A micro-scale method for determining relative metal-binding affinities of proteins

This article describes a quick and easy method for determining relative binding affinities between proteins and metal ions. The method is based on separating unbound metal ions from metal ions bound to protein by ultrafiltration using microcentrifuge ultrafiltration units. Bovine serum albumin (BSA) was used as the test protein and the relative affinity towards divalent metal ions was found to be Cu²⁺>Zn²⁺>Cd²⁺>Pb²⁺>Ni²⁺>Co²⁺, which corresponds to the relative orders reported in the literature.     

Comparison of statistical approaches for the analysis of proteome expression data of differentiating neural stem cells

Comparative proteomic studies often use statistical tests included in the software for the analysis of digitized images of two-dimensional electrophoresis gels. As these programs include only limited capabilities for statistical analysis, many studies do not further describe their statistical approach. To find potential differences produced by different data processing, we compared the results of (1) Student's t-test using a spreadsheet program, (2) the intrinsic algorithms implemented in the Phoretix 2D gel analysis software, and (3) the SAM algorithm originally developed for microarray analysis. We applied the algorithms to proteome data of undifferentiated neural stem cells versus in vitro differentiated neural stem cells. We found (1) 367 spots differentially expressed using Student's t-test, (2) 203 spots using the algorithms in Phoretix 2D, and (3) 119 spots using the algorithms in SAM, respectively, with an overlap of 42 spots detected by all three algorithms. Applying different statistical approaches on the same dataset resulted in divergent set of protein spots labeled as statistically "significant". Currently, there is no agreement on statistical data processing of 2DE datasets, but the statistical tests applied in 2DE studies should be documented. Tools for the statistical analysis of proteome data should be implemented and documented in the existing 2DE software.     

GLP-1 and GIP are colocalized in a subset of endocrine cells in the small intestine

BACKGROUND: The incretin hormones GIP and GLP-1 are thought to be produced in separate endocrine cells located in the proximal and distal ends of the mammalian small intestine, respectively. METHODS AND RESULTS: Using double immunohistochemistry and in situ hybridization, we found that GLP-1 was colocalized with either GIP or PYY in endocrine cells of the porcine, rat, and human small intestines, whereas GIP and PYY were rarely colocalized. Thus, of all the cells staining positively for either GLP-1, GIP, or both, 55-75% were GLP-1 and GIP double-stained in the mid-small intestine. Concentrations of extractable GIP and PYY were highest in the midjejunum [154 (95-167) and 141 (67-158) pmol/g, median and range, respectively], whereas GLP-1 concentrations were highest in the ileum [92 (80-207) pmol/l], but GLP-1, GIP, and PYY immunoreactive cells were found throughout the porcine small intestine. CONCLUSIONS: Our results provide a morphological basis to suggest simultaneous, rather than sequential, secretion of these hormones by postprandial luminal stimulation.     

Mitochondrial protein import: recognition of internal import signals of BCS1 by the TOM complex

BCS1, a component of the inner membrane of mitochondria, belongs to the group of proteins with internal, noncleavable import signals. Import and intramitochondrial sorting of BCS1 are encoded in the N-terminal 126 amino acid residues. Three sequence elements were identified in this region, namely, the transmembrane domain (amino acid residues 51 to 68), a presequence type helix (residues 69 to 83), and an import auxiliary region (residues 84 to 126). The transmembrane domain is not required for stable binding to the TOM complex. The Tom receptors (Tom70, Tom22 and Tom20), as determined by peptide scan analysis, interact with the presequence-like helix, yet the highest binding was to the third sequence element. We propose that the initial recognition of BCS1 precursor at the surface of the organelle mainly depends on the auxiliary region and does not require the transmembrane domain. This essential region represents a novel type of signal with targeting and sorting functions. It is recognized by all three known mitochondrial import receptors, demonstrating their capacity to decode various targeting signals. We suggest that the BCS1 precursor crosses the TOM complex as a loop structure and that once the precursor emerges from the TOM complex, all three structural elements are essential for the intramitochondrial sorting to the inner membrane.     

Effects of GH on urea,glucose and lipid metabolism,and insulin sensitivity during fasting in GH-deficient patients

Fasting-related states of distress pose major health problems, and growth hormone (GH) plays a key role in this context. The present study was designed to assess the effects of GH on substrate metabolism and insulin sensitivity during short-term fasting. Six GH-deficient adults underwent 42.5 h of fasting on two occasions, with and without concomitant GH replacement. Palmitate and urea fluxes were measured with the steady-state isotope dilution technique after infusion of [9,10-3H]palmitate and [13C]urea. During fasting with GH replacement, palmitate concentrations and fluxes increased by 50% [palmitate: 378 +/- 42 (GH) vs. 244 +/- 12 micromol/l, P < 0.05; palmitate: 412 +/- 58 (GH) vs. 276 +/- 42 microM, P = 0.05], and urea turnover and excretion decreased by 30-35% [urea rate of appearance: 336 +/- 22 (GH) vs. 439 +/- 43 micromol. kg-1. h-1, P < 0.01; urea excretion: 445 +/- 43 (GH) vs. 602 +/- 74 mmol/24 h, P < 0.05]. Insulin sensitivity (determined by a euglycemic hyperinsulinemic clamp) was significantly decreased [M value: 1.26 +/- 0.06 (GH) vs. 2.07 +/- 0.22 mg. kg-1. min-1, P < 0.01] during fasting with GH replacement. In conclusion, continued GH replacement during fasting in GH-deficient adults decreases insulin sensitivity, increases lipid utilization, and conserves protein.     

α<Subscript>2A</Subscript>- and α<Subscript>2C</Subscript>-Adrenoceptors as Potential Targets for Dopamine and Dopamine Receptor Ligands

The poor norepinephrine innervation and high density of Gi/o-coupled α_2A- and α_2C-adrenoceptors in the striatum and the dense striatal dopamine innervation have prompted the possibility that dopamine could be an effective adrenoceptor ligand. Nevertheless, the reported adrenoceptor agonistic properties of dopamine are still inconclusive. In this study, we analyzed the binding of norepinephrine, dopamine, and several compounds reported as selective dopamine D₂-like receptor ligands, such as the D₃ receptor agonist 7-OH-PIPAT and the D₄ receptor agonist RO-105824, to α₂-adrenoceptors in cortical and striatal tissue, which express α_2A-adrenoceptors and both α_2A- and α_2C-adrenoceptors, respectively. The affinity of dopamine for α₂-adrenoceptors was found to be similar to that for D₁-like and D₂-like receptors. Moreover, the exogenous dopamine receptor ligands also showed high affinity for α_2A- and α_2C-adrenoceptors. Their ability to activate Gi/o proteins through α_2A- and α_2C-adrenoceptors was also analyzed in transfected cells with bioluminescent resonance energy transfer techniques. The relative ligand potencies and efficacies were dependent on the Gi/o protein subtype. Furthermore, dopamine binding to α₂-adrenoceptors was functional, inducing changes in dynamic mass redistribution, adenylyl cyclase activity, and ERK1/2 phosphorylation. Binding events were further studied with computer modeling of ligand docking. Docking of dopamine at α_2A- and α_2C-adrenoceptors was nearly identical to its binding to the crystallized D₃ receptor. Therefore, we provide conclusive evidence that α_2A- and α_2C-adrenoceptors are functional receptors for norepinephrine, dopamine, and other previously assumed selective D₂-like receptor ligands, which calls for revisiting previous studies with those ligands.     

Biomarker indications for microbial contribution to Recent and Late Jurassic carbonate deposits

Summary Biomarker investigations were applied to the hydrocarbon fractions of three Recent (cyanobacterial mat, Lake Van microbialite and Lake Satonda microbialite) and two Late Jurassic carbonate samples obtained from sponge bioherms. The relative concentrations ofn-alkanes, monomethyl alkanes, acyclic isoprenoids, steroids and hopanoids in these samples are studied and their probable biological precursors are discussed. Normal alkanes with carbon chain lengths ranging from C₁₅ to C₃₄ and monomethyl alkanes ranging from C₁₇ to C₂₁ with a varying methyl branching pattern are found. The major hydrocarbons are low molecular weight (LMW)n-alkanes (C₁₅–C₂₁) with a slight to strong predominance ofn-heptadecane (C₁₇). High molecular weight (HMW)n-alkanes occur in low to moderate relative concentrations showing a preference of odd-carbon numbered compounds with a maximum at C₂₉. Within the acyclic isoprenoids, pristane, phytane/phytene, pentamethyl-eicosane, squalane and lycopane could be identified. Polycyclic terpenoids of the sterane and/or hopane type are present in all carbonate samples. The carbon numbers of these components range from 27 to 29 and 27 to 32, respectively. These organic compounds identified can be attributed to various source organisms such as cyanobacteria, archaebacteria, algae and vascular plants. All hydrocarbon fractions of the samples are characterized by moderate to high relative concentrations of compounds derived from cyanobacteria, signifying the role of these organisms as contributors to the Recent as well as to the Late Jurassic carbonate deposits.     

Soil organic carbon stocks in estuarine and marine mangrove ecosystems are driven by nutrient colimitation of P and N

Mangroves play an important role in carbon sequestration, but soil organic carbon (SOC) stocks differ between marine and estuarine mangroves, suggesting differing processes and drivers of SOC accumulation. Here, we compared undegraded and degraded marine and estuarine mangroves in a regional approach across the Indonesian archipelago for their SOC stocks and evaluated possible drivers imposed by nutrient limitations along the land‐to‐sea gradients. SOC stocks in natural marine mangroves (271–572 Mg ha^?1 m^?1) were much higher than under estuarine mangroves (100–315 Mg ha^?1 m^?1) with a further decrease caused by degradation to 80–132 Mg ha^?1 m^?1. Soils differed in C/N ratio (marine: 29–64; estuarine: 9–28), δ¹⁵N (marine: ?0.6 to 0.7‰; estuarine: 2.5 to 7.2‰), and plant‐available P (marine: 2.3–6.3 mg kg^?1; estuarine: 0.16–1.8 mg kg^?1). We found N and P supply of sea‐oriented mangroves primarily met by dominating symbiotic N₂ fixation from air and P import from sea, while mangroves on the landward gradient increasingly covered their demand in N and P from allochthonous sources and SOM recycling. Pioneer plants favored by degradation further increased nutrient recycling from soil resulting in smaller SOC stocks in the topsoil. These processes explained the differences in SOC stocks along the land‐to‐sea gradient in each mangrove type as well as the SOC stock differences observed between estuarine and marine mangrove ecosystems. This first large‐scale evaluation of drivers of SOC stocks under mangroves thus suggests a continuum in mangrove functioning across scales and ecotypes and additionally provides viable proxies for carbon stock estimations in PES or REDD schemes.