| 1. |
- 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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| 2. |
- 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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| 3. |
- 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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| 4. |
- 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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| 5. |
- Kampf, Caroline, et al.
(författare)
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The human liver-specific proteome defined by transcriptomics and antibody-based profiling
- 2014
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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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| 6. |
- 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
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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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| 7. |
- 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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| 8. |
- 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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| 9. |
- 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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| 10. |
- 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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