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PubMed2006

Intermittent administration of morphine alters protein expression in rat nucleus accumbens.

Repeated exposure to drugs of abuse causes time-dependent neuroadaptive changes in the mesocorticolimbic system of the brain that are considered to underlie the expression of major behavioral characteristics of drug addiction. We used a 2-D gel-based proteomics approach to examine morphine-induced temporal changes in protein expression and/or PTM in the nucleus accumbens (NAc) of morphine-sensitized rats. Rats were pretreated with saline [1 mL/kg subcutaneously (s.c.)] or morphine (10 mg/kg, s.c.) once daily for 14 days and the animals were decapitated 1 day later. The NAc was extracted and proteins resolved by 2-DE. Several protein functional groups were found to be regulated in the morphine-treated group, representing cytoskeletal proteins, proteins involved in neurotransmission, enzymes involved in energy metabolism and protein degradation, and a protein that regulates translation.

Animals↗

PubMedDate not supplied

Processing and classification of protein mass spectra.

Among the many applications of mass spectrometry, biomarker pattern discovery from protein mass spectra has aroused considerable interest in the past few years. While research efforts have raised hopes of early and less invasive diagnosis, they have also brought to light the many issues to be tackled before mass-spectra-based proteomic patterns become routine clinical tools. Known issues cover the entire pipeline leading from sample collection through mass spectrometry analytics to biomarker pattern extraction, validation, and interpretation. This study focuses on the data-analytical phase, which takes as input mass spectra of biological specimens and discovers patterns of peak masses and intensities that discriminate between different pathological states. We survey current work and investigate computational issues concerning the different stages of the knowledge discovery process: exploratory analysis, quality control, and diverse transforms of mass spectra, followed by further dimensionality reduction, classification, and model evaluation. We conclude after a brief discussion of the critical biomedical task of analyzing discovered discriminatory patterns to identify their component proteins as well as interpret and validate their biological implications.

Algorithms↗

PubMed2004

N-t-butyliodoacetamide and iodoacetanilide: two new cysteine alkylating reagents for relative quantitation of proteins.

The synthesis and application of two new alkylating reagents, N-tert-butyl-2-iodoacetamide (N-t-butyliodoacetamide) and 2-iodo-N-phenylacetamide (iodoacetanilide), are described. N-t-Butyliodoacetamide and iodoacetanilide were synthesised to purity in their d(0)-light and in their respective d(9)- and d(5)-heavy forms. The newly synthesised reagents are covalently bound to peptides containing cysteines via an alkylation reaction. The mass differences of 5 and 9 Da avoid possible problems of overlapping isotope distribution. For each alkylated cysteine a peptide mass increases, respectively, by a multiple of 113 and 133 Da for the d(0)-light form of N-t-butyliodoacetamide and iodoacetanilide. These reagents can therefore replace common alkylating reagents in existing proteomics-based applications. Alkylated peptides increase in mass in the same mass range as amino acids and remain suitable for tandem mass spectrometry (MS/MS) data acquisition and analysis. The compounds are simple to use and derivatisation is based on widely applied alkylating procedures. Preliminary results show that these reagents can be applied for both protein quantitation and identification by peptide mass finger printing and/or MS/MS techniques. Using these chemicals and the suggested workflow enables the quantitative analysis of the whole protein sample and realises access to peptides that may contain potential post-translational modifications. Other approaches that incorporate a matrix-assisted laser desorption/ionisation (MALDI) interface prior to MS can take advantage of these chemicals, such as the molecular scanner.

Acetanilides↗

PubMed2005

An automated method for the analysis of stable isotope labeling data in proteomics.

An algorithm is presented for the generation of a reliable peptide component peak table from liquid chromatography-mass spectrometry (LC-MS) and subsequent quantitative analysis of stable isotope coded peptide samples. The method uses chemical noise filtering, charge state fitting, and deisotoping toward improved analysis of complex peptide samples. Overlapping peptide signals in mass spectra were deconvoluted by correlation with modeled peptide isotopic peak profiles. Isotopic peak profiles for peptides were generated in silico from a protein database producing reference model distributions. Doublets of heavy and light labeled peak clusters were identified and compared to provide differential quantification of pairs of stable isotope coded peptides. Algorithms were evaluated using peptides from digests of a single protein and a seven-protein mixture that had been differentially coded with stable isotope labeling agents and mixed in known ratios. The experimental results correlated well with known mixing ratios.

Algorithms↗

PubMed2006

Proteomic analysis of rat hippocampus and frontal cortex after chronic treatment with fluoxetine or putative novel antidepressants: CRF1 and NK1 receptor antagonists.

Chronic administration of antidepressants is required for their efficacy, suggesting the involvement of long-term modifications. As the impact of antidepressant treatment on the brain molecular machinery is not completely understood, we performed a proteomic analysis of rat hippocampus and frontal cortex after chronic treatment with fluoxetine, with an NK1 receptor antagonist, GR205171, and a CRF receptor 1 antagonist, DMP696. After 2D electrophoresis, protein expression levels were compared with both univariate and multivariate statistical analyses and identified by mass spectrometry. All treatments modified levels of actin isoforms, whereas both fluoxetine and GR205171 reduced synapsin II. Fluoxetine treatment increased ERK2 and NP25 and decreased vacuolar ATP synthase. After GR205171 treatment, protein disulphide isomerase A was reduced; dynamin 1 and aldose reductase increased. DMP696 modulated DRP2, pyruvate kinase, LDH and ATP synthase. Although each compound induced a specific pattern of protein modulation, data suggest that antidepressants share the ability of modulating neural plasticity.

Animals↗

PubMed2006

Proteomics for the analysis of the Candida albicans biofilm lifestyle.

Candida albicans is an opportunistic pathogenic fungus capable of causing infections in immunocompromised patients. Candidiasis is often associated with the formation of biofilms on the surface of inert or biological materials. Biofilms are structured microbial communities attached to a surface and encased within a matrix of exopolymeric substance (EPS). At present, very little is known about the changes in protein profiles that occur during the transition from the planktonic to the biofilm mode of growth. Here, we report the use of proteomics for the comparative analysis of subcellular fractions obtained from C. albicans biofilm and planktonic cultures, including cell surface-associated proteins and secreted components present in liquid culture supernatants (for planktonic cultures) and EPS (for biofilms). The analysis revealed a high degree of similarity between the protein profiles associated with the planktonic and biofilm extracts, and led to the identification of several differentially expressed protein spots. Among the differentially expressed proteins, there was a preponderance of metabolic enzymes that have been described as cell surface proteins and immunodominant antigens. Proteins found in the biofilm matrix included a few predicted to form part of the secretome, and also many secretion-signal-less proteins. These observations contribute to our understanding of the C. albicans biofilm lifestyle.

Biofilms↗

PubMedDate not supplied

Histidine-rich peptide selection and quantification in targeted proteomics.

Agarose based immobilized copper (II) affinity chromatography (Cu(II)-IMAC) in tandem with reversed-phase chromatography was applied to a yeast protein extract. Histidine-rich peptides were selected and, in the process, samples were substantially simplified prior to mass spectral analysis. Samples of proteins from the yeast extract at fermentation time periods of 2.5 and 10 h were compared quantitatively used the GIST protocol. Acylation of the N-terminus of tryptic peptides with N-acetoxysuccinamide was used to globally label and quantify relative protein concentration changes. Together with N-terminal acylation, an imidazole elution procedure allowed histidine-rich peptides to be preferentially selected by Cu(II)-IMAC. An inverse labeling strategy was applied to increase reliability in determinations of up- and down-regulation. It was found that the concentration of some histidine-rich proteins changed in excess of 4-fold during fermentation. These proteins covered a wide range of molecular weight and pI values.

Amino Acid Sequence↗

PubMed2003

Efficient and specific removal of albumin from human serum samples.

Patient serum or plasma is frequently monitored for biochemical markers of disease or physiological status. Many of the rapidly evolving technologies of proteome analysis are being used to find additional clinically informative protein markers. The unusually high abundance of albumin in serum can interfere with the resolution and sensitivity of many proteome profiling techniques. We have used monoclonal antibodies against human serum albumin (HSA) to develop an immunoaffinity resin that is effective in the removal of both full-length HSA and many of the HSA fragments present in serum. This resin shows markedly better performance than dye-based resins in terms of both the efficiency and specificity of albumin removal. Immunoglobulins are another class of highly abundant serum protein. When protein G resin is used together with our immunoaffinity resin, Ig proteins and HSA can be removed in a single step. This strategy could be extended to the removal of any protein for which specific antibodies or affinity reagents are available.

Amino Acid Sequence↗

PubMedDate not supplied

Mass spectrometry and the search for moonlighting proteins.

Mass spectrometry has become one of the most important techniques in proteomics because of its use to identify the proteins found in different cell types, organelles, and multiprotein complexes. This information about protein location and binding partners can provide valuable clues to infer a protein's function. However, more and more proteins are found that "moonlight," or have more than one function, and the presence of moonlighting proteins can make more difficult the identification of protein function in those studies. This review discusses examples of moonlighting proteins and how their presence can affect the results of mass spectrometry studies that identify the locations, levels, and changes in protein expression. Although the presence of moonlighting proteins can complicate the results of those studies, mass spectrometry-derived protein-expression profiles potentially provides a very powerful method to find additional moonlighting proteins because they do not require a prior hypothesis of the protein's function.

Gene Expression Profiling↗

PubMedDate not supplied

MultiProtIdent: identifying proteins using database search and protein-protein interactions.

Protein identification is important in proteomics. Proteomic analyses based on mass spectra (MS) constitute innovative ways to identify the components of protein complexes. Instruments can obtain the mass spectrum to an accuracy of 0.01 Da or better, but identification errors are inevitable. This study shows a novel tool, MultiProtIdent, which can identify proteins using additional information about protein-protein interactions and protein functional associations. Both single and multiple Peptide Mass Fingerprints (PMFs) are input to MultiProtIdent, which matches the PMFs to a theoretical peptide mass database. The relationships or interactions among proteins are considered to reduce false positives in PMF matching. Experiments to identify protein complexes reveal that MultiProtIdent is highly promising. The website associated with this study is http://dbms104.csie.ncu.edu.tw/.

Algorithms↗

PubMed2002

What does it mean to identify a protein in proteomics?

The annotation of the human genome indicates the surprisingly low number of approximately 40,000 genes. However, the estimated number of proteins encoded by these genes is two to three orders of magnitude higher. The ability to unambiguously identify the proteins is a prerequisite for their functional investigation. As proteins derived from the same gene can be largely identical, and might differ only in small but functionally relevant details, protein identification tools must not only identify a large number of proteins but also be able to differentiate between close relatives. This information can be generated by mass spectrometry, an approach that identifies proteins by partial analysis of their digestion-derived peptides. Information gleaned from databases fills in the missing sequence information. Because both sequence databases and experimental data are limited, a certain ambiguity often remains concerning which sequence variant(s) and modification(s) are present. As the common denominator of all the isoforms is a gene, in our opinion, it would be more accurate to state that a product of this particular gene rather than a certain protein has been identified by mass spectrometry.

Gene Expression Profiling↗

PubMed2005

Statistical analysis and prediction of protein-protein interfaces.

Predicting protein-protein interfaces from a three-dimensional structure is a key task of computational structural proteomics. In contrast to geometrically distinct small molecule binding sites, protein-protein interface are notoriously difficult to predict. We generated a large nonredundant data set of 1494 true protein-protein interfaces using biological symmetry annotation where necessary. The data set was carefully analyzed and a Support Vector Machine was trained on a combination of a new robust evolutionary conservation signal with the local surface properties to predict protein-protein interfaces. Fivefold cross validation verifies the high sensitivity and selectivity of the model. As much as 97% of the predicted patches had an overlap with the true interface patch while only 22% of the surface residues were included in an average predicted patch. The model allowed the identification of potential new interfaces and the correction of mislabeled oligomeric states.

Animals↗

PubMed1999

[Proteome analysis: the state of the art of the methodology].

The proteome is the protein complement of a genome. Proteome analysis has been progressing worldwide. Two-dimensional electrophoresis (2-DE), a key technique in proteome analysis, separates proteins on a polyacrylamide gel according to the isoelectric point and molecular mass. A total of 1,000-1,500 protein spots can be separated and detected on a polyacrylamide gel using silver-staining. It is important to identify individual protein spots in order to correlate the information of the genome to that of the corresponding proteome. By automatic amino-terminal sequencing, around 15 amino acid residues from the amino terminus can be determined from 1 pmole of a protein sample. The homology search of the obtained sequences against a protein sequence database can clarify the protein unambigously. Recently, a carboxyl-terminal sequencing method using a vapor from a high concentration of an organic acid has been developed. Peptide-mass-fingerprinting is a new method for protein identification using residue-specific proteases and mass spectrometry. Two types of chemical cleavage methods, the carboxyl side cleavage of the aspartyl peptide bond and the amino terminal cleavage of serine/threonine peptide bonds would be more suitable for peptide-mass-fingerprinting of micro amount protein because of no contamination from the gel matrix or the enzyme used. It would be possible to analyse less amount protein sample (100 femtomole) more rapidly according to advancement of mass spectrometry.

Amino Acid Sequence↗

PubMed2006

Neural network prediction of peptide separation in strong anion exchange chromatography.

MOTIVATION: The still emerging combination of technologies that enable description and characterization of all expressed proteins in a biological system is known as proteomics. Although many separation and analysis technologies have been employed in proteomics, it remains a challenge to predict peptide behavior during separation processes. New informatics tools are needed to model the experimental analysis method that will allow scientists to predict peptide separation and assist with required data mining steps, such as protein identification. RESULTS: We developed a software package to predict the separation of peptides in strong anion exchange (SAX) chromatography using artificial neural network based pattern classification techniques. A multi-layer perceptron is used as a pattern classifier and it is designed with feature vectors extracted from the peptides so that the classification error is minimized. A genetic algorithm is employed to train the neural network. The developed system was tested using 14 protein digests, and the sensitivity analysis was carried out to investigate the significance of each feature. AVAILABILITY: The software and testing results can be downloaded from ftp://ftp.bbc.purdue.edu.

Algorithms↗

PubMed2000

Tandem mass spectrometry methods for definitive protein identification in proteomics research.

Optimized procedures have been developed for the addition of sulfonic acid groups to the N-termini of low-level peptides. These procedures have been applied to peptides produced by tryptic digestion of proteins that have been separated by two-dimensional (2-D) gel electrophoresis. The derivatized peptides were sequenced using matrix-assisted laser desorption/ionization (MALDI) post-source decay (PSD) and electrospray ionization-tandem mass spectrometry methods. Reliable PSD sequencing results have been obtained starting with sub-picomole quantities of protein. We estimate that the current PSD sequencing limit is about 300 fmol of protein in the gel. The PSD mass spectra of the derivatized peptides usually allow much more specific protein sequence database searches than those obtained without derivatization. We also report initial automated electrospray ionization-tandem mass spectrometry sequencing of these novel peptide derivatives. Both types of tandem mass spectra provide predictable fragmentation patterns for arginine-terminated peptides. The spectra are easily interpreted de novo, and they facilitate error-tolerant identification of proteins whose sequences have been entered into databases.

Amino Acid Sequence↗

PubMed2005

Proteome dynamics in complex organisms: using stable isotopes to monitor individual protein turnover rates.

The complete definition of changes in a proteome requires information about dynamics and specifically the rate at which the individual proteins are turned over intracellularly. Whilst this can be achieved in single-cell culture using stable isotope precursors, it is more challenging to develop methods for intact animals. In this study, we show how dietary administration of stable isotope-labelled amino acids can obtain information on the relative rates of synthesis and degradation of individual proteins in a proteome. The pattern of stable isotope-labelling in tryptic peptides can be deconstructed to yield a highly reliable measure of the isotope abundance of the precursor pool, a parameter that is often difficult to acquire. We demonstrate this approach using chickens fed a semisynthetic diet containing [(2)H(8)]valine at a calculated relative isotope abundance (RIA) of 0.5. When the labelling pattern of gel-resolved muscle proteins was analyzed, the intracellular precursor isotope abundance was 0.35, consistent with dilution of the amino acid precursor pool with unlabelled amino acids derived from degradation of pre-existing proteins. However, the RIA was stable over an extended labelling window, and permitted calculation of the rates of synthesis and degradation of individual proteins isolated by gel electrophoresis. For the first time, it is feasible to contemplate the analysis of turnover of individual proteins in intact animals.

Animals↗

PubMed2003

Beta-elimination: an unexpected artefact in proteome analysis.

Two persistent myths, ingrained in the electrophoretic literature of the last thirty years, namely carbamylation and deamidation, have been recently dispelled (Herbert et al., J. Proteome Res. 2002, in press). We report here, for the first time, a noxious and unexpected artefact in proteome analysis: beta-elimination (or desulfuration), which results on the loss of an H(2)S group (34 Da) from cysteine (Cys) residues for protein focusing in the alkaline pH region. With such an elimination event, a dehydro alanine residue is generated at the Cys site. In turn, the presence of a double bond in this position elicits lysis of the peptide bond, generating a number of peptides of fairly large size from an intact protein. The first process seems to be favored by the electric field, probably due to the continuous harvesting of the SH(-) anion produced. The only remedy found to this noxious degradation pathway is the reduction and alkylation of all Cys residues prior to their exposure to the electric field. Alkylation appears to substantially reduce both beta-elimination and the subsequent amido bond lysis.

Alkylation↗

PubMed2001

A specialised proteomic database for comparing matrix-assisted laser desorption/ionization-time of flight mass spectrometry data of tryptic peptides with corresponding sequence database segments.

We have developed a specialised proteomic database for the analysis of matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS) data derived from tryptic peptides of Sinorhizobium meliloti proteins. This database currently contains the amino acid sequence data of the proteins predicted from the complete chromosome, MALDI-TOF MS data from proteolytic peptides of about 400 tryptically digested proteins, and the results of a search of the MALDI-TOF MS spectra against the chromosomal amino acid sequences. The database made it possible to access and compare the sequences of theoretical tryptic peptides that correspond to MALDI-TOF peaks in the mass spectrum with predicted tryptic peptides from identified proteins that could not be matched to MALDI-TOF peaks. A comparison of the molecular weights, isoelectric points and amino acid compositions of the identified and nonidentified peptides is presented. We also show how the system can assist in the development of an automated scoring function that facilitates and consolidates protein identification.

Databases, Protein↗