Proteomics -- the protein expression technology to study connective tissue biology

Budesonide/formoterol effects on metalloproteolytic balance in TGFbeta-activated human lung fibroblasts

In the airways of asthmatic patients, activated fibroblasts account for an excessive matrix production including proteoglycans (PGs). Transforming growth factor-beta (TGFbeta), metalloproteinases (MMPs) and their tissue inhibitors (TIMPs) play key roles in matrix turnover. It is unclear whether asthma therapy with combination of inhaled glucocorticoids and long-acting beta(2)-agonists affects metalloproteolytic equilibrium and by that counteracts airway fibrosis. The effects of the glucocorticoid, budesonide, and the long-acting beta(2)-agonist, formoterol, on the PG production and the activity of PGs' main regulators: MMP-3, MMP-9, MMP-2 and TIMP-1 were investigated in human lung fibroblasts (HFL-1) treated for 24h with TGFbeta1 (10 ng/ml) without/with budesonide (10(-9) to 10(-6)M) and/or formoterol (10(-11) to 10(-6)M). TGFbeta1 significantly increased production of PGs and TIMP-1, and the activity of MMP-3, MMP-9 and MMP-2. Concurrent budesonide/formoterol combination counteracted the enhanced: PG and TIMP-1 production, MMP-9 activity and MMP-9/TIMP-1 ratio, whereas MMP-2 and MMP-3 were not affected and so their ratios to TIMP-1 were significantly increased. Budesonide or formoterol alone achieved equal effects as budesonide/formoterol on MMP-9 and MMP-9/TIMP-1 ratio but had no effects on TIMP-1, MMP-2 or MMP-3. In the formoterol absence, higher budesonide concentrations were required to reduce the PG production, whereas formoterol alone had no effects. These results suggest that the budesonide/formoterol combination enhanced metalloproteolytic activity of human lung fibroblasts via a synergistic decrease of TIMP-1, and that this mechanism may be involved in the synergistic inhibition of the TGFbeta1-induced PG production. This implies that budesonide/formoterol combination therapy can counteract excessive matrix production and thus pathological airway fibrotic remodeling in asthma.

Proteomics in liver fibrosis is more than meets the eye

Liver fibrosis is a serious health issue for many liver patients and is currently diagnosed using liver biopsy. The erroneous nature of this technique urges the search for better, noninvasive alternatives. In this regard, proteomics has been described as a useful biomarker discovery tool and has become increasingly applied in the study of liver fibrosis. Experimental and clinical studies have already provided deeper insights in the molecular pathways of liver fibrosis and even confirmed previous findings. Recent advances in proteomic strategies and tools enable multiple fractionation, multiple protein identifications and parallel analyses of multiple samples. Despite its increasing popularity, proteomics still faces certain pitfalls concerning preanalytical variability, protein coverage and statistic reliability. Proteomics is still evolving, but will undoubtedly contribute to a better understanding of the basics of the pathology and certainly offer opportunities in liver fibrosis diagnostics and therapeutics.

Proteomics of TGF-beta signaling and its impact on breast cancer

The complexity of mechanisms leading to the appearance and progression of cancer is a challenge being addressed by large-scale studies, such as proteomics. Simultaneous monitoring of thousands of proteins uncovers novel signaling mechanisms, thus revising our knowledge of tumorigenesis. Transforming growth factor (TGF)-beta is a secreted polypeptide that is known to inhibit tumor growth at the early stages of cancer, but promote metastasis at the later stages. Proteomics-based studies have significantly widened our knowledge of TGF-beta-dependent regulation of cell proliferation, apoptosis, DNA damage repair and transcription. This leads to better understanding of the TGF-beta role in human breast tumorigenesis, and opens the way for the development of novel anticancer treatments and drugs, with some of the drugs already entering clinics. This review discusses recent advances in proteomics studies of TGF-beta signaling and its contribution to the understanding and treatment of breast cancer.

Proteomics as a route to identification of toxicity targets in environmental toxicology

Ecotoxicology describes a three-way relationship between ecosystems, chemical pollutants and living organisms. It is predicated on the fact that chemical pollution can exert toxic effects on organisms at the individual and population levels. These toxic effects may provide important information to supplement chemical analysis of environmental samples and aid in assessing the environmental quality of specific ecosystems. Traditionally, effects have been detected by means of biomarkers which, of necessity, were often molecules or processes known to be affected by pollutants. Proteomics provides a means of achieving high-throughput analysis of effects on protein populations and sub-populations with the potential to identify novel biomarkers. This review summarises the main approaches currently used in this area and assesses the potential of proteomics for identification of novel toxicity targets.

Specific haptoglobin expression in bronchoalveolar lavage during differentiation of circulating fibroblast progenitor cells in mild asthma

Haptoglobin is an acute-phase glycoprotein considered to be involved in tissue repair and is produced by fibroblasts and inflammatory cells. By using a gel-based proteomic approach, we show for the first time a possible role for haptoglobin in the differentiation of fibroblast progenitor cells, termed fibrocytes, in patients with mild asthma. Bronchoalveolar lavage fluid (BALF) was performed to sample circulating fibrocytes from patients with mild asthma and nonasthmatic control subjects. Fibrocytes from the airway lumen were characterized by triple staining of the markers CD34/CD45R0/alpha-smooth muscle actin, and subjected to confocal microscopy. The protein expression pattern was analyzed using two-dimensional electrophoresis (2-DE) and matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF). Elevated levels of haptoglobin expression in BALF was reported in a sub-group of patients with mild asthma (p < 0.05) when compared to the other subjects. In addition, this increase in haptoglobin was accompanied by differentiation of fibrocytes into fibroblast-like cells. When further analyzing the expression pattern of haptoglobin isoforms, a heterozygous expression was detected in the patients where fibrocyte differentiation could be observed. These data raise the possibility that an acute and specific inflammatory state facilitates the differentiation of fibroblast progenitor cells into activated fibroblasts. Furthermore, this study proposes a novel role for haptoglobin in airway remodeling in patients with asthma.

Proteomic identification of lower apolipoprotein A-I in Alzheimer's disease

Many researches have been trying to find the potential biomarkers for Alzheimer's disease (AD). We hereby used the proteomics method to search for protein expression differences in the serum between AD patients and controls. We enrolled 59 AD patients and 74 age- and sex-matched controls in this study. Ten AD patients and 10 controls were selected for proteomic analysis. Apolipoprotein A-I (ApoA-I) was found to have a lower expression in the AD group by a proteomics two-dimensional gel electrophoresis study. We further measured the serum ApoA-I level which was significantly lower in the AD patients (112.29 +/- 21.33 mg/dl) in comparison to the controls (144.53 +/- 19.91 mg/dl; p < 0.0002). Lower serum ApoA-I levels might be a potential biomarker for AD.

The potential of proteomics and peptidomics for allergy and asthma research

Progress in the field of proteomics, the branch of biology that studies the full set of proteins derived from a given genome, is moving fast. Two-dimensional gel electrophoresis (2DG) separation of complex protein mixtures and the subsequent analysis of isolated protein spots by mass spectrometry allow fast and accurate identification of proteins. The comparison of spots from different samples separated on customized 2D gels allows the detection of punctual differences in their mobility and facilitates tracing back differences in protein expression, presence of isoforms, splice variants and posttranslational modifications by mass spectrometry. In spite of significant analytical challenges owing to the high complexity of the proteome and the challenge deriving from the necessity to process huge amounts of raw data generated by mass spectrometric profiling, proteomics has evolved to an indispensable tool in life sciences. A restricted window of the proteome that consists of peptides and small proteins not easily manageable by conventional gel electrophoresis prompted the development of separation methods based on liquid chromatography. This new research field termed peptidomics already contributed, together with proteomics to enlarge our knowledge about biological processes and supported by sophisticated bioinformatics tools, to the discovery of new diagnostic and therapeutic targets. The technological capabilities of biophysical separation, mass spectrometry and bioinformatics form the basis of discovery programs that aim at mining the proteome starting from microgram amounts of protein extracts derived from body fluids and tissues. Proteomics and peptidomics have a great potential to speed up allergy and asthma research, where disease- and tissue-specific samples are easy to obtain.

Use of Legendre moments for the fast comparison of two-dimensional polyacrylamide gel electrophoresis maps images

In this paper, Legendre moments are calculated to extract the global information from a set of two-dimensional polyacrylamide gel electrophoresis map images. The dataset contains 18 samples belonging to two different cell lines (PACA44 and T3M4) of control (untreated) and drug-treated pancreatic ductal carcinoma cells. The aim of this work was to obtain the correct classification of the 18 samples, using the Legendre moments as discriminant variables. For each image the Legendre moments up to a maximum order of 100 were computed. The stepwise linear discriminant analysis (LDA) was performed in order to select the moments with the highest discriminating power. The results demonstrate that the Legendre moments can be successfully applied for fast classification purposes and similarity analysis.

Study of proteomic changes associated with healthy and tumoral murine samples in neuroblastoma by principal component analysis and classification methods

BACKGROUND

The adrenal gland is the election organ forming primary neuroblastoma (NB) tumours, the most common extracranial solid tumours of infancy and childhood.

METHODS

Samples of adrenal gland belonging to healthy and diseased nude mouse were analysed by 2D gel-electrophoresis. The resulting 2D-PAGE maps were digitized by PDQuest and investigated by principal component analysis (PCA).

RESULTS

The analysis of the loadings of the first principal component (PC) permitted the evaluation of the spots characterising each class of samples. Moreover, the soft-independent model of class analogy (SIMCA) method confirmed the separation of the samples in the two classes and allowed the identification of the modelling and discriminating spots. Very good correlation was found between the data obtained by analysis of 2D maps via the commercial software PDQuest and the present PCA analysis. In both cases, the comparison between such maps showed up- and down-regulation of 84 polypeptide chains, out of a total of 700 spots detected by a fluorescent stain, Sypro Ruby. Spots that were differentially expressed between the two groups were analysed by matrix-assisted laser desorption time-of-flight (MALDI-TOF) mass spectrometry and 14 of these spots were identified so far.

Pathway Proteomics

Biological pathways represent the relationships (reactions and interactions) between biological molecules in the context of normal cellular functions and disease mechanisms. Understanding the roles of proteins and signaling pathways expressed within disease, and their link to drug discovery and drug development are central in today's target-driven pharmaceutical processes. This article gives an overview of proteomics strategies, including global expression analysis as well as focused approaches using multidimensional separation by both gel- and liquid-phase techniques linked to mass spectrometry, as applied to two of the pathways involved in inflammatory diseases. In primary human cell studies, our group has annotated and identified thousands of proteins using both electrospray ionization and matrix-assisted laser desorption ionization (MALDI)-sequencing technology. Annotations made from gel images and chromatography fractionation, interfaced to high-end mass spectrometry sequence and structure identity, are cornerstones in cutting-edge protein expression profiling. Regarding phosphorylation mechanisms of kinases, the quantitative stoichiometry can be determined using affinity probe isolations. Another strategy involves micro-preparative sample processing, which has been used to analyze single-target phosphoproteins and their relative phospho-stoichiometry.

Proteome annotations and identifications of the human pulmonary fibroblast

We hereby report on a three year project initiative undertaken by our research team encompassing large-scale protein expression profiling and annotations of human primary lung fibroblast cells. An overview is given of proteomic studies of the fibroblast target cell involved in several diseases such as asthma, idiopatic pulmonary disease, and COPD. It has been the objective within our research team to map and identify the protein expressions occurring in both activated-, as well as resting cell states. The JGGL database www.2DDB.org has been built around these data, allowing advanced hypothesis building using the interactive query bioinformatic tools developed. Gene ontology has been applied to these annotations, classifying and correlating protein expressions to function. The localization as well as the biological processes involved for the annotations are being presented including an annotation-, and sequence-identification strategy, resulting in close to 2000 protein identities. Both gel based, high resolution 2D-gels, and liquid-phase separation (three-dimensional HPLC), as well as the combination of gel- and LC-based approaches (1D-gels and nano-capillary LC, reversed-phase) were utilized. Protein sequencing and structure identities were acquired by a combination of MALDI-, and electrospray-mass spectrometry techniques. Phenotypical and morphological characterizations were also made for this human disease target cell in both stimulated- and resting-cell states. The use of functional assays that demonstrate the key regulating role of growth factors and cytokine stimuli such as PDGF, TGF-beta, and EGF and the effect of ECM molecules such as Biglycan, are also presented and discussed.

Clinical proteomics in lung diseases

Proteomics is a relatively new approach for understanding the pathology and pathogenesis of various diseases. It has also been used for characterizing the modifications in protein expression during the development of interstitial lung diseases, in lung tumors, or following exposure to exogenous stress signals. We compared the protein composition of primary human lung fibroblasts derived from patients with lung fibrosis and control fibroblasts of unaffected lung tissues. We found a predominant modulation in proteins related to the cytoskeleton, including decreased expression of vimentin and lamin A/C, and increased expression of moesin. Furthermore, we observed lower levels of components of the antioxidative system, such as omega class glutathione S-transferase and an up-regulation of an intracellular chloride channel. In fibroblasts obtained from fibrotic lungs, the expression of a major histocompatibility complex class I C was decreased, and so was the expression of tripeptidyl-peptidase-I-precursor, a collagen-degrading exopeptidase. Our results and the studies reviewed in this paper represent just the beginning of detailed studies that should unravel the relevance and the functional consequences of differential protein expressions in the diseased lung.

Proteomics: current techniques and potential applications to lung disease

Proteomics aims to study the whole protein content of a biological sample in one set of experiments. Such an approach has the potential value to acquire an understanding of the complex responses of an organism to a stimulus. The large vascular and air space surface area of the lung expose it to a multitude of stimuli that can trigger a variety of responses by many different cell types. This complexity makes the lung a promising, but also challenging, target for proteomics. Important steps made in the last decade have increased the potential value of the results of proteomics studies for the clinical scientist. Advances in protein separation and staining techniques have improved protein identification to include the least abundant proteins. The evolution in mass spectrometry has led to the identification of a large part of the proteins of interest rather than just describing changes in patterns of protein spots. Protein profiling techniques allow the rapid comparison of complex samples and the direct investigation of tissue specimens. In addition, proteomics has been complemented by the analysis of posttranslational modifications and techniques for the quantitative comparison of different proteomes. These methodologies have made the application of proteomics on the study of specific diseases or biological processes under clinically relevant conditions possible. The quantity of data that is acquired with these new techniques places new challenges on data processing and analysis. This article provides a brief review of the most promising proteomics methods and some of their applications to pulmonary research.

Computational tools for the study of allergens

Allergy is a major cause of morbidity worldwide. The number of characterized allergens and related information is increasing rapidly creating demands for advanced information storage, retrieval and analysis. Bioinformatics provides useful tools for analysing allergens and these are complementary to traditional laboratory techniques for the study of allergens. Specific applications include structural analysis of allergens, identification of B- and T-cell epitopes, assessment of allergenicity and cross-reactivity, and genome analysis. In this paper, the most important bioinformatic tools and methods with relevance to the study of allergy have been reviewed.

Application of three-way principal component analysis to the evaluation of two-dimensional maps in proteomics

Three-way PCA has been applied to proteomic pattern images to identify the classes of samples present in the dataset. The developed method has been applied to two different datasets: a rat sera dataset, constituted by five samples of healthy Wistar rat sera and five samples of nicotine-treated Wistar rat sera; a human lymph-node dataset constituted by four healthy lymph-nodes and four lymph-nodes affected by a non-Hodgkin's lymphoma. The method proved to be successful in the identification of the classes of samples present in both of the groups of 2D-PAGE images, and it allowed us to identify the regions of the two-dimensional maps responsible for the differences occurring between the classes for both rat sera and human lymph-nodes datasets.

Cutting-edge technology. II. Proteomics: core technologies and applications in physiology

Technologies for proteomics, e.g., studies examining the protein complement of the genome, have been in development for over 20 years. More recently, proteomics has become formalized by combining techniques for large-scale protein separation with very precise, high-fidelity approaches that analyze, identify, and characterize the separated proteins. These methods bring to reality the powerful scope of proteomics, enabling researchers to investigate cellular function at the protein level and thus representing one of proteomics' most fitting applications. In this review, we take a brief and concise look at some of the current, physiologically relevant technologies that comprise proteomics and report specific applications in which proteomics has provided valuable biological insight.

Genomics and proteomics of allergic disease

The world-wide effort to identify susceptibility genes for allergic diseases is motivated by the conviction that the identification of disease genes may permit the design of new classes of anti-inflammatory compounds. Molecules concerned with the allergic reaction, such as cytokines, chemokines, their receptors, major histocompatibility complex molecules, and transcription factors, could provide the candidate genes of the allergic diseases. On the basis of genetic studies, multiple research groups have attempted to identify a susceptibility gene for allergy using the candidate gene approach and/or genome-wide screening. Both of these approaches suggest genetic heterogeneity of allergic diseases. Many variants of candidate genes are or are not associated with particular diseases in different ethnic groups and the function of variants is now being investigated. Based on the information accumulated thus far and the information on the human genome sequence, future advances in research on genetic factors for allergic diseases will be likely lead to the establishment of more effective prophylaxis and therapy for these diseases.