Silver staining of proteins in polyacrylamide gels

Silver staining is used to detect proteins after electrophoretic separation on polyacrylamide gels. It combines excellent sensitivity (in the low nanogram range) with the use of very simple and cheap equipment and chemicals. It is compatible with downstream processing, such as mass spectrometry analysis after protein digestion. The sequential phases of silver staining are protein fixation, then sensitization, then silver impregnation and finally image development. Several variants of silver staining are described here, which can be completed in a time range from 2 h to 1 d after the end of the electrophoretic separation. Once completed, the stain is stable for several weeks

Disease-Associated Mutant Ubiquitin Causes Proteasomal Impairment and Enhances the Toxicity of Protein Aggregates

Protein homeostasis is critical for cellular survival and its dysregulation has been implicated in Alzheimer's disease (AD) and other neurodegenerative disorders. Despite the growing appreciation of the pathogenic mechanisms involved in familial forms of AD, much less is known about the sporadic cases. Aggregates found in both familial and sporadic AD often include proteins other than those typically associated with the disease. One such protein is a mutant form of ubiquitin, UBB+1, a frameshift product generated by molecular misreading of a wild-type ubiquitin gene. UBB+1 has been associated with multiple disorders. UBB+1 cannot function as a ubiquitin molecule, and it is itself a substrate for degradation by the ubiquitin/proteasome system (UPS). Accumulation of UBB+1 impairs the proteasome system and enhances toxic protein aggregation, ultimately resulting in cell death. Here, we describe a novel model system to investigate how UBB+1 impairs UPS function and whether it plays a causal role in protein aggregation. We expressed a protein analogous to UBB+1 in yeast (Ubext) and demonstrated that it caused UPS impairment. Blocking ubiquitination of Ubext or weakening its interactions with other ubiquitin-processing proteins reduced the UPS impairment. Expression of Ubext altered the conjugation of wild-type ubiquitin to a UPS substrate. The expression of Ubext markedly enhanced cellular susceptibility to toxic protein aggregates but, surprisingly, did not induce or alter nontoxic protein aggregates in yeast. Taken together, these results suggest that Ubext interacts with more than one protein to elicit impairment of the UPS and affect protein aggregate toxicity. Furthermore, we suggest a model whereby chronic UPS impairment could inflict deleterious consequences on proper protein aggregate sequestration

Computational Methods for Protein Identification from Mass Spectrometry Data

Protein identification using mass spectrometry is an indispensable computational tool in the life sciences. A dramatic increase in the use of proteomic strategies to understand the biology of living systems generates an ongoing need for more effective, efficient, and accurate computational methods for protein identification. A wide range of computational methods, each with various implementations, are available to complement different proteomic approaches. A solid knowledge of the range of algorithms available and, more critically, the accuracy and effectiveness of these techniques is essential to ensure as many of the proteins as possible, within any particular experiment, are correctly identified. Here, we undertake a systematic review of the currently available methods and algorithms for interpreting, managing, and analyzing biological data associated with protein identification. We summarize the advances in computational solutions as they have responded to corresponding advances in mass spectrometry hardware. The evolution of scoring algorithms and metrics for automated protein identification are also discussed with a focus on the relative performance of different techniques. We also consider the relative advantages and limitations of different techniques in particular biological contexts. Finally, we present our perspective on future developments in the area of computational protein identification by considering the most recent literature on new and promising approaches to the problem as well as identifying areas yet to be explored and the potential application of methods from other areas of computational biology

Advances in structure elucidation of small molecules using mass spectrometry

The structural elucidation of small molecules using mass spectrometry plays an important role in modern life sciences and bioanalytical approaches. This review covers different soft and hard ionization techniques and figures of merit for modern mass spectrometers, such as mass resolving power, mass accuracy, isotopic abundance accuracy, accurate mass multiple-stage MS(n) capability, as well as hybrid mass spectrometric and orthogonal chromatographic approaches. The latter part discusses mass spectral data handling strategies, which includes background and noise subtraction, adduct formation and detection, charge state determination, accurate mass measurements, elemental composition determinations, and complex data-dependent setups with ion maps and ion trees. The importance of mass spectral library search algorithms for tandem mass spectra and multiple-stage MS(n) mass spectra as well as mass spectral tree libraries that combine multiple-stage mass spectra are outlined. The successive chapter discusses mass spectral fragmentation pathways, biotransformation reactions and drug metabolism studies, the mass spectral simulation and generation of in silico mass spectra, expert systems for mass spectral interpretation, and the use of computational chemistry to explain gas-phase phenomena. A single chapter discusses data handling for hyphenated approaches including mass spectral deconvolution for clean mass spectra, cheminformatics approaches and structure retention relationships, and retention index predictions for gas and liquid chromatography. The last section reviews the current state of electronic data sharing of mass spectra and discusses the importance of software development for the advancement of structure elucidation of small molecules

Protein expression profiles in human breast ductal carcinoma and histologically normal tissue.

Reference two-dimensional (2-D) gels are presented for human breast ductal carcinoma and histologically normal tissue. Whole biopsy fragments were analyzed, including epithelial and nonepithelial components. Thirty-five spots have been assigned by gel matching to the human liver SWISS-2DPAGE reference map and/or to the human primary keratinocyte IPG map from the Danish Center for Human Genome. N-terminal microsequencing was applied to confirm randomly chosen matching assignments and to identify six new spots. Protein expression profiles in ductal carcinoma and in normal breast tissue appeared to be similar, except for a pattern consisting of 32 spots, which were highly expressed in all carcinoma specimens, and less intense and occasionally undetectable in normal tissue. This difference was statistically significant. Assignment has been obtained for several spots, namely GRP94, GRP78, GRP75, mitochondrial HSP60, calreticulin, protein disulfide isomerase, peptidyl-prolyl cis-trans isomerase, collagen-binding protein 2, fructose bisphosphate aldolase, glyceraldehyde-3-phosphate dehydrogenase, thioredoxin, cytochrome c oxidase VA subunit, tubulin beta isoform and macrophage migration inhibitory factor (MIF). The cancer- and tissue-specificity of the described pattern was assessed by matching to the Swiss-2DPAGE human liver, hepatoma, lymphoma, erythroleukemia reference maps. The pattern of 32 spots was found to be indicative of epithelial neoplasia