In‐depth characterization of the secretome of mouse CNS cell lines by LC‐MS/MS without prefractionation

Microglia, astrocytes, and neurons, which have important functions in the central nervous system (CNS), communicate mutually to generate a signal through secreted proteins or small molecules, but many of which have not been identified. Because establishing a reference for the secreted proteins from CNS cells could be invaluable in examining cell‐to‐cell communication in the brain, we analyzed the secretome of three murine CNS cell lines without prefractionation by high‐resolution mass spectrometry. In this study, 2795 proteins were identified from conditioned media of the three cell lines, and 2125 proteins were annotated as secreted proteins by bioinformatics analysis. Further, approximately 500 secreted proteins were quantifiable as differentially expressed proteins by label‐free quantitation. As a result, our secretome references are useful datasets for the future study of neuronal diseases. All MS data have been deposited in the ProteomeXchange with identifier PXD001597 ( http://proteomecentral.proteomexchange.org/dataset/PXD001597 ).     

Proteomic identification of secreted proteins from human skeletal muscle cells and expression in response to strength training

Regular physical activity protects against several types of diseases. This may involve altered secretion of signaling proteins from skeletal muscle. Our aim was to identify the most abundantly secreted proteins in cultures of human skeletal muscle cells and to monitor their expression in muscles of strength-training individuals. A total of 236 proteins were detected by proteome analysis in medium conditioned by cultured human myotubes, which was narrowed down to identification of 18 classically secreted proteins expressed in skeletal muscle, using the SignalP 3.0 and Human Genome Expression Profile databases together with a published mRNA-based reconstruction of the human skeletal muscle secretome. For 17 of the secreted proteins, expression was confirmed at the mRNA level in cultured human myotubes as well as in biopsies of human skeletal muscles. RT-PCR analyses showed that 15 of the secreted muscle proteins had significantly enhanced mRNA expression in m. vastus lateralis and/or m. trapezius after 11 wk of strength training among healthy volunteers. For example, secreted protein acidic and rich in cysteine, a secretory protein in the membrane fraction of skeletal muscle fibers, was increased 3- and 10-fold in m. vastus lateralis and m. trapezius, respectively. Identification of proteins secreted by skeletal muscle cells in vitro facilitated the discovery of novel responses in skeletal muscles of strength-training individuals.     

Targeted Proteomics of the Secretory Pathway Reveals the Secretome of Mouse Embryonic Fibroblasts and Human Embryonic Stem Cells

Proteins endogenously secreted by human embryonic stem cells (hESCs) and those present in hESC culture medium are critical regulators of hESC self-renewal and differentiation. Current MS-based approaches for identifying secreted proteins rely predominantly on MS analysis of cell culture supernatants. Here we show that targeted proteomics of secretory pathway organelles is a powerful alternate approach for interrogating the cellular secretome. We have developed procedures to obtain subcellular fractions from mouse embryonic fibroblasts (MEFs) and hESCs that are enriched in secretory pathway organelles while ensuring retention of the secretory cargo. MS analysis of these fractions from hESCs cultured in MEF conditioned medium (MEF-CM) or MEFs exposed to hESC medium revealed 99 and 129 proteins putatively secreted by hESCs and MEFs, respectively. Of these, 53 and 62 proteins have been previously identified in cell culture supernatants of MEFs and hESCs, respectively, thus establishing the validity of our approach. Furthermore, 76 and 37 putatively secreted proteins identified in this study in MEFs and hESCs, respectively, have not been reported in previous MS analyses.The identification of low abundance secreted proteins via MS analysis of cell culture supernatants typically necessitates the use of altered culture conditions such as serum-free medium. However, an altered medium formulation might directly influence the cellular secretome. Indeed, we observed significant differences between the abundances of several secreted proteins in subcellular fractions isolated from hESCs cultured in MEF-CM and those exposed to unconditioned hESC medium for 24 h. In contrast, targeted proteomics of secretory pathway organelles does not require the use of customized media. We expect that our approach will be particularly valuable in two contexts highly relevant to hESC biology: obtaining a temporal snapshot of proteins secreted in response to a differentiation trigger, and identifying proteins secreted by cells that are isolated from a heterogeneous population.Human embryonic stem cells (hESCs)¹ are pluripotent cells isolated from the inner cell mass of a pre-implantation blastocyst stage embryo (1). They have potential applications in regenerative medicine, are an attractive source of human cells for drug evaluation, and are useful models for understanding human development. The self-renewal or differentiation of hESCs is controlled by endogenous proteins secreted by hESCs and by exogenous factors present in cell culture medium (2, 3). For instance, hESCs are routinely cultured on feeder layers of mouse embryonic fibroblasts (MEFs) or on Matrigel-coated plates in mouse embryonic fibroblast–conditioned medium (MEF-CM). In these cases, cytokines secreted by MEFs and present in MEF-CM, together with cytokines and extracellular matrix (ECM) proteins secreted by hESCs, form a localized microenvironment that regulates hESC fate.The comprehensive identification of proteins secreted by MEFs and hESCs—their cellular secretome—can help unravel the molecular mechanisms that regulate hESC fate. Yet the use of MS-based approaches for secretome analysis remains challenging. In general, secretome studies of various cell types have relied on MS analysis of cell culture supernatants (reviewed in Ref. 4). However, such an approach typically results in the identification of small numbers of extracellular proteins. This was indeed the case with MS analysis of conditioned medium (CM) from MEFs or other feeder cells that support the maintenance of undifferentiated hESCs (5–8). A low abundance of secreted proteins of interest and a high concentration of serum proteins in cell culture media significantly impede MS analysis. To overcome these limitations, Bendall et al. implemented an iterative-exclusion MS (IE-MS) strategy, in conjunction with the use of medium without serum or serum replacer, for the identification of proteins secreted by MEFs and hESCs (2). Using this approach, large numbers of previously unreported proteins secreted by MEFs and hESCs could be identified, showing that IE-MS is a powerful strategy for the identification of low abundance proteins. However, the use of medium without serum or serum replacer for secretomic analysis can be problematic. Specifically, the use of a “blank” or serum-free medium might alter cellular physiology and, consequently, the profile of secreted proteins. Indeed, we observe that hESCs are highly prone to apoptosis under such growth conditions. Moreover, an analysis of the cell culture supernatant is not specifically targeted toward endogenously secreted ECM proteins, which are also an important component of the cellular microenvironment. ECM proteins form a matrix that associates with the cell and might not be present in the cell culture supernatant. Moreover, many growth factors are known to be sequestered by ECM proteins and might not be released into the culture medium (9). Here we present a rigorous evaluation of an alternate strategy to interrogate the entire cellular secretome, including cytokines and ECM proteins. Notably, our approach does not require the use of customized media lacking serum and serum replacers, and it is compatible with cell culture systems utilizing media of unknown or poorly defined composition, such as CM from MEFs.To identify the secretome of MEFs and hESCs, we carried out an MS analysis of their subcellular fractions that were enriched in secretory pathway organelles. The secretory pathway comprises the endoplasmic reticulum (ER), the Golgi apparatus, and the associated transport vesicles. Detailed MS analysis of these organelles identifies the secretory cargo (i.e. proteins destined to be secreted) in addition to the secretory pathway proteome (10). Indeed, we have previously identified several secreted proteins in hESCs as a result of contamination by the ER and Golgi (11) in our subcellular fractions. In light of these reports, we hypothesized that targeted proteomic analysis of the secretory pathway is a viable approach for comprehensive characterization of the cellular secretome. Accordingly, we developed protocols to isolate subcellular fractions enriched in the ER and Golgi compartments from MEFs and hESCs, and we subsequently carried out MS analysis on these samples. Several proteins secreted by MEFs and hESCs could be identified in this manner. Strikingly, the numbers of proteins identified were comparable to those obtained with the highly efficient IE-MS approach. Furthermore, we also show that short-term changes in medium composition affect the profile and quantitative levels of several proteins that transit through the secretory pathway, including secreted and membrane proteins. Taken together, our results validate the use of targeted secretory pathway proteomics as a powerful alternate approach to interrogate the cellular secretome.     

Nanozeolite‐driven approach for enrichment of secretory proteins in human hepatocellular carcinoma cells

Given the importance of secreted proteins as a source for early detection and diagnosis of disease, secreted proteins have been arousing considerable attention. However, the analysis of secreted proteins represents a challenge for current proteomic techniques. One of the difficulties in secretomic study is to concentrate proteins from large volume of growth media, particularly, the low abundant and low molecular weight proteins (molecular weight <30 kDa). Herein, we describe a novel strategy for harvesting secretory proteins. In this approach, proteins secreted from the human hepatocellular carcinoma cell line were enriched by zeolite LTL nanocrystals, followed by 1‐D SDS‐PAGE for protein fractionation and then by LC‐ESI‐MS/MS for protein identification. In total, 1474 unique proteins were confidently identified, including 505 low molecular weight proteins, and covered a broad range of pI and molecular weight. Furthermore, this study not only offered an efficient and powerful method for the enrichment of secretory proteins but also allowed in‐depth study of secretome of hepatocellular carcinoma cells. The reported work is expected to represent one of the most comprehensive secretomic analyses so far.     

Quantitative proteomic analysis of the secretory proteins from rat adipose cells using a 2D liquid chromatography-MS/MS approach

We have developed two-dimensional liquid chromatography-tandem mass spectrometry (2D-LC-MS/MS) and 18O proteolytic labeling strategies to identify and compare levels of secretory proteins with low abundance in the conditioned medium of rat adipose cells without or with insulin stimulation. Culture medium was concentrated and secreted proteins were separated on a RP-HPLC followed by LC-MS/MS analysis. For 18O proteolytic labeling, 16O- to 18O-exchange in the digested peptides from eight individual fractions was carried out in parallel in H2(16)O and H(2)18O with immobilized trypsin, and the ratios of isotopically distinct peptides were measured by mass spectrometry. A total of 84 proteins was identified as secreted adipokines. This large number of secretory proteins comprise multiple functional categories. Comparative proteomics of 18O proteolytic labeling allows the detection of different levels of many secreted proteins as exemplified here by the difference between basal and insulin treatment of adipose cells. Taken together, our proteomic approach is able to identify and quantify the comprehensive secretory proteome of adipose cells. Thus, our data support the endocrine role of adipose cells in pathophysiological states through the secretion of signaling molecules.     

Muscle tissue as an endocrine organ: comparative secretome profiling of slow-oxidative and fast-glycolytic rat muscle explants and its variation with exercise

The notion that skeletal muscle is a secretory organ capable to release proteins that can act locally in an autocrine/paracrine manner or even in an endocrine manner to communicate with distant tissues has now been recognized. Under this context, a new paradigm has arisen implicating the muscle in metabolism regulation. Considering the evidences that give exercise a protective role against illnesses associated to physical inactivity, it becomes of especial relevance to characterize muscle secreted proteins. In the present study we show for the first time the secretome characterization and the comparative 2-DE secretome analysis among fast-glycolytic (gastrocnemius) and slow-oxidative (soleus) rat muscle explants and its variation after exercise intervention. We have identified 19 differently secreted proteins when comparing soleus and gastrocnemius secretomes, and 10 in gastrocnemius and 17 in soleus distinctive secreted proteins after 1 week of endurance exercise training. Among identified proteins, DJ-1 was found to be more abundant in fast-glycolytic fiber secretomes. On the contrary, FABP-3 was elevated in slow-oxidative fiber secretomes, although its secretion from gastrocnemius muscle increased in exercised animals. These and other secreted proteins identified in this work may be considered as potential myokines.     

Identification of proteins secreted by head and neck cancer cell lines using LC-MS/MS: Strategy for discovery of candidate serological biomarkers

In search of blood-based biomarkers that would enhance the ability to diagnose head and neck/oral squamous cell carcinoma (HNOSCC) in early stages or predict its prognosis, we analyzed the HNOSCC secretome (ensemble of proteins secreted and/or shed from the tumor cells) for potential biomarkers using proteomic technologies. LC-MS/MS was used to identify proteins in the conditioned media of four HNOSCC cell lines (SCC4, HSC2, SCC38, and AMOSIII); 140 unique proteins were identified on the basis of 5% global false discovery rate, 122 of which were secretory proteins, with 29 being previously reported to be overexpressed in HNOSCC in comparison to normal head and neck tissues. Of these, five proteins including α-enolase, peptidyl prolyl isomerase A/cyclophilin A, 14-3-3 ζ, heterogeneous ribonucleoprotein K, and 14-3-3 σ were detected in the sera of HNOSCC patients by Western blot analysis. Our study provides the evidence that analysis of head and neck cancer cells' secretome is a viable strategy for identifying candidate serological biomarkers for HNOSCC. In future, these biomarkers may be useful in predicting the likelihood of transformation of oral pre-malignant lesions, prognosis of HNOSCC patients and evaluate response to therapy using minimally invasive tests.     

Secretome profiling of primary human skeletal muscle cells

The skeletal muscle is a metabolically active tissue that secretes various proteins. These so-called myokines have been proposed to affect muscle physiology and to exert systemic effects on other tissues and organs. Yet, changes in the secretory profile may participate in the pathophysiology of metabolic diseases. The present study aimed at characterizing the secretome of differentiated primary human skeletal muscle cells (hSkMC) derived from healthy, adult donors combining three different mass spectrometry based non-targeted approaches as well as one antibody based method. This led to the identification of 548 non-redundant proteins in conditioned media from hSkmc. For 501 proteins, significant mRNA expression could be demonstrated. Applying stringent consecutive filtering using SignalP, SecretomeP and ER_retention signal databases, 305 proteins were assigned as potential myokines of which 12 proteins containing a secretory signal peptide were not previously described. This comprehensive profiling study of the human skeletal muscle secretome expands our knowledge of the composition of the human myokinome and may contribute to our understanding of the role of myokines in multiple biological processes. This article is part of a Special Issue entitled: Biomarkers: A Proteomic Challenge.     

Computational reconstruction of the human skeletal muscle secretome

In multicellular organisms, secreted proteins play pivotal regulatory roles in intercellular communication. Proteins secreted by skeletal muscle can act locally on muscle cells through autocrine/paracrine loops and on surrounding tissues such as muscle blood vessels, or they can be released into the blood stream, thus producing systemic effects. By a computational approach, we have screened 6255 products of genes expressed in normal human skeletal muscle. Putatively secreted proteins were identified by sequential steps of sieving, through prediction of signal peptide, recognition of transmembrane regions, and analysis of protein annotation. The resulting putative skeletal muscle secretome consists of 319 proteins, including 78 still uncharacterized proteins. This is the first human skeletal muscle secretome produced by computational analysis. Knowledge of proteins secreted by skeletal muscle could stimulate development of novel treatments for different diseases, including muscle atrophy and dystrophy. In addition, better knowledge of the secretion process in skeletal muscle can be useful for future gene therapy approaches.     

SILAC‐based quantitative proteomic analysis of secretome of Marc‐145 cells infected with porcine reproductive and respiratory syndrome virus

Porcine reproductive and respiratory syndrome virus (PRRSV) is the causative agent of PRRS, which causes severe reproductive failure in sows, respiratory disease in young and growing pigs, and enormous economic losses to the global swine industry. In this study, SILAC combined with MS/MS was used to quantitatively identify the secretory proteins differentially expressed in PRRSV‐infected Marc‐145 cells compared with mock‐infected controls. In total, we identified 204 secretory proteins showing significant differences in infected cells (163 upregulated, 41 downregulated). Intensive bioinformatic analysis of secretome data revealed that PRRSV infection strongly activated nonclassical protein secretion, especially vesicle‐mediated release of exosomal proteins, including different danger‐associated molecular pattern molecules and the majority of secreted proteins involved in protein binding and transport, regulation of response to stimulus, metabolic processes, and immune responses. According to the functional proteins analysis, we speculate that proteins functioning in binding, transport, and the immune response are exploited by PRRSV to facilitate virus replication and immune evasion. Our study for the first time analyzes the secretory protein profile of PRRSV‐infected Marc‐145 cells and provides valuable insight into the host response to PRRSV infection.     

Characterization of the secretome of chickpea suspension culture reveals pathway abundance and the expected and unexpected secreted proteins

The secretome of an organism is defined as a set of secreted proteins that encompasses all proteins exported to the extracellular space. To better understand the chickpea secretome, we used callus culture to isolate and identify secreted proteins as a step toward determining their functions. Proteins in the extracellular media of the suspension culture were examined using SDS-PAGE and mass spectrometry (LC-MS/MS). Proteomic analysis led to the identification of 773 proteins, presumably involved in a variety of functions including metabolism, signal transduction, transport, and cell defense, in addition to maintaining redox status of extracellular space. Bioinformatic analysis confirmed 724 proteins, accounting for 94% of the identified proteins, as constituents of the secretome. Analysis of the secretome revealed the presence of several proteins of unknown function and a large number of classical and nonclassical secreted proteins. This represents the first comprehensive secretome of a legume genome, which is yet to be sequenced. Comparative analysis of the chickpea secretome with those of Medicago, Arabidopsis, and rice revealed that the majority of identified proteins are seemingly species-specific. This study demonstrates that characterization of the chickpea secretome in vitro can be used to identify secreted proteins, which has implications for systems biology research.     

Identification and Validation of Novel Contraction-Regulated Myokines Released from Primary Human Skeletal Muscle Cells

Proteins secreted by skeletal muscle, so called myokines, have been shown to affect muscle physiology and additionally exert systemic effects on other tissues and organs. Although recent profiling studies have identified numerous myokines, the amount of overlap from these studies indicates that the secretome of skeletal muscle is still incompletely characterized. One limitation of the models used is the lack of contraction, a central characteristic of muscle cells. Here we aimed to characterize the secretome of primary human myotubes by cytokine antibody arrays and to identify myokines regulated by contraction, which was induced by electrical pulse stimulation (EPS). In this study, we validated the regulation and release of two selected myokines, namely pigment epithelium derived factor (PEDF) and dipeptidyl peptidase 4 (DPP4), which were recently described as adipokines. This study reveals that both factors, DPP4 and PEDF, are secreted by primary human myotubes. PEDF is a contraction-regulated myokine, although PEDF serum levels from healthy young men decrease after 60 min cycling at VO₂max of 70%. Most interestingly, we identified 52 novel myokines which have not been described before to be secreted by skeletal muscle cells. For 48 myokines we show that their release is regulated by contractile activity. This profiling study of the human skeletal muscle secretome expands the number of myokines, identifies novel contraction-regulated myokines and underlines the overlap between proteins which are adipokines as well as myokines.     

Identification of the amyloid β-protein precursor and cystatin C as novel epidermal growth factor receptor regulated secretory proteins in nasopharyngeal carcinoma by proteomics

The epidermal growth factor receptor (EGFR) is usually overexpressed in nasopharyngeal carcinoma (NPC) and is associated with pathogenesis of NPC. However, while EGFR-modulated intracellular proteins have been extensively studied, little is known concerning their extracellular counterparts. To identify EGFR-regulated secreted proteins in NPC, we compared the secretome profiles of TGF-α-stimulated and unstimulated NPC cell line CNE-2. CNE-2 cells were cultured in the absence or presence of TGF-α for 24 h, and secreted proteins were obtained from conditioned serum-free media and enriched by ultrafiltration centrifugation. Using 2-DE and subsequent mass spectrometry, we identified 16 differential secreted proteins, among which the amyloid β-protein precursor (APP) was up-regulated and cystatin C was down-regulated after TGF-α stimulation. We further showed that the secretory changes of APP and cystatin C in CNE-2 after TGF-α stimulation could be abrogated by pretreatment of EGFR tyrosine kinase inhibitor PD153035 and PI3 kinase inhibitor Wortmannin, validating that APP and cystatin C are EGFR-regulated secreted proteins in NPC cells. Immunohistochemistry showed that the expression level of EGFR was positively correlated with the expression level of APP and negatively correlated with the expression level of cystatin C in NPC tissues, indicating that EGFR also regulates expression of APP and cystatin C in clinical NPC tissues. Furthermore, functional analysis showed that the growth and migration of CNE-2 cells decreased after neutralization of secretory APP in the medium using the anti-APP antibody. Our data provide substantial evidence that APP and cystatin C are target secreted proteins of EGFR in NPC, and upregulation of secretory APP by EGFR may be involved in the pathogenesis of NPC.     

Proteomic analysis of secreted proteins by human bronchial epithelial cells in response to cadmium toxicity

For years, many studies have been conducted to investigate the intracellular response of cells challenged with toxic metal(s), yet, the corresponding secretome responses, especially in human lung cells, are largely unexplored. Here, we provide a secretome analysis of human bronchial epithelial cells (BEAS‐2B) treated with cadmium chloride (CdCl₂), with the aim of identifying secreted proteins in response to Cd toxicity. Proteins from control and spent media were separated by two‐dimensional electrophoresis and visualized by silver staining. Differentially‐secreted proteins were identified by MALDI‐TOF‐MS analysis and database searching. We characterized, for the first time, the extracellular proteome changes of BEAS‐2B dosed with Cd. Our results unveiled that Cd treatment led to the marked upregulation of molecular chaperones, antioxidant enzymes, enzymes associated with glutathione metabolic process, proteins involved in cellular energy metabolism, as well as tumor‐suppressors. Pretreatment of cells with the thiol antioxidant glutathione before Cd treatment effectively abrogated the secretion of these proteins and prevented cell death. Taken together, our results demonstrate that Cd causes oxidative stress‐induced cytotoxicity; and the differentially‐secreted protein signatures could be considered as targets for potential use as extracellular biomarkers upon Cd exposure.     

Pitfalls and opportunities in the characterization of unconventionally secreted proteins by secretome analysis

Proteins are released from cells by different secretory pathways. The secretory pathway via the ER-Golgi route - realized by a signal sequence - is referred to as “classical secretion”. In contrast, alternative secretory pathways were summarized as “unconventional protein secretion”. Until now, unconventional protein secretion was lacking attention due to the absence of detailed mechanistic insight and limited experimental access. However, there is a growing number of experimental data showing that a large proportion of secreted proteins is released by these alternative routes. Secretomics - the analysis of all secreted proteins of a cell population - offers the opportunity to gain more functional insight into unconventional protein secretion. Several pitfalls in secretome analysis starting with the analyzed cell model and sample preparation to data analysis have to be considered for detailed characterization of the secretome. Here, we highlight the investigation of secretomes by quantitative LC-MS/MS analysis and discuss pitfalls and opportunities in the characterization of unconventionally secreted proteins by secretome analysis.     

Comparative secretome analysis of human bone marrow‐derived mesenchymal stem cells during osteogenesis

Osteogenesis is a tightly regulated process that involves coordinated extracellular signals from autocrine and paracrine loops. Secretory proteins during osteogenesis can inhibit cell proliferation and activate cell differentiation toward mature osteoblasts, which are characterized by mineralization. In this study, we attempted to identify these secretory proteins during osteogenesis using LC–MS/MS analysis. We compared the secretome between undifferentiated human bone marrow‐derived mesenchymal stem cells (hBMSCs) and differentiated osteoblasts. Among 315 proteins that were identified, 177 proteins were present at increased levels in osteoblasts, whereas 88 proteins were present at decreased levels. Among the identified proteins, several were validated by quantitative RT‐PCR and immunoblot analysis. Of particular interest, calcium homeostasis‐related proteins were upregulated, whereas stem cell proliferation‐related proteins and other lineage‐related proteins were downregulated during osteogenesis. These findings provide information about the dynamic changes in the expression and secretion of proteins during osteogenesis and suggest the putative role of secretory proteins in osteogenesis. J. Cell. Physiol. 228: 216–224, 2013. © 2012 Wiley Periodicals, Inc.     

Proteomic profiling of high glucose primed monocytes identifies cyclophilin A as a potential secretory marker of inflammation in type 2 diabetes

Hyperglycemia is widely recognized to be a potent stimulator of monocyte activity, which is a crucial event in the pathogenesis of atherosclerosis. We analyzed the monocyte proteome for potential markers that would enhance the ability to screen for early inflammatory status in Type 2 diabetes mellitus (T2DM), using proteomic technologies. Monocytic cells (THP-1) were primed with high glucose (HG), their protein profiles were analyzed using 2DE and the downregulated differentially expressed spots were identified using MALDI TOF/MS. We selected five proteins that were secretory in function with the help of bioinformatic programs. A predominantly downregulated protein identified as cyclophilin A (sequence coverage 98%) was further validated by immunoblotting experiments. The cellular mRNA levels of cyclophilin A in various HG-primed cells were studied using qRT-PCR assays and it was observed to decrease in a dose-dependent manner. LC-ESI-MS was used to identify this protein in the conditioned media of HG-primed cells and confirmed by Western blotting as well as ELISA. Cyclophilin A was also detected in the plasma of patients with diabetes. We conclude that cyclophilin A is secreted by monocytes in response to HG. Given the paracrine and autocrine actions of cyclophilin A, the secreted immunophilin could be significant for progression of atherosclerosis in type 2 diabetes. Our study also provides evidence that analysis of monocyte secretome is a viable strategy for identifying candidate plasma markers in diabetes.     

Comparison of isotope-labeled amino acid incorporation rates (CILAIR) provides a quantitative method to study tissue secretomes

Adipose tissue is an endocrine organ involved in regulation of whole-body energy metabolism via storage of lipids and secretion of various peptide hormones (adipokines). We previously characterized the adipose tissue secretome and showed that [(13)C]lysine incorporation into secreted proteins can be used to determine the origin of identified proteins. In the present study we determined the effect of insulin on the secretome by comparing incorporation rates of (13)C-labeled lysine in the presence and absence of insulin. Human visceral adipose tissue from one patient was divided over six dishes. After subsequent washes to remove serum proteins, [(13)C]lysine-containing medium was added. Three dishes also received 60 nm insulin. The other three were controls. After 72 h of culture, media were collected and processed separately, involving concentration by ultrafiltration and fractionation by SDS-PAGE followed by in-gel digestion of excised bands and LC-MS/MS analyses. The obtained spectra were used for database searching and calculation of heavy/light ratios. The three control data sets shared 342 proteins of which 156 were potentially secreted and contained label. The three insulin-derived data sets shared 361 proteins of which 141 were potentially secreted and contained label. After discarding secreted proteins with very low label incorporation, 121 and 113 proteins remained for control and insulin data sets, respectively. The average coefficient of variation for control triplicates was 10.0% and for insulin triplicates was 18.3%. By comparing heavy/light ratios in the absence and presence of insulin we found 24 up-regulated proteins and four down-regulated proteins, and 58 proteins showed no change. Proteins involved in the endoplasmic reticulum stress response and in extracellular matrix remodeling were up-regulated by insulin. In conclusion, comparison of isotope-labeled amino acid incorporation rates (CILAIR) allows quantitative assessment of changes in protein secretion without the need for 100% label incorporation, which cannot be reached in differentiated tissues or cells.