A Dual SILAC Proteomic Labeling Strategy for Quantifying Constitutive

Jul 20, 2015 - A Dual SILAC Proteomic Labeling Strategy for Quantifying Constitutive and Cell–Cell Induced Protein Secretion ... *E-mail: cambridge@...
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A Dual SILAC Proteomic Labeling Strategy for Quantifying Constitutive and Cell−Cell Induced Protein Secretion Michael Stiess,†,‡ Sabine Wegehingel,§ Chuong Nguyen,∥ Walter Nickel,§ Frank Bradke,†,⊥ and Sidney B. Cambridge*,# †

Max-Planck-Institute for Neurobiology, Am Klopferspitz 18, 82152 Munich-Martinsried, Germany Biozentrum, University of Basel, Klingelbergstrasse 50, 4056 Basel, Switzerland § Heidelberg University Biochemistry Center, Im Neuenheimer Feld 328, 69120 Heidelberg, Germany ∥ Department of Structural Biology & Biophysics, Pfizer, Groton, Connecticut 06340, United States ⊥ Axon Growth and Regeneration Group, Deutsches Zentrum für Neurodegenerative Erkrankungen, 51375 Bonn, Germany # Department of Functional Neuroanatomy, University of Heidelberg, Im Neuenheimer Feld 307, 69120 Heidelberg, Germany ‡

S Supporting Information *

ABSTRACT: Recent evidence suggests that the extracellular protein milieu is much more complex than previously assumed as various secretome analyses from different cell types described the release of hundreds to thousands of proteins. The extracellular function of many of these proteins has yet to be determined particularly in the context of threedimensional tissues with abundant cell−cell contacts. Toward this goal, we developed a strategy of dual SILAC labeling astrocytic cultures for in silico exclusion of unlabeled proteins from serum or neurons used for stimulation. For constitutive secretion, this strategy allowed the precise quantification of the extra-to-intracellular protein ratio of more than 2000 identified proteins. Ratios covered 4 orders of magnitude indicating that the intracellular vs extracellular contributions of different proteins can be variable. Functionally, the secretome of labeled forebrain astrocytic cultures specifically changed within hours after adding unlabeled, “physiological” forebrain neurons. “Nonphysiological” cerebellar hindbrain neurons, however, elicited a different, highly repulsive secretory response. Our data also suggest a significant association of constitutive secretion with the classical secretion pathway and regulated secretion with unconventional pathways. We conclude that quantitative proteomics can help to elucidate general principles of cellular secretion and provide functional insight into the abundant extracellular presence of proteins. KEYWORDS: extracellular matrix, astrocytes, proteomics, secretion, SILAC

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INTRODUCTION Protein secretion from mammalian cells can be classified into classical/conventional and unconventional pathways. Many secretory proteins use the classical, endoplasmatic reticulum (ER)/Golgi dependent route,1 but proteins can also be exported by unconventional pathways.2 Different pathways of unconventional protein secretion have been identified that are mediated either by direct translocation across the plasma membrane or involve intracellular vesicle intermediates, as seen with FGF2 or Interleukin 1β, respectively.3 A large body of studies has used mass spectrometry to study secreted proteins including secretomes of bacteria,4 stem cells,5 plants,6 or cancer cells.7 However, many of these studies lacked quantitative analyses. More recently, SILAC (stable isotope labeling of cells in culture)8 based approaches have been used for quantitative assessment of secretion with particular emphasis on stimulation-induced changes in secretion.9−11 These studies used biologically active molecules for stimulation that could be added to the medium. However, analysis of cell− cell induced stimulation of secretion has thus far been difficult to achieve because the secreted proteins could not be © XXXX American Chemical Society

unambiguously classified as coming from one cell type or the other.12 In addition, the proteins contained in the serum used for preparing culture media are typically secreted proteins, and thus, considerable effort has to be taken to recognize contaminating serum proteins in secretion studies.13 To overcome both problems, we adopted a simple, modified dual SILAC labeling strategy. Standard triple SILAC labeling strategies involve “light” (unmodified), “medium”, and “heavy” isotope labeled amino acids. Instead, we exposed cells only to “medium” and “heavy” isotopes for labeling and quantification to exclude all “light”/unmodified peptides. With this approach, proteins in the supernatants from a sample of two different cell populations, one labeled and one unlabeled, could be unmistakably assigned. We chose the brain as a model system to study cell−cell induced stimulation of secretion because cells and tissues from different regions are experimentally easily obtained. Cortical forebrain and cerebellar hindbrain tissue can be readily dissected from the rest of the brain and cultured in Received: March 4, 2015

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DOI: 10.1021/acs.jproteome.5b00199 J. Proteome Res. XXXX, XXX, XXX−XXX

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flasks (two with Lys4/Arg6, two with Lys8/Arg10) were first maintained at 18 °C for 3 h and washed with 18 °C HBSS; then protein-free medium was added, and finally two flasks (one with Lys4/Arg6, one with Lys8/Arg10) were transferred to 37 °C while the other two remained at 18 °C, and were incubated for 5 h.

vitro. Astrocyte cultures from the forebrain were thus used to see if neurons added from either forebrain or hindbrain cerebellum would have differential impacts on astrocytic secretion. In the brain, many extracellular guidance cues function by contact-induced signaling via binding to the mobile, membranous cellular protrusions. Some of these cues are secreted soluble proteins, that are also involved in other processes, including neuronal maintenance and survival.14 Astrocytes and glia cells are known to be important for neuronal migration and the establishment of guidance maps that provide attractive and repulsive cues for axonal growth.15 Thus, the aim of our study was to characterize astrocytic secretion to provide further insight into astrocyte−neuron interactions and to investigate basic concepts of secretion.

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Mass Spectrometry and MaxQuant

Supernatants and cell lysates were processed for MS by standard GelC/MS.17 Briefly, medium and heavy SILAC samples were mixed, run on a 1D SDS gel to increase the dynamic range followed by in-gel tryptic digest,19 peptide extraction, washing and elution with “stage tips”, and finally automated HPLC processing for NanoES. Peptides were separated by reverse phase chromatography using in housemade C18 microcolumns (75 μm i.d. packed with ReproSil-Pur C18-AQ 3 μm resin, Dr. Maisch GmbH) with a 87 min gradient from 5% to 60% acetonitrile in 0.5% acetic acid at a flow rate of 250 nL/min. Agilent 1100 or 1200 nanoflow LCSystem HPLC systems were coupled to a linear iontrap LTQOrbitrap (ThermoFisher Scientific). All MS measurements were performed in the positive ion mode. Precursor ions were measured in the Orbitrap analyzer at 60 000 resolution (at 400 m/z) and a target value of 106 ions. Survey full scan MS spectra (m/z 300−2000) were acquired, and the five most intense ions (with a target value of 5000 ions, with charge states ≥+2) from the survey scan were sequenced by collision induced dissociation (collision energy 35%) in the linear ion trap. The ion selection threshold was set at 500 counts for collisioninduced dissociation MS/MS. Maximum ion accumulation times were 1000 ms for full scans and 150 ms for collisioninduced dissociation MS/MS scans. The dynamic exclusion list was restricted to a maximum of 500 entries with a maximum retention period of 90 s and a relative mass window of 10 ppm. Further MS parameters used with the LTQ Orbitrap: 2.2 kV spray voltage; no sheath and auxiliary gas; 200 °C heated capillary temperature; normal automatic gain control was enabled, 110 V tube lens voltage. Data were acquired using Xcalibur software. Mass spectra were analyzed using the software MaxQuant (version 1.1.1.25).20 The data was searched against the Rat International Protein Index protein sequence database (IPI, version 3.46) and concatenated with reversed copies of all sequences (2 × 39925 entries) using Andromeda, a probabilistic search engine incorporated into the MaxQuant framework.21 Initial maximum allowed mass deviation was set to 7 ppm for monoisotopic precursor ions and 0.5 Da for MS/MS peaks. The required false positive rate was set to 1% at the peptide level; the required false discovery rate was set to 1% at the protein level (including automatic filtering on peptide length, mass error precision estimates, and peptide scores of all forward and reversed peptide identifications); the maximum number of missed cleavages was set at two, and the minimum required peptide length to 6 amino acids. In addition to the protein false discovery rate threshold, reported protein groups required at least two sequenced peptides (one unique) for protein identification and three measured SILAC peptide pairs for quantification. Carbamidomethylation of cysteines was set as a fixed modification. N-terminal acetylation and oxidation of methionines were set as variable modifications.

EXPERIMENTAL PROCEDURES

Cell Culture and SILAC Labeling

Rat forebrain glia cells were obtained by standard procedures. Meninges were removed from cerebral hemispheres of E17/ E18 rat embryos (∼4−5 hemispheres for one 75 cm2 culture flask). The hemispheres were trypsinated and mechanically dissociated.16 One day after plating, the medium was changed to remove cellular debris. Generally, cells were split after reaching about 70−80% confluency. SILAC labeling was achieved by incubating cells for 10−14 days in medium containing SILAC amino acids (Lys4/Arg6 or Lys8/Arg10) at standard concentrations, DMEM, and 10% dialyzed serum.17 Five cell divisions were found to be sufficient for complete exchange of unlabeled amino acids with labeled amino acids.8 After the labeling period, cultures were enriched for astrocytes (Supporting Information Figure 1). Cultures were extensively washed followed by incubation with protein-free minimal medium (MEM, 0.22% NaHCO3, 1% (w/v) glucose, 1 mM glutamine, 0.1 mg/mL pyruvate, 20 nM progesterone, 100 μM putrescine-dihydrochloride, 30 nM selenium-dioxide) for the indicated times prior to removal of the supernatant for MS processing. Cells were either lysed in modified RIPA buffer (Experiment Exp1) or 1% SDS in PBS (Experiment Exp2) containing protease inhibitors (Roche). For the second EIR mass spectrometry experiment (Figure 2a, Experiment Exp2), we had prepared and processed additional parallel samples for Western blotting to allow direct comparison to the mass spectrometry results. For a single MS run, we collected supernatants from a 75 cm2 cell culture flask containing 15 mL of medium. Supernatants were concentrated with 3 kDa cutoff membranes in two steps: first by large volume spin columns (Centriprep YM-3, Millipore) and the resulting 500−700 μL were then further concentrated to less than 30 μL (3K, Amicon Ultra-0.5 mL, Millipore). For the EIR analysis, supernatants were combined with 1/150 of lysate volume to ensure similar amounts of protein in both samples. For analysis of neuron-dependent secretion, forebrain16 and cerebellar granular neurons18 were prepared as described. After washing the astrocytes, 5 × 106 freshly dissociated embryonic neurons (E18) were added to achieve a ratio of about 1:1 neurons/astrocytes and incubated for 5 h. Experiments to block secretion were performed by adding Brefeldin A (BFA) to a final concentration 2 μg/mL for 3 h (or ethanol as vehicle control), washing cells, and incubating cells then in protein-free medium for 5 h with BFA or ethanol. For the low temperature experiments, all four 75 cm2 cell culture

Bioinformatic Analysis

Statistical data analysis was performed using Prism 5.0 (GraphPad Software, San Diego, CA). The SignalP and B

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Figure 1. Experimental setup for mass spectrometry. (A) Raw spectrum of a peptide derived from Biglycan-1, which is secreted from astrocytes but is also present in serum. (Unlabeled) black peaks are derived from serum, blue from “medium” and red peaks from the “heavy” labeled supernatants. (B) Raw spectrum of a peptide derived from Metalloproteinase K, which is secreted from astrocytes but not present in serum. Blue peaks derive from the “medium” and red peaks from the “heavy” labeled lysate. (C) Experimental scheme to investigate the extra- to intracellular ratio (EIR) of proteins. (D) Experimental scheme to investigate neuron-dependent astrocyte secretion. (E and F) Control experiments to investigate the effects of Brefeldin A or low temperature on secretion.

SecretomeP web-based tools can be found at http://www.cbs. dtu.dk/services/. The set of rat transmembrane proteins was obtained by applying the respective protein domain filter with the “Biomart” (www.ensembl.org) database tool. Summed peptide intensities of the MS measurements were used as a proxy for total protein abundance.22 Information about human protein complexes was obtained from the HPRD database (www.hprd.org).

value as EIR. The % extracellular abundance was calculated as EIR/(EIR + 1). For the cell−cell induced stimulation experiments, only proteins were included whose measurements met our requirements in all three conditions (unstimulated, with forebrain or hindbrain neurons). In addition, we excluded proteins that were measured in one condition with two replicates and the respective ratios being more than one magnitude apart. A handful of proteins were included with only one replicate in one condition. All of these were manually analyzed. For the control experiments, only proteins were included that exhibited corresponding “inverse” values (1) in the crossover analyses. For example, replicates with crossover values of 2.1 (heavy/medium) and 0.4 (medium/ heavy) would be included, but not 0.3 and 0.7. The data displayed in the Supporting Information Tables show averages across all replicates. Western Blotting and Immunostaining

Astrocytic supernatants and cellular lysates were separated on standard 1D SDS-PAGE gels, transferred to Immobilon FL membranes, and the relative protein abundance determined by quantitating the fluorescence of dyes coupled to the secondary antibodies (Alexa Fluor 680 goat anti-mouse, IRDye 800CW goat anti-rabbit) used for detection (Odyssey system, LI-COR). The following mouse monoclonal antibodies were used: pan 14-3-3 (Santa Cruz # sc-1657), GAPDH (Ambion, # AM4300), as well as a rabbit polyclonal against Galectin-123 and -3 (Sabine Wegehingel and Walter Nickel, unpublished). The total amount of protein loaded in lysates vs supernatants was D

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Figure 3. Secretion of forebrain astrocytes (FA) in the presence of forebrain neurons (FN) or hindbrain cerebellar neurons (CN). Four numbers in each plot represent: total number of proteins(#Prot)-SignalP positive proteins (SigP)-SecretomeP (SecP) positive proteins-shedded proteins (Shedd). The numbers in parentheses indicate fold change with FN/CN compared to FA alone (normalized to 1). Panels A−H are grouped according to 3-fold changes with FN or CN compared to FA.

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RESULTS To develop a robust assay for SILAC-based quantitative mass spectrometry (MS) of astrocytic secretion, we labeled isolated rat cortical forebrain astrocytic cultures with either “medium” (Lysine4/Arginine6) or “heavy” (Lysine8/Arginine10) SILAC isotopes.8 The key advantage of our SILAC approach was that the analysis could be restricted to “medium” and “heavy” labeled proteins while excluding unlabeled proteins that may have derived from serum, contaminations, or unlabeled neurons added for stimulation. Figure 1A shows the spectrum of a peptide derived from a typical serum protein, Biglycan-1, which was also found to be secreted by astrocytes. Despite washing the astrocytes after growing in serum-containing medium and using protein-free medium for collection of supernatants, there were still obvious peaks measurable in the unlabeled, i.e., “light” fraction of the spectrum. Because the MaxQuant software20

used for MS analysis restricted quantification to the medium (red) and heavy (blue) peaks, even substantial amounts of unlabeled serum peptides in this particular sample did not affect quantification. Similarly, when we used unlabeled, freshly dissociated neurons for stimulation of astrocytic secretion, neuronal and SILAC-labeled astrocytic proteins could be differentiated as well. Secreted proteins for which no unlabeled molecules were present in the sample, for example, Metalloproteinase K, were also quantified based on medium and heavy peptides (Figure 1B). The different experimental schemes for sample comparison are depicted in Figure 1C−F. In a first set of experiments, we sought to characterize constitutive, unstimulated astrocytic secretion by determining the relative extra- to intracellular ratio (EIR) of individual proteins. The experimental protocol depicted in Figure 1C is as follows: Unlabeled astrocytes E

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Journal of Proteome Research secrete unlabeled proteins (black dots surrounding the cell). After 2 weeks of incubation with medium (blue) or heavy (red) SILAC isotope amino acids, the cells and their secreted proteins (blue or red dots) are labeled. Labeled cells were washed and incubated with serum-free medium for 12 h, and their supernatants and cellular lysates were collected for analyses. In two individual experiments Exp1 and Exp2, two mediumlabeled lysates were each separately mixed with heavy-labeled supernatants and two heavy-labeled lysates were mixed with medium-labeled supernatants for quadruplicate, crossover analyses (Figure 1C). Stimulus-dependent secretion was characterized in triplicate by comparing the supernatants of labeled, untreated forebrain astrocytes with supernatants of labeled forebrain astrocytes to which either unlabeled forebrain neurons or unlabeled cerebellar neurons had been added for 5 h (Figure 1D). Finally, mass spectrometry based control experiments were conducted by comparing the supernatants of labeled, untreated astrocytes with the supernatants of labeled astrocytes whose secretion was either blocked with Brefeldin A (BFA) (Figure 1E) or with low temperature (18−20 °C) (Figure 1F).

values for justification. As a control, the cytosolic GAPDH protein was not detected at all in Exp2 even though it is a highly abundant protein and only trace amounts were found in Exp1 (EIR 0.1%). This strongly suggests that proteins identified in the astrocytic supernatants did not derive from lysed or dying cells. By the combination of experimental data, in silico analyses, and confirmation through literature knowledge, we conclude that these data sets truly represent secreted astrocytic proteins. A large number of nontransmembrane proteins (37%) in the astrocytic supernatants did not score with either SignalP or SecretomeP prediction algorithms and, therefore, were categorized as “undefined” (Figure 2E). Proteins in this “undefined” group exhibited a wide range of EIRs and, thus, as a group, cannot be considered low abundant in the supernatant. We found in this group several known secreted proteins (Figure 2E, red), for example, Galectin-1.26 In addition, proteins whose secretion exhibited neuron-dependent changes (yellow, see also Figure 3 and Supporting Information Table S2) and proteins whose secretion was reduced at least 2fold upon BFA treatment (green, see also Figure 4 and Supporting Information Table S3) were also highlighted. As can be seen, almost all highlighted proteins were near or above

Relative Extra- to Intracellular Abundance of Proteins

We first investigated constitutive secretion by analyzing the relative extra- to intracellular ratio (EIR) of proteins. To our knowledge, this is the first attempt to provide a global picture of protein EIRs of any cell type. In experiment Exp1, the four biological replicates yielded a total of 2021 identified proteins. From the EIRs, for each protein the percentage of extracellular abundance out of total protein was derived. Overall, the values varied from 0.004% to 65% in experiment Exp1 and from 0.017% to 63% in experiment Exp2 (838 proteins) (Figure 2A). The EIR of almost all proteins was based on at least two replicates, while 246 proteins were quantified in each of the 4 replicates in both experiments, so that 8 independent replicates contributed to an average EIR (Supporting Information Table S1). The EIRs of the two independent experiments confirm that constitutive secretion is reproducible as the variation between replicates was similar to the variation between the experiments. We selected 6 proteins across the entire spectrum of values and highlighted them in Figure 2A; note the log rhythmic scale. The correlation of 813 EIRs from proteins detected in both experiments was also statistically significant (Pearsons’ correlation r = 0.123, P = 0.0004). We therefore pooled the results so that all subsequently presented EIRs are derived from both experiments. In total, the EIRs of 2046 proteins were quantified. All identified proteins were analyzed with SignalP24 and SecretomeP25 software, separately, to obtain evidence as to whether detected proteins were secreted via the classical pathway (12% of all detected proteins, Figure 2B) or through one of several distinct unconventional secretory pathways (37%, Figure 2C). Transmembrane proteins whose extracellular ectodomains could be detected were categorized as “shedded” (14%, Figure 2D). We found many known secreted proteins in each of the three categories (classical, unconventional, or shedded) across the entire ranges of extracellular abundances reported here. Known secreted proteins were also found at the extreme ends of the graphs, which, particularly for very low values of extracellular abundance, indicated that these proteins were in fact truly secreted proteins and were not unspecifically released into the medium. In each graph, we thus highlighted a few known secreted proteins at the extreme ends of measured

Figure 4. Control MS experiments to block secretion. (A) Quantitative analysis of astrocytic secretion comparing vehicle control with Brefeldin A. Dot values represent the fold secretion difference between control and treated conditions. Proteins identified by SignalP as being secreted by the classical pathway are indicated as red dots, shedded proteins by green dots. Black dots: SecretomeP score of proteins which did not score with SignalP (red dots). Proteins with a SecretomeP score above 0.5 are classified as being unconventionally secreted, with a score below 0.5 were designated as “undefined” (blue dots). (B) Similar to (A) but with low temperature treatment (18−20 °C). F

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Figure 5. Semiquantitative Western blotting. (A) The lysates and supernatants of 4 samples (a−d) were analyzed by immunoblotting to reveal the extra- and intracellular abundance. Note that the amount of protein loaded for lysates and supernatants was adjusted separately for quantification and visualization. For each experiment, 0.5% of lysates and 20% of supernatants were analyzed. (B) Comparison of semiquantitative Western blotting (black, average of B, error bars indicate STD) and mass spectrometry results (gray, EIRs).

We identified only four proteins with a markedly decreased secretion in the presence of forebrain (Col5a2/Col12a1; Figure 3C) or cerebellar (Attractin/Semaphrorin7a; Figure 3D) neurons compared to astrocytes alone. Schwann cell derived collagenV supports Schwann cell proliferation but inhibits axon growth of dorsal root ganglia neurons,27 while decreased collagenV has been also linked to reduced apoptosis.28 This is in line with our data, where decreased apoptosis and increased axonal growth in the presence of forebrain neurons would be a plausible “positive feedback”. Attractin-deficient rats exhibit abnormal myelinogenesis and hypomyelination in the CNS,29 while Semaphorin7a loss-of-function impairs neuronal migration and axon branching. 30 Clearly, reduction of the extracellular abundance of both proteins thus should impair function of “misplaced” nonphysiological hindbrain neurons. The most outstanding groups (42 of all 63 proteins that changed more than 3-fold) were formed by proteins with substantial and sometimes dramatic increases of up to two magnitudes in the presence of cerebellar neurons while forebrain neurons elicited only minor changes (Figure 3E,F). Almost all of these proteins provided exclusively repulsive, “negative feedback” cues to cerebellar neurons. For example, soluble CD44 (fold change with FN:0.9/CN:80.2) is cytotoxic to retinal ganglion cells through pro-apoptotic pathways,31 while Fibulin-2 (FN:2.8/CN:17.4) has been described as antiangiogenic and as a tumor suppressor gene.32 Other proteins in these groups showed equally prominent qualitative and quantitative restrictive responses suggesting that a key contribution of astrocytes to tissue homeostasis is this type of “negative feedback”.

the line of 1% protein being extracellular. On the basis of this observation, we propose that many of the about 400 “undefined” proteins with an extracellular abundance above 1% are physiologically released by astrocytes in vitro. Future experimental validation of their presumed extracellular function will ultimately be needed to confirm these mass spectrometry results. Overall, our experiments suggest that about 1000−1500 different proteins, which are present in supernatants, are secreted or released from astrocytes in a physiologically relevant manner. Neuron-Dependent Astrocytic Secretion

To quantitatively investigate the influence of neurons on astrocytic secretion, we sought to identify the physiological secretory response of forebrain astrocytes in the presence of physiological, i.e., forebrain neurons (FN), or nonphysiological, i.e., “misplaced” cerebellar granular neurons (CN) of the hindbrain. In total, 196 proteins were detected in all three conditions, and their extracellular abundance was normalized to 1 in untreated forebrain astrocytic (FA) cultures. The values of fold-change in the presence of neurons is given for some proteins in parentheses. For display purposes, we arbitrarily set a cutoff value of a 3 fold-change for grouping untreated control and neuron-exposed conditions, albeit with a few exceptions (Figure 3, Supporting Information Table S2). A detailed description of known functions for many of the detected proteins is discussed in the Supporting Information. Most proteins (∼68%, Figure 3A) could be placed into one group showing only minor, less than 3-fold changes in the presence of both types of neurons compared to control astrocytes. Of the 133 proteins in this group, 39 scored with SignalP as being classically secreted and SecretomeP identified another 38 proteins for unconventional secretion, and 18 proteins were being released into the medium by shedding. The group profile was thus summarized as Prot#(133)SigP(39)SecP(38)Shedd(18). Many prominent proteins were in this group, including SPARC/Osteonectin or Superoxide Dismutase. We also detected 63 proteins that changed at least 3-fold in the presence of neurons compared to astrocytes alone and these were subdivided into seven groups (Figure 3B−H). Among those were two groups that increased specifically to hippocampal (Figure 3B) or generally to all neurons (Figure 3G). Potentially, this could be trophic support; however, none of the proteins were previously reported to exhibit trophic functions and their known functions did not reveal any obvious involvement either.

Control Experiments To Block Secretion

Next, we performed mass spectrometry-based control experiments to validate the results by blocking secretion with BFA33 or with low temperature (18−20 °C) 34 (Supporting Information Table S3). Almost all extracellularly detected proteins were more abundant in control supernatants compared to secretion blocked conditions and thus exhibited a ratio control/treatment ratio >1. We grouped proteins as being secreted via classical (red dots), shedded (green dots), unconventional pathways (black dots, with a SecretomeP score above 0.5), or “undefined” (blue dots). For 226 of 230 proteins identified, the ratio of abundance in control vs BFA treated cultures was larger than 1 with a total control/treatment median ratio of 1.6 (Figure 4A). Similarly, for 160 of 183 proteins, the low temperature treatment reduced extracellular abundance (Figure 4B) with a total control/treatment median G

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Figure 6. Pathway-dependent constitutive and stimulated secretion. (A) Median EIRs for the four different secretion categories. (B) Secretion of forebrain astrocytes (FA) in the presence of forebrain neurons (FN) or hindbrain cerebellar neurons (CN). Graph shows the median of each of the four secretion categories.

secretion, noncontact stimulation through proteins secreted from the added neurons may also play a significant role. A general trend is clearly that “sameness”, i.e., astrocytes and neurons both being derived from forebrain tissue, did not elicit a response as intense and obvious as the presence of “different”/“misplaced” neurons. In the latter case, astrocytes used protein secretion in a variety of cellular modes to physiologically attack cerebellar neurons including, among others, inflammatory, antiangiogenic, antimyelinogenic, and cytotoxic processes. Remarkably, the astrocytes appeared to “remember” their tissue origin even after being cultured for 2 weeks in vitro. The depth of our coverage permitted robust statistical analyses and the extraction of physiologically relevant trends for secretion. The median EIRs were 5.9 for classical, 1.2 for unconventional, 1.3 for shedded, and 1.0 for “undefined” secretion (Figure 6A). The differences are highly significant between classical secretion and the other three (ANOVA, P < 0.001). Like the three other secretion categories, shedded proteins also appeared to play a prominent functional role in the negative feedback response (Figure 6B). Moreover, shedded proteins exhibited the most substantial and highly significant decrease in abundance following inhibition of secretion with low temperature (Figure 4B). While it is possible that shedding is the most temperature sensitive pathway, another conceivable explanation could be that shedding is the most dynamic and rapid pathway and thus is most affected by a short sampling time of 5 h. Consequently, the data may be interpreted as shedding being functionally involved in rapid, negative feedback responses toward cells that improperly invade tissues. Future research will have to characterize the contribution of sheddase temperaturesensitivity vs dynamics to our results. Curiously, we also found a link between the overall turnover of a protein and its EIR, as high protein turnover significantly correlated with large EIRs and low turnover with small EIRs, at least for proteins of classical secretion pathway (Persons’ correlation r = 0.34, P = 0.0003). Protein turnover data were derived from a HeLa data set.39 The relevance of this finding is unclear, but there are several aspects that contribute to extracellular turnover such as reuptake into cells vs extracellular degradation, both of which may be affected by in vitro culturing. Proteins of the classical pathway exhibited the least changes, i.e., regulation upon neuronal addition (Figure 6B). Conversely, unconventionally secreted proteins were significantly more upregulated upon exposure to forebrain neurons compared to

ratio of 1.9. As expected, the median fold change upon BFA treatment for classically secreted proteins (1.91) was significantly bigger compared to unconventional (1.57) or “undefined” (1.59) groups (ANOVA, P < 0.001). After low temperature treatment, the fold change of shedded proteins was by far the highest for all groups (2.95) and significantly different to unconventional (1.73) or “undefined” (1.69) groups (ANOVA, P < 0.001) and classically secreted proteins (2.12, ANOVA, P < 0.01). In total, 130 proteins responded to both treatments and their control/treatment ratio in extracellular abundance correlated well between temperature and BFA conditions (Pearsons’ correlation r = 0.29, P = 0.0004). This establishes that low temperature treatment is a valid approach for blocking secretion comparable to administration of BFA. Semiquantitative Western Blotting

To validate our mass spectrometry results with an independent method, we performed semiquantitative Western blotting for EIR analysis. Four different proteins with different levels of extracellular abundance were included in the analysis (Figure 5A). As expected, GAPDH exhibited negligible signals in the supernatant samples, while Galectin-1 and -3 as well as the proteins detected with a pan-14-3-3 antibody were abundant. Figure 5B shows a very good correlation between the average extra-to intracellular ratios derived from mass spectrometry and Western blotting. Across the spectrum from not secreted (GAPDH) to variable levels of secretion, both methods faithfully matched each other’s results.

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DISCUSSION We presented here a high-throughput, quantitative description of constitutive and stimulated secretion from astrocytic cultures. Constitutive secretion of astrocytes has been investigated before,35,36 but including all other published secretome studies, we are the first to provide a global characterization of the relative extra- to intracellular abundance of secreted proteins. Similarly, changes in astrocytic secretion following stimulation has been demonstrated37,38 but never before using dissociated cells as a stimulant. We could stimulate labeled astrocytes with unlabeled neurons to analyze astrocytic secretion, and because of the sensitivity of our experimental approach, we could sample supernatants within 5 h after washing so that the set of detected proteins represented an acute “snapshot” of the primary secretory response after neuron-dependent stimulation. Of note, while we think that cell−cell contacts are the predominant stimulant of the neuron-dependent astrocytic H

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Journal of Proteome Research classically secreted ones (1.54 vs 0.98; ANOVA, P < 0.05). Thus, proteins of the nonclassical pathways displayed less extracellular abundance based on constitutive secretion, but showed much more pronounced increases upon stimulated secretion. This is corroborated by the observation, that classically secreted proteins exhibited a much higher correlation (r = 0.29) between extracellular vs total protein abundance compared to unconventionally (r = 0.13) or “undefined” (r = 0.09) secreted proteins (Pearsons’ correlation for all 2046 measured proteins: r = 0.25, P < 0.0001) (Supporting Information Figure 2A). Together, and despite many wellknown examples of regulated classical secretion, our data indicate that the classical secretion pathway is preferentially involved in constitutive, unregulated secretion and unconventional pathways in regulated secretion. We discovered this principle with neuron-dependent stimulation and future research will have to determine if other stimulation paradigms show similarly relevant regulation. In support of regulated unconventional secretion, caspase-1 has been described as a general regulator of unconventional secretion.40 Finally, for several protein complexes of which we detected at least three subunits, we found quasi-stoichiometric amounts in the supernatants (Supporting Information Figure 2B−D). It remains to be determined which pathway these complexes actually use for reaching the extracellular space, but the data clearly indicated that protein secretion in form of complexes is not uncommon. A likely path to secrete intact protein complexes would be via exosomes which are cell-derived vesicles that were found to contain many cytosolic proteins.41 In conclusion, our data show that astrocytes prominently contribute to the extracellular environment in the mammalian brain, an environment that is much more diverse and complex than previously assumed.

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ABBREVIATIONS

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REFERENCES

SILAC, stable isotope labeling in cell culture; BFA, Brefeldin A; GelC/MS, Gelelectrophoresis/Chromatography/Mass Spectrometry; EIR, extra- to intracellular ratio; FA, forebrain astrocytes; FN, forebrain neurons; CN, cerebellar granular neurons

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ASSOCIATED CONTENT

S Supporting Information *

Supporting Information Table 1: % extracellular abundance of 2046 identified proteins. Supporting Information Table 2: Neuron-dependent changes of astrocytic secretion. Supporting Information Table 3: Control experiments with BFA or low temperature to block secretion. Supporting Information Figure 1: Purity of astrocytic cultures. Supporting Information Figure 2: Comparison of protein abundance and protein clustering with EIRs. The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/ acs.jproteome.5b00199.

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AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. Tel: +49-6221548671. Fax: +49-6221-544951. Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS We thank Liane Meyn for the cell culture work. We gratefully acknowledge support from the Deutsche Forschungsgemeinschaft (F.B.). M.S. was supported by a European Molecular Biology Organization (EMBO) long-term fellowship and is supported by the Human Frontier Science Program. I

DOI: 10.1021/acs.jproteome.5b00199 J. Proteome Res. XXXX, XXX, XXX−XXX

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DOI: 10.1021/acs.jproteome.5b00199 J. Proteome Res. XXXX, XXX, XXX−XXX