A reference map of a human pituitary adenoma proteome

In order to compare the proteomes from different cell types of pituitary adenomas for our long-term goal to clarify the molecular mechanisms that participate in the formation of pituitary adenoma, and to detect any tumor-related marker for an "early-stage" diagnosis, the two-dimensional gel electrophoresis (2-DE) reference map of a pituitary adenoma tissue proteome is described here. A vertical, two-dimensional (2-D) polyacrylamide gel electrophoresis system and PDQuest image analysis software have been used to provide a high level of between-gel reproducibility and to accurately array each protein expressed in a pituitary adenoma tissue. Mass spectrometry (matrix-assisted laser desorption/ionization-time of flight MALDI-TOF and liquid chromatography-electrospray ionization-quadrupole-ion trap LC-ESI-Q-IT) and protein databases were used to characterize each protein in the 2-D gel. The results demonstrate that a good reproducibility of the 2-D gel pattern was attained. The position deviation of matched spots among four 2-D gels was 1.95 +/- 0.45 mm in the isoelectric focusing direction, and 1.70 +/- 0.53 mm in the sodium dodecyl sulfate-polyacrylamide gel electrophoresis direction. A total of ca. 1000 protein spots were separated by 2-DE, and 135 protein spots that represent 111 proteins were characterized with mass spectrometry (96 spots for MALDI-TOF, 39 spots for LC-ESI-Q-IT). The characterized proteins include pituitary hormones, cellular signals, enzymes, cellular-defense proteins, cell-structure proteins, transport proteins, etc. Those proteins were located in the cytoplasmic, cellular membrane, mitochondrial, endoplasmic reticulum, nuclear, ribonucleosome, extracellular fractions, or were secreted in plasma, etc. Those identified proteins contribute to a functional profile of the pituitary adenoma proteome. These data will be used to expand the proteome database of the human pituitary, which can be accessed in the website http://www.utmem.edu /proteomics.     

Analysis of the human saliva proteome

Interest in the characterization of the salivary proteome has increased in the last few years. This review discusses the different techniques and methodologies applied to the separation and identification of salivary proteins. Nowadays, proteomic techniques are the state of the art for the analysis of biologic materials and saliva is no exception. 2D electrophoresis and tryptic digest analysis by mass spectrometry are the typical methodology, but new approaches using 2D liquid chromatography/mass spectrometry methods have already been introduced for saliva analysis. Due to their important physiologic role in the oral cavity, low-molecular-weight proteins and peptides are also included in this article and the methodologies discussed.     

Analysis of the human serum proteome

Changes in serum proteins that signal histopathological states, such as cancer, are useful diagnostic and prognostic biomarkers. Unfortunately, the large dynamic concentration range of proteins in serum makes it a challenging proteome to effectively characterize. Typically, methods to deplete highly abundant proteins to decrease this dynamic protein concentration range are employed, yet such depletion results in removal of important low abundant proteins. A multi-dimensional peptide separation strategy utilizing conventional separation techniques combined with tandem mass spectrometry (MS/MS) was employed for a proteome analysis of human serum. Serum proteins were digested with trypsin and resolved into 20 fractions by ampholyte-free liquid phase isoelectric focusing. These 20 peptide fractions were further fractionated by strong cation-exchange chromatography, each of which was analyzed by microcapillary reversed-phase liquid chromatography coupled online with MS/MS analysis. This investigation resulted in the identification of 1444 unique proteins in serum. Proteins from all functional classes, cellular localization, and abundance levels were identified. This study illustrates that a majority of lower abundance proteins identified in serum are present as secreted or shed species by cells as a result of signalling, necrosis, apoptosis, and hemolysis. These findings show that the protein content of serum is quite reflective of the overall profile of the human organism and a conventional multidimensional fractionation strategy combined with MS/MS is entirely capable of characterizing a significant fraction of the serum proteome. We have constructed a publicly available human serum proteomic database (http://bpp.nci.nih.gov) to provide a reference resource to facilitate future investigations of the vast archive of pathophysiological content in serum. These authors contributed equally to this work.     

Analysis of the human saliva proteome

Interest in the characterization of the salivary proteome has increased in the last few years. This review discusses the different techniques and methodologies applied to the separation and identification of salivary proteins. Nowadays, proteomic techniques are the state of the art for the analysis of biologic materials and saliva is no exception. 2D electrophoresis and tryptic digest analysis by mass spectrometry are the typical methodology, but new approaches using 2D liquid chromatography/mass spectrometry methods have already been introduced for saliva analysis. Due to their important physiologic role in the oral cavity, low-molecular-weight proteins and peptides are also included in this article and the methodologies discussed.     

Estrogen regulation of the rat anterior pituitary gland proteome

Estrogen is known to affect the regulation of all six of the established anterior pituitary gland (AP) hormones, but little is known of the specifics of its regulation of the AP hormones, their isoforms, and nonhormonal AP proteins. We used difference gel electrophoresis in conjunction with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry and peptide mass fingerprinting to quantify the effects of estrogen on the AP-soluble protein fraction in rats. Two-month-old rats were ovariectomized and used at 6 months of age. They were injected subcutaneously with sesame oil vehicle or 50 mug estradiol valerate in vehicle and studied 48 hrs later, approximately 3 hrs before the time of the anticipated onset of the estrogen-induced surges of gonadotropins in blood. The APs were pooled, and the soluble protein fraction was examined in replicate analyses. After DeCyder software analysis, we identified 26 protein spots that had a 1.5-fold or greater average increase in the experimental group relative to the controls. Nineteen showed a 1.5-fold or greater decrease. Estrogen increased levels of the more acidic isoforms of growth hormone and prolactin and of proteins involved in protein synthesis, folding, and secretion (e.g., eukaryotic translation elongation factor 2, ERp57, ERp29, Hsc70-ps1, calreticulin, coatomer delta subunit, and secretogranin II) and of some metabolic enzymes (e.g., arginosuccinate synthetase, enolase 1, creatine kinase B, phosphoglycerate mutase, malate dehydrogenase, pyruvate kinase, and aldolase A). The majority of the downregulated proteins were involved in RNA or DNA interactions (e.g., five heterogeneous nuclear ribonucleoproteins, DEAD-box proteins 17 and 48, ssDNA binding protein PUR-alpha, PTB-associated splicing factor, and Pigpen protein), but isovaleryl coenzyme A dehydrogenase, mitochondrial aldehyde dehydrogenase, stathmin 1, vinculin, radixin, and secretogranin III were also reduced. Our results indicate that estrogen acts in vivo within 48 hrs to modulate levels of a significant number of AP proteins.     

Analysis of human liver proteome using replicate shotgun strategy

In this study, a liquid-based shotgun strategy was used to comprehensively identify the expression of human liver proteome. Proteins were extracted from human liver tissue and digested in-solution. The tryptic digest mixture was desalted and separated by off-line strong cation exchange (SCX) chromatography with a 60-min elution. The MS/MS spectra were acquired in data-dependent mode after an RP chromatographic separation combined with linear IT MS analysis. To obtain the most comprehensive human liver proteome, each SCX fraction was run six times in RPLC MS/MS manner. Finally, more than 6,000,000 MS/MS spectra were collected. Using a relatively strict filter criteria, 24,311 proteins (48.42% of the predicted human proteome from human International Protein Index (IPI) protein database 3.07) corresponding to 13,150 nonredundant proteins were successfully identified, in which 7001 proteins (53.24%) were identified by two or more peptides, which could be considered as a high-confident dataset. Among the 6149 proteins (46.76%) identified by single peptide, 3812 proteins (61.99%) were detected more than twice in six repeated runs. Comparative analysis between different runs shows that the overlap of identified proteins between any two runs ranged from 25 to 44%. Of the nonredundant proteins identified, 8919 proteins (67.83%) were detected more than twice and 4231 proteins (32.17%) were detected only once in six RPLC MS/MS runs. The Gene Ontology annotation shows that the identified proteins come from various subcellular components. In addition, a large number of low abundant proteins were identified. The dynamic range of the approach reached at least nine orders of magnitude by estimating the concentration of proteins.     

Aggregation propensity of the human proteome

Formation of amyloid-like fibrils is involved in numerous human protein deposition diseases, but is also an intrinsic property of polypeptide chains in general. Progress achieved recently now allows the aggregation propensity of proteins to be analyzed over large scales. In this work we used a previously developed predictive algorithm to analyze the propensity of the 34,180 protein sequences of the human proteome to form amyloid-like fibrils. We show that long proteins have, on average, less intense aggregation peaks than short ones. Human proteins involved in protein deposition diseases do not differ extensively from the rest of the proteome, further demonstrating the generality of protein aggregation. We were also able to reproduce some of the results obtained with other algorithms, demonstrating that they do not depend on the type of computational tool employed. For example, proteins with different subcellular localizations were found to have different aggregation propensities, in relation to the various efficiencies of quality control mechanisms. Membrane proteins, intrinsically disordered proteins, and folded proteins were confirmed to have very different aggregation propensities, as a consequence of their different structures and cellular microenvironments. In addition, gatekeeper residues at strategic positions of the sequences were found to protect human proteins from aggregation. The results of these comparative analyses highlight the existence of intimate links between the propensity of proteins to form aggregates with β-structure and their biology. In particular, they emphasize the existence of a negative selection pressure that finely modulates protein sequences in order to adapt their aggregation propensity to their biological context.     

Intrinsic disorder in the human spliceosomal proteome

The spliceosome is a molecular machine that performs the excision of introns from eukaryotic pre-mRNAs. This macromolecular complex comprises in human cells five RNAs and over one hundred proteins. In recent years, many spliceosomal proteins have been found to exhibit intrinsic disorder, that is to lack stable native three-dimensional structure in solution. Building on the previous body of proteomic, structural and functional data, we have carried out a systematic bioinformatics analysis of intrinsic disorder in the proteome of the human spliceosome. We discovered that almost a half of the combined sequence of proteins abundant in the spliceosome is predicted to be intrinsically disordered, at least when the individual proteins are considered in isolation. The distribution of intrinsic order and disorder throughout the spliceosome is uneven, and is related to the various functions performed by the intrinsic disorder of the spliceosomal proteins in the complex. In particular, proteins involved in the secondary functions of the spliceosome, such as mRNA recognition, intron/exon definition and spliceosomal assembly and dynamics, are more disordered than proteins directly involved in assisting splicing catalysis. Conserved disordered regions in spliceosomal proteins are evolutionarily younger and less widespread than ordered domains of essential spliceosomal proteins at the core of the spliceosome, suggesting that disordered regions were added to a preexistent ordered functional core. Finally, the spliceosomal proteome contains a much higher amount of intrinsic disorder predicted to lack secondary structure than the proteome of the ribosome, another large RNP machine. This result agrees with the currently recognized different functions of proteins in these two complexes.     

Variability of the healthy human proteome

The aim of this review is to analyze results of studies on characteristics of protein variability and diversity of posttranslational modifications of proteins in healthy humans. Numerous studies have demonstrated that a proteomic profile is characterized by significant intra- and inter-individual variability, and quite often natural (“normal”) variability of some proteins can be comparable to changes observed in pathological processes. Results obtained by our research group have demonstrated high intra-individual variability of serum low-molecular subproteome of healthy volunteers, certified by a special medial committee (the coefficient of variation (CV) of 42.6%). The proteins characterized by high variability under normal conditions (e.g. haptoglobin — 0–40 mg/ml; lysozyme — 0.01–0.1 mg/ml; C-reactive protein — 0.01–0.3 mg/ml) cannot be considered as potential biomarkers of diseases. On the contrary, proteins and peptides characterized by insignificant dispersion in healthy population (such as albumin ( CV = 9%); transferrin-(CV = 14%); C3c complement (CV = 17%), α-1 acid glycoprotein (CV = 21%), α-2-macroglobulin (CV = 20%); transthyretin fragment (CV = 28.3%) and α2-HS-glycoprotein βchain (CV = 29.7%)) can provide valuable information about the state of health. Thus, studies of plasticity in the proteomic profiles of healthy humans will help to correct reference intervals used in clinical proteomics.     

Spaceflight induced changes in the human proteome

Introduction: Spaceflight is one of the most extreme conditions encountered by humans: Individuals are exposed to radiation, microgravity, hypodynamia, and will experience isolation. A better understanding of the molecular processes induced by these factors may allow us to develop personalized countermeasures to minimize risks to astronauts.

Areas covered: This review is a summary of literature searches from PubMed, NASA, Roskosmos and the authors’ research experiences and opinions. The review covers the available proteomic data on the effects of spaceflight factors on the human body, including both real space missions and ground-based model experiments.

Expert commentary: Overall, the authors believe that the present background, methodology and equipment improvements will enhance spaceflight safety and support accumulation of new knowledge on how organisms adapt to extreme conditions.     

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.     

Analysis of the microbial proteome

Proteomics has begun to provide insight into the biology of microorganisms. The combination of proteomics with genetics, molecular biology, protein biochemistry and biophysics is particularly powerful, resulting in novel methods to analyse complex protein mixtures. Emerging proteomic technologies promise to increase the throughput of protein identifications from complex mixtures and allow for the quantification of protein expression levels.