Size determination of hyaluronan using a gas-phase electrophoretic mobility molecular analysis.

Hyaluronan (HA) is a linear non-sulfated polysaccharide mainly found in the extracellular matrix. The size of HA can vary from a few disaccharides up to at least 25,000 units, reaching molecular weights of 10 10(3) kDa. HA has many biological functions, and both its size and tissue concentration play an important role in many physiological and pathological processes. It is relatively easy to determine the HA concentration using enzyme-linked binding protein assays, but the molecular weight of HA has so far been shown to be a more challenging task to measure. Here, we present a method for size determination of HA using gas-phase electrophoretic mobility molecular analysis (GEMMA), which utilizes the electrophoretic mobility of molecules in air to estimate the molecular weight of the analyte. We show that this method gives reliable molecular weight estimations of HA in the range of 30-2400 kDa, which covers almost its whole biological range. The average measuring time for one GEMMA spectrum is between 5 and 10 min using only 6 pg of HA. In addition, the peak area in a GEMMA spectrum can be used to estimate the HA concentration in the sample. The high sensitivity and small sample volumes make GEMMA an excellent tool for both size determinations and estimation of concentration of samples with low HA concentration, as is the case for HA extracted from small tissue samples.

Metabolomic Quality Assessment of EDTA Plasma and Serum Samples.

Handling and processing of blood can significantly alter the molecular composition and consistency of biobank samples and can have a major impact on the identification of biomarkers. It is thus crucial to identify tools to determine the quality of samples to be used in biomarker discovery studies. In this study, a non-targeted gas chromatography/time-of-flight mass spectrometry (GC-TOFMS) metabolomic strategy was used with the aim of identifying quality markers for serum and plasma biobank collections lacking proper documentation of preanalytical handling. The effect of postcentrifugation delay was examined in serum stored in tubes with gel separation plugs and ethylenediaminetetraacetic acid (EDTA) plasma in tubes with or without gel separation plugs. The change in metabolic pattern was negligible in all sample types processed within 3 hours after centrifugation regardless of whether the samples were kept at 4°C or 22°C. After 8 and 24 hours postcentrifugation delay before aliquoting, there was a pronounced increase in the number of affected metabolites, as well as in the magnitude of the observed changes. No protective effect on the metabolites was observed in gel-separated EDTA plasma samples. In a separate series of experiments, lactate and glucose levels were determined in plasma to estimate the effect of precentrifugation delay. This separate experiment indicates that the lactate to glucose ratio may serve as a marker to identify samples with delayed time to centrifugation. Although our data from the untargeted GC-TOFMS analysis did not identify any specific markers, we conclude that plasma and serum metabolic profiles remain quite stable when plasma and serum are centrifuged and separated from the blood cells within 3 hours.

Metabolite and peptide levels in plasma and CSF differentiating healthy controls from patients with newly diagnosed Parkinson's disease.

BACKGROUND: Parkinson's disease (PD) is a progressive, multi-focal neurodegenerative disease for which there is no effective disease modifying treatment. A critical requirement for designing successful clinical trials is the development of robust and reproducible biomarkers identifying PD in preclinical stages. OBJECTIVE: To investigate the potential for a cluster of biomarkers visualized with multiple analytical platforms to provide a clinically useful tool. METHODS: Gas Chromatography-Mass Spectrometry (GC-TOFMS) based metabolomics and immunoassay-based protein/peptide analyses on samples from patients with PD diagnosed in Northern Sweden. Low molecular weight compounds from both plasma and cerebrospinal fluid (CSF) from 20 healthy subjects (controls) and 20 PD patients at the time of diagnosis (baseline) were analyzed. RESULTS: In plasma, we found a significant increase in several amino acids and a decrease in C16-C18 saturated and unsaturated fatty acids in patients as compared to control subjects. We also observed an increase in plasma levels of pyroglutamate and 2-oxoisocaproate (ketoleucine) that may be indicative of increased metabolic stress in patients. In CSF, there was a generally lower level of metabolites in PD as compared to controls, with a specific decrease in 3-hydroxyisovaleric acid, tryptophan and creatinine. Multivariate analysis and modeling of metabolites indicates that while the PD samples can be separated from control samples, the list of detected compounds will need to be expanded in order to define a robust predictive model. CSF biomarker immunoassays of candidate peptide/protein biomarkers revealed a significant decrease in the levels of Aß-38 and Aß-42, and an increase in soluble APPα in CSF of patients. Furthermore, these peptides showed significant correlations to each other, and positive correlations to the CSF levels of several 5- and 6-carbon sugars. However, combining these metabolites and proteins/peptides into a single model did not significantly improve the statistical analysis. CONCLUSIONS: Together, this metabolomics study has detected significant alterations in plasma and CSF levels of a cluster of amino acids, fatty acids and sugars based on clinical diagnosis and levels of known protein and peptide biomarkers.

Using OPLS-DA to find new hypotheses in vast amounts of gene expression data - studying the progression of cardiac hypertrophy in the heart of aorta ligated rat.

One of the great problems facing science today lies in data mining of the vast amount of data. In this study we explore a new way of using orthogonal partial least squares-discrimination analysis (OPLS-DA) to analyze multidimensional data. Myocardial tissues from aorta ligated and control rats (sacrificed at the acute, the adaptive and the stable phases of hypertrophy) were analyzed with whole genome microarray and OPLS-DA. Five functional gene transcript groups were found to show interesting clusters associated with the aorta ligated or the control animals. Clustering of "ECM and adhesion molecules" confirmed previous results found with traditional statistics. The clustering of "Fatty acid metabolism", "Glucose metabolism", "Mitochondria" and "Atherosclerosis" which are new results is hard to interpret, thereby being possible subject to new hypothesis formation. We propose that OPLS-DA is very useful in finding new results not found with traditional statistics, thereby presenting an easy way of creating new hypotheses.

Growth factor stimulation of cardiomyocytes induces changes in the transcriptional contents of secreted exosomes.

Exosomes are nano-sized extracellular vesicles, released from various cells, which can stimulate or repress responses in targets cells. We recently reported that cultured cardiomyocytes are able to release exosomes and that they, in turn, are involved in facilitating events in target cells by alteration of gene expression. We investigated whether external stimuli of the cardiomyocyte might influence the transcriptional content of the released exosomes. Exosomes were isolated from media collected from cultured cardiomyocytes (HL-1) with or without growth factor treatment (TGF-ß2 and PDGF-BB), with a series of differential centrifugations, including preparative ultracentrifugation and separation with a sucrose gradient. The exosomes were characterized with dynamic light scattering (DLS), electron microscopy (EM) and Western blot and analyzed with Illumina whole genome microarray gene expression. The exosomes were rounded in shape and had an average size of 50-90 nm in diameter with no difference between treatment groups. Analysis of the mRNA content in repeated experiments conclusively revealed 505 transcripts in the control group, 562 in the TGF-ß2-treated group and 300 in the PDGF-BB-treated group. Common transcripts (217) were found in all 3 groups. We show that the mode of stimulation of parental cells affects the characteristics of exosomes released. Hence, there is a difference in mRNA content between exosomes derived from cultured cardiomyocytes stimulated, or not stimulated, with growth factors. We also conclude that all exosomes contain a basic package consisting of ribosomal transcripts and mRNAs coding for proteins with functions within the energy supply system.

Growth factor PDGF-BB stimulates cultured cardiomyocytes to synthesize the extracellular matrix component hyaluronan.

BACKGROUND: Hyaluronan (HA) is a glycosaminoglycan located in the interstitial space which is essential for both structural and cell regulatory functions in connective tissue. We have previously shown that HA synthesis is up-regulated in a rat model of experimental cardiac hypertrophy and that cardiac tissue utilizes two different HA synthases in the hypertrophic process. Cardiomyocytes and fibroblasts are two major cell types in heart tissue. The fibroblasts are known to produce HA, but it has been unclear if cardiomyocytes share the same feature, and whether or not the different HA synthases are activated in the different cell types. METHODOLOGY/PRINCIPAL FINDINGS: This study shows, for the first time that cardiomyocytes can produce HA. Cardiomyocytes (HL-1) and fibroblasts (NIH 3T3) were cultivated in absence or presence of the growth factors FGF2, PDGF-BB and TGFB2. HA concentration was quantified by ELISA, and the size of HA was estimated using dynamic light scattering. Cardiomyocytes synthesized HA but only when stimulated by PDGF-BB, whereas fibroblasts synthesized HA without addition of growth factors as well as when stimulated by any of the three growth factors. When fibroblasts were stimulated by the growth factors, reverse dose dependence was observed, where the highest dose induced the least amount of HA. With the exception of TGFB2, a trend of reverse dose dependence of HA size was also observed. CONCLUSIONS/SIGNIFICANCE: Co-cultivation of cardiomyocytes and fibroblasts (80%/20%) increased HA concentration far more that can be explained by HA synthesis by the two cell types separately, revealing a crosstalk between cardiomyocytes and fibroblasts that induces HA synthesis. We conclude that dynamic changes of the myocardium, such as in cardiac hypertrophy, do not depend on the cardiomyocyte alone, but are achieved when both cardiomyocytes and fibroblasts are present.