yet been fulfilled in part due to production scaling issues and the need to maintain the correct phenotype after re-implantation. One aspect of extracorporeal growth that may be manipulated to optimize cell growth and differentiation is metabolism. The metabolism of MSCs changes during and in response to differentiation and immunomodulatory changes. MSC metabolism may be linked to functional differences but how this occurs and influences MSC function remains unclear. Understanding how MSC metabolism relates to cell function is however important as metabolite availability and environmental circumstances in the body may affect the success of implantation. Genome-scale constraint based metabolic modeling can be used as a tool to fill gaps in knowledge of MSC metabolism, acting as a framework to integrate and understand various data types (e.g., genomic, transcriptomic and metabolomic). These approaches have long been used to optimize the growth and productivity of bacterial production systems and are being increasingly used to provide insights into human health research. Production of tissue for implantation using MSCs requires both optimized production of cell mass and the understanding of the patient and phenotype specific metabolic situation. This review considers the current knowledge of MSC metabolism and how it may be optimized along with the current and future uses of genome scale constraint based metabolic modeling to further this aim.

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“…Note that the Z pathway score is corrected for the background distribution as calculated in

. Pathways with significant

scores are called reporter pathways (Çakir, 2015 ).…”

Section: Methodsmentioning

confidence: 99%

“…Here we take advantage of an algorithm that maps metabolic gene expression by identifying the most significantly changed reporter metabolites using neighboring genes and gene-metabolite association. This reporter metabolite analysis, which has been successfully used in organisms such as yeast, Arabidopsis and rice (Çakir, 2015 ; Kim et al, 2015 ; Lakshmanan et al, 2015 ), elucidates the metabolic pathway regulation of cold stress in Arabidopsis .…”

Section: Introductionmentioning

confidence: 99%

Metabolite-Centric Reporter Pathway and Tripartite Network Analysis of Arabidopsis Under Cold Stress

Koç

Yüksel

Caetano‐Anollés

2018

Front. Bioeng. Biotechnol.

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The study of plant resistance to cold stress and the metabolic processes underlying its molecular mechanisms benefit crop improvement programs. Here we investigate the effects of cold stress on the metabolic pathways of Arabidopsis when directly inferred at system level from transcriptome data. A metabolite-centric reporter pathway analysis approach enabled the computation of metabolites associated with transcripts at four time points of cold treatment. Tripartite networks of gene-metabolite-pathway connectivity outlined the response of metabolites and pathways to cold stress. Our metabolome-independent analysis revealed stress-associated metabolites in pathway routes of the cold stress response, including amino acid, carbohydrate, lipid, hormone, energy, photosynthesis, and signaling pathways. Cold stress first triggered the mobilization of energy from glycolysis and ethanol degradation to enhance TCA cycle activity via acetyl-CoA. Interestingly, tripartite networks lacked power law behavior and scale free connectivity, favoring modularity. Network rewiring explicitly involved energetics, signal, carbon and redox metabolisms and membrane remodeling.

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Reporter pathway analysis from transcriptome data: Metabolite-centric versus Reaction-centric approach

Cited by 15 publications

References 60 publications

Network-based metabolic characterization of renal cell carcinoma

Network-based metabolic characterization of renal cell carcinoma

Current Status and Future Prospects of Genome-Scale Metabolic Modeling to Optimize the Use of Mesenchymal Stem Cells in Regenerative Medicine

Metabolite-Centric Reporter Pathway and Tripartite Network Analysis of Arabidopsis Under Cold Stress

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