Secretomics

Secretomics is a subset of proteomics in which all of the secreted proteins of a cell, tissue, or organism are analyzed. Secreted proteins are involved in a variety of physiological processes, including cell signaling and matrix remodeling, but are also integral to invasion and metastasis of malignant cells. Secretomics has thus been especially important in the discovery of biomarkers for cancer and understanding molecular basis of pathogenesis. Secretomics is a subset of proteomics in which all of the secreted proteins of a cell, tissue, or organism are analyzed. Secreted proteins are involved in a variety of physiological processes, including cell signaling and matrix remodeling, but are also integral to invasion and metastasis of malignant cells. Secretomics has thus been especially important in the discovery of biomarkers for cancer and understanding molecular basis of pathogenesis. In 2000 Tjalsma et al. coined the term 'secretome' in their study of the eubacterium B. subtilis. They defined the secretome as all of the secreted proteins and secretory machinery of the bacteria. Using a database of protein sequences in B. subtilis and an algorithm that looked at cleavage sites and amino-terminal signal peptides characteristic of secreted proteins they were able to predict what fraction of the proteome is secreted by the cell. In 2001 the same lab set a standard of secretomics – predictions based on amino acid sequence alone are not enough to define the secretome. They used two-dimensional gel electrophoresis and mass spectrometry to identify 82 proteins secreted by B. subtilis, only 48 of which had been predicted using the genome-based method of their previous paper. This demonstrates the need for protein verification of predicted findings. As the complicated nature of secretory pathways was revealed – namely that there are many non-classical pathways of secretion and there are many non-secreted proteins that are a part of the classical secretory pathway – a more in-depth definition of the secretome became necessary. In 2010, Agrawal et al. suggested defining the secretome as 'the global group of secreted proteins into the extracellular space by a cell, tissue, organ, or organism at any given time and conditions through known and unknown secretory mechanisms involving constitutive and regulated secretory organelles'. In culture, cells are surrounded by contaminants. Bovine serum from cell culture media and cellular debris can contaminate the collection of secreted proteins used for analysis. Bovine contaminants present a particular challenge because the protein sequences of many bovine extracellular proteins, like fibronectin and fibulin-1, are similar to the human protein sequences. To remove these contaminants, cells can be washed with PBS or serum-free medium (SFM) before incubating in SFM and collecting secreted proteins. Care must be taken not to burst cells, releasing intracellular proteins. In addition, incubation time and conditions must be optimized so that the metabolic stress that can be induced by the lack of nutrients in SFM does not affect secretomic analysis. Some proteins are secreted in low abundance and then diluted further in the cell culture medium or body fluid, making these proteins difficult to detect and analyze. Concentration methods like TCA precipitation can be used as well as highly sensitive methods like antibody microarrays that can detect even single molecules of a protein. Many secretomic studies are conducted in vitro with cell culture methods, but it is unclear whether the same proteins are secreted in vivo. More and more studies, especially those looking at the cancer secretome, are using in vivo methods to confirm the relevance of the results obtained in vitro. For example, proximal biological fluids can be collected adjacent to a tumor in order to conduct a secretomic analysis. Many secreted proteins have an N-terminal peptide sequence that signals for the translated protein to move into the endoplasmic reticulum where the processing occurs that will ultimately lead to secretion. The presence of these signal peptides can be used to predict the secretome of a cell. Software such as SignalP can identify signal sequences (and their cleavage sites) to predict proteins that are secreted. Since transmembrane proteins are also processed in the ER, but not secreted, software like the TMHMM server is used to predict transmembrane domains and therefore eliminate false positives. Some secretory proteins do not have classical signal peptide sequences. These 'leaderless secretory proteins' (LSPs) will be missed by SignalP. SecretomeP is a software that has been developed to try to predict these non-classical secretory proteins from their sequences. Genome-wide secretomes have been predicted for a wide range of organisms, including human, mouse, zebrafish, and hundreds of bacteria. Genome-wide prediction methods have a variety of problems. There is a high possibility of false positives and false negatives. In addition, gene expression is heavily influenced by environmental conditions, meaning a secretome predicted from the genome or a cDNA library is not likely to match completely with the true secretome. Proteomic approaches are necessary to validate any predicted secreted proteins. Several genome-wide secretome databases or knowledgebases are available based on both curation and computational prediction. These databases include: the fungal secretome database (FSD), the fungal secretome knowledgebase (FunSecKB),(FunSecKB2), (PlantSecKB), and the lactic acid bacterial secretome database. The human and animal protein subcellular location database (MetaSecKB) and the protist subcellular proteome database (ProtSecKB) are also recently released. Though there are some inaccuracies in the computational prediction, these databases provide useful resources for further characterizing the protein subcellular locations.