Captopril apparently increase and cisplatin apparently decrease human albumin concentration in artificial urinary solutions.

BACKGROUND: Measurement of urinary albumin (HSA) is very important in diagnostic of kidney diseases. Much less is known about the possible impact of substances present in urine together with albumin on the results of measurements. METHODS: We investigated the effect of the presence of captopril and cisplatin in the solution on the result of the determination of HSA by native polyacrylamide gel electrophoresis. Protein conformation in the absence and presence of the drugs was examined using Fourier Transform Infrared Spectroscopy (FTIR). RESULTS: The presence of captopril apparently increases HSA concentration while cisplatin causes an apparent decrease in the HSA concentration. The presence of both drugs also influence the secondary structure forms of HSA albumin investigated by FTIR. CONCLUSION: Both drugs tested in the concentration of human use can have an impact on the results of determination of albumin in urine which can influence clinical decision.

Evaluation of DNA bending models in their capacity to predict electrophoretic migration anomalies of satellite DNA sequences.

DNA containing a sequence that generates a local curvature exhibits a pronounced retardation in electrophoretic mobility. Various theoretical models have been proposed to explain relationship between DNA structural features and migration anomaly. Here, we studied the capacity of 15 static wedge-bending models to predict electrophoretic behavior of 69 satellite monomers derived from four divergent families. All monomers exhibited retarded mobility in PAGE corresponding to retardation factors ranging 1.02-1.54. The curvature varied both within and across the groups and correlated with the number, position, and lengths of A-tracts. Two dinucleotide models provided strong correlation between gel mobility and curvature prediction; two trinucleotide models were satisfactory while remaining dinucleotide models provided intermediate results with reliable prediction for subsets of sequences only. In some cases, similarly shaped molecules exhibited relatively large differences in mobility and vice versa. Generally less accurate predictions were obtained in groups containing less homogeneous sequences possessing distinct structural features. In conclusion, relatively universal theoretical models were identified suitable for the analysis of natural sequences known to harbor relatively moderate curvature. These models could be potentially applied to genome wide studies. However, in silico predictions should be viewed in context of experimental measurement of intrinsic DNA curvature.

Analysis of the Plasmodium falciparum proteasome using Blue Native PAGE and label-free quantitative mass spectrometry.

Detailed knowledge of the composition of protein complexes is crucial for the understanding of their structure and function; however, appropriate techniques for compositional analyses of complexes largely rely on elaborate tagging, immunoprecipitation, cross-linking and purification strategies. The proteasome is a prototypical protein complex and therefore an excellent model to assess new methods for protein complex characterisation. Here we evaluated the applicability of Blue Native (BN) PAGE in combination with label-free protein quantification and protein correlation profiling (PCP) for the investigation of proteasome complexes directly from biological samples. Using the purified human 20S proteasome we showed that the approach can accurately detect members of a complex by clustering their gel migration profiles. We applied the approach to address proteasome composition in the schizont stage of the malaria parasite Plasmodium falciparum. The analysis, performed in the background of the whole protein extract, revealed that all subunits comigrated and formed a tight cluster with a single maximum, demonstrating presence of a single form of the 20S proteasome. This study shows that BN PAGE in combination with label-free quantification and PCP is applicable to the analysis of multiprotein complexes directly from complex protein mixtures.