Secret-AAR: a web server to assess the antigenic density of proteins and homology search against bacterial and parasite secretome proteins

The secretome refers to all the Excreted/Secreted (ES) proteins of a cell, and these are involved in critical biological processes, such as cell-cell communication, and host immune responses. Recently, we introduced the Abundance of Antigenic Aegions (AAR) value to assess the protein antigenic density and to evaluate the antigenic potential of secretomes. Here, to facilitate the AAR calculation, we implemented it as a user-friendly webserver. We extended the webserver capabilities implementing a sequence-based tool for searching homologous proteins across secretomes, including experimental and predicted secretomes of Mycobacterium tuberculosis and Taenia solium. Additionally, twelve secretomes of helminths, five of Mycobacterium and two of Gram-negative bacteria are also available. Our webserver is a useful tool for researchers working on immunoinformatics and reverse vaccinology, aiming at discovering candidate proteins for new vaccines or diagnostic tests, and it can be used to prioritize the experimental analysis of proteins for druggability assays. The Secret-AAR web server is available at http://microbiomics.ibt.unam.mx/tools/aar/.     

Assessing proteolytic events in bioinformatic reanalysis of public secretome data from melanoma cell lines

Autocrine and paracrine signals are of paramount importance in both normal and oncogenic events and the composition of such secreted molecular signals (i.e the secretome) designate the communication status of cells. In this context, the analysis of post-translational modifications in secreted proteins may unravel biological circuits regulated by irreversible modifications such as proteolytic processing. In the present study, we have performed a bioinformatic reanalysis of public proteomics data on melanoma cell line secretomes, changing database searching parameters to allow for the identification of proteolytic events generated by active proteases. Such approach enabled the identification of proteolytic signatures which suggested active proteases and whose expression profiles might be targeted in patient tissues or liquid biopsies, as well as their cleaved substrates. Although N-terminomics approaches continue to be the method of choice for the evaluation of proteolytic signaling events in complex samples, the simple approach performed in this work resulted in the gain of biological insights derived from shotgun proteomics data.     

Secreted proteins as a fundamental source for biomarker discovery

The proteins secreted by various cells (the secretomes) are a potential rich source of biomarkers as they reflect various states of the cells at real time and at given conditions. To have accessible, sufficient and reliable protein markers is desirable as they mark various stages of disease development and their presence/absence can be used for diagnosis, prognosis, risk stratification and therapeutic monitoring. As direct analysis of blood/plasma, a common and noninvasive patient screening method, can be difficult for candidate protein biomarker identification, the alternative/complementary approaches are required, one of them is the analysis of secretomes in cell conditioned media in vitro. As the proteins secreted by cells as a response to various stimuli are most likely secreted into blood/plasma, the identification and pre-selection of candidate protein biomarkers from cell secretomes with subsequent validation of their presence at higher levels in serum/plasma is a promising approach. In this review, we discuss the proteins secreted by three progenitor cell types (smooth muscle, endothelial and cardiac progenitor cells) and two adult cell types (neonatal rat ventrical myocytes and smooth muscle cells) which can be relevant to cardiovascular research and which have been recently published in the literature. We found, at least for secretome studies included in this review, that secretomes of progenitor and adult cells overlap by 48% but the secretomes are very distinct among progenitor cell themselves as well as between adult cells. In addition, we compared secreted proteins to protein identifications listed in the Human Plasma PeptideAtlas and in two reports with cardiovascular-related proteins and we performed the extensive literature search to find if any of these secreted proteins were identified in a biomarker study. As expected, many proteins have been identified as biomarkers in cancer but 18 proteins (out of 62) have been tested as biomarkers in cardiovascular diseases as well.     

Mass spectrometry‐based secretome analysis of non‐small cell lung cancer cell lines

Tyrosine kinase inhibitors, such as erlotinib, display reliable responses and survival benefits for the treatment of human non‐small cell lung cancer (NSCLC) patients. However, primary or acquired resistance limits their therapeutic success. In this study, we conducted in‐depth mass spectrometric analyses of NSCLC cell secretomes. To identify secreted proteins that are differentially regulated in erlotinib‐sensitive (PC‐9) and ‐resistant (PC‐9ER) NSCLC cell lines, SILAC experiments were performed. On average, 900 proteins were identified in each sample with low variations in the numbers of identified proteins. Fourteen proteins were found to be differently regulated among erlotinib‐sensitive and ‐resistant NSCLC cell lines, with five proteins (tissue‐type plasminogen activator, epidermal growth factor receptor, urokinase‐type plasminogen activator, platelet‐derived growth factor D, and myeloid‐derived growth factor) showing the most prominent regulation. Tissue‐type plasminogen activator (t‐PA) was up to 10‐times upregulated in erlotinib‐resistant NSCLC cells compared with erlotinib‐sensitive cells. T‐PA is an established tumor marker for various cancer types and seems to be a promising prognostic marker to differentiate erlotinib‐sensitive from erlotinib‐resistant NSCLC cells. To gain further insights into t‐PA‐regulated pathways, a t‐PA variant was expressed in E. coli cells and its interactions with proteins secreted from erlotinib‐sensitive and ‐resistant NCSLC cells were studied by a combined affinity enrichment chemical cross‐linking/mass spectrometry (MS) approach. Fourteen proteins were identified as potential t‐PA interaction partners, deserving a closer inspection to unravel the mechanisms underlying erlotinib resistance in NSCLC cells.     

Secretome analysis using a hollow fiber culture system for cancer biomarker discovery

Secreted proteins, collectively referred to as the secretome, were suggested as valuable biomarkers in disease diagnosis and prognosis. However, some secreted proteins from cell cultures are difficult to detect because of their intrinsically low abundance; they are frequently masked by the released proteins from lysed cells and the substantial amounts of serum proteins used in culture medium. The hollow fiber culture (HFC) system is a commercially available system composed of small fibers sealed in a cartridge shell; cells grow on the outside of the fiber. Recently, because this system can help cells grow at a high density, it has been developed and applied in a novel analytical platform for cell secretome collection in cancer biomarker discovery. This article focuses on the advantages of the HFC system, including the effectiveness of the system for collection of secretomes, and reviews the process of cell secretome collection by the HFC system and proteomic approaches to discover cancer biomarkers. The HFC system not only provides a high-density three-dimensional (3D) cell culture system to mimic tumor growth conditions in vivo but can also accommodate numerous cells in a small volume, allowing secreted proteins to be accumulated and concentrated. In addition, cell lysis rates can be greatly reduced, decreasing the amount of contamination by abundant cytosolic proteins from lysed cells. Therefore, the HFC system is useful for preparing a wide range of proteins from cell secretomes and provides an effective method for collecting higher amounts of secreted proteins from cancer cells. This article is part of a Special Issue entitled: An Updated Secretome.     

Atomic force microscopy-based cancer diagnosis by detecting cancer-specific biomolecules and cells

Atomic force microscopy (AFM) has recently attracted much attention due to its ability to analyze biomolecular interactions and to detect certain biomolecules, which play a crucial role in disease expression. Despite recent studies reporting AFM imaging for the analyses of biomolecules, the application of AFM-based cancer-specific biomolecule/cell detection has remained largely underexplored, especially for the early diagnosis of cancer. In this paper, we review the recent attempts, including our efforts, to analyze and detect cancer-specific biomolecules and cancer cells. We particularly focus on two AFM-based cancer diagnosis techniques: (i) AFM imaging-based biomolecular and cellular detection, (ii) AFM cantilever-based biomolecular sensing and cell analysis. It is shown that AFM-based biomolecular detection has been applied for not only early diagnosing cancer, by measuring the minute amount of cancer-specific proteins, but also monitoring of cancer progression, by correlating the amount of cancer-specific proteins with the progression of cancer. In addition, AFM-based cell imaging and detection have been employed for diagnosing cancer, by detecting cancerous cells in tissue, as well as understanding cancer progression, by characterizing the dynamics of cancer cells. This review, therefore, highlights AFM-based biomolecule/cell detection, which will pave the way for developing a fast and point-of-care diagnostic system for biomedical applications.     

Secretome analysis of human bone marrow derived mesenchymal stromal cells

As an essential cellular component of the bone marrow (BM) microenvironment mesenchymal stromal cells (MSC) play a pivotal role for the physiological regulation of hematopoiesis, in particular through the secretion of cytokines and chemokines. Mass spectrometry (MS) facilitates the identification and quantification of a large amount of secreted proteins (secretome), but can be hampered by the false-positive identification of contaminating proteins released from dead cells or derived from cell medium. To reduce the likelihood of contaminations we applied an approach combining secretome and proteome analysis to characterize the physiological secretome of BM derived human MSC. Our analysis revealed a secretome consisting of 315 proteins. Pathway analyses of these proteins revealed a high abundance of proteins related to cell growth and/or maintenance, signal transduction and cell communication thereby representing key biological functions of BM derived MSC on protein level. Within the MSC secretome we identified several cytokines and growth factors such as VEGFC, TGF-β1, TGF-β2 and GDF6 which are known to be involved in the physiological regulation of hematopoiesis. By comparing the peptide patterns of secretomes and cell lysates 17 proteins were identified as candidates for proteolytic processing. Taken together, our combined MS work-flow reduced the likelihood of contaminations and enabled us to carve out a specific overview about the composition of the secretome from human BM derived MSC. This methodological approach and the specific secretome signature of BM derived MSC may serve as basis for future comparative analyses of the interplay of MSC and HSPC in patients with hematological malignancies.     

The evolutionary context of robust and redundant cell biological mechanisms

The robustness of biological processes to perturbations has so far been mainly explored in unicellular organisms; multicellular organisms have been studied for developmental processes or in the special case of redundancy between gene duplicates. Here we explore the robustness of cell biological mechanisms of multicellular organisms in an evolutionary context. We propose that the reuse of similar cell biological mechanisms in different cell types of the same organism has evolutionary implications: (1) the maintenance of apparently redundant mechanisms over evolutionary time may in part be explained by their differential requirement in various cell types; (2) the relative requirement for two alternative mechanisms may evolve among homologous cells in different organisms. We present examples of cell biological processes, such as centrosome separation in prophase, spindle formation or cleavage furrow positioning, that support the first proposition. We propose experimental tests of these hypotheses.     

Mining the gastric cancer secretome: identification of GRN as a potential diagnostic marker for early gastric cancer

Gastric cancer is the second leading cause of cancer deaths worldwide, and currently, there are no clinically relevant biomarkers for gastric cancer diagnosis or prognosis. In this study, we applied a 2D-LC-MS/MS based approach, in combination with iTRAQ labeling, to study the secretomes of the gastric cancer cell lines AGS and MKN7. By performing a comparative analysis between the conditioned media and the whole cell lysates, our workflow allowed us to differentiate the bona fide secreted proteins from the intracellular contaminants within the conditioned media. Ninety proteins were found to have higher abundance in the conditioned media as compared to the whole cell lysates of AGS and MKN7 cells. Using a signal peptide and nonclassical secretion prediction tool and an online exosome database, we demonstrated that up to 92.2% of these 90 proteins can be exported out of the cells by classical or nonclassical secretory pathways. We then performed quantitative comparisons of the secretomes between AGS and MKN7, identifying 43 differentially expressed secreted proteins. Among them, GRN was found to be frequently expressed in gastric tumor tissues, but not in normal gastric epithelia by immunohistochemistry. Sandwich ELISA assay also showed elevation of serum GRN levels in gastric cancer patients, particularly those with early gastric cancer. Receiver operating characteristic (ROC) curves analysis confirmed that serum GRN can provide diagnostic discriminations for gastric cancer patients.     

Proteomic Analysis of the Secretome of Porcine Alveolar Macrophages Infected with Porcine Reproductive and Respiratory Syndrome Virus

Porcine reproductive and respiratory syndrome virus (PRRSV) causes porcine reproductive and respiratory syndrome (PRRS), which is characterized by reproductive failure and respiratory disorders. The secretome of PRRSV‐infected porcine alveolar macrophages (PAMs), which are the primary target cells of PRRSV, was analyzed by label‐free quantitative proteomics to gain a profile of proteins secreted during PRRSV infection. A total of 95 secreted proteins with differentially expressed levels between PRRSV‐ and mock‐infected PAMs was screened. Among these, the expression levels of 49 and 46 proteins were up‐regulated and down‐regulated, respectively, in PRRSV‐infected cell supernatants, as compared with mock‐infected cell supernatants. Bioinformatic analysis revealed that the differentially expressed proteins were enriched in several signaling pathways related to the immune and inflammatory responses, such as the Toll‐like receptor signaling pathway and NF‐kappa B signaling pathway, and involved in a great diversity of biological processes, such as protein binding and localization, as well as immune effector processes. In addition, PRRSV‐infected cell supernatants induced significant expression of inflammatory cytokines in vascular endothelial cells. These findings suggest that the secreted proteins play potential roles in the host immune and inflammatory responses as well as PRRSV replication, thereby providing new insights into cell‐to‐cell communication during PRRSV infection.     

Prions on the run: How extracellular vesicles serve as delivery vehicles for self-templating protein aggregates

Extracellular vesicles (EVs) are actively secreted, membrane-bound communication vehicles that exchange biomolecules between cells. EVs also serve as dissemination vehicles for pathogens, including prions, proteinaceous infectious agents that cause transmissible spongiform encephalopathies (TSEs) in mammals. Increasing evidence accumulates that diverse protein aggregates associated with common neurodegenerative diseases are packaged into EVs as well. Vesicle-mediated intercellular transmission of protein aggregates can induce aggregation of homotypic proteins in acceptor cells and might thereby contribute to disease progression. Our knowledge of how protein aggregates are sorted into EVs and how these vesicles adhere to and fuse with target cells is limited. Here we review how TSE prions exploit EVs for intercellular transmission and compare this to the transmission behavior of self-templating cytosolic protein aggregates derived from the yeast prion domain Sup 35 NM. Artificial NM prions are non-toxic to mammalian cell cultures and do not cause loss-of-function phenotypes. Importantly, NM particles are also secreted in association with exosomes that horizontally transmit the prion phenotype to naive bystander cells, a process that can be monitored with high accuracy by automated high throughput confocal microscopy. The high abundance of mammalian proteins with amino acid stretches compositionally similar to yeast prion domains makes the NM cell model an attractive model to study self-templating and dissemination properties of proteins with prion-like domains in the mammalian context.     

Surface manipulation of biomolecules for cell microarray applications

Many biological events, such as cellular communication, antigen recognition, tissue repair and DNA linear transfer, are intimately associated with biomolecule interactions at the solid-liquid interface. To facilitate the study and use of these biological events for biodevice and biomaterial applications, a sound understanding of how biomolecules behave at interfaces and a concomitant ability to manipulate biomolecules spatially and temporally at surfaces is required. This is particularly true for cell microarray applications, where a range of biological processes must be duly controlled to maximize the efficiency and throughput of these devices. Of particular interest are transfected-cell microarrays (TCMs), which significantly widen the scope of microarray genomic analysis by enabling the high-throughput analysis of gene function within living cells. This article reviews this current research focus, discussing fundamental and applied research into the spatial and temporal surface manipulation of DNA, proteins and other biomolecules and the implications of this work for TCMs.     

Patterning of proteins and cells on functionalized surfaces prepared by polyelectrolyte multilayers and micromolding in capillaries

A method for protein and cell patterning on polyelectrolyte-coated surfaces using simple micromolding in capillaries (MIMIC) is described. MIMIC produced two distinctive regions. One contained polyethylene glycol (PEG) microstructures fabricated using photopolymerization that provided physical, chemical, and biological barriers to the nonspecific binding of proteins, bacteria, and fibroblast cells. The second region was the polyelectrolyte (PEL) coated surface that promoted protein and cell immobilization.

The difference in surface functionality between the PEL region and background PEG microstructures resulted in simple patterning of biomolecules. Fluorescein isothiocyanate-tagged bovine serum albumin, E. coli expressing green fluorescence protein (GFP), and fibroblast cells were successfully bound to the exposed PEL surfaces at micron scale. Compared with the simple adsorption of protein, fluorescence intensity was dramatically improved (by about six-fold) on the PEL-modified surfaces. Although animal cell patterning is prerequisite for adhesive protein layer to survive on desired area, the PEL surface without adhesive proteins provides affordable microenvironment for cells.

The simple preparation of functionalized surface but universal platform can be applied to various biomolecules such as proteins, bacteria, and cells.     

Quantification of mRNA and protein and integration with protein turnover in a bacterium

Biological function and cellular responses to environmental perturbations are regulated by a complex interplay of DNA, RNA, proteins and metabolites inside cells. To understand these central processes in living systems at the molecular level, we integrated experimentally determined abundance data for mRNA, proteins, as well as individual protein half‐lives from the genome‐reduced bacterium Mycoplasma pneumoniae. We provide a fine‐grained, quantitative analysis of basic intracellular processes under various external conditions. Proteome composition changes in response to cellular perturbations reveal specific stress response strategies. The regulation of gene expression is largely decoupled from protein dynamics and translation efficiency has a higher regulatory impact on protein abundance than protein turnover. Stochastic simulations using in vivo data show how low translation efficiency and long protein half‐lives effectively reduce biological noise in gene expression. Protein abundances are regulated in functional units, such as complexes or pathways, and reflect cellular lifestyles. Our study provides a detailed integrative analysis of average cellular protein abundances and the dynamic interplay of mRNA and proteins, the central biomolecules of a cell.     

A high-quality secretome of A549 cells aided the discovery of C4b-binding protein as a novel serum biomarker for non-small cell lung cancer

Cancer secretomes are a promising source for biomarker discovery. The analysis of cancer secretomes still faces some difficulties mainly related to the intracellular contamination, which hinders the qualification and follow-up validations. This study aimed to establish a high-quality secretome of A549 cells by using the cellular proteome as a reference and to test the merits of this refined secretome for biomarker discovery for non-small cell lung cancer (NSCLC). Using one-dimensional gel electrophoresis followed by liquid-chromatography tandem mass spectrometry, we comprehensively investigated the secretome and the concurrent cellular proteome of A549 cells. A high-quality secretome consisting of 382 proteins was refined from 889 initial secretory proteins. More than 85.3% of proteins were annotated as secreted and 76.8% as extracellular or membrane-bound. The discriminative power of the lung-cancer associated secretome was confirmed by gene expression and serum proteomic data. The elevated level of C4b-binding Protein (C4BP) in NSCLC blood was verified by enzyme-linked immunosorbent assays (ELISA, p = 6.07e-6). Moreover, the serum C4BP level in 89 patients showed a strong association with the clinical staging of NSCLC. Our reference-experiment-driven strategy is simple and widely applicable, and may facilitate the identification of novel promising biomarkers of lung cancer.     

simBio: a Java package for the development of detailed cell models

Quantitative dynamic computer models, which integrate a variety of molecular functions into a cell model, provide a powerful tool to create and test working hypotheses. We have developed a new modeling tool, the simBio package (freely available from http://www.sim-bio.org/), which can be used for constructing cell models, such as cardiac cells (the Kyoto model from Matsuoka et al., 2003, 2004a, b, the LRd model from Faber and Rudy, 2000, and the Noble 98 model from Noble et al., 1998), epithelial cells (Strieter et al., 1990) and pancreatic β cells (Magnus and Keizer, 1998). The simBio package is written in Java, uses XML and can solve ordinary differential equations. In an attempt to mimic biological functional structures, a cell model is, in simBio, composed of independent functional modules called Reactors, such as ion channels and the sarcoplasmic reticulum, and dynamic variables called Nodes, such as ion concentrations. The interactions between Reactors and Nodes are described by the graph theory and the resulting graph represents a blueprint of an intricate cellular system. Reactors are prepared in a hierarchical order, in analogy to the biological classification. Each Reactor can be composed or improved independently, and can easily be reused for different models. This way of building models, through the combination of various modules, is enabled through the use of object-oriented programming concepts. Thus, simBio is a straightforward system for the creation of a variety of cell models on a common database of functional modules.     

Cyr61 suppresses growth of human endometrial cancer cells

Cyr61 (CCN1) is a member of the CCN protein family; these secreted proteins are involved in diverse biological processes such as cell adhesion, angiogenesis, apoptosis, and either growth arrest or growth stimulation depending on the cellular context. We studied the role of Cyr61 in endometrial tumorigenesis. Levels of Cyr61 were decreased in endometrial tumors compared with normal endometrium. Knockdown of Cyr61 expression by RNA interference in a well differentiated endometrial adenocarcinoma cell line (Ishikawa) stimulated its cellular growth. Conversely, overexpression of the protein in the undifferentiated AN3CA endometrial cancer cell line decreased their growth concurrently with increased apoptosis in liquid culture. These same cells had decreased clonogenic capacity and a nearly complete loss of tumorigenicity in vivo. Furthermore, partially purified Cyr61 suppressed growth of endometrial cancer cells. The increased apoptosis in these endometrial cancer cells with forced overexpression of Cyr61 was associated with elevated expression of the pro-apoptotic proteins Bax, Bad, and TRAIL (tumor necrosis factor receptor-associated ligand). Cyr61-induced caspase-3 activation and depolarization of mitochondrial membrane. In summary, endometrial cancer cells have decreased expression of Cyr61 compared with normal endometrium, and this lowered expression may provide the transformed cells a growth advantage over their normal counterpart.