Organisms can essentially be classified according to two codon patterns

We recently classified 23 bacteria into two types based on their complete genomes; “S-type” as represented by Staphylococcus aureus and “E-type” as represented by Escherichia coli. Classification was characterized by concentrations of Arg, Ala or Lys in the amino acid composition calculated from the complete genome. Based on these previous classifications, not only prokaryotic but also eukaryotic genome structures were investigated by amino acid compositions and nucleotide contents. Organisms consisting of 112 bacteria, 15 archaea and 18 eukaryotes were classified into two major groups by cluster analysis using GC contents at the three codon positions calculated from complete genomes. The 145 organisms were classified into “AT-type” and “GC-type” represented by high A or T (low G or C) and high G or C (low A or T) contents, respectively, at every third codon position. Reciprocal changes between G or C and A or T contents at the third codon position occurred almost synchronously in every codon among the organisms. Correlations between amino acid concentrations (Ala, Ile and Lys) and the nucleotide contents at the codon position were obtained in both “AT-type” and “GC-type” organisms, but with different regression coefficients. In certain correlations of amino acid concentrations with GC contents, eukaryotes, archaea and bacteria showed different behaviors; thus these kingdoms evolved differently. All organisms are basically classifiable into two groups having characteristic codon patterns; organisms with low GC and high AT contents at the third codon position and their derivatives, and organisms with an inverse relationship.     

Estimation of membrane proteins in the human proteome

Genomics and proteomics have added valuable information to our knowledgebase of the human biological system including the discovery of therapeutic targets and disease biomarkers. However, molecular profiling studies commonly result in the identification of novel proteins of unknown localization. A class of proteins of special interest is membrane proteins, in particular plasma membrane proteins. Despite their biological and medical significance, the 3-dimensional structures of less than 1% of plasma membrane proteins have been determined. In order to aid in identification of membrane proteins, a number of computational methods have been developed. These tools operate by predicting the presence of transmembrane segments. Here, we utilized five topology prediction methods (TMHMM, SOSUI, waveTM, HMMTOP, and TopPred II) in order to estimate the ratio of integral membrane proteins in the human proteome. These methods employ different algorithms and include a newly-developed method (waveTM) that has yet to be tested on a large proteome database. Since these tools are prone for error mainly as a result of falsely predicting signal peptides as transmembrane segments, we have utilized an additional method, SignalP. Based on our analyses, the ratio of human proteins with transmembrane segments is estimated to fall between 15% and 39% with a consensus of 13%. Agreement among the programs is reduced further when both a positive identification of a membrane protein and the number of transmembrane segments per protein are considered. Such a broad range of prediction depends on the selectivity of the individual method in predicting integral membrane proteins. These methods can play a critical role in determining protein structure and, hence, identifying suitable drug targets in humans.     

Physiological conditions can be reflected in human urine proteome and metabolome

Biomarkers are the measurable changes associated with physiological or pathophysiological processes. Urine, unlike blood, lacks mechanisms for maintaining homeostasis: it is therefore an ideal source of biomarkers that can reflect systemic changes. Urinary proteome and metabolome have been studied for their diagnostic capabilities, ability to monitor disease and prognostic utility. In this review, the effects of common physiological conditions such as gender, age, diet, daily rhythms, exercise, hormone status, lifestyle and extreme environments on human urine are discussed. These effects should be considered when biomarker studies of diseases are conducted. More importantly, if physiological changes can be reflected in urine, we have reason to expect that urine will become widely used to detect small and early changes in pathological and/or pharmacological conditions.     

Mapping the membrane proteome of Corynebacterium glutamicum

In order to avoid the specific problems with intrinsic membrane proteins in proteome analysis, a new procedure was developed which is superior to the classical two-dimensional polyacrylamide gel electrophoresis (2-D PAGE) method in terms of intrinsic membrane proteins. For analysis of the membrane proteome from Corynebacterium glutamicum, we replaced the first separation dimension, i.e., the isoelectric focusing step, by anion-exchange chromatography, followed by sodium dodecyl sulfate (SDS)-PAGE in the second separation dimension. Enrichment of the membrane intrinsic subproteome was achieved by washing with 2.5 M NaBr which removed more than 35% of the membrane-associated soluble proteins. For the extraction and solubilization of membrane proteins, the detergent amidosulfobetaine 14 (ASB-14) was most efficient in a detailed screening procedure and proved also suitable for chromatography. 356 gel bands were spotted, and out of 170 different identified proteins, 50 were membrane-integral. Membrane proteins with one up to 13 transmembrane helices were found. Careful analysis revealed that this new procedure covers proteins from a wide pI range (3.7-10.6) and a wide mass range of 10-120 kDa. About 50% of the identified membrane proteins belong to various functional categories like energy metabolism, transport, signal transduction, protein translocation, and proteolysis while for the others a function is not yet known, indicating the potential of the developed method for elucidation of membrane proteomes in general.     

Structural proteome of human colostral fat globule membrane proteins

Milk fat globule membrane (MFGM) contains proteins derived from the apical membrane of secreting epithelial cells of the mammary gland. Between 2-4% of total human milk protein content is associated with the fat globule fraction, as MFGM proteins. While MFGM proteins have very low classical nutritional value, they play important roles in various cell processes and defence mechanisms for the newborn. To date, fewer than 30 human MFGM proteins have been identified and characterized, either by immunological methods or by Edman sequencing and mass spectrometry. This study aimed to update the structural proteome of human colostral MFGM proteins and to create an annotated two-dimensional electrophoresis (2-DE) MFGM protein database available on-line. More than one hundred 2-DE spots derived from human colostral MFGM proteins were investigated by matrix-assisted laser desorption/ionization-time of flight mass spectrometry and proteins were identified by three different software packages available on the web (PeptIdent, MS-Fit and ProFound); uncertain identifications were solved by nanoelectrospray ionization-ion trap mass spectrometry using SEQUEST software.     

Mapping the human skeletal muscle proteome: progress and potential

Introduction: Human skeletal muscle represents 40% of our body mass and deciphering its proteome composition to further understand mechanisms regulating muscle function under physiological and pathological conditions has proved a challenge. The inter-individual variability, the presence of structurally and functionally different muscle types and the high protein dynamic range require carefully selected methodologies for the assessment of the muscle proteome. Furthermore, physiological studies are understandingly hampered by ethical issues related to biopsies on healthy subjects, making it difficult to recruit matched controls essential for comparative studies.

Areas covered: This review critically analyses studies performed on muscle to date and identifies what still remains unknown or poorly investigated in physiological and pathological states, such as training, aging, metabolic disorders and muscular dystrophies.

Expert commentary: Efforts should be made on biological fluid analyses targeting low abundant/low molecular weight fragments generated from muscle cell disruption to improve diagnosis and clinical monitoring. From a methodological point of view, particular attention should be paid to improve the characterization of intact proteins and unknown post translational modifications to better understand the molecular mechanisms of muscle disorders.     

The human urinary proteome contains more than 1500 proteins, including a large proportion of membrane proteins

Background  

Urine is a desirable material for the diagnosis and classification of diseases because of the convenience of its collection in large amounts; however, all of the urinary proteome catalogs currently being generated have limitations in their depth and confidence of identification. Our laboratory has developed methods for the in-depth characterization of body fluids; these involve a linear ion trap-Fourier transform (LTQ-FT) and a linear ion trap-orbitrap (LTQ-Orbitrap) mass spectrometer. Here we applied these methods to the analysis of the human urinary proteome.     

Mapping and analyzing the human liver proteome: progress and potential

Introduction: The liver is an important organ in humans. Hepatocellular carcinoma (HCC) is one of the deadliest cancers in the world. Progress in the Human Liver Proteome Project (HLPP) has improved understanding of the liver and the liver cancer proteome.

Areas covered: Here, we summarize the recent progress in liver proteome modification profiles, proteomic studies in liver cancer, proteomic study in the search for novel liver cancer biomarkers and drug targets, and progress of the Chromosome Centric Human Proteome Project (CHPP) in the past five years in the Institutes of Biomedical Sciences (IBS) of Fudan University.

Expert commentary: Recent advances and findings discussed here provide great promise of improving the outcome of patients with liver cancer.     

From genes to proteins: high-throughput expression and purification of the human proteome

The development of high-throughput methods for gene discovery has paved the way for the design of new strategies for genome-scale protein analysis. Lawrence Livermore National Laboratory and Onyx Pharmaceuticals, Inc., have produced an automatable system for the expression and purification of large numbers of proteins encoded by cDNA clones from the IMAGE (Integrated Molecular Analysis of Genomes and Their Expression) collection. This high-throughput protein expression system has been developed for the analysis of the human proteome, the protein equivalent of the human genome, comprising the translated products of all expressed genes. Functional and structural analysis of novel genes identified by EST (Expressed Sequence Tag) sequencing and the Human Genome Project will be greatly advanced by the application of this high-throughput expression system for protein production. A prototype was designed to demonstrate the feasibility of our approach. Using a PCR-based strategy, 72 unique IMAGE cDNA clones have been used to create an array of recombinant baculoviruses in a 96-well microtiter plate format. Forty-two percent of these cDNAs successfully produced soluble, recombinant protein. All of the steps in this process, from PCR to protein production, were performed in 96-well microtiter plates, and are thus amenable to automation. Each recombinant protein was engineered to incorporate an epitope tag at the amino terminal end to allow for immunoaffinity purification. Proteins expressed from this system are currently being analyzed for functional and biochemical properties.     

Relationship between the tissue-specificity of mouse gene expression and the evolutionary origin and function of the proteins

Background  

The combination of complete genome sequence information with expression data enables us to characterize the relationship between a protein's evolutionary origin or functional category and its expression pattern. In this study, mouse proteins were assigned into functional and phyletic groups and the gene expression patterns of the different protein groupings were examined by microarray analysis in various mouse tissues.     

Partitioning the proteome: phase separation for targeted analysis of membrane proteins in human post-mortem brain

Neuroproteomics is a powerful platform for targeted and hypothesis driven research, providing comprehensive insights into cellular and sub-cellular disease states, Gene × Environmental effects, and cellular response to medication effects in human, animal, and cell culture models. Analysis of sub-proteomes is becoming increasingly important in clinical proteomics, enriching for otherwise undetectable proteins that are possible markers for disease. Membrane proteins are one such sub-proteome class that merit in-depth targeted analysis, particularly in psychiatric disorders. As membrane proteins are notoriously difficult to analyse using traditional proteomics methods, we evaluate a paradigm to enrich for and study membrane proteins from human post-mortem brain tissue. This is the first study to extensively characterise the integral trans-membrane spanning proteins present in human brain. Using Triton X-114 phase separation and LC-MS/MS analysis, we enriched for and identified 494 membrane proteins, with 194 trans-membrane helices present, ranging from 1 to 21 helices per protein. Isolated proteins included glutamate receptors, G proteins, voltage gated and calcium channels, synaptic proteins, and myelin proteins, all of which warrant quantitative proteomic investigation in psychiatric and neurological disorders. Overall, our sub-proteome analysis reduced sample complexity and enriched for integral membrane proteins by 2.3 fold, thus allowing for more manageable, reproducible, and targeted proteomics in case vs. control biomarker studies. This study provides a valuable reference for future neuroproteomic investigations of membrane proteins, and validates the use Triton X-114 detergent phase extraction on human post mortem brain.     

Computational prediction of human proteins that can be secreted into the bloodstream

We present a novel computational method for predicting which proteins from highly and abnormally expressed genes in diseased human tissues, such as cancers, can be secreted into the bloodstream, suggesting possible marker proteins for follow-up serum proteomic studies. A main challenging issue in tackling this problem is that our understanding about the downstream localization after proteins are secreted outside the cells is very limited and not sufficient to provide useful hints about secretion to the bloodstream. To bypass this difficulty, we have taken a data mining approach by first collecting, through extensive literature searches, human proteins that are known to be secreted into the bloodstream due to various pathological conditions as detected by previous proteomic studies, and then asking the question: 'what do these secreted proteins have in common in terms of their physical and chemical properties, amino acid sequence and structural features that can be used to predict them?' We have identified a list of features, such as signal peptides, transmembrane domains, glycosylation sites, disordered regions, secondary structural content, hydrophobicity and polarity measures that show relevance to protein secretion. Using these features, we have trained a support vector machine-based classifier to predict protein secretion to the bloodstream. On a large test set containing 98 secretory proteins and 6601 non-secretory proteins of human, our classifier achieved approximately 90% prediction sensitivity and approximately 98% prediction specificity. Several additional datasets are used to further assess the performance of our classifier. On a set of 122 proteins that were found to be of abnormally high abundance in human blood due to various cancers, our program predicted 62 as blood-secreted proteins. By applying our program to abnormally highly expressed genes in gastric cancer and lung cancer tissues detected through microarray gene expression studies, we predicted 13 and 31 as blood secreted, respectively, suggesting that they could serve as potential biomarkers for these two cancers, respectively. Our study demonstrated that our method can provide highly useful information to link genomic and proteomic studies for disease biomarker discovery. Our software can be accessed at http://csbl1.bmb.uga.edu/cgi-bin/Secretion/secretion.cgi.     

Properties of the membrane proteins of rat liver lysosomes. The majority of lysosomal membrane proteins are exposed to the cytoplasm.

Rat liver lysosomes were lysed and subfractionated by differential centrifugation through 0.2M-NaCl to yield a membranous pellet. This membrane fraction contains less than 20% of the lysosomal protein, adenosine triphosphatase activity of about 1.2mumol/min per mg of protein, 120nmol of thiol groups/mg of protein and at least 16 protein and glycoprotein bands on sodium dodecyl sulphate/polyacrylamide-gel electrophoresis. The gel patterns of membranes isolated from lysosomes after treatment with (1) [125I]iodidehydrogen peroxide-lactoperoxidase, (2) toluene 2,4-di-isocyanate-activated bovine serum albumin, (3) trypsin and (4) subtilisin indicate that most of the membrane proteins are exposed to the cytoplasm. These exposed proteins are candidates for intracellular receptors which recognize either substances that are to be degraded or vesicles containing those substances.     

Unseen proteome: mining below the tip of the iceberg to find low abundance and membrane proteins

Abundant and hydrophilic nonmembrane proteins with isoelectric points below pH 8 are the predominant proteins identified in most proteomics projects. In yeast, however, low-abundance proteins make up 80% of the predicted proteome, approximately 50% have pl's above pH 8 and 30% of the yeast ORFs are predicted to encode membrane proteins with at least 1 trans-membrane span. By applying highly solubilizing reagents and isoelectric fractionation to a membrane fraction of yeast we have a purified and identified 780 protein isoforms, representing 323 gene products, including 28% low abundance proteins and 49% membrane or membrane associated proteins. More importantly, considering the frequency and importance of co- and post-translational modifications, the separation of protein isoforms is essential and two-dimensional electrophoresis remains the only technique which offers sufficient resolution to address this at a proteomic level.     

Use of a proteome strategy for tagging proteins present at the plasma membrane

A plasma membrane (PM) fraction was purified from Arabidopsis thaliana using a standard procedure and analyzed by two-dimensional (2D) gel electrophoresis. The proteins were classified according to their relative abundance in PM or cell membrane supernatant fractions. Eighty-two of the 700 spots detected on the PM 2D gels were microsequenced. More than half showed sequence similarity to proteins of known function. Of these, all the spots in the PM-specific and PM-enriched fractions, together with half of the spots with similar abundance in PM fraction and supernatant, have previously been found at the PM, supporting the validity of this approach. Extrapolation from this analysis indicates that (i) approximately 550 polypeptides found at the PM could be resolved on 2D gels; (ii) that numerous proteins with multiple locations are found at the PM; and (iii) that approximately 80% of PM-specific spots correspond to proteins with unknown function. Among the later, half are represented by ESTs or cDNAs in databases. In this way, several unknown gene products were potentially localized to the PM. These data are discussed with respect to the efficiency of organelle proteome approaches to link systematically genomic data to genome expression. It is concluded that generalized proteomes can constitute a powerful resource, with future completion of Arabidopsis genome sequencing, for genome-wide exploration of plant function.     

In-depth analysis of the thylakoid membrane proteome of Arabidopsis thaliana chloroplasts: new proteins, new functions, and a plastid proteome database

An extensive analysis of the Arabidopsis thaliana peripheral and integral thylakoid membrane proteome was performed by sequential extractions with salt, detergent, and organic solvents, followed by multidimensional protein separation steps (reverse-phase HPLC and one- and two-dimensional electrophoresis gels), different enzymatic and nonenzymatic protein cleavage techniques, mass spectrometry, and bioinformatics. Altogether, 154 proteins were identified, of which 76 (49%) were alpha-helical integral membrane proteins. Twenty-seven new proteins without known function but with predicted chloroplast transit peptides were identified, of which 17 (63%) are integral membrane proteins. These new proteins, likely important in thylakoid biogenesis, include two rubredoxins, a potential metallochaperone, and a new DnaJ-like protein. The data were integrated with our analysis of the lumenal-enriched proteome. We identified 83 out of 100 known proteins of the thylakoid localized photosynthetic apparatus, including several new paralogues and some 20 proteins involved in protein insertion, assembly, folding, or proteolysis. An additional 16 proteins are involved in translation, demonstrating that the thylakoid membrane surface is an important site for protein synthesis. The high coverage of the photosynthetic apparatus and the identification of known hydrophobic proteins with low expression levels, such as cpSecE, Ohp1, and Ohp2, indicate an excellent dynamic resolution of the analysis. The sequential extraction process proved very helpful to validate transmembrane prediction. Our data also were cross-correlated to chloroplast subproteome analyses by other laboratories. All data are deposited in a new curated plastid proteome database (PPDB) with multiple search functions (http://cbsusrv01.tc.cornell.edu/users/ppdb/). This PPDB will serve as an expandable resource for the plant community.