Mesenchymal stem cells. A review

Neðst á síðunni er hægt að nálgast greinina í heild sinni með því að smella á hlekkinn View/OpenThe bone marrow contains various types of stem cells. Among them are hematopoietic stem cells, which are the precursors of all blood cells, and mesenchymal stem cells. Mesenchymal stem cells have recently received a lot of attention in biological research because of their capability to self renewal, to expand and transdifferentiate into many different cell types; bone cells, adipocytes, chondrocytes, tendocytes, neural cells and stromal cells of the bone marrow. Mesenchymal stem cells can be cultured in vitro although their differentiation potential is not yet fully understood. Several experiments have been conducted in animal models where mesenchymal stem cells have been transplanted in order to enhance hematopoiesis or to facilitate the repair of mesenchymal tissue. Similar experiments are being conducted in humans. Mesenchymal stem cells are believed to be able to enhance hematopoietic stem cells transplantation by rebuilding the bone marrow microenvironment which is damaged after radiation- and/or chemotherapy. Mesenchymal stem cells are promising as vehicles for gene transfer and therapy. It may prove possible to tranduce them with a gene coding for a defective protein i.e. collagen I in osteogenesis imperfecta. The cells could then be expanded ex vivo and transplanted to the patients where they home to the bone marrow, differentiate and produce the intact protein. Future medicine will probably involve mesenchymal stem cells in various treatment settings.Í beinmergnum er að finna ýmsar gerðir stofnfrumna. Meðal þeirra eru blóðmyndandi stofnfrumur (hematopoietic stem cells) og bandvefsstofnfrumur (mesenchymal stem cells). Rannsóknir á líffræði bandvefsstofnfrumna benda til að þær hafi hæfileika til að endurnýja sjálfar sig, fjölga sér og sérhæfast í margar mismunandi frumugerðir: beinfrumur, fitufrumur, brjóskfrumur, frumur sina, taugafrumur og stoðfrumur beinmergs (stromal cells). Mögulegt er að rækta þessar frumur in vitro þó ekki sé til fullnustu þekkt hvernig sérhæfing þeirra á sér stað. Í fjölmörgum dýratilraunum hafa bandvefsstofnfrumur verið græddar í dýrin með það fyrir augum að laga mismunandi tegundir bandvefs og/eða ýta undir blóðmyndun. Tilraunir í mönnum hafa verið gerðar í svipuðum tilgangi. Bandvefsstofnfrumur eru taldar geta eflt ígræðslur með blóðmyndandi stofnfrumum með því að byggja upp beinmergsumhverfið sem verður fyrir skemmdum við geisla- og/eða lyfjameðferð. Bandvefsstofnfrumur eru ákjósanlegar sem markfrumur í genameðferð. Hægt er að setja inn í þær gen sem skráir fyrir ákveðnu prótíni sem skortur er á, til dæmis kollageni I í beinbrotasýki (osteogenesis imperfecta). Síðan eru frumurnar látnar fjölga sér ex vivo og græddar í sjúkling þar sem þær rata sjálfkrafa í beinmerginn, sérhæfast og mynda það prótín sem vantar. Bandvefsstofnfrumur munu væntanlega nýtast við meðhöndlun ýmissa sjúkdóma í framtíðinni

Elucidating dynamic metabolic physiology through network integration of quantitative time-course metabolomics.

Efst á síðunni er hægt að nálgast greinina í heild sinni með því að smella á hlekkinn To access publisher's full text version of this article. Please click on the hyperlink in Additional Links field.The increasing availability of metabolomics data necessitates novel methods for deeper data analysis and interpretation. We present a flux balance analysis method that allows for the computation of dynamic intracellular metabolic changes at the cellular scale through integration of time-course absolute quantitative metabolomics. This approach, termed "unsteady-state flux balance analysis" (uFBA), is applied to four cellular systems: three dynamic and one steady-state as a negative control. uFBA and FBA predictions are contrasted, and uFBA is found to be more accurate in predicting dynamic metabolic flux states for red blood cells, platelets, and Saccharomyces cerevisiae. Notably, only uFBA predicts that stored red blood cells metabolize TCA intermediates to regenerate important cofactors, such as ATP, NADH, and NADPH. These pathway usage predictions were subsequently validated through (13)C isotopic labeling and metabolic flux analysis in stored red blood cells. Utilizing time-course metabolomics data, uFBA provides an accurate method to predict metabolic physiology at the cellular scale for dynamic systems.National Heart Lung and Blood Institute European Research Council U.S. Department of Energ

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

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

Gold nanoisland substrates for SERS characterization of cultured cells.

To access publisher's full text version of this article, please click on the hyperlink in Additional Links field or click on the hyperlink at the top of the page marked DownloadWe demonstrate a simple approach for fabricating cell-compatible SERS substrates, using repeated gold deposition and thermal annealing. The substrates exhibit SERS enhancement up to six orders of magnitude and high uniformity. We have carried out Raman imaging of fixed mesenchymal stromal cells cultured directly on the substrates. Results of viability assays confirm that the substrates are highly biocompatible and Raman imaging confirms that cell attachment to the substrates is sufficient to realize significant SERS enhancement of cellular components. Using the SERS substrates as an in vitro sensing platform allowed us to identify multiple characteristic molecular fingerprints of the cells, providing a promising avenue towards non-invasive chemical characterization of biological samples.Icelandic Centre for Research Haskoli Islands European Research Council (ERC

Visualizing metabolic network dynamics through time-series metabolomic data.

BACKGROUND: New technologies have given rise to an abundance of -omics data, particularly metabolomic data. The scale of these data introduces new challenges for the interpretation and extraction of knowledge, requiring the development of innovative computational visualization methodologies. Here, we present GEM-Vis, an original method for the visualization of time-course metabolomic data within the context of metabolic network maps. We demonstrate the utility of the GEM-Vis method by examining previously published data for two cellular systems-the human platelet and erythrocyte under cold storage for use in transfusion medicine. RESULTS: The results comprise two animated videos that allow for new insights into the metabolic state of both cell types. In the case study of the platelet metabolome during storage, the new visualization technique elucidates a nicotinamide accumulation that mirrors that of hypoxanthine and might, therefore, reflect similar pathway usage. This visual analysis provides a possible explanation for why the salvage reactions in purine metabolism exhibit lower activity during the first few days of the storage period. The second case study displays drastic changes in specific erythrocyte metabolite pools at different times during storage at different temperatures. CONCLUSIONS: The new visualization technique GEM-Vis introduced in this article constitutes a well-suitable approach for large-scale network exploration and advances hypothesis generation. This method can be applied to any system with data and a metabolic map to promote visualization and understand physiology at the network level. More broadly, we hope that our approach will provide the blueprints for new visualizations of other longitudinal -omics data types. The supplement includes a comprehensive user\u27s guide and links to a series of tutorial videos that explain how to prepare model and data files, and how to use the software SBMLsimulator in combination with further tools to create similar animations as highlighted in the case studies

Quantitative time-course metabolomics in human red blood cells reveal the temperature dependence of human metabolic networks

To access publisher's full text version of this article click on the hyperlink belowThe temperature dependence of biological processes has been studied at the levels of individual biochemical reactions and organism physiology (e.g. basal metabolic rates) but has not been examined at the metabolic network level. Here, we used a systems biology approach to characterize the temperature dependence of the human red blood cell (RBC) metabolic network between 4 and 37 °C through absolutely quantified exo- and endometabolomics data. We used an Arrhenius-type model (Q10) to describe how the rate of a biochemical process changes with every 10 °C change in temperature. Multivariate statistical analysis of the metabolomics data revealed that the same metabolic network-level trends previously reported for RBCs at 4 °C were conserved but accelerated with increasing temperature. We calculated a median Q10 coefficient of 2.89 ± 1.03, within the expected range of 2-3 for biological processes, for 48 individual metabolite concentrations. We then integrated these metabolomics measurements into a cell-scale metabolic model to study pathway usage, calculating a median Q10 coefficient of 2.73 ± 0.75 for 35 reaction fluxes. The relative fluxes through glycolysis and nucleotide metabolism pathways were consistent across the studied temperature range despite the non-uniform distributions of Q10 coefficients of individual metabolites and reaction fluxes. Together, these results indicate that the rate of change of network-level responses to temperature differences in RBC metabolism is consistent between 4 and 37 °C. More broadly, we provide a baseline characterization of a biochemical network given no transcriptional or translational regulation that can be used to explore the temperature dependence of metabolism.European Research Council United States Department of Energy NHLBI, National Institutes of Healt

Stofnfrumur - tækifæri eða tálsýn? [myndefni]

Hægt er að horfa á fyrirlesturinn með því að smella á hlekkinn hér fyrir neðan - ATH, einungis er hægt að horfa á fyrirlesturinn úr tölvum tengdum spítalanetinu.Sveinn Guðmundsson, yfirlæknir Blóðbankans og Dr. Ólafur E. Sigurjónsson, forstöðumaður stofnfrumuvinnslu Blóðbankans og lektor við H.R. fjalla um hvað stofnfrumur eru og hvernig má nota þær, klínískar tilraunir og samstarfsverkefni við Blóðlækningadeild LSH. Sveinn ræðir um hverning þetta málefni horfir við almenningi og hvaða vonir og væntingar gera vart við sig þegar málefni um stofnfrumur ber á góma. Heilbrigðisyfirvöld þurfa framtíðarsýn á þessu sviði. Stofnfrumumeðferð opnar leið fyrir aðra framþróun í framtíðinni. - Lengd: 62 mínútu

Stofnfrumur - tækifæri eða tálsýn? [myndefni]

Hægt er að horfa á fyrirlesturinn með því að smella á hlekkinn hér fyrir neðan - ATH, einungis er hægt að horfa á fyrirlesturinn úr tölvum tengdum spítalanetinu.Sveinn Guðmundsson, yfirlæknir Blóðbankans og Dr. Ólafur E. Sigurjónsson, forstöðumaður stofnfrumuvinnslu Blóðbankans og lektor við H.R. fjalla um hvað stofnfrumur eru og hvernig má nota þær, klínískar tilraunir og samstarfsverkefni við Blóðlækningadeild LSH. Sveinn ræðir um hverning þetta málefni horfir við almenningi og hvaða vonir og væntingar gera vart við sig þegar málefni um stofnfrumur ber á góma. Heilbrigðisyfirvöld þurfa framtíðarsýn á þessu sviði. Stofnfrumumeðferð opnar leið fyrir aðra framþróun í framtíðinni. - Lengd: 62 mínútu

New strategies to understand platelet storage lesion

To access publisher's full text version of this article click on the hyperlink belowModern health care is dependent on the banking and transfusion of platelet concentrates. Platelets, however, can pose a problem for stock management at blood banks due to their limited storage time. In most countries, platelets can be stored from 3 to 7 days and due limited storage time up to 30% of all platelet concentrates are discarded without ever being used for clinical transfusion. The main reasons for this limited storage time are increased risk of bacterial contamination, due to the storage conditions at 22°C, and a formation of a condition termed platelet storage lesion (PSL) that decreases the quality of the platelets and makes them less efficient for clinical use as the storage prolongs. Increased understanding of PSL formation and how it can be combated is important to increase the quality of platelets during storage, in turn making them more efficient for clinical use. There are several methods used to detect formation of PSL, including analysing expression of surface markers on platelets using flow cytometry, analysing function of platelets using light transmission aggregometry and release of cytokines and growth factors using, for example ELISA. However, those methods focus more on studying the consequence of PSL instead of the cause of PSL. In recent years, several laboratories, including ours, have been using novel ways to further try to understand the formation of PSL. These include, for example analysing changes in proteomics, miRNA and metabolomics in platelets during storage. In this short overview, we will review how novel methods have been used to shed new lights on the formation of PSL