Accentuate the Negative:Proteome Comparisons Using the Negative Proteome Database

The availability of complete genome sequence information for diverse organisms including model genetic organisms has ushered in a new era of protein sequence comparisons making it possible to search for commonalities among entire proteomes using the Basic Local Alignment Search Tool (BLAST). Although the identification and analysis of proteins shared by humans and model organisms has proven an invaluable tool to understanding gene function, the sets of proteins unique to a given model organism's proteome have remained largely unexplored. We have constructed a searchable database that allows biologists to identify proteins unique to a given proteome. The Negative Proteome Database (NPD) is populated with pair-wise protein sequence comparisons between each of the following proteomes: Homo sapiens, Mus musculus, Drosophila melanogaster, Caenorhabditis elegans, Saccharomyces cerevisiae, Dictyostelium discoideum, Chlamydomonus reinhardti, Escherichia coli K12, Arabidopsis thaliana and Methanoscarcina acetivorans. Our analysis of negative proteome datasets using the NPD has thus far revealed 107 proteins in humans that may be involved in motile cilia function, 1628 potential pesticide target proteins in flies, 659 proteins shared by flies and humans that are not represented in the less neurologically complex worm proteome, and 180 nuclear encoded human disease associated proteins that are absent from the fly proteome. The NPD is the only online resource where users can quickly perform complex negative and positive comparisons of model organism proteomes. We anticipate that the NPD and the adaptable algorithm which can readily be used to duplicate this analysis on custom sets of proteomes will be an invaluable tool in the investigation of organism specific protein sets.     

Highly specific protein-protein interactions, evolution and negative design

We consider highly specific protein-protein interactions in proteomes of simple model proteins. We are inspired by the work of Zarrinpar et al (2003 Nature 426 676). They took a binding domain in a signalling pathway in yeast and replaced it with domains of the same class but from different organisms. They found that the probability of a protein binding to a protein from the proteome of a different organism is rather high, around one half. We calculate the probability of a model protein from one proteome binding to the protein of a different proteome. These proteomes are obtained by sampling the space of functional proteomes uniformly. In agreement with Zarrinpar et al we find that the probability of a protein binding a protein from another proteome is rather high, of order one tenth. Our results, together with those of Zarrinpar et al, suggest that designing, say, a peptide to block or reconstitute a single signalling pathway, without affecting any other pathways, requires knowledge of all the partners of the class of binding domains the peptide is designed to mimic. This knowledge is required to use negative design to explicitly design out interactions of the peptide with proteins other than its target. We also found that patches that are required to bind with high specificity evolve more slowly than those that are required only to not bind to any other patch. This is consistent with some analysis of sequence data for proteins engaged in highly specific interactions.     

Profiling the membrane proteome of Shewanella oneidensis MR-1 with new affinity labeling probes

The membrane proteome plays a critical role in electron transport processes in Shewanella oneidensis MR-1, a bacterial organism that has great potential for bioremediation. Biotinylation of intact cells with subsequent affinity-enrichment has become a useful tool for characterization of the membrane proteome. As opposed to these commonly used, water-soluble commercial reagents, we here introduce a family of hydrophobic, cell-permeable affinity probes for extensive labeling and detection of membrane proteins. When applied to S. oneidensis cells, all three new chemical probes allowed identification of a substantial proportion of membrane proteins from total cell lysate without the use of specific membrane isolation method. From a total of 410 unique proteins identified, approximately 42% are cell envelope proteins that include outer membrane, periplasmic, and inner membrane proteins. This report demonstrates the first application of this intact cell biotinylation method to S. oneidensis and presents the results of many identified proteins that are involved in metal reduction processes. As a general labeling method, all chemical probes we introduced in this study can be extended to other organisms or cell types and will help expedite the characterization of membrane proteomes.     

Phylomat: an automated protein motif analysis tool for phylogenomics

Recent progress in genomics, proteomics, and bioinformatics enables unprecedented opportunities to examine the evolutionary history of molecular, cellular, and developmental pathways through phylogenomics. Accordingly, we have developed a motif analysis tool for phylogenomics (Phylomat, http://alg.ncsa.uiuc.edu/pmat) that scans predicted proteome sets for proteins containing highly conserved amino acid motifs or domains for in silico analysis of the evolutionary history of these motifs/domains. Phylomat enables the user to download results as full protein or extracted motif/domain sequences from each protein. Tables containing the percent distribution of a motif/domain in organisms normalized to proteome size are displayed. Phylomat can also align the set of full protein or extracted motif/domain sequences and predict a neighbor-joining tree from relative sequence similarity. Together, Phylomat serves as a user-friendly data-mining tool for the phylogenomic analysis of conserved sequence motifs/domains in annotated proteomes from the three domains of life.     

种子蛋白质组的研究进展

蛋白质组学是通过对全套蛋白质动态的研究,来阐明生物体、组织、细胞和亚细胞全部蛋白质的表达模式及功能模式。大量可用的核苷酸序列信息和灵敏高速的质谱鉴定技术,使得蛋白质组学方法为分析模式植物和农作物的复杂功能开辟了新的途径。目前,种子蛋白质组研究主要集中在两个方面：一方面是鉴定尽可能多的蛋白,以创建种子特定生命时期的蛋白质组参照图谱;另一方面主要集中在差异蛋白质组,通过比较分析不同蛋白质组,以探明关键功能蛋白。该文综述了近年来种子蛋白质组的研究进展,内容包括种子发育过程中蛋白质组的变化,与种子休眠/萌发相关的蛋白质组、翻译后修饰蛋白质组、细胞与亚细胞差异蛋白质组以及环境因子对种子蛋白质组的影响;并对种子蛋白质组研究的热点问题进行了展望。     

种子蛋白质组的研究进展

蛋白质组学是通过对全套蛋白质动态的研究, 来阐明生物体、组织、细胞和亚细胞全部蛋白质的表达模式及功能模式。大量可用的核苷酸序列信息和灵敏高速的质谱鉴定技术, 使得蛋白质组学方法为分析模式植物和农作物的复杂功能开辟了新的途径。目前, 种子蛋白质组研究主要集中在两个方面: 一方面是鉴定尽可能多的蛋白, 以创建种子特定生命时期的蛋白质组参照图谱; 另一方面主要集中在差异蛋白质组, 通过比较分析不同蛋白质组, 以探明关键功能蛋白。该文综述了近年来种子蛋白质组的研究进展, 内容包括种子发育过程中蛋白质组的变化, 与种子休眠/萌发相关的蛋白质组、翻译后修饰蛋白质组、细胞与亚细胞差异蛋白质组以及环境因子对种子蛋白质组的影响; 并对种子蛋白质组研究的热点问题进行了展望。     

The use of proteome similarity for the qualitative and quantitative profiling of reperfused myocardium

An LC-MS-based approach is presented for the identification and quantification of proteins from unsequenced organisms. The method relies on the preservation of homology across species and the similarity in detection characteristics of proteomes in general. Species related proteomes share similarity that progresses from the amino acid frequency distribution to the complete amino sequence of matured proteins. Moreover, the comparative analysis between theoretical and experimental proteome distributions can be used as a measure for the correctness of detection and identification obtained through LC-MS-based schemes. Presented are means to the identification and quantification of rabbit myocardium proteins, immediately after inducing cardiac arrest, using a data-independent LC-MS acquisition strategy. The employed method of acquisition affords accurate mass information on both the precursor and associated product ions, whilst preserving and recording the intensities of the ions. The latter facilitates label-free quantification. The experimental ion density observations obtained for the rabbit sub proteome were found to share great similarity with five other mammalian samples, including human heart, human breast tissue, human plasma, rat liver and a mouse cell line. Redundant, species-homologues peptide identifications from other mammalian organisms were used for initial protein identification, which were complemented with peptide identifications of translated gene sequences. The feasibility and accuracy of label-free quantification of the identified peptides and proteins utilizing above mentioned strategy is demonstrated for selected cardiac rabbit proteins.     

Plant proteome analysis

Proteome analysis is becoming a powerful tool in the functional characterization of plants. Due to the availability of vast nucleotide sequence information and based on the progress achieved in sensitive and rapid protein identification by mass spectrometry, proteome approaches open up new perspectives to analyze the complex functions of model plants and crop species at different levels. In this review, an overview is given on proteome studies performed to analyze whole plants or specific tissues with particular emphasis on important physiological processes such as germination. The chapter on subcellular proteome analysis of plants focuses on the progress achieved for plastids and mitochondria but also mentions the difficulties associated with membrane-bound proteins of these organelles. Separate chapters are dedicated to the challenging analysis of woody plants and to the use of proteome approaches to investigate the interaction of plants with pathogens or with symbiotic organisms. Limitations of current techniques and recent conceptual and technological perspectives for plant proteomics are briefly discussed in the final chapter.     

Investigation of the mouse serum proteome

With the rapid assimilation of genomic information and the equally impressive developments in the field of proteomics, there is an unprecedented interest in biomarker discovery. Although human biofluids represent increasingly attractive samples from which new and more accurate disease biomarkers may be found, the intrinsic person-to-person variability in these samples complicates their discovery. One of the most extensively used animal models for studying human disease is mouse because, unlike humans, they represent a highly controllable experimental model system. Unfortunately, very little is known about the proteomic composition of mouse serum. In this study, a multidimensional fractionation approach on both the protein and the peptide level that does not require depletion of highly abundant serum proteins was combined with tandem mass spectrometry to characterize proteins within mouse serum. Over 12 300 unique peptides that originate from 4567 unique proteins-approximately 16% of all known mouse proteins-were identified. The results presented here represent the broadest proteome coverage in mouse serum and provide a foundation from which quantitative comparisons can be made in this important animal model.     

Improvements in proteomic metrics of low abundance proteins through proteome equalization using ProteoMiner prior to MudPIT

Ideally, shotgun proteomics would facilitate the identification of an entire proteome with 100% protein sequence coverage. In reality, the large dynamic range and complexity of cellular proteomes results in oversampling of abundant proteins, while peptides from low abundance proteins are undersampled or remain undetected. We tested the proteome equalization technology, ProteoMiner, in conjunction with Multidimensional Protein Identification Technology (MudPIT) to determine how the equalization of protein dynamic range could improve shotgun proteomics methods for the analysis of cellular proteomes. Our results suggest low abundance protein identifications were improved by two mechanisms: (1) depletion of high abundance proteins freed ion trap sampling space usually occupied by high abundance peptides and (2) enrichment of low abundance proteins increased the probability of sampling their corresponding more abundant peptides. Both mechanisms also contributed to dramatic increases in the quantity of peptides identified and the quality of MS/MS spectra acquired due to increases in precursor intensity of peptides from low abundance proteins. From our large data set of identified proteins, we categorized the dominant physicochemical factors that facilitate proteome equalization with a hexapeptide library. These results illustrate that equalization of the dynamic range of the cellular proteome is a promising methodology to improve low abundance protein identification confidence, reproducibility, and sequence coverage in shotgun proteomics experiments, opening a new avenue of research for improving proteome coverage.     

Development of a Listeria monocytogenes EGDe partial proteome reference map and comparison with the protein profiles of food isolates

A partially annotated proteome reference map of the food pathogen Listeria monocytogenes was developed for exponentially growing cells under standardized, optimal conditions by using the sequenced strain EGDe (serotype 1/2a) as a model organism. The map was developed by using a reproducible total protein extraction and two-dimensional (2-D) polyacrylamide gel electrophoresis analysis procedure, and it contained 33 identified proteins representing the four main protein functional classes. In order to facilitate analysis of membrane proteins, a protein compartmentalization procedure was assessed. The method used provided partial fractionation of membrane and cytosolic proteins. The total protein 2-D profiles of three serotype 1/2a strains and one serotype 1/2b strain isolated from food were compared to the L. monocytogenes EGDe proteome. An average of 13% of the major protein spots in the food strain proteomes were not matched in the strain EGDe proteome. The variation was greater for the less intense spots, and on average 28% of these spots were not matched. Two of the proteins identified in L. monocytogenes EGDe were missing in one or more of the food isolates. These two proteins were proteins involved in the main glycolytic pathway and in metabolism of coenzymes and prosthetic groups. The two corresponding genes were found by PCR amplification to be present in the four food isolates. Our results show that the L. monocytogenes EGDe reference map is a valuable starting point for analyses of strains having various origins and could be useful for analyzing the proteomes of different isolates of this pathogen.     

Deep coverage mouse red blood cell proteome: a first comparison with the human red blood cell

Mice have close genetic/physiological relationships to humans, breed rapidly, and can be genetically modified, making them the most used mammal in biomedical research. Because the red blood cell (RBC) is the sole gas transporter in vertebrates, diseases of the RBC are frequently severe; much research has therefore focused on RBC and cardiovascular disorders of mouse and humans. RBCs also host malaria parasites. Recently we presented an in-depth proteome for the human RBC. Here we present directly comparable data for the mouse RBC as membrane-only, soluble-only, and combined membrane-bound/soluble proteomes (comprising, respectively, 247, 232, and 165 proteins). All proteins were identified, validated, and categorized in terms of subcellular localization, protein family, and function, and in comparison with the human RBC, were classified as orthologs, family-related, or unique. Splice isoforms were identified, and polypeptides migrating with anomalous apparent molecular weights were grouped into putatively ubiquitinated or partially degraded complexes. Overall there was close concordance between mouse and human proteomes, confirming the unexpected RBC complexity. Several novel findings in the human proteome have been confirmed here. This comparison sheds light on several open issues in RBC biology and provides a departure point for more comprehensive understanding of RBC function.     

Exo‐ and surface proteomes of the probiotic bacterium Lactobacillus acidophilus NCFM

Lactobacillus acidophilus NCFM is a well‐known probiotic bacterium extensively studied for its beneficial health effects. Exoproteome (proteins exported into culture medium) and surface proteome (proteins attached to S‐layer) of this probiotic were identified by using 2DE followed by MALDI TOF MS to find proteins potentially involved in bacteria–host interactions. The exo‐ and surface proteomes included 43 and 39 different proteins from 72 and 49 successfully identified spots, respectively. Twenty‐two proteins were shared between the two proteomes; both contained the major surface layer protein that participates in host interaction as well as several well‐known and putative moonlighting proteins. The exoproteome contained nine classically‐secreted (containing a signal sequence) and ten nonclassically‐secreted proteins, while the surface proteome contained four classically‐secreted and eight nonclassically secreted proteins. Identification of exo‐ and surface proteomes contributes describing potential protein‐mediated probiotic–host interactions.     

PCAS – a precomputed proteome annotation database resource

Background  

Many model proteomes or "complete" sets of proteins of given organisms are now publicly available. Much effort has been invested in computational annotation of those "draft" proteomes. Motif or domain based algorithms play a pivotal role in functional classification of proteins. Employing most available computational algorithms, mainly motif or domain recognition algorithms, we set up to develop an online proteome annotation system with integrated proteome annotation data to complement existing resources.