Open Access

Proteomics paves the way for Q fever diagnostics

  • Malgorzata Kowalczewska1Email author,
  • Zuzana Sekeyová2 and
  • Didier Raoult1
Genome Medicine20113:50

DOI: 10.1186/gm266

Published: 30 July 2011

Abstract

Q fever is a worldwide zoonosis caused by Coxiella burnetii. The disease most frequently manifests clinically as a self-limited febrile illness, as pneumonia (acute Q fever) or as a chronic illness that presents mainly as infective endocarditis. The extreme infectivity of the bacterium results in large outbreaks, and the recent outbreak in the Netherlands underlines its impact on public health. Recent studies on the bacterium have included genome sequencing, the investigation of host-bacterium interactions, the development of cellular and animal models of infection, and the comprehensive analysis of different clinical isolates by whole genome and proteomic approaches. Current approaches for diagnosing Q fever are based on serological methods and PCR techniques, but the diagnosis of early stage disease lacks specificity and sensitivity. Consequently, different platforms have been created to explore Q fever biomarkers. Several studies using a combination of proteomics and recombinant protein screening approaches have been undertaken for the development of diagnostics and vaccines. In this review, we highlight advances in the field of C. burnetii proteomics, focusing mainly on the contribution of these technologies to the development and improvement of Q fever diagnostics.

Coxiella burnetii and the diagnosis of Q fever

Coxiella burnetii is the infectious agent responsible for Q fever, which occurs worldwide [1]. Many reservoirs have been reported, including mammals, birds and arthropods (mainly ticks), but infectious aerosols produced by farm animals and pets, including those from feces, milk, hides and wool, are the most frequent source of human infection [1]. Person-to-person transmission is rare [1, 2], although sexual transmission has been documented [3]. Presentation of the disease is extremely variable. A non-immunized person develops a primary infection in 60% of cases (Table 1). This can lead to the acute disease (in 40% of cases), which mostly presents as a flu-like syndrome or as severe pneumonia; 2% of patients with acute disease are hospitalized [1]. In patients with pre-existing valvulopathy, infection can progress to the chronic form (in 2-5% of patients), which is characterized by blood-culture-negative endocarditis [1, 4]. The fever and characteristic vegetations (a mixture of bacteria and blood clots on heart valves) are frequently absent, making diagnosis difficult [1]. Importantly, Q fever is associated with high morbidity and mortality in pregnant women [1, 4], although only few such cases have been reported to date [2, 4]. The incidence of Q fever was recently re-evaluated by analyzing Q fever data collected at the French National Reference Center (FNRC) between 1985 and 2009 [5]. During this 25-year period, the FNRC identified 32 outbreaks in Europe, indicating that the number of Q fever cases was increasing [5].
Table 1

Main characteristics of the immune responses to C. burnetii infection occurring in the acute and chronic phases

Immune response

Acute phase

Chronic phase

Detection or exploration methods

Cells

T lymphocytes

Fewer T lymphocytes (CD4/CD8)

Flow cytometry

Total eradication of bacteria

No

No

qRT-PCR, qPCR

Granuloma formation

Yes

No, large vacuole

Immunohistochemistry

Detection of bacteria in granuloma/large vacuole

No, very weak

Yes

Immunohistochemistry and qRT-PCR, qPCR

Antibody production

IgG against phase I, IgM against phase II

IgG, IgM, IgA against both phase I and II

Serology (IFA)

Properties of monocytes from convalescent patients

Able to kill C. burnetii and migrate through the endothelium

Unable to kill C. burnetii or migrate through the endothelium

qRT-PCR, qPCR targeting C. burnetii, apoptosis detection (TUNEL assay)

Cytokines

IFN-γ and TNFα, mediated through TLR4 activation

IL-10

qRT-PCR targeting the specific cytokines

Immune response

Efficient

Deleterious

-

IFA, immunofluorescence assay; IFN-γ, Interferon-gamma; IgG, Immunoglobulin G; IgM, Immunoglobulin M; IgA, Immunoglobulin A; IL-10, Interleukin 10; qRT-PCR, quantitative real time polymerase chain reaction; qPCR, quantitative polymerase chain reaction; TLR4, Toll-like receptor 4; TNFα, tumor necrosis factor α; TUNEL, terminal deoxynucleotidyl transferase dUTP nick end labeling.

In the recent outbreak of Q fever in the Netherlands, a rapid increase in human Q fever cases (3,523 in total) was observed between 2007 (182) and 2009 (2,361) [2, 6, 7]. Q fever had already been endemic in the Netherlands, and the disease was previously diagnosed in dairy goats and dairy sheep in 2005 [2, 7]. The sudden increase may have been linked to a more virulent subtype of C. burnetii [2, 6, 7]. Indeed, several genotypes of C. burnetii were involved in the Dutch outbreak. When tested by multiple-locus variable-number tandem repeat analysis (MLVA) typing, the strains were found to differ by only a single repeat difference and it was thought that they might represent microvariants of a hypervirulent strain [7]. The rising number of reported outbreaks over the past 10 years worldwide is, however, considered to be a consequence of more efficient detection [6]. In the Dutch outbreak, several factors were considered to have contributed to the increase in Q fever cases, including: (i) the high density of farms in the regions where the bacterium is endemic, (ii) asymptomatic infection in the majority of infected animals, and (iii) more efficient diagnostic tests [2, 6, 7]. Nevertheless, important factors still need to be assessed including the persistence of C. burnetii in the environment and in different hosts, and the potential to prevent and control the next outbreak. Q fever has become a serious public health problem in many areas not previously known as endemic zones. The bacterium is highly infectious and, consequently, the Centers for Disease Control and Prevention (CDC) in the USA have classified it as a category B bioterrorism agent [8].

In the past decade, technological developments have contributed an improved understanding of some of the pathological aspects of the intracellular life-cycle of C. burnetii and the role of host immunity. The diagnosis of C. burnetii infection still lacks sensitivity and specificity, especially at the early stage of infection. Therefore, recent efforts have focused on identifying strain-specific or clinical-outcome-specific protein markers (Table 2). Here, we review recent studies on C. burnetii, focusing on the contribution of proteomic technologies to our understanding of C. burnetii infection and to the diagnosis of Q fever.
Table 2

Main protein candidates for serodiagnosis that have been cross-validated by proteomic studies

Protein (locus-tag)

Identification

MW (kDa)

pI

Protein function

Nature of protein

Peptide signal sequence

Nature of analyzed samples

DT

Clinical significance

Reference(s)

CBU_0952

Acute disease antigen A (adaA)

25.9

8.67

Unknown

Membrane

MKKLTVTFLTFISIFFAATAAFA

Cb isolates

BT, IP

Marker of acute Q fever

[31, 63]

CBU_0612

Putative outer membrane chaperone protein (ompH, Skp)

18.8

9.71

Molecular chaperone, interacts with unfolded proteins

Membrane*

MIKRLLSAICLSVAMIWSVAAVAQTVGLVD

Patient sera, Cb NM II TPE

IP, RP

Marker of Q fever endocarditis, SP with Q fever patients (general)

[56, 57]

CBU_0937

Hypothetical protein

51.4

8.99

Unknown

Membrane

MTSKLVISALGLCVSGALSTTLAST

mAbs, Cb NM II TPE, RP-based ELISA/HS

IP, BT

Marker of Q fever endocarditis. Marker of phase II

[17, 56, 58]

CBU_1910

Outer membrane protein (com1)

27.6

9.08

Protein disulfide oxidoreductase, unknown role in pathogenesis

Membrane

MKNRLTALFLAGTLTAGVAIAAPSQF

mAbs, Cb NM II TPE

IP, BT, RP

SP with both acute Q fever and Q fever endocarditis. Marker of both phase I and phase II

[17, 58, 65, 6769]

CBU_0236

Elongation factor Tu (tuf-2)

43.5

5.32

GTP-dependent binding of aminoacyl-tRNA in protein biosynthesis

Soluble*

 

mAbs, TPE Cb NM II, HS, AS (infected/vaccinated guinea pigs)

IP

SP, marker of acute Q fever

[31, 58, 65, 68]

CBU_0092

Tol-pal system protein (YbgF)

34.3

6.46

Critical for maintaining integrity of bacterial outer membrane Involved in protein-protein interactions

Membrane

MRLIKMKIKTLCVSSALAALMLSAPLTWADA

TPE Cb NM I and II HS Q-fever (general), AS (immunized guinea pigs) protein microarray

IP, RP

Phase II-specific marker (early diagnosis of acute Q fever), marker of Q fever (general)

[68, 69]

CBU_0311

Outer membrane porin (Coxiella porin P1)

26.8

8.44

Able to form pore in lipid bilayers

Membrane* OM location shown for Cb NM I

METTTKLAIGVSALCCLASAAFAGGPD

ELISA and ELISPOT based on RP/AS IP: HS, and AS (infected/vaccinated guinea pigs)

RP, IP

Marker of Q fever (general), marker of acute Q fever; applications for drug and vaccine development

[31, 67]

CBU_1718

Chaperonin (GroL)

58.284

5.14

Protein folding, ATP hydrolysis

Soluble

 

HS/TPE Cb NM II/RP; IP HS, and AS (infected/vaccinated guinea pigs)

IP, RP

Marker of Q fever (general), marker of acute Q fever

[31, 65]

CBU_0229

50S ribosomal protein L7/L12 (RplJ)

13.2

4.71

Binding site for several factors in protein synthesis

Membrane

MAQLSKDDILEAVANMSVMDVVDLVKAMEEKFGVSAQAAIAVAGPVAGGEA

IP: HS, and AS (infected/vaccinated guinea pigs)

BT, IP

Marker of both phase I and phase II, marker of acute Q fever

[17, 31]

CBU_0263

DNA-directed RNA polymerase subunit alpha (rpoA)

35.5

5.61

DNA-dependent RNA polymerase transcription

Soluble

 

OMP fraction of Cb NM II and CbuG_Q212 II; Phase 1 HS (chronic )

IP

Marker of chronic Q fever

[2, 69]

CBU_1916

Universal stress protein family

15.78

6.58

Stress response

Soluble*

 

OMP fraction of Cb NM II and CbuG_Q212 II; Phase 1 HS (chronic)

IP

Marker of chronic Q fever

[1, 69]

I, phase I; II, phase II; AS, animal sera; BT, biotyping; Cb, Coxiella burnetii; DT, discovery technology; HS, human sera; IP, immunoproteomics; mAb, monoclonal antibody; MW, molecular weight; NM, Nine Mile; OM, outer membrane; OMP, outer membrane protein; pI, isoelectric point; RP, recombinant protein-based approaches; SP, seroreactive proteins; TPE, total protein extract.

Soluble (cytosolic). Membrane (having a signal peptide that directs protein to the cell membrane). *More than two-fold more abundant in the LCV stage than in the SCV stage. Proteins common to SCV and LCV.

Coxiella burnetii

Bacteriology

C. burnetii is a small (0.3-1 μm) obligate intracellular Gram-negative coccobacillus. The cell wall structure of this bacterium displays characteristics similar to those of Gram-negative bacteria, but does not stain reliably with Gram stain; for this reason, Gimenez staining has been used historically [9]. C. burnetii has been classified as a member of the γ-proteobacteria [1, 8].

Genetic variability of isolates

Currently, the genome sequences of six C. burnetii strains (CBuG Q212, CBuK Q154, Dugway 5J108-111, RSA331, RSA493 and MSU Goat Q177) are available; Nine Mile RSA493 was the first C. burnetii genome to be sequenced [10, 11]. C. burnetii isolates also harbor different plasmid types (QpH1, QpRS, QpDG or QpDV), which define specific genovars [8]. It remains to be determined whether these plasmids are involved in virulence.

Voth et al. [12] suggested that C. burnetii plasmids play an important role in host-cell modifications [12]. Proteins encoded by plasmid QpH1 (such as CBUA0014) are translocated into the host cell by the Dot/Icm type IV secretion system (T4SS). Compared to those of other strictly intracellular bacteria, the C. burnetii genome harbors multiple copies of insertion sequence (IS) elements that are probably involved in genomic plasticity [13], but it possesses fewer pseudogenes, suggesting a recent genome reduction event [10]. The T4SS, together with genes encoding a large proportion of basic proteins, including ion exchangers that enable the bacterium to live in an acidic environment, are characteristic of the C. burnetii genome [10].

Phase variation

In addition to the reported genetic variability, antigenic variation due to different lipopolysaccharide (LPS) structures [3, 14] and sugar compositions [15] is common among C. burnetii isolates. This is frequently referred to as phase variation. Smooth, full-length LPS is characteristic of isolates from naturally infected biological samples (phase I, virulent), whereas rough, truncated LPS is found in sub-cultured bacteria (phase II, avirulent). Unique C. burnetii carbohydrates have been identified and studied in detail [14, 16]. Among these are 3-C(hydroxymethyl)-L-lyxofuranose, known as dihydroxystreptose (Strep), and 6-deoxy-3-methyl-D-gulopyranose, known as virenose (Vir), a unique marker of phase I virulent strains [14]. Recently, the virulent phase I and avirulent phase II variants of the Nine Mile RSA493 and RSA439 strains of C. burnetii were compared using tandem liquid chromatography mass spectrometry (LC-MS/MS) [17]. This study allowed the identification of strain-specific and clinical-outcome-specific protein markers [17] (Table 3). A total of 235 and 215 non-redundant proteins were identified from phase I and II variants, respectively. The most interesting outcomes of this work were the identification of 17 proteins that are involved in LPS biosynthesis, the first identification of DotD protein of the T4SS, and finally the identification of two ankyrins (CBU_0898 and CBU_1482). Biomarkers of LPS phase I were identified and might contribute to development of more sensitive diagnostic tests [17].
Table 3

Proteomic approaches for C. burnetii biomarker selection

Approach

Technique(s)

Cbisolates (culture method*)

Sera/mAbs

Applications

Identified proteins

Reference(s)

Biotyping

      

Detection of specific markers for Cb isolates

MALDI-TOF MS

Cb: RSA493, BUD, Priscilla (CYSEE)

-

Optimization of method for typing Cb for specific strains or clinical isolates

RSA493-specific: CBU_1637, CBU_0401, CBU_0394, CBU_1592, CBU_1378, CBU_0403, CBU_0078, CBU_0961, CBU_1698, CBU_0644, CBU_1055 Priscilla-specific: CBU_0149, CBU_0438, CBU_0168, CBU_0745 BUD-specific: CBU_1989, CBU_2085

[20, 54]

Identification of Cb strains and isolates

MALDI-TOF MS

Cb: NMI, Australian QD, M44, KAV, PAV, Henzerling, Ohio (CYSEE)

-

Cb isolate typing or diagnosis

Mass spectral peaks (1000-6000 Da), species-selective and strain-specific

[55]

Proteome of Cb NM I

2-DE and nanoLC-ESI MS/MS, LC-MALDI TOF/TOF MS, MALDI-TOF MS

TPE Cb RSA493, NM I (CC)

-

Markers of early stage infection, and therapeutic or vaccine development

197 distinct proteins. Vir and Strep: CBU_0691, CBU_0683 SP: CBU_0091, CBU_0109, CBU_0395, CBU_0867, CBU_1221, CBU_1268, CBU_1718, CBU_1910

[19]

In silico prediction of OMPs and identification of Cb (NM I) LP

Bioinformatics

Cb RSA493 genome sequence

-

Vaccine development or serodiagnosis

21 predicted OMPs and 9 LP; LP: CBU_1190 (LolA), CBU_1829 (LolB)

[59]

Proteome of Cb strain NM phase II

2-DE, 2D SDS-tricine PAGE, MALDI-TOF

TPE Cb NM II (CC, Vero)

-

Markers of active Cb infection, serology or therapeutic development

Proteins involved in Cb pathogenesis and survival mechanisms (NM II)

[94]

Proteome of Cb I and II

LC-MS/MS

Cb NM I and II (CYSEE)

-

Phase I and phase II distinct biomarkers, serology or biotyping (blood transfusion)

150 proteins reported (pI > 9. 5); virulence type I and T4SS: CBU_0884, CBU_0085, CBU_0318, CBU_0744, CBU_1099, CBU_1352, CBU_0338, DotD protein (CBU_1643); Anks: CBU_0898, CBU_1482; 7 enzymes involved in LPS phase I synthesis: CBU_0676, CBU_0678, CBU_0674, CBU_0681, CBU_0682, CBU_0683, CBU_0691, CBU_0846, CBU_1657

[17]

Cb secretome

Tricine-SDS PAGE, ESI-MS/MS, bioinformatics

Cb NM II (CC, Vero)

Cytoplasmic fraction from infected Vero cells

Characterization of T4SS, drug development

50 T4SS effector candidates: CBU_1440, CBU_0312, CBU_1091, CBU_1386, CBU_1518, Orf145, QpH1_p21, CBU_1297, CburD_01001397

[33]

Two Cb strains, subproteome (OMPs) and candidate proteins for serodiagnosis

Tris-Tricine SDS-PAGE, doubled SDS-PAGE, IP 2-DE, MALDI TOF/TOF

Cb strains NM RSA 493 II (acute) and CbuG_Q212 II (chronic), (CC, Vero)

OMP-enriched fraction, 1 HS (chronic)

Subproteome of Cb, chronic Q fever markers

86 identified OMPs. SP: htpB, CBU_0236, CBU_0263, CBU_1471, CBU_0572, CBU_0235, CBU_1916, CBU_0612, CBU_0937

[56]

Immunoproteomics or serology

    

Candidate proteins for acute Q fever serodiagnosis

IP/serodiagnosis

17 Cb strains (CC) (BGM or L929)

RP ada (rada), AS immunized with rada

Marker of acute Q fever

adaA (CBU_0952)

[31, 63]

Identification of Cb cell-variant-specific common SCV/LCV proteins

IP (2-DE, MALDI-TOF)

Purified SCVs and LCVs

HS (convalescent-phase, acute Q fever), AS from infected or vaccinated guinea pigs

Subunit vaccines or serodiagnostics for acute Q fever, unique SCV/LCV markers

Proteins that are differentially expressed in SCV and LCV forms. SP: CBU_1718, CBU_0236, CBU_0229, CBU_1943, CBU_1416, CBU_0952, CBU_0963, CBU_0737, CBU_0497, CBU_1200

[31]

SP for serodiagnosis of Q fever endocarditis

IP (2-DE/MALDI-TOF)

TPE Cb NM II (CC, Vero)

HS (acute Q fever or IE Q fever)

Markers of chronic Q fever (IE), serodiagnosis

CBU_0612, CBU_0480

[57]

Identification of Cb proteins reacting with Cb mAbs

IP (2-DE/MALDI-TOF) RP-based ELISA

TPE Cb NM II (CC, Vero)

Specific mAbs; HS acute or chronic (IE)

Markers of chronic Q fever (IE), serodiagnosis

Q fever markers (general): CBU_1910, CBU_0236 Chronic Q fever marker (IE): CBU_0937

[58]

SP for early serodiagnosis of Q fever

IP (2-DE, LC-MS/MS) (pH 5-8, pH 3-10; phase I and phase II antigens )

TPE Cb NM I and II (CC, L929), Cb NM RSA493 I (CYSEE)

AS from immunized guinea pigs

Markers of early stage acute Q fever, serodiagnosis or vaccine development

Phase-I-specific SP: CBU_1706, CBU_12190, CBU_0495, CBU_0780, CBU_0955, Phase-II-specific SP: CBU_1290, CBU_0235, CBU_0215, CBU_0572, CBU_1398, CBU_0236, CBU_0092, CBU_1241, CBU_1396, CBU_1227, CBU_0481, CBU_0299, CBU_0481, CBU_0495, CBU_0482, CBU_0937, CBU_0236

[68]

RP-based approaches

     

Candidate RPs for Q fever vaccine development and serodiagnosis

TAP products and expression of selected SP

 

HS (acute, chronic phase vaccine)

Serodiagnosis or vaccine development

SP: CBU_0008, CBU_0381, CBU_0612, CBU_0781, CBU_1115, CBU_1143, CBU_1157, CBU_1249, CBU_1853, CBU_1869 Top candidates: CBU_0781 (AnkG), CBU_1115 (lipoprotein), CBU_1143 (YajC)

[66]

Candidate RPs for Q fever vaccine development and serodiagnosis

Protein microarray

 

HS Q fever (general)

Markers of Q fever (general)

SP: CBU_1910, CBU_0891, CBU_0109, CBU_1143, CBU_0612, CBU_0092, CBU_0545, CBU_1398, CBU_0630, CBU_1513, CBU_1719, CBU_0229, CBU_0653

[69]

Candidate RPs for Q fever vaccine development and serodiagnosis

ELISA (HS), ELISPOT (AS)

11 RPs, Cb NM RSA493 I

HS Q-fever (IFA-positive, convalescent), HS chronic (transgenic mice, immunized with Cb NM RSA493 I)

Subunit vaccine development, serodiagnosis

SP: CBU_1910, CBU_1716, CBU_612, CBU_718, CBU_311

[67]

Identification of Cb SP

IP (2D, LC-MS), tripartite fusion RP

TPE Cb (I and II Henzerling strain) (CC, Vero)

HS Q fever (general)

Serodiagnosis or vaccine development

SP: CBU_0091, CBU_0109, CBU_0395, CBU_0867, CBU_1221, CBU_1268, CBU_1718, CBU_1910 Six RP(Cb II): GroEL, Com1, RecA, EF-Tu, OmpA-like and FtsZ

[65]

I, phase I; II, phase II; adaA, acute disease antigen A; AS, animal sera; Cb, Coxiella burnetii; IE, infective endocarditis; HS, human sera; IP, immunoproteomics; LP, lipoproteins; MAb, monoclonal antibody; MW, molecular weight; nanoLC-ESI MS/MS, nano liquid chromatography-electrospray ionization mass spectrometry; NM, Nine Mile; OM, outer membrane; OMP, outer membrane protein; RP, recombinant protein; SP, seroreactive proteins; TAP products, transcriptionally active PCR products, TPE, total protein extract; Vir and Strep: synthesis of virenose and streptose.

*CYSEE, cultured on yolk sacs in embryonated eggs; CC, cultured in cell lines.

Culture conditions

C. burnetii is cultured in level 3 biosafety laboratory conditions. The bacterium can be propagated under laboratory conditions in cell lines [18] or in embryonated eggs [19, 20]. C. burnetii is able to infect various types of cells, including monocyte-macrophage systems and macrophage, fibroblast and epithelial cells [3, 21]. The isolation of bacteria from clinical samples is carried out using the shell vial centrifugation technique [1]. C. burnetii was recently described as being cultivable in axenic medium (a medium that is free of contaminating organisms) under laboratory conditions [22]. The bacteria can be grown when incubated in a mesophilic atmosphere in an acidified citrate medium that is enriched with cysteine and casamino acids [22] and contains divalent metal cations. LimB (CBU_1224a), a unique C. burnetii lipoprotein identified using matrix-assisted laser desorption ionization-time of flight/time of flight MS (MALDI-TOF/TOF MS), serves as surface receptor for such ions and may be involved in C. burnetii replication and pathogenesis [23]. Notably, the C. burnetii proteome includes a eukaryotic-like Δ24 sterol reductase homolog, CBU_1206, which might be involved in the intracellular growth of the bacterium [24].

Host-bacteria interactions

Physiopathology

Immune control of C. burnetii infection depends on T lymphocytes: chronic Q fever has been shown to develop preferentially in a nude mouse model that has a greatly reduced number of T cells [8]. In acute-phase disease, granuloma formation is a hallmark of an efficient immune response (Table 1), but C. burnetii is frequently missing from granulomas, resulting in the inability of PCR or immunocytochemistry tests to produce a positive diagnosis. In the chronic phase of infection, the immune response is inefficient or deleterious [8] (Table 1). The inoculum size, route of infection, host factors, and pathogenic potential of strains all play a role in the clinical presentation of acute Q fever [8]. Age, circadian rhythms and sex-related differences [25] may be involved in the development of the chronic form. Female sexual hormones (17-β-estradiol) are thought to have a protective role [8, 26].

Intracellular survival

C. burnetii, an obligate intracellular bacterium, has evolved not only to survive but to thrive in the phagolysosome. The intracellular survival of C. burnetii is characterized by two distinct morphological forms: the large cell variant (LCV), which has evolved to persist within the acidified phagolysosome of monocytes or macrophages, and the 'spore-like' small cell variant (SCV), which can persist both in the phagolysosome and in extreme environmental conditions [27]. How C. burnetii mediates the establishment of the phagolysosomal-like compartment in which it resides and replicates is not well understood. We do know that bacterial protein synthesis is required for this process, suggesting that bacterial proteins directly influence the biogenesis of the C. burnetii-occupied vacuole [28, 29]. Some of these mechanisms have been elucidated using proteomics and molecular biology [2831]. Both developmental forms (SCV and LCV) were analyzed by a combination of two-dimensional electrophoresis (2-DE) and MS after differential fractionation [31]. Fifty proteins were identified in vitro from cytoplasm from Vero cells that were infected with C. burnetii (Table 3), but their roles have not been determined [31, 32]. A Dot/Icm-dependent translocation in host cytoplasm was demonstrated for only a few of these, including Coxiella effector proteins such as CpeA (CBUA0006), CpeB (CBUA0013), CpeC (CBUA0014), CpeD (CBUA0015), CpeE (CBUA0016) and CpeF (CBUA0023) [29, 32]. The T4SS candidate proteins identified by proteomic approaches remains to be functionally validated [31, 32]. The majority of the identified proteins were found to be important for the intracellular survival of bacteria and were involved in RNA and DNA processing [33], confirming the results of Coleman et al. [31]. Notably, most of the identified proteins had basic physicochemical properties and contained eukaryotic motifs (such as ankyrin repeat-containing domains (Anks)) [33]. When Legionella pneumophila was used as a surrogate host, several different C. burnetii Anks could be delivered into the host cells by the L. pneumophila T4SS, suggesting that C. burnetii T4SS effector proteins affect host cell signal transduction pathways [28, 34]. Moreover, when ectopically expressed, the C. burnetii Anks localized to a variety of subcellular regions in mammalian cells [32]. An understanding of the trafficking and role of Anks and of the secretion of T4SS effectors could help in selective drug design.

Current approaches for diagnosis of Q fever

The major issue for Q fever diagnosis is the non-specific clinical picture produced by the disease. Early stage detection of C. burnetii lacks specificity and is not sensitive enough for diagnosis of acute Q fever [35]. Moreover, the serological profiles of acute and chronic Q fever differ [5]. In acute cases, immunoglobulin M (IgM) is produced against phase I and II variants, and patients will have immunoglobulin G (IgG) antibodies against phase II antigens. In chronic Q fever, high levels of IgG against phase I and II antigens are produced [5] and persist for months or years after the initial infection. Increased IgG and immunoglobulin A (IgA) antibodies against phase I antigens are also often indicative of chronic Q fever [36]. In the early stage of infection (<10 days), the specific antibodies remain undetectable [37]. The prevalence of auto-antibodies, including antibodies similar to those seen in cases of rheumatoid arthritis and lupus, presents another problem in Q fever diagnosis [21].

Direct diagnosis

The laboratory diagnosis of Q fever depends on the stage of disease (acute or chronic), which in turn determines which sample should be used for analysis: blood, cerebrospinal fluid, bone marrow, cardiac valve biopsy, vascular aneurysm or graft, bone biopsy, liver biopsy, milk, placenta, fetal specimens in cases of abortion, or cell culture supernatants [38]. The choice of technique also depends on the available laboratory capabilities and on the clinical presentation of disease.

Immunodetection

In patients with chronic Q fever who are undergoing treatment, immunodetection of C. burnetii in fresh tissue samples or samples after formalin fixation and paraffin embedding may be very useful [1]. Several techniques can be employed: either an immunoperoxidase technique or immunofluorescence with polyclonal or monoclonal antibodies is frequently used [1]. New diagnostic tools, including autoimmunohistochemistry [39] and immunohistochemical peroxidase-based methods, have been reported for the diagnosis of blood culture-negative endocarditis [1]. The specificity of immunodetection is strongly correlated to the quality of the antibodies used.

Molecular tests

Several PCR-based assays have been developed in the past decade [1, 37, 40, 41]. Although lacking sensitivity, PCR targeting the htpAB-associated repetitive element, which is present in 20 copies in the genome of C. burnetii [10], is routinely used to detect bacteria in cell cultures and clinical samples from both acute and chronic Q fever patients [1]. Light cycler nested-PCR (LCN-PCR) has been optimized for the early diagnosis of acute Q fever [40] when antibodies are absent [37]. This test, together with serology, is recommended in the first 2 weeks of acute Q fever [37]. Real-time quantitative PCR assay targeting the multicopy insertion sequences IS1111 and IS30a is also highly specific and sensitive [40, 41]. Detection of the adaA gene (encoding acute disease antigen A) can be used to confirm acute Q fever [1]. Overall, PCR is useful for detecting C. burnetii in the early course of infection, following antigen shedding in livestock, or when applied to biopsies from patients with chronic Q fever. Molecular testing is generally recommended in addition to serology [2] but the possibility of reagent contamination leading to false-positive results is its major drawback [2, 42, 43].

Serology

The microbiological diagnosis of Q fever is usually based on serology and most commonly uses an indirect immunofluorescence assay (IFA) [2, 5]. The cut-off for serological titres was first established in 1994 [44] but has been revised recently [5]. The diagnosis of Q fever is performed using different methods: a complement fixation test with commercially available antigen preparations combined with real-time PCR [45], enzyme-linked immunosorbent assay (ELISA) [46], IFA, and nested PCR [46]. ELISA helps in the diagnosis of Q fever after the fifth day of infection, whereas PCR is an efficient diagnostic tool during the first few days of infection [46].

According to guidelines for Q fever diagnosis, combined approaches, including PCR (≤7 days) and IFA (≥7 days), are strongly recommended in the early phase of infection [5, 37, 47] (Figure 1). In the case of chronic Q fever, especially with endocarditis, a positive result from systematic serological testing has been included as a major criterion in the modified Duke criteria [48]. When cross-reactivity with Legionella micdadei [49], Bartonella [50] and Rickettsiae [51] is observed, immunoblotting with adsorbed cross-reacting antigens is recommended.
Figure 1

Flow diagram showing the evolution of Q fever disease in the absence of treatment. Q fever disease starts with asymptomatic primary infection (0-10 days), followed by acute Q fever (10 days to 3 months), and some subjects then develop the chronic form of disease (>3 months). The clinical sample used initially for the detection of C. burnetii at each stage is patient serum. The strategy for early-stage Q fever diagnosis consists of combined approaches, including PCR (≤7 days) and antigen detection by immunofluorescence assay (IFA) or enzyme-linked immunosorbent assay (ELISA) (≥7 days) performed on whole-cell antigen (formalin-inactivated bacteria). Immuno-PCR (IPCR) performed with whole-cell protein extracts may also be a promising detection tool. The diagnosis of chronic Q fever relies mainly on serology. The cut-off stands at (i) IgM phase II ≥25 and IgG phase II (and I) ≥200 for acute Q fever serodiagnosis; and (ii) IgG phase II and I ≥1,600 associated with the presence of IgA phase I ≥50 for chronic Q fever serodiagnosis. IgM may be still detectable in cases of chronic Q fever. The protein candidates for serodiagnosis selected by several proteomic studies are shown in the circles. In the centre, the most antigenic proteins, namely CBU_1910 (Com1) and CBU_1718 (GroEL), as well as whole-cell antigen, are versatile markers of Q fever.

The InoDiag automated fluorescence multiplexed antigen microarray method [52] has been compared with the IFA reference method for the detection of C. burnetii IgM. The advantages of the InoDiag technique are speed of analysis, the need for only a small quantity of sampled serum (5 μl) and multiplexing [53]. The sensitivity and specificity obtained by automated assay for diagnosis of the acute form were excellent, and the serological parameters obtained for serodiagnosis of Q fever endocarditis were also adequate [52]. This is a first step towards IFA standardization [52, 53].

Proteomics

Recent technological developments in the field of molecular medicine have moved beyond genomics and transcriptomics to proteomics, with the goal of characterizing the impact of disease and therapy on cellular networks. Advances in proteomics-based research provide potential for the development of efficient diagnostic and therapeutic assays (Figure 1). Depending on the availability of clinical samples (storage, standardization and cohort), methods for proteomic analysis include mass spectrometry (MS), gel-based proteomics, 2-DE, differential gel electrophoresis (DIGE), immunoproteomics, recombinant protein-based arrays, and methods for the analysis of post-translational modifications (PTMs).

MS-based approaches

Several recent proteomics studies have been undertaken to identify clinical biomarkers that facilitate the accurate detection of the infectious agent, and offer new insights into inter- or intra-species relatedness. Several attempts have been made to characterize the whole proteome of C. burnetii, aiming to identify biomarkers that are useful in diagnosis or vaccine production for different strains or isolates (Table 3) [19, 20, 54]. These studies have helped to determine appropriate conditions for MS analysis, focusing on different matrices that can be used (such as α-cyano-4-hydroxycinnamic acid is a good matrix choice for samples with molecular weight (MW) <10,000 Da; sinapinic acid is an appropriate matrix choice for samples with MW >10,000 Da; or 2,5-dihydroxybenzoic acid is a good a matrix choice for hydrophobic compounds) and the nature of the sample (such as intact bacterial cells, cell-free extracts). Altogether, these studies have improved the MS-based laboratory pipeline.

Characteristic and reproducible MS fingerprints containing unique biomarker profiles have also been obtained. This approach was applied for C. burnetii strain and phase identification by two independent laboratories for strains NMI, Australian QD, M44, KAV, PAV, Henzerling and Ohio [55] and for strains RSA493, BUD and Priscilla [20, 54]. The method was validated by the prediction of samples in an independent test set with 100% sensitivity and specificity for five out of six strain classes [55]. Differences in the ion-signal profiles of three isolates, RSA493, BUD and Priscilla, were observed for peptides in the mass range 3-18 kDa [20, 54]. In the recent work of Papadioti et al. [56], the outer-membrane protein (OMP) fractions of C. burnetii strains Nine Mile RSA 493 and CbuG_Q212 (phase II) were compared using sodium dodecyl sulphate-polyacrylamide gel electrophoresis (SDS-PAGE) combined with MS/MS analysis. Markers of chronic Q fever, such as CBU_0612 and CBU_0937, were identified [5658] with agreement to predicted in silico C. burnetii OMPs [59].

When compared with conventional phenotypic and molecular identification methods, the implementation of MS in clinical laboratories could improve both the speed and sensitivity with which human pathogenic infections are diagnosed [60, 61]. Nevertheless, proteomic approaches such as MALDI-TOF should not completely replace traditional diagnostic techniques in clinical microbiology, even though these traditional approaches have a number of shortcomings including the need for time-consuming biochemical and antibiotic sensitivity tests [60]. Recently, Hernychova et al. [62] demonstrated that C. burnetii can be identified rapidly at the species level by MALDI-TOF. To date, however, no routine method for the identification of C. burnetii clinical isolates has been shown to be fully reliable, probably because of the restrictions in culturing and handling C. burnetii. Further optimization of C. burnetii culture on solid media should facilitate its improved identification by routine biotyping.

Immunoproteomics

Despite the availability of sensitive and specific laboratory tests, the diagnosis of Q fever remains difficult. Moreover, a differential diagnosis to distinguish chronic (mainly endocarditis) from acute Q fever is greatly needed. Thus, several immunoproteomic studies, combining the use of combine 2-DE immunoblots and MS, have set out to find specific biomarkers of Q fever for the development of accurate diagnostic tools (Tables 2, 3).

To date, only a few studies have investigated the possibility of differentiating between acute and chronic Q fever [57, 58, 63]. Several markers have been proposed: (i) a marker of acute Q fever, adaA (CBU_0952) [63], and (ii) CBU_0612 (OmpH) and CBU_0480 (an arginine repressor), which were identified as promising markers for patients with Q fever endocarditis [57]. In another study, Q fever-specific proteins, namely the CBU_0937 protein, the OMP Com1 (CBU_1910) and elongation factor Tu (CBU_0236) were found to be discriminated by monoclonal antibodies [58]. Two of these proteins (CBU_0937 and CBU_1910) were cloned, expressed and tested by ELISA with sera from patients with acute and chronic Q fever [58]. Com1 (CBU_1910) has been widely studied [31, 57, 6467] and is currently used for seroimmunological screening. Although tests using these immunoreactive proteins (CBU_0937 and CBU_1910) were neither sensitive nor specific enough for routine clinical application, the serological parameters for Com1 protein (CBU_1910) were cross-validated [58] and were in the same range as those reported by Beare et al. [66]. Moreover, Papadioti et al. [56] also demonstrated the seroreactivity of proteins CBU_0937 and CBU_0612 by two-dimensional immunoblot performed with serum from a patient with chronic Q fever [56].

Recent work by Deringer et al. [68] has raised the possibility of early- and late-stage serodiagnosis. These authors evaluated the IgG-specific response in a guinea pig model following vaccination with the Nine Mile strain of C. burnetii. Nine novel seroreactive C. burnetii proteins were identified (Table 3). Furthermore, several immunoreactive proteins from this study were identified in other studies as being immunoreactive with human Q fever sera [31, 57, 66, 69]. This study did not, however, identify specific protein markers for each phase (I and II) separately. Notably, the identification of seroreactive C. burnetii proteins with low homology to other proteins seems to be promising for serodiagnosis because of the likelihood of low cross-reactivity. However, the low similarities of CBU_0937 with proteins in other bacteria were not sufficient for it to be considered useful as a specific marker. The serological operating parameters for Q fever serodiagnosis using CBU_0937 showed low sensitivity, even though the specificity was acceptable [58]. For patients with acute Q fever and endocarditis, the results were in the same range, indicating the low diagnostic potential of CBU_0937 [56, 58].

Multiplexed biomarker protein patterns have a significantly higher positive predictive value (PPV) for disease discrimination. Immunoproteomic studies have been used to build a library of potential diagnostic or vaccine-related protein targets in several bacterial species: Chlamydia trachomatis [7072], Helicobacter pylori [7377], Francisella tularensis [7882], Shigella flexnerii [83, 84], Tropheryma whipplei [85, 86] and Bartonella henselae [87, 88]. Indeed, recent technological progress has enabled high-throughput, large-scale screening in miniaturized formats, such as protein microarrays. The laboratory pipeline could be enhanced by the validation of discovered diagnostic value (Figure 2). Some of the comprehensive studies performed on selected immunoproteomic targets were previously performed using molecular approaches. One such study involved H. pylori urease, which has diagnostic value (in the13C urea breath test (UBT) and in UBT-C13/UBT-C14 urease activity-based tests) and is a vaccine candidate [74]. In addition, these immunoproteomic studies were not applied for routine diagnostics, but contributed to the selection, and in some cases validation, of specific biomarkers. Immunoproteomics is time consuming, but has been an important first step in biomarker discovery. Further progress will probably depend on the miniaturization of clinical assays and the use of recombinant proteins.
Figure 2

Proteomic technologies used in applied research on C. burnetii pathogenesis. Several proteomic approaches have been used to identify biomarkers of Q fever or to characterize the proteome of C. burnetii. (a) Laboratory pipeline for biotyping. Biotyping of C. burnetii is not yet applied routinely because of restrictions in manipulating the organism, which is a potential bioterrorism agent. With the recent development of axenic solid culture for C. burnetii, however, the laboratory isolation of strains from blood- culture-negative samples associated with endocarditis (chronic Q fever) or from a variety of other samples such as blood or rhinopharyngeal swabs (acute Q fever) might be possible. The sample or bacterial products are subjected to analysis by matrix-assisted laser desorption ionization-time of flight/time of flight mass spectrometry (MALDI-TOF/TOF MS). Colonies of C. burnetii are picked from solid medium, co-crystallized with matrix, and processed for MALDI TOF MS analysis. The obtained MS spectra are analyzed against an available database, which allows identification of the bacteria. In parallel, classical phenotypic identification methods, including Gimenez- or Gram-staining of bacteria and biochemical tests, can be applied to confirm the identity of bacteria. (b) Laboratory pipeline for immunoproteomics. The whole-cell protein extract or fraction (such as sarcosyl-insoluble fraction, containing mainly membrane proteins) is resolved on two-dimensional (2D) acrylamide gels. The resolved proteins are stained (using silver nitrate or Coomassie blue) or transferred onto nitrocellulose or polyvinylidene fluoride (PVDF) membranes and then processed for immunoblotting with sera. The sera are from patients or animals with Q fever (general, acute or chronic Q fever) and from naïve subjects (control group). The immunoblots are analyzed and compared to silver-stained gels (using commercially available software). This analysis can be improved by statistical methods (such as principal component analysis (PCA)), which allows more discriminating spot selection. All the selected spots are subjected to MS identification. In some studies, the best targets are validated by using different approaches, such as recombinant-based enzyme-linked immunosorbent assay (ELISA) or protein array. (c) Laboratory pipeline for recombinant protein-based approaches. The large-scale recombinant protein systems allow a high level of genome coverage (>75% of predicted open reading frames (ORFs)). C. burnetii proteins are expressed using Escherichia coli or acellular translation systems (such as the rapid translation system (RTS)). Expressed and/or purified recombinant proteins are transferred to arrays and screened with serum samples from patients and control subjects. Seroreactivity is detected using a fluorescently labeled anti-human IgG antibody. The arrays are read using a laser confocal scanner and the signal intensity of each protein is quantified. The results are analyzed and normalized using statistical tools. The normalized intensity is shown according to a color scale. The top seroreactive proteins are selected by using a determined cut-off.

Screening of recombinant proteins

Proteomics focuses on the large-scale study of an organism's proteins, particularly their structures, functions and expression. After the identification and subsequent verification of specific protein biomarkers, their utility as highly reliable, specific diagnostic markers can be investigated using complementary methods to previously used biological tests. The combination of immunoproteomic methods with protein expression and validation techniques provides an ideal basis for this highly demanding challenge (Figure 2). The study of Chao et al. [65] is an example of the integration of complementary technologies. Eleven protein candidates were selected using an immunoproteomic approach, and six (hsp60, Com-1, RecA, EF-Tu, OmpA-like protein and FtsZ) were successfully cloned [65], but these proteins were not tested for their diagnostic potential [65]. Other studies investigated diagnostic value using serodiagnostic screening with recombinant proteins [66, 67, 89]. High-throughput screening for the selection of serodiagnostic candidates has recently been performed [66, 69]. Transcriptionally active PCR products (TAP products) corresponding to 1,988 C. burnetii open reading frames (ORFs) were tested using a protein microarray [66]. In total, 75% of the full-length proteins were produced using an in vitro transcription and translation system, and these were screened with sera from patients with Q fever and with sera from vaccinated individuals [66]. Fifty strongly immunoreactive protein candidates were proposed as serodiagnostic markers, including several previously identified proteins [31, 57, 64, 65, 67], Ank and multiple hypothetical proteins [66]. The top ten candidates, and the most reactive hypothetical membrane-associated protein CBU_0089, are listed in Table 3 [66]. In a study from the same group [67], all 11 of these recombinant proteins were able to differentiate a majority of IFA-positive sera from IFA-negative sera, but the reaction was stronger when sera from patients with endocarditis was used rather than sera from patients with acute Q fever. In the study by Vigil et al. [69], 84% of the entire proteome was expressed using a rapid translation system and screened with serum samples from 40 acute Q fever patients and 20 healthy individuals [69]. Only 21 antigens reacted strongly with IgG antibodies from infected C. burnetii patients [69]. Of these, 13 were specific to C. burnetii and eight cross-reacted with sera from healthy blood donors. As expected, CBU_1910 was the most reactive antigen with high specificity [69]. Among the identified proteins, several had already been identified in other studies and tested in a proof-of-principle diagnostic assay [31, 57, 58, 66, 68]. The results from Vigil et al. [69] and Beare et al. [66] showed similar ranges of reactivity for the best candidate protein biomarkers (CBU_1910, CBU_0891, CBU_1143, CBU_0612, CBU_0545, and CBU_1398).

In addition, several biomarkers were selected using immunoproteomic studies [31, 57, 68] and were reported to be promising proteins for Q fever serodiagnosis. In a large-scale comprehensive study, only about 1% of the whole proteome of C. burnetii expressed in vitro showed seroreactivity [69]. This proportion of reactive antigens is comparable to that reported by Beare et al. [66]. Altogether, the data suggest that a limited number of proteins are involved in the humoral response to C. burnetii [66, 69].

Recently, protein microarrays were used to evaluate the humoral response to C. trachomatis [90, 91]. Sera from mice immunized with live and non-viable elementary bodies were screened with 99% of the genomic and plasmid proteins expressed in vitro [90]. The results revealed that 185 proteins elicited a strong early and sustained antibody response in mice. Indeed, most of these proteins have already been reported as seroreactive [90, 91]. In similar work, 933 genomic- and plasmid-derived recombinant glutathione S-transferase (GST) fusion proteins were tested with sera from 99 women with urogenital infections. Among 27 seroreactive serum samples, 12 proteins had already been reported as having diagnostic value and a further 15 proteins were newly identified [91]. Both studies narrowed down the number of seroreactive targets, showing that the number of proteins involved in the humoral host response is limited. A miniaturized protein microarray model has been used to investigate both the humoral response against Burkholderia pseudomallei, the causative agent of melioidosis (classified among the group B bioterrorism weapons by the CDC [92]), and B. henselae, the causative agent of cat scratch disease and infective endocarditis [93]. A few specific and sensitive antigens with diagnostic value are now available for a number of infectious diseases. The diagnostic potential of recombinant proteins might be useful in complementing the usual tests, but is insufficient to replace whole antigen- based serology of Q fever. The major drawback of recombinant proteins, generally expressed using Escherichia coli-based systems, is the lack of PTMs, which are of increasing interest for translational and clinical applications.

Conclusions and future directions

The future of diagnostic testing relies upon the development of new technologies, and proteomics is rapidly contributing to this area (Table 4). More sensitive and specific tests for early-stage Q fever detection as well as reliable methods for clinical follow-up of patients are needed.
Table 4

Advantages and limitations of proteomic technologies in clinical microbiology

Technical approach

Advantages

Limitations

MS-based approaches

  

Biotyping

• MALDI-TOF MS has several applications in diagnosis and clinical microbiology, including the identification of bacteria and characterization of bacterial proteomes • Selection of protein targets for diagnostic, vaccine or therapeutic development • Applicable to a variety of samples: including bacterial colonies, clinical samples such as blood cultures or urine, and environmental samples • Availability of commercial database (includes 1,660 bacteria isolates and 66 cell types) • Low cost and easy handling compared with classical phenotype-based bacterial identification

• When several bacterial species are present (such as Streptococcus spp. or anaerobic Gram-negative bacteria in addition to C. burnetii) poor mass-peak signals may result, which may not be distinguished from the signals produced by the culture medium • Limitations in C. burnetii handling (such as level 3 biosafety laboratory needed, difficulties of culturing an intracellular bacteria) • Blood culture is slow (with slow-growing bacteria) or negative (for example in cases of blood-culture-negative endocarditis caused by C. burnetii) and insufficiently sensitive (for example when the patient has previously received antibiotics)

SDS-PAGE coupled to nano-LC proteome identification

• In general, better coverage and sensitivity when compared with MALDI-TOF MS • Identification of low molecular weight proteins • Suitable for investigations of PTMs

• Requires culture of the pathogen, for C. burnetii this involves labor-intensive purification from eukaryotic cells and processing of samples • Labor-intensive, time-consuming • Requires skilled operators • Costly

Immunoproteomics (2-DE coupled to MALDI-TOF)

• Low cost • Resolved proteins contain PTMs that can be visualized on gels (isoforms) • Robust and suitable method for biomarker selection • Can provide an individual profile of reactivity for each patient sample • Can be used with monoclonal antibodies

• Requires the culture and purification of C. burnetii in a level 3 biosafety laboratory, and is labor-intensive • Requires large samples • Variable findings can result, depending on culture conditions, strains, technology and operator skills • Differences between 2D stained gels and immunoblots • Limitations with 2-DE in resolving basic membrane proteins, and low and high MW proteins • In general, low genome coverage (5-30% of total predicted ORFs)

Recombinant protein-based approaches

 

Protein array

• Does not require the culturing or handling of C. burnetii • Miniaturized systems require small amounts of clinical samples (such as 1-2 μl sera) and allows high-throughput screening (>75% of total predicted ORFs) • Low cost, does not require specific operator skills

Escherichia coli system produces proteins without their PTMs (phosphorylations, glycolysations), which are known to be antigenic • Misfolded or multimeric proteins may not be recognized • Requires costly laboratory equipment (fluorescent scanner and spot robot)

ELISA

• Easy to perform, does not require sophisticated technology

• Lower sensitivity than protein array or IPCR

IPCR, immuno-PCR; LC, liquid chromatography; MALDI-TOF MS, matrix-assisted laser desorption ionization-time of flight mass spectrometry; ORF, open-reading frame; PTM, post-translational modification.

Proteomics is paving the way for serodiagnosis development by first selecting seroreactive protein candidates and then validating them in recombinant-protein-based screening systems, such as classic ELISAs and large-scale comprehensive protein arrays. To date, however, none of the proteomics-based techniques has been applied for routine diagnosis of Q fever, mainly because the majority of the resulting discoveries are awaiting large-scale validation. Moreover, the equipment and resources available in diagnostic laboratories outside of large hospitals are generally insufficient for proteomic investigations, and the technology remains expensive and time-consuming.

One of the most important challenges in Q fever diagnosis is the detection of C. burnetii during the early stage of disease, because asymptomatic seroconversion is observed in only 60% of patients. Optimization of the conditions for obtaining specific MALDI-TOF signatures of C. burnetii-infected serum (acute Q fever) will be the first step towards the routine application of this technology. Moreover, in the event of a C. burnetii outbreak, MS-based approaches could be useful in strain subtyping, which in turn allows preventive measures and treatments to be used. Strain-specific proteins have been already characterized [19, 20, 94]. Considering that the immune response to recombinant proteins is limited, their routine use in acute Q fever diagnosis is doubtful. Nevertheless, diagnoses made using recombinant-protein-based microarrays might enhance the discriminatory power of whole antigen-based serology and PCR. This can be particularly useful when searching for serum markers of chronic infection in 'at risk' patients.

The specificity of Q fever serology might also be enhanced by employing monoclonal antibodies raised against C. burnetii, and these are available in several laboratories [58, 95101]. Such approaches can be useful for the detection of C. burnetii infection using serum samples and immuno-PCR (IPCR) [102, 103] when no such infection has been detected by classic whole antigen-based ELISA. Routine clinical applications are still needed for the detection of intracellular pathogens. An immune-MALDI-TOF MS [104] could be another alternative for investigating chronic Q fever samples (such as biopsies of infected organs). Even in this post-genomic era, however, new technologies are not yet able to replace the isolation and culturing of pathogens. The development of C. burnetii axenic medium was an enormous breakthrough [22] that has allowed the genetic manipulation of these bacteria. Indeed, a C. burnetii genetic mutant lacking the FtsZ protein has been generated [105]. Genetic manipulation of these bacteria will allow several new areas of investigation, including further proteomic studies of the immune response to C. burnetti, studies of the effectors of the T4SS, and investigation of the intracellular survival mechanisms of C. burnetii. The information garnered in such studies will, in turn, facilitate the development of more specific and sensitive diagnostic assays for Q fever.

Abbreviations

adaA

acute disease antigen A gene

Ank: 

ankyrin repeat-containing domain

CDC: 

Centers for Disease Control and Prevention

2-DE: 

two-dimensional electrophoresis

ELISA: 

enzyme-linked immunosorbent assay

FNRC: 

French National Reference Center

IFA: 

immunofluorescence assay

IgG: 

Immunoglobulin G

IgM: 

Immunoglobulin M

IgA: 

Immunoglobulin A

IPCR: 

immuno-PCR

IS: 

insertion sequence

LCV: 

large cell variant

LPS: 

lipopolysaccharide

MS: 

mass spectrometry

MW: 

molecular weight

OMP: 

outer-membrane protein

ORF: 

open-reading frame

PTM: 

post-translational modification

SCV: 

small cell variant

SDS-PAGE: 

sodium dodecyl sulphate-polyacrylamide gel electrophoresis

T4SS: 

type IV secretion system

UBT: 

urea breath test.

Declarations

Acknowledgements

This work was partially supported by a VEGA grant (Nos. 2/0156/11, 2/0031/11 and 2/0065/09) from the Slovak Academy of Sciences, Bratislava, Slovakia, and by a grant from the Direction Générale de l'Armement, 91710 Vert-le-Petit, France (No. CP209812DGA0004). It is also part of a bilateral project between CNRS France and SAS Slovakia (Nos. 22525-CNRS and 2-SAS).

Authors’ Affiliations

(1)
URMITE, CNRS UMR 6236-IRD 198, Université de la Méditerranée, Faculté de Médecine
(2)
Institute of Virology, Slovak Academy of Sciences

References

  1. Angelakis E, Raoult D: Q Fever. Vet Microbiol. 2010, 140: 297-309. 10.1016/j.vetmic.2009.07.016.PubMedGoogle Scholar
  2. Roest HI, Tilburg JJ, van der Hoek W, Vellema P, van Zijderveld FG, Klaassen CH: The Q fever epidemic in The Netherlands: history, onset, response and reflection. Epidemiol Infect. 2010, 139: 1-12.PubMedGoogle Scholar
  3. Miceli MH, Veryser AK, Anderson AD, Hofinger D, Lee SA, Tancik C: A case of person-to-person transmission of Q fever from an active duty serviceman to his spouse. Vector Borne Zoonotic Dis. 2010, 10: 539-541. 10.1089/vbz.2009.0101.PubMedGoogle Scholar
  4. Carcopino X, Raoult D, Bretelle F, Boubli L, Stein A: Q Fever during pregnancy: a cause of poor fetal and maternal outcome. Ann N Y Acad Sci. 2009, 1166: 79-89. 10.1111/j.1749-6632.2009.04519.x.PubMedGoogle Scholar
  5. Frankel D, Richet H, Renvoise A, Raoult D: Q fever in France, 1985-2009. Emerg Infect Dis. 2011, 17: 350-356.PubMed CentralPubMedGoogle Scholar
  6. Enserink M: Infectious diseases. Questions abound in Q-fever explosion in The Netherlands. Science. 2010, 327: 266-267.Google Scholar
  7. Klaassen CH, Nabuurs-Franssen MH, Tilburg JJ, Hamans MA, Horrevorts AM: Multigenotype Q fever outbreak, The Netherlands. Emerg Infect Dis. 2009, 15: 613-614. 10.3201/eid1504.081612.PubMed CentralPubMedGoogle Scholar
  8. Raoult D, Marrie T, Mege JL: Natural history and pathophysiology of Q fever. Lancet Infect Dis. 2005, 5: 219-226. 10.1016/S1473-3099(05)70052-9.PubMedGoogle Scholar
  9. Gimenez DF: Staining Rickettsiae in yolk-sac cultures. Stain Technol. 1964, 39: 135-140.PubMedGoogle Scholar
  10. Seshadri R, Paulsen IT, Eisen JA, Read TD, Nelson KE, Nelson WC: Complete genome sequence of the Q-fever pathogen Coxiella burnetii. Proc Natl Acad Sci USA. 2003, 100: 5455-5460. 10.1073/pnas.0931379100.PubMed CentralPubMedGoogle Scholar
  11. Beare PA, Porcella SF, Seshadri R, Samuel JE, Heinzen RA: Preliminary assessment of genome differences between the reference Nine Mile isolate and two human endocarditis isolates of Coxiella burnetii. Ann N Y Acad Sci. 2005, 1063: 64-67. 10.1196/annals.1355.007.PubMedGoogle Scholar
  12. Voth DE, Beare PA, Howe D, Sharma UM, Samoilis G, Cockrell DC: The Coxiella burnetii cryptic plasmid is enriched in genes encoding type IV secretion system substrates. J Bacteriol. 2011, 193: 1493-1503. 10.1128/JB.01359-10.PubMed CentralPubMedGoogle Scholar
  13. Beare PA, Unsworth N, Andoh M, Voth DE, Omsland A, Gilk SD: Comparative genomics reveal extensive transposon-mediated genomic plasticity and diversity among potential effector proteins within the genus Coxiella. Infect Immun. 2009, 77: 642-656. 10.1128/IAI.01141-08.PubMed CentralPubMedGoogle Scholar
  14. Vadovic P, Fuleova A, Ihnatko R, Skultety L, Halada P, Toman R: Structural studies of lipid A from a lipopolysaccharide of the Coxiella burnetii isolate RSA 514 (Crazy). Clin Microbiol Infect. 2009, 15: 198-199.PubMedGoogle Scholar
  15. Vadovic P, Slaba K, Fodorova M, Skultety L, Toman R: Structural and functional characterization of the glycan antigens involved in immunobiology of Q fever. Ann N Y Acad Sci. 2005, 1063: 149-153. 10.1196/annals.1355.023.PubMedGoogle Scholar
  16. Toman R, Skultety L, Ihnatko R: Coxiella burnetii glycomics and proteomics -- tools for linking structure to function. Ann N Y Acad Sci. 2009, 1166: 67-78. 10.1111/j.1749-6632.2009.04512.x.PubMedGoogle Scholar
  17. Skultety LHM, Flores-Ramirez G, Miernyk JA, Ciampor F, Toman R, Sekeyova Z: Proteomic comparaison of virulent phase I and avirulent phase II of Coxiella burnetii, the causautive agent of Q fever. J Proteomics. 2011Google Scholar
  18. Musso D, Raoult D: Coxiella burnetii blood cultures from acute and chronic Q-fever patients. J Clin Microbiol. 1995, 33: 3129-3132.PubMed CentralPubMedGoogle Scholar
  19. Skultety L, Hernychova L, Toman R, Hubalek M, Slaba K, Zechovska J: Coxiella burnetii whole cell lysate protein identification by mass spectrometry and tandem mass spectrometry. Ann N Y Acad Sci. 2005, 1063: 115-122. 10.1196/annals.1355.019.PubMedGoogle Scholar
  20. Skultety L, Hernychova L, Bereghazyova E, Slaba K, Toman R: Detection of specific spectral markers of Coxiella burnetii isolates by MALDI-TOF mass spectrometry. Acta Virol. 2007, 51: 55-58.PubMedGoogle Scholar
  21. Maurin M, Raoult D: Q fever. Clin Microbiol Rev. 1999, 12: 518-553.PubMed CentralPubMedGoogle Scholar
  22. Omsland A, Cockrell DC, Howe D, Fischer ER, Virtaneva K, Sturdevant DE: Host cell-free growth of the Q fever bacterium Coxiella burnetii. Proc Natl Acad Sci USA. 2009, 106: 4430-4434. 10.1073/pnas.0812074106.PubMed CentralPubMedGoogle Scholar
  23. Battisti JM, Hicks LD, Minnick MF: A unique Coxiella burnetiilipoprotein involved in metal-binding (LimB). Microbiology. 2011, Google Scholar
  24. Gilk SD, Beare PA, Heinzen RA: Coxiella burnetii expresses a functional Δ24 sterol reductase. J Bacteriol. 2010, 192: 6154-6159. 10.1128/JB.00818-10.PubMed CentralPubMedGoogle Scholar
  25. Textoris J, Ban LH, Capo C, Raoult D, Leone M, Mege JL: Sex-related differences in gene expression following Coxiella burnetii infection in mice: potential role of circadian rhythm. PLoS One. 2010, 5: e12190-10.1371/journal.pone.0012190.PubMed CentralPubMedGoogle Scholar
  26. Leone M, Honstettre A, Lepidi H, Capo C, Bayard F, Raoult D: Effect of sex on Coxiella burnetii infection: protective role of 17beta-estradiol. J Infect Dis. 2004, 189: 339-345. 10.1086/380798.PubMedGoogle Scholar
  27. Voth DE, Heinzen RA: Coxiella type IV secretion and cellular microbiology. Curr Opin Microbiol. 2009, 12: 74-80. 10.1016/j.mib.2008.11.005.PubMed CentralPubMedGoogle Scholar
  28. Luhrmann A, Nogueira CV, Carey KL, Roy CR: Inhibition of pathogen-induced apoptosis by a Coxiella burnetii type IV effector protein. Proc Natl Acad Sci USA. 2010, 107: 18997-19001. 10.1073/pnas.1004380107.PubMed CentralPubMedGoogle Scholar
  29. Chen C, Banga S, Mertens K, Weber MM, Gorbaslieva I, Tan Y: Large-scale identification and translocation of type IV secretion substrates by Coxiella burnetii. Proc Natl Acad Sci USA. 2010, 107: 21755-21760. 10.1073/pnas.1010485107.PubMed CentralPubMedGoogle Scholar
  30. Coleman SA, Fischer ER, Howe D, Mead DJ, Heinzen RA: Temporal analysis of Coxiella burnetii morphological differentiation. J Bacteriol. 2004, 186: 7344-7352. 10.1128/JB.186.21.7344-7352.2004.PubMed CentralPubMedGoogle Scholar
  31. Coleman SA, Fischer ER, Cockrell DC, Voth DE, Howe D, Mead DJ: Proteome and antigen profiling of Coxiella burnetii developmental forms. Infect Immun. 2007, 75: 290-298. 10.1128/IAI.00883-06.PubMed CentralPubMedGoogle Scholar
  32. Voth DE, Beare PA, Howe D, Sharma UM, Samoilis G, Cockrell DC, Omsland A, Heinzen RA: The Coxiella burnetii cryptic plasmid enriched in genes encoding type IV secretion system. J Bacteriol. 2011, 193: 1493-1503. 10.1128/JB.01359-10.PubMed CentralPubMedGoogle Scholar
  33. Samoilis G, Aivaliotis M, Vranakis I, Papadioti A, Tselentis Y, Tsiotis G: Proteomic screening for possible effector molecules secreted by the obligate intracellular pathogen Coxiella burnetii. J Proteome Res. 2010, 9: 1619-1626. 10.1021/pr900605q.PubMedGoogle Scholar
  34. Voth DE, Howe D, Beare PA, Vogel JP, Unsworth N, Samuel JE: The Coxiella burnetii ankyrin repeat domain-containing protein family is heterogeneous, with C-terminal truncations that influence Dot/Icm-mediated secretion. J Bacteriol. 2009, 191: 4232-4242. 10.1128/JB.01656-08.PubMed CentralPubMedGoogle Scholar
  35. Tissot-Dupont H, Raoult D: Q fever. Infect Dis Clin North Am. 2008, 22: 505-514. 10.1016/j.idc.2008.03.002.PubMedGoogle Scholar
  36. Imbert G, La Scola B: Diagnosis of Q fever using indirect microimmunofluorescence. Methods Mol Biol. 2006, 345: 197-202.PubMedGoogle Scholar
  37. Fournier PE, Raoult D: Comparison of PCR and serology assays for early diagnosis of acute Q fever. J Clin Microbiol. 2003, 41: 5094-5098. 10.1128/JCM.41.11.5094-5098.2003.PubMed CentralPubMedGoogle Scholar
  38. La Scola B: Current laboratory diagnosis of Q fever. Semin Pediatr Infect Dis. 2002, 13: 257-262. 10.1053/spid.2002.127199.Google Scholar
  39. Lepidi H, Casalta JP, Fournier PE, Habib G, Collart F, Raoult D: Quantitative histological examination of mechanical heart valves. Clin Infect Dis. 2005, 40: 655-661. 10.1086/427504.PubMedGoogle Scholar
  40. Fenollar F, Fournier PE, Raoult D: Molecular detection of Coxiella burnetii in the sera of patients with Q fever endocarditis or vascular infection. J Clin Microbiol. 2004, 42: 4919-4924. 10.1128/JCM.42.11.4919-4924.2004.PubMed CentralPubMedGoogle Scholar
  41. Klee SR, Ellerbrok H, Tyczka J, Franz T, Appel B: Evaluation of a real-time PCR assay to detect Coxiella burnetii. Ann N Y Acad Sci. 2006, 1078: 563-565. 10.1196/annals.1374.111.PubMedGoogle Scholar
  42. Tilburg JJ, Nabuurs-Franssen MH, van Hannen EJ, Horrevorts AM, Melchers WJ, Klaassen CH: Contamination of commercial PCR master mix with DNA from Coxiella burnetii. J Clin Microbiol. 2010, 48: 4634-4635. 10.1128/JCM.00464-10.PubMed CentralPubMedGoogle Scholar
  43. Tilburg JJ, Melchers WJ, Pettersson AM, Rossen JW, Hermans MH, van Hannen EJ: Interlaboratory evaluation of different extraction and real-time PCR methods for detection of Coxiella burnetii DNA in serum. J Clin Microbiol. 2010, 48: 3923-3927. 10.1128/JCM.01006-10.PubMed CentralPubMedGoogle Scholar
  44. Dupont HT, Thirion X, Raoult D: Q fever serology: cutoff determination for microimmunofluorescence. Clin Diagn Lab Immunol. 1994, 1: 189-196.PubMed CentralPubMedGoogle Scholar
  45. Tilburg JJ, Horrevorts AM, Peeters MF, Klaassen CH, Rossen JW: Identification by genotyping of a commercial antigen preparation as the source of a laboratory contamination with Q fever and as an unexpected rich source of control DNA. J Clin Microbiol. 2010, 49: 383-384.PubMed CentralPubMedGoogle Scholar
  46. Boden K, Wagner-Wiening C, Seidel T, Baier M, Bischof W, Straube E: Diagnosis of acute Q fever with emphasis on enzyme-linked immunosorbent assay and nested polymerase chain reaction regarding the time of serum collection. Diagn Microbiol Infect Dis. 2010, 68: 110-116. 10.1016/j.diagmicrobio.2010.06.001.PubMedGoogle Scholar
  47. Fournier PE, Marrie TJ, Raoult D: Diagnosis of Q fever. J Clin Microbiol. 1998, 36: 1823-1834.PubMed CentralPubMedGoogle Scholar
  48. Li JS, Sexton DJ, Mick N, Nettles R, Fowler VG, Ryan T: Proposed modifications to the Duke criteria for the diagnosis of infective endocarditis. Clin Infect Dis. 2000, 30: 633-638. 10.1086/313753.PubMedGoogle Scholar
  49. Musso D, Raoult D: Serological cross-reactions between Coxiella burnetii and Legionella micdadei. Clin Diagn Lab Immunol. 1997, 4: 208-212.PubMed CentralPubMedGoogle Scholar
  50. La Scola B, Raoult D: Serological cross-reactions between Bartonella quintana, Bartonella henselae, and Coxiella burnetii. J Clin Microbiol. 1996, 34: 2270-2274.PubMed CentralPubMedGoogle Scholar
  51. Dupont HT, Brouqui P, Faugere B, Raoult D: Prevalence of antibodies to Coxiella burnetti, Rickettsia conorii, and Rickettsia typhi in seven African countries. Clin Infect Dis. 1995, 21: 1126-1133. 10.1093/clinids/21.5.1126.PubMedGoogle Scholar
  52. Gouriet F, Levy PY, Samson L, Drancourt M, Raoult D: Comparison of the new InoDiag automated fluorescence multiplexed antigen microarray to the reference technique in the serodiagnosis of atypical bacterial pneumonia. Clin Microbiol Infect. 2008, 14: 1119-1127. 10.1111/j.1469-0691.2008.02119.x.PubMedGoogle Scholar
  53. Gouriet F, Samson L, Delaage M, Mainardi JL, Meconi S, Drancourt M: Multiplexed whole bacterial antigen microarray, a new format for the automation of serodiagnosis: the culture-negative endocarditis paradigm. Clin Microbiol Infect. 2008, 14: 1112-1118. 10.1111/j.1469-0691.2008.02094.x.PubMedGoogle Scholar
  54. Skultety L, Hernychova L, Toman R, Kroca M, Stulik J, Macela A: Initial peptide mass fingerprinting analysis of proteins obtained by lysis of Coxiella burnetii cells. Acta Virol. 2004, 48: 29-33.PubMedGoogle Scholar
  55. Pierce CY, Barr JR, Woolfitt AR, Moura H, Shaw EI, Thompson HA: Strain and phase identification of the U.S. category B agent Coxiella burnetii by matrix assisted laser desorption/ionization time-of-flight mass spectrometry and multivariate pattern recognition. Anal Chim Acta. 2007, 583: 23-31. 10.1016/j.aca.2006.09.065.PubMedGoogle Scholar
  56. Papadioti A, Markoutsa S, Vranakis I, Tselentis Y, Karas M, Psaroulaki A: A proteomic approach to investigate the differential antigenic profile of two Coxiella burnetii strains. J Proteomics. 2011, 74: 1150-1159. 10.1016/j.jprot.2011.04.016.PubMedGoogle Scholar
  57. Sekeyova Z, Kowalczewska M, Decloquement P, Pelletier N, Spitalska E, Raoult D: Identification of protein candidates for the serodiagnosis of Q fever endocarditis by an immunoproteomic approach. Eur J Clin Microbiol Infect Dis. 2009, 28: 287-295. 10.1007/s10096-008-0621-4.PubMedGoogle Scholar
  58. Sekeyova Z, Kowalczewska M, Vincentelli R, Decloquement P, Flores-Ramirez G, Skultety L: Characterization of antigens for Q fever serodiagnostics. Acta Virol. 2010, 54: 173-180. 10.4149/av_2010_03_173.PubMedGoogle Scholar
  59. Flores-Ramirez G, Toman R, Sekeyova Z, Skultety L: In silico prediction and identification of outer membrane proteins and lipoproteins from Coxiella burnetii by the mass spectrometry techniques. Clin Microbiol Infect. 2009, 15: 196-197.PubMedGoogle Scholar
  60. Seng P, Drancourt M, Gouriet F, La Scola B, Fournier PE, Rolain JM: Ongoing revolution in bacteriology: routine identification of bacteria by matrix-assisted laser desorption ionization time-of-flight mass spectrometry. Clin Infect Dis. 2009, 49: 543-551. 10.1086/600885.PubMedGoogle Scholar
  61. Murray PR: Matrix-assisted laser desorption ionization time-of-flight mass spectrometry: usefulness for taxonomy and epidemiology. Clin Microbiol Infect. 2010, 16: 1626-1630. 10.1111/j.1469-0691.2010.03364.x.PubMedGoogle Scholar
  62. Hernychova L, Toman R, Ciampor F, Hubalek M, Vackova J, Macela A: Detection and identification of Coxiella burnetii based on the mass spectrometric analyses of the extracted proteins. Anal Chem. 2008, 80: 7097-7104. 10.1021/ac800788k.PubMedGoogle Scholar
  63. Zhang G, To H, Russell KE, Hendrix LR, Yamaguchi T, Fukushi H: Identification and characterization of an immunodominant 28-kilodalton Coxiella burnetii outer membrane protein specific to isolates associated with acute disease. Infect Immun. 2005, 73: 1561-1567. 10.1128/IAI.73.3.1561-1567.2005.PubMed CentralPubMedGoogle Scholar
  64. Hendrix LR, Mallavia LP, Samuel JE: Cloning and sequencing of Coxiella burnetii outer membrane protein gene com1. Infect Immun. 1993, 61: 470-477.PubMed CentralPubMedGoogle Scholar
  65. Chao CC, Chen HW, Li X, Xu WB, Hanson B, Ching WM: Identification, cloning, and expression of potential diagnostic markers for Q fever. Ann N Y Acad Sci. 2005, 1063: 76-78. 10.1196/annals.1355.010.PubMedGoogle Scholar
  66. Beare PA, Chen C, Bouman T, Pablo J, Unal B, Cockrell DC: Candidate antigens for Q fever serodiagnosis revealed by immunoscreening of a Coxiella burnetii protein microarray. Clin Vaccine Immunol. 2008, 15: 1771-1779. 10.1128/CVI.00300-08.PubMed CentralPubMedGoogle Scholar
  67. Chen C, Bouman TJ, Beare PA, Mertens K, Zhang GQ, Russell-Lodrigue KE: A systematic approach to evaluate humoral and cellular immune responses to Coxiella burnetii immunoreactive antigens. Clin Microbiol Infect. 2009, 15: 156-157.PubMed CentralPubMedGoogle Scholar
  68. Deringer JR, Chen C, Samuel JE, Brown WC: Immunoreactive Coxiella burnetii Nine Mile proteins separated by 2D electrophoresis and identified by tandem mass spectrometry. Microbiology. 2010, 157: 526-542.PubMedGoogle Scholar
  69. Vigil A, Ortega R, Nakajima-Sasaki R, Pablo J, Molina DM, Chao CC: Genome-wide profiling of humoral immune response to Coxiella burnetii infection by protein microarray. Proteomics. 2010, 10: 2259-2269. 10.1002/pmic.201000064.PubMed CentralPubMedGoogle Scholar
  70. Bini L, Sanchez-Campillo M, Santucci A, Magi B, Marzocchi B, Comanducci M: Mapping of Chlamydia trachomatis proteins by immobiline-polyacrylamide two-dimensional electrophoresis: spot identification by N-terminal sequencing and immunoblotting. Electrophoresis. 1996, 17: 185-190. 10.1002/elps.1150170130.PubMedGoogle Scholar
  71. Birkelund S, Bini L, Pallini V, Sanchez-Campillo M, Liberatori S, Clausen JD: Characterization of Chlamydia trachomatis l2-induced tyrosine-phosphorylated HeLa cell proteins by two-dimensional gel electrophoresis. Electrophoresis. 1997, 18: 563-567. 10.1002/elps.1150180338.PubMedGoogle Scholar
  72. Sanchez-Campillo M, Bini L, Comanducci M, Raggiaschi R, Marzocchi B, Pallini V: Identification of immunoreactive proteins of Chlamydia trachomatis by Western blot analysis of a two-dimensional electrophoresis map with patient sera. Electrophoresis. 1999, 20: 2269-2279. 10.1002/(SICI)1522-2683(19990801)20:11<2269::AID-ELPS2269>3.0.CO;2-D.PubMedGoogle Scholar
  73. Jungblut PR, Schiele F, Zimny-Arndt U, Ackermann R, Schmid M, Lange S: Helicobacter pylori proteomics by 2-DE/MS, 1-DE-LC/MS and functional data mining. Proteomics. 2010, 10: 182-193. 10.1002/pmic.200900361.PubMedGoogle Scholar
  74. Bumann D, Jungblut PR, Meyer TF: Helicobacter pylori vaccine development based on combined subproteome analysis. Proteomics. 2004, 4: 2843-2848. 10.1002/pmic.200400909.PubMedGoogle Scholar
  75. Bernarde C, Khoder G, Lehours P, Burucoa C, Fauchere JL, Delchier JC: Proteomic Helicobacter pylori biomarkers discriminative of low-grade gastric MALT lymphoma and duodenal ulcer. Proteomics Clin Appl. 2009, 3: 672-681. 10.1002/prca.200800158.PubMedGoogle Scholar
  76. Bernarde C, Lehours P, Lasserre JP, Castroviejo M, Bonneu M, Megraud F: Complexomics study of two Helicobacter pylori strains of two pathological origins: potential targets for vaccine development and new insight in bacteria metabolism. Mol Cell Proteomics. 2010, 9: 2796-2826. 10.1074/mcp.M110.001065.PubMed CentralPubMedGoogle Scholar
  77. Mullaney E, Brown PA, Smith SM, Botting CH, Yamaoka YY, Terres AM: Proteomic and functional characterization of the outer membrane vesicles from the gastric pathogen Helicobacter pylori. Proteomics Clin Appl. 2009, 3: 785-796. 10.1002/prca.200800192.PubMedGoogle Scholar
  78. Havlasova J, Hernychova L, Halada P, Pellantova V, Krejsek J, Stulik J: Mapping of immunoreactive antigens of Francisella tularensis live vaccine strain. Proteomics. 2002, 2: 857-867. 10.1002/1615-9861(200207)2:7<857::AID-PROT857>3.0.CO;2-L.PubMedGoogle Scholar
  79. Havlasova J, Hernychova L, Brychta M, Hubalek M, Lenco J, Larsson P: Proteomic analysis of anti-Francisella tularensis LVS antibody response in murine model of tularemia. Proteomics. 2005, 5: 2090-2103. 10.1002/pmic.200401123.PubMedGoogle Scholar
  80. Twine S, Bystrom M, Chen W, Forsman M, Golovliov I, Johansson A: A mutant of Francisella tularensis strain SCHU S4 lacking the ability to express a 58-kilodalton protein is attenuated for virulence and is an effective live vaccine. Infect Immun. 2005, 73: 8345-8352. 10.1128/IAI.73.12.8345-8352.2005.PubMed CentralPubMedGoogle Scholar
  81. Twine SM, Mykytczuk NC, Petit M, Tremblay TL, Lanthier P, Conlan JW: Francisella tularensis proteome: low levels of ASB-14 facilitate the visualization of membrane proteins in total protein extracts. J Proteome Res. 2005, 4: 1848-1854. 10.1021/pr050102u.PubMedGoogle Scholar
  82. Twine SM, Petit MD, Shen H, Mykytczuk NC, Kelly JF, Conlan JW: Immunoproteomic analysis of the murine antibody response to successful and failed immunization with live anti-Francisella vaccines. Biochem Biophys Res Commun. 2006, 346: 999-1008. 10.1016/j.bbrc.2006.06.008.PubMedGoogle Scholar
  83. Zhao G, Zhu L, Feng E, Cao X, Shang N, Liu X: A novel anti-virulence gene revealed by proteomic analysis in Shigella flexneri 2a. Proteome Sci. 2010, 8: 30-10.1186/1477-5956-8-30.PubMed CentralPubMedGoogle Scholar
  84. Pieper R, Zhang Q, Parmar PP, Huang ST, Clark DJ, Alami H: The Shigella dysenteriae serotype 1 proteome, profiled in the host intestinal environment, reveals major metabolic modifications and increased expression of invasive proteins. Proteomics. 2009, 9: 5029-5045. 10.1002/pmic.200900196.PubMed CentralPubMedGoogle Scholar
  85. Kowalczewska M, Fenollar F, Lafitte D, Raoult D: Identification of candidate antigen in Whipple's disease using a serological proteomic approach. Proteomics. 2006, 6: 3294-3305. 10.1002/pmic.200500171.PubMedGoogle Scholar
  86. Kowalczewska M, Raoult D: Advances in Tropheryma whipplei research: the rush to find biomarkers for Whipple's disease. Future Microbiol. 2007, 2: 631-642. 10.2217/17460913.2.6.631.PubMedGoogle Scholar
  87. Eberhardt C, Engelmann S, Kusch H, Albrecht D, Hecker M, Autenrieth IB: Proteomic analysis of the bacterial pathogen Bartonella henselae and identification of immunogenic proteins for serodiagnosis. Proteomics. 2009, 9: 1967-1981. 10.1002/pmic.200700670.PubMedGoogle Scholar
  88. Saisongkorh W, Kowalczewska M, Azza S, Decloquement P, Rolain JM, Raoult D: Identification of candidate proteins for the diagnosis of Bartonella henselae infections using an immunoproteomic approach. FEMS Microbiol Lett. 2010, 310: 158-167. 10.1111/j.1574-6968.2010.02058.x.PubMedGoogle Scholar
  89. Minnick MF, Heinzen RA, Frazier ME, Mallavia LP: Characterization and expression of the cbbE' gene of Coxiella burnetii. J Gen Microbiol. 1990, 136: 1099-1107.PubMedGoogle Scholar
  90. Cruz-Fisher MI, Cheng C, Sun G, Pal S, Teng A, Molina DM: Identification of immunodominant antigens by probing a whole Chlamydia ORFome microarray using sera from immunized mice. Infect Immun. 2010, 79: 246-257.PubMed CentralPubMedGoogle Scholar
  91. Wang J, Zhang Y, Lu C, Lei L, Yu P, Zhong G: A genome-wide profiling of the humoral immune response to Chlamydia trachomatis infection reveals vaccine candidate antigens expressed in humans. J Immunol. 2010, 185: 1670-1680. 10.4049/jimmunol.1001240.PubMedGoogle Scholar
  92. Felgner PL, Kayala MA, Vigil A, Burk C, Nakajima-Sasaki R, Pablo J: A Burkholderia pseudomallei protein microarray reveals serodiagnostic and cross-reactive antigens. Proc Natl Acad Sci USA. 2009, 106: 13499-13504. 10.1073/pnas.0812080106.PubMed CentralPubMedGoogle Scholar
  93. Vigil A, Ortega R, Jain A, Nakajima-Sasaki R, Tan X, Chomel BB: Identification of the feline humoral immune response to Bartonella henselae infection by protein microarray. PLoS One. 2010, 5: e11447-10.1371/journal.pone.0011447.PubMed CentralPubMedGoogle Scholar
  94. Samoilis G, Psaroulaki A, Vougas K, Tselentis Y, Tsiotis G: Analysis of whole cell lysate from the intercellular bacterium Coxiella burnetii using two gel-based protein separation techniques. J Proteome Res. 2007, 6: 3032-3041. 10.1021/pr070077n.PubMedGoogle Scholar
  95. Zhang YX, Zhi N, Yu SR, Li QJ, Yu GQ, Zhang X: Protective immunity induced by 67 K outer membrane protein of phase I Coxiella burnetii in mice and guinea pigs. Acta Virol. 1994, 38: 327-332.PubMedGoogle Scholar
  96. Jaspers U, Thiele D, Krauss H: Monoclonal antibody based competitive ELISA for the detection of specific antibodies against Coxiella burnetii in sera from different animal species. Zentralbl Bakteriol. 1994, 281: 61-66.PubMedGoogle Scholar
  97. Sekeyova Z, Kovacova E, Kazar J, Toman R, Olvecka S: Monoclonal antibodies to Coxiella burnetii that cross-react with strain Nine Mile. Clin Diagn Lab Immunol. 1995, 2: 531-534.PubMed CentralPubMedGoogle Scholar
  98. McCaul TF, Banerjee-Bhatnagar N, Williams JC: Antigenic differences between Coxiella burnetii cells revealed by postembedding immunoelectron microscopy and immunoblotting. Infect Immun. 1991, 59: 3243-3253.PubMed CentralPubMedGoogle Scholar
  99. Banerjee-Bhatnagar N, Bolt CR, Williams JC: Pore-forming activity of Coxiella burnetii outer membrane protein oligomer comprised of 29.5- and 31-kDa polypeptides. Inhibition of porin activity by monoclonal antibodies 4E8 and 4D6. Ann N Y Acad Sci. 1996, 791: 378-401. 10.1111/j.1749-6632.1996.tb53545.x.PubMedGoogle Scholar
  100. Sekeyova Z, Kovacova E: Identification and characterization of Coxiella burnetii strains and isolates using monoclonal antibodies. Ann N Y Acad Sci. 2006, 1078: 557-560. 10.1196/annals.1374.109.PubMedGoogle Scholar
  101. Raoult D, Laurent JC, Mutillod M: Monoclonal antibodies to Coxiella burnetii for antigenic detection in cell cultures and in paraffin-embedded tissues. Am J Clin Pathol. 1994, 101: 318-320.PubMedGoogle Scholar
  102. Malou N, Raoult D: Immuno-PCR: a promising ultrasensitive diagnostic method to detect antigens and antibodies. Trends Microbiol. 2011, 19: 295-302. 10.1016/j.tim.2011.03.004.PubMedGoogle Scholar
  103. Sano T, Smith CL, Cantor CR: Immuno-PCR: very sensitive antigen detection by means of specific antibody-DNA conjugates. Science. 1992, 258: 120-122. 10.1126/science.1439758.PubMedGoogle Scholar
  104. Sparbier K, Wenzel T, Dihazi H, Blaschke S, Muller GA, Deelder A: Immuno-MALDI-TOF MS: new perspectives for clinical applications of mass spectrometry. Proteomics. 2009, 9: 1442-1450. 10.1002/pmic.200800616.PubMedGoogle Scholar
  105. Beare PA, Howe D, Cockrell DC, Omsland A, Hansen B, Heinzen RA: Characterization of a Coxiella burnetii ftsZ mutant generated by Himar1 transposon mutagenesis. J Bacteriol. 2009, 191: 1369-1381. 10.1128/JB.01580-08.PubMed CentralPubMedGoogle Scholar

Copyright

© BioMed Central Ltd 2011