Murat Eravci

Concentrations of Seven Iodothyronine Metabolites in Brain Regions and the Liver of the Adult Rat

The concentrations of the iodothyronine metabolites T4 ,T 3, 3,5-diiodothyronine (3,5-T2), 3,3-diiodothyronine (3,3-T2), reverse T3 (rT3), 3,3-T2 sulfate (3,3T2S), and T3 sulfate (T3S) were measured in 12 regions of the brain, the pituitary gland, and liver in adult male rats. Quantification of iodothyronine was performed by RIA following a newly developed method of purification and separation by HPLC. 3,5-T2, 3,3-T2 ,r T 3 and T2S were detectable in the low femtomolar range (20 –200 fmol/g) in most areas of the rat brain. T3S was detectable only in the hypothalamus. The concentrations of T3 and T4 were approximately 20- to 60-fold higher, ranging between 1 and 6 pmol/g. There was a significant negative correlation between the activities of inner-ring deiodinase and T3 concentrations across brain areas. In the liver, 3,5-T2 ,r T3, and T3S were measurable in the low femtomolar range, whereas 3,3-T2 and 3,3T2S were not detectable. 3,5-T2 and 3,3-T2 were not detectable in mitochondrial fractions of the brain regions. Tissue concentrations of 3,5-T2 exhibited a circadian variation closely parallel to those of T3 in the brain regions and liver. T3 was not a substrate for outer-ring deiodination under different experimental conditions; thus, it remains unclear which substrate(s) and enzyme(s) are involved in the production of 3,5-T2. These results indicate that five iodothyronine metabolites other than T3 and T4 are detectable in the low femtomolar range in the rat brain and/or liver. The physiological implications of this finding are discussed. (Endocrinology 143: 1789 –1800, 2002)

Effects of lithium and carbamazepine on thyroid hormone metabolism in rat brain

The effects of lithium (LI) and carbamazepine (CBM) on thyroid hormone metabolism were investigated in 11 regions of the brain and three peripheral tissues in rats decapitated at three different times of day (4:00 a.m., 1:00 p.m., and 8:00 p.m.). Interest was focused on the changes in the two enzymes that catalyze: (1) the 5′deiodination of T4 to the biologically active T3, i.e., type II 5′deiodinase (5′D-II) and (2) the 5 (or inner-ring) deiodination of T3 to the biologically inactive 3′3-T2, i.e., type III 5 deiodinase (5D-III). A 14-day treatment with both LI and CBM induced significant reductions in 5D-III activity. However, 5′D-II activity was elevated by CBM and reduced by LI, both administered in concentrations leading to serum levels comparable with those seen in the prophylactic treatment of affective disorders. The effects were dose dependent, varied according to the region of the brain under investigation, and strongly depended on the time of death within the 24-hour rhythm. The consequences of these complex effects of LI and CBM on deiodinase activities for thyroid hormone function in the CNS and also their possible involvement in the mechanisms underlying the mood-stabilizing effects of both LI and CBM remain to be investigated.

Improved comparative proteome analysis based on two-dimensional gel electrophoresis.

The purpose of this study was to test the extent to which differences in spot intensity can be reliably recognized between two groups of two‐dimensional electrophoresis gels (pHu20054–7, visualized with ruthenium fluorescent stain) each loaded with different amounts of protein from rat brain (power analysis). Initial experiments yielded only unsatisfactory results: 546 spots were matched from two groups of 6 gels each loaded with 200u2005µg and 250u2005µg protein, respectively. Only 72 spots were higher (p<0.05), while 58 spots were significantly lower in the 250‐µg group. The construction of new apparatuses that allowed the simultaneous processing of 24 gels throughout all steps between rehydration and staining procedure considerably lowered the between‐gel variation. This resulted in the detection of significant differences in spot intensities in 77–90% of all matched spots on gel groups with a 25% difference in protein load. This applied both when protein from 24 biological replicates was loaded onto two groups of 12 gels and when two pooled tissue samples were each loaded onto 6 gels. At a difference of 50% in protein load, more than 90% of all spots differed significantly between two experimental groups.

Results and reliability of protein quantification for two-dimensional gel electrophoresis strongly depend on the type of protein sample and the method employed

We investigated the effects of tissue samples taken from rat brain on the reliability of three protein quantification kits: the Bradford assay, the 2‐D Quant Kit, and the EZQ Protein Quantitation Kit. All three assays measured significantly smaller amounts of protein after extraction than the reference values before extraction. Only small effects were seen in homogenates, but very pronounced differences in membrane‐enriched and highly lipophilic subcellular fractions. Researchers should evaluate which method of protein quantification is best qualified for their specific experimental design.

Technical strategies to reduce the amount of "false significant" results in quantitative proteomics.

When the p‐value is set at <0.05 in statistical group comparisons, a 5% rate of “false significant” results is expected. In order to test the reliability of our 2‐DE method, we loaded each of 24 gels with equal‐sized samples (200u2005μg protein from pooled rat brain, pHu20054–7, stained with ruthenium fluorescent stain for visualization) and statistically compared the first 12 gels with the last 12. In numerous experiments the rate of significant differences found far exceeded 5%. Several factors were identified as causing the following rates of false significant differences in spot intensities: (i) running samples in two different 2‐DE runs (42%), (ii) running second dimension gels produced in two different gel casters (16%), (iii) normalizing the entire gel instead of separately normalizing several different gel zones (11%), (iv) using IPG strips from different packages (19%), (v) dividing the whole sample into subgroups during software analysis (9%). After controlling for all these factors, the rates of “false positive” results in our experiments were regularly reduced to approximately 5%. This is an indispensable prerequisite for avoiding too high a rate of false positive results in experiments in which different subgroups are compared statistically.

The whereabouts of transmembrane proteins from rat brain synaptosomes during two‐dimensional gel electrophoresis

Little is known about what happens to transmembrane proteins (TMP) in 2‐DE. In order to obtain more insight into the whereabouts of these proteins we prepared membrane‐enriched synaptosomes from rat frontal cortex and washed them with 7u2005M urea or Na2CO3. From each preparation, 200u2005µg protein was loaded on 2‐DE gels covering the 4–7 and 6–11 pH ranges, respectively. MALDI‐MS/MS analysis detected only 3 TMP among 421 identified spots. However, when the samples had been washed with Na2CO3, only few well‐focused spots remained detectable on the gel covering the pH 6–11 range. Instead, a heavily ruthenium‐stained smear became visible at the upper edge of the gel at the location where the samples had been applied by cup loading. LC‐MS/MS analysis revealed that this smear contained 38 unfocused TMP with up to 12 transmembrane helices. After transfer to the second dimension, no major areas of protein staining were left on the IPG strips. This indicates that after extraction and denaturation the TMP may form high‐molecular aggregates, due to their “hydrophobic interactions”. These aggregates enter the IPG strips, but do not focus regularly. They are then transferred onto the 2‐DE‐gels, where they remain caught at the upper edge.

Effects of thawing, refreezing and storage conditions of tissue samples and protein extracts on 2-DE spot intensity

We report that reliable quantitative proteome analyses can be performed with tissue samples stored at −80°C for up to 10 years. However, storing protein extracts at 4°C for 24u2009h and freezing protein extracts at −80°C and thawing them significantly altered 41.6 and 17.5% of all spot intensities on 2‐DE gels, respectively. Fortunately, these storing effects did not impair the reliability of quantifying 2‐DE experiments. Nonetheless, the results show that freezing and storage conditions should be carefully controlled in proteomic experiments.

In-Gel 18O Labeling for Improved Identification of Proteins from 2-DE Gel Spots in Comparative Proteomic Experiments

The reliability of 2-DE gel-based comparative proteomics is severely impaired by the potential presence of overlapping proteins. We describe a methodological procedure which may solve this problem. Corresponding protein spots from two experimental groups are digested in the presence of 16O and 18O, respectively. Samples are pooled and proteins identified by MS. The 18O/16O-ratios of the different proteins found in the same spot distinguish proteins with altered from those whose intensity is unchanged.

Strategies for a Reliable Biostatistical Analysis of Differentially Expressed Spots from Two-Dimensional Electrophoresis Gels

We performed quantitative comparisons with the two-dimensional gel electrophoresis technique and evaluated the reliability of biostatistical tests for the correction of false significant results (alpha-error) by performing repeated runs of an experiment. Results based on uncorrected p-values yielded numerous significant differences in spot intensity which could not be replicated in two additional runs. The best strategy for avoiding these false-positive results was strongly dependent on the type of result. In experiments yielding very marked group differences in spot intensity, calculation of the False Discovery Rate (FDR) by the Benjamini and Hochberg method corrected the results with sufficient reliability. In experiments yielding relatively small (p-values>0.001) group differences, up to 100% of all results which were significant in two repeated runs were excluded (false-negative) by calculation of the FDR. In such experiments, significant differences need confirmation by repeated runs.