Comparison of bottom-up protein identification methods

With the rapid development of proteomics, a number of different methods appeared for the basic task of protein identification. We made a simple comparison between a common liquid chromatography-tandem mass spectrometry (LC-MS/MS) workflow using an ion trap mass spectrometer and a combined LC-MS and LC-MS/MS method using Fourier transform ion cyclotron resonance (FTICR) mass spectrometry and accurate peptide masses. To compare the two methods for protein identification, we grew and extracted proteins from E. coli using established protocols. Cystines were reduced and alkylated, and proteins digested by trypsin. The resulting peptide mixtures were separated by reversed-phase liquid chromatography using a 4 h gradient from 0 to 50% acetonitrile over a C18 reversed-phase column. The LC separation was coupled on-line to either a Bruker Esquire HCT ion trap or a Bruker 7 tesla APEX-Qe Qh-FTICR hybrid mass spectrometer. Data-dependent Qh-FTICR-MS/MS spectra were acquired using the quadrupole mass filter and collisionally induced dissociation into the external hexapole trap. Proteins were in both schemes identified by Mascot MS/MS ion searches and the peptides identified from these proteins in the FTICR MS/MS data were used for automatic internal calibration of the FTICR-MS data, together with ambient polydimethylcyclosiloxane ions.

Protein precipitation behaviour of condensed tannins from Lotus pedunculatus and Trifolium repens with different mean degrees of polymerization

The precipitation of bovine serum albumin (BSA), lysozyme (LYS) and alfalfa leaf protein (ALF) by two large- and two medium-sized condensed tannin (CT) fractions of similar flavan-3-ol subunit composition is described. CT fractions isolated from white clover flowers and big trefoil leaves exhibited high purity profiles by 1D/2D NMR and purities >90% (determined by thiolysis). At pH 6.5, large CTs with a mean degree of polymerization (mDP) of ~18 exhibited similar protein precipitation behaviors and were significantly more effective than medium CTs (mDP ~9). Medium CTs exhibited similar capacities to precipitate ALF or BSA, but showed small but significant differences in their capacity to precipitate LYS. All CTs precipitated ALF more effectively than BSA or LYS. Aggregation of CT-protein complexes likely aided precipitation of ALF and BSA, but not LYS. This study, one of the first to use CTs of confirmed high purity, demonstrates that mDP of CTs influences protein precipitation efficacy.

Retention time prediction and protein identification

Proteins are commonly identified through enzymatic digestion and generation of short sequence tags or fingerprints of peptide masses by mass spectrometry. Separation methods, such as liquid chromatography and electrophoresis, are often used to fractionate complex protein or peptide mixtures and these separations also provide information on the different species, such as molecular weight and isoelectric point from electrophoresis and hydrophobicity in reversed-phase chromatography. These are also properties that can be predicted from amino acid sequences derived from genomic sequences and used in protein identification. This chapter reviews recently introduced methods based on retention time prediction to extract information from chromatographic separations and the applications to protein identification in organisms with small and large genomes. Novel data on retention time prediction of posttranslationally modified peptides is also presented.

Optimizing the methods of synthesis for barium hexagonal ferrite: an experimental and theoretical study

M-type barium hexaferrite (BaM) is a hard ferrite, crystallizing in space group P6(3)/mmc possessing a hexagonal magneto-plumbite structure, which consists of alternate hexagonal and spinel blocks. The structure of BaM is thus related to those of garnet and spinel ferrite. However the material has proved difficult to synthesize. By taking into account the presence of the spinel block in barium hexagonal ferrite, highly efficient new synthetic methods were devised with routes significantly different from existing ones. These successful variations in synthetic methods have been derived by taking into account a detailed investigation of the structural features of barium hexagonal ferrite and the least change principle whereby configuration changes are kept to a minimum. Thus considering the relevant mechanisms has helped to improve the synthesis efficiencies for both hydrothermal and co-precipitation methods by choosing conditions that invoke the formation of the cubic block or the less stable Fe3O4. The role played by BaFe2O4 in the synthesis is also discussed. The distribution of iron from reactants or intermediates among different sites was also successfully explained. The proposed mechanisms are based on the principle that the cubic block must be self-assembled to form the final product. Thus, it is believed that these formulated mechanisms should be helpful in designing experiments to obtain a deeper understanding of the synthesis process and to investigate the substitution of magnetic ions with doping ions.

Do all tannins have similar nutritional effects? A comparison of three Brazilian fodder legumes

Three tropical legumes, namely Leucaena leucocephala, Sesbania sesban and Cajanus cajan, were subjected to chemical analysis plus in vitro, in situ and in vivo evaluations. Three different assays were used to determine total tannins: adsorption to polyvinyl pyrrolidine (PVPP-tannins), radial diffusion (RD-tannins) and protein precipitation capacity (BSA-tannins). Total phenols, total tannins and condensed tannins were highest for Sesbania. RD-tannins were correlated with total phenols (r(2) = 0.93), PVPP-tannins (r(2) = 0.92) and condensed tannins (r(2) = 0.99). The protein precipitation capacity of Sesbania, Leucaena and Cajanus were 25.9, 6.13 and 4.05 mu g BSA/g DM, respectively. Gas production at 24h was negatively correlated with total phenols (r(2) = 0.99), PVPP-tannins (r(2) = 0.99) and condensed tannins (r(2) = 0.91). The RD-, PVPP-tannins and the response to polyethylene glycol (PEG) in the gas production assay appeared to be useful as a first screen for tannins. In situ degradability did not reflect any adverse effects of tannins. However, in vivo experiments showed that the apparent DM digestibility of Sesbania and Leucaena was lower than the basal diet. The apparent protein digestibility was lower for all legumes compared to the basal diet. Most treatments caused a negative nitrogen balance. The problems associated with browse feeding were not only related to tannin contents, other factors such as inherently poor digestibility and low energy intake may also have lead to the poor animal performance on these diets. We propose, given the limitations of current tannin assays, that it is not possible to predict beneficial or harmful nutritional effects from total tannin concentrations per se. (C) 2004 Elsevier B.V. All rights reserved.

Proteomic analysis of redox- and ErbB2-dependent changes in mammary luminal epithelial cells using cysteine- and lysine-labelling two-dimensional difference gel electrophoresis

Differential protein expression analysis based on modification of selected amino acids with labelling reagents has become the major method of choice for quantitative proteomics. One such methodology, two-dimensional difference gel electrophoresis (2-D DIGE), uses a matched set of fluorescent N-hydroxysuccinimidyl (NHS) ester cyanine dyes to label lysine residues in different samples which can be run simultaneously on the same gels. Here we report the use of iodoacetylated cyanine (ICy) dyes (for labelling of cysteine thiols, for 2-D DIGE-based redox proteomics. Characterisation of ICy dye labelling in relation to its stoichiometry, sensitivity and specificity is described, as well as comparison of ICy dye with NHS-Cy dye labelling and several protein staining methods. We have optimised conditions for labelling of nonreduced, denatured samples and report increased sensitivity for a subset of thiol-containing proteins, allowing accurate monitoring of redox-dependent thiol modifications and expression changes. Cysteine labelling was then combined with lysine labelling in a multiplex 2-D DIGE proteomic study of redox-dependent and ErbB2-dependent changes in epithelial cells exposed to oxidative stress. This study identifies differentially modified proteins involved in cellular redox regulation, protein folding, proliferative suppression, glycolysis and cytoskeletal organisation, revealing the complexity of the response to oxidative stress and the impact that overexpression of ErbB2 has on this response.

Proteomic analysis of redox- and ErbB2-dependent changes in mammary luminal epithelial cells using cysteine- and lysine-labelling two-dimensional difference gel electrophoresis

Differential protein expression analysis based on modification of selected amino acids with labelling reagents has become the major method of choice for quantitative proteomics. One such methodology, two-dimensional difference gel electrophoresis (2-D DIGE), uses a matched set of fluorescent N-hydroxysuccinimidyl (NHS) ester cyanine dyes to label lysine residues in different samples which can be run simultaneously on the same gels. Here we report the use of iodoacetylated cyanine (ICy) dyes (for labelling of cysteine thiols, for 2-D DIGE-based redox proteomics. Characterisation of ICy dye labelling in relation to its stoichiometry, sensitivity and specificity is described, as well as comparison of ICy dye with NHS-Cy dye labelling and several protein staining methods. We have optimised conditions for labelling of nonreduced, denatured samples and report increased sensitivity for a subset of thiol-containing proteins, allowing accurate monitoring of redox-dependent thiol modifications and expression changes, Cysteine labelling was then combined with lysine labelling in a multiplex 2-D DIGE proteomic study of redox-dependent and ErbB2-dependent changes in epithelial cells exposed to oxidative stress. This study identifies differentially modified proteins involved in cellular redox regulation, protein folding, proliferative suppression, glycolysis and cytoskeletal organisation, revealing the complexity of the response to oxidative stress and the impact that overexpression of ErbB2 has on this response.

Genetic polymorphisms in the hypothalamic pathway in relation to subsequent weight change--the DiOGenes study

BACKGROUND: Single nucleotide polymorphisms (SNPs) in genes encoding the components involved in the hypothalamic pathway may influence weight gain and dietary factors may modify their effects. AIM: We conducted a case-cohort study to investigate the associations of SNPs in candidate genes with weight change during an average of 6.8 years of follow-up and to examine the potential effect modification by glycemic index (GI) and protein intake. METHODS AND FINDINGS: Participants, aged 20-60 years at baseline, came from five European countries. Cases ('weight gainers') were selected from the total eligible cohort (n = 50,293) as those with the greatest unexplained annual weight gain (n = 5,584). A random subcohort (n = 6,566) was drawn with the intention to obtain an equal number of cases and noncases (n = 5,507). We genotyped 134 SNPs that captured all common genetic variation across the 15 candidate genes; 123 met the quality control criteria. Each SNP was tested for association with the risk of being a 'weight gainer' (logistic regression models) in the case-noncase data and with weight gain (linear regression models) in the random subcohort data. After accounting for multiple testing, none of the SNPs was significantly associated with weight change. Furthermore, we observed no significant effect modification by dietary factors, except for SNP rs7180849 in the neuromedin β gene (NMB). Carriers of the minor allele had a more pronounced weight gain at a higher GI (P = 2 x 10⁻⁷). CONCLUSIONS: We found no evidence of association between SNPs in the studied hypothalamic genes with weight change. The interaction between GI and NMB SNP rs7180849 needs further confirmation.

Relationship between condensed tannin structures and their ability to precipitate feed proteins in the rumen

Abstract BACKGROUND Tannins can bind to and precipitate protein by forming insoluble complexes resistant to fermentation and with a positive effect on protein utilisation by ruminants. Three protein types, Rubisco, rapeseed protein and bovine serum albumin (a single high-molecular weight protein), were used to test the effects of increasing concentrations of structurally different condensed tannins on protein solubility/precipitation. RESULTS Protein type (PT) influenced solubility after addition of condensed tannins (P < 0.001) in the order: Rubisco < rapeseed < BSA (P < 0.05). The type of condensed tannin (CT) affected protein solubility (P = 0.001) with a CT × PT interaction (P = 0.001). Mean degree of polymerisation, proportions of cis- versus trans-flavanol subunits or prodelphinidins versus procyanidins among CTs could not explain precipitation capacities. Increasing tannin concentration decreased protein solubility (P < 0.001) with a PT × CT concentration interaction. The proportion of low-molecular weight rapeseed proteins remaining in solution increased with CT concentration but not with Rubisco. CONCLUSIONS Results of this study suggest that PT and CT type are both of importance for protein precipitation but that the CT structures investigated did not allow identification of parameters that contribute most to precipitation. It is possible that the three-dimensional structures of tannins and proteins may be more important factors in tannin–protein interactions. © 2013 Society of Chemical Industry

Downscaling from GCM precipitation: a benchmark for dynamical and statistical downscaling methods

A precipitation downscaling method is presented using precipitation from a general circulation model (GCM) as predictor. The method extends a previous method from monthly to daily temporal resolution. The simplest form of the method corrects for biases in wet-day frequency and intensity. A more sophisticated variant also takes account of flow-dependent biases in the GCM. The method is flexible and simple to implement. It is proposed here as a correction of GCM output for applications where sophisticated methods are not available, or as a benchmark for the evaluation of other downscaling methods. Applied to output from reanalyses (ECMWF, NCEP) in the region of the European Alps, the method is capable of reducing large biases in the precipitation frequency distribution, even for high quantiles. The two variants exhibit similar performances, but the ideal choice of method can depend on the GCM/reanalysis and it is recommended to test the methods in each case. Limitations of the method are found in small areas with unresolved topographic detail that influence higher-order statistics (e.g. high quantiles). When used as benchmark for three regional climate models (RCMs), the corrected reanalysis and the RCMs perform similarly in many regions, but the added value of the latter is evident for high quantiles in some small regions.

Disorder prediction methods, their applicability to different protein targets and their usefulness for guiding experimental studies

The role and function of a given protein is dependent on its structure. In recent years, however, numerous studies have highlighted the importance of unstructured, or disordered regions in governing a protein’s function. Disordered proteins have been found to play important roles in pivotal cellular functions, such as DNA binding and signalling cascades. Studying proteins with extended disordered regions is often problematic as they can be challenging to express, purify and crystallise. This means that interpretable experimental data on protein disorder is hard to generate. As a result, predictive computational tools have been developed with the aim of predicting the level and location of disorder within a protein. Currently, over 60 prediction servers exist, utilizing different methods for classifying disorder and different training sets. Here we review several good performing, publicly available prediction methods, comparing their application and discussing how disorder prediction servers can be used to aid the experimental solution of protein structure. The use of disorder prediction methods allows us to adopt a more targeted approach to experimental studies by accurately identifying the boundaries of ordered protein domains so that they may be investigated separately, thereby increasing the likelihood of their successful experimental solution.

The binding site distance test score: a robust method for the assessment of predicted protein binding sites

We propose a novel method for scoring the accuracy of protein binding site predictions – the Binding-site Distance Test (BDT) score. Recently, the Matthews Correlation Coefficient (MCC) has been used to evaluate binding site predictions, both by developers of new methods and by the assessors for the community wide prediction experiment – CASP8. Whilst being a rigorous scoring method, the MCC does not take into account the actual 3D location of the predicted residues from the observed binding site. Thus, an incorrectly predicted site that is nevertheless close to the observed binding site will obtain an identical score to the same number of nonbinding residues predicted at random. The MCC is somewhat affected by the subjectivity of determining observed binding residues and the ambiguity of choosing distance cutoffs. By contrast the BDT method produces continuous scores ranging between 0 and 1, relating to the distance between the predicted and observed residues. Residues predicted close to the binding site will score higher than those more distant, providing a better reflection of the true accuracy of predictions. The CASP8 function predictions were evaluated using both the MCC and BDT methods and the scores were compared. The BDT was found to strongly correlate with the MCC scores whilst also being less susceptible to the subjectivity of defining binding residues. We therefore suggest that this new simple score is a potentially more robust method for future evaluations of protein-ligand binding site predictions.

Recent advances in capillary electrophoresis methods for food analysis

This review article addresses recent advances in the analysis of foods and food components by capillary electrophoresis (CE). CE has found application to a number of important areas of food analysis, including quantitative chemical analysis of food additives, biochemical analysis of protein composition, and others. The speed, resolution and simplicity of CE, combined with low operating costs, make the technique an attractive option for the development of improved methods of food analysis for the new millennium.

Effect of prolonged intravenous glucose and essential amino acid infusion on nitrogen balance, muscle protein degradation and ubiquitin-conjugating enzyme gene expression in calves

Background: Intravenous infusions of glucose and amino acids increase both nitrogen balance and muscle accretion. We hypothesised that co-infusion of glucose ( to stimulate insulin) and essential amino acids (EAA) would act additively to improve nitrogen balance by decreasing muscle protein degradation in association with alterations in muscle expression of components of the ubiquitin-proteasome proteolytic pathway. Methods: We examined the effect of a 5 day intravenous infusions of saline, glucose, EAA and glucose + EAA, on urinary nitrogen excretion and muscle protein degradation. We carried out the study in 6 restrained calves since ruminants offer the advantage that muscle protein degradation can be assessed by excretion of 3 methyl-histidine and multiple muscle biopsies can be taken from the same animal. On the final day of infusion blood samples were taken for hormone and metabolite measurement and muscle biopsies for expression of ubiquitin, the 14-kDa E2 ubiquitin conjugating enzyme, and proteasome sub-units C2 and C8. Results: On day 5 of glucose infusion, plasma glucose, insulin and IGF-1 concentrations were increased while urea nitrogen excretion and myofibrillar protein degradation was decreased. Co-infusion of glucose + EAA prevented the loss of urinary nitrogen observed with EAA infusions alone and enhanced the increase in plasma IGF-1 concentration but there was no synergistic effect of glucose + EAA on the decrease in myofibrillar protein degradation. Muscle mRNA expression of the ubiquitin conjugating enzyme, 14-kDa E2 and proteasome sub-unit C2 were significantly decreased, after glucose but not amino acid infusions, and there was no further response to the combined infusions of glucose + EAA. Conclusion: Prolonged glucose infusion decreases myofibrillar protein degradation, prevents the excretion of infused EAA, and acts additively with EAA to increase plasma IGF-1 and improve net nitrogen balance. There was no evidence of synergistic effects between glucose + EAA infusion on muscle protein degradation or expression of components of the ubiquitin-proteasome proteolytic pathway.

Rapid model quality assessment for protein structure predictions using the comparison of multiple models without structural alignments

MOTIVATION: The accurate prediction of the quality of 3D models is a key component of successful protein tertiary structure prediction methods. Currently, clustering or consensus based Model Quality Assessment Programs (MQAPs) are the most accurate methods for predicting 3D model quality; however they are often CPU intensive as they carry out multiple structural alignments in order to compare numerous models. In this study, we describe ModFOLDclustQ - a novel MQAP that compares 3D models of proteins without the need for CPU intensive structural alignments by utilising the Q measure for model comparisons. The ModFOLDclustQ method is benchmarked against the top established methods in terms of both accuracy and speed. In addition, the ModFOLDclustQ scores are combined with those from our older ModFOLDclust method to form a new method, ModFOLDclust2, that aims to provide increased prediction accuracy with negligible computational overhead. RESULTS: The ModFOLDclustQ method is competitive with leading clustering based MQAPs for the prediction of global model quality, yet it is up to 150 times faster than the previous version of the ModFOLDclust method at comparing models of small proteins (<60 residues) and over 5 times faster at comparing models of large proteins (>800 residues). Furthermore, a significant improvement in accuracy can be gained over the previous clustering based MQAPs by combining the scores from ModFOLDclustQ and ModFOLDclust to form the new ModFOLDclust2 method, with little impact on the overall time taken for each prediction. AVAILABILITY: The ModFOLDclustQ and ModFOLDclust2 methods are available to download from: http://www.reading.ac.uk/bioinf/downloads/ CONTACT: l.j.mcguffin@reading.ac.uk.