Proteomic profiling of the cancer cell secretome: informing clinical research

Introduction: Cancer represents one of the major causes of human deaths. Identification of proteins as biomarkers for early detection of cancer and therapeutic targets for cancer treatment are important issues in precision medicine. Secretome of cancer cells represents the collection of proteins secreted or shed from cancer cells. Proteomic profiling of the cancer cell secretome has been proven to be a convenient and efficient way to discover cancer biomarker and/or therapeutic targets.

Areas covered: There have been numerous reviews describing the history and application of secretome analysis in cancer biomarker/therapeutic target research. The present review focuses on the technological advancement for profiling low-molecular-mass proteins in secretome, the latest information regarding the new candidate biomarkers and molecular mechanisms discovered on the basis of cancer cell secretome analysis, as well as the previously discovered candidate biomarkers that enter into clinical trials.

Expert commentary: Current technologies for protein sample preparation/separation and MS-based protein identification have allowed in-depth analysis of cancer cell secretome. Future efforts should focus on the comprehensiveness of cancer cell secretome, meta-analysis of different secretome datasets and integrated analysis via combining other omics datasets, as well as the incorporation of MS-based biomarker verification pipeline into both preclinical studies and clinical trials.     

Gaining insights into cancer biology through exploration of the cancer secretome using proteomic and bioinformatic tools

Introduction: Tumor-associated proteins released by cancer cells and by tumor stroma cells, referred as ‘cancer secretome’, represent a valuable resource for discovery of potential cancer biomarkers. The last decade was marked by a great increase in number of studies focused on various aspects of cancer secretome including, composition and identification of components externalized by malignant cells and by the components of tumor microenvironment.

Areas covered: Here, we provide an overview of achievements in the proteomic analysis of the cancer secretome, elicited through the tumor-associated interstitial fluid recovered from malignant tissues ex vivo or the protein component of conditioned media obtained from cultured cancer cells in vitro. We summarize various bioinformatic tools and approaches and critically appraise their outcomes, focusing on problems and challenges that arise when applied for the analysis of cancer secretomic databases.

Expert commentary: Recent achievements in the omics- analysis of structural and metabolic aspects of altered cancer secretome contribute greatly to the various hallmarks of cancer including the identification of clinically significant biomarkers and potential targets for therapeutic intervention.     

FUNGALOXPHOS: An integrated database for oxidative phosphorylation in fungi

The oxidative phosphorylation (OXPHOS) system is the main energy-producing pathway in aerobic organisms. Here we present FUNGALOXPHOS, a web based platform that stores OXPHOS proteins encoded in fungal nuclear genomes and that incorporates tools for the extraction, classification and bioinformatic screening of all the putative nuclear encoded fungal OXPHOS proteins. FUNGALOXPHOS includes local, parsing and remote tools that allow exploring the properties of OXPHOS proteins in fungal genomes. FUNGALOXPHOS is freely available on the web at http://bioinformatics.unavarra.es:1000/FUNGALOXPHOS_CSS/main.html.     

Secretome Prediction and Analysis in Sacred Lotus (Nelumbo nucifera Gaertn.)

Sacred lotus, Nelumbo nucifera (Gaertn.), is a basal eudicot with agricultural and medicinal importance. The secretome and proteins in some other subcellular locations including endoplasmic reticulum (ER), mitochondrion, chloroplast, and membrane of sacred lotus were predicted using a set of computational tools. The distribution of proteins in each subcellular location in sacred lotus was compared with proteins in five other plant species. Plant proteomes contained approximately 6–9 % of secreted proteins, 13–15 % membrane proteins, 12–20 % mitochondrial or chloroplast proteins, respectively. Plant secreted proteins consist of a large number of hydrolases and peroxidases which may contribute to cell wall formation, rhizome development and seed germination regulation. The information of secretome and other protein subcellular locations in sacred lotus and other species can be accessed at the PlantSecKB website (http://proteomics.ysu.edu/secretomes/plant.php).     

FaaPred: A SVM-Based Prediction Method for Fungal Adhesins and Adhesin-Like Proteins

Adhesion constitutes one of the initial stages of infection in microbial diseases and is mediated by adhesins. Hence, identification and comprehensive knowledge of adhesins and adhesin-like proteins is essential to understand adhesin mediated pathogenesis and how to exploit its therapeutic potential. However, the knowledge about fungal adhesins is rudimentary compared to that of bacterial adhesins. In addition to host cell attachment and mating, the fungal adhesins play a significant role in homotypic and xenotypic aggregation, foraging and biofilm formation. Experimental identification of fungal adhesins is labor- as well as time-intensive. In this work, we present a Support Vector Machine (SVM) based method for the prediction of fungal adhesins and adhesin-like proteins. The SVM models were trained with different compositional features, namely, amino acid, dipeptide, multiplet fractions, charge and hydrophobic compositions, as well as PSI-BLAST derived PSSM matrices. The best classifiers are based on compositional properties as well as PSSM and yield an overall accuracy of 86%. The prediction method based on best classifiers is freely accessible as a world wide web based server at http://bioinfo.icgeb.res.in/faap. This work will aid rapid and rational identification of fungal adhesins, expedite the pace of experimental characterization of novel fungal adhesins and enhance our knowledge about role of adhesins in fungal infections.     

Proteomics and pulse azidohomoalanine labeling of newly synthesized proteins: what are the potential applications?

Introduction: Measuring the immediate changes in cells that arise from changing environmental conditions is crucial to understanding the underlying mechanisms involved. These changes can be measured with metabolic stable isotope fully labeled proteomes, but requires looking for changes in the midst of a large background. In addition, labeling efficiency can be an issue in primary and fully differentiated cells.

Area covered: Azidohomoalanine (AHA), an analog of methionine, can be accepted by cellular translational machinery and incorporated into newly synthesized proteins (NSPs). AHA-NSPs can be coupled to biotin via CuAAC-mediated click-chemistry and enriched using avidin-based affinity purification. Thus, AHA-containing proteins or peptides can be enriched and efficiently separated from the whole proteome. In this review, we describe the development of mass spectrometry (MS) based AHA strategies and discuss their potential to measure proteins involved in immune response, secretome, gut microbiome, and proteostasis as well as their potential for clinical uses.

Expert commentary: AHA strategies have been used to identify synthesis activity and to compare two biological conditions in various biological model organisms. In combination with instrument development, improved sample preparation and fractionation strategies, MS-based AHA strategies have the potential for broad application, and the methods should translate into clinical use.     

Proteomics and metabolomics in biomarker discovery for cardiovascular diseases: progress and potential

Introduction: The process of discovering novel biomarkers and potential therapeutic targets may be shortened using proteomic and metabolomic approaches.

Areas covered: Several complementary strategies, each one presenting different advantages and limitations, may be used with these novel approaches. In vitro studies show how cells involved in cardiovascular disease react, although the phenotype of cultured cells differs to that occurring in vivo. Tissue analysis either in human specimens or animal models may show the proteins that are expressed in the pathological process, although the presence of structural proteins may be confounding. To identify circulating biomarkers, analyzing the secretome of cultured atherosclerotic tissue, analysis of blood cells and/or plasma may be more straightforward. However, in the latter approach, high-abundant proteins may mask small molecules that could be potential biomarkers. The study of sub-proteomes such as high-density lipoproteins may be useful to circumvent this limitation. Regarding metabolomics, most studies have been performed in small populations, and we need to perform studies in large populations in order to discover robust biomarkers.

Expert commentary: It is necessary to involve the clinicians in these areas to improve the design of clinical studies, including larger populations, in order to obtain consistent novel biomarkers.     

Performance of the auxotrophic Saccharomyces cerevisiae BY4741 as host for the production of IL-1β in aerated fed-batch reactor: role of ACA supplementation, strain viability, and maintenance energy

Background

Pichia pastoris is widely used as a production platform for heterologous proteins and model organism for organelle proliferation. Without a published genome sequence available, strain and process development relied mainly on analogies to other, well studied yeasts like Saccharomyces cerevisiae.

Results

To investigate specific features of growth and protein secretion, we have sequenced the 9.4 Mb genome of the type strain DSMZ 70382 and analyzed the secretome and the sugar transporters. The computationally predicted secretome consists of 88 ORFs. When grown on glucose, only 20 proteins were actually secreted at detectable levels. These data highlight one major feature of P. pastoris, namely the low contamination of heterologous proteins with host cell protein, when applying glucose based expression systems. Putative sugar transporters were identified and compared to those of related yeast species. The genome comprises 2 homologs to S. cerevisiae low affinity transporters and 2 to high affinity transporters of other Crabtree negative yeasts. Contrary to other yeasts, P. pastoris possesses 4 H⁺/glycerol transporters.

Conclusion

This work highlights significant advantages of using the P. pastoris system with glucose based expression and fermentation strategies. As only few proteins and no proteases are actually secreted on glucose, it becomes evident that cell lysis is the relevant cause of proteolytic degradation of secreted proteins. The endowment with hexose transporters, dominantly of the high affinity type, limits glucose uptake rates and thus overflow metabolism as observed in S. cerevisiae. The presence of 4 genes for glycerol transporters explains the high specific growth rates on this substrate and underlines the suitability of a glycerol/glucose based fermentation strategy. Furthermore, we present an open access web based genome browser http://www.pichiagenome.org.     

orthoFind Facilitates the Discovery of Homologous and Orthologous Proteins

Finding homologous and orthologous protein sequences is often the first step in evolutionary studies, annotation projects, and experiments of functional complementation. Despite all currently available computational tools, there is a requirement for easy-to-use tools that provide functional information. Here, a new web application called orthoFind is presented, which allows a quick search for homologous and orthologous proteins given one or more query sequences, allowing a recurrent and exhaustive search against reference proteomes, and being able to include user databases. It addresses the protein multidomain problem, searching for homologs with the same domain architecture, and gives a simple functional analysis of the results to help in the annotation process. orthoFind is easy to use and has been proven to provide accurate results with different datasets. Availability: http://www.bioinfocabd.upo.es/orthofind/.     

An approach to systematic detection of protein structural motifs

A procedure to detect similar local structures of proteins fromC coordinates is presented. First, the conformations of seven-residuepeptide segments are approximated by a limited number of representatives,each of which is assigned a symbol. Thus, the overall conformationof a protein is represented by a symbol string. The comparisonof these symbol strings using a sequence alignment techniquethen gives pairs of similar local structures. These pairs areconsidered candidates of structural motifs. The applicationof the procedure to the analysis of 93 proteins gave 858 pairsof similar local structures, which included several well-knownstructural motifs such as the nucleotide-binding ßß-unitand the calcium-binding EF hand. The characterization of aminoacid patterns of similar local structures given by the procedureshould be useful for the development of protein structure predictionbased on the acquisition of empirical rules from a large-scaledatabase.     

Filling gaps in bacterial catabolic pathways with computation and high-throughput genetics

To discover novel catabolic enzymes and transporters, we combined high-throughput genetic data from 29 bacteria with an automated tool to find gaps in their catabolic pathways. GapMind for carbon sources automatically annotates the uptake and catabolism of 62 compounds in bacterial and archaeal genomes. For the compounds that are utilized by the 29 bacteria, we systematically examined the gaps in GapMind’s predicted pathways, and we used the mutant fitness data to find additional genes that were involved in their utilization. We identified novel pathways or enzymes for the utilization of glucosamine, citrulline, myo-inositol, lactose, and phenylacetate, and we annotated 299 diverged enzymes and transporters. We also curated 125 proteins from published reports. For the 29 bacteria with genetic data, GapMind finds high-confidence paths for 85% of utilized carbon sources. In diverse bacteria and archaea, 38% of utilized carbon sources have high-confidence paths, which was improved from 27% by incorporating the fitness-based annotations and our curation. GapMind for carbon sources is available as a web server (http://papers.genomics.lbl.gov/carbon) and takes just 30 seconds for the typical genome.     

SECISearch3 and Seblastian: new tools for prediction of SECIS elements and selenoproteins

Selenoproteins are proteins containing an uncommon amino acid selenocysteine (Sec). Sec is inserted by a specific translational machinery that recognizes a stem-loop structure, the SECIS element, at the 3′ UTR of selenoprotein genes and recodes a UGA codon within the coding sequence. As UGA is normally a translational stop signal, selenoproteins are generally misannotated and designated tools have to be developed for this class of proteins. Here, we present two new computational methods for selenoprotein identification and analysis, which we provide publicly through the web servers at http://gladyshevlab.org/SelenoproteinPredictionServer or http://seblastian.crg.es. SECISearch3 replaces its predecessor SECISearch as a tool for prediction of eukaryotic SECIS elements. Seblastian is a new method for selenoprotein gene detection that uses SECISearch3 and then predicts selenoprotein sequences encoded upstream of SECIS elements. Seblastian is able to both identify known selenoproteins and predict new selenoproteins. By applying these tools to diverse eukaryotic genomes, we provide a ranked list of newly predicted selenoproteins together with their annotated cysteine-containing homologues. An analysis of a representative candidate belonging to the AhpC family shows how the use of Sec in this protein evolved in bacterial and eukaryotic lineages.     

Comparative genetic analysis of PP2A-Cdc55 regulators in budding yeast

Cdc55, a regulatory B subunit of the protein phosphatase 2A (PP2A) complex, plays various functions during mitosis. Sequestration of Cdc55 from the nucleus by Zds1 and Zds2 is important for robust activation of mitotic Cdk1 and mitotic progression in budding yeast. However, Zds1-family proteins are found only in fungi but not in higher eukaryotes. In animal cells, highly conserved ENSA/ARPP-19 family proteins bind and inhibit PP2A–B55 activity for mitotic entry.

In this study, we compared the relative contribution of Zds1/Zds2 and ENSA-family proteins Igo1/Igo2 on Cdc55 functions in budding yeast mitosis. We confirmed that Igo1/Igo2 can inhibit Cdc55 in early mitosis, but their contribution to Cdc55 regulation is relatively minor compared with the role of Zds1/Zds2. In contrast to Zds1, which primarily localized to the sites of cell polarity and in the cytoplasm, Igo1 is localized in the nucleus, suggesting that Igo1/Igo2 inhibit Cdc55 in a manner distinct from Zds1/Zds2.

Our analysis confirmed an evolutionarily conserved function of ENSA-family proteins in inhibiting PP2A-Cdc55, and we propose that Zds1-dependent sequestration of PP2A-Cdc55 from the nucleus is uniquely evolved to facilitate closed mitosis in fungal species.     

Bile: miRNA pattern and protein-based biomarkers may predict acute cellular rejection after liver transplantation

Context: Bile rather than blood depicts the local inflammation in the liver and may improve prediction and diagnosis of acute cellular rejection (ACR) after liver transplantation (OLT).

Methods: Secretome and miRNAs were analyzed during the first two weeks and on clinical suspicion of ACR in the bile of 45 OLT recipients.

Results: Levels of CD44, CXCL9, miR-122, miR-133a, miR-148a and miR-194 were significantly higher in bile of patients who developed ACR within the first 6 months after OLT and during ACR.

Conclusion: Analysis of secretome and miRNA in bile could improve our understanding of the local inflammatory process during rejection.     

Proteome analysis of adrenal cortical tumors

Introduction: Adrenal tumor is a relatively common tumor. The discrimination between adrenal cortical adenoma (ACA) and adrenal cortical carcinoma (ACC) is crucial as these two diseases have distinct prognosis. ACA is a benign tumor curable by surgical excision, while the prognosis of ACC is extremely poor, with a 5-year mortality of 75–90%. Therefore, previous proteomic studies focused on markers allowing the differentiation between ACA and ACC.

Areas covered: Several proteomic approaches based on the analysis of various samples such as human tissues, urine, and cell lines. In this review, we focused on proteomic studies performed to improve adrenal tumor diagnosis and identify ACC therapeutic targets.

Expert commentary: The rapid development of cancer genomics provided a lot of information, which affects functional proteomics. In practice, differentially expressed proteins between ACA and ACC have been suggested in several proteomic studies and had a biologic implication in ACC.     

ExonVisualiser – application for visualization exon units in 2D and 3D protein structures

The web application oriented on identification and visualization of protein regions encoded by exons is presented. The Exon Visualiser can be used for visualisation on different levels of protein structure: at the primary (sequence) level and secondary structures level, as well as at the level of tertiary protein structure. The programme is suitable for processing data for all genes which have protein expressions deposited in the PDB database. The procedure steps implemented in the application: I) loading exons sequences and theirs coordinates from GenBank file as well as protein sequences: CDS from GenBank and aminoacid sequence from PDB II) consensus sequence creation (comparing amino acid sequences form PDB file with the CDS sequence from GenBank file) III) matching exon coordinates IV) visualisation in 2D and 3D protein structures. Presented web-tool among others provides the color-coded graphical display of protein sequences and chains in three dimensional protein structures which are correlated with the corresponding exons.

Availability

http://149.156.12.53/ExonVisualiser/     

Combination of sepsis biomarkers may indicate an invasive fungal infection in haematological patients

Background: Invasive fungal infections are a major threat to a large cohort of immunocompromised patients, including patients with chemotherapy-associated neutropenia. Early differential diagnosis with bacterial infections is often complicated, which leads to a delay in empirical antifungal therapy and increases risk for adverse outcome. Accessibility and performance of specific fungal antigen and PCR-tests are still limited, while sepsis biomarkers are more broadly used in most settings currently.

Methods: Haematological patients hospitalized to receive chemotherapy with proven or probable invasive fungal infection or microbiologically proven bacterial bloodstream infection were included in the study. C-reactive protein was assessed daily during the profound neutropenia period, while procalcitonin or presepsin were measured during the first 48?hours after the onset of febrile episode.

Results: There were totally 64 patients included in the study, 53 with bacterial bloodstream infections and 11 with invasive fungal infections. Combination of CRP >120 with PCT <1.25 or presepsin <170 was shown to be a possible combined biomarker for invasive fungal infections in immunocompromised patients, with areas under the ROC-curves: 0.962 (95% CI 0.868 to 0.995) for PCT-based combination and 0.907 (95% CI 0.692 to 0.990) for presepsin-based combination.     

Transgenic expression of plant chitinases to enhance disease resistance

Crop plants have evolved an array of mechanisms to counter biotic and abiotic stresses. Many pathogenesis-related proteins are expressed by plants during the attack of pathogens. Advances in recombinant DNA technology and understanding of plant–microbe interactions at the molecular level have paved the way for isolation and characterization of genes encoding such proteins, including chitinases. Chitinases are included in families 18 and 19 of glycosyl hydrolases (according to www.cazy.org) and they are further categorized into seven major classes based on their aminoacid sequence homology, three-dimensional structures, and hydrolytic mechanisms of catalytic reactions. Although chitin is not a component of plant cell walls, plant chitinases are involved in development and non-specific stress responses. Also, chitinase genes sourced from plants have been successfully over-expressed in crop plants to combat fungal pathogens. Crops such as tomato, potato, maize, groundnut, mustard, finger millet, cotton, lychee, banana, grape, wheat and rice have been successfully engineered for fungal resistance either with chitinase alone or in combination with other PR proteins.