
Web Release Date: November 23,
Proteomic Analysis of Cervical-Vaginal Fluid: Identification of Novel Biomarkers for Detection of Intra-amniotic Infection










and

Division of Reproductive Sciences, Oregon National Primate Research Center, Beaverton, Oregon 97006, Department of Obstetrics and Gynecology, University of Washington, Seattle, Washington 98195, Departments of Obstetrics & Gynecology and Pediatrics, Oregon Health and Science University, Portland, Oregon 97239, and ProteoGenix, Inc., Portland, Oregon 97213
Received April 6, 2006
Abstract:
Intra-amniotic infection (IAI) is associated with preterm birth and perinatal mortality. To identify potential biomarkers, we performed a comprehensive survey of the cervical-vaginal fluid (CVF) proteome from a primate IAI model utilizing multidimensional protein identification technology (LC/LC-MS/MS) and MALDI-TOF-MS analyses. Analyses of CVF proteome identified 205 unique proteins and differential expression of 27 proteins in controls and IAI samples. Protein expression signatures and immunodetection of specific biomarkers identified can be employed for noninvasive detection of IAI.
Keywords: intra-amniotic infection
preterm birth
cervical-vaginal fluid
Intrauterine infections, including intra-amniotic infections
and chorioamnionitis, are an important and potentially preventable cause of maternal and perinatal mortality and morbidity.1 Intra-amniotic infection (IAI), in particular, accounts
for up to 40% of cases of febrile morbidity in the peripartum
period and is associated with at least one-third of early neonatal
sepsis and pneumonia.2 More recently, IAI has been implicated
as a major cause of preterm birth. Despite improvements in
prenatal care, preterm birth still occurs in 12.3% of births in
the United States and remains the major obstetrical problem
in developed countries.3 Intra-amniotic infections are associated with more than 50% of the very-low-birth-weight neonates
that account for the highest number of neonatal deaths, the
most serious complications, including neurologic handicap,
and a disproportionate share of perinatal health care costs.1
Accurate and early diagnosis of IAI would facilitate timelier and
more appropriate interventions, as well as enhance the design
of therapeutic trials. Early diagnosis of IAI is problematic,
however, because clinical signs and symptoms tend to be late
manifestations of this condition. Furthermore, the available
noninvasive tests, for example, maternal white blood cell count
or C-reactive protein, have limited predictive value, or in the
case of more predictive tests of amniotic fluid, for example,
interleukin-6, polymerase chain reaction, or microbial culture,
the results are often delayed and amniocentesis is required.4,5
We have previously demonstrated, in a nonhuman primate
model, the causal relationships among experimental IAI with
Group B Streptococcus, Ureaplasma parvum, or Mycoplasma
hominis, and preterm birth.6,7
In this study, we utilized multidimensional liquid chromotography coupled to tandem mass spectrometry (Multidimensional Protein Identification Technology; MudPIT) and spectral counting to characterize the proteins present in CVF and to determine the relative abundance of these proteins to detect the early appearance of sensitive and specific protein markers for IAI in CVF in nonhuman primates with experimental IAI caused by U. parvum. In addition, we utilized matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) to examine IAI-specific protein signatures in CVF and to compare them to signatures that we have previously described in AF.
Experimental IAI in Nonhuman Primates. This protocol was
approved by the Institutional Animal Care and Utilization
Committee of Oregon Health & Science University. Four
pregnant rhesus monkeys (Macaca mulatta) with timed gestations were chronically catheterized at 120 days gestation (term
is 167 days) as previously described.6 Experimental IAI was
established by intra-amniotic inoculation of 107 colony-forming
units of a clinical low-passage U. parvum, serovar 1, grown in
10B culture media.7 Each animal served as its own control.
Before and after inoculation, AF and CVF samples were serially
collected for quantitative bacterial cultures, white blood cell
analysis, and cytokine and prostaglandin concentrations, as
previously reported,6,7 and for proteomic analysis. CVF was
collected from the posterior vaginal fornix with sterile Dacron
swabs (Solon, catalog no. 36816), which were then placed into
phosphate-buffered saline containing a protease inhibitor
cocktail (Roche Diagnostics, catalog no. 11836), to prevent
nonspecific proteolysis from naturally occurring proteases
within the vagina. Following protein extraction, samples were
centrifuged to remove cellular debris, and the supernatant was
stored at -70
C until assayed. For these assays, pooled CVF
samples were utilized from samples obtained prior to infection
and from samples collected 24-72 h after infection. Uterine
contractility was recorded as the area under the amniotic fluid
pressure curve and expressed as the hourly contraction area
[HCA; recorded as (mmHg s)/h]. Fetal, decidual, placental, and
bacterial cultures were obtained after delivery, by Cesarean,
from infected animals to confirm infection, and histopathologic
studies were performed to confirm histologic chorioamnionitis.
MALDI-TOF-MS Profiling of CVF and AF. A total of 0.5-3.0
g of unfractionated protein from CVF and AF was analyzed
on a MALDI-TOF-TOF mass spectrometer (AutoFLEX II TOF/TOF, Bruker Daltonics, Billerica, MA) equipped with a pulsed-ion extraction source. Briefly, 1
L of sample was diluted with
4
L of 50% acetonitrile (ACN)/0.1% trifluoroacetic acid (TFA)
and 5
L of matrix solution (saturated sinapinic acid in 50%
ACN/0.5% TFA). Samples were spotted (2
L) in quadruplicate,
onto a 382-well ground steel Scout target (Bruker Daltonics,
Billerica, MA). The Autoflex was used in linear mode with an
accelerating voltage of +20 kV. The pulsed-ion extraction drop
voltage was 1500 V with a delay time of 350 ns. Matrix ions
were suppressed up to 3000 Da using the maximum ion gating
setting. The sampling rate was 2.0 GHz, and each profile
spectrum represents a sum of 500 laser shots fired at 10
different positions. A nitrogen laser (
= 337 nm) operating at
50 Hz was used to irradiate samples. The output energy of the
laser was ~110
J attenuated with an offset of 62% and a range
of 36%. Samples were irradiated at a laser power of 30% and
standards at 20%. Spectra were manually collected from m/z
3000 to 20 000 at a fixed laser power. Spectra were calibrated
by external calibration using Protein calibration standard I
mixture (Bruker Daltonics, Billerica, MA) containing the following: insulin (m/z 5734.6), ubiquitin (m/z 8565.9), cytochrome c (m/z 12361.9), and myoglobin (m/z 16952.6), and
analyzed using ClinProt software version 2.0 (Bruker Daltonics,
Billerica, MA).
One-Dimensional PAGE Coupled with LC-MS/MS Analysis.
One hundred
g of CVF protein from control and infected
samples was reduced with iodoacetamide and resolved on a
Tris-tricine, 10-20% gradient SDS-PAGE gel. The gel was
stained with Coomassie blue R-250, and distinct bands from
each lane were cut from the gel, destained, and digested in-gel with trypsin for 24 h at 37
C using the method of
Courchesne and Patterson.13 Peptides were then extracted with
0.1% TFA and purified using Zip-Tip c18 pipet tips from
Millipore. After in-gel digestion, samples were analyzed on a
Q-Tof-2 mass spectrometer (Micromass UK Ltd, U.K.) coupled
with a CapLC (Waters, Inc., Milford, MA). Masses from 400 to
1500 Da were scanned for the MS survey, and masses of 50-1900 Da were scanned for MS/MS. Data analysis for protein
identification was done as described below in MudPIT analysis.
MudPIT Protein Identification and Spectral Counting. For
CVF MudPIT analysis, 100
g each from four control and
infected samples were pooled to create a 0.4 mg sample from
each condition. Protein was dissolved in 100
L of digestion
buffer containing 8 M urea, 1 M Tris base, 80 mM methylamine,
and 8 mM CaCl2 (pH 8.5). For reduction and alkylation of
cysteine residues, samples were first incubated at 50
C in 12.5
L of 0.9 M DTT for 15 min. and then in 25
L of 1.0 M
iodoacetamide in the dark at room temperature for another
15 min. Before adding 40
L of mass spectrometry-grade trypsin
(1
g/
L; Promega, Madison WI), an additional 12.5
L of 0.9
M DTT along with 210
L of water and 1 N NaOH to adjust the
solution to pH 8.5 were added. Samples were then thoroughly
mixed and incubated overnight at 37
C. Digestion was halted
by the addition of 40
L of formic acid. Digests were desalted
prior to MudPIT analysis using C18 Sep-Pak cartridges (Waters,
Inc., Milford, MA).
Desalted digests (1 mL) were injected onto a polysulfoethyl
strong cation exchange column (2.1 mm i.d. × 100 mm, 5
m
particles, and 300
m pore size (Nest Group, Southborough,
MA) and fractionated using an HPLC equipped with a UV
detector and a fraction collector. Solvent A was 5.6 mM
potassium phosphate (pH 3) with 25% acetonitrile (ACN), and
Solvent B was 5.6 mM potassium phosphate (pH 3) and 350
mM KCl with 25% ACN. A 95-min gradient at a flow rate of
200
L/min was employed for fractionation of peptides: 100%
A for 10 min, ramp to 50% B over 45 min, ramp to 100% B
over 15 min, and ramp back to 100% A in 0.1min, then hold at
100% A for 20 min. A total of 80 fractions was collected and
stored at -20
C. The fractions were evaporated and resuspended in 100
L of 0.1% TFA for desalting using a 96-well spin
column (Vydac C18 silica: Nest Group, Southborough, MA).
After elution in 80% ACN/0.1% formic acid (FA), fractions were
consolidated into 43 fractions, evaporated, and resuspended
in 25
L of 5% FA.
SCX fractions (5
L each) were analyzed on a Q-Tof-2 mass
spectrometer connected to a CapLC (Waters, Inc., Milford, MA).
The Q-Tof-2 was equipped with a nanospray source. Each SCX
fraction was separated using a Nanoease C18 75
m i.d. × 15
cm fused silica capillary column (Waters, Inc., Milford, MA)
and a 95-min water/ACN gradient. The mass spectrometer was
calibrated using Glu1Fibrinopeptide B. An MS/MSMS survey
method was used to acquire spectra. Masses from m/z 400-1500 were scanned for MS survey and masses from m/z 50-1900 for were scanned for MS/MS. MS/MS spectra were
processed with ProteinLynx Global Server v.2.1 software (Waters, Inc., Milford, MA).
A total of 3120 MS/MS spectra from control samples and
2800 MS/MS spectra from IAI samples were searched against
a combined database containing known contaminants and
forward and reverse entries of the Swiss-Prot human database (version 46.6) using three independent search engines:
OpenSea,14,15
0.8) identification. Protein
identifications having at least two independent peptide identifications (probability
0.8) were considered likely to be
present in the sample.
Polyclonal Antibodies and Western Immunoblotting. Immunogenic peptides and/or recombinant proteins were used
to generate rabbit and goat polyclonal antibodies (DSL Laboratories, Webster, TX). Affinity-purified antibodies were then
used for Western blots. One hundred micrograms of CVF
protein was resolved on 4-20% SDS-PAGE and transferred to
PVDF membranes. The membranes were blocked with 5%
fatfree milk in PBST for 45 min at room temperature and
incubated with 1
g/mL primary antibody (IGFBP-1, azurocidin, calgranulin-A, calgranulin-B, anexin II, lipocalin, profilin)
overnight at 4
C. After three washes with TBST, the membrane
was incubated with IgG-HRP secondary antibody (Sigma-Aldrich Co.) and visualized with enhanced chemiluminescence
(Pierce).
Statistical Analysis. Spectral counting was used to determine
the proteins that were differentially expressed between control
and infected MudPIT samples. All proteins with more than two
confident peptide identifications were considered for protein
quantification using spectral counting. Identified protein lists
were further curated by collapsing spectral counts for similar
proteins (e.g., immunoglobulins,
-1-acid-glycoproteins 1 and
2, and pregnancy-specific glycoproteins) into a single entry.
Spectral counts of identical peptides between dissimilar proteins were split between the proteins in equal ratios. Curated
protein lists for both samples were merged, and an independent 2 × 2
2 test on the spectral counts for each protein
between the samples was used to find proteins that were
differentially present between them. To reduce the false-positive rate of differentially abundant proteins, only proteins
with a p-value
0.1 and with at least two independent peptides
matched to at least four MS/MS spectra (probability
0.8) in
at least one of the samples were considered as statistically
significant. Fold changes of proteins passing the above criteria
were determined using a published formula for calculating
spectral count ratios.17
Experimental IAI Following U. parvum Infection. Following
intra-amniotic inoculation, infection was rapidly established
in all animals. Increases in uterine contractility from basal levels
of 100 HCA to levels in excess of 3000-6000 HCA occurred an
average of 54 (range 34-72) h after inoculation with U. parvum
and led to progressive cervical changes, as measured by the
Bishop score. Increases in uterine contractility were preceded
by significant elevations in the pro-inflammatory cytokines
TNF-
, IL-1
, IL-6, and IL-8, and prostaglandins E2 and F2
as
previously reported.6,7 No animal had other clinical signs of IAI
at the time of initial increases in uterine contractility. Following
delivery, histopathologic examination confirmed chorioamnionitis in all cases.
Global Analysis of the CVF Proteome in a Nonhuman Primate Experimental IAI Model Using Multidimensional Protein Identification Technology (MudPIT). Increasing confidence in mass spectrometry-based peptide identification and quantification methods has launched the development of extensive and varied multidimensional peptide separations coupled with MS/MS. Such "shotgun" peptide sequencing endeavors produce reliable protein identifications, as well as relative quantitative information, for comparing sets of samples analyzed in parallel.
A total of 205 unique proteins (supplementary Table 1
,
Supporting Information) were identified in CVF using MudPIT
and gel-based fractionation (1D PAGE coupled to LC-tandem
mass spectrometry) analyses. Functional annotation of the CVF
proteome using GeneOntology terms (DAVID V 2.1) showed
(Figure 1A) a majority of them to be associated with metabolism
(25%) and immune response (23%). Analysis of the predicted
subcellular location of the proteins identified from CVF (Figure
1B) showed that the annotated proteins are from cytoplasmic
(24%), secretory (18%), cytoskeletal (14%), and nuclear (14%)
categories. No information was available regarding the cellular
location of 13% of the proteins identified.
For the analysis of differential protein levels in the setting of infection, CVF samples obtained before and after experimental IAI were digested with trypsin and subjected to MudPIT analysis. MS/MS spectra derived from the MudPIT analysis led to the high-confidence identification (2 or more peptides/protein) of 149 and 151 proteins in the control and infected samples, respectively. To decrease false-positive protein identification rates, MS/MS spectra were searched against a database containing known contaminants (i.e., trypsin, keratin, and serum albumin) and both forward and reverse peptide sequence entries from the Swiss-Prot human and primate databases using three independent search engines. A probability-based algorithm, Scaffold (Proteome Software, Inc., Portland, OR), was used to combine results from the three search engines. The use of multiple searching algorithms increases the confidence in reported identifications by decreasing peptide identifications occurring by chance. Protein identification numbers reported above had two or more unique peptide identifications.
For quantitative comparison of control and IAI samples, a
spectral counting method was implemented. Spectral counting
permits rapid detection of abundance differences between two
sample pools without resorting to complicated differential
labeling experimentation.37 Curated protein lists from control
and IAI were compiled, and independent
2 tests on the spectral
counts of each protein were performed. Proteins with calculated
2 values over 2.706 (90% confidence interval) are reported
in Table 1. Included in the table are the spectral counts and
the number of MS/MS peptide spectra matching to the given
protein, for the control and IAI samples. The fold change
between control and IAI for each of the significant proteins
was also calculated.17 Of the 27 proteins found to be differentially present between control and IAI by spectral counting, 19
proteins had
2 values in the 99% confidence interval, and 8
proteins had
2 values in the 95% confidence interval. When
compared to quantitative proteomic studies performed using
protein separations (1D PAGE LC-MS/MS), 15 proteins found
by spectral counting corresponded to differential trends seen
in 1-D gel-based experiments. The identification of potential
lower-abundance serum protein markers is one of the benefits
of MudPIT analysis. The multidimensional front-end peptide
separations (SCX and RP-LC) permit the interrogation of a
wider dynamic range of concentration over gel-based proteomic analyses as well as MALDI profiling technologies.
The potential biomarkers for detection of IAI in CVF,
summarized in Table 1, were predominantly immunoregulatory
proteins. Several of these, including calgranulins A and B,
azurocidin, and IGFBP-1, which were differentially present in
IAI AF,8 were also found to be upregulated in IAI CVF. The
differential abundance of total IGFBP-1 (Table 1) reflected both
the intact 30-kDa protein and a proteolytic fragment, identified
by Western blot in Figure 2. However, the majority of IGFBP-1
present in the setting of IAI was comprised of the proteolytic
fragment (Figure 2). Defensins, previously identified by others
as markers for intra-amniotic or lower genital tract infections,18-20
Identification of IAI Protein Profiles by MALDI-TOF MS. MALDI-TOF MS analyses of CVF and AF protein extracts revealed several peak intensity differences in the 3-5 and 11-12-kDa regions between infected and noninfected primate and human CVF and AF (Figure 2), similar to the previously reported protein signature profile in AF obtained by SELDI-TOF.8
A 10.8-kDa cluster was consistently upregulated in infected CVF and amniotic fluid in all cases. Of interest, the relative intensity of this peak was greater among CVF samples than among AF samples following infection, consistent with the hypothesis that the basal state of the lower genital tract milieu is pro-inflammatory. The increased expression of the 3-5-kDa cluster in response to IAI is more robust in AF compared to CVF. The proteins with masses 3432 and 4128 Da were commonly overexpressed in AF and CVF in the presence of IAI. These masses may represent defensins, as reported earlier.18 Longitudinal sampling following U. parvum infection revealed that the 10.8-kDa cluster intensity was increased as early as 24 h after inoculation and preceded increases in HCA in infected animals in both CVF and AF samples (data not shown).
Immunodetection of IAI Biomarkers. To validate the differential expression of proteins identified in IAI, we selected five of the markers identified by MudPIT analysis. Antibodies were raised for calgranulins A and B, IGFBP-1, azurocidin, lipocalin, annexin II, and an unregulated protein (haptoglobin) to confirm the differential abundance of potential IAI biomarkers. As shown in Figure 3, Western blot analysis confirmed the differential presence of all of these biomarkers, which exhibited differential levels that were consistent with the protein identification experiments performed on IAI CVF.
| Figure 3 Immunodetection of potential CVF biomarkers for IAI. Haptoglobin, unregulated control marker. IGFBP-1 bands represent the intact protein (~30 kDa) and proteolytic fragment (~19 kDa). |
Subclinical IAI is present in at least 50% of extremely premature births, in which neonatal morbidity and mortality are disproportionately high.1 The early clinical diagnosis of IAI is difficult because signs and symptoms of IAI are a late manifestation of the infection. Furthermore, the available noninvasive diagnostic tests (e.g., maternal white blood cell count or C-reactive protein) have limited predictive value. Other tests, including measurement of AF glucose, leukocytes, interleukin-6, or Gram stain, require amniocentesis, and additionally, in the case of AF culture, the results are delayed beyond a clinically optimal time frame.
A causal relationship between IAI and preterm delivery that parallels the course observed in women has been demonstrated in a nonhuman primate experimental model.6 In a previous study, we utilized SELDI-TOF mass spectrometry to characterize protein profiles in AF from rhesus monkeys with experimental IAI and in women with subclinical IAI and preterm delivery.8 We identified a unique SELDI-TOF profile with elevated levels of peptides in the 3-5-kDa and in the 10.8-kDa molecular weight ranges in all AF samples after infection, and in no AF obtained prior to infection. Similarly, this unique protein profile was observed in all women with IAI and preterm delivery, and in no women with preterm labor without infection and subsequent delivery at term.8 Proteins identified by tandem mass spectrometry within these mass ranges included calgranulins A and B and a unique proteolytic fragment of IGFBP-1. These findings have recently been confirmed, and other protein biomarkers of IAI have been identified, by Buhimschi et al.18
In the present study, we sought first to characterize the
proteome of CVF and to characterize and to compare with AF,
the protein profile in CVF from rhesus monkeys with experimental IAI utilizing the same experimental model as previously
described.6-8 This is the first report utilizing MALDI-TOF mass
spectrometry and multidimensional protein identification technology (MudPIT) to characterize the protein profile of CVF and
to identify novel biomarkers for IAI in a site that allows for
noninvasive collection of serial samples from a more accessible
maternal sampling site. This may allow for the risk prediction
or diagnosis of ascending intrauterine infection in the etiology
of IAI and, by comparison with maternal serum and fetal AF
sampling, provide new insights into the pathogenesis of IAI.
We utilized a well-established, nonhuman primate model in
which experimental IAI was caused by intra-amniotic inoculation of U. parvum. We chose this pathogen because the most
frequently isolated microorganisms from placentae of women
with histologic chorioamnionitis21 or from AF of women in
preterm labor with intact fetal membranes are Ureaplasma
species (Ureaplasma urealyticum and U. parvum). Ureaplasma
species have also been implicated in postpartum endomyometritis, neonatal sepsis, meningitis, and neonatal bronchopulmonary dysplasia.22-24
We utilized two very distinct proteomic approaches in this
study: a rapid protein fingerprinting approach (MALDI-TOF
MS) that generates distinct expression profiles and is amenable
for developing rapid screening assays, together with a in-depth
protein identification and quantification approach (LC-LC-MS/MS, MudPIT) that provides the identity of the biomarkers
suitable for identification by conventional immunoassays.
MALDI-TOF MS-based profiling techniques have been targeted
for their robustness, ease-of-use, and high-throughput nature.
A majority of profiling studies to date have evaluated disease
states using MALDI-MS protein profiling methods involving
serum fractionation using chromatographic techniques coupled
with MALDI-TOF MS.25-27
Two-dimensional gel electrophoresis (2-DE) commonly used
to detect differential protein expression patterns28,29
Characterization of proteins expressed in CVF in control and
IAI using MudPIT analyses revealed a significant number of
immune response/defense-related proteins that were upregulated in IAI. There is a considerable degree of overlap between
the differentially abundant proteins in AF and CVF during IAI.
In our study, calgranulins, azurocidin, lipocalin, L-plastin, and
others, which were previously identified as potential biomarkers
for IAI in amniotic fluid, were also differentially present in CVF.
In addition to the above-mentioned immunomodulators, the
detection of the antibacterial protein azurocidin in CVF in
response to infection provides new insights into the intrauterine immune response. Azurocidin (CAP37) is a cationic antimicrobial protein isolated from human neutrophils that has
potentially important actions in host defense and inflammation.38 Another antimicrobial protein with elevated expression
in IAI is cathelin, which has a C-terminal 37-residue
-helical
peptide active against bacterial infection.39 The increased levels
of annexins in infected CVF may relate to CVF-specific IAI
responses. Annexins are a group of Ca2+-binding proteins that
are associated with inflammatory and defense responses.
Annexin A2 is upregulated in viral-transformed cell lines and
in human tumors.40 Annexin 1 modulates the antiinflammatory
actions of the steroid hormones.41 Matrix metalloproteinases
(MMPs) are a family of zinc-dependent endopeptidases that
are expressed in many inflammatory conditions and contribute
to connective tissue breakdown. It has been proposed that
bacterial products and/or the proinflammatory cytokines IL-1
and TNF-
, as paracrine or autocrine signals, may trigger
amniochorion cells to induce MMP expression.42,43
In the second approach, we utilized MALDI-TOF MS and detected a significantly overexpressed 10.8-kDa cluster in CVF in the setting of experimental primate IAI. This is similar to the AF proteome profile observed in our previous studies8 and confirms the specificity of this signature profile for the detection of IAI in CVF. This overexpressed cluster could represent the basic intrauterine immune response to infection, as one set of proteins identified in this unique cluster, that is, the calgranulins, are members of the S-100 calcium binding protein family that is expressed by macrophages and by epithelial cells in acutely inflamed tissues. The second candidate from this cluster, a proteolytic fragment of IGFBP-1, indicates a potential protease-related mechanism in response to infection. Intact IGFBP-1 is the major IGFBP found in AF and is synthesized by both fetal membranes and maternal decidua. Notably, however, this signature is present, albeit in lower relative concentrations, in CVF samples, but absent in AF samples prior to infection. The higher basal levels of these immunoregulatory peptides may reflect the basal inflammatory characteristics of the vaginal milieu compared to that of amniotic fluid. Amniotic fluid is normally sterile, with minimal concentrations of inflammatory markers. In contrast, the vagina is characterized by a pro-inflammatory, microbe-rich environment. Thus, while CVF samples may have the advantage of ease of noninvasive sampling, the results may be confounded by local inflammatory conditions such as bacterial vaginosis.
Characterization of the CVF proteome and identification of a significant number of proteins differentially expressed in IAI complements the sensitive proteomic approaches used to identify biomarkers and their potential value in development of noninvasive testing for IAI. Much can be learned about the pathogenesis of IAI by analysis of temporal and quantitative samples from CVF, AF, and maternal serum. Analogous issues have been raised by surveys of other cervical-vaginal inflammatory biomarkers such as pro-inflammatory cytokines and fetal fibronectin.9-12 These observations, and ours, are consistent with the hypothesis that, during infection-associated preterm birth, there is a disruption of the extracellular matrix at the choriodecidual interface, and that inflammatory mediators produced at this interface reach the vaginal pool, possibly in association with a breakdown in cervical barriers.
In summary, we utilized two complementary proteomic approaches to characterize the global expression of cervical-vaginal proteins and to identify potential biomarkers of IAI in cervical vaginal fluid. Distinct immunoregulatory peptides were identified that were differentially expressed in CVF following experimental IAI. The differential expression of these peptides was confirmed with immunoassay, and provides an opportunity for the development of noninvasive reliable tests for the diagnosis of IAI.
Supported in part by NIH Grants AI42490 and HD06159 and by ProteoGenix, Inc. Oregon Health & Science University and Drs. Gravett, Roberts, and Nagalla all have a significant financial interest in ProteoGenix, Inc., a company that may have a commercial interest in the results of this research and technology. This potential conflict of interest has been reviewed and a management plan approved by the OHSU Conflict of Interest in Research Committee.
List of unique proteins identified in CVF using MudPIT. This material is available free of charge via the Internet at http://pubs.acs.org.
* Addess correspondence to Michael G. Gravett, M.D., Department of Obstetrics & Gynecology, University of Washington, 1959 NE Pacific St., Box 356460, Seattle, WA 98195. E-mail: gravettm@u.washington.edu.
Oregon National Primate Research Center.
Department of Obstetrics and Gynecology, University of Washington.
Department of Obstetrics & Gynecology, Oregon Health and Science
University.
ProteoGenix, Inc.
Department of Pediatrics, Oregon Health and Science University.
1. Goldenberg, R. L.; Hauth, J. C.; Andrews, W. W. Intrauterine
infection and preterm delivery. N. Engl. J. Med. 2000, 342 (20),
1500-7.
2. Newton, E. R. Chorioamnionitis and intraamniotic infection. Clin.
Obstet. Gynecol. 1993, 36 (4), 795-808.
3. Martin, J. A.; Hamilton, B. E.; Sutton, P. D.; Ventura, S. J.;
Menacker, F.; Munson, M. L. Births: final data for 2003. Natl.
Vital Stat. Rep. 2005, 54 (2), 1-116.
4. Hitti, J.; Riley, D. E.; Krohn, M. A.; Hillier, S. L.; Agnew, K. J.;
Krieger, J. N.; Eschenbach, D. A. Broad-spectrum bacterial rDNA
polymerase chain reaction assay for detecting amniotic fluid
infection among women in premature labor. Clin. Infect. Dis.
1997, 24 (6), 1228-32.
5. Watts, D. H.; Krohn, M. A.; Hillier, S. L.; Eschenbach, D. A. The
association of occult amniotic fluid infection with gestational age
and neonatal outcome among women in preterm labor. Obstet.
Gynecol. 1992, 79 (3), 351-7.
6. Gravett, M. G.; Witkin, S. S.; Haluska, G. J.; Edwards, J. L.; Cook,
M. J.; Novy, M. J. An experimental model for intraamniotic
infection and preterm labor in rhesus monkeys. Am. J. Obstet.
Gynecol. 1994, 171 (6), 1660-7.
7. Novy. M. J.; Duffy, L.; Axthelm, M. K.; Cook, M. J.; Haluska, G. J.; Witkin, S. S.; Gerber, S.; Gravett, M. G.; Sadowsky, D.W.; Cassell, G. H. Experimental primate model for Ureaplasma chorioamnionitis and preterm labor. Society for Gynecologic Investigation. 2001, Toronto, Canada, March 14-17, 2001.
8. Gravett, M. G.; Novy, M. J.; Rosenfeld, R. G.; Reddy, A. P.; Jacob,
T.; Turner, M.; McCormack, A.; Lapidus, J. A.; Hitti, J.; Eschenbach, D. A.; Roberts, C. T., Jr.; Nagalla, S. R. Diagnosis of intra-amniotic infection by proteomic profiling and identification of novel
biomarkers. JAMA, J. Am. Med. Assoc. 2004, 292 (4), 462-9.
9. Rizzo, G.; Capponi, A.; Rinaldo, D.; Tedeschi, D.; Arduini, D.;
Romanini, C. Interleukin-6 concentrations in cervical secretions
identify microbial invasion of the amniotic cavity in patients with
preterm labor and intact membranes. Am. J. Obstet. Gynecol.
1996, 175 (4
10. Holst, R. M.; Mattsby-Baltzer, I.; Wennerholm, U. B.; Hagberg,
H.; Jacobsson, B. Interleukin-6 and interleukin-8 in cervical fluid
in a population of Swedish women in preterm labor: relationship
to microbial invasion of the amniotic fluid, intra-amniotic
inflammation, and preterm delivery. Acta Obstet. Gynecol. Scand.
2005, 84 (6), 551-7.
11. Di Naro, E.; Ghezzi, F.; Raio, L.; Romano, F.; Mueller, M. D.;
McDougall, J.; Cicinelli, E. C-reactive protein in vaginal fluid of
patients with preterm premature rupture of membranes. Acta
Obstet. Gynecol. Scand. 2003, 82 (12), 1072-9.
12. Yoon, B. H.; Romero, R.; Moon, J. B.; Oh, S. Y.; Han, S. Y.; Kim,
J. C.; Shim, S. S. The frequency and clinical significance of intra-amniotic inflammation in patients with a positive cervical fetal
fibronectin. Am. J. Obstet. Gynecol. 2001, 185 (5), 1137-42.
13. Courchesne, P. L.; Patterson, S. D. Identification of proteins by
matrix-assisted laser desorption/ionization mass spectrometry
using peptide and fragment ion masses. Methods Mol. Biol. 1999,
112, 487-511.
14. Searle, B. C.; Dasari, S.; Turner, M.; Reddy, A. P.; Choi, D.;
Wilmarth, P. A.; McCormack, A. L.; David, L. L.; Nagalla, S. R.
High-throughput identification of proteins and unanticipated
sequence modifications using a mass-based alignment algorithm
for MS/MS de novo sequencing results. Anal. Chem. 2004, 76 (8),
2220-30.
15. Searle, B. C.; Dasari, S.; Wilmarth, P. A.; Turner, M.; Reddy, A. P.;
David, L. L.; Nagalla, S. R. Identification of protein modifications
using MS/MS de novo sequencing and the OpenSea alignment
algorithm. J. Proteome Res. 2005, 4 (2), 546-54.
16. Craig, R.; Cortens, J. P.; Beavis, R. C. Open source system for
analyzing, validating, and storing protein identification data. J.
Proteome Res. 2004, 3 (6), 1234-42.
17. Old, W. M.; Meyer-Arendt, K.; Aveline-Wolf, L.; Pierce, K. G.;
Mendoza, A.; Sevinsky, J. R.; Resing, K. A.; Ahn, N. G. Comparison
of label-free methods for quantifying human proteins by shotgun
proteomics. Mol. Cell. Proteomics 2005, 4 (10), 1487-502.
18. Buhimschi, I. A.; Christner, R.; Buhimschi, C. S. Proteomic
biomarker analysis of amniotic fluid for identification of intra-amniotic inflammation. BJOG 2005, 112 (2), 173-81.
19. Valore, E. V.; Park, C. H.; Quayle, A. J.; Wiles, K. R.; McCray, P.
B., Jr.; Ganz, T. Human beta-defensin-1: an antimicrobial peptide
of urogenital tissues. J. Clin. Invest. 1998, 101 (8), 1633-42.
20. Balu, R. B.; Savitz, D. A.; Ananth, C. V.; Hartmann, K. E.; Miller,
W. C.; Thorp, J. M.; Heine, R. P. Bacterial vaginosis and vaginal
fluid defensins during pregnancy. Am. J. Obstet. Gynecol. 2002,
187 (5), 1267-71.
21. Hillier, S. L.; Martius, J.; Krohn, M.; Kiviat, N.; Holmes, K. K.;
Eschenbach, D. A. A case-control study of chorioamnionic
infection and histologic chorioamnionitis in prematurity. N. Engl.
J. Med. 1988, 319 (15), 972-8.
22. Chaim, W.; Horowitz, S.; David, J. B.; Ingel, F.; Evinson, B.; Mazor,
M. Ureaplasma urealyticum in the development of postpartum
endometritis. Eur. J. Obstet. Gynecol. Reprod. Biol. 2003, 109 (2),
145-8.
23. Viscardi, R. M.; Manimtim, W. M.; Sun, C. C.; Duffy, L.; Cassell,
G. H. Lung pathology in premature infants with Ureaplasma
urealyticum infection. Pediatr. Dev. Pathol. 2002, 5 (2), 141-50.
24. Yoon, B. H.; Romero, R.; Kim, M.; Kim, E. C.; Kim, T.; Park, J. S.;
Jun, J. K. Clinical implications of detection of Ureaplasma
urealyticum in the amniotic cavity with the polymerase chain
reaction. Am. J. Obstet. Gynecol. 2000, 183 (5), 1130-7.
25. Tang, N.; Tornatore, P.; Weinberger, S. R. Current developments
in SELDI affinity technology. Mass Spectrom. Rev. 2004, 23 (1),
34-44.
26. Issaq, H. J.; Conrads, T. P.; Prieto, D. A.; Tirumalai, R.; Veenstra,
T. D. SELDI-TOF MS for diagnostic proteomics. Anal. Chem. 2003,
75 (7), 148A-155A.
27. Petricoin, E. F.; Ardekani, A. M.; Hitt, B. A.; Levine, P. J.; Fusaro,
V. A.; Steinberg, S. M.; Mills, G. B.; Simone, C.; Fishman, D. A.;
Kohn, E. C.; Liotta, L. A. Use of proteomic patterns in serum to
identify ovarian cancer. Lancet 2002, 359 (9306), 572-7.
28. Tsangaris, G.; Weitzdorfer, R.; Pollak, D.; Lubec, G.; Fountoulakis,
M. The amniotic fluid cell proteome. Electrophoresis 2005, 26 (6),
1168-73.
29. Pieper, R.; Gatlin, C. L.; Makusky, A. J.; Russo, P. S.; Schatz, C. R.;
Miller, S. S.; Su, Q.; McGrath, A. M.; Estock, M. A.; Parmar, P. P.;
Zhao, M.; Huang, S. T.; Zhou, J.; Wang, F.; Esquer-Blasco, R.;
Anderson, N. L.; Taylor, J.; Steiner, S. The human serum proteome: display of nearly 3700 chromatographically separated
protein spots on two-dimensional electrophoresis gels and
identification of 325 distinct proteins. Proteomics 2003, 3 (7),
1345-64.
30. Gorg, A.; Weiss, W.; Dunn, M. J. Current two-dimensional
electrophoresis technology for proteomics. Proteomics 2004, 4
(12), 3665-85.
31. Washburn, M. P.; Wolters, D.; Yates, J. R., III. Large-scale analysis
of the yeast proteome by multidimensional protein identification
technology. Nat. Biotechnol. 2001, 19 (3), 242-7.
32. Schirmer, E. C.; Florens, L.; Guan, T.; Yates, J. R., III; Gerace, L.
Nuclear membrane proteins with potential disease links found
by subtractive proteomics. Science 2003, 301 (5638), 1380-2.
33. Le Roch, K. G.; Johnson, J. R.; Florens, L.; Zhou, Y.; Santrosyan,
A.; Grainger, M.; Yan, S. F.; Williamson, K. C.; Holder, A. A.;
Carucci, D. J.; Yates, J. R., III; Winzeler, E. A. Global analysis of
transcript and protein levels across the Plasmodium falciparum
life cycle. Genome Res. 2004, 14 (11), 2308-18.
34. Peng, J.; Schwartz, D.; Elias, J. E.; Thoreen, C. C.; Cheng, D.;
Marsischky, G.; Roelofs, J.; Finley, D.; Gygi, S. P. A proteomics
approach to understanding protein ubiquitination. Nat. Biotechnol. 2003, 21 (8), 921-6.
35. Ideker, T.; Thorsson, V.; Ranish, J. A.; Christmas, R.; Buhler, J.;
Eng, J. K.; Bumgarner, R.; Goodlett, D. R.; Aebersold, R.; Hood,
L. Integrated genomic and proteomic analyses of a systematically
perturbed metabolic network. Science 2001, 292 (5518), 929-34.
36. Liu, H.; Sadygov, R. G.; Yates, J. R., III. A model for random
sampling and estimation of relative protein abundance in
shotgun proteomics. Anal. Chem. 2004, 76 (14), 4193-201.
37. Zybailov, B.; Coleman, M. K.; Florens, L.; Washburn, M. P.
Correlation of relative abundance ratios derived from peptide ion
chromatograms and spectrum counting for quantitative proteomic analysis using stable isotope labeling. Anal. Chem. 2005,
77 (19), 6218-24.
38. Gabay, J. E.; Scott, R. W.; Campanelli, D.; Griffith, J.; Wilde, C.;
Marra, M. N.; Seeger, M.; Nathan, C. F. Antibiotic proteins of
human polymorphonuclear leukocytes. Proc. Natl. Acad. Sci.
U.S.A. 1989, 86 (14), 5610-4.
39. Zhao, C.; Nguyen, T.; Boo, L. M.; Hong, T.; Espiritu, C.; Orlov,
D.; Wang, W.; Waring, A.; Lehrer, R. I. RL-37, an alpha-helical
antimicrobial peptide of the rhesus monkey. Antimicrob. Agents
Chemother. 2001, 45 (10), 2695-702.
40. Filipenko, N. R.; MacLeod, T. J.; Yoon, C. S.; Waisman, D. M.
Annexin A2 is a novel RNA-binding protein. J. Biol. Chem. 2004,
279 (10), 8723-31.
41. Castro-Caldas, M.; Duarte, C. B.; Carvalho, A. R.; Lopes, M. C.
17beta-estradiol promotes the synthesis and the secretion of
annexin I in the CCRF-CEM human cell line. Mediators Inflammation 2001, 10 (5), 245-51.
42. Vadillo-Ortega, F.; Sadowsky, D. W.; Haluska, G. J.; Hernandez-Guerrero, C.; Guevara-Silva, R.; Gravett, M. G.; Novy, M. J.
Identification of matrix metalloproteinase-9 in amniotic fluid and
amniochorion in spontaneous labor and after experimental
intrauterine infection or interleukin-1 beta infusion in pregnant
rhesus monkeys. Am. J. Obstet. Gynecol. 2002, 186 (1), 128-38.
43. Vadillo-Ortega, F.; Estrada-Gutierrez, G. Role of matrix metalloproteinases in preterm labour. BJOG 2005, 112 (Suppl 1), 19-22.![]()
|
(protein ID) description |
control spectral count |
infected spectral count |
|
fold change |
|
(P04083) Annexin A1 |
22 |
53 |
23.54 |
3.1 |
|
(P05109) Calgranulin A (Migration inhibitory factor-related protein 8) |
83 |
115 |
18.73 |
1.9 |
|
(P08833) Insulin-like growth factor binding protein 1 |
0 |
14 |
17.56 |
16.2 |
|
(P31949) Calgizzarin (S100 calcium-binding protein A11) |
1 |
16 |
17.23 |
10.2 |
|
(Q9UBC9) Small proline-rich protein 3 (Cornifin beta) |
1 |
16 |
17.23 |
10.2 |
|
(P60709) Actin, cytoplasmic 1 |
23 |
47 |
16.7 |
2.7 |
|
(P07355) Annexin A2 |
14 |
35 |
16.17 |
3.2 |
|
(Q01469) Fatty acid-binding protein, epidermal (E-FABP) |
12 |
30 |
13.85 |
3.1 |
|
(P06702) Calgranulin B (Migration inhibitory factor-related protein 14) |
170 |
187 |
13.32 |
1.5 |
|
(P35322) Cornifin (Small proline-rich protein I) (SPR-I) |
4 |
18 |
12.84 |
4.9 |
|
(Q862Z5) Cystatin B |
10 |
24 |
10.54 |
3 |
|
(P14780) Matrix metalloproteinase-9 precursor (MMP-9) |
25 |
40 |
9.12 |
2.1 |
|
(P04217) Alpha-1B-glycoprotein precursor |
13 |
0 |
8.91 |
-8.7 |
|
(P04196) Histidine-rich glycoprotein precursor |
13 |
0 |
8.91 |
-8.7 |
|
(Q4R5C0) Cofilin-1 (Cofilin, nonmuscle isoform). |
0 |
6 |
7.01 |
7.7 |
|
(P13796) L-plastin (Lymphocyte cytosolic protein 1) |
26 |
36 |
5.73 |
1.8 |
|
(P08133) Annexin A6 |
8 |
16 |
5.46 |
2.5 |
|
(P03973) Antileukoproteinase 1 precursor |
26 |
8 |
5.33 |
-2.2 |
|
(Q28514) Glutathione S-transferase P |
9 |
17 |
5.29 |
2.4 |
|
(Q9GLV5) Cathelin. |
24 |
32 |
4.55 |
1.7 |
|
(P29034) S100 calcium-binding protein A2 |
0 |
5 |
4.49 |
6.6 |
|
(Q09666) Neuroblast differentiation associated protein AHNAK |
0 |
4 |
3.22 |
5.6 |
|
(P08246) Leukocyte elastase precursor |
0 |
4 |
3.22 |
5.6 |
|
(P16401) Histone H1.5 (Histone H1a) |
0 |
4 |
3.22 |
5.6 |
|
(P02545) Lamin A/C (70 kDaa lamin) |
0 |
4 |
3.22 |
5.6 |
|
(P25815) S-100P protein |
0 |
4 |
3.22 |
5.6 |