Inhibition of protein carbamylation in urea solution using ammonium-containing buffers

Urea solution is one of the most commonly employed protein denaturants for protease digestion in proteomic studies. However, it has long been recognized that urea solution can cause carbamylation at the N termini of proteins/peptides and at the side chain amino groups of lysine and arginine residues. Protein/peptide carbamylation blocks protease digestion and affects protein identification and quantification in mass spectrometry analysis by blocking peptide amino groups from isotopic/isobaric labeling and changing peptide charge states, retention times, and masses. In addition, protein carbamylation during sample preparation makes it difficult to study in vivo protein carbamylation. In this study, we compared the peptide carbamylation in urea solutions of different buffers and found that ammonium-containing buffers were the most effective buffers to inhibit protein carbamylation in urea solution. The possible mechanism of carbamylation inhibition by ammonium-containing buffers is discussed, and a revised procedure for the protease digestion of proteins in urea and ammonium-containing buffers was developed to facilitate its application in proteomic research.     

Computational methods for protein identification from mass spectrometry data

Protein identification using mass spectrometry is an indispensable computational tool in the life sciences. A dramatic increase in the use of proteomic strategies to understand the biology of living systems generates an ongoing need for more effective, efficient, and accurate computational methods for protein identification. A wide range of computational methods, each with various implementations, are available to complement different proteomic approaches. A solid knowledge of the range of algorithms available and, more critically, the accuracy and effectiveness of these techniques is essential to ensure as many of the proteins as possible, within any particular experiment, are correctly identified. Here, we undertake a systematic review of the currently available methods and algorithms for interpreting, managing, and analyzing biological data associated with protein identification. We summarize the advances in computational solutions as they have responded to corresponding advances in mass spectrometry hardware. The evolution of scoring algorithms and metrics for automated protein identification are also discussed with a focus on the relative performance of different techniques. We also consider the relative advantages and limitations of different techniques in particular biological contexts. Finally, we present our perspective on future developments in the area of computational protein identification by considering the most recent literature on new and promising approaches to the problem as well as identifying areas yet to be explored and the potential application of methods from other areas of computational biology.     

Accumulation of “Old Proteins” and the Critical Need for MS‐based Protein Turnover Measurements in Aging and Longevity

Aging and age‐related diseases are accompanied by proteome remodeling and progressive declines in cellular machinery required to maintain protein homeostasis (proteostasis), such as autophagy, ubiquitin‐mediated degradation, and protein synthesis. While many studies have focused on capturing changes in proteostasis, the identification of proteins that evade these cellular processes has recently emerged as an approach to studying the aging proteome. With advances in proteomic technology, it is possible to monitor protein half‐lives and protein turnover at the level of individual proteins in vivo. For large‐scale studies, these technologies typically include the use of stable isotope labeling coupled with MS and comprehensive assessment of protein turnover rates. Protein turnover studies have revealed groups of highly relevant long‐lived proteins (LLPs), such as the nuclear pore complexes, extracellular matrix proteins, and protein aggregates. Here, the role of LLPs during aging and age‐related diseases and the methods used to identify and quantify their changes are reviewed. The methods available to conduct studies of protein turnover, used in combination with traditional proteomic methods, will enable the field to perform studies in a systems biology context, as changes in proteostasis may not be revealed in studies that solely measure differential protein abundances.     

Proteomics and polycystic ovary syndrome

Polycystic ovary syndrome (PCOS) is a complex endocrine disorder of heterogeneous etiology. Proteomics techniques have been used for elucidating the physiopathology of PCOS, yet the proteins identified so far were rarely the same across tissues and studies. The present review discusses the current challenges in the application of proteomics to the study of PCOS. A well-defined research design and an appropriate selection of study populations, samples and proteomic platforms are essential in clinical proteomics. Furthermore, the findings derived from proteomic approaches should be validated by complementary techniques, and the reproducibility of the results has ideally to be confirmed by different studies. Only when meeting these requirements, the proteins identified by proteomic techniques should be considered as candidates for future studies aiming to define specific molecular phenotypes of PCOS and their possible role in the metabolic and hormonal abnormalities characteristic of this syndrome.     

A proteomic approach to identify plasma proteins in patients with abdominal aortic aneurysm

Our aim was to identify the key proteins involved in the pathogenesis of AAAs. To explore the possible pathogenetic mechanisms involved in AAA, we analyzed by proteomics modifications in plasma proteome of patients with AAA. Therefore, the present study analyzed the soluble plasma proteins using two dimensional electrophoresis (2-DE) and mass spectrometry (MS). We identified 33 protein spots, 31 of which show an up-regulation in AAA patients whilst the expression level of 2 protein spots is reduced. We confirm a number of biomarkers associated with AAA that have been previously identified by various authors. We identified a significant increase of a class of proteins such as fibrinogen, α1-antitrypsin and haptoglobin in plasma from AAA patients. The presence of these proteins in human AAA plasma may be related to the inflammatory processes active in these subjects. We have seen a negative correlation between the vitamin D-binding protein (DBP) and hemoglobin subunit β and AAA presence. DBP levels have been found to increase in AAA wall tissues by others and this discrepancy with our results could be due to the different analysis source. We wanted to analyze the factors measurable in plasma-associated rather than in tissue-associated markers because the application of circulating biomarkers in diagnostic laboratories would be relatively simple. DBP is very important for vascular remodelling and it may have an important role in the protection of vascular walls. In plasma tissue this protein reduces platelet aggregation and extends coagulation time. No one protein identified in this study has the biologic plausibility to be used singularly as a biomarker of aneurysmal disease due to inadequate specificity. The effect of using multiple biomarkers combined with clinical factors requires investigation in carefully designed population-based studies and these studies need to select the criteria of choice to define healthy controls very carefully. Clearer identification of various markers is needed, possibly using other proteomic techniques to screen for new candidates such as gel-free proteomic technology that enables us to handle larger groups of subject compared to gel-based proteomic technology.     

Proteomics of mitochondrial inner and outer membranes

For the proteomic study of mitochondrial membranes, documented high quality mitochondrial preparations are a necessity to ensure proper localization. Despite the state-of-the-art technologies currently in use, there is no single technique that can be used for all studies of mitochondrial membrane proteins. Herein, we use examples to highlight solubilization techniques, different chromatographic methods, and developments in gel electrophoresis for proteomic analysis of mitochondrial membrane proteins. Blue-native gel electrophoresis has been successful not only for dissection of the inner membrane oxidative phosphorylation system, but also for the components of the outer membrane such as those involved in protein import. Identification of PTMs such as phosphorylation, acetylation, and nitration of mitochondrial membrane proteins has been greatly improved by the use of affinity techniques. However, understanding of the biological effect of these modifications is an area for further exploration. The rapid development of proteomic methods for both identification and quantitation, especially for modifications, will greatly impact the understanding of the mitochondrial membrane proteome.     

Quantitative proteomic analyses of crop seedlings subjected to stress conditions; a commentary

Quantitative proteomics is one of the analytical approaches used to clarify crop responses to stress conditions. Recent remarkable advances in proteomics technologies allow for the identification of a wider range of proteins than was previously possible. Current proteomic methods fall into roughly two categories: gel-based quantification methods, including conventional two-dimensional gel electrophoresis and two-dimensional fluorescence difference gel electrophoresis, and MS-based quantification methods consists of label-based and label-free protein quantification approaches. Although MS-based quantification methods have become mainstream in recent years, gel-based quantification methods are still useful for proteomic analyses. Previous studies examining crop responses to stress conditions reveal that each method has both advantages and disadvantages in regard to protein quantification in comparative proteomic analyses. Furthermore, one proteomics approach cannot be fully substituted by another technique. In this review, we discuss and highlight the basis and applications of quantitative proteomic analysis approaches in crop seedlings in response to flooding and osmotic stress as two environmental stresses.     

In Vitro Identification of Histatin 5 Salivary Complexes

With recent progress in the analysis of the salivary proteome, the number of salivary proteins identified has increased dramatically. However, the physiological functions of many of the newly discovered proteins remain unclear. Closely related to the study of a protein’s function is the identification of its interaction partners. Although in saliva some proteins may act primarily as single monomeric units, a significant percentage of all salivary proteins, if not the majority, appear to act in complexes with partners to execute their diverse functions. Coimmunoprecipitation (Co-IP) and pull-down assays were used to identify the heterotypic complexes between histatin 5, a potent natural antifungal protein, and other salivary proteins in saliva. Classical protein–protein interaction methods in combination with high-throughput mass spectrometric techniques were carried out. Co-IP using protein G magnetic Sepharose TM beads suspension was able to capture salivary complexes formed between histatin 5 and its salivary protein partners. Pull-down assay was used to confirm histatin 5 protein partners. A total of 52 different proteins were identified to interact with histatin 5. The present study used proteomic approaches in conjunction with classical biochemical methods to investigate protein–protein interaction in human saliva. Our study demonstrated that when histatin 5 is complexed with salivary amylase, one of the 52 proteins identified as a histatin 5 partner, the antifungal activity of histatin 5 is reduced. We expected that our proteomic approach could serve as a basis for future studies on the mechanism and structural-characterization of those salivary protein interactions to understand their clinical significance.     

Analytical nanobiotechnology for medicine diagnostics

The review is concerned with the state-of-the-art and the prospects of development of nanotechnologies in clinical proteomics. Nanotechnology in clinical proteomics is a new medical research direction, dealing with the creation and application of nanodevices for performing proteomic analyses in the clinic. Nanotechnological progress in the field of atomic force microscopy makes it possible to perform clinical studies on the revelation, visualization and identification of protein disease markers, in particular of those with the sensitivity of 10(-17) M that surpasses by several orders the sensitivity of commonly adopted clinical methods. At the same time, implementation of nanotechnological approaches into diagnostics allows for the creation of new diagnostic systems based on the optical, electro-optical, electromechanical and electrochemical nanosensoric elements with high operating speed. The application of nanotechnological approaches to creating nanopore-based devices for express sequencing of the genome is discussed.     

Expanding the protein catalogue in the proteome reference map of human breast cancer cells

In this report we present a catalogue of 162 proteins (including isoforms and variants) identified in a prototype of proteomic map of breast cancer cells. This work represents the prosecution of previous studies describing the protein complement of breast cancer cells of the line 8701-BC, which has been well characterized for several parameters, providing to be a useful model for the study of breast cancer-associated candidate biomarkers. In particular, 110 spots were identified ex novo by PMF, or validated following previous gel matching identification method; 30 were identified by N-terminal microsequencing and the remaining by gel matching with maps available from our former work. As a consequence of the expanded number of proteins, we have updated our previous classification extending the number of protein groups from 4 to 13. In order to facilitate comparative proteome studies of different kinds of breast cancers, in this report we provide the whole complement of proteins so far identified and grouped into the new classification. A consistent number of them were not described before in other proteomic maps of breast cancer cells or tissues, and therefore they represent a valuable contribution for breast cancer protein databases and for future application in basic and clinical researches.     

Proteomics techniques for the development of flood tolerant crops

Proteomics is a useful analytical approach for investigating crop responses to stress. Recent remarkable advances in proteomic techniques allow for the identification of a wider range of proteins than was previously possible. The application of proteomic techniques to clarify the molecular mechanisms underlying crop responses to flooding stress may facilitate the development of flood tolerant crops. Flooding is an environmental stress found worldwide and may increase in frequency due to changes in global climate. Waterlogging resulting from flooding causes significant reductions in the growth and yield of several crops. Transient flooding displaces gases in soil pores and often causes hypoxia in plants grown on land with poor drainage. Changes in protein expression and post-translational modification of proteins occur as plants activate their defense system in response to flooding stress. In this review, we discuss the contributions that proteomic studies have made toward increasing our understanding of the well-organized cellular response to flooding in soybean and other crops. The biological relevance of the proteins identified using proteomic techniques in regard to crop stress tolerance will be discussed as well.     

Label-free quantification in clinical proteomics

Nowadays, proteomic studies no longer focus only on identifying as many proteins as possible in a given sample, but aiming for an accurate quantification of them. Especially in clinical proteomics, the investigation of variable protein expression profiles can yield useful information on pathological pathways or biomarkers and drug targets related to a particular disease. Over the time, many quantitative proteomic approaches have been established allowing researchers in the field of proteomics to refer to a comprehensive toolbox of different methodologies. In this review we will give an overview of different methods of quantitative proteomics with focus on label-free proteomics and its use in clinical proteomics.     

Clinical cancer proteomics: promises and pitfalls

Proteome analysis promises to be valuable for the identification of tissue and serum biomarkers associated with human malignancies. In addition, proteome technologies offer the opportunity to analyze protein expression profiles and to analyze the activity of signaling pathways. Many published proteomic studies of human tumor tissue are associated with weaknesses in tumor representativity, sample contamination by nontumor cells and serum proteins. Studies often include a moderate number of tumors which may not be representative of clinical materials. It is therefore very important that biomarkers identified by proteomics are validated in representative tumor materials by other techniques, such as immunohistochemistry. Proteome technologies can be used to identify disease markers in human serum. Tumor derived proteins are present at nanomolar to picomolar concentrations in cancer patient sera, 10(6)-10(9)-fold lower than albumin, and will give rise to correspondingly smaller spots/peaks in protein separations. This leads to the need to prefractionate serum samples before analysis. Despite various pitfalls, proteomic analysis is a promising approach to the identification of biomarkers, and for generation of protein expression profiles that can be analyzed by artificial learning methods for improved diagnosis of human malignancy. Recent advances in the field of proteomic analysis of human tumors are summarized in the present review.     

High-abundance proteins depletion for serum proteomic analysis: concomitant removal of non-targeted proteins

In clinical and pharmaceutical proteomics, serum and plasma are frequently used for detection of early diagnostic biomarkers for therapeutic targets. Although obtaining these body fluid samples is non-invasive and easy, they contain some abundant proteins that mask other protein components present at low concentrations. The challenge in identifying serum biomarkers is to remove the abundant proteins, uncovering and enriching at the same time the low-abundance ones. The depletion strategies, however, could lead to the concomitant removal of some non-targeted proteins that may be of potential interest. In this study, we compared three different methods aimed to deplete high-abundance proteins from human serum, focusing on the identification of non-specifically bound proteins which might be eventually removed. A Cibacron blue-dye-based method for albumin removal, an albumin and IgG immunodepletion method and an immunoaffinity column (Multiple Affinity Removal System) that simultaneously removes a total of six high-abundance proteins, were investigated. The bound proteins were eluted, separated by two-dimensional gel electrophoresis and identified by Nano LC-CHIP-MS system. Flow-through fractions and bound fractions were also analysed with the ProteinChip technology SELDI-TOF-MS. Our results showed that the methods tested removed not only the targeted proteins with high efficiency, but also some non-targeted proteins. We found that the Multiple Affinity Removal Column improved the intensity of low-abundance proteins, displayed new protein spots and increased resolution. Notably, the column showed the lowest removal of untargeted proteins, proved to be the most promising depletion approach and a reliable method for serum preparation prior to proteomic studies.     

Carbonylated proteins in bronchoalveolar lavage of patients with sarcoidosis, pulmonary fibrosis associated with systemic sclerosis and idiopathic pulmonary fibrosis

Oxygen-derived free radicals produced by phagocytes have been postulated to contribute to lung tissue damage occurring during diffuse lung diseases (DLD). The two-dimensional electrophoretic (2-DE) analysis of bronchoalveolar lavage (BAL) protein composition revealed different protein profiles in sarcoidosis (S), idiopathic pulmonary fibrosis (IPF) and systemic sclerosis (SSc) with a significant increase of low molecular weight proteins in IPF. Some of these proteins are involved in antioxidant processes. The aims of this report were to analyse the oxidative stress occurring in patients with DLD through determination of BAL protein carbonyl content and to identify target proteins of oxidation by a proteomic approach (2-DE combined with immunoblotting with specific antibodies for carbonyl groups). Carbonylated proteins detected by enzyme-linked immunosorbent assay (ELISA) were increased in BAL of patients with S, IPF and SSc compared to healthy controls with a significant difference for S and IPF. The proteomic approach to the analysis of BAL revealed that protein carbonylation was a process involving specific carbonylation-sensitive proteins and that in IPF a greater number of proteins target of oxidation were present. In conclusion, to our knowledge, this is the first report providing a database of proteins target of oxidation in BAL of patients with sarcoidosis, idiopathic pulmonary fibrosis and systemic sclerosis.     

Expanding the proteome two-dimensional gel electrophoresis reference map of human renal cortex by peptide mass fingerprinting

Proteomics methodologies hold great promise in basic renal research and clinical nephrology. The classical approach for proteomic analysis couples two-dimensional gel electrophoresis (2-DE) with protein identification by mass spectrometry, to produce more global information regarding normal protein expression and alterations in different physiological and pathological states. In this report we have expanded the identification of proteins in the renal cortex, improving the previously published map to facilitate the study of different diseases affecting the human kidney. About 250 spots were analyzed by peptide mass fingerprinting, 89 proteins and 74 isoforms for some of them were identified and implemented in the normal human renal cortex 2-DE reference map. This more comprehensive view of the proteome of the human renal cortex could be of invaluable help to the differential proteomic display of urological diseases.     

Proteomic analysis of mammalian primary cilia

The primary cilium is a microtubule-based organelle that senses extracellular signals as a cellular antenna. Primary cilia are found on many types of cells in our body and play important roles in development and physiology. Defects of primary cilia cause a broad class of human genetic diseases called ciliopathies. To gain new insights into ciliary functions and better understand the molecular mechanisms underlying ciliopathies, it is of high importance to generate a catalog of primary cilia proteins. In this study, we isolated primary cilia from mouse kidney cells by using a calcium-shock method and identified 195 candidate primary cilia proteins by MudPIT (multidimensional protein identification technology), protein correlation profiling, and subtractive proteomic analysis. Based on comparisons with other proteomic studies of cilia, around 75% of our candidate primary cilia proteins are shared components with motile or specialized sensory cilia. The remaining 25% of the candidate proteins are possible primary cilia-specific proteins. These possible primary cilia-specific proteins include EVC2, INPP5E, and inversin, several of which have been linked to known ciliopathies. We have performed the first reported proteomic analysis of primary cilia from mammalian cells. These results provide new insights into primary cilia structure and function.     

Advances in quantitative proteomics via stable isotope tagging and mass spectrometry

The high-throughput identification and accurate quantification of proteins are essential components of proteomic strategies for studying cellular functions and processes. Techniques that are largely based on stable isotope protein or peptide labeling and automated tandem mass spectrometry are increasingly being applied in quantitative proteomic studies. Over the past year, significant progress has been made toward improving and diversifying these technologies with respect to the methods for stable isotope labeling, process automation and data processing and analysis. Advances in stable isotope protein labeling and recent biological studies that used stable isotope based quantitative proteomics techniques are reviewed.     

Extraction and proteomic analysis of proteins from normal and multiple sclerosis postmortem brain

In this study, a reproducible fractionation procedure was developed to reduce levels of the abundant cytoskeletal proteins that are present in normal and pathological central nervous system (CNS) tissues. The fractionation and proteomic analysis techniques employed greatly facilitated comparison of the spectrum of proteins in normal postmortem brain with proteins in samples from patients with multiple sclerosis, an inflammatory demyelinating disease in which complex changes in protein expression occur as lesions develop. This approach may be of value for the proteomic identification and quantitation of proteins which undergo disease-related changes in CNS disorders, and also for protein expression studies on normal adult and developing CNS tissues.