| 1. |
- Mardinoglu, Adil, 1982, et al.
(författare)
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Genome-scale metabolic modelling of hepatocytes reveals serine deficiency in patients with non-alcoholic fatty liver disease
- 2014
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Ingår i: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 5, s. 3083-
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Tidskriftsartikel (refereegranskat)abstract
- Several liver disorders result from perturbations in the metabolism of hepatocytes, and their underlying mechanisms can be outlined through the use of genome-scale metabolic models (GEMs). Here we reconstruct a consensus GEM for hepatocytes, which we call iHepatocytes2322, that extends previous models by including an extensive description of lipid metabolism. We build iHepatocytes2322 using Human Metabolic Reaction 2.0 database and proteomics data in Human Protein Atlas, which experimentally validates the incorporated reactions. The reconstruction process enables improved annotation of the proteomics data using the network centric view of iHepatocytes2322. We then use iHepatocytes2322 to analyse transcriptomics data obtained from patients with non-alcoholic fatty liver disease. We show that blood concentrations of chondroitin and heparan sulphates are suitable for diagnosing non-alcoholic steatohepatitis and for the staging of non-alcoholic fatty liver disease. Furthermore, we observe serine deficiency in patients with NASH and identify PSPH, SHMT1 and BCAT1 as potential therapeutic targets for the treatment of non-alcoholic steatohepatitis.
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| 2. |
- Mardinoglu, Adil, 1982, et al.
(författare)
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Integration of clinical data with a genome-scale metabolic model of the human adipocyte
- 2013
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Ingår i: Molecular Systems Biology. - : EMBO. - 1744-4292 .- 1744-4292. ; 9, s. 649-
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Tidskriftsartikel (refereegranskat)abstract
- We evaluated the presence/absence of proteins encoded by 14 077 genes in adipocytes obtained from different tissue samples using immunohistochemistry. By combining this with previously published adipocyte-specific proteome data, we identified proteins associated with 7340 genes in human adipocytes. This information was used to reconstruct a comprehensive and functional genome-scale metabolic model of adipocyte metabolism. The resulting metabolic model, iAdipocytes1809, enables mechanistic insights into adipocyte metabolism on a genome-wide level, and can serve as a scaffold for integration of omics data to understand the genotype-phenotype relationship in obese subjects. By integrating human transcriptome and fluxome data, we found an increase in the metabolic activity around androsterone, ganglioside GM2 and degradation products of heparan sulfate and keratan sulfate, and a decrease in mitochondrial metabolic activities in obese subjects compared with lean subjects. Our study hereby shows a path to identify new therapeutic targets for treating obesity through combination of high throughput patient data and metabolic modeling.
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| 3. |
- Ågren, Rasmus, 1982, et al.
(författare)
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Identification of anticancer drugs for hepatocellular carcinoma through personalized genome-scale metabolic modeling
- 2014
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Ingår i: Molecular Systems Biology. - : EMBO. - 1744-4292. ; 10:3
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Tidskriftsartikel (refereegranskat)abstract
- Synopsis Personalized GEMs for six hepatocellular carcinoma patients are reconstructed using proteomics data and a task-driven model reconstruction algorithm. These GEMs are used to predict antimetabolites preventing tumor growth in all patients or in individual patients. The presence of proteins encoded by 15,841 genes in tumors from 27 HCC patients is evaluated by immunohistochemistry. Personalized GEMs for six HCC patients and GEMs for 83 healthy cell types are reconstructed based on HMR 2.0 and the tINIT algorithm for task-driven model reconstruction. 101 antimetabolites are predicted to inhibit tumor growth in all patients. Antimetabolite toxicity is tested using the 83 cell type-specific GEMs. Genome-scale metabolic models (GEMs) have proven useful as scaffolds for the integration of omics data for understanding the genotype-phenotype relationship in a mechanistic manner. Here, we evaluated the presence/absence of proteins encoded by 15,841 genes in 27 hepatocellular carcinoma (HCC) patients using immunohistochemistry. We used this information to reconstruct personalized GEMs for six HCC patients based on the proteomics data, HMR 2.0, and a task-driven model reconstruction algorithm (tINIT). The personalized GEMs were employed to identify anticancer drugs using the concept of antimetabolites; i.e., drugs that are structural analogs to metabolites. The toxicity of each antimetabolite was predicted by assessing the in silico functionality of 83 healthy cell type-specific GEMs, which were also reconstructed with the tINIT algorithm. We predicted 101 antimetabolites that could be effective in preventing tumor growth in all HCC patients, and 46 antimetabolites which were specific to individual patients. Twenty-two of the 101 predicted antimetabolites have already been used in different cancer treatment strategies, while the remaining antimetabolites represent new potential drugs. Finally, one of the identified targets was validated experimentally, and it was confirmed to attenuate growth of the HepG2 cell line.
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| 4. |
- Ågren, Rasmus, 1982, et al.
(författare)
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Reconstruction of Genome-Scale Active Metabolic Networks for 69 Human Cell Types and 16 Cancer Types Using INIT
- 2012
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Ingår i: PLoS Computational Biology. - : Public Library of Science (PLoS). - 1553-734X .- 1553-7358. ; 8:5
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Tidskriftsartikel (refereegranskat)abstract
- Development of high throughput analytical methods has given physicians the potential access to extensive and patient-specific data sets, such as gene sequences, gene expression profiles or metabolite footprints. This opens for a new approach in health care, which is both personalized and based on system-level analysis. Genome-scale metabolic networks provide a mechanistic description of the relationships between different genes, which is valuable for the analysis and interpretation of large experimental data-sets. Here we describe the generation of genome-scale active metabolic networks for 69 different cell types and 16 cancer types using the INIT (Integrative Network Inference for Tissues) algorithm. The INIT algorithm uses cell type specific information about protein abundances contained in the Human Proteome Atlas as the main source of evidence. The generated models constitute the first step towards establishing a Human Metabolic Atlas, which will be a comprehensive description (accessible online) of the metabolism of different human cell types, and will allow for tissue-level and organism-level simulations in order to achieve a better understanding of complex diseases. A comparative analysis between the active metabolic networks of cancer types and healthy cell types allowed for identification of cancer-specific metabolic features that constitute generic potential drug targets for cancer treatment.
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| 5. |
- Adiels, Martin, 1976, et al.
(författare)
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Kinetic Studies to Elucidate Impaired Metabolism of Triglyceride-rich Lipoproteins in Humans.
- 2015
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Ingår i: Frontiers in Physiology. - : Frontiers Media SA. - 1664-042X. ; 6:NOV, s. 342-
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Forskningsöversikt (refereegranskat)abstract
- To develop novel strategies for prevention and treatment of dyslipidemia, it is essential to understand the pathophysiology of dyslipoproteinemia in humans. Lipoprotein metabolism is a complex system in which abnormal concentrations of various lipoprotein particles can result from alterations in their rates of production, conversion, and/or catabolism. Traditional methods that measure plasma lipoprotein concentrations only provide static estimates of lipoprotein metabolism and hence limited mechanistic information. By contrast, the use of tracers labeled with stable isotopes and mathematical modeling, provides us with a powerful tool for probing lipid and lipoprotein kinetics in vivo and furthering our understanding of the pathogenesis of dyslipoproteinemia.
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| 6. |
- Altay, Özlem, et al.
(författare)
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Current Status of COVID-19 Therapies and Drug Repositioning Applications
- 2020
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Ingår i: Iscience. - : Elsevier BV. - 2589-0042. ; 23:7
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Tidskriftsartikel (refereegranskat)abstract
- The rapid and global spread of a new human coronavirus (SARS-CoV-2) has produced an immediate urgency to discover promising targets for the treatment of COVID-19. Drug repositioning is an attractive approach that can facilitate the drug discovery process by repurposing existing pharmaceuticals to treat illnesses other than their primary indications. Here, we review current information concerning the global health issue of COVID-19 including promising approved drugs and ongoing clinical trials for prospective treatment options. In addition, we describe computational approaches to be used in drug repurposing and highlight examples of in silico studies of drug development efforts against SARS-CoV-2.
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| 7. |
- Altay, Özlem, et al.
(författare)
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Revealing the Metabolic Alterations during Biofilm Development of Burkholderia cenocepacia Based on Genome-Scale Metabolic Modeling
- 2021
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Ingår i: Metabolites. - : MDPI AG. - 2218-1989 .- 2218-1989. ; 11:4
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Tidskriftsartikel (refereegranskat)abstract
- Burkholderia cenocepacia is among the important pathogens isolated from cystic fibrosis (CF) patients. It has attracted considerable attention because of its capacity to evade host immune defenses during chronic infection. Advances in systems biology methodologies have led to the emergence of methods that integrate experimental transcriptomics data and genome-scale metabolic models (GEMs). Here, we integrated transcriptomics data of bacterial cells grown on exponential and biofilm conditions into a manually curated GEM of B. cenocepacia. We observed substantial differences in pathway response to different growth conditions and alternative pathway susceptibility to extracellular nutrient availability. For instance, we found that blockage of the reactions was vital through the lipid biosynthesis pathways in the exponential phase and the absence of microenvironmental lysine and tryptophan are essential for survival. During biofilm development, bacteria mostly had conserved lipid metabolism but altered pathway activities associated with several amino acids and pentose phosphate pathways. Furthermore, conversion of serine to pyruvate and 2,5-dioxopentanoate synthesis are also identified as potential targets for metabolic remodeling during biofilm development. Altogether, our integrative systems biology analysis revealed the interactions between the bacteria and its microenvironment and enabled the discovery of antimicrobial targets for biofilm-related diseases.
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| 8. |
- Altay, Özlem, et al.
(författare)
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Systems biology perspective for studying the gut microbiota in human physiology and liver diseases
- 2019
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Ingår i: EBioMedicine. - : Elsevier BV. - 2352-3964. ; 49:November, s. 363-373
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Forskningsöversikt (refereegranskat)abstract
- The advancement in high-throughput sequencing technologies and systems biology approaches have revolutionized our understanding of biological systems and opened a new path to investigate unacknowledged biological phenomena. In parallel, the field of human microbiome research has greatly evolved and the relative contribution of the gut microbiome to health and disease have been systematically explored. This review provides an overview of the network-based and translational systems biology-based studies focusing on the function and composition of gut microbiota. We also discussed the association between the gut microbiome and the overall human physiology, as well as hepatic diseases and other metabolic disorders.
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| 9. |
- Arif, Muhammad, et al.
(författare)
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INetModels 2.0: An interactive visualization and database of multi-omics data
- 2021
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Ingår i: Nucleic Acids Research. - : Oxford University Press (OUP). - 0305-1048 .- 1362-4962. ; 49:W1, s. W271-W276
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Tidskriftsartikel (refereegranskat)abstract
- It is essential to reveal the associations between various omics data for a comprehensive understanding of the altered biological process in human wellness and disease. To date, very few studies have focused on collecting and exhibiting multi-omics associations in a single database. Here, we present iNetModels, an interactive database and visualization platform of Multi-Omics Biological Networks (MOBNs). This platform describes the associations between the clinical chemistry, anthropometric parameters, plasma proteomics, plasma metabolomics, as well as metagenomics for oral and gut microbiome obtained from the same individuals. Moreover, iNetModels includes tissue- and cancer-specific Gene Co-expression Networks (GCNs) for exploring the connections between the specific genes. This platform allows the user to interactively explore a single feature's association with other omics data and customize its particular context (e.g. male/female specific). The users can also register their data for sharing and visualization of the MOBNs and GCNs. Moreover, iNetModels allows users who do not have a bioinformatics background to facilitate human wellness and disease research. iNetModels can be accessed freely at https://inetmodels.com without any limitation.
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| 10. |
- Benfeitas, Rui, et al.
(författare)
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Characterization of heterogeneous redox responses in hepatocellular carcinoma patients using network analysis
- 2019
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Ingår i: Ebiomedicine. - : Elsevier BV. - 2352-3964. ; 40, s. 471-487
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Tidskriftsartikel (refereegranskat)abstract
- Background: Redox metabolism is often considered a potential target for cancer treatment, but a systematic examination of redox responses in hepatocellular carcinoma (HCC) is missing. Methods: Here, we employed systems biology and biological network analyses to reveal key roles of genes associated with redox metabolism in HCC by integrating multi-omics data. Findings: We found that several redox genes, including 25 novel potential prognostic genes, are significantly co-expressed with liver-specific genes and genes associated with immunity and inflammation. Based on an integrative analysis, we found that HCC tumors display antagonistic behaviors in redox responses. The two HCC groups are associated with altered fatty acid, amino acid, drug and hormone metabolism, differentiation, proliferation, and NADPH-independent vs - dependent antioxidant defenses. Redox behavior varies with known tumor subtypes and progression, affecting patient survival. These antagonistic responses are also displayed at the protein and metabolite level and were validated in several independent cohorts. We finally showed the differential redox behavior using mice transcriptomics in HCC and noncancerous tissues and associated with hypoxic features of the two redox gene groups. Interpretation: Our integrative approaches highlighted mechanistic differences among tumors and allowed the identification of a survival signature and several potential therapeutic targets for the treatment of HCC.
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| 11. |
- Benfeitas, Rui, et al.
(författare)
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New challenges to study heterogeneity in cancer redox metabolism
- 2017
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Ingår i: Frontiers in Cell and Developmental Biology. - : Frontiers Media S.A.. - 2296-634X. ; 5:JUL
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Tidskriftsartikel (refereegranskat)abstract
- Reactive oxygen species (ROS) are important pathophysiological molecules involved in vital cellular processes. They are extremely harmful at high concentrations because they promote the generation of radicals and the oxidation of lipids, proteins, and nucleic acids, which can result in apoptosis. An imbalance of ROS and a disturbance of redox homeostasis are now recognized as a hallmark of complex diseases. Considering that ROS levels are significantly increased in cancer cells due to mitochondrial dysfunction, ROS metabolism has been targeted for the development of efficient treatment strategies, and antioxidants are used as potential chemotherapeutic drugs. However, initial ROS-focused clinical trials in which antioxidants were supplemented to patients provided inconsistent results, i.e., improved treatment or increased malignancy. These different outcomes may result from the highly heterogeneous redox responses of tumors in different patients. Hence, population-based treatment strategies are unsuitable and patient-tailored therapeutic approaches are required for the effective treatment of patients. Moreover, due to the crosstalk between ROS, reducing equivalents [e.g., NAD(P)H] and central metabolism, which is heterogeneous in cancer, finding the best therapeutic target requires the consideration of system-wide approaches that are capable of capturing the complex alterations observed in all of the associated pathways. Systems biology and engineering approaches may be employed to overcome these challenges, together with tools developed in personalized medicine. However, ROS- and redox-based therapies have yet to be addressed by these methodologies in the context of disease treatment. Here, we review the role of ROS and their coupled redox partners in tumorigenesis. Specifically, we highlight some of the challenges in understanding the role of hydrogen peroxide (H2O2), one of the most important ROS in pathophysiology in the progression of cancer. We also discuss its interplay with antioxidant defenses, such as the coupled peroxiredoxin/thioredoxin and glutathione/glutathione peroxidase systems, and its reducing equivalent metabolism. Finally, we highlight the need for system-level and patient-tailored approaches to clarify the roles of these systems and identify therapeutic targets through the use of the tools developed in personalized medicine.
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| 12. |
- Bidkhori, Gholamreza, et al.
(författare)
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Metabolic Network-Based Identification and Prioritization o f Anticancer Targets Based on Expression Data in Hepatocellular Carcinoma
- 2018
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Ingår i: Frontiers in Physiology. - : Frontiers Media SA. - 1664-042X. ; 9:JUL
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Tidskriftsartikel (refereegranskat)abstract
- Hepatocellular carcinoma (HCC) is a deadly form of liver cancer with high mortality worldwide. Unfortunately, the large heterogeneity of this disease makes it difficult to develop effective treatment strategies. Cellular network analyses have been employed to study heterogeneity in cancer, and to identify potential therapeutic targets. However, the existing approaches do not consider metabolic growth requirements, i.e., biological network functionality, to rank candidate targets while preventing toxicity to non-cancerous tissues. Here, we developed an algorithm to overcome these issues based on integration of gene expression data, genome-scale metabolic models, network controllability, and dispensability, as well as toxicity analysis. This method thus predicts and ranks potential anticancer non-toxic controlling metabolite and gene targets. Our algorithm encompasses both objective-driven and-independent tasks, and uses network topology to finally rank the predicted therapeutic targets. We employed this algorithm to the analysis of transcriptomic data for 50 HCC patients with both cancerous and non-cancerous samples. We identified several potential targets that would prevent cell growth, including 74 anticancer metabolites, and 3 gene targets (PRKACA, PGS1, and CRLS1). The predicted anticancer metabolites showed good agreement with existing FDA-approved cancer drugs, and the 3 genes were experimentally validated by performing experiments in HepG2 and Hep3B liver cancer cell lines. Our observations indicate that our novel approach successfully identifies therapeutic targets for effective treatment of cancer. This approach may also be applied to any cancer type that has tumor and non-tumor gene or protein expression data.
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| 13. |
- Bidkhori, Gholamreza, et al.
(författare)
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Metabolic network-based stratification of hepatocellular carcinoma reveals three distinct tumor subtypes
- 2018
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Ingår i: Proceedings of the National Academy of Sciences of the United States of America. - : Proceedings of the National Academy of Sciences. - 0027-8424 .- 1091-6490. ; 115:50
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Tidskriftsartikel (refereegranskat)abstract
- Hepatocellular carcinoma (HCC) is one of the most frequent forms of liver cancer, and effective treatment methods are limited due to tumor heterogeneity. There is a great need for comprehensive approaches to stratify HCC patients, gain biological insights into subtypes, and ultimately identify effective therapeutic targets. We stratified HCC patients and characterized each subtype using transcriptomics data, genome-scale metabolic networks and network topology/controllability analysis. This comprehensive systems-level analysis identified three distinct subtypes with substantial differences in metabolic and signaling pathways reflecting at genomic, transcriptomic, and proteomic levels. These subtypes showed large differences in clinical survival associated with altered kynurenine metabolism, WNT/beta-catenin-associated lipid metabolism, and PI3K/AKT/mTOR signaling. Integrative analyses indicated that the three subtypes rely on alternative enzymes (e.g., ACSS1/ACSS2/ACSS3, PKM/PKLR, ALDOB/ALDOA, MTHFD1L/MTHFD2/MTHFD1) to catalyze the same reactions. Based on systems-level analysis, we identified 8 to 28 subtype-specific genes with pivotal roles in controlling the metabolic network and predicted that these genes may be targeted for development of treatment strategies for HCC subtypes by performing in silico analysis. To validate our predictions, we performed experiments using HepG2 cells under normoxic and hypoxic conditions and observed opposite expression patterns between genes expressed in high/moderate/low-survival tumor groups in response to hypoxia, reflecting activated hypoxic behavior in patients with poor survival. In conclusion, our analyses showed that the heterogeneous HCC tumors can be stratified using a metabolic network-driven approach, which may also be applied to other cancer types, and this stratification may have clinical implications to drive the development of precision medicine.
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| 14. |
- Björnson, Elias, 1988, et al.
(författare)
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Personalized Cardiovascular Disease Prediction and Treatment-A Review of Existing Strategies and Novel Systems Medicine Tools
- 2016
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Ingår i: Frontiers in Physiology. - : Frontiers Media SA. - 1664-042X. ; 7:JAN
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Forskningsöversikt (refereegranskat)abstract
- Cardiovascular disease (CVD) continues to constitute the leading cause of death globally. CVD risk stratification is an essential tool to sort through heterogeneous populations and identify individuals at risk of developing CVD. However, applications of current risk scores have recently been shown to result in considerable misclassification of high-risk subjects. In addition, despite long standing beneficial effects in secondary prevention, current CVD medications have in a primary prevention setting shown modest benefit in terms of increasing life expectancy. A systems biology approach to CVD risk stratification may be employed for improving risk-estimating algorithms through addition of high-throughput derived omics biomarkers. In addition, modeling of personalized benefit-of-treatment may help in guiding choice of intervention. In the area of medicine, realizing that CVD involves perturbations of large complex biological networks, future directions in drug development may involve moving away from a reductionist approach toward a system level approach. Here, we review current CVD risk scores and explore how novel algorithms could help to improve the identification of risk and maximize personalized treatment benefit. We also discuss possible future directions in the development of effective treatment strategies for CVD through the use of genome-scale metabolic models (GEMs) as well as other biological network-based approaches.
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| 15. |
- Björnson, Elias, 1988, et al.
(författare)
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Stratification of Hepatocellular Carcinoma Patients Based on Acetate Utilization
- 2015
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Ingår i: Cell Reports. - : Elsevier BV. - 2211-1247. ; 13:9, s. 2014-2026
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Tidskriftsartikel (refereegranskat)abstract
- Hepatocellular carcinoma (HCC) is a deadly form of liver cancer that is increasingly prevalent. We analyzed global gene expression profiling of 361 HCC tumors and 49 adjacent noncancerous liver samples by means of combinatorial network-based analysis. We investigated the correlation between transcriptome and proteome of HCC and reconstructed a functional genome-scale metabolic model (GEM) for HCC. We identified fundamental metabolic processes required for cell proliferation using the network centric view provided by the GEM. Our analysis revealed tight regulation of fatty acid biosynthesis (FAB) and highly significant deregulation of fatty acid oxidation in HCC. We predicted mitochondrial acetate as an emerging substrate for FAB through upregulation of mitochondrial acetyl-CoA synthetase (ACSS1) in HCC. We analyzed heterogeneous expression of ACSS1 and ACSS2 between HCC patients stratified by high and low ACSS1 and ACSS2 expression and revealed that ACSS1 is associated with tumor growth and malignancy under hypoxic conditions in human HCC.
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| 16. |
- Bosley, J. R., et al.
(författare)
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Informing Pharmacokinetic Models With Physiological Data: Oral Population Modeling of L-Serine in Humans
- 2021
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Ingår i: Frontiers in Pharmacology. - : Frontiers Media SA. - 1663-9812. ; 12
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Tidskriftsartikel (refereegranskat)abstract
- To determine how to set optimal oral L-serine (serine) dose levels for a clinical trial, existing literature was surveyed. Data sufficient to set the dose was inadequate, and so an (n = 10) phase I-A calibration trial was performed, administering serine with and without other oral agents. We analyzed the trial and the literature data using pharmacokinetic (PK) modeling and statistical analysis. The therapeutic goal is to modulate specific serine-related metabolic pathways in the liver using the lowest possible dose which gives the desired effect since the upper bound was expected to be limited by toxicity. A standard PK approach, in which a common model structure was selected using a fit to data, yielded a model with a single central compartment corresponding to plasma, clearance from that compartment, and an endogenous source of serine. To improve conditioning, a parametric structure was changed to estimate ratios (bioavailability over volume, for example). Model fit quality was improved and the uncertainty in estimated parameters was reduced. Because of the particular interest in the fate of serine, the model was used to estimate whether serine is consumed in the gut, absorbed by the liver, or entered the blood in either a free state, or in a protein- or tissue-bound state that is not measured by our assay. The PK model structure was set up to represent relevant physiology, and this quantitative systems biology approach allowed a broader set of physiological data to be used to narrow parameter and prediction confidence intervals, and to better understand the biological meaning of the data. The model results allowed us to determine the optimal human dose for future trials, including a trial design component including IV and tracer studies. A key contribution is that we were able to use human physiological data from the literature to inform the PK model and to set reasonable bounds on parameters, and to improve model conditioning. Leveraging literature data produced a more predictive, useful model.
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| 17. |
- Chaudhari, Aditi, et al.
(författare)
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ARAP2 promotes GLUT1-mediated basal glucose uptake through regulation of sphingolipid metabolism
- 2016
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Ingår i: Biochimica et Biophysica Acta - Molecular and Cell Biology of Lipids. - : Elsevier BV. - 1388-1981 .- 1879-2618. ; 1861:11, s. 1643-1651
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Tidskriftsartikel (refereegranskat)abstract
- Lipid droplet formation, which is driven by triglyceride synthesis, requires several droplet-associated proteins. We identified ARAP2 (an ADP-ribosylation factor 6 GTPase-activating protein) in the lipid droplet proteome of NIH-3T3 cells and showed that knockdown of ARAP2 resulted in decreased lipid droplet formation and triglyceride synthesis. We also showed that ARAP2 knockdown did not affect fatty acid uptake but reduced basal glucose uptake, total levels of the glucose transporter GLUT1, and GLUT1 levels in the plasma membrane and the lipid micro-domain fraction (a specialized plasma membrane domain enriched in sphingolipids). Microarray analysis showed that ARAP2 knockdown altered expression of genes involved in sphingolipid metabolism. Because sphingolipids are known to play a key role in cell signaling, we performed lipidomics to further investigate the relationship between ARAP2 and sphingolipids and potentially identify a link with glucose uptake. We found that ARAP2 knockdown increased glucosylceramide and lactosylceramide levels without affecting ceramide levels, and thus speculated that the rate-limiting enzyme in glycosphingolipid synthesis, namely glucosylceramide synthase (GCS), could be modified by ARAP2. In agreement with our hypothesis, we showed that the activity of GCS was increased by ARAP2 knockdown and reduced by ARAP2 overexpression. Furthermore, pharmacological inhibition of GCS resulted in increases in basal glucose uptake, total GLUT1 levels, triglyceride biosynthesis from glucose, and lipid droplet formation, indicating that the effects of GCS inhibition are the opposite to those resulting from ARAP2 knockdown. Taken together, our data suggest that ARAP2 promotes lipid droplet formation by modifying sphingolipid metabolism through GCS.
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| 18. |
- Cregg, P. J., et al.
(författare)
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Inclusion of interactions in mathematical modelling of implant assisted magnetic drug targeting
- 2012
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Ingår i: Applied Mathematical Modelling. - : Elsevier BV. - 0307-904X. ; 36:1, s. 1-34
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Forskningsöversikt (refereegranskat)abstract
- Drug delivery technologies are an important area within biomedicine. Targeted drug delivery aims to reduce the undesired side effects of drug usage by directing or capturing the active agents near a desired site within the body. This is particularly beneficial in, for instance, cancer chemotherapy, where the side effects of general (systemic) drug administration can be severe. One approach to targeted drug delivery uses magnetic nanoparticles as the constituents of carriers for the desired active agent. Once injected into the body, the behaviour of these magnetic carriers can be influenced and controlled by magnetic fields. In implant assisted magnetic drug targeting systems a magnetic implant, typically a stent, wire or spherical seed can be used to target sites deep within the body as the implant acts as a focus for the resulting magnetic force. This can be easily understood as the force depends on the gradient of the magnetic field and the gradient near the implant is large. In designing such a system many factors need to be considered including physical factors such as the size and nature of the implants and carriers, and the fields required. Moreover, the range of applicability of these systems in terms of the regions of the vasculature system, from low blood velocity environments, such as capillary beds to higher velocity arteries, must be considered. Furthermore, assessment criteria for these systems are needed. Mathematical modelling and simulation has a valuable role to play in informing in vitro and in vivo experiments, leading to practical system design. Specifically, the implant assisted magnetic drug targeting systems of Aviles. Ebner and Ritter are considered within this review, and two dimensional mathematical modelling is performed using the open source C++ finite volume library OpenFOAM. In the first system treated, a large ferromagnetic particle is implanted into a capillary bed as a seed to aid collection of single domain nanoparticles (radius 20-100 nm). The Langevin function is used to calculate the magnetic moment of the particles, and the model is further adapted to treat the agglomeration of particles known to occur in these systems. This agglomeration can be attributed to interparticle interactions and here the magnetic dipole-dipole and hydrodynamic interactions for two mutually interacting nanoparticles are modelled, following Mikkelsen et al. who treated two particle interactions in microfluidic systems, with low magnetic field (0.05 T). The resulting predicted performance is found to both increase and decrease significantly depending on initial positions of the particles. Secondly, a ferromagnetic, coiled wire stent is implanted in a large arterial vessel. The magnetic dipole-dipole and hydrodynamic interactions for multiple particles are included. Different initial positions are considered and the system performance is assessed. Inclusion of these interactions yields predictions that are in closer agreement with the experimental results of Aviles et al. We conclude that the discrepancies between the non interacting theoretical predictions and the corresponding experimental results can (as suggested by Aviles et al.) be largely attributed to interparticle interactions and the consequent agglomeration.
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| 19. |
- Fagerberg, Linn, et al.
(författare)
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Analysis of the human tissue-specific expression by genome-wide integration of transcriptomics and antibody-based proteomics
- 2014
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Ingår i: Molecular & Cellular Proteomics. - 1535-9476 .- 1535-9484. ; 13:2, s. 397-406
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Tidskriftsartikel (refereegranskat)abstract
- Global classification of the human proteins with regards to spatial expression patterns across organs and tissues is important for studies of human biology and disease. Here, we used a quantitative transcriptomics analysis (RNA-Seq) to classify the tissue-specific expression of genes across a representative set of all major human organs and tissues and combined this analysis with antibody- based profiling of the same tissues. To present the data, we launch a new version of the Human Protein Atlas that integrates RNA and protein expression data corresponding to 80% of the human protein-coding genes with access to the primary data for both the RNA and the protein analysis on an individual gene level. We present a classification of all human protein-coding genes with regards to tissue-specificity and spatial expression pattern. The integrative human expression map can be used as a starting point to explore the molecular constituents of the human body.
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| 20. |
- Ghaffari Nouran, Pouyan, 1980, et al.
(författare)
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Identifying anti-growth factors for human cancer cell lines through genome-scale metabolic modeling
- 2015
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Ingår i: Scientific Reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 5, s. 8183-
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Tidskriftsartikel (refereegranskat)abstract
- Human cancer cell lines are used as important model systems to study molecular mechanisms associated with tumor growth, hereunder how genomic and biological heterogeneity found in primary tumors affect cellular phenotypes. We reconstructed Genome scale metabolic models (GEMs) for eleven cell lines based on RNA-Seq data and validated the functionality of these models with data from metabolite profiling. We used cell line-specific GEMs to analyze the differences in the metabolism of cancer cell lines, and to explore the heterogeneous expression of the metabolic subsystems. Furthermore, we predicted 85 antimetabolites that can inhibit growth of, or even kill, any of the cell lines, while at the same time not being toxic for 83 different healthy human cell types. 60 of these antimetabolites were found to inhibit growth in all cell lines. Finally, we experimentally validated one of the predicted antimetabolites using two cell lines with different phenotypic origins, and found that it is effective in inhibiting the growth of these cell lines. Using immunohistochemistry, we also showed high or moderate expression levels of proteins targeted by the validated antimetabolite. Identified anti-growth factors for inhibition of cell growth may provide leads for the development of efficient cancer treatment strategies.
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| 21. |
- Grinberg, Marianna, et al.
(författare)
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Toxicogenomics directory of chemically exposed human hepatocytes
- 2014
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Ingår i: Archives of Toxicology. - : Springer Science and Business Media LLC. - 1432-0738 .- 0340-5761. ; 88:12, s. 2261-2287
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Tidskriftsartikel (refereegranskat)abstract
- A long-term goal of numerous research projects is to identify biomarkers for in vitro systems predicting toxicity in vivo. Often, transcriptomics data are used to identify candidates for further evaluation. However, a systematic directory summarizing key features of chemically influenced genes in human hepatocytes is not yet available. To bridge this gap, we used the Open TG-GATES database with Affymetrix files of cultivated human hepatocytes incubated with chemicals, further sets of gene array data with hepatocytes from human donors generated in this study, and publicly available genome-wide datasets of human liver tissue from patients with non-alcoholic steatohepatitis (NASH), cirrhosis, and hepatocellular cancer (HCC). After a curation procedure, expression data of 143 chemicals were included into a comprehensive biostatistical analysis. The results are summarized in the publicly available toxicotranscriptomics directory (http://wiki.toxbank.net/toxicogenomics-map/) which provides information for all genes whether they are up- or downregulated by chemicals and, if yes, by which compounds. The directory also informs about the following key features of chemically influenced genes: (1) Stereotypical stress response. When chemicals induce strong expression alterations, this usually includes a complex but highly reproducible pattern named 'stereotypical response.' On the other hand, more specific expression responses exist that are induced only by individual compounds or small numbers of compounds. The directory differentiates if the gene is part of the stereotypical stress response or if it represents a more specific reaction. (2) Liver disease-associated genes. Approximately 20 % of the genes influenced by chemicals are up- or downregulated, also in liver disease. Liver disease genes deregulated in cirrhosis, HCC, and NASH that overlap with genes of the aforementioned stereotypical chemical stress response include CYP3A7, normally expressed in fetal liver; the phase II metabolizing enzyme SULT1C2; ALDH8A1, known to generate the ligand of RXR, one of the master regulators of gene expression in the liver; and several genes involved in normal liver functions: CPS1, PCK1, SLC2A2, CYP8B1, CYP4A11, ABCA8, and ADH4. (3) Unstable baseline genes. The process of isolating and the cultivation of hepatocytes was sufficient to induce some stress leading to alterations in the expression of genes, the so-called unstable baseline genes. (4) Biological function. Although more than 2,000 genes are transcriptionally influenced by chemicals, they can be assigned to a relatively small group of biological functions, including energy and lipid metabolism, inflammation and immune response, protein modification, endogenous and xenobiotic metabolism, cytoskeletal organization, stress response, and DNA repair. In conclusion, the introduced toxicotranscriptomics directory offers a basis for a rationale choice of candidate genes for biomarker evaluation studies and represents an easy to use source of background information on chemically influenced genes.
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| 22. |
- Heinonen, S., et al.
(författare)
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Mitochondria-related transcriptional signature is downregulated in adipocytes in obesity: a study of young healthy MZ twins
- 2017
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Ingår i: Diabetologia. - : Springer Science and Business Media LLC. - 1432-0428 .- 0012-186X. ; 60:1, s. 169-181
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Tidskriftsartikel (refereegranskat)abstract
- Low mitochondrial activity in adipose tissue is suggested to be an underlying factor in obesity and its metabolic complications. We aimed to find out whether mitochondrial measures are downregulated in obesity also in isolated adipocytes. We studied young adult monozygotic (MZ) twin pairs discordant (n = 14, intrapair difference Delta BMI ae 3 kg/m(2)) and concordant (n = 5, Delta BMI
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| 23. |
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| 24. |
- Kampf, Caroline, et al.
(författare)
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Defining the human gallbladder proteome by transcriptomics and affinity proteomics
- 2014
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Ingår i: Proteomics. - : Wiley. - 1615-9853 .- 1615-9861. ; 14:21-22, s. 2498-2507
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Tidskriftsartikel (refereegranskat)abstract
- Global protein analysis of human gallbladder tissue is vital for identification of molecular regulators and effectors of its physiological activity. Here, we employed a genome-wide deep RNA sequencing analysis in 28 human tissues to identify the genes overrepresented in the gallbladder and complemented it with antibody-based immunohistochemistry in 48 human tissues. We characterized human gallbladder proteins and identified 140 gallbladder-specific proteins with an elevated expression in the gallbladder as compared to the other analyzed tissues. Five genes were categorized as enriched, with at least fivefold higher levels in gallbladder, 60 genes were categorized as group enriched with elevated transcript levels in gallbladder shared with at least one other tissue and 75 genes were categorized as enhanced with higher expression than the average expression in other tissues. We explored the localization of the genes within the gallbladder through cell-type specific antibody-based protein profiling and the subcellular localization of the genes through immunofluorescent-based profiling. Finally, we revealed the biological processes and metabolic functions carried out by these genes through the use of GO, KEGG Pathway, and HMR2.0 that is compilation of the human metabolic reactions. We demonstrated the results of the combined analysis of the transcriptomics and affinity proteomics.
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| 25. |
- Kampf, Caroline, et al.
(författare)
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The human liver-specific proteome defined by transcriptomics and antibody-based profiling
- 2014
-
Ingår i: FASEB Journal. - : Wiley. - 1530-6860 .- 0892-6638. ; 28:7, s. 2901-2914
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Tidskriftsartikel (refereegranskat)abstract
- Human liver physiology and the genetic etiology of the liver diseases can potentially be elucidated through the identification of proteins with enriched expression in the liver. Here, we combined data from RNA sequencing (RNA-Seq) and antibody-based immunohistochemistry across all major human tissues to explore the human liver proteome with enriched expression, as well as the cell type-enriched expression in hepatocyte and bile duct cells. We identified in total 477 protein-coding genes with elevated expression in the liver: 179 genes have higher expression as compared to all the other analyzed tissues; 164 genes have elevated transcript levels in the liver shared with at least one other tissue type; and an additional 134 genes have a mild level of increased expression in the liver. We identified the precise localization of these proteins through antibody-based protein profiling and the subcellular localization of these proteins through immunofluorescent-based profiling. We also identified the biological processes and metabolic functions associated with these proteins, investigated their contribution in the occurrence of liver diseases, and identified potential targets for their treatment. Our study demonstrates the use of RNA-Seq and antibody-based immunohistochemistry for characterizing the human liver proteome, as well as the use of tissue-specific proteins in identification of novel drug targets and discovery of biomarkers.
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| 26. |
- Klevstig, Martina, et al.
(författare)
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Cardiac expression of the microsomal triglyceride transport protein protects the heart function during ischemia
- 2019
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Ingår i: Journal of Molecular and Cellular Cardiology. - : Elsevier BV. - 0022-2828 .- 1095-8584. ; 137, s. 1-8
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Tidskriftsartikel (refereegranskat)abstract
- Aims: The microsomal triglyceride transport protein (MTTP) is critical for assembly and secretion of apolipoprotein B (apoB)-containing lipoproteins and is most abundant in the liver and intestine. Surprisingly, MTTP is also expressed in the heart. Here we tested the functional relevance of cardiac MTTP expression. Materials and methods: We combined clinical studies, advanced expression analysis of human heart biopsies and analyses in genetically modified mice lacking cardiac expression of the MTTP-A isoform of MTTP. Results: Our results indicate that lower cardiac MTTP expression in humans is associated with structural and perfusion abnormalities in patients with ischemic heart disease. MTTP-A deficiency in mice heart does not affect total MTTP expression, activity or lipid concentration in the heart. Despite this, MTTP-A deficient mice displayed impaired cardiac function after a myocardial infarction. Expression analysis of MTTP indicates that MTTP expression is linked to cardiac function and responses in the heart. Conclusions: Our results indicate that MTTP may play an important role for the heart function in conjunction to ischemic events.
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| 27. |
- Lam, S., et al.
(författare)
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A systems biology approach for studying neurodegenerative diseases
- 2020
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Ingår i: Drug Discovery Today. - : Elsevier BV. - 1359-6446 .- 1878-5832. ; 25:7, s. 1146-1159
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Tidskriftsartikel (refereegranskat)abstract
- Neurodegenerative diseases (NDDs), such as Alzheimer's (AD) and Parkinson's (PD), are among the leading causes of lost years of healthy life and exert a great strain on public healthcare systems. Despite being first described more than a century ago, no effective cure exists for AD or PD. Although extensively characterised at the molecular level, traditional neurodegeneration research remains marred by narrow-sense approaches surrounding amyloid beta (A beta), tau, and alpha-synuclein (alpha-syn). A systems biology approach enables the integration of multi-omics data and informs discovery of biomarkers, drug targets, and treatment strategies. Here, we present a comprehensive timeline of high-throughput data collection, and associated biotechnological advancements and computational analysis related to AD and PD. We hereby propose that a philosophical change in the definitions of AD and PD is now needed.
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| 28. |
- Lam, S., et al.
(författare)
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Addressing the heterogeneity in liver diseases using biological networks
- 2021
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Ingår i: Briefings in Bioinformatics. - : Oxford University Press (OUP). - 1467-5463 .- 1477-4054. ; 22:2, s. 1751-1766
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Tidskriftsartikel (refereegranskat)abstract
- The abnormalities in human metabolism have been implicated in the progression of several complex human diseases, including certain cancers. Hence, deciphering the underlying molecular mechanisms associated with metabolic reprogramming in a disease state can greatly assist in elucidating the disease aetiology. An invaluable tool for establishing connections between global metabolic reprogramming and disease development is the genome-scale metabolic model (GEM). Here, we review recent work on the reconstruction of cell/tissue-type and cancer-specific GEMs and their use in identifying metabolic changes occurring in response to liver disease development, stratification of the heterogeneous disease population and discovery of novel drug targets and biomarkers. We also discuss how GEMs can be integrated with other biological networks for generating more comprehensive cell/tissue models. In addition, we review the various biological network analyses that have been employed for the development of efficient treatment strategies. Finally, we present three case studies in which independent studies converged on conclusions underlying liver disease.
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| 29. |
- Laudette, Marion, 1992, et al.
(författare)
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Cardiomyocyte-specific PCSK9 deficiency compromises mitochondrial bioenergetics and heart function
- 2023
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Ingår i: Cardiovascular Research. - : Oxford University Press (OUP). - 0008-6363 .- 1755-3245. ; 119:7, s. 1537-1552
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Tidskriftsartikel (refereegranskat)abstract
- Aims Pro-protein convertase subtilisin-kexin type 9 (PCSK9), which is expressed mainly in the liver and at low levels in the heart, regulates cholesterol levels by directing low-density lipoprotein receptors to degradation. Studies to determine the role of PCSK9 in the heart are complicated by the close link between cardiac function and systemic lipid metabolism. Here, we sought to elucidate the function of PCSK9 specifically in the heart by generating and analysing mice with cardiomyocyte-specific Pcsk9 deficiency (CMPcsk9−/− mice) and by silencing Pcsk9 acutely in a cell culture model of adult cardiomyocyte-like cells. Methods and results Mice with cardiomyocyte-specific deletion of Pcsk9 had reduced contractile capacity, impaired cardiac function, and left ventricular dilatation at 28 weeks of age and died prematurely. Transcriptomic analyses revealed alterations of signalling pathways linked to cardiomyopathy and energy metabolism in hearts from CM-Pcsk9−/− mice vs. wild-type littermates. In agreement, levels of genes and proteins involved in mitochondrial metabolism were reduced in CM-Pcsk9−/− hearts. By using a Seahorse flux analyser, we showed that mitochondrial but not glycolytic function was impaired in cardiomyocytes from CM-Pcsk9−/− mice. We further showed that assembly and activity of electron transport chain (ETC) complexes were altered in isolated mitochondria from CM-Pcsk9−/− mice. Circulating lipid levels were unchanged in CM-Pcsk9−/− mice, but the lipid composition of mitochondrial membranes was altered. In addition, cardiomyocytes from CM-Pcsk9−/− mice had an increased number of mitochondria–endoplasmic reticulum contacts and alterations in the morphology of cristae, the physical location of the ETC complexes. We also showed that acute Pcsk9 silencing in adult cardiomyocyte-like cells reduced the activity of ETC complexes and impaired mitochondrial metabolism. Conclusion PCSK9, despite its low expression in cardiomyocytes, contributes to cardiac metabolic function, and PCSK9 deficiency in cardiomyocytes is linked to cardiomyopathy, impaired heart function, and compromised energy production.
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| 30. |
- Lee, Sunjae, et al.
(författare)
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Integrated Network Analysis Reveals an Association between Plasma Mannose Levels and Insulin Resistance
- 2016
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Ingår i: Cell Metabolism. - : Elsevier BV. - 1550-4131 .- 1932-7420. ; 24:1, s. 172-184
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Tidskriftsartikel (refereegranskat)abstract
- To investigate the biological processes that are altered in obese subjects, we generated cell-specific integrated networks (INs) by merging genome-scale metabolic, transcriptional regulatory and protein-protein interaction networks. We performed genome-wide transcriptomics analysis to determine the global gene expression changes in the liver and three adipose tissues from obese subjects undergoing bariatric surgery and integrated these data into the cell-specific INs. We found dysregulations in mannose metabolism in obese subjects and validated our predictions by detecting mannose levels in the plasma of the lean and obese subjects. We observed significant correlations between plasma mannose levels, BMI, and insulin resistance (IR). We also measured plasma mannose levels of the subjects in two additional different cohorts and observed that an increased plasma mannose level was associated with IR and insulin secretion. We finally identified mannose as one of the best plasma metabolites in explaining the variance in obesity-independent IR.
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| 31. |
- Lee, SangWook, et al.
(författare)
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Network analyses identify liver-specific targets for treating liver diseases
- 2017
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Ingår i: Molecular Systems Biology. - : EMBO. - 1744-4292. ; 13:8
-
Tidskriftsartikel (refereegranskat)abstract
- We performed integrative network analyses to identify targets that can be used for effectively treating liver diseases with minimal side effects. We first generated co-expression networks (CNs) for 46 human tissues and liver cancer to explore the functional relationships between genes and examined the overlap between functional and physical interactions. Since increased de novo lipogenesis is a characteristic of nonalcoholic fatty liver disease (NAFLD) and hepatocellular carcinoma (HCC), we investigated the liver-specific genes co-expressed with fatty acid synthase (FASN). CN analyses predicted that inhibition of these liver-specific genes decreases FASN expression. Experiments in human cancer cell lines, mouse liver samples, and primary human hepatocytes validated our predictions by demonstrating functional relationships between these liver genes, and showing that their inhibition decreases cell growth and liver fat content. In conclusion, we identified liver-specific genes linked to NAFLD pathogenesis, such as pyruvate kinase liver and red blood cell (PKLR), or to HCC pathogenesis, such as PKLR, patatin-like phospholipase domain containing 3 (PNPLA3), and proprotein convertase subtilisin/kexin type 9 (PCSK9), all of which are potential targets for drug development.
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| 32. |
- Lee, Sunjae, et al.
(författare)
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TCSBN: a database of tissue and cancer specific biological networks
- 2018
-
Ingår i: Nucleic Acids Research. - : Oxford University Press (OUP). - 0305-1048 .- 1362-4962. ; 46:D1
-
Tidskriftsartikel (refereegranskat)abstract
- Biological networks provide new opportunities for understanding the cellular biology in both health and disease states. We generated tissue specific integrated networks (INs) for liver, muscle and adipose tissues by integratingmetabolic, regulatory and protein-protein interaction networks. We also generated human co-expression networks (CNs) for 46 normal tissues and 17 cancers to explore the functional relationships between genes as well as their relationships with biological functions, and investigate the overlap between functional and physical interactions provided by CNs and INs, respectively. These networks can be employed in the analysis of omics data, provide detailed insight into disease mechanisms by identifying the key biological components and eventually can be used in the development of efficient treatment strategies. Moreover, comparative analysis of the networks may allow for the identification of tissue-specific targets that can be used in the development of drugs with the minimum toxic effect to other human tissues. These context-specific INs and CNs are presented in an interactive website http://inetmodels.com without any limitation.
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| 33. |
- Li, Xiangyu, et al.
(författare)
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Classification of clear cell renal cell carcinoma based on PKM alternative splicing
- 2020
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Ingår i: Heliyon. - : Elsevier BV. - 2405-8440. ; 6:2
-
Tidskriftsartikel (refereegranskat)abstract
- Clear cell renal cell carcinoma (ccRCC) accounts for 70-80% of kidney cancer diagnoses and displays high molecular and histologic heterogeneity. Hence, it is necessary to reveal the underlying molecular mechanisms involved in progression of ccRCC to better stratify the patients and design effective treatment strategies. Here, we analyzed the survival outcome of ccRCC patients as a consequence of the differential expression of four transcript isoforms of the pyruvate kinase muscle type (PKM). We first extracted a classification biomarker consisting of eight gene pairs whose within-sample relative expression orderings (REOs) could be used to robustly classify the patients into two groups with distinct molecular characteristics and survival outcomes. Next, we validated our findings in a validation cohort and an independent Japanese ccRCC cohort. We finally performed drug repositioning analysis based on transcriptomic expression profiles of drug-perturbed cancer cell lines and proposed that paracetamol, nizatidine, dimethadione and conessine can be repurposed to treat the patients in one of the subtype of ccRCC whereas chenodeoxycholic acid, fenoterol and hexylcaine can be repurposed to treat the patients in the other subtype.
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| 34. |
- Li, Xiangyu, et al.
(författare)
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Stratification of patients with clear cell renal cell carcinoma to facilitate drug repositioning
- 2021
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Ingår i: iScience. - : Elsevier BV. - 2589-0042. ; 24:7
-
Tidskriftsartikel (refereegranskat)abstract
- Clear cell renal cell carcinoma (ccRCC) is the most common histological type of kidney cancer and has high heterogeneity. Stratification of ccRCC is important since distinct subtypes differ in prognosis and treatment. Here, we applied a systems biology approach to stratify ccRCC into three molecular subtypes with different mRNA expression patterns and prognosis of patients. Further, we developed a set of biomarkers that could robustly classify the patients into each of the three subtypes and predict the prognosis of patients. Then, we reconstructed subtype-specific metabolic models and performed essential gene analysis to identify the potential drug targets. We identified four drug targets, including SOAT1, CRLS1, and ACACB, essential in all the three subtypes and GPD2, exclusively essential to subtype 1. Finally, we repositioned mitotane, an FDA-approved SOAT1 inhibitor, to treat ccRCC and showed that it decreased tumor cell viability and inhibited tumor cell growth based on in vitro experiments.
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| 35. |
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| 36. |
- Lindskog, Cecilia, et al.
(författare)
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The human cardiac and skeletal muscle proteomes defined by transcriptomics and antibody-based profiling
- 2015
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Ingår i: BMC Genomics. - : Springer Science and Business Media LLC. - 1471-2164. ; 16
-
Tidskriftsartikel (refereegranskat)abstract
- Background: To understand cardiac and skeletal muscle function, it is important to define and explore their molecular constituents and also to identify similarities and differences in the gene expression in these two different striated muscle tissues. Here, we have investigated the genes and proteins with elevated expression in cardiac and skeletal muscle in relation to all other major human tissues and organs using a global transcriptomics analysis complemented with antibody-based profiling to localize the corresponding proteins on a single cell level. Results: Our study identified a comprehensive list of genes expressed in cardiac and skeletal muscle. The genes with elevated expression were further stratified according to their global expression pattern across the human body as well as their precise localization in the muscle tissues. The functions of the proteins encoded by the elevated genes are well in line with the physiological functions of cardiac and skeletal muscle, such as contraction, ion transport, regulation of membrane potential and actomyosin structure organization. A large fraction of the transcripts in both cardiac and skeletal muscle correspond to mitochondrial proteins involved in energy metabolism, which demonstrates the extreme specialization of these muscle tissues to provide energy for contraction. Conclusions: Our results provide a comprehensive list of genes and proteins elevated in striated muscles. A number of proteins not previously characterized in cardiac and skeletal muscle were identified and localized to specific cellular subcompartments. These proteins represent an interesting starting point for further functional analysis of their role in muscle biology and disease.
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| 37. |
- Liu, Zhengtao, et al.
(författare)
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Meta-Analysis of Adiponectin as a Biomarker for the Detection of Metabolic Syndrome
- 2018
-
Ingår i: Frontiers in Physiology. - : Frontiers Media SA. - 1664-042X. ; 9:SEP
-
Forskningsöversikt (refereegranskat)abstract
- Previous studies revealed the potential significance of circulating adiponectin levels with respect to the diagnosis and prediction of metabolic syndrome, but uncertainty has been noted across different cohorts. Systematic evaluation was performed for diagnostic accuracy and predictivity of adiponectin variation for metabolic syndrome in enrolled studies including 1,248 and 6,020 subjects, respectively. Adiponectin can identify metabolic syndrome with moderate accuracy (area under the curve = 0.81, 95% CI: 0.77-0.84). Heterogeneity analysis revealed that an increasing index of insulin resistance was independently associated with improving the performance of adiponectin upon metabolic syndrome diagnosis (ratio of diagnostic odds ratio = 3.89, 95% CI: 1.13-13.9). In addition, reductions in adiponectin were associated with increasing metabolic syndrome incidence in a linear dose-response manner. The risk of hypoadiponectinemia with metabolic syndrome was especially increased in men (P < 0.05). Further Mendelian randomization analysis identified that the amplified risk could be attributed to increased susceptibility (up to 7%) to insulin resistance compared with women. In conclusion, adiponectin measurement might have potential benefits in the detection of metabolic syndrome. Factors that affect insulin resistance should be considered for adjustment in future assessments.
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| 38. |
- Liu, Zhengtao, et al.
(författare)
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Pyruvate kinase L/R is a regulator of lipid metabolism and mitochondrial function
- 2019
-
Ingår i: Metabolic Engineering. - : Elsevier BV. - 1096-7176 .- 1096-7184. ; 52, s. 263-272
-
Tidskriftsartikel (refereegranskat)abstract
- The pathogenesis of non-alcoholic fatty liver disease (NAFLD) and hepatocellular carcinoma (HCC) has been associated with altered expression of liver-specific genes including pyruvate kinase liver and red blood cell (PKLR), patatin-like phospholipase domain containing 3 (PNPLA3) and proprotein convertase subtilisin/kexin type 9 (PCSK9). Here, we inhibited and overexpressed the expression of these three genes in HepG2 cells, generated RNA-seq data before and after perturbation and revealed the altered global biological functions with the modulation of these genes using integrated network (IN) analysis. We found that modulation of these genes effects the total triglycerides levels within the cells and viability of the cells. Next, we generated IN for HepG2 cells, identified reporter transcription factors based on IN and found that the modulation of these genes affects key metabolic pathways associated with lipid metabolism (steroid biosynthesis, PPAR signalling pathway, fatty acid synthesis and oxidation) and cancer development (DNA replication, cell cycle and p53 signalling) involved in the progression of NAFLD and HCC. Finally, we observed that inhibition of PKLR lead to decreased glucose uptake and decreased mitochondrial activity in HepG2 cells. Hence, our systems level analysis indicated that PKLR can be targeted for development efficient treatment strategy for NAFLD and HCC.
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| 39. |
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| 40. |
- Lovric, Alen, et al.
(författare)
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Characterization of different fat depots in NAFLD using inflammation-associated proteome, lipidome and metabolome
- 2018
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Ingår i: Scientific Reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 8
-
Tidskriftsartikel (refereegranskat)abstract
- Non-alcoholic fatty liver disease (NAFLD) is recognized as a liver manifestation of metabolic syndrome, accompanied with excessive fat accumulation in the liver and other vital organs. Ectopic fat accumulation was previously associated with negative effects at the systemic and local level in the human body. Thus, we aimed to identify and assess the predictive capability of novel potential metabolic biomarkers for ectopic fat depots in non-diabetic men with NAFLD, using the inflammation-associated proteome, lipidome and metabolome. Myocardial and hepatic triglycerides were measured with magnetic spectroscopy while function of left ventricle, pericardial and epicardial fat, subcutaneous and visceral adipose tissue were measured with magnetic resonance imaging. Measured ectopic fat depots were profiled and predicted using a Random Forest algorithm, and by estimating the Area Under the Receiver Operating Characteristic curves. We have identified distinct metabolic signatures of fat depots in the liver (TAG50:1, glutamate, diSM18:0 and CE20:3), pericardium (N-palmitoyl-sphinganine, HGF, diSM18:0, glutamate, and TNFSF14), epicardium (sphingomyelin, CE20:3, PC38:3 and TNFSF14), and myocardium (CE20:3, LAPTGF-beta 1, glutamate and glucose). Our analyses highlighted non-invasive biomarkers that accurately predict ectopic fat depots, and reflect their distinct metabolic signatures in subjects with NAFLD.
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| 41. |
- Mardinoglu, Adil, 1982, et al.
(författare)
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An Integrated Understanding of the Rapid Metabolic Benefits of a Carbohydrate-Restricted Diet on Hepatic Steatosis in Humans
- 2018
-
Ingår i: Cell Metabolism. - : Elsevier BV. - 1550-4131 .- 1932-7420. ; 27:3
-
Tidskriftsartikel (refereegranskat)abstract
- A carbohydrate-restricted diet is a widely recommended intervention for non-alcoholic fatty liver disease (NAFLD), but a systematic perspective on the multiple benefits of this diet is lacking. Here, we performed a short-term intervention with an isocaloric low-carbohydrate diet with increased protein content in obese subjects with NAFLD and characterized the resulting alterations in metabolism and the gut microbiota using a multi-omics approach. We observed rapid and dramatic reductions of liver fat and other cardiometabolic risk factors paralleled by (1) marked decreases in hepatic de novo lipogenesis; (2) large increases in serum beta-hydroxybutyrate concentrations, reflecting increased mitochondrial beta-oxidation; and (3) rapid increases in folate-producing Streptococcus and serum folate concentrations. Liver transcriptomic analysis on biopsy samples from a second cohort revealed downregulation of the fatty acid synthesis pathway and upregulation of folate-mediated one-carbon metabolism and fatty acid oxidation pathways. Our results highlight the potential of exploring diet-microbiota interactions for treating NAFLD.
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| 42. |
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| 43. |
- Mardinoglu, Adil, 1982, et al.
(författare)
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Broad Views of Non-alcoholic Fatty Liver Disease
- 2018
-
Ingår i: Cell Systems. - : Elsevier BV. - 2405-4712 .- 2405-4720. ; 6:1, s. 37-51.e9
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- Multi-omics multi-tissue data are used to interpret genome-wide association study results from mice to identify key driver genes of non-alcoholic fatty liver disease. Non-alcoholic fatty liver disease (NAFLD) is the accumulation of fat (steatosis) in the liver due to causes other than excessive alcohol consumption. The disease may progress to more severe forms of liver diseases, including non-alcoholic steatohepatitis, cirrhosis, and hepatocellular carcinoma. In this issue of Cell Systems, Krishnan et al. (2018) reveal mechanisms underlying NAFLD by generating multi-omics data using liver and adipose tissues obtained from the Hybrid Mouse Diversity Panel, consisting of 113 mouse strains with various degrees of NAFLD. The study identified key driver genes of NAFLD that can be used in the development of efficient treatment strategies and illustrates the potential utility of systematic analysis of multi-layer biological networks. Multi-omics multi-tissue data are used to interpret genome-wide association study results from mice to identify key driver genes of non-alcoholic fatty liver disease. Non-alcoholic fatty liver disease (NAFLD) is the accumulation of fat (steatosis) in the liver due to causes other than excessive alcohol consumption. The disease may progress to more severe forms of liver diseases, including non-alcoholic steatohepatitis, cirrhosis, and hepatocellular carcinoma. In this issue of Cell Systems, Krishnan et al. (2018) reveal mechanisms underlying NAFLD by generating multi-omics data using liver and adipose tissues obtained from the Hybrid Mouse Diversity Panel, consisting of 113 mouse strains with various degrees of NAFLD. The study identified key driver genes of NAFLD that can be used in the development of efficient treatment strategies and illustrates the potential utility of systematic analysis of multi-layer biological networks.
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| 44. |
- Mardinoglu, Adil, 1982
(författare)
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Calculation of nanoparticle capture efficiency in magnetic drug targeting
- 2008
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Ingår i: Journal of Magnetism and Magnetic Materials. ; 320:23, s. 3272-3275
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Tidskriftsartikel (refereegranskat)abstract
- The implant assisted magnetic targeted drug delivery system of Avilés, Ebner and Ritter, which uses high gradient magnetic separation (HGMS) is considered. In this 2D model large ferromagnetic particles are implanted as seeds to aid collection of multiple domain nanoparticles (radius ). Here, in contrast, single domain magnetic nanoparticles (radius in 20–100 nm) are considered and the Langevin function is used to describe the magnetization. Simulations based on this model were performed using the open source C++ finite volume library OpenFOAM. The simulations indicate that use of the Langevin function predicts greater collection efficiency than might be otherwise expected.
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| 45. |
- Mardinoglu, Adil, 1982, et al.
(författare)
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Confounding effects of metformin on the human gut microbiome in Type 2 diabetes
- 2016
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Ingår i: Cell Metabolism. - : Elsevier BV. - 1550-4131 .- 1932-7420. ; 23:1, s. 10-12
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Tidskriftsartikel (refereegranskat)abstract
- Type 2 diabetes (T2D) is associated with dysbiosis of the gut microbiota, though diabetes treatment regimens, including metformin, may confound the results. Forslund et al. (2015) identify distinct disease and drug signatures and highlight the importance of adjusting for treatment when investigating how T2D influences the human gut microbiome.
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| 46. |
- Mardinoglu, Adil, 1982, et al.
(författare)
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Defining the Human Adipose Tissue Proteome To Reveal Metabolic Alterations in Obesity
- 2014
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Ingår i: Journal of Proteome Research. - : American Chemical Society (ACS). - 1535-3893 .- 1535-3907. ; 13:11, s. 5106-5119
-
Tidskriftsartikel (refereegranskat)abstract
- White adipose tissue (WAT) has a major role in the progression of obesity. Here, we combined data from RNA-Seq and antibody-based immunohistochemistry to describe the normal physiology of human WAT obtained from three female subjects and explored WAT-specific genes by comparing WAT to 26 other major human tissues. Using the protein evidence in WAT, we validated the content of a genome-scale metabolic model for adipocytes. We employed this high-quality model for the analysis of subcutaneous adipose tissue (SAT) gene expression data obtained from subjects included in the Swedish Obese Subjects Sib Pair study to reveal molecular differences between lean and obese individuals. We integrated SAT gene expression and plasma metabolomics data, investigated the contribution of the metabolic differences in the mitochondria of SAT to the occurrence of obesity, and eventually identified cytosolic branched-chain amino acid (BCAA) transaminase 1 as a potential target that can be used for drug development. We observed decreased glutaminolysis and alterations in the BCAAs metabolism in SAT of obese subjects compared to lean subjects. We also provided mechanistic explanations for the changes in the plasma level of BCAAs, glutamate, pyruvate, and alpha-ketoglutarate in obese subjects. Finally, we validated a subset of our model-based predictions in 20 SAT samples obtained from 10 lean and 10 obese male and female subjects.
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| 47. |
- Mardinoglu, Adil, 1982
(författare)
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Development of artificial neuronal networks for molecular communication
- 2011
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Ingår i: Nano Communication Networks. - : Elsevier BV. - 1878-7789. ; 2:2-3, s. 150-160
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Tidskriftsartikel (refereegranskat)abstract
- Communication at the nanoscale can enhance capabilities for nanodevices, and at the same time open new opportunities for numerous healthcare applications. One approach toward enabling communication between nanodevices is through molecular communications. While a number of solutions have been proposed for molecular communication (e.g. calcium signaling, molecular motors, bacteria communication), in this paper, we propose the use of neuronal networks for molecular communication network. In particular, we provide two design aspects of neuron networks, which includes, (i) the design of an interface between nanodevice and neurons that can initiate signaling, and (ii) the design of transmission scheduling to ensure that signals initiated by multiple devices will successfully reach the receiver with minimum interference. The solution for (i) is developed through wet lab experiments, while the solution for (ii) is developed through genetic algorithm optimization technique, and is validated through simulations.
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| 48. |
- Mardinoglu, Adil, 1982, et al.
(författare)
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Elevated Plasma Levels of 3-Hydroxyisobutyric Acid Are Associated With Incident Type 2 Diabetes
- 2018
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Ingår i: Ebiomedicine. - : Elsevier BV. - 2352-3964. ; 27, s. 151-155
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Tidskriftsartikel (refereegranskat)abstract
- Branched-chain amino acids (BCAAs) metabolite, 3-Hydroxyisobutyric acid (3-HIB) has been identified as a secreted mediator of endothelial cell fatty acid transport and insulin resistance (IR) using animal models. To identify if 3-HIB is a marker of human IR and future risk of developing Type 2 diabetes (T2D), we measured plasma levels of 3-HIB and associated metabolites in around 10,000 extensively phenotyped individuals. The levels of 3-HIB were increased in obesity but not robustly associated with degree of IR after adjusting for BMI. Nevertheless, also after adjusting for obesity and plasma BCAA, 3-HIB levels were associated with future risk of incident T2D. We also examined the effect of 3-HIB on fatty acid uptake in human cells and found that both HUVEC and human cardiac endothelial cells respond to 3-HIB whereas human adipose tissue-derived endothelial cells do not respond to 3-HIB. In conclusion, we found that increased plasma level of 3-HIB is a marker of future risk of T2D and 3-HIB may be important for the regulation of metabolic flexibility in heart and muscles.
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| 49. |
- Mardinoglu, Adil, 1982, et al.
(författare)
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Genome-scale modeling of human metabolism - a systems biology approach.
- 2013
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Ingår i: Biotechnology journal. - : Wiley. - 1860-6768 .- 1860-7314. ; 8:9, s. 985-996
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Forskningsöversikt (refereegranskat)abstract
- Altered metabolism is linked to the appearance of various human diseases and a better understanding of disease-associated metabolic changes may lead to the identification of novel prognostic biomarkers and the development of new therapies. Genome-scale metabolic models (GEMs) have been employed for studying human metabolism in a systematic manner, as well as for understanding complex human diseases. In the past decade, such metabolic models – one of the fundamental aspects of systems biology – have started contributing to the understanding of the mechanistic relationship between genotype and phenotype. In this review, we focus on the construction of the Human Metabolic Reaction database, the generation of healthy cell type- and cancer-specific GEMs using different procedures, and the potential applications of these developments in the study of human metabolism and in the identification of metabolic changes associated with various disorders. We further examine how in silico genome-scale reconstructions can be employed to simulate metabolic flux distributions and how high-throughput omics data can be analyzed in a context-dependent fashion. Insights yielded from this mechanistic modeling approach can be used for identifying new therapeutic agents and drug targets as well as for the discovery of novel biomarkers. Finally, recent advancements in genome-scale modeling and the future challenge of developing a model of whole-body metabolism are presented. The emergent contribution of GEMs to personalized and translational medicine is also discussed.
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| 50. |
- Mardinoglu, Adil, 1982
(författare)
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Inclusion of magnetic dipole–dipole and hydrodynamic interactions in implant-assisted magnetic drug targeting
- 2009
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Ingår i: Journal of Magnetism and Magnetic Materials. - 0304-8853. ; 321:23, s. 3893-3898
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Tidskriftsartikel (refereegranskat)abstract
- Mathematical modelling of the implant-assisted magnetic drug targeting system of Avilés, Ebner and Ritter is performed. In order to model the agglomeration of particles known to occur in this system, the magnetic dipole–dipole and hydrodynamic interactions are included. Such interactions were calculated previously by Mikkelsen et al. under low magnetic fields (~0.05 T) in microfluidic systems. Here, a higher magnetic field (0.7 T) is considered and the effect of interactions on two nanoparticles with a seed implant is calculated. The calculations were performed with the open-source software OpenFOAM. Different initial positions are considered and the system performance is assessed in terms of capture cross section. Inclusion of both interactions was seen to alter the capture cross section of the system by up to 7% in absolute terms.
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