Comparison of Proteins Expressed on
Secretory Vesicle Membranes and Plasma
Membranes of Human Neutrophils
This information is current as
of June 15, 2017.
Silvia M. Uriarte, David W. Powell, Gregory C. Luerman,
Michael L. Merchant, Timothy D. Cummins, Neelakshi R.
Jog, Richard A. Ward and Kenneth R. McLeish
J Immunol 2008; 180:5575-5581; ;
doi: 10.4049/jimmunol.180.8.5575
http://www.jimmunol.org/content/180/8/5575
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Supplementary
Material
The Journal of Immunology
Comparison of Proteins Expressed on Secretory Vesicle
Membranes and Plasma Membranes of Human Neutrophils1
Silvia M. Uriarte,* David W. Powell,*† Gregory C. Luerman,† Michael L. Merchant,*
Timothy D. Cummins,* Neelakshi R. Jog,‡ Richard A. Ward,* and Kenneth R. McLeish2*†§
C
irculating neutrophils are capable of undergoing a series
of phenotypic changes that result in their transition from
cells that are poorly responsive to proinflammatory stimuli to become the primary effector cells of innate immunity. These
phenotypic changes involve the incorporation of proteins from the
membranes of intracellular storage granules into the plasma membrane and the release of proteins stored in granule matrix through
regulated exocytosis. Granule exocytosis contributes to enhanced
neutrophil tethering and adhesion to vascular endothelial cells at a
site of inflammation; enhanced migration across blood vessel
walls; chemotaxis to a site of microbial invasion; phagocytosis of
invading organisms; and microbicidal activity through a combination of enzymatic degradation, reactive oxygen species generation,
and release of microbicidal peptides into phagosomes. Neutrophils
contain a heterologous group of storage granules that have been
classified into four subsets based on density and composition:
azurophil (primary) granules, specific (secondary) granules, gelatinase (tertiary) granules, and secretory vesicles (1). These granule
subsets undergo hierarchical stimulated exocytosis, with secretory
vesicles the most easily and completely mobilized (2– 4). Gelatinase, specific, and azurophil granules are formed from the trans-
*Department of Medicine, †Department of Biochemistry and Molecular Biology, and
‡
Department of Microbiology and Immunology, University of Louisville, Louisville,
KY 40202; and §Veterans Affairs Medical Center, Louisville, KY 40206
Received for publication October 29, 2007. Accepted for publication February
7, 2008.
The costs of publication of this article were defrayed in part by the payment of page
charges. This article must therefore be hereby marked advertisement in accordance
with 18 U.S.C. Section 1734 solely to indicate this fact.
1
This work was supported by a Merit Review Grant from the Department of Veterans
Affairs (to K.R.M.), National Institutes of Health Grants DK62389 (to R.A.W. and
K.R.M.) and DK176743 (to D.W.P.), and the Office of Science Financial Assistance
Program, Department of Energy (to D.W.P.).
2
Address correspondence and reprint requests to Dr. Kenneth R. McLeish, Baxter I
Research Building, University of Louisville, 570 South Preston Street, Louisville, KY
40202. E-mail address: [email protected]
www.jimmunol.org
Golgi network during neutrophil maturation (1). The intragranule
constituents of secretory vesicles include plasma proteins, resulting in the hypothesis that secretory vesicles are formed by endocytosis and that functional changes from their exocytosis are due
entirely to incorporation of new molecules into the plasma membrane (1, 5). Thus, to understand the changes in neutrophil functional capability induced by secretory vesicle exocytosis, a comprehensive catalog of membrane proteins is required.
Proteomic techniques, which include methods for protein extraction and separation, protein identification and characterization,
and database analysis, provide an unbiased approach to identifying
proteins expressed in subcellular compartments (6 –9). We recently published a comprehensive proteomic analysis of neutrophil
gelatinase, specific, and azurophil granules (10). Using protein
separation by two-dimensional gel electrophoresis and two-dimensional HPLC coupled with MALDI-TOF-MS3 and ESI-MS/MS,
286 proteins were identified on one or more granule subsets, many
of which had not been found previously on neutrophil granules.
The current study was designed to use similar proteomic technologies to provide a more complete identification of secretory vesicle
membrane proteins and to compare those proteins with the proteins
expressed on neutrophil plasma membranes. The ability to extract
and solubilize membrane proteins is a major limitation to all proteomic approaches. To overcome this limitation, proteins were
extracted from membranes using a recently described methanol
extraction procedure, followed by two-dimensional HPLC and
ESI-MS/MS (11). With this approach, we identified a number of
membrane spanning and membrane associated proteins and uncovered significant differences between secretory vesicle-enriched and
plasma membrane-enriched proteomes.
3
Abbreviations used in this paper: MS, mass spectrometry; SCX, strong cation exchange; RP, reversed-phase; PAF, protein abundance factor; NCBI, National Center
for Biotechnology Information; IPKB, Ingenuity Pathways Knowledge Base;
SNARE, soluble NSF attachment receptor.
Downloaded from http://www.jimmunol.org/ by guest on June 15, 2017
Secretory vesicles are neutrophil intracellular storage granules formed by endocytosis. Understanding the functional consequences
of secretory vesicle exocytosis requires knowledge of their membrane proteins. The current study was designed to use proteomic
technologies to develop a more complete catalog of secretory vesicle membrane proteins and to compare the proteomes of secretory
vesicle and plasma membranes. A total of 1118 proteins were identified, 573 (51%) were present only in plasma membraneenriched fractions, 418 (37%) only in secretory vesicle-enriched membrane fractions, and 127 (11%) in both fractions. Gene
Ontology categorized 373 of these proteins as integral membrane proteins. Proteins typically associated with other intracellular
organelles, including nuclei, mitochondria, and ribosomes, were identified in both membrane fractions. Ingenuity Pathway Knowledge Base analysis determined that the majority of canonical and functional pathways were significantly associated with proteins
from both plasma membrane-enriched and secretory vesicle-enriched fractions. There were, however, some canonical signaling
pathways that involved proteins only from plasma membranes or secretory vesicles. In conclusion, a number of proteins were
identified that may elucidate mechanisms and functional consequences of secretory vesicle exocytosis. The small number of
common proteins suggests that the hypothesis that secretory vesicles are formed from plasma membranes by endocytosis requires
more critical evaluation. The Journal of Immunology, 2008, 180: 5575–5581.
5576
Materials and Methods
Neutrophil isolation
Neutrophils were isolated from healthy donors using plasma-Percoll gradients
as described by Haslett et al. (12). Trypan blue staining revealed that at least
97% of cells were neutrophils with ⬎95% viability. After isolation, neutrophils were suspended in Krebs-Ringer phosphate buffer (pH 7.2) at 4 ⫻ 107
cells/ml and treated with 5 mM diisopropyl fluorophosphate for 10 min on ice
to inhibit proteases (13). Extensive evaluation using respiratory burst activity
and granule exocytosis indicates that this isolation technique does not prime
neutrophils. The Human Studies Committee of the University of Louisville
approved the use of human donors.
Plasma membrane and secretory vesicle membrane enrichment
Protein extraction from plasma membrane and secretory vesicle
membranes
Fractions obtained from Percoll gradients were analyzed for alkaline phosphatase in the absence (nonlatent) or presence (latent) of Triton X-100
using p-nitrophenylphosphate as substrate. Briefly, 100:l aliquots of each
fraction were added to wells of a 96 flat-well plate with or without 0.3%
Triton X-100. Reactions were started by adding 200 ␮l of reaction buffer
containing 5 mM p-nitrophenylphosphate in 100 mM 2-amino-2-methyl1-propanol (pH 10.0). Following incubation for 30 min at 37°C, reactions
were stopped by addition of 150 ␮l of 0.04 N NaOH and absorbance was
read at 405 nm in a microplate reader. Fractions containing nonlatent, but
not latent, alkaline phosphatase were pooled and analyzed as plasma membrane-enriched. Fractions containing latent alkaline phosphatase were
pooled and analyzed as secretory vesicle-enriched membrane. Percoll was
removed from membranes by ultracentrifugation at 100,000 ⫻ g for 90
min. Membrane pellets were resuspended in 50 mM ammonium bicarbonate,
washed by centrifugation at 100,000 ⫻ g, then resuspended in 60% methanol
in 100 mM ammonium bicarbonate to extract membrane proteins (11). Proteins were digested by incubation with 3 ␮g each of trypsin and chymotrypsin
at 37°C overnight. Following centrifugation at 100,000 ⫻ g for 20 min at 4°C,
the supernatant was removed for peptide analysis. Peptides were lyophilized
and prepared for mass spectrometry analysis using a desalting trap method.
Briefly, peptides were resuspended in a 100 ␮l of 5% acetonitrile and 0.05%
formic acid and applied to a peptide microtrap (Michrom BioResources) equilibrated with 1 ml of the same buffer. The trap was then washed twice with
100 ␮l of resuspension buffer and peptides eluted with 100 ␮l of 95% acetonitrile, 0.05% formic acid. Eluted peptides were dried in a speed vacuum and
resuspended in 5–10 ␮l of 5% acetonitrile and 0.05% formic acid.
2D-LC-MS/MS and computer-assisted data analysis
A modified version of a previously described 2D-LC-MS/MS method was
applied (15). Trypsin/Chymotrypsin-generated peptides were loaded onto an
analytical 2D microcapillary chromatography column packed with 3– 4 cm of
5 ␮m (pore size) strong cation exchange (SCX) resin (Phenomenex) followed
by 2–3 cm of 5 ␮m (pore size) C18 reversed-phase (RP) resin (Phenomenex).
This bi-phasic column was attached to an analytical RP chromatography column (100 ⫻ 365 ␮m fused silica capillary with an integrated, laser pulled
emitter tip packed with 10 cm of Synergi 4 ␮m RP80A (Phenomenex)). Peptides were eluted from SCX with seven step gradients of 5, 10, 15, 30, 50, 70,
and 100% 500 mM ammonium acetate. Following each SCX elution step,
peptides were ionized and sprayed into the mass spectrometer using the following linear RP gradient: 20 min: 0% B, 80 min: 40% B, 90 min: and 60%
B at a flow rate of 200 nl/min (mobile phase A: 5% acetonitrile/0.1% formic
acid and mobile phase B: 80% acetonitrile/0.1% formic acid). Spectra were
acquired with a LTQ linear ion trap mass spectrometer (Thermo Fisher Scientific). During LC-MS/MS analysis, the mass spectrometer performed datadependent acquisition with a full MS scan between 300 and 2000 mass to
change ratio followed by five MS/MS scans (35% collision energy) on the five
most intense ions from the preceding MS scan. Data acquisition was performed using dynamic exclusion with a repeat count of 30 and a 1 and 3 min
exclusion duration window.
Mass spectral data interpretations
The acquired mass spectrometric data were searched against a human protein
database (human RefSeq) using the Sequest algorithm and a commercial computational platform (SequestSorcerer, Sage-N Research) assuming modifications of oxidation of methionine (⫹15.99) and carbamidomethylation of cysteine (⫹57). High-probability protein identifications were assigned from the
Sequest results using the BIGCAT (16) and ProteinProphet (17) statistical
platforms (18, 19). Both of these programs eliminate redundant listing by
grouping proteins with 100% identity and merging proteins with 100% shared
MS/MS spectra. The BIGCAT filter uses Sequest Xcorr cut-offs of 1.5, 2, and
2.5 for ⫹1, ⫹2, and ⫹3 ions, respectively. Proteins were also ranked by
relative abundance or enrichment using a protein abundance factor (PAF). The
PAF is defined as the total number of nonredundant spectra (spectral counts)
that correlate significantly to each respective candidate protein normalized to
the protein’s m.w. (⫻104). Studies demonstrating linearity between the number of spectral counts and protein concentration provide the framework for this
type of label-free quantitative analysis from 2D-LC-MS/MS experiments
(20 –22). The PAF approach has been highly successful in the development of
statistical models based on 2D-LC-MS/MS experimental data (23–25).
ProteinProphet gives each protein a ranked probability score, with 1.0 being
the highest probability. Our results were fitted into a model where probability
scores decreasing from 1.0 were correlated to a predicted false positive identification error rate. Proteins with a probability score greater than 0.65 predicted a false positive error of ⬍10%, and those proteins were included in the
list of candidates.
The proteins were further analyzed using the National Center for Biotechnology Information (NCBI) database. Any proteins that were removed from
the database in the process of annotation or that were identified as a bacterial
protein were excluded from the final protein list. To identify integral membrane proteins and to determine intracellular location and function, identified
proteins were analyzed using the NCBI database, by Gene Ontology (26), and
by the Ingenuity Pathways Knowledge Base (IPKB) (Ingenuity Systems) (27).
The IPBK is a comprehensive knowledge base of biological findings for genes
of human, mouse, and rat origin, which is used to construct pathways and
define biological functions (28). The canonical pathways are well-characterized metabolic and cell signaling pathways that have been curated from specific journal articles, review articles, text books, and KEGG Ligand. The functional analysis has three primary categories of functions: molecular and
cellular functions; physiological system development and function; and diseases and disorders. There are 85 high-level functional categories that are
classified under these categories. The significance value of a given canonical
pathway or functional analysis category is a measurement of the likelihood that
the pathway or function is associated with the data set by random chance. The
value of p is calculated using the right-tailed Fisher Exact Test, and values of
p ⬍ 0.05 were a priori assumed to be statistically significant.
Results
Neutrophils from four individual donors were subjected to membrane fractionation, and each set was analyzed separately by mass
spectrometry. A total of 1118 proteins were identified, for which
there was a ⬍10% probability that the identification was by chance
according to Protein Prophet, and which were confirmed to have
mammalian homologues according to the NCBI database. Of the
1118 proteins, 573 were present only in plasma membrane-enriched fractions, 418 only in secretory vesicle-enriched fractions,
and 127 in both fractions. The 1118 proteins, together with their
probability score, the peptides used to identify them, the membrane fraction from which they were identified, and the Gene Ontology analysis of membrane association, cellular location, and
function, are listed in supplemental data Tables I and II.4
4
The online version of this article contains supplemental material.
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Neutrophil plasma membrane and secretory vesicle membranes were enriched
by centrifugation on a two-layer Percoll density gradient as described by Dahlgren et al. (14). Briefly, isolated neutrophils from single donors (4 ⫻ 107/ml)
were incubated with diisopropyl fluorophosphate, pelleted by centrifugation,
and resuspended in disruption buffer containing 100 mM KCl, 1 mM NaCl, 1
mM ATPNa2, 3.5 mM MgCl2, 10 mM PIPES, and 0.5 mM PMSF. Cells were
disrupted by nitrogen cavitation at 380 p.s.i. and 4°C. The cavitate was collected, supplemented with 1.5 mM EGTA, and nuclei and intact cells were
removed by centrifugation at 400 ⫻ g for 5 min. The supernatant membrane
suspension was aspirated, placed in a 50-ml conical centrifuge tube, and mixed
with an equal volume of a 1.12 g/ml Percoll gradient. A total of 10 ml of the
membrane suspension/Percoll gradient was layered under 5 ml of disruption
buffer in a 50-ml ultracentrifuge tube. A total of 10 ml of 1.05 g/ml Percoll
gradient solution was layered under the membrane suspension, then 5 ml of
1.12 g/ml Percoll gradient solution layered under the 1.05 g/ml solution. The
gradient was centrifuged at 37,000 ⫻ g in a SS-34 fixed angle rotor in a Sorvall
RC-5B centrifuge for 30 min at 4°C. Following centrifugation, successive
1.5-ml fractions were collected from the top of the gradient.
NEUTROPHIL SECRETORY VESICLE PROTEOME
The Journal of Immunology
5577
Table I. Distribution of proteins by membrane association and cell locationa
Location
Membrane-Associated
Membrane-Independent
Membrane
Association
Unknown
Cytoplasm
Cytoskeleton
Endoplasmic reticulum
Endosome/lysosome/peroxisome
Extracellular
Golgi
Mitochondria
Nucleus
Plasma membrane
Ribosome
Secretory granule
Unknown
Total
0
0
27
9
0
6
24
9
268
0
16
14
373
151
65
13
6
44
4
31
196
0
25
17
0
552
1
1
4
1
0
3
4
8
0
0
1
170
193
Total
152
66
44
16
44
13
59
213
268
25
34
184
1118
a
All identified proteins were categorized by Gene Ontology as integral membrane proteins (membrane-associated), as not
associated with membranes (membrane-independent), and proteins whose membrane association was unknown and then listed
by cellular location.
In the past, protein extraction methods used in proteomic analysis
have provided poor identification of transmembrane proteins. To
address this limitation, we used a recently described protein extraction method in which 60% methanol was added to 100 mM
ammonium bicarbonate, as recently described by Fischer et al.
(11). To determine the effectiveness of methanol extraction in the
recovery of membrane proteins, each protein was analyzed for
known association with cellular membranes using the Gene Ontology database. Of the 1118 proteins identified, 373 were categorized as integral membrane proteins, 552 were not associated with
any cellular membranes, and the membrane association of 193
proteins was unknown (Table I). A number of proteins with single
transmembrane spanning regions were identified, including
Fc␥RIIa and IIIa, integrins ␣2b, ␣3, ␣4, ␣D, ␣M, ␣X, ␤1, and ␤2;
TLRs 2 and 8; and complement receptors 1 and 2. Numerous proteins with multiple transmembrane spanning regions were also
identified, including seven transmembrane spanning receptors for
leukotiene B4, formyl peptides, IL-8, C5a, and a number of ion
channels and transporters. Table I also shows the cellular location
of proteins that were integral to membranes, independent of membranes, or where membrane association was unknown. As expected, all 268 plasma membrane proteins were categorized as
membrane-associated. The remainder of the membrane-associated
proteins were primarily localized to the endoplasmic reticulum
(27), mitochondria (24), and secretory granules (16). The majority
of proteins not associated with a cellular membrane were localized
in the cytoplasm (151), nucleus (196), or with the cytoskeleton
(65). The majority of proteins for which membrane association was
unknown also had an unknown cellular location (169 of 193 proteins).
Cellular location of proteins identified in plasma membraneenriched and secretory vesicle-enriched membrane fractions
Table II shows the cellular location of proteins identified in plasma
membrane-enriched and secretory vesicle-enriched fractions.
Based on the Gene Ontology database, 25% of proteins were predicted to be from mitochondria, ribosomes, or nuclei. Of the remaining 821 proteins, over half were proteins known to be associated with the cytoskeleton or a cellular membrane compartment,
including plasma membrane, secretory granules, endoplasmic reticulum, endosomes, or golgi. Thus, the fractions enriched for
plasma membrane and secretory vesicle membranes also contain
proteins from a number of other cellular compartments. Another
recent analysis reported that proteins from endoplasmic reticulum,
mitochondria, and golgi coisolated with neutrophil secretory vesicle-enriched membranes and enriched plasma membranes separated by free flow electrophoresis (29). Of the 1118 proteins identified, 51% were found in plasma membrane-enriched fractions,
Table II. Distribution of proteins by cell locationa
Location
Plasma
Membrane
Secretory Vesicle
Common to PM
and SV
Total
Cytoplasm
Cytoskeleton
Endoplasmic reticulum
Endosome/lysosome/peroxisome
Extracellular
Golgi
Mitochondria
Nucleus
Plasma membrane
Ribosome
Secretory granule
Unknown
Total
70
30
25
4
23
5
33
113
159
1
10
100
573
68
22
9
9
16
7
15
81
76
22
15
78
418
14
14
10
3
5
1
11
19
33
2
9
6
127
152
66
44
16
44
13
59
213
268
25
34
184
1118
a
All proteins identified were categorized by the membrane fraction from which they were identified, plasma membrane
(PM), secretory vesicle (SV) membrane, or present in both membrane fractions (common to PM and SV). These proteins were
then listed by cell location based on Gene Ontology analysis.
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Recovery of membrane-associated proteins
5578
NEUTROPHIL SECRETORY VESICLE PROTEOME
Table III. Distribution of proteins by functional categorya
Plasma
Membrane
Secretory Vesicle
Common to PM
and SV
Total
Adhesion
Chaperone/protein folding
Chromosome organization
Cytoskeletal regulation
Enzyme/metabolism
GTPase
Immune/inflammatory response
Kinase/phosphatase
Membrane trafficking
Protein Modification/targeting
Proteolysis
Receptor/signal transduction
Redox
Structural proteins
Translation/transcription
Transport
Miscellaneous
Unknown
Total
31
7
1
29
28
13
8
33
30
7
23
49
5
2
9
33
12
108
426
14
4
0
27
23
20
4
15
22
1
22
27
0
7
8
16
11
79
300
6
6
0
16
8
5
5
3
5
2
5
7
4
2
2
3
5
11
95
51
17
1
72
59
38
17
49
57
10
50
83
9
11
19
52
28
198
821
a
Proteins, excluding those identified as nuclear, mitochondrial, or ribosomal, were categorized by the membrane fraction
from which they were identified, plasma membrane (PM), secretory vesicle (SV) membrane, or present in both membrane
fractions (common to PM and SV). These proteins were then listed by cellular function based on Gene Ontology analysis.
37% in secretory vesicle-enriched fractions, and 11% were found
in both fractions. When proteins were analyzed according to their
cellular location, several patterns were observed. Proteins localized to the endoplasmic reticulum, extracellular space, mitochondria, nucleus, plasma membrane, and whose location was unknown
were more likely to be present in plasma membrane-enriched fractions. Proteins localized from endosome/lysosome/peroxisome
compartments, golgi, ribosomes, and secretory granules were more
likely to be present in secretory vesicle-enriched fractions. Proteins
defined as cytoplasmic or cytoskeletal were fairly equally distributed between plasma membrane-enriched and secretory vesicleenriched fractions. Surprisingly, the number of proteins present in
both fractions was low for all Gene Ontology cell locations, ranging from 3% for proteins of unknown location to 26% for proteins
in secretory granules. These results indicate that there was effective separation of cellular membranes based on their density, and
the data suggest that proteins from all cellular compartments segregate into distinct membrane compartments of different densities.
Functional categorization of proteins
To obtain a more accurate assessment of the functions of proteins
most likely associated with plasma membrane and secretory ves-
icle, proteins localized to mitochondria, nuclei, and ribosomes
were eliminated from the analysis. All proteins identified from
plasma membrane-enriched fractions and secretory vesicle-enriched fractions, however, are listed in supplementary Table II.
Table III shows the distribution of the remaining 821 proteins from
plasma membrane-enriched and secretory vesicle-enriched fractions according to protein function. Functional categories were assigned based on analysis by the Gene Ontology database. Where
multiple functions were assigned to a protein, the function most
likely to be pertinent to neutrophils was chosen. The majority of
proteins were classified into the following functional categories:
adhesion, cytoskeletal regulation, enzyme/metabolism, kinase/
phosphatase, membrane trafficking, proteolysis, receptor/signal
transduction, and transport. For a given functional class, plasma
membrane-enriched fractions and secretory vesicle-enriched fractions contained either an approximately equal number of proteins
or there were more proteins in the plasma membrane-enriched
fractions. Only a limited number of proteins in each functional
category were found in both fractions, ranging from 6% of transport proteins to 22% of cytoskeletal regulatory proteins.
In addition to identification of 57 proteins involved in membrane trafficking, a total of 38 GTPases or their regulatory proteins
Table IV. Pattern of functions of plasma membrane and secretory vesicle proteinsa
Secretory Vesicle Proteins
Only
Secretory Vesicle and Common
Proteins
Gene expression
Protein folding
Protein degradation
Protein trafficking
Free radical scavenging
Nucleic acid metabolism
Plasma Membrane, Secretory Vesicle, and Common Proteins
Cell signaling
Cellular movement
Cell morphology
Tissue development
Cellular development
Cell growth and proliferation
Infectious disease
Immune response
Cellular assembly and organization
Cell-to-cell signaling and interaction
Inflammatory disease
Carbohydrate metabolism
Cell death
Molecular transport
Immune system function
Immunologic disease
Post-translational modification
Mineral metabolism
Lipid metabolism
Metabolic disease
Hematological disease
a
Proteins, excluding those identified as nuclear, mitochondrial, or ribosomal, were categorized by the membrane fraction from which they were identified, plasma membrane
(PM), secretory vesicle (SV) membrane, or present in both membrane fractions (common to PM and SV). Each of these categories was analyzed by Ingenuity Pathway Knowledge
Base to determine the likelihood that functional pathways were associated with the dataset by random chance. Only those functional pathways significantly associated with
proteins from one or more membrane fractions are listed.
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Function
The Journal of Immunology
5579
Table V. Pattern of proteins in canonical pathwaysa
PM and SV Proteins and/or Common
Proteins
Actin cytoskeleton signaling
Integrin signaling
Leukocyte extravasation signaling
Calcium signaling
Complement and coagulation cascade
Vascular endothelial growth factor
signaling
Ag presentation pathway
Protein ubiquitination pathway
Oxidative stress response
Epidermal growth factor signaling
Platelet-derived growth factor signaling
ERK/MAPK signaling
JNK signaling
SV Proteins
PM Proteins
cAMP-mediated signaling
G-protein coupled receptor signaling
Fibroblast growth factor signaling
PI3K/AKT signaling
Inositol metabolism
Fc⑀R signaling
Phosphatase and tensin homolog signaling
Apoptosis signaling
NK cell signaling
TLR signaling
WNT/␤-catenin signaling
TGF-␤ signaling
NF-␬B signaling
a
Proteins, excluding those identified as nuclear, mitochondrial, or ribosomal, were categorized by the membrane fraction from which they were
identified, plasma membrane (PM), secretory vesicle (SV) membrane, or present in both membrane fractions (common to PM and SV). Each of these
categories was analyzed by Ingenuity Pathway Knowledge Base to determine the likelihood that canonical pathways were associated with the dataset by
random chance. Only those canonical pathways significantly associated with proteins from one or more membrane fractions are listed.
Functional and canonical signaling pathways associated with
proteins in plasma membrane and secretory vesicle-enriched
membrane fractions
To better understand the functional roles of plasma membrane and
secretory vesicle proteins, the 821 proteins, excluding those localized to mitochondria, nuclei, and ribosomes, were subjected to
IPKB analysis for canonical pathways and functional pathways.
Canonical pathways are defined as well-characterized metabolic
and cell signaling pathways, whereas functional pathways contain
three primary categories of functions: molecular and cellular functions; physiological system development and function; and diseases and disorders. Of the 821 proteins, 743 could be mapped
using the IPKB, 368 proteins from the plasma membrane-enriched
fractions, 282 proteins from the secretory vesicle-enriched fractions, and 93 protein identified in both fractions. Table IV lists the
functional pathways that demonstrated a significant association
with proteins identified in each membrane fraction. The vast majority of functions, including cell signaling; cellular movement;
hematologic, infectious, immunologic, and inflammatory diseases;
and molecular transport, were significantly associated with proteins in all three groups, plasma membrane-enriched fractions, secretory vesicle-enriched fractions, and proteins common to both
fractions. Thus, proteins performing these functions were not segregated into any particular membrane fraction. Table V lists the
canonical pathways identified by the presence of multiple proteins
from each pathway in the membrane fraction. Three patterns were
observed. The largest number of canonical pathways contained
proteins present in both plasma membrane-enriched and secretory
vesicle-enriched fractions, and/or proteins which were common to
both membrane fractions. This group of pathways included actin
cytoskeletal signaling, integrin signaling, leukocyte extravasation
signaling, protein ubiquitination, oxidative stress, ERK or JNK
signaling, and growth factor (platelet-derived growth factor and
epidermal growth factor) signaling. Canonical pathways containing proteins only identified in secretory vesicle-enriched fractions
included G-protein coupled receptor signaling, fibroblast growth
factor signaling, PI3K/AKT signaling, and Fc␧R signaling. Canonical pathways containing proteins only identified in plasma
membrane-enriched fractions included phosphatase and tensin homolog signaling, TLR signaling, TGF-␤ signaling, and NF-␬B signaling. Thus, plasma membrane-enriched and secretory vesicleenriched fractions contained proteins common to a number of
functions and signaling pathways. There were, however, protein
components of signaling pathways unique to plasma membrane
and to secretory vesicles.
Discussion
Understanding the functional consequences of secretory vesicle
exocytosis in neutrophils requires knowledge of the membrane
proteins of this organelle. Previous studies using primarily Abbased methods identified individual proteins from secretory vesicle
membranes, including cytochrome b558 oxidase, CD11b/CD18 adhesion molecules, complement receptor 1 (CR1 or CD35), formyl
peptide receptors, Fc(RIIIa) (CD16), membrane metalloendopeptidase (CD10), aminopeptidase N (CD13), the TLR complex molecule CD14, the transmembrane protein tyrosine phosphatase
CD45, V-type H⫹-ATPase, the soluble NSF attachment receptor
(SNARE) protein VAMP-2, and the metalloproteinase leukolysin
(1). Subcellular fractionation, combined with mass spectrometrybased proteomics, represents a powerful approach to unbiased
identification of the protein composition of intracellular organelles
(6 –9). The current study applied these techniques to develop a
more complete catalog of neutrophil secretory vesicle membrane
proteins and to compare the proteomes of secretory vesicle membranes and plasma membranes. Over 1100 proteins were identified, the majority of which segregated to either the plasma membrane-enriched fractions or the secretory vesicle-enriched
membrane fractions; only 11% of identified proteins were present
in both membrane fractions.
Two significant problems affect the interpretation of our data.
First, the sensitivity of proteomic analysis makes the ability to
obtain highly purified intracellular organelles the limiting factor in
establishing the proteome of a specific organelle. Based on the
classification of our proteins by cell location and function using
Gene Ontology, proteins typically associated with other intracellular organelles, notably nuclei, mitochondria, and ribosomes,
were identified in both secretory vesicle-enriched and plasma
membrane-enriched fractions. One reason for the presence of those
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were identified. Thus, 95 proteins were identified that are recognized to participate in regulation of events leading to membrane
trafficking. These proteins were equally distributed between
plasma membrane-enriched and secretory vesicle-enriched fractions, and only 10 proteins were present in both fractions (Rap1B,
Rab1B, Rab5C, Rab7, G␣i2, dynein 8, kinesin 27, reticulon 3c,
testilin, and secretory carrier membrane protein 2).
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proteins in secretory vesicle-enriched fractions, whereas only 7
proteins (10%) were common to both fractions. Several explanations were considered to account for the low percentage of proteins
that were common to both membrane fractions. First, secretory
vesicles are not endocytic vesicles derived from the plasma membrane, as has been previously postulated (1, 5). Second, the protein
extraction and/or identification techniques failed to identify proteins common to the two membranes. Third, separation of plasma
membrane and secretory vesicle membrane by density results in
identification of proteins that segregate according to membrane
density, rather than by organelle. It is unlikely that the sensitivity
of proteomic techniques would vary between the two membrane
fractions, resulting in the failure to identify proteins common to
both. The localization of latent alkaline phosphatase to the membrane fraction with higher density suggests that proteins associated
with secretory vesicles were limited to one group of membrane
fractions. Our data do not allow us to distinguish between the
possibility that secretory vesicles are not endocytic vesicles or that
all membranes contain domains of lighter and heavier density to
which distinct sets of proteins localize. However, the data suggest
that the hypothesis that secretory vesicles are formed from plasma
membranes by endocytosis requires more critical evaluation.
The cell functional classification based on the Gene Ontology
database revealed a number of proteins that may elucidate mechanisms of secretory vesicle exocytosis. Examination of the 38
GTPases, the majority of which were identified in secretory vesicle-enriched fractions, revealed a number of Rab proteins known
to regulate membrane trafficking. Secretory vesicle-enriched fractions contained Rab11a, Rab14, Rab15, and Rab35; plasma membrane-enriched fractions contained Rab5b and Rab31, and Rab1b,
Rab5c, and Rab7 were common to both plasma membrane and
secretory vesicle-enriched fractions. Rab5 was reported to play a
significant role in chemoattractant receptor endocytosis and fusion
of intracellular granules with phagosomes in human neutrophils
(32–34). Rab5a was shown to undergo a significant translocation
from endosomes and secretory vesicles to the plasma membrane
with stimulation of human neutrophils (35), and Rab11 was reported to regulate endocytic-exocytic cycling of integrin molecules
(36). The roles of Rab 14, Rab15, Rab31, and Rab35 have not been
examined in neutrophils. A total of 57 proteins were identified that
play a role in membrane trafficking, 30 were in the plasma membrane, 22 in secretory vesicles, and 5 were common to both. The
present study found two SNARE proteins, VAMP-3 and VAMP-8,
on secretory vesicle-enriched membranes. VAMP-1, ⫺2, ⫺7, and
⫺8 were reported previously to be present in human neutrophils,
and VAMP-2 was identified on secretory vesicles (37– 40).
VAMP-3 has not been found previously in human neutrophils,
although it has been identified in human platelets and human
plasma cells (41, 42). Mollinedo et al. (39, 40) reported that
VAMP-1 and VAMP-2 mediated exocytosis of specific granules,
whereas VAMP-1 and VAMP-7 mediated azurophil granule exocytosis. The SNARE proteins involved in secretory vesicle exocytosis have not been determined. In addition to SNARE proteins,
the exocyst complex is a group of eight proteins involved in vesicle targeting and docking at the plasma membrane (43, 44). Two
components of the exocyst complex were identified in the current
study: exocyst complex component 2 (Sec3) was identified from
plasma membrane-enriched fractions, and exocyst complex component 5 (Sec10) was identified from secretory vesicle-enriched
fractions. Boyd et al. (45) reported that Sec3p localized to the
plasma membrane of Saccharomyces cerevisiae, while Sec10p was
found on vesicles. The exocyst complex is an effector for multiple
GTPases, including cdc42 and Rab11 (46, 47). Both of these
GTPases were identified, cdc42 from plasma membrane-enriched
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contaminating proteins is that nitrogen cavitation partially disrupts
a number of intracellular compartments, including mitochondria,
golgi, endoplasmic reticulum, and nuclei. In the case of neutrophils, this disruption is reported to extend to intracellular storage
granules (10, 29 –31). Soluble proteins released from these granules likely associate and cosediment with membranes from granule-free fractions, consistent with our finding myeloperoxidase,
elastase, and lactoferrin in plasma membrane and secretory vesicle
membrane fractions. It is also likely that membranes released by
partial disruption of other organelles cosediment in plasma membrane-enriched and secretory vesicle-enriched membrane fractions. Jethwaney et al. (29) identified proteins derived from mitochondria and endoplasmic reticulum in secretory vesicle-enriched
fractions derived by free-flow electrophoresis, whereas proteins
from these and other organelles were distributed in both membrane
fractions in the current study. Whether the presence in both membrane fractions of proteins from a broader range of organelles in
our study reflects differences in membrane enrichment or protein
identification techniques between the two studies cannot be determined. No direct comparison of free-flow electrophoresis and density-gradient centrifugation enrichment of secretory vesicle-enriched and plasma membrane-enriched fractions has been
performed. Although the presence of latent alkaline phosphatase
activity indicates that both methods obtain fractions containing
secretory vesicles, a comparative study is needed to determine similarities and differences between the two methods.
A total of 73 proteins were assigned by Gene Ontology to endosomes, golgi, or endoplasmic reticulum. The possible localization of
those proteins to plasma membranes or secretory vesicles, rather than
other intracellular membrane compartments, was not examined further in this study. A recent report, in which proteomic analysis of
phagosomes was performed, determined that endoplasmic reticulum
fuse with maturing phagosomes in macrophages, suggesting one
mechanism by which proteins may be “shared” by different intracellular compartments (9). Thus, it is likely that some proteins that localize
to cellular components, such as endoplasmic reticulum or endosomes,
may also be associated with secretory vesicles or plasma membrane.
The second problem with application of proteomic techniques to
identification of proteins in secretory and plasma membranes is the
difficulty extracting and identifying transmembrane proteins containing ␣ helices. Identifying transmembrane proteins is made difficult by
the absence of sites for tryptic cleavage in transmembrane regions,
variability in the size of exposed hydrophobic regions, low abundance
of transmembrane proteins, poor separation by two-dimensional gel
electrophoresis of integral membrane proteins, and poor solubility of
hydrophobic peptides. Fischer et al. (11) recently reported that tryptic
digestion of bacterial membrane proteins extracted in 60% methanol
increased identification of integral membrane proteins from 20 to 50%
of the total proteins identified. Our results suggest that this approach
is useful in membranes from mammalian cells, as one-third of the
proteins identified in the present study were classified as integral
membrane proteins by Gene Ontology.
The observation that only 11% of proteins identified were common to both plasma membrane-enriched and secretory vesicle-enriched fractions suggests that Percoll density-gradient centrifugation effectively enriched two different membrane populations.
Combined with the assays for total and latent alkaline phosphatase,
our findings suggest that there are greater differences in the protein
content of secretory vesicles and plasma membrane than previously appreciated. Jethwaney et al. (29) used free-flow electrophoresis to separate plasma membrane from secretory vesicles,
separated proteins by SDS-PAGE, and identified proteins using
HPLC-MS/MS. Similar to our results, these authors identified 30
proteins present in the plasma membrane-enriched fractions and 36
NEUTROPHIL SECRETORY VESICLE PROTEOME
The Journal of Immunology
Disclosures
The authors have no financial conflict of interest.
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fractions and Rab11A from secretory vesicle-enriched fractions.
These findings suggest that the exocyst complex plays a role in tethering secretory vesicles to the plasma membrane before SNARE-mediated membrane fusion. Consistent with our previous studies which
showed large amounts of actin associated with both neutrophil plasma
membranes and secretory vesicle membranes (4), 72 cytoskeletal and
cytoskeletal regulatory and binding proteins were equally distributed
in both membrane fractions. Two groups of actin assembly factors
were identified. Formins act in conjunction with profilin to drive nucleation, but not branching, of actin filaments (48). Formin 1 and 2
were identified from plasma membrane-enriched fractions, and profilin 1 was common to both fractions. The Arp2/3 complex acts as a
nucleation and branching factor, and members of this complex were
identified from secretory vesicle-enriched fractions. Although it was
suggested previously that actin and actin-associated proteins reflect
cytoskeletal contamination of these membrane fractions (29), the high
content of cytoskeletal proteins and the importance of actin reorganization in exocytosis of secretory granules make it more likely that
cytoskeletal proteins are associated with plasma and secretory vesicle
membranes (4, 10).
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