Targeted protein-omic methods are bridging the gap between proteomic and hypothesis-driven protein analysis approaches

While proteomic methods have illuminated many areas of biological protein space, many fundamental questions remain with regard to systems-level relationships between mRNAs, proteins and cell behaviors. While mass spectrometric methods offer a panoramic picture of the relative expression and modification of large numbers of proteins, they are neither optimal for the analysis of predefined targets across large numbers of samples nor for assessing differences in proteins between individual cells or cell compartments. Conversely, traditional antibody-based methods are effective at sensitively analyzing small numbers of proteins across small numbers of conditions, and can be used to analyze relative differences in protein abundance and modification between cells and cell compartments. However, traditional antibody-based approaches are not optimal for analyzing large numbers of protein abundances and modifications across many samples. In this article, we will review recent advances in methodologies and philosophies behind several microarray-based, intermediate-level, ‘protein-omic’ methods, including a focus on reverse-phase lysate arrays and micro-western arrays, which have been helpful for bridging gaps between large- and small-scale protein analysis approaches and have provided insight into the roles that protein systems play in several biological processes.     

Targeted protein-omic methods are bridging the gap between proteomic and hypothesis-driven protein analysis approaches

While proteomic methods have illuminated many areas of biological protein space, many fundamental questions remain with regard to systems-level relationships between mRNAs, proteins and cell behaviors. While mass spectrometric methods offer a panoramic picture of the relative expression and modification of large numbers of proteins, they are neither optimal for the analysis of predefined targets across large numbers of samples nor for assessing differences in proteins between individual cells or cell compartments. Conversely, traditional antibody-based methods are effective at sensitively analyzing small numbers of proteins across small numbers of conditions, and can be used to analyze relative differences in protein abundance and modification between cells and cell compartments. However, traditional antibody-based approaches are not optimal for analyzing large numbers of protein abundances and modifications across many samples. In this article, we will review recent advances in methodologies and philosophies behind several microarray-based, intermediate-level, 'protein-omic' methods, including a focus on reverse-phase lysate arrays and micro-western arrays, which have been helpful for bridging gaps between large- and small-scale protein analysis approaches and have provided insight into the roles that protein systems play in several biological processes.     

Sexual Dimorphism of the Protein Level in Urine of Muridae Rodents: Relation to Population Numbers

The results of a comparative study conducted on the water vole, steppe lemming, and Campbell hamster, fulfilled by data published on seven other Muridae rodent species, have revealed a positive relation between the extent of sexual dimorphism estimated by the protein level in urine and population numbers typical for each species and the amplitude of its variation. In species with usually low population numbers, the ratio of protein in urine of males to females comprises 0.9; in species with relative stable population numbers, it is 3.4; and, in species with a high amplitude of periodically fluctuating population numbers, it is 8.3.     

Analysis of miRNA regulation suggests an explanation for 'unexpected' increase in target protein levels

MicroRNA (miRNA) has been mostly associated with decrease in target protein expression levels. Recently, 'unexpected' observations of increase in target protein expression attributed to microRNA regulation have been reported. We formulate a comprehensive model for regulation by miRNA that includes both reversible mRNA-miRNA binding and selective return of RNA. We use this mathematical model incorporating multiple individual steps in the regulation process to study the simultaneous effects of these steps on the target protein level. We show that four dimensionless numbers obtained from 12 rate constants are sufficient to define the relative change in steady state target protein levels. We quantify the range of these numbers for which such pleiotropic increase in protein levels is possible, and interpret the experimental findings in the framework of our model such that the results are no longer unexpected. Finally, we show through stochastic simulation that the nature of the target protein distribution remains unchanged and the relative steady state noise levels are also completely defined by the values of these dimensionless numbers, irrespective of the individual reaction rate constants.     

Two-color fluorescence analysis of individual virions determines the distribution of the copy number of proteins in herpes simplex virus particles

We present a single virion method to determine absolute distributions of copy number in the protein composition of viruses and apply it to herpes simplex virus type 1. Using two-color coincidence fluorescence spectroscopy, we determine the virion-to-virion variability in copy numbers of fluorescently labeled tegument and envelope proteins relative to a capsid protein by analyzing fluorescence intensity ratios for ensembles of individual dual-labeled virions and fitting the resulting histogram of ratios. Using EYFP-tagged capsid protein VP26 as a reference for fluorescence intensity, we are able to calculate the mean and also, for the first time to our knowledge, the variation in numbers of gD, VP16, and VP22 tegument. The measurement of the number of glycoprotein D molecules was in good agreement with independent measurements of average numbers of these glycoproteins in bulk virus preparations, validating the method. The accuracy, straightforward data processing, and high throughput of this technique make it widely applicable to the analysis of the molecular composition of large complexes in general, and it is particularly suited to providing insights into virus structure, assembly, and infectivity.     

黄鳝血清和体表粘液蛋白的比较研究

本文用反相高效液相色谱法测定了黄鳝血清和体表粘液蛋白的氨基酸种类和含量,比较了二者的氨基酸组成变化。结果表明：二者都含有17种氨基酸,血清的氨基酸总量为397．11mg／l00ml,体表粘液蛋白的氨基酸总量为259．29mg／l00m1,血清与粘液蛋白中氨基酸含量差异最大的是蛋氨酸、半胱氨酸。应用SDS—PAGE分析和比较了血清和体表粘液蛋白的分子量大小及特有区带效,黄鳝血清与体表粘液蛋白分子量相同的蛋白区带数为2条,其分子量大小分别为19．5kDa、96．0kDa。其中血清的特有蛋白带为18条,体表粘液的特有蛋白带为8条。此外,对二者的相关性和体表粘液特异性的免疫机制作了探讨。     

THE NORMAL INTESTINAL FLORA OF THE PIG II. QUANTITATIVE BACTERIOLOGICAL STUDIES

SUMMARY: Faecal and caecal samples from normal pigs were examined and the factors causing variations in bacterial numbers investigated by a dilution count technique. The range of variation for viable counts of faeces from normal pigs was 1.0 × 10⁸-9.9 × 10⁹/g and was in sufficiently close agreement with the results obtained with caecal contents to justify the use of faecal counts as an index of caecal numbers. The use of individually-fed pigs instead of group-fed pigs, with the consequent reduction of variations in environmental factors, appeared to reduce the variability of the counts. Changes in diet, either by incorporating grass meal or replacing all the animal protein by vegetable protein, did not affect the total numbers of organisms. The small variations in bacterial numbers regarded as significant by some of the earlier workers thus appear to be of little importance. Smears from high dilutions indicated that the predominant organisms were lactobacilli and streptococci; coli-aerogenes types were present in smaller numbers.     

蛋白质空间结构属性与全基因组微生物耐热性的关系

 溶剂接触表面积、空腔个数和体积、紧密度、疏水性以及温度因子是影响蛋白质耐热的主要三维结构参数.挑选NCBI COG数据库中具有全基因组的单细胞微生物,选择其中三维结构已知的蛋白质作为研究对象,分析这些因素对细菌类和古细菌类微生物耐热性的影响.结果表明：（1）古细菌类蛋白质的空腔个数和体积与耐热性无关,极性面积和表面残基个数随耐热性增加而降低;（2）超高温细菌类蛋白质的分子量比较小,空腔个数和体积都小于常温蛋白质,而且空腔个数对稳定性的贡献大于空腔体积;（3）无论是古细菌还是细菌类蛋白质,疏水性和紧密度都不随耐热性变化,但暴露残基个数越多,蛋白质的耐热性越差;（4）两类蛋白质侧链的温度因子都高于主链,这与侧链的运动性（柔性）一般比主链高的实验结果一致;另外,超高温细菌类蛋白质的温度因子明显高于常温蛋白质.     

Negative correlation between protozoal and bacterial levels in rumen samples and its relation to the determination of dietary effects on the rumen microbial population.

The bacterial protein content and protozoal protein content of unfractionated samples from the liquid-small particle phase of the rumen were determined on the basis of direct microscopic measurement of bacteria numbers and protozoa numbers and cell volumes. Standard values of 8.7 X 10(-11) mg of protein per bacterial cell and 5.9 X 10(-11) mg/micron 3 of protozoa cell volume, obtained from analysis of isolated cells, were used to convert the microscopic measurements to an estimate of the protein content of the rumen sample. When the correlation between bacterial and protozoal protein levels was examined within groups of animals, a highly significant negative correlation between these two parameters was found (P less than 0.001). The variation among animals for total (bacterial plus protozoal) microbial protein was smaller than the variation among animals for bacterial or protozoal protein alone. There was also a highly significant positive correlation (P less than 0.001) between protozoal protein level and total microbial protein level. The variation found among animals in total microbial protein level could be reduced by using a regression equation determined for bacterial versus protozoal protein to correct for the different population dynamics of the two groups.     

Dot assay for neomycin phosphotransferase activity in crude cell extracts

A dot assay for determining neomycin phosphotransferase (NPT II) activity in crude cell extracts has been developed. The assay provides for the rapid screening of large numbers of cell cultures generated in gene transformation experiments using NPT II as a dominant selectable marker. Currently, the commonly used procedure for NPT II assay employs a time-consuming electrophoretic protein separation step to eliminate a positive interference resulting from putative protein kinase activities present in crude cell extracts. The dot method we have developed is based upon the ability of nitrocellulose membrane to eliminate that positive interference without a prior protein separation step. It provides a sensitive, reproducible, and significantly more convenient and rapid means of screening large numbers of cell extracts in order to distinguish cultures producing high levels of NPT II from those that do not.     

Prediction of contact numbers of amino acid residues using a neural network regression algorithm

The profile of contact numbers of amino acid residues in proteins contains important information about the protein structure and is connected with the accessibility of residues to solvent. Here we propose a method for predicting the profile of contact numbers of residues in protein from its amino acid sequence. The method is based on regression using a neural network algorithm. The algorithm predicts two types of profiles, namely, the total number of contacts and the number of close contacts with the neighbors in the chain. The Pearson coefficient of correlation between the actual and predicted values of total contact numbers amounted to 0.526–0.703. As for the number of close contacts, this coefficient was higher (0.662–0.743) for all the considered threshold contact distances (6, 8, 10, and 12 Å). The program for prediction of contact numbers CONNP is available at http://wwwmgs2.bionet.nsc.ru/reloaded.

     

ProLoc-GO: Utilizing informative Gene Ontology terms for sequence-based prediction of protein subcellular localization

Background  

Gene Ontology (GO) annotation, which describes the function of genes and gene products across species, has recently been used to predict protein subcellular and subnuclear localization. Existing GO-based prediction methods for protein subcellular localization use the known accession numbers of query proteins to obtain their annotated GO terms. An accurate prediction method for predicting subcellular localization of novel proteins without known accession numbers, using only the input sequence, is worth developing.     

Evaluation of the non-randomness of protein compositions

A method is described for assessing the non-randomness of protein compositions, based on the chi-squared statistic for the differences between the observed numbers of residues of each type and the numbers expected for a random distribution of codons. The analysis indicates that changes in at least 30% of the residues in natural proteins are selected against.     

Amino acid encoding schemes from protein structure alignments: multi-dimensional vectors to describe residue types

Bioinformatic software has used various numerical encoding schemes to describe amino acid sequences. Orthogonal encoding, employing 20 numbers to describe the amino acid type of one protein residue, is often used with artificial neural network (ANN) models. However, this can increase the model complexity, thus leading to difficulty in implementation and poor performance. Here, we use ANNs to derive encoding schemes for the amino acid types from protein three-dimensional structure alignments. Each of the 20 amino acid types is characterized with a few real numbers. Our schemes are tested on the simulation of amino acid substitution matrices. These simplified schemes outperform the orthogonal encoding on small data sets. Using one of these encoding schemes, we generate a colouring scheme for the amino acids in which comparable amino acids are in similar colours. We expect it to be useful for visual inspection and manual editing of protein multiple sequence alignments.     

Protein Information Crawler (PIC): extensive spidering of multiple protein information resources for large protein sets

Proteomic studies often produce sets of hundreds of proteins. Bioinformatic information for these large protein sets must be collected from multiple online resources. Protein Information Crawler (PIC) automatically bulk-collects such data from multiple databases and prediction servers, based on National Center for Biotechnology Information (NCBI) gi numbers or accession numbers, and summarizes them in a Microsoft Excel spreadsheet and/or HTML table. PIC greatly accelerates information procurement, helps to build customized protein information databases and drastically reduces manual database investigation in extensive proteomic studies. Availability: http://www.zoo.uni-heidelberg.de/mfa/PIC.     

Evaluating if Energy and Protein Limit Abundance of Hawaiian Moorhen

Abstract: Food abundance can affect a species' distribution. In many studies of potential food limitation, researchers focus on carrying capacity estimates during the nonbreeding season for temperate species consuming a fixed food source. Estimates of energetic carrying capacity for year-round breeders feeding on a replenishing resource would be more difficult and require much data. To determine whether gathering detailed information on year-round carrying capacity would be an important investment, we conducted an assessment to determine whether there was evidence that energy or protein might limit numbers of the tropical, endangered Hawaiian moorhen (Gallinula chloropus sandvicensis). We compared observed numbers of moorhen at 15 Oahu, Hawaii, USA, wetlands with predicted numbers based on measured energy and protein in food plants and abundance of these food plants in each wetland and on estimates of energy expenditure of moorhen. We made comparisons assuming moorhen are limited by their ability to metabolize food plants, by competition for food, and by estimated costs associated with reproduction. We also compared ranked moorhen abundance and density with ranked energy and protein under different wetland management regimes. Energy values consistently overestimated expected numbers of Hawaiian moorhen at wetlands except for one wetland location (predicted, 3803 ± 4856; observed, 6.2 ± 10.8). In addition, we detected no significant relationship between moorhen abundance and measures of energy (all r² = 0.02–0.73, all P > 0.1) or protein abundance (all r² = 0.08–0.50, all P > 0.3). This lack of relationship held once we controlled for wetland area or when we considered whether wetlands were managed for waterbirds. Hawaiian moorhen on Oahu did not appear to be limited by energy, nor did they appear to select sites based on energy or protein, in contrast to many studies relating animal numbers to energy in nonbreeding situations. Consequently, we suggest that researchers and managers explore other potentially limiting factors for Hawaiian moorhen.     

Quantitative proteome profiling of normal human circulating microparticles

Circulating microparticles (MPs) are produced as part of normal physiology. Their numbers, origin, and composition change in pathology. Despite this, the normal MP proteome has not yet been characterized with standardized high-resolution methods. We here quantitatively profile the normal MP proteome using nano-LC-MS/MS on an LTQ-Orbitrap with optimized sample collection, preparation, and analysis of 12 different normal samples. Analytical and procedural variation were estimated in triply processed samples analyzed in triplicate from two different donors. Label-free quantitation was validated by the correlation of cytoskeletal protein intensities with MP numbers obtained by flow cytometry. Finally, the validity of using pooled samples was evaluated using overlap protein identification numbers and multivariate data analysis. Using conservative parameters, 536 different unique proteins were quantitated. Of these, 334 (63%) were present in all samples and represent an MP core proteome. Technical triplicates showed <10% variation in intensity within a dynamic range of almost 5 decades. Differences due to variable MP numbers and losses during preparative steps could be normalized using cytoskeletal MP protein intensities. Our results establish a reproducible LC-MS/MS procedure, provide a simple and robust MP preparation method, and yield a baseline MP proteome for future studies of MPs in health and disease.     

RCNPRED: prediction of the residue co-ordination numbers in proteins

The RCNPRED server implements a neural network-based method to predict the co-ordination numbers of residues starting from the protein sequence. Using evolutionary information as input, RCNPRED predicts the residue states of the proteins in the database with 69% accuracy and scores 12 percentage points higher than a simple statistical method. Moreover the server implements a neural network to predict the relative solvent accessibility of each residue. A protein sequence can be directly submitted to RCNPRED: residue co-ordination numbers and solvent accessibility for each chain are returned via e-mail. AVAILABILITY: Freely available to non-commercial users at http://prion.biocomp.unibo.it/rcnpred.html.     

Stochastic Modeling of Autoregulatory Genetic Feedback Loops: A Review and Comparative Study

Autoregulatory feedback loops are one of the most common network motifs. A wide variety of stochastic models have been constructed to understand how the fluctuations in protein numbers in these loops are influenced by the kinetic parameters of the main biochemical steps. These models differ according to 1) which subcellular processes are explicitly modeled, 2) the modeling methodology employed (discrete, continuous, or hybrid), and 3) whether they can be analytically solved for the steady-state distribution of protein numbers. We discuss the assumptions and properties of the main models in the literature, summarize our current understanding of the relationship between them, and highlight some of the insights gained through modeling.