Halothane Binding Proteome in Human Brain Cortex Jonathan Z. Pan,*,† Jin Xi,† John W. Tobias,‡ Maryellen F. Eckenhoff,† and Roderic G. Eckenhoff† Department of Anesthesiology and Critical Care and Department of Bioinformatics, University of Pennsylvania Health System, Philadelphia, Pennsylvania 19104 Received June 26, 2006
Inhaled anesthetics bind specifically to a wide variety of proteins in the brain. This set of proteins must include those that contribute to the physiological and behavioral phenotypes of anesthesia and the related side effects. To identify the anesthetic-binding targets and functional pathways associated with these targets in human brain, halothane photolabeling and two-dimensional (2D) gel electrophoresis were used. Both membrane and soluble proteins from human temporal cortex were prepared. More than 300 membrane and 400 soluble protein spots were detected on the stained blots, of which 23 membrane and 34 soluble proteins were labeled by halothane and identified by mass spectroscopy. Their functional classification reveals five groups, including carbohydrate metabolism, protein folding, oxidative phosphorylation, nucleoside triphosphatase, and dimer/kinase activity with different correlative stringency. When network analysis of the interaction between these protein molecules is used, the weighted interaction accentuates the cellular protein components important in cell growth and proliferation, cell cycle and cell death, and cell-cell signaling and interactions, although no pathway was specific. This study provides evidence for multiple anesthetic binding targets and suggests potential pathways involved in their actions. Keywords: anesthetic • protein binding • protein expression • 2D gel electrophoresis • CNS • soluble proteins • membrane proteins • functional classification • network analysis
Introduction The pool of potential molecular targets for the inhaled anesthetics, rather than shrinking to reveal a small subset of important targets, appears to be expanding. For example, recent work has suggested that a variety of ion channels,1-3 mitochondrial complexes,4 and synaptic vesicle trafficking proteins5,6 be included in the list of plausible anesthesia effectors. However, there remains little evidence of a direct interaction between anesthetic and many of these targets, in part due to the difficulty of measuring the binding of these lowaffinity ligands. Photolabeling with 14C-halothane, an unmodified clinical volatile anesthetic, has allowed preliminary assessments of the number and identity of binding targets in membranes prepared from whole rodent brain.7 Approximately 15% of the detectable spots on two-dimensional (2D) gel electrophoresis incorporated label with an affinity and stoichiometry consistent with being molecular effectors for this drug. Prominent were various mitochondrial targets, including subunits of respiratory complex IV and ATP synthase, and the * To whom correspondence should be addressed: Jonathan Z. Pan, MD, Ph.D., Department of Anesthesiology and Critical Care, 305 John Morgan Building, 3620 Hamilton Walk, University of Pennsylvania Health System, Philadelphia, PA 19104. Phone: 215-615-0221. Fax: 215-349-5708. E-mail:
[email protected]. † Department of Anesthesiology and Critical Care, University of Pennsylvania Health System. ‡ Department of Bioinformatics, University of Pennsylvania Health System.
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voltage-dependent anion channel, all of which are functionally plausible molecular targets. It is important to define the molecular targets in human brain, as many of the effects of these drugs are not easily measured, or may not exist in the rodent, for example, awareness. In this study, we analytically examined both membrane and soluble protein fractions from human temporal lobe brain samples to allow eventual correlation of the anesthetic targets with endpoints observed in humans. We identify and quantitate halothane binding in about 60 detectable proteins. Functional classification of the identified membrane and soluble proteins identifies at least five functional groups. Network analyses do not provide evidence for a specific affected pathway, but rather implicate diverse networks and functions as potentially underlying halothane’s various actions.
Materials and Methods Human Cortex Membrane and Soluble Protein Preparation. This study was approved as an exemption protocol by the University of Pennsylvania Institutional Review Board. Brain tissues were obtained from epilepsy patients (n ) 3, all female) who underwent surgical removal of part of their temporal lobe cortex. Patients received general anesthesia for this procedure and were taking a variety of antiepileptic medications, but their identity, dosage, and duration were not known. Procedures of protein preparation were similar to our previously reported work in rat brain.7 Briefly, after excision, the tissue was cooled 10.1021/pr060311u CCC: $37.00
2007 American Chemical Society
Proteomic Analysis of Halothane Binding
on ice and the cortical layer visually identified and divided into ∼0.2 g pieces. These were rapidly frozen in liquid nitrogen and stored at -80 °C. Prior to labeling, tissue was thawed, homogenized in 0.32 M sucrose, 20 mM Tris-HCl (pH 7.5), 1 mM EDTA (Sigma-Aldrich, St. Louis, MO), 1 mM phenylmethylsulfonyl fluoride, and 1 µL/mL protease inhibitor mixture (P-8340, Sigma-Aldrich, St. Louis, MO), and then centrifuged at 1000g for 15 min to eliminate large debris. The supernatant was collected for photolabeling. Halothane Photoaffinity Labeling. Photolabeling was conducted as described previously.7 Briefly, the above supernatant samples were mixed with [14C]halothane (2-bromo-2-chloro1,1,1-[1-14C]trifluoroethane; specific activity, 55.4 mCi/mmol; Perkin-Elmer, Wellesley, MA) to produce a final concentration of 0.5 mM, with or without 5 mM nonradioactive halothane (Halocarbon Laboratories, River Edge, NJ) in 2-mL Teflonstoppered quartz cuvettes (5-mm path length) (Markson LabSales, Inc., Wayne, NJ) at 25 °C. Higher competing concentrations of halothane were not used due to limited solubility and UV absorption. The samples were exposed to 254-nm light from a low-pressure mercury (argon) pencil calibration lamp (Thermo Oriel, Stratford, CT) at a distance of ∼5 mm for 60 s with continuous stirring from enclosed micro stir bars. After labeling, the sample was centrifuged at 100 000g for 60 min. The supernatant containing soluble protein was collected and washed with 10 mM Tris-HCl (pH 7.5) by repeated filtration through 10 kDa cutoff centrifuge filters. The pellet containing membrane protein was washed with the same buffer by repeated suspension and sedimentation. Two-Dimensional Gel Electrophoresis. Protein concentrations were determined using a modified Bio-Rad protein assay.8 The washed pellets or supernatants were dissolved in sample buffer consisting of 7 M urea (Sigma-Aldrich, St. Louis, MO), 2 M thiourea (Sigma-Aldrich, St. Louis, MO), 4% CHAPS (BioRad, Hercules, CA), 2 mM tributylphosphine (Bio-Rad, Hercules, CA), and 0.2% carrier ampholytes (Bio-Rad, Hercules, CA). Approximately 150 µg of total protein was applied on immobilized pH 3-10 nonlinear gradient (IPG, Bio-Rad, Hercules, California) strips (7 cm) for isoelectric focusing. The IPG strips were rehydrated with samples for 16 h at 20 °C. Focusing proceeded from 0 to 350 V over 20 min, and then the voltage was gradually increased to 4000 V over 2 h and kept constant until 20 000 V-h was reached. Focused strips were either stored at -80 °C or used directly for SDS-PAGE. After running the second dimension on 12% polyacrylamide gels (Bio-Rad, Hercules, CA), proteins were electrophoretically transferred onto polyvinylidene fluoride (PVDF) membranes (Bio-Rad, Hercules, CA) with mini-Trans-Blot Cell (Bio-Rad, Hercules, CA) overnight at 4 °C and stained with Coomassie Brilliant Blue R-250 (SigmaAldrich, St. Louis, MO). The PVDF membranes were placed on X-ray film at 0 °C for 12 days. The PVDF membranes and autoradiogram films were scanned (GS-710 Scanner, Bio-Rad, Hercules, CA), processed, and quantified with Z3 software (Compugen, Richmond Hill, Ontario, Canada) to calculate the area and density of each spot as well as the molecular weights and isoelectric points. Three complete sets of data for both membrane and soluble proteins were collected and averaged. Protein Identification and Labeling Quantitation. Control gels (nonphotolabeled) were stained with Coomassie Blue and saved for spot excision and identification. Visual inspection of the autoradiograms (Compugen, Richmond Hill, Ontario, Canada) was used to select prominently labeled spots for identification (40 for membrane and 50 for soluble protein
research articles spots). Five random unlabeled spots, defined as those not detected by the Z3 software on the autoradiogram but clearly detected on the stained blot, were selected from both membrane and soluble protein gels. Selected spots were represented in labeled gels from all three patients. Spots were excised from the gel, digested using a standard trypsin in-gel protocol,9 and then analyzed via matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectroscopy10 using a Voyager 4700 Proteomics Analyzer (Applied Biosystems, Foster City, CA). Peptide peaks were searched against the National Center for Biotechnology Information (NCBI) database. Spots on stained PVDF and autoradiographs were quantified by calculating the product of area and contrast (optical density). The ratio of this product in the autoradiogram (a measure of 14 C incorporation) to that in the PVDF membrane (a measure of protein mass) provided a relative measure of labeling or binding. Multiplication by the molecular weight produced a relative measure of binding stoichiometry. By comparing these normalized ratios to labeled proteins of known halothane binding stoichiometry (from isothermal titration calorimetry or crystallography) and incorporating the molecular weight, we were able to generate an estimate of absolute binding stoichiometry, as previously described.7 Functional Classification by DAVID Database. DAVID2.1beta (database for annotation, visualization, and integrated discovery)11,12 was used to classify the detected halothane-binding targets by their annotated functions. DAVID uses grouping of species-specific gene/protein identifiers to agglomerate a diverse array of functional and sequence annotation from a variety of public genomic resources including NCBI, PIR, and Uniprot/Swiss-Prot. Briefly, the algorithm adopts kappa statistics to quantitatively measure the level of the agreement of how genes/proteins share the similar annotation terms13 and generate a gene-to-gene similarity matrix based on shared functional annotation using over 75 000 terms from 14 functional annotation sources. In the kappa statistic, a chancecorrected measure of agreement between two sets of categorized data is calculated. A value of kappa ) 1 represents a perfect agreement, whereas there is no agreement if kappa ) 0. Further, the algorithm also uses fuzzy heuristic partitioning to classify highly related genes into functionally related groups. With the use of this approach, an object (gene/protein) can participate in more than one cluster, which better reflects biology in that a given gene may be associated with more than one functional group of genes. The algorithm also allows automatic determination of the optimal numbers of clusters (K) and exclusion of members (genes/proteins) that have weak relationships to other members. Different levels of similarity stringencies (from lowest to highest) can be set to cluster membership of each group. Ingenuity Pathway Analysis (IPA). The data set containing the identifiers (GI number) and binding intensities of the proteins was uploaded as a tab-delimited text file into the IPA software (http://www.ingenuity.com).14,15 This Web-based program uses the Ingenuity Pathways Knowledge Base (IPKB), a database with large amounts of individually modeled relationships between proteins, to construct significant biological networks and pathways. The submitted proteins, called “focus proteins”, are used as starting points for generating biological networks, which rely on IPKB for interactions with all the other proteins stored in the IPKB. A set of networks with a maximum size of 35 proteins is generated, and a p-value for each is calculated according to the fit of our set of labeled proteins. Journal of Proteome Research • Vol. 6, No. 2, 2007 583
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Figure 1. Human brain membrane and soluble proteins separated by 2D gel electrophoresis. Coomassie-stained PVDF membranes (A and C) and corresponding autoradiograms (B and D) of the membrane (A and B) and soluble (C and D) protein fractions from human temporal lobe cortex. The spots identified are numbered and correspond to those in Figure 2 and in the tables.
The p-value compares the number of focus proteins that participate in a given network or pathway, to the total number of occurrences of the same proteins in all IPKB networks or pathways. The score of each network (given as the negative log) indicates the likelihood of the focus proteins occupying a network due to random chance. Therefore, a score of 2 has a 1% chance of being generated by chance alone. Importantly, this analysis allows labeling intensity to be included, since the affinity and/or stoichiometry of binding enhances the likelihood that the protein’s function is altered.
Results Protein Separation and Visualization. The membrane and soluble protein spots were visualized with good resolution on PVDF membranes with Coomassie Blue (Figure 1A for membrane proteins, Figure 1C for soluble proteins). The resolution was somewhat reduced with protein samples photolabeled with [14C]halothane and UV light, but no significant differences in 584
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spot position were observed. The 12-day autoradiographs of the PVDF membrane showed selective labeling of the resolved proteins (Figure 1B for membrane proteins, Figure 1D for soluble proteins). There were 300 membrane proteins detected on the PVDF membranes, and 100 photolabeled spots detected on the autoradiographs. Cold halothane significantly reduced labeling (>50%) in 75 of the 100 spots. On the soluble protein blots, 410 spots were detected, and 130 spots were noted on the associated autoradiographs, of which 98 were significantly inhibited by cold halothane. Among the detectable protein spots, 40 membrane and 50 soluble proteins, including 5 unlabeled control spots, were visually selected and submitted for mass spectroscopic identification Mass Spectroscopic Identification. Of the 40 membrane protein spots submitted for MALDI-TOF identification, 26 spots were identified with confidence (Table 1A), and in the soluble protein set, 34 out of 50 spots were identified with confidence (Table 1B). The identification of these spots allowed the gels
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Proteomic Analysis of Halothane Binding Table 1. Halothane-Labeled Spot Identification in Human Brain Membrane and Soluble Proteinsa spot no.
NCBI protein ID
1 2 3 4 5 6 9 10 11
gi|1942682|pdb|1GBU|B gi|3660145|pdb|1BUW| gi|4758038|ref|NP_004246.1 gi|4503057|ref|NP_001876.1| gi|5803135|ref|NP_006852.1| gi|5453559|ref|NP_006347.1| gi|33872678|gb|AAH03623.2| gi|33872678|gb|AAH03623.2| gi|5803225|ref|NP_006752.1|
12 15
gi|1066765|gb|AAA88054.1| gi|129070|sp|P11177|ODPB|
16 17 18 19 21 24
gi|386750|gb|AAA52584.1| gi|125294|sp|P12277|KCRB gi|4503979|ref|NP_002046.1| gi|14389309|ref|NP_116093.1| gi|4507879|ref|NP_003365.1| gi|4503377|ref|NP_001377.1|
25 26 28 29 *31 *32
gi|1346343|sp|P04264|K2C1| gi|1346343|sp|P04264|K2C1| gi|16507237|ref|NP_005338.1| gi|119360|sp|P14625| gi|5174743|ref|NP_005994.1| gi|4758788|ref|NP_004542.1|
*33 *37 38
gi|21361091|ref|NP_004172.2| gi|15680208|gb|AAH14455.1| gi|4757810|ref|NP_004037.1|
M1
gi|40254816|ref|NP_005339.2
1 2 3 4 5
gi|3660145|pdb|1BUW| gi|1942682|pdb|1GBU|B gi|13195586|gb|AAK15770.1| gi|7669492|ref|NP_002037.2| gi|4505621|ref|NP_002558.1|
8 9
gi|4503057|ref|NP_001876.1| gi|4505621|ref|NP_002558.1|
11 12 13 14 15 18 19 20 21 22 23 24 26 27 28
gi|15824412|gb|AAL09330.1| gi|4503571|ref|NP_001419.1| gi|4503571|ref|NP_001419.1| gi|4503571|ref|NP_001419.1| gi|4505701|ref|NP_003672.1| gi|7513433|pir||T08755| gi|4557321|ref|NP_000030.1| gi|4505753|ref|NP_002620.1| gi|17389815|gb|AAH17917.1| gi|17389815|gb|AAH17917.1| gi|4505763|ref|NP_000282.1| gi|28614|emb|CAA30979.1| gi|4885281|ref|NP_005262.1| gi|20072188|gb|AAH26196.1| gi|4503377|ref|NP_001377.1|
29 30 32 33
gi|5803011|ref|NP_001966.1| gi|180570|gb|AAC31758.1| gi|33872678|gb|AAH03623.2| gi|5803225|ref|NP_006752.1|
34 36 39 41
gi|4507729|ref|NP_001060.1| gi|4185720|gb|AAD09172.1| gi|5031635|ref|NP_005498.1| gi|5174539|ref|NP_005908.1|
description
(A) Human Brain Membrane Proteins Chain B, Human Hemoglobin Chain B, Human Hemoglobin A Cytochrome c oxidase subunit Va precursor; mitochondrial precursor Crystallin alpha B; heat-shock 20 kDa like-protein RAB35 member RAS oncogene family ATP synthase H+ transporting mitochondrial F0 complex subunit d YWHAZ protein YWHAZ protein Tyrosine 3/tryptophan 5-monooxygenase activation protein epsilon polypeptide; 14-3-3 epsilon; protein kinase C inhibitor protein-1 Beta-globin Pyruvate dehydrogenase E1 component beta subunit mitochondrial precursor (PDHE1-B) Guanine nucleotide-binding protein Creatine kinase, B chain (B-CK) Glial fibrillary acidic protein Tubulin alpha 6 Voltage-dependent anion channel 1 Dihydropyrimidinase-like 2; collapsin response mediator protein hCRMP-2 Keratin type II cytoskeletal 1 Keratin type II cytoskeletal 1 Heat shock 70 kDa protein 5 (GRP 78 kDa) Endoplasmin precursor (GRP94) (Tumor rejection antigen 1) Ubiquinol-cytochrome c reductase Rieske iron-sulfur polypeptide 1 NADH dehydrogenase (ubiquinone) Fe-S protein 3 30 kDa (NADHcoenzyme Q reductase) Ubiquitin carboxyl-terminal esterase L1 (ubiquitin thiolesterase); NEDD5 protein ATP synthase H+ transporting mitochondrial F1 complex alpha subunit isoform 1 cardiac Heat shock 90kDa protein 1, alpha (B) Human Brain Soluble Proteins Chain B, Human Hemoglobin A Chain B, Human Hemoglobin Hemoglobin alpha 1 globin chain Glyceraldehyde-3-phosphate dehydrogenase Prostatic binding protein; phosphatidylethanolamine binding protein; Raf kinase inhibitor protein Crystallin alpha B; heat-shock 20 kDa like-protein Prostatic binding protein; phosphatidylethanolamine binding protein; Raf kinase inhibitor protein Neuronal protein 22 Enolase 1; phosphopyruvate hydratase Enolase 1; phosphopyruvate hydratase Enolase 1; phosphopyruvate hydratase Pyridoxal kinase Yes-associated protein homologue DKFZp586I1419.1 Apolipoprotein A-I precursor Phosphoglycerate mutase 1 (brain) Triosephosphate isomerase 1 Triosephosphate isomerase 1 Phosphoglycerate kinase 1 Aldolase A Glutamate dehydrogenase 1 Aconitase 2 Dihydropyrimidinase-like 2; collapsin response mediator protein hCRMP-2 Enolase 2 (neuronal) Creatine kinase YWHAZ protein Tyrosine 3/tryptophan 5-monooxygenase activation protein, epsilon polypeptide; 14-3-3 epsilon; protein kinase C inhibitor protein-1 Tubulin beta polypeptide Ubiquitin carboxy-terminal hydrolase L1 Cofilin 1 (non-muscle) Cytosolic malate dehydrogenase
Mr (kDa)
pI
cover.
B.I.
16 16 17 20 23 18 32 32 29
6.8 6.8 6.3 6.8 8.5 5.2 4.9 4.9 4.6
38 19 15 53 45 70 43 43 50
1.2 1.0 7.2 0.7 1.7 2.6 2.8 3.0 2.0
16 39
6.7 6.2
68 29
1.7 2.0
40 43 50 50 31 62
5.3 5.3 5.4 5.0 8.6 6.0
41 36 71 23 76 46
5.4 5.4 12.0 8.7 1.8 7.0
66 66 72 92 30 30
8.2 8.2 5.1 4.8 8.6 7.0
32 26 22 15 32 55
2.8 2.3 7.3 7.0 0 0
25 41 60
5.3 6.1 9.2
34 44 49
0 0 1.3
85
4.9
-
6.9
16 16 107 36 21
6.8 6.8 7.1 8.6 7.0
19 38 69 21 54
NAb 1.4 1.6 1.4 1.3
20 21
6.8 7.0
57 38
3.6 1.8
22 47 47 47 35 28 31 29 27 27 45 39 61 86 62
6.8 7.0 7.0 7.0 5.7 4.9 5.6 6.7 6.4 6.4 8.3 8.3 7.7 7.6 6.0
56 43 51 45 45 10 73 44 45 32 44 36 41 31 52
2.2 1.1 1.1 1.7 2.8 1.7 5.6 1.8 1.3 1.2 2.1 2.7 5.1 2.9 8.7
47 43 32 29
4.9 5.3 4.9 4.6
58 48 65 18
8.0 6.0 5.6 3.0
50 23 18 36
4.8 5.3 8.2 6.9
41 30 17 32
12.1 1.0 1.0 1.0
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Table 1 (Continued) spot no.
NCBI protein ID
description
Mr (kDa)
pI
cover.
B.I.
*42 46 47 49 M1
gi|6912328|ref|NP_036269.1| gi|13129150|ref|NP_005339.1| gi|5729877|ref|NP_006588.1| gi|5729877|ref|NP_006588.2| gi|113576|sp|P02768|
(B) Human Brain Soluble Proteins DDAH1 protein Heat shock 90 kDa protein 1 alpha Heat shock 70 kDa protein 8 isoform 1 Peroxiredoxin 1; thioredoxin-dependent peroxide reductase 2 Serum albumin precursor
31 85 71 22 69
5.5 4.9 5.4 8.3 5.9
35 34 53 44 -
0 7.2 6.3 0.6 6.3
a Identified spot information: individual proteins are marked with the letter of the corresponding spot from the two-dimensional gels in Figure 1 and are designated with their NCBI accession numbers. The Mr and pI value and the sequence coverage (cover.) are reported directly from the database. *, represents no labeling by radioactive halothane. Spot number with initial M represents identification by published brain map. B.I., binding intensity. b NA, no mean value was reported due to missing replicates.
Figure 3. Protein functions identified by DAVID functional classification (see text).
Figure 2. Relative spot halothane-labeling intensities in membrane and soluble proteins. Spot ratios (relative labeling intensity; see text) for each spot numbered in Figure 1. A ratio of greater than about 2 corresponds to a binding stoichiometry of 1:1 at 0.5 mM halothane. Error bars denote SEM, n ) 3.
to be calibrated so that additional photolabeled spots could be identified based on previously published human brain 2D maps.16,17 For example, membrane protein spot no. M1 and soluble protein spot no. M1 were unambiguously identified by the brain map. Further, among the 26 identified membrane proteins, 22 proteins were photolabeled and 4 unlabeled. Thirty-three soluble proteins were photolabeled and 1 unlabeled in the 34 identified soluble proteins. Detailed information about the identified proteins is listed in Table 1. Although a single spot usually represents a single protein or peptide, some spots were identified as different subunits of the same protein complex or the same protein or subunit at different pI values, which are grouped in Table 1. As expected, a few identified spots were found in both membrane and soluble protein set (e.g., crystallin and YWHAZ proteins). Labeling Quantitation. The relative labeling intensity (spot ratio) is calculated as the ratio of autoradiograph spot volume to stain volume (where volume ) area of the spot × its optical density) (Figure 2). This ratio is a reflection of the binding stoichiometry, which could be further calibrated against proteins of known anesthetic binding stoichiometry from crystal structures or calorimetry. Thus, human serum albumin has a halothane-binding affinity of ∼1 mM and a stoichiometry of ∼7:1 (halothane/albumin).18-20 The halothane/hemoglobin af586
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finity is similar, but the stoichiometry is approximately 1:1 (subunit) depending on the halothane concentration and the experimental approach. Thus, occupancy of one site per protein under our labeling conditions should produce a spot ratio range of approximately 2-4. These estimates suggest that about half of the labeled proteins have one or more halothane molecules bound at 0.5 mM halothane. Smaller spot ratios are interpreted as partial occupancy of presumably lower affinity binding sites. Similarly, it is also possible that ratios higher than 4 indicate partial occupancy of many low-affinity sites. The single concentration of halothane used in this study does not allow discrimination between stoichiometry and affinity, although the displacement of labeling in most identified proteins by 5 mM nonradioactive halothane indicates limited capacity and therefore a degree of specificity. These estimates must be viewed as tentative because of the nonequilibrium nature of these brief photolabeling experiments. Functional Classification and Network Analysis. To include the possible interactions between membrane and soluble proteins, the two groups were combined to generate a list of 44 brain proteins out of the labeled group of 23 membrane and 34 soluble proteins. Five proteins appear in both the membrane and soluble groups, and some identified proteins are redundant (e.g., spots 12-14 from the soluble group). The GI numbers of our protein list were uploaded as tab-delimited text files into the Web-based DAVID database. There were 40 proteins identified by the functional classification of DAVID. The program was run at varying degrees of similarity stringency, and thereby generated five functional groups (Figure 3) from highest to lowest stringency (Table 2). The functional term for
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Proteomic Analysis of Halothane Binding Table 2. DAVID Functional Classification on Both Membrane and Soluble Proteinsa group
GI number
description
solubility
stringency
network (IPKB)
1
7669492 5803011 4503571 4505753 20072188 4185720 28614 4505763 4885281 17389815 129070 5174539 5729877 119360 4503057 16507237 40254816 386750 4507729 5729877 5803135 14389309 4757810 4758038 5453559 33872678 4505701 125294 180570 4505621
glyceraldehyde-3-phosphate dehydrogenase enolase 2 (gamma, neuronal) enolase 1, (alpha) phosphoglycerate mutase 1 (brain) aconitase 2, mitochondrial ubiquitin carboxyl-terminal esterase L1 (ubiquitin thiolesterase) aldolase A, fructose-bisphosphate phosphoglycerate kinase 1 glutamate dehydrogenase pseudogene 5 triosephosphate isomerase 1 pyruvate dehydrogenase (lipoamide) beta malate dehydrogenase 1, NAD (soluble) heat shock 70 kDa protein 8 Endoplasmin precursor (tumor rejection antigen 1) Crystallin, alpha B heat shock 70kDa protein 5 (glucose-regulated protein, 78kDa) heat shock 90 kDa protein 1, alpha guanine nucleotide binding protein (G protein), alpha activating activity polypeptide O tubulin, beta 2 heat shock 70 kDa protein 8 RAB35, member RAS oncogene family tubulin alpha 6 ATP synthase, H+ transporting, mitochondrial F1 complex, alpha subunit cytochrome c oxidase subunit Va ATP synthase, H+ transporting, mitochondrial F0 complex, subunit d YWHAZ protein pyridoxal (pyridoxine, vitamin B6) kinase creatine kinase, brain creatine kinase, brain prostatic binding protein
S S S S S S S S S S S S S M S/M M M M S S M M M M M S/M S M S S
Highest Highest Highest Highest Low Lowest Highest Highest Lowest Highest High Low Medium Medium Lowest Medium Medium Lowest Low Lowest Low Low Low Low Low Lowest Lowest Lowest Lowest Lowest
1,3 2 2 1 1 1 3 3 1 3 3 1 2 3 3 2 2 1 2 2 2 3 2 1 3 2 2 3
2
3
4 5
a Of the 44 combined membrane and soluble proteins, protein classification based on annotation by DAVID2.1beta five functional groups (Figure 3) of proteins with varied similarity stringency were revealed. The membership of each protein in the IPKB-network is also indicated.
each group was selected using the most significantly represented terminology for the function of all member molecules using available annotation sources. Thus, the 12 enzymes in Group 1 are involved in carbohydrate metabolism, with 7 having the highest stringency. Group 2 includes 5 proteins contributing to protein folding and stress responses with 4 in medium stringency. Proteins in groups 3, 4, or 5 have less stringency (low to lowest), including 5 proteins in nucleoside triphosphatase activity, 3 in oxidative phosphorylation, and 5 with dimer/kinase activity. For the network analysis, the combined 44 proteins with the associated labeling intensity values were loaded into IPA, and 38 proteins were subsequently recognized by the IPKB database. Three independent networks were reported with significant p-values (negative log of p-value > 2) (Table 3). Network I contains 13 of the labeled proteins in the area of cell growth and proliferation (Figure 4). Network II has 13 proteins identified as contributing to cell cycle and death (Figure 5), and the 12 proteins in network III are involved in cell-cell signaling and interaction (Figure 6).
Discussion Previous work has established that halothane photolabeling is a reliable reflection of binding, both qualitatively and quantitatively.21 Therefore, this study provides direct evidence for specific interactions between the inhaled anesthetic (halothane) and multiple human brain proteins. If the ratio of labeled to unlabeled proteins observed for these abundant proteins holds across the proteome, these results suggest that about a quarter of the proteome binds halothane specifically. Not unexpectedly, this fraction is slightly lower than the 36%
estimate resulting from an analysis of internal protein cavities in a nonredundant set of ∼6700 protein structures in the PDB.22 Clearly, our knowledge of the structural determinants of anesthetic binding is immature. Quantitation of the photolabeling allows rough estimates of affinity and stoichiometry of binding, and these are generally consistent with sufficient target occupancy to alter function during clinical anesthesia in many identified proteins. The presence of multiple binding targets might indicate that the mechanism of anesthesia relies on a distributed alteration in activity, or it could indicate that smaller subsets of targets are associated with each of the many side effects that these drugs exhibit (emesis, hypotension, delirium, and weakness). It is also possible that specific binding can occur with no change in target function, although good examples of this are lacking in the pharmacologic literature. In our previous work in the rat brain, using similar approaches, we found evidence for specific halothane binding to multiple membrane proteins.7 Membrane proteins have been the favored potential anesthetic targets because of their hydrophobic nature, coupled with the well-known correlation between potency and hydrophobicity in the wide array of anesthetic drugs (Overton-Meyer rule). In this study, we have also found evidence for anesthetic binding to multiple human membrane proteins, with some overlap to those found in the rat (Figure 7). Interestingly, the overlapping proteins are mitochondrial and stress related proteins, suggesting a role in the “anesthetic” features of halothane (hypnosis and immobility). The differences between the two species might underlie different actions as implied in the introduction, or alternatively, it could be partly due to the differences in spot selection criteria in the two experiments, or spot identification confidence by Journal of Proteome Research • Vol. 6, No. 2, 2007 587
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Table 3. Biological Networks Generated by Ingenuity Pathways Analysis (IPA)a
a (A) Network analysis by the IPA generates three distinct biological networks with statistical significance; (B) shapes of the symbols for Figures 4-6; (C) edge information for Figures 4-6. Panels B and C were modified according to the symbol annotation from ingenuity online help (www.ingenuity.com). In panel C, “acts on” and “inhibits” may also include a binding event.
mass spectroscopy. Surprisingly, a large number of photolabeled soluble proteins were found as well. This does not defy the Overton-Meyer rule, since the interior of soluble proteins is as hydrophobic as that of membrane proteins.23 It also raises the possibility for mechanistic contributions from this large group of generally abundant proteins as well. To begin to assemble these revealed binding targets, we employed two proteomic approaches (see Figures 3-6 and Table 3). In DAVID, proteins with similar function were clustered together based on their annotation in the database. However, because this contains little information on interactions between molecules, either direct or indirect, and cannot incorporate labeling intensity, we also used ingenuity pathway analysis (IPA). IPA allows potential interactions between these targets and related molecules to be mapped out in networks using the pre-existing IPKB database. Metabolic Pathways. Of the combined 44 unique halothanelabeled proteins, 12 soluble proteins are enzymes that are associated with glycolysis and gluconeogenesis, and three, 588
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located on mitochondria membrane, are involved in oxidative phosphorylation (Table 2). This apparent target preference is consistent with the known effect of the inhaled anesthetics on cellular metabolism.24,25 Further, the mitochondrion has recently received renewed attention as a potential anesthetic target.26,27 Although it is not yet clear how inhaled anesthetics affect mitochondrial function, studies have suggested that selective enzymes (e.g., complex I) or ion channel targets (ATP sensitive potassium channel) in mitochondria play a role in organism sensitivity to the sedating effects of anesthetics27 or in preconditioning against ischemic injury,28 respectively. Protein Folding and Stress Response Pathways. Several members of the heat shock protein family, involved in the prevention of protein unfolding or misfolding were labeled by halothane (Figure 3 and Table 2). This includes heat shock 70 kDa protein 8, endoplasmin precursor (a.k.a. tumor rejection antigen-1), crystallin-alpha B, heat shock 70 kDa protein 5 (glucose-regulated protein, 78 kDa), and heat shock 90 kDa protein 1-alpha. Many of these proteins are significantly
Proteomic Analysis of Halothane Binding
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Table 4. Abbreviations in Ingenuity Pathway Analysis (IPA) Network
induced during stressful events like heat shock, hypoxia, or ischemia.29,30 In anesthetic preconditioning (APC), heat shock protein 70 precursor and heat shock protein 90 mRNA are apparently downregulated,31 suggesting that anesthetics could increase vulnerability to some stress pathways. Whether this downregulation is mediated through the binding event reported here awaits further study. Regardless, inhibition of the heat
shock response may result in the production of misfolded proteins, increasing the possibility of forming nonphysiological oligomers or aggregates, or of triggering apoptosis.32 Cell Signaling Pathway. Molecules involved in cell signaling have been regarded as likely anesthetic targets in recent work.33-35 A prominent group of such proteins are the Gprotein-coupled receptors (GPCR),36-38 that serve as neuroJournal of Proteome Research • Vol. 6, No. 2, 2007 589
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Figure 4. Ingenuity pathway analysis (IPA) biological network I: cell growth and proliferation (see text). Proteins are represented as nodes, and the biological relationship between two nodes is represented as an edge (line). All edges are supported by at least 1 reference stored in the IPKB. The intensity of the node color indicates the labeling intensity. Nodes are displayed using various shapes that represent the functional class of the proteins (see Table 3).
Pan et al.
Figure 6. IPA network III: cell-cell signaling and interaction (see text and Table 3).
Figure 7. Overlap of photolabeled rat (7) and human membrane proteins. The five overlapping proteins between the two species have more than 75% sequence identity by NCBI protein Basic Local Alignment Search Tool (BLAST): (1) subunit d of mitochondrial H-ATP synthase (77%); (2) cytochrome C oxidase, subunit Va (89%); (3) voltage-dependent anion channel 1 (98%); (4) heat shock 70 kDa protein 5 (99%); (5) endoplasmin precursor (98%).
Figure 5. IPA network II: cell cycle and death (see text and Table 3).
transmitter receptors and modulate the function of ion channels and various second messenger systems. Previously published work shows unambiguously that inhaled anesthetics bind to39 and alter the function of various G-protein-coupled receptors.34,35,40-42 Unfortunately, GPCRs themselves are typically of insufficient abundance in whole brain to be detected on 2D 590
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gels. However, we find labeling of related signaling molecules, such as guanine nucleotide binding protein R polypeptide (GNAO), RAB protein (the largest subfamily of RAS), YWHAZ protein (a.k.a. 14-3-3 protein or protein kinase C inhibitor protein 1), and prostatic binding protein (PBP, a.k.a. Raf kinase inhibitor protein) (Table 2). Having intrinsic nucleotide hydrolysis activity, the labeled proteins in group 2, such as GNAO, RAB proteins, R, β-tubulin, and heat shock protein 70-1, all have close functional resemblance to G proteins.43-45 Altered related bioactivities might include microtubule nucleation,46 protein folding and aggregation, and neurotransmitter synthesis and transport processes.45,47,48 Further, detection of halothanelabeled YWHAZ protein and PBP could also indicate involvement of protein kinase C and Ras/Raf/MEK/ERK pathway in some aspects of anesthetic action.49-53 Network Analysis. Besides focusing on our binding targets by their functional annotation, we also looked for interactions between these proteins and other molecules using IPA. We identified 3 potential networks, including cell growth and proliferation, cell cycle and cell death, and cell-cell signaling and interaction (Figures 4-6). In each network, our binding targets appear either as regulators or targets of related mol-
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Proteomic Analysis of Halothane Binding
ecules and are color-coded by their binding intensities. This approach not only allows us to understand the role of the revealed proteins within a network, but also helps to identify other candidate targets, with the most or unique interactions with our labeled members. This is a complementary mining approach because these other proteins may be either unlabeled by halothane or undetected on 2D gels. Thus, in network I (Figure 4), 13 proteins are involved and their functional theme is cell growth and proliferation. The key molecules that interact most with our labeled proteins include growth hormone (GH) and transcription factor, peroxisomal proliferation agonist receptor gamma (PPARG).54 Such targets may contribute more to well-known effects of inhaled anesthetics on cell metabolism than hypnosis. In network II (Figure 5), the essential components between our labeled proteins include TGFβ1, Bcl-2, and IL-6. The functional consequence of this network relates to cell cycle, growth, and survival.55-57 At the transcriptional level, inhaled anesthetics downregulate the heat shock protein family (e.g., hsp 70 and 90) in isolated heart tissue31 and alter the balance of pro-apoptotic and anti-apoptotic genes, leading to cytotoxicity.56 Such actions could underlie both anesthetic preconditioning and anesthesia neurotoxicity, depending on the magnitude of effect. In network III (Figure 6), more diverse functions are implicated. Among these, YWHAZ protein (a.k.a. 14-3-3 protein) mediates the phosphorylation of Raf-1 and, thereby, modulates the activity of PKC.51,58 Since accumulating evidence has indicated the involvement of protein kinase C in anesthetic action,34,49,50 an interaction with YWHAZ protein may provide another point for modulation of this important signaling pathway. Functional Representation and Protein Abundance. Abundance of members in some pathways may bias representation in our labeled group. To test for preferential representation, the ratio of labeled proteins to all proteins in each of the three pathways (carbohydrate metabolism, protein folding, and oxidative phosphorylation) were compared to the ratio of all proteins in that pathway to the total number of proteins.59 These ratios are not significantly different; thus, we cannot rule out the null hypothesis that the prevalence of detectable proteins from a given pathway is controlling the labeling pattern, rather than binding specificity of the pathway, per se. This cannot be used to rule out involvement of a specific pathway in anesthetic action, as the ultimate effect on a pathway function may not correlate with the number of member proteins affected, but rather position within the pathway. In addition, equal attention should be devoted to those less well-represented pathways (because of low abundance), yet with significant biological importance (e.g., GPCRs). Tissue Sample Limitations. The limitations of using human operative tissue samples bear mentioning. Although these samples were freshly obtained and optimally handled, they came from anesthetized patients on a variety of other drugs and contained an epileptic focus of unknown size. Although probably more representative of normal functioning brain tissue than post-mortem or tumor samples, this could have altered the representation of anesthetic binding in some targets, through competitive binding interactions or altered expression. Nevertheless, given the difficulty of obtaining fresh normal human brain, this is probably the optimal source for this work.
Conclusion Photolabeling and 2D gel electrophoresis allowed us to identify a group of halothane binding proteins in human cortex. Approximately 24% of detectable proteins specifically bind halothane, and about 70% of these were identified with mass spectroscopy. Functional classification of these proteins suggested effects on carbohydrate metabolism and protein folding, while network analysis suggested involvement in cell growth and proliferation, cell cycle, cell death, and cell-cell signaling. These results provide a direct protein binding basis for many of the known effects of these widely used drugs.
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