WO2014037924A2 - Analysis of saliva proteome for biomarkers of gingivitis and periodontitis using ft-icr-ms/ms - Google Patents

Abstract

Methods for diagnosing the status of periodontitis disease includes selecting a set of protein biomarkers including one or more biomarkers which have been shown to vary in abundance at particular stages of periodontitis. The set of protein biomarkers may be identified and quantified in expression in an acquired gingival crevicular fluid (GCF) or saliva oral fluid sample in order to distinguish between different states of periodontitis. Methods of diagnosing the status of periodontitis oral disease at varying levels of severity, e.g. gingivitis, mild periodontitis, or severe periodontitis, may include selecting a set of protein biomarkers which are capable distinguishing between different stages of periodontitis.

Description

ANALYSIS OF SALIVA PROTEOME FOR BIOMARKERS OF GINGIVITIS AND PERIODONTITIS USING FT-ICR-MS/MS

The present application pertains to the fields of proteomics and bioinformatics. More particularly, the present application relates to diagnosing a status of an oral disease, e.g. periodontitis, at varying levels of severity through the quantification of protein biomarkers.

Gingivitis is a non-destructive form of periodontal disease involving soft tissue inflammation of the gums. Gingivitis typically occurs as a bodily response to bacterial biofilms, or plaques, which have adhered to teeth. In the absence of proper treatment, gingivitis may progress to periodontitis, which represents a destructive form of periodontal disease. Periodontitis may begin with a milder of the disease, which later progresses into severe periodontitis. Periodontitis is always preceded by the onset of gingivitis.

Periodontal diseases are the leading cause of tooth loss in adults. Accordingly, diagnostic tests have been developed to identify the probability of whether an individual has developed periodontitis. Oral- fluid-based point-of-case (POC) diagnostics are commonly used for various diagnostic tests in medicine and more recently are being adapted for the determination of oral diseases (Tabak, 2007, Ann N Y Acad Sci 1098: 7-14). The use of oral fluids for POC diagnostics has been shown to be effective in detecting oral cancer (Li et al, 2004, Clin Cancer Res 10:8442-8450; Zimmerman et al, 2008, Oral Oncol. 44(5):425-9) or HIV infection (Delaney et al, 2006, Aids 20: 1655-1660).

Periodontal diseases are presently diagnosed by evaluating clinical parameters such as pocket depth, bleeding on probing, and radiographs. These parameters have limitations in that they lack the ability to predict future attachment loss, and provide information only on the existence of past disease activity. Furthermore, no clinical parameters have been shown to be predictive for periodontal disease activity ("Clinical risk indicators for periodontal attachment loss," Journal of Clinical Periodontology 1991 : v. 18: 117-125"). Diagnostic methods in clinical practice today lack the ability to both detect the onset of inflammation, e.g. non-destructive gingivitis, and to identify the likelihood of developing destructive forms of periodontitis in the future.

Thus, there exists a need in the art for an efficient, accurate, and sensitive oral fluid diagnostic methods that can not only recognize the existence of past oral disease activity, but can also diagnose and assess earlier stages of oral diseases. In the case of periodontitis, oral fluid diagnostic methods should be able to distinguish at least between healthy patients and those that have developed gingivitis, milder forms of periodontitis, and/or more severe forms of periodontitis. This diagnostic method may advantageously include the quantification of particular protein biomarkers which are present in oral fluids. These oral fluids may be non-invasively acquired from a patient as gingival crevicular fluid (GCF) and/or saliva fluid.

BRIEF SUMMARY

Demonstrated herein in an exemplary embodiment is a method for diagnosing the status of periodontitis disease. The method includes providing at least one of a gingival crevicular fluid (GCF) sample and a saliva sample, selecting a set of protein biomarkers for identifying a particular state of periodontitis, and determining the expression levels in the selected set of protein biomarkers to diagnose the status of periodontitis disease.

In an aspect of the method, the set of protein biomarkers is selected for distinguishing between a gingivitis state and a periodontitis state.

In another aspect of the method, the set of protein biomarkers is selected for distinguishing between a periodontal health and a disease state.

In yet another aspect of the method, the set of protein biomarkers is selected for distinguishing between a mild periodontitis state and a severe periodontitis state.

In some aspects of the method, the set of protein biomarkers includes at least one protein selected from the group consisting of haemoglobin chains alpha and beta, carbonic anhydrase 1 (International Protein Index or "IPI" #IPI00980674), and plastin 1.

In another aspect of the method, the set of protein biomarkers includes at least one protein selected from the group consisting of S100-P, transaldolase, S100-A8 (calgranulin-A), myosin-9, Haemoglobin Alpha, and Haemoglobin Beta.

In yet another aspect of the method, the set of protein biomarkers includes at least one protein selected from the group consisting of Alpha- 1 -acid glycoprotein 1 and 2, matrix metalloproteinase-9, Peptidyl-prolyl cis-trans isomerase A, and Haptoglobin-related protein (IPI00431645.1).

In some aspect of the method, the set of protein biomarkers includes at least one protein selected from the group consisting of NADPH oxidase and Alpha-N- acetylgalactosaminidase.

In an aspect of the method, the set of protein biomarkers includes Alpha-N- acetylgalactosaminidase. In another aspect of the method, the set of protein biomarkers includes at least one protein selected from the group consisting of Protein SlOO-Al l (IPI00013895.1), Protein IPI00037070.3, catalase (IPI00465436.4), Choline transporter-like protein 2 derivative (IPI00903245.1), and titin isoformN2-B (IPI00985334.2).

In yet another aspect of the method, the set of protein biomarkers includes two or more biomarkers.

In some aspects of the method, the method further includes providing both the GCF sample and saliva sample, generating a first and second protein profile by analyzing the proteome of a GCF sample and a saliva sample, and determining an overlap region between the first and second protein profiles. The set of protein biomarkers are selected for distinguishing between particular states of periodontitis, including calculating a change in abundance of proteins within the overlap region during different stages of periodontitis and selecting those proteins which are under or over expressed during a single state of periodontitis.

In another aspect of the method, the method further includes generating a protein profile by analyzing the proteome of the at least one oral fluid sample, and clustering the protein profile to determine a set of protein biomarkers.

Demonstrated herein in an exemplary embodiment is a kit for diagnosing the status of periodontitis disease. The kit includes a set of protein biomarkers selected to distinguish between gingivitis and periodontitis.

In an aspect of the kit, the set of protein biomarkers includes at least one protein selected from the group consisting of haemoglobin chains alpha and beta, carbonic anhydrase 1 (International Protein Index or "IPI" #IPI00980674), and plastin-1.

In another aspect of the kit, the kit diagnoses gingivitis or mild periodontitis, and the set of protein biomarkers further includes at least one protein biomarkers from saliva data clusters IB, ID, 1A4, and 1A5.

BRIEF DESCRIPTION OF THE DRAWINGS

These and other aspects, features and advantages of which the disclosed methods and kits are capable of will be apparent and elucidated from the following description of embodiments of the methods and kits, reference being made to the accompanying drawings, in which

FIG. 1 is a flow-chart illustration of a method for diagnosing a status of an oral disease according to one embodiment; FIG. 2 is a graph of UV Absorbance (mAU) v. time (min) for a patient saliva sample. The UV trace was obtained as the output of an SCX system recording UV Absorbance at 214 nm.

FIG. 3 is a graph of UV Absorbance (mAU) v. time (min) for a patient GCF sample. The UV trace was obtained as the output of an SCX system recording UV Absorbance at 214 nm.

FIG. 4 is a group average clustering graph showing change in protein abundance (transformed by a base 2 logarithmic scale) vs. six (6) proteomic MS analysis groups (defined in TABLE 3) for GCF sample data. The group average clustering identified six (6) different clusters of protein biomarkers. Cluster 1 contained the majority of the proteins (243 proteins), cluster 2 contained 19 proteins, clusters 3, 5 and 6 each contained only one protein, and cluster 4 contained five proteins.

FIG. 5 is a first round re-clustering graph showing change in protein abundance (transformed by a base 2 logarithmic scale) vs. six (6) proteomic MS analysis groups (defined in TABLE 3) for GCF sample data. Cluster 1 from FIG. 4 was re-clustered into four cluster groups, where Group A contained the majority of the proteins (233), groups B and C contained two proteins each, and group D contained six proteins.

FIG. 6 is a second round clustering graph showing change in protein abundance (transformed by a base 2 logarithmic scale) vs. six (6) proteomic MS analysis groups (defined in TABLE 3) for GCF sample data. Cluster A from FIG. 5 was re-clustered into four cluster groups, where the largest cluster (1A1) still contained 171 proteins, cluster 1A2 contained 50 proteins, 1A3 contained 10 proteins, and 1A4 contained two proteins.

FIG. 7 is a final round clustering graph showing change in protein abundance (transformed by a base 2 logarithmic scale) vs. six (6) proteomic MS analysis groups (defined in TABLE 3) for GCF sample data. Cluster 1 Al from FIG. 6 was re-clustered into four groups. There are no clusters from this analysis which appear to be of interest, as the change in protein abundance is now below 1.0 in magnitude.

FIG. 8 is a group average clustering graph showing change in protein abundance (transformed by a base 2 logarithmic scale) vs. six (6) proteomic MS analysis groups (defined in TABLE 3) for Saliva sample data. The group average clustering identified five (5) different clusters of protein biomarkers. The largest cluster (1) contained 297 proteins, clusters 2 and 5 each contained one protein. Cluster 3 contained 11 proteins and cluster 4 contained three proteins. Cluster 2 appears to distinguish severe periodontitis from milder conditions. FIG. 9 is a first round re-clustering graph showing change in protein abundance (transformed by a base 2 logarithmic scale) vs. six (6) proteomic MS analysis groups (defined in TABLE 3) for GCF sample data. Cluster 1 from FIG. 8 was re-clustered into four cluster groups, the largest of which contained 166 proteins (cluster 1A). Clusters IB and ID contained 14 and one protein respectively. These two groups may distinguish between gingivitis/mild periodontitis and severe periodontitis.

FIG. 10 is a second round re-clustering graph showing change in protein abundance (transformed by a base 2 logarithmic scale) vs. six (6) proteomic MS analysis groups (defined in TABLE 3) for GCF sample data. Cluster 1 A from FIG. 9 was re-clustered into 5 cluster groups, the largest containing 150 proteins. There do not appear to be any significant clusters here based on lack of abundance change.

FIG. 11 is a second round re-clustering graph showing change in protein abundance (transformed by a base 2 logarithmic scale) vs. six (6) proteomic MS analysis groups (defined in TABLE 3) for GCF sample data. Cluster 1C from FIG. 9 was re-clustered into three clusters. Cluster 1C2 containing seven proteins show a near linear increase in proteins abundance up to severe periodontitis before a reduction post treatment.

FIG. 12 is a final round re-clustering graph showing change in protein abundance (transformed by a base 2 logarithmic scale) vs. six (6) proteomic MS analysis groups (defined in TABLE 3) for GCF sample data. Cluster 1A1 from FIG. 10. Five clusters were observed with a group of proteins showing an increase in abundance for severe periodontitis (cluster 1 Alb) but none of the other groups. There were five proteins identified in this cluster.

FIG. 13 is a Venn diagram showing the overlap between the GCF and Saliva sample datasets.

FIG. 14 is a cluster graph showing Log (2) transformed abundance levels of protein S100-P vs six (6) proteomic MS analysis groups (defined in TABLE 3) in combined GCF and Saliva sample data.

FIG. 15 is a cluster graph showing Log (2) transformed abundance levels of protein S100-A8 vs six (6) proteomic MS analysis groups (defined in TABLE 3) in combined GCF and Saliva sample data.

FIG. 16 is a cluster graph showing Log (2) transformed abundance levels of myosin-9 vs six (6) proteomic MS analysis groups (defined in TABLE 3) in combined GCF and Saliva sample data. FIG. 17 is a cluster graph showing Log (2) transformed abundance levels of transaldolase vs six (6) proteomic MS analysis groups (defined in TABLE 3) in combined GCF and Saliva sample data.

FIG. 18 is a cluster graph showing Log (2) transformed abundance levels of haemoglobin beta vs six (6) proteomic MS analysis groups (defined in TABLE 3) in combined GCF and Saliva sample data.

DETAILED DESCRIPTION OF EMBODIMENTS

Several embodiments of the methods and kits of the present application will be described in more detail below with reference to the accompanying drawings in order for those skilled in the art to be able to carry out the disclosed methods and kits. The methods and kits may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosed methods and kits to those skilled in the art. The embodiments do not limit the scope of disclosed methods or kits. The embodiments are only limited by the appended patent claims. Furthermore, the terminology used in the detailed description of the particular embodiments illustrated in the accompanying drawings is not intended to be limiting of the disclosed methods or kits.

The present application details methods for diagnosing the status of an oral disease, such as periodontitis. The methods may comprise determining the expression level of a set of biomarkers. The set of protein biomarkers may include one or more protein biomarkers which have been shown to vary in abundance at particular stages of oral disease. Accordingly, the set of protein biomarkers may be identified and quantified in expression in order to distinguish between different states of oral disease.

The methods of the present application demonstrate a role for biomarkers to serve as indicators of periodontitis at varying levels of severity, e.g. gingivitis, mild periodontitis. The work described herein demonstrates that elevated levels of multiple biomarkers can be used as a tool for accurately and rapidly determining the status of an oral disease, for example, periodontitis.

As used herein, the term "periodontal health state" is a threshold criteria based and not simply a vague state of health. Patients with a periodontal health state exhibit <10% sites with G.I. of 1.0 or B.O.P. and no sites with G.I. of 2.0 or 3.0. Additionally, they have no sites with interproximal attachment loss and no sites with ppd > 3mm. As used herein, the term "gingivitis state" is a threshold criteria based on patients exhibiting generalized gingivitis and is not simply a vague state. Generalized gingivitis is shown in patients exhibiting > 30% of sites with G.I. > 2.0, no sites with interproximal attachment loss, and no sites with ppd > 4mm.

As used herein, the term "mild periodontitis state" is a threshold criteria based on patients exhibiting mild-moderate periodontitis and is not simply a vague state. Mild- moderate periodontitis is shown in patients exhibiting ppd of 5-7mm and interproximal CAL of 2-4mm at > 8 teeth).

As used herein, the term "severe periodontics state" is a threshold criteria based on patients exhibiting severe periodontitis and is not simply a vague state. Severe periodontitis is shown in patients exhibiting ppd of > 7mm and an interproximal CAL of > 5mm at > 12 teeth.

As used herein, the term "biomarker" means a substance that is measured objectively and evaluated as an indicator of normal biologic processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention.

Provided herein is a method to diagnose a status of an oral disease by a measurement of prognostic protein biomarkers indicative of a select status of the oral disease. In an exemplary embodiment, the oral disease is periodontitis, and the protein biomarkers are indicative of either gingivitis, mild periodontitis, or severe periodontitis.

Through a proteomic analysis of gingival cervical fluid (GCF) and saliva samples taken from patients with varying states of oral disease, protein biomarkers may be identified which are increased or decreased in abundance during distinct phases of periodontitis. At least one protein biomarker may be used, alone or in combination, to distinguish between healthy patients, those suffering from gingivitis, and those suffering from mild or severe periodontitis.

Proteomic analysis may be conducted through a combination of liquid chromatography and mass spectrometry techniques. In particular, the proteome of GCF and Saliva oral liquid samples may be analyzed by Fourier Transform - tandem Mass Spectrometry (FT MS/MS). The FT MS/MS proteomic approach may be applied to GCF and Saliva samples collected from periodontally healthy volunteers, those with gingivitis, those with mild and severe periodontitis, and those with no teeth (edentulous controls), in order to try and elucidate a panel of biomarkers that will distinguish between healthy and diseased oral states. In particular, the FT MS/MS approach may be undertaken to discover novel protein biomarkers capable of distinguishing between periodontal health and disease, between gingivitis and periodontitis, and between mild and severe periodontitis, through the use of non-presumptive proteomic analysis of gingival crevicular fluid (GCF) and stimulated saliva.

The inventors have astonishingly found that the expression of a small set of particular protein biomarkers may be determined to identify gingivitis or mild periodontitis. These protein biomarkers show an enhanced change (either increase or decrease) in abundance during gingivitis/mild disease states of periodontitis, and show little changes during severe states of periodontitis. Additionally, the expression of a small set of particular protein biomarkers may be determined to identify severe periodontitis. These protein biomarkers show an enhanced change (either increase or decrease) in abundance during the severe state of periodontitis, and show little changes during gingivitis and mild states of periodontitis. The set of protein biomarkers for identifying and distinguishing severe gingivitis relative to mild periodontitis or gingivitis.

With reference to FIG. 1, a method (S100) for diagnosing a status of an oral disease starts at S101. According to an exemplary embodiment, the oral disease is periodontitis and the status of periodontitis may include periodontal health, gingivitis, mild periodontitis, and severe periodontitis.

At S102, at least one oral fluid sample is provided. According to one embodiment, the oral disease is periodontitis and at least one of a GCF and Saliva sample are provided. The samples may be non-invasively collected from a patient.

At S104, a protein profile is generated by analyzing the proteome of at least one of GCF and Saliva samples. In another embodiment, the protein profile is discovered using LC FT MS/MS.

At S106, the protein profile is clustered to determine those proteins which are best fit to serve in a set of protein biomarkers. Clustering may be performed using a combination of statistical methods including principle component analysis, gamma statistics, and metric multidimensional scaling (MMDS). In one embodiment, group average link hierarchical clustering is employed to determine the set of protein biomarkers. In another embodiment, complete link hierarchical clustering methods are employed to determine the set of protein biomarkers.

At S108, a set of protein biomarkers is selected for distinguishing between different states of an oral disease. In one embodiment, the oral disease is periodontitis and the set of protein biomarkers are selected for distinguishing between gingivitis and periodontitis. In another embodiment, the oral disease is periodontitis and the set of protein biomarkers are selected for distinguishing between mild periodontitis and severe periodontitis.

At SI 10, the expression levels of the proteins in the selected set of protein biomarkers are determined to diagnose the status of the oral disease.

According to one aspect of the methods, a method for diagnosing the status of an oral disease comprises providing at least one oral fluid sample, generating a protein profile by analyzing the proteome of the at least one oral fluid sample, clustering the protein profile to determine a set of protein biomarkers, selecting a set of protein biomarkers for distinguishing between particular states of an oral disease, and determining the expression levels in the selected set of protein biomarkers to diagnose the status of the oral disease.

According to yet another aspect of the methods, a method for diagnosing the status of periodontitis disease comprises providing at least one of a gingival crevicular fluid (GCF) and a saliva sample, selecting a set of protein biomarkers for identifying a particular state of periodontitis, and determining the expression levels in the selected set of protein biomarkers to diagnose the status of the oral disease.

In some aspect of the methods, the set of biomarkers is selected by analyzing the proteome of gingival crevicular fluid (GCF) and saliva. Proteomic analysis may include Fourier Transform - tandem Mass Spectrometry (FT MS/MS) analysis of proteins which are identified to be over or under expressed in varying states of periodontitis.

Another aspect of the methods, the biomarkers may include only one, or a combination of particular biomarkers which are useful for the diagnosis of a disease state. The expression levels of one, two, or more protein biomarkers are determined to determine a status of an oral disease. In further aspects, three, four, five, or more biomarkers are determined and used to determine the status of an oral disease.

In various aspects of the methods, the one or more protein biomarkers are selected from the group consisting of haemoglobin chains alpha and beta, carbonic anhydrase 1 (International Protein Index or "IPI" #IPI00980674), and plastin 1. The method according to this aspect may be used to distinguish between a healthy state, gingivitis state, a mild state, and a severe state of periodontitis.

In yet another aspect of the methods, one or more protein biomarkers are selected from the group consisting of S100-P, transaldolase, S100-A8 (calgranulin-A), myosin-9, Haemoglobin Alpha, and Haemoglobin Beta. The method according to this aspect may be used to identify the severe state of periodontitis, and distinguish to the severe state of periodontitis from the milder states, e.g. mild periodontitis and gingivitis. In some aspects of the disclosed methods, one or more protein biomarkers are selected from the group consisting of Alpha- 1 -acid glycoprotein 1 and 2, matrix metalloproteinase-9, Peptidyl-prolyl cis-trans isomerase A, and Haptoglobin-related protein (IPI00431645.1). The method according to this aspect may be used to identify the severe state of periodontitis, and distinguish to the severe state of periodontitis from the milder states, e.g. mild periodontitis and gingivitis.

In still another aspect of the methods, protein biomarker Alpha-N- acetylgalactosaminidase is selected for identifying gingivitis or mild periodontitis state, and distinguishing them from a severe periodontitis state.

In a further aspect of the methods, one or more protein biomarkers are selected from NADPH oxidase and Alpha-N-acetylgalactosaminidase for identifying gingivitis or mild periodontitis, and distinguishing them from a severe periodontitis state.

According to some aspects, the method for diagnosing the status of an oral disease further includes providing the GCF and saliva sample, generating a first and second protein profile by analyzing the proteome of a GCF sample and a saliva sample, and determining an overlap region between the first and second protein profiles. The selecting the set of protein biomarkers for distinguishing between particular states of periodontitis may include calculating a change in abundance of proteins within the overlap region during different stages of periodontitis and selecting those proteins which are under or over expressed during a single state of periodontitis.

In yet another aspect, the method for diagnosing a status of an oral disease as disclosed by the previous embodiments is performed by a diagnostic kit. The diagnostic kit comprises a set of protein biomarkers for identifying the status of an oral disease. The kit includes the necessary reagents to carry out the assays of the disclosed methods.

While the present application has been described in terms of various embodiments and examples, it is understood that variations or improvements will occur to those skilled in the art. Therefore, only such limitations as appear in the claims should be placed on the disclosed embodiments.

EXAMPLES

Example 1 The proteome of gingival crevicular fluid (GCF) and saliva was analyzed to identify biomarkers for different oral disease states, e.g. gingivitis, mild periodontitis, and severe periodontitis. GCF and saliva samples were collected non-invasively from the mouths of several patients. Liquid chromatography techniques coupled with Fourier Transform - tandem Mass Spectrometry (FT MS/MS) were used to separate protein biomarkers from within the samples and to identify the protein biomarkers.

The FT MS/MS proteomic approach was applied to samples collected from periodontally healthy volunteers, those with gingivitis, those with mild and severe periodontitis, and those with no teeth (edentulous controls), in order to try and elucidate a panel of biomarkers that will distinguish between healthy and diseased oral states. In particular, the FTMS/MS approach was undertaken to discover novel protein biomarkers capable of:

1. distinguishing between periodontal health and disease

2. distinguishing between gingivitis and periodontitis

3. distinguishing between mild and severe periodontitis by non-presumptive proteomic analysis of gingival crevicular fluid (GCF) and stimulated saliva.

STUDY DESIGN

TABLE 1

Patient Group

Number For Oral Disease State

Sample Collection

Group 1 Patients with periodontal health (<10% sites with G.I. of 1.0 or B.O.P. & no sites with G.I. of 2.0 or 3.0. No sites with interproximal attachment loss and no sites with ppd > 3mm).

Group 2 Patients with generalized gingivitis (>30% of sites with G.I. > 2.0, no sites with interproximal attachment loss & no sites with ppd >4mm).

Group 3 Patients with mild-moderate periodontitis (ppd of 5-7mm and

interproximal CAL of 2-4mm at > 8 teeth).

Group 4 Patients with severe periodontitis (ppd of > 7mm & interproximal

CAL of > 5mm at > 12 teeth).

Group 5 Edentulous patients (no teeth) with no evidence of oral ulceration or

Five groups of patient volunteers were recruited as defined in TABLE 1. The study was performed as a cross-sectional study with no interventions planned other than routine therapy that may be clinically indicated. Only 1 visit was required at baseline for sampling, but those in Group 3 and 4 required routine periodontal scaling, root surface debridement and prophylaxis and were therefore re-examined and sampled 3-months following completion of their therapy. Longitudinal analysis was therefore available for groups 3 and 4. The clinical assessments were carried out by a trained study dental surgeon. SAMPLE COLLECTION

Volunteers were asked to provide 6 samples of GCF collected from the gingival (gum) margin, non- invasive ly on standard filter papers strips (Periopapers™). They were also asked to provide a stimulated saliva sample by rolling a sterile marble around their mouths for five minutes and expectorating into a graduated sterile glass collection vile for volume measurement.

GCF and saliva were collected from 10 volunteers in each of five clearly defined phenotypic groups: healthy, gingivitis, mild periodontitis, severe periodontitis, and edentulous patients as a -ve control group. A total of 50 patients were therefore recruited and sampled. Volunteers with periodontitis (Groups 3 & 4) were then treated non- surgically in order to remove the periodontal inflammation and restore improved health. GCF and saliva were also collected 3 months post -treatment in these two groups, providing longitudinal data.

Table 2 presents the mean clinical data at a time of baseline and post-therapy obtained from 50 patients representing five phenotypic groups. GCF and Saliva samples were collected from 10 volunteers in each of five clearly defined phenotypic groups: Group I (healthy), Group II (gingivitis), Group III (mild periodontitis), Group IV (severe periodontitis), Group V (edentulous patients as a negative control group), where the phenotypic groups are defined based on predefined clinical data thresholds. Volunteers with periodontitis (Groups 3 & 4) were treated non-surgically in order to remove the periodontal inflammation and restore improved health, and therefore have both "baseline" and "review" clinical data.

TABLE 2 Criteria Time Group 1 Group 2 Group 3 Group 4 Group 5

PPD Baseline 1.31 + 0.65 1.89 + .070 3.35 + 1.67 4.68 + 2.33 -

(mm) Review - - 2.45 + 1.06 3.06 + 1.56 -

Baseline

REC 0.00 + 0.00 0.00 + 0.00 0.70 + 0.86 0.77 + 0.89 -

(mm) Review - - 0.83 + .093 1.34 + 1.07 -

CAL Baseline 1.31 + 0.65 1.89 + .070 4.05 + 1.88 5.45 + 2.49 -

(mm) Review - - 3.27 + 1.44 4.37 + 1.92 -

Baseline

BOP d 3.60 + 2.24 - 100.57 + 61.28 127.29 + 71.10 -

(% sites) Review - - 29.22 + 18.36 40.13 + 22.07 -

BOP m Baseline 2.80 +2.56 27.00 + 24.9 51.70 + 47.40 71.30 + 60.79 -

(% sites) Review - - 15.20 + 13.69 20.60 + 17.02 -

MGI Baseline 44.00 127.10 189.30 192.90 -

(FM

total) Review - - 83.90 112.70 -

PI Baseline - - 79.80 + 72.72 86.90 + 73.73 -

(% sites) Review - - 55.67 + 50.60 49.80 + 42.38 -

GCF Baseline 0.10 +0.08 0.29 + 0.14 0.33 + 0.20 0.49 + 0.27 -

(mean

vol μΐβ) Review - - 0.23 + 0.15 0.32 + 0.23 -

SAMPLE PROCESSING GFC Samples

GCF samples were collected on periopaper strips from the mesio-buccal sites of six teeth per volunteer, for 30 seconds as is convention and volumes read on a Perotron 8000™ (Chappie et al 1999). These were placed in 400μί of a lOOmM ammonium bicarbonate buffer in 1.5 mL screw top cryo-tubes. The GCF samples were immediately frozen to -80°C. Prior to analysis GCF was defrosted on ice. The tubes were vortexed for 30 seconds and the solution removed into a clean snaptop eppendorf tube. 200μί of ammonium bicarbonate (100 mM) was added to the strips. These were re-vortexed for 30 seconds and re-centrifuged at 13,000 RPM for five minutes. The solution was removed and added to the previous. From each sample within a group 150μί was combined to give a single "pooled" sample per group. Individual patient samples were held back to allow a post-study re-evaluation at a patient- specific level once the preferred biomarker panels had been elucidated. Therefore 6 x 1.5 mL "population" samples were available for proteomic analysis by MS as indicated in Table 3. TABLE 3

Saliva Samples

Saliva production was stimulated using a sterile marble and collected for five minutes into 15 mL Falcon tubes. Tubes were frozen at -80°C. Prior to analysis the saliva was defrosted at 4°C. Additional falcon tubes were weighed prior to defrost to transfer the clarified saliva to. Once defrosted the saliva was aliquoted into 1.5 mL snaptop eppendorf tubes and centrifuged at 13,000 rpm for five minutes. The supernatant was transferred into the pre-weighed tubes. The debris pellet was also retained for potential future analysis. Both the weight and volume of saliva was recorded. 10.5μί of each saliva sample per group was combined in the same manner as GCF samples. However, unlike GCF, saliva was available from the edentulous patient group (Group 5), therefore a total of 7 x 105μί "population" saliva samples resulted. As for GCF the individual patient samples were held back to allow future "patient- level" analysis. The Pooled saliva samples were centrifuged at 13,000 RPM for five minutes and ΙΟΟμί retained. This was to ensure no debris was transferred into the final sample. Ammonium bicarbonate (ΙΟΟμί, 200mM) was added to each sample.

SAMPLE ANALYSIS BY LC FT MS/MS

Dithiothrietol was added (20μΕ, 50mM) to both GCF and saliva samples, which were incubated with shaking at 60 °C for 45 minutes to reduce any disulphide bonds. The samples were returned to room temperature prior to addition of lodoacetamide (ΙΟΟμί, 22mM) and incubation at room temperature in the dark for 25 minutes. lodoacetamide alkylates free thiol group on cysteine residues. Dithiothrietol (2.8μΕ, 50mM) was added to quench any remaining lodoacetamide. 1 μg of Lys-C (cleaves proteins at the C terminus of lysine residues) was added to each sample (1 : 100 enzyme :protein) and incubated at 37°C with shaking for four hours. 2μg of trypsin (cleaves proteins at the C terminus of lysine and arginine residues) was added and the digest continued over night at 37°C.

The samples were vacuum centrifuged dry prior to desalting (required for iTRAQ labelling). The samples were acidified (200μΙ,, 0.5% TFA) and desalting was performed using a Macrotrap (Michrom). The trap was wetted with acetonitrile (3x 50%, 200μί) followed by washing with trifluoroacetic acid (3x 0.1 %, 200μί). The sample was then loaded through the trap and the elutant passed through the trap again. The trap was washed again with trifluoroacetic acid (3x 0.1 %, 200μί), finally the peptides were eluted with acetonitrile (70%), ΙΟΟμί). The samples were vacuum centrifuged dry.

The dry samples were labeled with the iTRAQ 8-plex labels as shown in Table 4 below. The labeling allows all samples to be subsequently mixed together and run under one set of conditions in triplicate. Subsequently the individual group samples were identified from the iTRAQ labels.

TABLE 4

The samples were incubated with the labels for two hours at room temperature before all individual samples were mixed together for GCF and Saliva respectively. The combined samples (1 pooled saliva and 1 pooled GCF) were vacuum centrifuged dry. The samples were re-suspended in ΙΟΟμί of mobile phase A for the SCX system (10 mM KH₂P0₄, pH 3, 20% MeCN). The peptides were separated using strong cation exchange chromatography using the above mobile phase A and mobile phase B (10 mM KH₂P0₄, 500 mM KC1, pH 3, 20% MeCN ). The gradient ran for 90 minutes. 15 fractions were collected. Fractions 15 and 12 were combined as were 13 and 14 to give 13 fractions.

With reference to FIGs. 2 and 3, resulting SCX UV traces with the UV recorded at 214 nm are shown for a Saliva sample and GCF sample respectively. The Saliva and GCF samples were then desalted with the Macrotrap LC column as above, vacuum centrifuged and re-suspended in 200μΙ, of 0.1 % formic acid. 20μί of the samples were desalted with two ziptips and eluted in 20μί.

Fraction Analysis

Each fraction was analysed in triplicate by LC-MS/MS. Peptides were loaded onto a 150mm Acclaim PepMaplOO C18 column in mobile phase A (0.1% formic acid). Peptides were separated over a linear gradient from 3.2% to 44% mobile phase B (acetonitrile + 0.1 % formic acid) with a flow rate of 350nl/min. The column was then washed with 90% mobile phase B before re-equilibrating at 3.2% mobile phase B. The column oven was heated to 35°C. The LC system was coupled to an Advion Triversa Nanomate (Advion, Ithaca, NY) which infused the peptides with a spray voltage of 1.7 kV. Peptides were infused directly into the LTQ-Orbitrap Velos ETD (Thermo Fischer Scientific, Bremen, Germany). The mass spectrometer performed a full FT-MS scan (m/z 380-1600) and subsequent collision induced dissociation (CID) MS/MS scans of the three most abundant ions followed by higher energy collisional dissociation (HCD) of the same three ions. The CID spectra were used to identify the peptides and the HCD spectra were used to quantify them.

Data analysis

The data were analyzed using Proteome Discoverer (VI .2, Thermo Fisher Scientific). Data were analyzed as the technical repeats. The Mascot and SEQUEST algorithms were used to search the data with identical setting used. The database was the IPI human database supplemented with oral bacteria as described by Socransky. This database was concatenated with a reverse version to provide false discovery rates. The data were searched with the following settings: semi-trypsin was selected as the enzyme with a maximum of 2 missed cleavages, 5 ppm mass accuracy for the precursor ion, fragment ion mass tolerance was set to 0.5 Da. Carboxyamidomethylation of cysteine and iTRAQ addition to the N-terminus and lysine residues were set as a static modification. Phosphorylation of serine, threonine and tyrosine was set as a variable modification as was oxidation of methionine and iTRAQ addition to tyrosine.

The search results from each of the technical replicates were combined and proteins which were identified with two or more peptides were classed as identified. Only unique peptides were used for protein quantification and protein grouping was employed (only proteins which contained unique peptides were used).

GCF ANALYSIS PRELIMINARY RESULTS - DISCOVERED PROTEINS From the analysis of all GCF samples, 270 proteins were identified with two or more peptides. This included 264 human proteins and 6 bacterial proteins. The identified proteins are shown along with relative quantification values in the Appendix, Supplemental Table 1. All proteins show ratios relative to the Healthy control group (label 113- health). This data was subsequently normalized to collected GCF volumes and also log transformed (base 2) to give positive and negative abundance values.

There were no proteins which were solely identified in any of the disease states. The majority of the proteins showed a decrease in abundance between health, gingivitis and disease (229 proteins were lower abundance in gingivitis compared to health, 195 in mild periodontitis and 174 in severe periodontitis). This decrease in abundance across the groups may be due to an increase in GCF volume as tissues become more inflamed and as evidenced in Table 2. Alternatively, a "non-normalized" analysis of GCF may be performed to address this issue, which is recognized in the literature (Lamster et al 1986, Chappie et al 1994 & 1999).

GCF CLUSTERING ANALYSIS PERFORMED ON DISCOVERED PROTEINS

Discovered proteins were clustered using the Poly SNAP 3 software. PolySNAP 3 compares each 1 dimensional protein profile with every other and uses a weighted mean of Pearson parametric and Spearman nonparametric correlation coefficients to produce similarity scores. The profiles were clustered using a combination of statistical methods including principle component analysis, gamma statistics, and metric multidimensional scaling (MMDS). The data were then visualized in dendrograms, PCA plots, and MMDS plots. In this analysis, the group average link hierarchical clustering and complete link hierarchical clustering methods were used to group the data. In all cases, the number of clusters used was automatically set by PolySNAP3.

From the group average clustering three rounds of clustering were performed. The group with the largest number of proteins was re-clustered at each point.

First Round of Clustering

With reference to FIG. 4, the first round of analysis provided 6 clusters. Cluster 1 contained the majority of the proteins (243 proteins), cluster 2 contained 19 proteins, clusters 3, 5 and 6 each contained only one protein and cluster 4 contained five proteins.

With continuing reference to FIG. 4, Cluster 4 may be of interest as it includes a set of proteins which decrease in abundance during disease but do not return to baseline post- resolution. The nineteen proteins identified as cluster 2 show an increase in abundance with gingivitis before returning to baseline like levels in periodontitis. This may be due to one of the GCF samples containing blood, however bleeding is a critical clinical sign of gingivitis and periodontitis and blood-related proteins may be very discriminatory between health and disease. There are several blood related proteins identified in this group including haemoglobin alpha and beta. This could be of interest as a group that could distinguish between gingivitis and periodontitis and health, notwithstanding the possible presence of blood. Clusters 3 and 5 for example appear to distinguish untreated periodontitis from health/gingivitis .

The proteins identified clusters of interest, clusters 3, 4, and 5, are shown in the Appendix, Supplementary Table 2.

Second Round of Clustering

With reference to FIG. 5, the 243 proteins from cluster 1 of FIG. 4 were re-clustered, which gave a total of four groups. Group 1A contained the majority of the proteins (233), groups IB and 1C contained two proteins each and group ID contained six proteins. Group ID shows little change between health and gingivitis before increasing with periodontitis. There is a fall in relative abundance between mild periodontitis and treated mild periodontitis and a return to baseline in the treated severe periodontitis. The two proteins identified in group 1C appear to follow disease, with a decrease to gingivitis and a larger decrease to the two perio groups before returning towards the baseline in the treated samples. Such proteins could be envisaged as being analyzed as outcome measures of whether treatment was successful or not.

The proteins identified in clusters of interest, clusters 1C and ID, are shown in the Appendix, Supplementary Table 3.

Third Round of Clustering

With reference to FIG. 6, the 233 proteins from cluster 1A of FIG. 5 were clustered again, resulting in four clusters, though the change in abundance is now less than 2 on the log scale (4 times increase/decrease). The largest cluster (1A1) still contained 171 proteins, cluster 1A2 contained 50 proteins, 1A3 contained 10 and 1A4 contained 2 proteins. Again there appear to be groups of potential interest in this analysis.

The proteins identified in each cluster of interest, 1A3 and 1A4, are shown in the

Appendix, Supplementary Table 4.

Final Round of Clustering With reference to FIG. 7, a final round of clustering was performed the 171 proteins from cluster 1A1 of FIG. 6. This resulted in 4 groups as shown in Figure 6. There are no clusters from this analysis which appear of interest.

The multiple rounds of clustering analysis suggest that there are some groups of proteins in GCF which may distinguish between different disease states of periodontitis.

SALIVA ANALYSIS PRELIMINARY RESULTS - DISCOVERED PROTEINS

All saliva samples were analyzed similarly to GCF samples. 314 proteins were identified with two or more peptides, including 307 human proteins and 7 bacterial proteins. One protein was identified in only one sample group (edentulous). The identified proteins are shown along with relative quantification values in the Appendix, Supplemental Table 5.

SALIVA CLUSTERING ANALYSIS PERFORMED ON DISCOVERED PROTEINS

First Round of Clustering

For the clustering analysis the edentulous samples were not included.

Clustering analysis was performed using PolySNAP3. With reference to FIG. 8, the first round of clustering resulted in five clusters. The largest cluster (1) contained 297 proteins, while clusters 2 and 5 each contained one protein. Cluster 3 contained 11 proteins and cluster 4 contained three proteins. As with the GCF dataset there is a group of proteins which are down-regulated with disease and do not return to baseline following treatment. Cluster 2 appears to distinguish severe periodontitis from milder conditions.

The proteins identified in the cluster of interest, cluster 2, is shown in the Appendix, Supplementary Table 6.

Sound Round of Clustering

With reference to FIG. 9, Cluster 1 from FIG. 8 was re-clustered resulting in an additional 4 groups. The largest group contained 166 proteins (cluster 1A). Clusters IB and ID contained 14 and one protein respectively. These two groups may distinguish between gingivitis/mild periodontitis and severe periodontitis. However, in both cases, the signal for severe periodontitis is close to healthy levels, though after treatment an increase in protein abundance for both mild and severe periodontitis occurs. Cluster 1C contained 116 proteins. In this group, little change is shown between health and gingivitis followed by an increase to mild periodontitis before a large increase to severe periodontitis. These values are reduced in the treated samples but still at greater levels than the gingivitis group. The proteins identified in each cluster of interest, clusters IB and ID, are shown in the Appendix, Supplementary Table 7.

Third Round of Clustering

With reference to FIG. 10, cluster 1 A from FIG. 9 was re-clustered. Cluster 1 A gave resulted in 5 groups, the largest cluster (1A1) containing 150 proteins. There do not appear to be any significant clusters here. Cluster 1A4 provided 3 proteins, and Cluster 1A5 provided one protein. The protein biomarkers in Clusters 1A4 and 1A5 all show an increase or decrease in protein abundance between health and gingivitis which is greater in mild periodontitis but less in severe periodontitis.

The proteins identified in clusters 1A4 and 1A5 are shown in the Appendix,

Supplementary Table 8.

With reference to FIG. 11, cluster 1C from FIG. 9 was re-clustered, resulting in three clusters. Cluster 1C2 contained 7 proteins showing a near linear increase in proteins abundance up to severe periodontitis before a reduction post treatment. This group was not clustered any further. The proteins identified in cluster 1C2 are shown in the Appendix, Supplementary Table 9.

Final Round of Clustering

With reference to FIG. 12, cluster 1A1 from FIG. 10 was re-clustered. Five clusters were observed with a group of proteins showing an increase in abundance for severe periodontitis (cluster 1 Alb) but none of the other groups. There were five proteins identified in this cluster. The proteins identified in cluster lAlb are shown in the Appendix, Supplementary Table 10.

COMPARISON OF GCF AND SALIVA DATASETS

The proteins observed in the two data sets were compared to identify protein biomarkers that were discovered in both saliva and GCF samples. With reference to FIG. 13, 95 proteins were identified in both the GCF and saliva, represented by the overlapping region of the Venn diagram of FIG. 13. This is approximately a third of the total number of proteins identified on the GCF dataset.

The proteins which are observed in the overlapping region are shown in the

Appendix, Supplemental Table 11. The associated abundance data for the proteins in Supplemental Table 11 was collected and subsequently transformed to portray the log (2) ratios for the protein abundance observed. Additionally, two values for the GCF was measured, one normalized to the volume collected, and the other not. If it is assumed that GCF is a component of saliva, and when saliva is not normalized to the same GCF volumes, it may be of use to compare the three values. Analysis of these triple values shows some of these proteins to have very similar profile. Some of those protein biomarkers with a large increase or decrease in abundance values are depicted in FIGS. 14-17.

FIG. 14 shows the three traces for protein S100-P. S100-P is involved in the regulation of cell cycle progression and differentiation. It has been observed in both GCF and saliva and has been suggested as a potential biomarker for oral squamous cell carcinoma. As shown in FIG. 14, iTRAQ measured abundance of S100-P protein show there is a large increase between mild periodontitis and severe periodontitis. Accordingly, S100-P may serve as a useful protein biomarker for distinguishing between mild and severe periodontitis.

FIG. 15 shows the three traces for protein S100-A8, which is also known as calgranulin-A. It has antimicrobial activity towards bacteria. It is a pro -inflammatory mediator in inflammation and up-regulates the release of IL8. High levels of S100-A8 have been detected in the plasma of patients with chronic periodontitis. As shown in FIG. 15, iTRAQ measured abundanceof S100-A8 protein show there is a large increase between mild periodontitis and severe periodontitis. Accordingly, S100-A8 may serve as a useful protein biomarker for distinguishing between mild and severe periodontitis.

FIG. 16 shows the three traces for protein myosin-9. As shown in FIG. 16, iTRAQ measured abundance of myosin-9 protein show there is a large increase between mild periodontitis and severe periodontitis. Accordingly, myosin-9 may serve as a useful protein biomarker for distinguishing between mild and severe periodontitis.

FIG. 17 shows the three traces for protein transaldolase. As shown in FIG. 17, iTRAQ measured abundance of transaldolase protein show there is a large increase between mild periodontitis and severe periodontitis. Accordingly, transaldolase may serve as a useful protein biomarker for distinguishing between mild and severe periodontitis.

FIG. 18 shows the three traces for protein haemoglobin beta. As shown in FIG. 18, iTRAQ measured abundance of haemoglobin beta protein show there is a large increase between mild periodontitis and severe periodontitis. The traces also increase and decrease throughout the range of all oral disease states. Accordingly, haemoglobin beta (or alpha) may serve as a useful protein biomarker for distinguishing between mild and severe periodontitis, and/or other oral disease states. DISCUSSION OF RESULTS

Gene ontology analysis using The Database for Annotation, Visualization and Integrated Discovery (DAVID) on the GCF and Saliva datasets shows that the most significantly enriched biological process in the saliva dataset were the defense responses, and in GCF dataset, was cytoskeletal organization. The top twenty processes are shown in the Appendix, Supplemental Table 12. Seven of the twenty are enriched in both GCF and saliva including defense responses, responses to stimuli, and glycolysis.

The analysis of GCF and saliva identified 270 proteins in GCF and 314 proteins in saliva of which 95 were identified in both. All proteins except one (solely identified in edentulous saliva) were quantified over the different disease and resolution phases. Of the proteins which are identified in both GCF and saliva there are several proteins which show increases (in both GCF and Saliva datasets) with disease which could potentially be used to distinguish between health, gingivitis, mild and severe periodontitis and resolution of disease.

According to an exemplary embodiment, a method for diagnosing a status of an oral disease includes selecting at least one protein biomarker from the group consisting of: haemoglobin chains alpha and beta, carbonic anhydrase 1(IPI00980674), and plastin-1. The method may further include diagnosing the status at least one of a healthy state, gingivitis state, and a mild and/or severe periodontitis state. In another embodiment, the at least one protein biomarker is selected from the group consisting of the protein biomarkers in saliva data cluster 1C2 (Supplemental Table 9): Protein #IPI00016347.5, Protein #IPI00377122.4, haemoglobin subunit alpha (IPI00410714.5), haemoglobin subunit delta (IPI00473011.3), haemoglobin subunit beta (IPI00654755.3), protein # IPI00980674.1, and protein accession number #083773.

There are also several protein biomarkers which are potential indicators for severe periodontitis by showing increases in abundance in both the GCF and saliva datasets. In an exemplary embodiment, a method for diagnosing severe periodontitis includes selecting at least one protein biomarker from the group consisting of: S100-P, transaldolase, S100-A8 (calgranulin-A), myosin-9, haemoglobin alpha, and haemoglobin beta. In another aspect, the method for diagnosing severe periodontitis includes selecting at least one protein biomarker from the group consisting of the protein biomarkers in saliva data cluster lAlb (Supplemental Table 10): Protein S100-A11 (IPI00013895.1), Protein IPI00037070.3, catalase (IPI00465436.4), Choline transporter-like protein 2 derivative (IPI00903245.1), and titin isoformN2-B (IPI00985334.2). In yet another aspect, the method for diagnosing severe periodontitis includes selecting at least one protein biomarker from the group consisting of: S100-P, transaldolase, S100-A8 (calgranulin-A), myosin-9, haemoglobin alpha, and haemoglobin beta, alpha- 1 -acid glycoprotein 1 and 2, matrix metalloproteinase-9, peptidyl-prolyl cis-trans isomerase A and haptoglobin-related protein (IPI00431645.1 ).

According to another exemplary embodiment, a method for diagnosing gingivitis or mild periodontitis includes selecting at least one protein biomarker from the group consisting of the protein biomarkers in saliva data clusters IB, ID (Supplementary Table 7) and/or in saliva data clusters 1A4, 1 A5 (Supplementary Table 8). These protein biomarkers all show an increase or decrease in protein abundance between health and gingivitis which is greater in mild periodontitis but less in severe periodontitis. It may be possible to use these to differentiate between gingivitis and mild periodontitis with severe periodontitis.

According to another aspect, a method for diagnosing gingivitis or mild periodontitis includes selecting at least one protein biomarker from NADPH oxidase activator- 1 and alpha- N-acetylgalactosaminidase. NADPH oxidase activator- 1 is involved in the production of reactive oxygen species. alpha-N-acetylgalactosaminidase portrays has some of the highest ratios for gingivitis and mild periodontitis compared to severe periodontitis. This protein is involved in the breakdown of glycolipids. In another aspect, the method for diagnosing gingivitis or mild periodontitis includes selecting an Alphaa alpha-N-acetylgalactosaminidase biomarker.

APPENDIX

SUPPLEMENTARY TABLE 1

A6: A6: A6: A6: A6:

Accession Description

114/113 115/113 116/113 117/113 118/113

A8AW99 Phosphoenolpyruvate carboxylase 1.091 2.214 2.994 1.390 1.661

OS=Streptococcus gordonii (strain Challis /

ATCC 35105 / CHI / DL1 / V288) GN=ppc

PE=3 SV=1

A7I0P7 Peptide chain release factor 2 2.185 6.140 9.502 1.589 2.120

OS=Campylobacter hominis (strain ATCC BAA- 381 / LMG 19568 / NCTC 13146 / CH001A)

GN=prfB PE=3 SV=1 - [RF2_CAMHC]

A8AX28 tRNA pseudouridine synthase B 2.447 7.298 12.453 2.095 1.862

OS=Streptococcus gordonii (strain Challis /

ATCC 35105 / CHI / DL1 / V288) GN=truB

PE=3 SV=1 - [TRUB_STRGC]

A8AW24 Isoleucine--tRNA ligase OS=Streptococcus 1.378 2.731 3.417 0.891 0.519 gordonii (strain Challis / ATCC 35105 / CHI /

DL1 / V288) GN=ileS PE=3 SV= 1

IPI00003269.1 Beta-actin-like protein 2 1.174 2.429 4.466 0.977 1.590

IPI00003935.6 Histone H2B type 2-E 1.704 3.139 7.450 1.589 1.710

IPI00004550.5 Keratin, type I cytoskeletal 24 0.868 2.271 3.037 0.915 1.134

IPI00005721.1 Neutrophil defensin 1 1.062 0.949 1.070 0.923 1.599

IPI00006988.1 Resistin 2.419 0.897 0.642 0.961 2.719

IPI00007047.1 Protein S100-A8 1.545 2.762 3.767 1.515 2.262

IPI00008359.2 Keratin, type II cytoskeletal 2 oral 0.940 1.217 1.617 1.403 1.828

IPI00008405.5 Arylsulfatase F 1.650 3.529 5.536 1.426 2.000

IPI00008895.1 Epithelial membrane protein 2 6.951 13.266 2.545 10.122 6.138

IPI00009724.3 Isoform 1 of EF-hand calcium-binding domain- containing protein 6 1.471 8.313 13.940 1.860 1.369

IPI00009865.4 Keratin, type I cytoskeletal 10 0.935 1.487 1.166 1.344 1.038

IPI00009866.7 Isoform 1 of Keratin, type I cytoskeletal 13 0.918 1.528 1.612 1.242 1.393

IPI00009867.3 Keratin, type II cytoskeletal 5 1.269 2.339 2.862 1.999 2.119

IPI00010133.3 Coronin-IA 2.069 2.459 4.193 1.629 2.510

IPI00010349.1 Alkyldihydroxyacetonephosphate synthase, 2.729 12.079 12.838 11.323 1.586 peroxisomal

IPI00010471.6 Plastin-2 1.663 3.060 5.513 1.635 2.622

IPI00013163.1 Myeloid cell nuclear differentiation antigen 2.025 2.914 5.563 1.109 1.678

IPI00013890.2 Isoform 1 of 14-3-3 protein sigma 1.877 4.014 7.830 1.566 1.574

IPI00013895.1 Protein S100-A11 1.011 0.550 0.480 1.003 2.233

IPI00017526.1 Protein S100-P 1.411 1.835 4.329 1.192 1.657

IPI00019038.1 Lysozyme C 1.427 2.107 2.605 1.293 1.787

IPI00019359.4 Keratin, type I cytoskeletal 9 1.547 1.827 1.793 1.385 1.341

IPI00019502.3 Isoform 1 of Myosin-9 1.787 2.006 2.761 1.386 2.194

IPI00019580.1 Plasminogen 2.288 1.643 1.937 1.261 1.948

IPI00019869.3 Protein S100-A2 8.362 3.474 4.944 2.218 2.994

IPI00020091.1 Alpha-l-acid glycoprotein 2 1.461 0.453 0.519 0.699 1.969

IPI00021263.3 14-3-3 protein zeta/delta 1.935 2.378 4.007 1.337 2.087

IPI00021439.1 Actin, cytoplasmic 1 1.532 3.145 4.896 1.445 2.320

IPI00021828.1 Cystatin-B 1.026 1.725 1.936 1.094 1.383

IPI00021841.1 Apolipoprotein A-I 2.054 1.828 3.046 1.710 2.498

IPI00022371.1 Histidine-rich glycoprotein 2.157 1.828 2.648 1.880 2.269

IPI00022429.3 Alpha-l-acid glycoprotein 1 1.524 0.515 0.601 0.977 2.217

IPI00022463.2 Serotransferrin 2.035 1.860 2.638 1.763 2.374

IPI00022488.1 Hemopexin 2.864 2.697 3.481 1.933 3.455

IPI00022974.1 Prolactin-inducible protein 1.786 1.298 1.464 1.495 3.193

IPI00025512.2 Heat shock protein beta-1 1.152 1.258 1.517 1.471 2.055

IPI00027462.1 Protein S100-A9 1.380 2.491 2.812 1.513 2.136

IPI00027463.1 Protein S100-A6 2.846 4.107 3.748 2.172 4.088

IPI00027509.5 Matrix metalloproteinase-9 2.216 3.561 3.127 2.021 1.365

IPI00027769.1 Neutrophil elastase 1.836 2.667 9.024 1.281 1.919

IPI00028064.1 Cathepsin G 1.391 1.130 1.206 1.072 1.571

IPI00030362.1 Isoform 1 of Proteolipid protein 2 1.389 2.013 4.137 1.411 1.791

IPI00032294.1 Cystatin-S 0.657 0.573 0.729 0.853 1.867 IPI00037070.3 Uncharacterized protein 2.165 0.946 1.272 1.135 1.887

IPI00081836.3 Histone H2A type 1-H 1.107 0.716 1.909 1.903 3.763

IPI00152758.1 FU00198 protein (Fragment) 23.303 4.014 7.989 2.169 2.697

IPI00167191.1 CDNA FU25707 fis, clone TST04879 1.935 0.186 0.337 1.789 2.778

IPI00168728.1 FU00385 protein (Fragment) 2.284 9.149 13.295 3.104 2.935

IPI00174541.1 Isoform 4 of Interleukin-1 receptor antagonist 1.402 0.948 1.229 1.205 2.084 protein

IPI00177428.1 Isoform 2 of Mitochondrial intermembrane 1.091 0.307 0.335 0.775 0.854 space import and assembly protein 40

IPI00180240.2 Thymosin beta-4-like protein 3 1.819 2.538 4.657 1.818 2.105

IPI00216691.5 Profilin-1 2.126 3.193 4.898 1.993 3.376

IPI00216974.1 Isoform 1 of Probable phospholipid- 37.175 0.920 3.993 1.491 1.460 transporting ATPase IK

IPI00217465.5 Histone HI.2 3.025 3.780 6.682 2.143 3.026

IPI00217468.3 Histone HI.5 1.816 3.043 4.613 1.645 2.749

IPI00217963.3 Keratin, type I cytoskeletal 16 0.906 1.190 1.304 1.299 1.537

IPI00218131.3 Protein S100-A12 1.831 2.688 8.152 1.919 2.218

IPI00218918.5 Annexin Al 1.310 2.384 2.914 1.317 1.806

IPI00219037.5 Histone H2A 2.459 3.327 8.477 1.536 2.063

IPI00219208.1 Isoform 2 of Granulocyte-macrophage colony- 1.797 2.298 4.347 1.840 2.175 stimulating factor receptor subunit alpha

IPI00219395.3 Isoform 6 of Voltage-dependent T-type calcium 3.160 6.602 10.369 2.696 4.044 channel subunit alpha-lG

IPI00219502.1 Isoform Short of Gl/S-specific cyclin-E2 1.657 1.027 1.319 1.477 4.004

IPI00219757.13 Glutathione S-transferase P 1.563 2.730 4.126 1.820 2.059

IPI00220056.1 Kelch domain-containing protein 5 1.232 1.456 2.136 1.420 1.499

IPI00220327.4 Keratin, type II cytoskeletal 1 1.116 1.181 1.449 1.163 1.170

IPI00236554.1 Isoform H14 of Myeloperoxidase 2.434 4.087 10.319 1.735 2.189

IPI00290077.3 Keratin, type I cytoskeletal 15 0.981 0.876 0.777 1.045 1.535

IPI00292579.4 Stabilin-2 5.188 18.978 17.247 7.542 2.843

IPI00293665.9 Keratin, type II cytoskeletal 6B 0.924 1.657 1.791 1.741 1.746

IPI00296215.2 Epithelial cell adhesion molecule 13.055 0.830 1.428 1.586 1.096

IPI00297056.2 Cornulin 1.613 2.387 2.849 1.361 1.963

IPI00297763.4 Retinal-specific ATP-binding cassette 1.662 3.618 7.512 1.030 1.452 transporter

IPI00298497.3 Fibrinogen beta chain 1.627 1.774 2.386 1.309 1.816

IPI00299078.1 Salivary acidic proline-rich phosphoprotein 1/2 0.684 0.967 0.989 1.197 1.396

IPI00299547.4 Isoform 1 of Neutrophil gelatinase-associated 2.854 3.215 8.337 1.534 3.224 lipocalin

IPI00300725.7 Keratin, type II cytoskeletal 6A 0.909 1.345 1.079 2.018 1.701

IPI00305477.6 Cystatin-SN 1.286 1.089 1.617 1.253 2.407

IPI00307770.2 Uncharacterized protein 1.106 1.956 1.584 1.259 1.019

IPI00328296.2 PDZ domain-containing protein GIPC2 0.765 0.759 0.811 0.735 0.923

IPI00334400.2 Isoform 2 of Plakophilin-4 0.374 0.797 1.320 0.616 0.541

IPI00374975.2 Probable phosphoglycerate mutase 4 0.857 0.479 0.362 1.082 2.494

IPI00375293.2 Isoform 2 of High affinity immunoglobulin

gamma Fc receptor I 2.130 7.149 20.796 0.789 2.361

IPI00377081.1 erythrocyte band 7 integral membrane protein 1.951 2.869 5.214 1.399 1.858 isoform b

IPI00384282.2 FERM, C-terminal PH-like domain containing 1.804 2.321 1.684 1.562 2.468 protein

IPI00384444.6 Keratin, type I cytoskeletal 14 1.098 1.767 1.755 1.580 1.937

IPI00384938.1 Putative uncharacterized protein 3.048 3.013 4.415 2.739 3.220

DKFZp686N02209

IPI00385373.1 Truncated proliferating cell nuclear antigen 2.277 5.425 10.797 1.879 3.952

IPI00394951.1 Putative ubiquitin carboxyl-terminal hydrolase 0.794 1.094 1.055 1.100 1.280

17-like protein 1

IPI00397585.1 Isoform 2 of Leucine-rich repeat LGI family

member 4 1.485 5.536 11.795 1.242 1.470

IPI00399007.7 Putative uncharacterized protein 2.176 4.694 8.528 2.583 4.705

DKFZp686I04196 (Fragment)

IPI00402502.2 secernin-2 isoform 2 1.847 3.169 5.171 1.638 1.359

IPI00410714.5 Hemoglobin subunit alpha 19.785 2.146 5.893 1.815 2.553

IPI00418153.1 Putative uncharacterized protein 2.111 9.132 16.172 3.105 3.051

DKFZp686I15212

IPI00418262.5 Fructose-bisphosphate aldolase 2.633 2.420 4.379 1.698 1.846

IPI00795501.3 Low affinity immunoglobulin gamma Fc region 1.571 0.823 0.820 1.112 2.117 receptor III-B

IPI00796727.1 Uncharacterized protein 1.214 1.058 1.307 1.277 1.278

IPI00797270.4 Isoform 1 of Triosephosphate isomerase 1.602 4.407 9.141 1.604 1.199

IPI00807400.2 Isoform 2 of Structural maintenance of 1.721 2.850 4.573 1.550 1.726 chromosomes protein IB

IPI00815843.1 RPL14 protein (Fragment) 1.016 1.489 1.604 1.720 1.596

IPI00816314.1 Putative uncharacterized protein 3.011 3.313 6.320 2.707 3.279

DKFZp686I15196

IPI00816687.1 FGB protein (Fragment) 1.627 1.774 2.386 1.309 1.816

IPI00816741.1 Complement component 5 variant (Fragment) 1.971 6.126 7.845 2.710 1.725

IPI00829896.1 Hemoglobin Lepore-Baltimore (Fragment) 2.476 2.209 3.061 1.420 1.481

IPI00845508.3 BAH and coiled-coil domain-containing protein 2.207 4.497 7.543 2.159 3.719

1

IPI00848259.1 Merlin variant 14 0.763 3.070 1.933 2.357 1.915

IPI00848276.1 Isoform 1 of Uncharacterized protein C10orfl8 0.452 1.711 1.520 0.635 0.597

IPI00853045.1 Anti-RhD monoclonal T125 kappa light chain 2.325 2.720 4.016 1.949 3.138

IPI00853068.2 Hemoglobin alpha-2 46.021 2.885 11.499 2.248 3.976

IPI00853525.1 Uncharacterized protein 1.991 1.067 1.430 1.674 2.615

IPI00855985.2 Mitogen-activated protein kinase kinase kinase 1.515 2.157 3.919 1.315 2.010

1

IPI00872684.2 cDNA FU54141, highly similar to Ezrin 1.669 1.861 1.318 1.498 2.844

IPI00878282.1 23 kDa protein 2.295 6.632 15.416 2.522 1.777

IPI00879437.1 Protein 1.872 1.883 2.321 1.522 2.591

IPI00884996.1 Isoform 1 of Dynein heavy chain 6, axonemal 2.020 2.936 5.556 1.342 1.546

IPI00885046.1 Isoform 3 of Dynein heavy chain 1, axonemal 32.735 12.945 42.874 3.459 2.779

IPI00885122.1 Isoform 1 of Diffuse panbronchiolitis critical 2.041 3.306 9.940 1.637 2.026 region protein 1

IPI00888187.2 Putative zinc finger protein 487 8.799 4.879 5.499 3.205 5.113

IPI00893981.1 Uncharacterized protein 1.361 2.469 5.074 1.032 1.852

IPI00902755.1 FGA protein (Fragment) 2.400 2.028 3.058 2.061 2.746

IPI00903112.1 cDNA FU36533 fis, clone TRACH2004428, 2.664 3.137 5.644 2.044 2.428 highly similar to Lactotransferrin (Fragment)

IPI00908402.1 cDNA FU51275 1.554 0.515 0.526 1.250 2.617

IPI00908776.3 cDNA FU61380, highly similar to Alpha-actinin- 1.971 2.092 2.061 1.342 2.370

4

IPI00908791.3 L-lactate dehydrogenase 1.690 2.824 5.085 1.566 2.454

IPI00908881.3 Glucose-6-phosphate isomerase 2.095 4.977 9.723 1.670 2.216

IPI00909059.5 cDNA FU53910, highly similar to Keratin, type 0.912 1.283 0.913 2.144 2.156

II cytoskeletal 6A

IPI00909509.1 cDNA FU59138, highly similar to Annexin A2 1.856 1.005 1.392 1.114 1.521

IPI00909530.1 cDNA FU52843, highly similar to Histone H3.3 1.910 3.080 6.500 1.568 2.261

IPI00909658.1 cDNA FU52759, highly similar to Plastin-2 1.812 2.489 6.118 1.494 2.698

IPI00910407.1 Peptidyl-prolyl cis-trans isomerase 1.879 2.581 2.584 1.471 1.961

IPI00910544.1 cDNA FU57640, highly similar to Serpin B5 1.521 2.576 2.975 1.682 2.259

IPI00910709.1 cDNA FU53133, highly similar to Erythrocyte 1.133 3.066 0.904 0.868 1.604 band 7 integral membrane protein

IPI00910754.1 L-lactate dehydrogenase A chain isoform 2 1.618 2.749 4.408 1.422 2.253

IPI00910974.1 Phosphoglycerate kinase 1.486 4.229 10.034 1.340 1.553

IPI00910979.1 pyruvate kinase isozymes M1/M2 isoform e 1.685 1.671 2.448 1.421 2.812

IPI00911039.1 cDNA FLJ54408, highly similar to Heat shock 1.587 1.556 1.862 1.324 1.772

70 kDa protein 1

IPI00914847.2 nebulin isoform 1 0.867 1.322 1.361 1.031 1.161

IPI00916185.2 Isoform 4 of Dynein heavy chain 1, axonemal 17.718 8.329 25.793 2.109 2.507

IPI00916517.2 28 kDa protein 1.997 3.800 4.818 1.948 3.008

IPI00917176.1 Isoform 5 of Dynein heavy chain 1, axonemal 21.419 5.385 11.708 1.394 1.894

IPI00922216.1 Adenylyl cyclase-associated protein 1.669 2.359 2.792 1.493 2.233

IPI00922673.1 cDNA FU55309 11.198 2.427 5.107 7.320 5.842

IPI00924436.1 Uncharacterized protein 0.855 0.734 0.950 1.141 1.961

IPI00924608.1 vacuolar protein sorting-associated protein 13D 4.375 15.621 22.791 6.247 2.323 isoform 1

IPI00925547.2 Uncharacterized protein 2.438 2.568 4.876 1.556 1.963

IPI00927887.1 Histone H2A 1.023 0.668 0.793 0.664 1.378

IPI00930073.1 cDNA, FLJ93744, highly similar to Homo 0.878 1.278 1.048 2.277 2.347 sapiens keratin 6E (KRT6E), mRNA

IPI00930144.1 Histone H2A 1.101 0.772 0.843 0.711 1.325 IPI00930351.1 Hbbm fused globin protein (Fragment) 5.696 2.581 4.831 1.515 1.644

IPI00930442.1 Putative uncharacterized protein 1.532 1.295 1.792 1.656 2.465

DKFZp686M24218

IPI00930614.1 GUCA1B protein (Fragment) 0.943 1.457 1.403 1.085 1.278

IPI00939521.1 10 kDa protein 3.468 2.723 5.483 1.624 1.930

IPI00940399.2 Uncharacterized protein 0.596 0.553 1.176 0.232 0.414

IPI00940673.2 cDNA FU36348 fis, clone THYMU2007025, 2.356 2.516 4.369 1.762 2.641 highly similar to TRANSKETOLASE

IPI00945626.2 cDNA FU54029, highly similar to 2.124 1.674 2.181 1.819 2.673

Serotransferrin

IPI00946655.1 Isoform 1 of Actin-related protein 3C 3.030 8.158 11.061 3.034 2.477

IPI00947307.1 cDNA FU58075, highly similar to Ceruloplasmin 3.799 2.779 4.874 2.259 4.018

IPI00964070.1 Uncharacterized protein 2.290 4.252 7.797 1.974 2.200

IPI00964635.1 Uncharacterized protein 1.843 1.324 1.650 1.286 1.907

IPI00965713.3 fibrinogen beta chain isoform 2 preproprotein 1.488 1.582 2.102 1.172 1.673

IPI00966664.1 Uncharacterized protein 2.641 1.602 2.256 1.275 2.020

IPI00967416.1 Uncharacterized protein 2.167 1.776 2.853 1.556 2.101

IPI00967791.1 Protein 1.582 2.155 2.671 1.559 2.464

IPI00972963.1 Lambda light chain of human immunoglobulin 2.264 2.955 4.213 2.075 3.259 surface antigen-related protein (Fragment)

IPI00973588.1 Full-length cDNA clone CS0DI019YF20 of 2.706 9.806 15.041 3.359 2.641

Placenta of Homo sapiens (Fragment)

IPI00974274.1 Uncharacterized protein 1.968 2.167 2.275 1.697 2.331

IPI00974428.1 Uncharacterized protein 55.064 1.529 2.624 4.044

IPI00975690.1 Vimentin variant 3 2.191 3.482 6.483 1.417 1.796

IPI00975801.1 Uncharacterized protein 1.883 0.863 0.946 1.047 2.470

IPI00976599.1 Uncharacterized protein 1.596 0.743 1.063 0.907 3.364

IPI00977575.1 Uncharacterized protein 39.712 4.075 22.681 1.709 1.810

IPI00978296.1 Uncharacterized protein 28.145 0.255 1.653 1.637 2.836

IPI00978338.1 Wilms tumor 1 5.475 3.551 10.012 1.042 1.521

IPI00978796.1 17 kDa protein 1.740 3.718 5.675 1.139 2.307

IPI00980674.1 Uncharacterized protein 13.509 1.040 2.885 1.677 2.479

IPI00981317.1 cDNA FU75025, highly similar to Homo sapiens 2.557 3.259 4.123 1.803 2.636 peptidylprolyl isomerase A (cyclophilin A)

(PPIA), transcript variant 2, mRNA

IPI00981659.1 Similar to Cold agglutinin FS-1 H-chain 1.504 1.967 3.733 0.982 1.173

IPI00981943.1 Uncharacterized protein 2.022 0.885 1.226 1.067 1.914

IPI00982472.1 Transaldolase 1.870 2.506 4.255 1.583 2.420

IPI00984226.2 Uncharacterized protein 2.988 0.950 1.276 1.116 1.606

IPI00985334.2 titin isoform N2-B 6.506 1.481 3.001 2.668 2.421

IPI01009324.2 Uncharacterized protein 2.015 2.419 3.996 1.458 2.271

IPI01009332.1 cDNA FU61543, highly similar to Desmoplakin 0.973 1.588 1.597 1.892 1.943

IPI01009809.1 51 kDa protein 1.093 1.572 1.574 1.323 1.570

IPI01010323.1 cDNA FU38286 fis, clone FCBBF3008153, 1.005 0.681 0.714 0.941 2.218 highly similar to ALPHA-AMYLASE 2B

IPI01011210.1 Isoform 4 of Potassium voltage-gated channel 1.865 4.165 6.680 1.856 3.342 subfamily C member 2

IPI01011319.1 annexin A6 isoform 2 2.030 2.117 2.293 1.766 2.373

IPI01011344.1 Uncharacterized protein 1.549 3.576 4.754 1.731 2.201

IPI01011530.1 Uncharacterized protein 1.711 3.147 4.479 1.649 2.247

IPI01011804.1 Uncharacterized protein 1.378 2.425 4.677 1.082 2.089

IPI01011912.1 Phosphoglycerate kinase 1.462 3.359 8.933 1.331 1.826

IPI01011970.1 6-phosphogluconate dehydrogenase, 1.477 1.984 3.160 1.281 1.592 decarboxylating

IPI01012623.1 Uncharacterized protein 2.982 6.695 10.668 2.551 3.922

IPI01012744.1 Uncharacterized protein 1.935 11.056 8.458 3.207 1.616

IPI01013112.1 Uncharacterized protein 2.596 8.476 17.899 2.424 3.131

IPI01013314.1 cDNA FU53395, highly similar to Prolyl 3- 18.301 27.571 55.459 16.630 3.594 hydroxylase 1

IPI01013441.1 Uncharacterized protein 2.293 1.376 1.354 1.366 2.016

IPI01013543.1 Triosephosphate isomerase 1.583 2.620 3.451 1.544 1.736

IPI01014005.1 AMY1A protein (Fragment) 1.105 0.879 0.901 1.148 2.442

IPI01014138.1 Uncharacterized protein 1.679 2.739 3.783 1.830 2.511

IPI01014668.1 Isoform 6 of Afadin 0.392 0.686 0.648 0.467 0.630

IPI01014975.1 Uncharacterized protein 2.447 1.090 1.955 1.969 2.527 IPI01015050.2 Uncharacterized protein 1.539 2.230 3.161 1.285 2.343

IPI01015738.1 Uncharacterized protein 1.962 2.414 2.212 1.611 2.282

IPI01018060.1 Ig lambda-3 chain C regions 2.143 3.807 6.225 2.172 3.213

IPI01018799.1 Isoform 2 of Dystonin 2.614 2.861 4.054 2.074 3.431

IPI01020720.1 cDNA FU54328, highly similar to Heat shock 2.232 3.358 5.006 1.677 2.299

70 kDa protein 1

IPI01021999.1 Uncharacterized protein 1.813 5.475 6.467 1.970 1.650

IPI01022175.1 cDNA FU55805, highly similar to Keratin, type 0.807 1.416 1.443 1.087 1.078

II cytoskeletal 4

IPI01022327.1 keratin, type II cytoskeletal 4 0.861 1.347 1.387 1.043 1.078

IPI01025024.1 27 kDa protein 1.850 1.722 2.055 1.495 2.357

IPI01025103.1 20 kDa protein 1.454 2.261 3.413 1.400 2.351

IPI01026451.1 Protein 2.571 7.608 26.692 0.218 0.825

IPI00019779.3 Putative uncharacterized protein 1.964 7.204 22.332 0.817 2.105

DKFZp686B0790

Q73NE3 ATP-dependent protease ATPase subunit HsIU 2.283 4.788 10.385 2.164 3.335

OS=Treponema denticola (strain ATCC 35405 /

CIP 103919 / DSM 14222) GN=hslU PE=3

SV=1 - [HSLU_TREDE]

Q97QZ6 Putative lipid kinase SP_1045 1.346 2.270 6.525 0.712 1.261

OS=Streptococcus pneumoniae GN=SP_1045

PE=1 SV= 1 - [Y1045_STRPN]

SUPPLEMENTARY TABLE 2

CLUSTER 3

Sample # 52: IPI00167191.1 CDNA FU25707 fis, clone TST04879

CLUSTER 4

SUPPLEMENTARY TABLE 3

CLUSTER 1C

CLUSTER ID

Sample # 17 IPI00010349.1 Alkyldihydroxyacetonephosphate synthase, peroxisomal

Sample # 66 IPI00292579.4 Stabilin-2

Sample # 99 IPI00470476.3 Uncharacterized protein C9orfl44A

Sample # 125: IPI00745280.1 Similar to Keratin, type II cytoskeletal 7 Sample # 130: IPI00783859.2 Isoform 2 of Vacuolar protein sorting-associated protein 13D

Sample # 181 : IPI00924608.1 vacuolar protein sorting-associated protein 13D isoform 1

SUPPLEMENTARY TABLE 4

CLUSTER 1A3

SUPPLEMENTARY TABLE 5

Number

of quant A6: A6: A6: A6: A6: A6:

Accession Description peptides 114/113 115/113 116/113 117/113 118/113 119/113

Elongation factor Tu

OS=Campylobacter hominis

(strain ATCC BAA-381 / LMG

19568 / NCTC 13146 /

CH001A) GN=tuf PE=3 SV=1

A7I3U7 - [EFTU CAMHC1 1 1.334 1.068 1.383 0.931 0.965 0.909

IPI00002557.1 Coatomer subunit gamma-2 3 2.422 3.431 5.719 1.270 1.857 0.973

IPI00002851.1 Cystatin-D 45 1.067 1.155 1.212 1.946 1.669 2.013

IPI00003269.1 Beta-actin-like protein 2 1 1.133 1.512 1.605 1.476 1.238 1.541

IPI00003935.6 Histone H2B type 2-E 5 1.265 1.484 1.633 0.388 0.634 0.551

Polymeric immunoglobulin

IPI00004573.2 receptor 344 1.355 1.004 1.141 1.339 1.164 2.048

IPI00004656.3 Beta-2-microglobulin 12 1.151 0.818 1.107 1.181 0.921 1.456

IPI00005721.1 Neutrophil defensin 1 31 1.339 1.818 3.735 1.321 1.880 0.325

IPI00007047.1 Protein S100-A8 105 2.089 3.485 5.821 3.001 3.414 0.761

Fatty acid-binding protein,

IPI00007797.3 epidermal 37 0.869 0.659 1.116 0.868 0.730 1.118

IPI00008405.5 Arylsulfatase F 1 2.459 1.617 2.073 1.893 1.433 1.685

Epithelial membrane protein

IPI00008895.1 2 2 1.432 1.014 1.025 0.465 0.654 0.343

IPI00009650.1 Lipocalin-1 88 0.821 0.659 0.774 0.770 0.849 1.003

Isoform 1 of Acyl-CoA-

IPI00010182.4 binding protein 2 0.541 0.683 1.343 0.535 0.586 1.083

IPI00010471.6 Plastin-2 60 1.927 2.427 3.986 1.449 1.981 0.749 IPI00010796.1 Protein disulfide-isomerase 22 1.158 1.242 1.913 1.246 1.360 1.128

Chloride intracellular channel

IPI00010896.3 protein 1 1 1.302 2.597 4.398 1.171 1.693 0.000

IPI00012024.1 Histatin-1 19 1.681 2.703 1.813 8.008 3.163 5.536

Coiled-coil domain-containing

IPI00012199.1 protein 86 5 3.494 1.199 0.471 2.583 1.608 9.492

Putative uncharacterized

IPI00012525.1 protein (Fragment) 3 0.923 1.037 0.621 1.198 0.931 2.992

IPI00012796.1 Glutamate decarboxylase 2 6 0.524 0.591 0.909 0.338 0.252 0.342

IPI00013382.1 Cystatin-SA 154 1.612 2.447 1.976 3.388 3.313 2.284

IPI00013885.1 Caspase-14 4 0.821 0.982 1.293 0.866 1.008 1.908

Isoform 1 of 14-3-3 protein

IPI00013890.2 sigma 2 0.749 0.478 0.614 0.806 0.626 1.215

IPI00013895.1 Protein S100-A11 3 0.964 0.923 2.966 0.659 0.985 1.115

Isoform 3 of Uncharacterized

IPI00016347.5 protein C2orf54 1 4.154 8.928 16.772 1.275 2.398 1.915

IPI00017526.1 Protein S100-P 8 1.552 2.065 4.222 1.358 1.880 0.603 cDNA FU25678 fis, clone

TST04067, highly similar to

PURINE NUCLEOSIDE

IPI00017672.4 PHOSPHORYLASE 5 0.918 1.218 5.022 1.120 1.446 0.815

IPI00019038.1 Lysozyme C 4 2.326 1.456 2.240 1.721 1.671 3.324

IPI00019449.1 Non-secretory ribonuclease 2 1.376 2.430 3.652 1.226 1.337 1.147

IPI00019502.3 Isoform 1 of Myosin-9 2 2.000 3.924 8.217 1.892 3.411 0.808

IPI00020008.1 NEDD8 3 1.428 1.588 2.203 1.005 1.461 1.352

IPI00020091.1 Alpha-l-acid glycoprotein 2 17 1.535 1.385 4.699 1.421 1.782 1.147

Peptidoglycan recognition

IPI00021085.1 protein 1 5 1.221 1.458 2.897 0.970 1.046 0.753

IPI00021263.3 14-3-3 protein zeta/delta 3 1.178 1.027 1.446 1.289 1.279 1.287

Keratin, type II cytoskeletal 2

IPI00021304.1 epidermal 5 0.982 1.009 1.276 1.151 3.128 1.063

IPI00021447.1 Alpha-amylase 2B 3 1.079 0.862 0.705 1.222 0.933 2.067

IPI00021828.1 Cystatin-B 81 0.828 0.544 0.876 0.676 0.686 1.099

IPI00021841.1 Apolipoprotein A-I 18 0.835 0.832 1.867 0.694 0.860 0.745

IPI00022429.3 Alpha-l-acid glycoprotein 1 53 1.424 1.537 4.423 1.523 1.798 0.917

IPI00022463.2 Serotransferrin 146 1.459 1.092 2.155 1.029 1.126 0.881

IPI00022488.1 Hemopexin 32 1.404 1.403 2.394 0.981 1.138 0.948

IPI00022974.1 Prolactin-inducible protein 246 1.227 1.209 1.292 1.748 1.622 1.103

IPI00022990.1 Statherin 7 1.429 2.406 2.568 3.207 2.496 2.384

Submaxillary gland

androgen-regulated protein

IPI00023011.2 3B 90 1.742 2.454 2.287 2.367 2.098 2.577

Basic salivary proline-rich

IPI00023038.2 protein 1 4 1.218 0.961 1.368 1.927 1.498 3.110

IPI00027462.1 Protein S100-A9 96 1.798 3.205 6.274 2.954 3.150 1.038

IPI00027463.1 Protein S100-A6 2 2.194 2.125 3.066 1.586 2.024 1.628

IPI00027509.5 Matrix metalloproteinase-9 10 1.467 1.875 4.619 1.046 1.606 0.603

IPI00027769.1 Neutrophil elastase 12 1.439 2.081 3.690 0.986 1.648 0.671

IPI00028064.1 Cathepsin G 2 1.820 1.721 2.885 1.107 2.606 0.827

IPI00028931.2 Desmoglein-2 5 0.928 1.331 0.424 0.680 0.401 1.298

UDP-GlcNAc:betaGal beta- 1,3-N- acetylglucosaminyltransferase

IPI00031983.4 3 1 1.175 1.644 1.973 1.315 1.081 1.234

IPI00032220.3 Angiotensinogen 3 1.522 0.794 2.030 0.934 1.162 1.027 IPI00032293.1 Cystatin-C 25 1.258 1.117 1.166 1.533 1.176 1.776

IPI00032294.1 Cystatin-S 234 1.385 1.513 1.441 2.037 1.440 1.319

IPI00037070.3 Uncharacterized protein 1 0.603 0.706 3.183 0.527 0.552 0.625

Zymogen granule protein 16

IPI00060800.5 homolog B 154 2.141 1.224 0.812 1.888 1.294 0.914

Isoform 2 of UPF0585 protein

IPI00065475.6 C16orfl3 1 1.307 1.489 2.017 1.064 0.979 1.041

Isoform 2 of WAP four- disulfide core domain protein

IPI00103636.1 2 11 1.213 0.761 1.013 1.286 1.328 2.436

IPI00141938.4 histone H2A.V isoform 2 7 1.184 1.149 1.390 0.377 0.633 0.822

IPI00152154.2 Mucin-7 11 1.390 1.341 1.362 1.481 1.205 0.846

IPI00166729.4 Zinc-alpha-2-glycoprotein 126 1.184 0.986 1.046 1.204 1.017 1.645

IPI00169244.1 106 kDa protein 1 1.285 1.692 1.105 1.831 1.341 2.026

Isoform 3 of Keratin, type I

IPI00171196.2 cytoskeletal 13 28 0.997 2.372 3.765 0.914 0.921 0.784

Isoform 4 of Interleukin-1

IPI00174541.1 receptor antagonist protein 27 0.951 0.847 0.969 0.874 0.848 1.522

IPI00178926.2 Immunoglobulin J chain 48 1.411 0.946 1.422 1.191 1.292 1.833

Thymosin beta-4-like protein

IPI00180240.2 3 4 1.890 2.250 5.361 1.801 2.320 1.482

IPI00182138.4 Isoform 2 of Granulins 8 1.159 1.156 2.207 1.104 1.212 0.833

Isoform VI of Versican core

IPI00215628.1 protein 4 0.753 0.233 0.118 0.868 0.167 2.209

IPI00216298.6 Thioredoxin 20 0.714 0.530 0.903 0.637 0.618 0.868

IPI00216691.5 Profilin-1 43 2.306 2.912 7.249 1.671 2.447 0.862

Isoform 2 of NADPH oxidase

IPI00216835.2 activator 1 2 4.163 3.228 1.127 3.132 3.034 4.653

IPI00217473.5 Hemoglobin subunit zeta 1 2.065 4.113 2.853 5.036 4.045 3.416

Isoform 4 of Uncharacterized

IPI00217846.3 protein C5orf25 6 1.208 1.328 2.126 1.044 0.906 1.302

Keratin, type I cytoskeletal

IPI00217963.3 16 1 1.136 1.173 1.859 1.552 1.383 0.770

Isoform 1 of L-lactate

IPI00217966.9 dehydrogenase A chain 7 1.420 1.287 3.600 1.170 1.608 1.021

IPI00218131.3 Protein S100-A12 7 2.018 2.382 5.247 1.969 3.303 0.870

IPI00218918.5 Annexin Al 6 0.901 0.866 1.135 0.842 1.134 1.151

Glyceraldehyde-3-phosphate

IPI00219018.7 dehydrogenase 7 1.890 2.015 3.068 2.405 3.303 1.254

IPI00219365.3 Moesin 5 2.446 3.238 5.521 1.827 2.468 1.272

IPI00219757.13 Glutathione S-transferase P 5 1.167 1.143 2.071 0.961 1.121 1.127

IPI00220327.4 Keratin, type II cytoskeletal 1 10 1.379 1.390 1.249 1.338 2.501 1.922

Isoform 3 of Apoptosis- associated speck-like protein

IPI00221362.3 containing a CARD 3 1.298 1.275 2.918 0.872 1.230 0.674

Isoform H14 of

IPI00236554.1 Myeloperoxidase 7 0.972 1.284 1.511 0.698 0.702 0.622

Isoform 3 of Contactin-

IPI00255103.8 associated protein-like 3B 1 0.804 0.796 1.113 0.715 0.650 0.736

Keratin, type I cytoskeletal

IPI00290077.3 15 3 0.713 1.001 1.373 0.894 1.092 0.636

Isoform 1 of Long palate,

lung and nasal epithelium

carcinoma-associated protein

IPI00291410.3 1 5 0.565 0.499 0.630 0.648 0.723 0.588

Proteasome subunit alpha

IPI00291922.2 type-5 2 1.205 1.447 3.311 1.219 1.520 0.848

Macrophage migration

IPI00293276.10 inhibitory factor 2 1.102 1.154 3.849 0.903 1.245 0.864 cDNA FU60163, highly

IPI00295105.3 similar to Carbonic anhydrase 89 1.200 0.995 0.740 1.345 0.973 1.944 6

Bactericidal/permeability-

IPI00296654.2 increasing protein-like 1 102 1.038 0.964 1.128 1.036 1.059 0.979

IPI00298497.3 Fibrinogen beta chain 3 1.271 1.495 2.748 1.090 1.251 0.768

Salivary acidic proline-rich

IPI00299078.1 phosphoprotein 1/2 105 1.717 1.175 0.948 1.780 0.958 2.336

Isoform 1 of Neutrophil

gelatinase-associated

IPI00299547.4 lipocalin 10 1.335 1.374 4.163 0.862 1.261 1.122

IPI00299729.4 Transcobalamin-1 11 1.254 1.092 1.409 1.080 0.911 1.048

Protein-glutamine gamma-

IPI00300376.5 glutamyltransferase E 4 1.381 1.362 1.519 0.934 1.308 1.472

IPI00300786.1 Alpha-amylase 1 1385 1.018 0.914 0.835 1.024 0.877 2.316

Vasodilator-stimulated

IPI00301058.5 phosphoprotein 6 1.831 2.325 3.191 1.358 1.822 1.087

Isoform 3 of Protein

IPI00301658.7 FAM194A 2 1.908 1.390 1.034 0.892 2.194 1.993

Short palate, lung and nasal

epithelium carcinoma-

IPI00304557.2 associated protein 2 117 0.967 0.839 0.582 1.462 1.133 1.411

IPI00304808.4 Isoform 1 of Kallikrein-1 33 1.143 1.071 1.088 1.193 0.996 2.770

IPI00305477.6 Cystatin-SN 328 1.029 1.165 1.402 1.480 1.224 1.340

IPI00373937.3 Suprabasin 3 1.089 1.447 1.976 1.499 1.271 1.150

IPI00374315.1 UPF0762 protein C6orf58 35 1.219 0.889 0.891 0.899 0.814 0.628 peroxiredoxin-5,

mitochondrial isoform c

IPI00375307.2 precursor 1 2.176 1.892 2.076 2.669 2.607 2.187

Isoform 2 of WD repeat-

IPI00377122.4 containinq protein KIAA1875 2 3.250 8.184 9.606 1.741 5.015 1.041

Pituitary tumor transforming

IPI00383627.1 qene protein 1 1.664 1.085 0.789 2.088 1.348 3.280

IPI00383981.3 AZU1 protein (Fraqment) 1 1.239 1.215 1.506 1.029 1.043 1.587

Isoform 2 of Guanine

nucleotide exchange factor

IPI00384251.1 for ab-3A 2 2.806 4.222 2.254 2.408 1.972 0.903

IPI00384382.1 AngRem52 2 5.427 4.310 0.488 5.921 5.682 13.414

Keratin, type I cytoskeletal

IPI00384444.6 14 9 0.828 1.020 1.545 1.135 1.213 0.629

IPI00384975.4 Uncharacterized protein 3 1.703 1.882 3.972 1.491 1.887 1.072

Ig kappa chain V-III region

IPI00385252.1 GOL 1 1.122 1.376 1.627 0.603 0.797 0.991

IPI00386132.1 Iq kappa chain V-IV reqion JI 3 1.135 1.470 2.104 1.164 1.192 1.304 cDNA FU 14473 fis, clone

MAMMA1001080, highly

similar to Homo sapiens

SNC73 protein (SNC73)

IPI00386879.1 mRNA 35 1.468 0.875 1.253 1.497 1.229 2.044

Isoform 2 of

Ribonucleoprotein PTB-

IPI00397768.5 binding 2 2 1.697 1.040 0.494 0.974 0.716 0.626

Putative uncharacterized

protein DKFZp686I04196

IPI00399007.7 (Fragment) 22 1.366 1.235 3.744 1.003 1.606 0.685 basic salivary proline-rich

protein 1 isoform 3

IPI00399260.2 preproprotein 4 0.817 0.602 0.858 1.338 0.896 2.761

IPI00410714.5 Hemoglobin subunit alpha 295 3.564 5.378 11.480 1.052 1.813 1.174

Isoform 2 of 14-3-3 protein

IPI00411765.3 sigma 1 0.669 0.409 0.557 0.667 0.485 1.131

Alpha-N-

IPI00414909.1 acetylgalactosaminidase 2 2.859 3.040 0.525 3.474 2.633 17.162

Alpha-2-macroglobulin-like

IPI00419215.6 protein 1 6 0.874 0.695 1.359 0.997 0.806 1.642 Peptidyl-prolyl cis-trans

IPI00419585.9 isomerase A 14 1.235 1.302 2.881 0.983 1.272 0.902

Putative uncharacterized

protein DKFZp686G21220

IPI00423460.3 (Fragment) 68 1.253 0.886 1.122 1.420 1.036 2.031

Putative uncharacterized

IPI00426051.3 protein DKFZp686C15213 6 1.301 1.325 3.380 1.042 1.585 0.771

IPI00431645.2 31 kDa protein 19 1.534 1.353 3.752 1.022 1.684 1.119

IPI00448925.6 44 kDa protein 39 1.816 1.994 4.028 1.449 1.637 1.038

Isoform 2 of Triosephosphate

IPI00451401.3 isomerase 11 0.939 0.943 1.929 0.911 0.914 0.938

IPI00453473.6 Histone H4 19 0.940 1.178 1.774 0.294 0.442 0.599

Isoform alpha-enolase of

IPI00465248.5 Alpha-enolase 77 1.577 1.636 3.750 1.376 1.676 1.053

IPI00465436.4 Catalase 3 0.849 0.892 4.163 0.689 0.719 0.588

Fructose-bisphosphate

IPI00465439.5 aldolase A 8 1.126 1.108 2.388 0.895 1.034 0.932

PR domain zinc finger protein

IPI00472974.2 2 isoform c 1 1.322 0.782 0.594 0.499 0.606 0.826

IPI00473011.3 Hemoglobin subunit delta 10 2.137 4.652 11.181 0.891 1.396 1.521

IPI00477265.2 archaemetzincin-2 isoform 2 2 1.045 1.803 1.409 1.232 1.202 1.036

IPI00478003.3 Alpha-2-macroglobulin 32 1.781 1.541 2.997 1.162 1.369 1.261 haptoglobin isoform 2

IPI00478493.3 preproprotein 22 1.618 1.346 3.690 1.046 1.698 1.126

Isoform M2 of Pyruvate

IPI00479186.7 kinase isozymes M1/M2 9 1.071 1.140 4.945 1.178 1.376 0.947

Full-length cDNA clone

CS0DD006YL02 of

Neuroblastoma of Homo

IPI00479708.6 sapiens 25 1.453 1.136 1.956 1.318 1.367 1.145

IPI00549413.2 Uncharacterized protein 7 0.823 0.790 0.992 0.864 1.115 1.100

Putative uncharacterized

IPI00550731.2 protein 162 1.388 1.056 1.827 1.336 1.377 1.778

Basic salivary proline-rich

IPI00552432.3 protein 2 13 1.468 1.308 2.302 2.485 2.204 4.018

IPI00552768.1 Uncharacterized protein 44 0.725 0.542 0.941 0.661 0.638 0.878

Isoform 1 of Alpha- 1-

IPI00553177.1 antitrypsin 1 2.622 1.595 2.982 3.246 2.000 9.201

IPI00554696.2 Uncharacterized protein 141 1.153 0.946 0.733 1.287 0.901 1.893 vitamin D-binding protein

IPI00555812.5 isoform 1 precursor 2 1.540 0.864 1.313 0.642 0.864 0.776 rab GDP dissociation inhibitor

IPI00640006.1 beta isoform 2 2 1.094 1.139 2.142 0.875 0.960 1.079

IPI00640335.1 Protein 2 1.020 1.000 1.104 0.715 0.763 1.381

IPI00641047.5 Uncharacterized protein 2 1.030 1.256 2.841 0.875 1.109 0.724

IPI00641737.2 Haptoglobin 9 1.558 1.456 3.624 1.039 1.631 1.146

IPI00642247.1 Uncharacterized protein 1 1.345 1.142 1.335 1.592 1.976 3.355

Adenylyl cyclase-associated

IPI00642414.1 protein 8 1.525 1.749 4.087 1.080 1.601 0.632

IPI00643231.1 Uncharacterized protein 7 0.799 0.724 0.856 0.806 0.949 1.048

Putative uncharacterized

IPI00645363.2 protein DKFZp686P15220 13 1.731 1.816 3.774 1.500 1.768 1.103

IPI00646265.2 58 kDa protein 1 0.446 0.419 0.711 0.756 0.440 2.129

IPI00654755.3 Hemoglobin subunit beta 206 5.138 7.744 19.343 0.958 2.207 1.176

IPI00658053.1 Uncharacterized protein 3 1.025 0.706 1.138 1.215 1.057 1.976

Isoform 5 of Deleted in

malignant brain tumors 1

IPI00658218.1 protein 33 1.134 0.848 1.072 1.484 1.104 2.882

IPI00719452.1 IGL@ protein 3 1.619 1.410 2.306 1.524 1.564 1.899 Immunolgoobulin heavy

IPI00735451.4 chain 3 1.458 1.342 1.931 1.375 1.529 1.614

POTE ankyrin domain family

IPI00740545.1 member I 1 1.544 1.863 5.939 1.646 1.829 1.201

Bardet-Biedl syndrome 10

IPI00742775.1 protein 3 1.797 1.054 0.649 1.610 1.479 3.659

IPI00745872.2 Isoform 1 of Serum albumin 1199 1.253 1.073 1.906 0.893 1.020 0.693

IPI00748022.2 Actin-like protein (Fragment) 3 0.658 0.450 15.108 0.904 1.215 0.342

IPI00748184.4 Uncharacterized protein 1 1.190 0.580 0.806 0.721 0.783 1.577

Isoform

Cytoplasmic+peroxisomal of

Peroxiredoxin-5,

IPI00759663.1 mitochondrial 3 2.019 1.866 2.939 2.017 2.349 1.436

Isoform Short of 14-3-3

IPI00759832.1 protein beta/alpha 4 1.613 1.872 2.478 1.732 2.004 1.079

Immunglobulin heavy chain

IPI00782983.3 variable region 1 1.274 0.966 1.380 0.984 1.124 1.435

Isoform 2 of

Lysophospholipid

IPI00783192.1 acyltransferase LPCAT4 2 1.835 2.502 4.115 0.957 1.295 0.426

Immunglobulin heavy chain

IPI00783287.1 variable region (Fragment) 6 1.370 1.178 1.908 1.273 1.351 1.855

IPI00783987.2 Complement C3 (Fragment) 31 1.310 1.335 1.824 1.083 1.300 0.939

Ig kappa chain V-III region

IPI00784430.5 VG (Fraqment) 3 1.432 1.606 2.025 1.687 1.269 1.802 cDNA FU41981 fis, clone

SMINT2011888, highly

similar to Protein Tro alphal

IPI00784830.1 H, myeloma 20 1.313 0.969 1.755 1.137 1.364 1.729

Putative uncharacterized

IPI00784842.1 protein DKFZp686G11190 5 1.677 1.158 2.049 1.110 1.290 1.805

Putative uncharacterized

IPI00784950.1 protein DKFZp686L19235 34 1.385 1.031 1.794 1.307 1.680 1.966

IPI00784985.1 IGK@ protein 4 1.659 1.619 2.137 1.341 1.216 1.390 cDNA, FU79516, highly

similar to 14-3-3 protein

IPI00789337.4 zeta/delta 11 1.014 0.979 1.408 1.077 1.151 1.104

IPI00793319.1 Uncharacterized protein 15 1.056 0.817 1.892 0.803 0.955 1.135

Isoform 3 of Leukotriene A-4

IPI00793812.3 hydrolase 2 2.073 3.756 2.090 2.556 3.836 1.378

Glyceraldehyde-3-phosphate

IPI00795257.3 dehydrogenase 20 1.906 2.414 4.423 2.475 3.309 1.095 cDNA FU54081, highly

similar to Keratin, type II

IPI00796776.2 cytoskeletal 5 8 0.956 1.653 2.132 1.055 1.262 0.895

IPI00796823.1 Uncharacterized protein 3 1.332 1.018 1.531 1.274 1.060 1.634

Isoform 1 of Triosephosphate

IPI00797270.4 isomerase 12 0.954 0.958 1.977 0.942 0.936 0.954

Putative uncharacterized

IPI00807428.1 protein 11 1.663 1.256 2.096 1.521 1.622 2.108

IPI00816687.1 FGB protein (Fragment) 2 1.256 1.455 2.629 1.158 1.171 0.861

IPI00829697.1 13 kDa protein 2 1.291 1.053 1.273 1.258 1.076 1.344

IPI00844600.1 9 kDa protein 34 1.819 1.908 4.485 1.795 3.045 0.855

IPI00847989.3 Pyruvate kinase 7 1.034 1.075 5.892 1.073 1.314 0.992

IPI00853525.1 Uncharacterized protein 32 0.974 0.952 2.041 0.787 0.978 0.740

Immunglobulin heavy chain

IPI00854743.1 variable region 3 1.793 1.577 2.106 1.672 1.477 1.621

Isoform 3 of Alpha-1-

IPI00869004.1 antitrypsin 3 2.465 1.626 3.011 3.218 2.013 8.595

Isoform 7 of Deleted in

malignant brain tumors 1

IPI00872278.1 protein 73 1.096 0.859 1.032 1.459 1.193 2.904

IPI00876888.1 cDNA FU78387 24 1.938 2.052 4.124 1.445 1.739 1.089 cDNA FU59430, highly

similar to Protein disulfide-

IPI00878551.2 isomerase 6 1.132 1.179 1.789 1.162 1.248 1.130

IPI00879084.2 Uncharacterized protein 2 0.869 0.734 1.657 0.639 0.844 0.847

IPI00879437.1 Protein 6 1.140 1.244 2.007 1.342 1.500 1.118

1P100879438.1 Uncharacterized protein 7 1.599 1.349 2.028 1.286 1.446 1.754

IPI00883885.3 PRB3 protein 2 1.958 4.184 10.696 4.152 5.160 3.582 basic salivary proline-rich

IPI00884451.2 protein 4 precursor 4 1.487 1.901 1.782 3.621 2.533 6.502

IPI00892657.1 Protein 3 1.054 0.900 0.852 0.988 0.843 1.529

IPI00893981.1 Uncharacterized protein 15 1.884 3.572 9.128 1.543 2.690 0.933 cDNA FU33251 fis, clone

ASTRO2005242, highly

similar to Rho guanine

IPI00902602.1 nucleotide exchange factor 5 2 0.931 0.313 0.160 1.079 0.232 2.915

IPI00902755.1 FGA protein (Fragment) 13 1.306 1.305 2.165 0.863 1.298 0.851 cDNA FU36533 fis, clone

TRACH2004428, highly

similar to Lactotransferrin

IPI00903112.1 (Fragment) 35 1.075 1.133 1.275 0.905 0.900 1.574 cDNA FU44586 fis, clone

ASTRO2015162, highly

similar to Choline

IPI00903245.1 transporter-like protein 2 3 1.185 1.237 3.194 0.543 1.024 0.603

IPI00908402.1 cDNA FU51275 21 0.875 0.775 1.042 0.763 0.863 1.697 cDNA FU51535, highly

similar to

Phosphatidylethanolamine-

IPI00908746.1 binding protein 1 2 1.215 1.080 1.494 0.992 0.979 1.399

Glucose-6-phosphate

IPI00908881.3 isomerase 21 1.390 1.889 4.093 1.235 1.632 0.778

IPI00909239.1 Isoform 2 of Alpha-actinin-1 2 0.959 1.185 3.107 0.847 0.983 0.761 cDNA FU52843, highly

IPI00909530.1 similar to Histone H3.3 2 0.863 1.184 1.638 0.284 0.466 0.389 cDNA FU55140, highly

similar to SPARC-like protein

IPI00909737.1 1 3 1.576 1.040 1.195 1.687 1.148 1.266

Peptidyl-prolyl cis-trans

IPI00910407.1 isomerase 4 1.257 1.380 2.526 1.134 1.306 1.122 cDNA FU60194, highly

similar to WW domain-

IPI00910819.2 binding protein 11 2 0.419 0.169 0.340 0.174 0.162 0.819 cDNA FU54408, highly

similar to Heat shock 70 kDa

IPI00911039.1 protein 1 24 1.286 1.230 2.977 0.919 1.177 1.015

Isoform 3 of WD repeat- and

FYVE domain-containing

IPI00914858.1 protein 4 1 0.710 0.782 2.267 0.797 0.708 0.764

IPI00915959.2 Uncharacterized protein 1 1.027 0.847 1.058 0.822 1.078 1.278

IPI00916434.1 Anti-(ED-B) scFV (Fragment) 22 1.451 1.070 1.836 1.129 1.270 1.745

IPI00916818.1 Phosphoglycerate kinase 3 1.905 2.138 4.346 1.691 2.285 1.158

Mucin 5AC, oligomeric

IPI00918002.1 mucus/gel-forming 148 0.803 0.649 0.774 0.894 0.946 0.792

IPI00921945.1 cDNA FU57374 3 2.551 1.937 1.257 2.959 2.453 5.295 cDNA FU56822, highly

similar to Alpha-2-HS-

IPI00922262.1 glycoprotein 3 1.453 1.413 2.569 1.226 1.486 0.917

IPI00924751.1 Protein 2 6.044 5.591 1.745 9.960 7.333 6.159

IPI00927887.1 Histone H2A 6 1.166 1.117 1.335 0.340 0.595 0.859

IPI00929669.1 Similar to Keratin 16 1 0.846 0.939 1.745 1.197 1.161 0.460

Putative uncharacterized

IPI00930072.1 protein DKFZp686E23209 9 1.493 1.318 4.185 1.146 1.974 0.697 cDNA FU57283, highly

IPI00930226.1 similar to Actin, cytoplasmic 2 144 1.614 2.170 5.681 1.448 1.915 0.897

Putative uncharacterized

IPI00930442.1 protein DKFZp686M24218 10 1.357 1.336 3.471 0.849 1.304 0.710 cDNA FU59081, highly

IPI00936444.2 similar to Mucin-5B 375 0.767 0.618 0.731 0.872 0.943 0.744

IPI00939521.1 10 kDa protein 11 1.417 1.299 1.919 1.323 1.499 1.796 cDNA FU36348 fis, clone

THYMU2007025, highly

IPI00940673.2 similar to TRANSKETOLASE 27 1.263 1.421 2.558 1.151 1.346 1.090 cysteine-rich secretory

IPI00942117.2 protein 3 isoform 1 precursor 3 1.602 1.679 1.851 2.268 1.658 1.236

IPI00942257.3 Uncharacterized protein 8 0.831 1.298 2.436 1.171 1.063 0.668

IPI00942979.1 Transketolase 56 1.799 2.383 4.969 1.448 2.125 0.778 glycogen phosphorylase, liver

IPI00943894.1 form isoform 2 3 1.700 2.112 8.124 2.052 2.690 0.942

IPI00945694.1 Uncharacterized protein 4 2.032 1.446 1.134 0.943 2.198 2.126

Isoform 1 of Actin-related

IPI00946655.1 protein 3C 6 1.390 1.496 5.005 1.472 2.156 0.949

IPI00947240.1 24 kDa protein 3 0.683 0.962 0.883 0.531 0.547 0.793

IPI00964000.1 Uncharacterized protein 110 1.452 0.954 1.354 1.277 1.294 1.901

IPI00965100.1 Uncharacterized protein 20 1.738 2.050 1.646 3.357 2.292 1.017 fibrinogen beta chain isoform

IPI00965713.3 2 preproprotein 2 1.515 1.521 3.117 1.023 1.453 0.671

IPI00966755.1 Uncharacterized protein 2 1.956 1.775 1.376 1.277 1.506 0.649

IPI00967145.1 Uncharacterized protein 5 0.920 0.286 0.265 1.014 0.277 2.146

IPI00968182.1 Uncharacterized protein 5 0.702 0.698 1.209 0.588 0.762 0.850

Salivary proline-rich protein 2

IPI00969578.1 (Fragment) 3 0.384 0.298 0.467 0.428 0.296 2.190

Lambda light chain of human

immunoglobulin surface

antigen-related protein

IPI00972963.1 (Fraqment) 28 1.623 1.250 2.236 1.587 1.700 2.028

IPI00973998.1 Uncharacterized protein 4 0.855 1.217 1.587 0.311 0.383 0.315

IPI00974112.1 22 kDa protein 3 1.518 1.547 1.709 2.228 1.636 1.129

Isoform SV of 14-3-3 protein

IPI00974544.1 epsilon 4 1.198 1.054 1.576 0.983 1.235 0.878

IPI00975690.1 Vimentin variant 3 5 1.490 2.426 3.841 1.423 1.455 0.479

IPI00975820.1 Uncharacterized protein 3 1.341 0.908 0.965 1.223 0.866 0.639

IPI00976039.1 Uncharacterized protein 7 1.316 1.174 1.162 1.623 1.390 1.853

Similar to Rheumatoid factor

IPI00976187.1 G9 heavy chain 5 1.343 0.913 1.190 0.948 1.033 1.320

Similar to Myosin-reactive

immunoglobulin heavy chain

IPI00976928.1 variable region 4 1.848 1.462 1.590 1.501 1.147 1.387

Isoform 1 of Immunoglobulin

IPI00977041.1 lambda-like polypeptide 5 5 1.510 1.304 1.783 1.427 1.426 1.854

Similar to VH4 heavy chain

IPI00977297.1 variable region precursor 6 1.179 0.809 1.325 0.893 0.986 1.307

Similar to Ig kappa chain V-

IPI00977405.1 III region VG precursor 5 1.476 1.645 2.074 1.634 1.205 1.807

IPI00977704.1 Uncharacterized protein 1 1.794 2.829 5.564 0.908 1.354 1.299

Similar to Hepatitis B virus

IPI00977788.1 receptor binding protein 6 1.015 0.952 1.480 1.052 0.982 1.314

Conserved hypothetical

IPI00978315.1 protein 2 0.987 0.913 1.992 0.499 0.712 0.576

Conserved hypothetical

IPI00979837.1 protein 3 1.470 1.866 3.592 1.451 1.808 0.801

IPI00980674.1 Uncharacterized protein 11 2.724 4.406 9.159 0.884 1.734 1.214

IPI00980807.1 5 kDa protein 4 1.304 3.346 1.734 6.962 3.179 3.962 Similar to Cold agglutinin FS-

IPI00981659.1 1 H-chain 11 1.775 1.889 4.199 1.191 1.455 0.898

IPI00982472.1 Transaldolase 19 1.276 1.416 3.039 1.011 1.238 0.745

IPI00982588.1 Protein 2 1.404 1.095 1.125 1.587 1.258 2.002

Similar to Ig kappa chain V-

IPI00984004.1 III region WOL 1 1.345 1.206 1.794 1.449 1.176 1.690

IPI00984370.1 Uncharacterized protein 1 1.681 2.137 2.999 2.333 2.090 2.109

Similar to Immunglobulin

IPI00984640.1 heavy chain variable region 15 2.300 2.083 2.111 1.618 1.775 1.900

IPI00984835.1 16 kDa protein 2 4.667 1.241 0.485 3.896 1.002 12.522

IPI00985334.2 titin isoform N2-B 3 1.057 1.108 2.004 0.654 1.002 0.621

IPI00985505.1 Uncharacterized protein 3 0.795 1.052 0.653 1.359 0.731 2.521

IPI01009389.1 DNA methyltransferase 3 4.745 3.371 0.401 6.191 4.063 12.096

IPI01009456.2 34 kDa protein 3 1.200 1.522 3.292 1.059 1.495 0.874

Adenylyl cyclase-associated

IPI01009563.1 protein 3 1.488 1.598 4.019 1.105 1.534 0.762

IPI01010684.1 Uncharacterized protein 7 0.855 0.667 1.161 1.015 0.862 2.082

IPI01011090.1 Uncharacterized protein 2 1.759 2.275 2.702 1.622 1.984 1.655

IPI01011344.1 Uncharacterized protein 35 1.710 2.297 4.424 1.556 2.008 0.946

IPI01011676.1 Uncharacterized protein 4 1.390 1.652 2.651 0.848 1.032 1.002

IPI01011820.1 Uncharacterized protein 4 1.286 1.318 2.605 1.057 1.352 0.779

6-phosphogluconate

dehydrogenase,

IPI01011970.1 decarboxylating 12 1.270 1.514 2.734 1.340 1.478 0.906

IPI01012346.1 Uncharacterized protein 2 1.617 2.046 5.188 1.135 1.631 0.652

IPI01012426.1 Uncharacterized protein 2 1.070 1.154 2.030 0.831 0.852 0.952

6-phosphogluconate

dehydrogenase,

IPI01012504.1 decarboxylating 38 1.359 1.542 3.026 1.406 1.599 0.918

IPI01012528.1 Uncharacterized protein 15 1.690 1.785 3.294 1.624 1.882 1.142

1P101013019.1 Airway lactoperoxidase 24 0.882 0.733 1.101 1.167 0.906 2.216

IPI01013112.1 Uncharacterized protein 2 1.502 1.616 3.136 1.163 1.581 0.786

IPI01013441.1 Uncharacterized protein 37 1.478 1.614 3.728 1.113 1.452 0.624

IPI01013537.1 Uncharacterized protein 8 1.128 0.999 1.396 1.072 0.980 1.148

IPI01013543.1 Triosephosphate isomerase 3 0.553 0.639 1.933 0.614 0.563 0.726 cDNA FU53963, highly

similar to Leukocyte elastase

IPI01014238.1 inhibitor 3 1.093 0.902 0.940 1.238 1.013 1.197

IPI01014975.1 Uncharacterized protein 4 1.298 1.759 6.183 1.213 1.747 0.620

IPI01015050.2 Uncharacterized protein 10 1.075 1.221 3.161 0.882 1.159 0.708

IPI01015184.1 Uncharacterized protein 2 1.649 1.436 1.903 1.081 1.226 1.151

IPI01015504.1 Uncharacterized protein 5 1.726 1.551 2.266 1.769 1.763 2.780

IPI01015565.1 Uncharacterized protein 3 2.337 2.119 2.126 1.706 1.583 1.924 cDNA FU55361, highly

similar to Nucleolar protein

IPI01015921.1 11 5 3.253 6.211 2.964 1.562 1.872 2.294

IPI01018060.1 Ig lambda-3 chain C regions 23 1.272 0.992 1.609 1.476 1.335 1.720

IPI01019128.1 Uncharacterized protein 1 1.461 1.790 1.194 0.640 0.973 1.539

IPI01021118.1 Uncharacterized protein 1 0.671 0.503 0.728 0.286 0.369 1.274 cDNA FU55805, highly

similar to Keratin, type II

IPI01022175.1 cytoskeletal 4 13 0.751 3.532 8.674 0.944 0.728 0.836

IPI01022408.1 Uncharacterized protein 3 1.609 1.588 2.160 1.128 1.363 1.526 IPI01022662.1 Uncharacterized protein 3 1.561 1.720 1.533 1.291 1.122 1.085

IPI01023021.1 Uncharacterized protein 2 2.702 1.781 2.674 1.532 1.735 1.014

IPI01024806.1 Alpha-actinin 1 5 1.098 1.431 3.435 1.031 1.276 0.762

IPI01026033.1 9 kDa protein 2 0.604 0.402 0.671 0.552 0.550 1.382

IPI01026288.1 Uncharacterized protein 14 1.097 1.071 1.045 1.123 1.014 2.762

50S ribosomal protein L22

OS=Treponema pallidum

(strain Nichols) GN=rplV

083224 PE=3 SV= 1 - [RL22_TREPA] 2 2.132 3.140 3.922 1.528 2.328 1.160

Uncharacterized protein

TP_0451 OS=Treponema

pallidum (strain Nichols)

GN=TP_0451 PE=4 SV=1 -

083465 [Y451_TREPA] 2 4.618 3.313 1.304 3.726 3.516 5.718

Uncharacterized protein

TP_0795 OS=Treponema

pallidum (strain Nichols)

GN=TP_0795 PE=4 SV=1 -

083773 [Y795_TREPA] 2 4.450 9.222 10.821 1.969 4.533 0.810

Phosphocarrier protein HPr

OS=Streptococcus salivarius

GN=ptsH PE=1 SV=2 -

P24366 [PTHP STRSL1 3 0.735 0.259 0.797 0.316 0.262 1.029

Zinc transport system

membrane protein troD

OS=Treponema pallidum

(strain Nichols) GN=troD

P96119 PE=3 SV= 1 - [TROD_TREPA] 3 1.209 1.223 1.320 1.302 2.272 1.126

3-isopropylmalate

dehydratase large subunit

(Fragment)

OS=Streptococcus gordonii

GN=leuC PE=3 SV=1 -

Q9AIM3 [LEUC STRGN1 2 2.397 1.049 0.615 1.752 0.661 5.701

SUPPLEMENTARY TABLE 6

CLUSTER 2

Protein # 165: IPI00748022.2 Actin-like protein (Fragment) |

SUPPLEMENTARY TABLE 7

CLUSTER IB

Protein # 19: IPI00012199.1 Coiled-coil domain-containing protein 86

Protein # 58: IPI00060800.5 Zymogen granule protein 16 homolog B

Protein # 73: IPI00216835.2 Isoform 2 of NADPH oxidase activator 1

Protein # 94: IPI00299078.1 Salivary acidic proline-rich phosphoprotein 1/2

Protein # 108: IPI00383627.1 Pituitary tumor transforming gene protein

Protein # 110: IPI00384251.1 Isoform 2 of Guanine nucleotide exchange factor for Rab-3A

Protein # 111 : IPI00384382.1 AngRem52

Protein # 122: IPI00414909.1 Alpha-N-acetylgalactosaminidase

Protein # 163: IPI00742775.1 Bardet-Biedl syndrome 10 protein

Protein # 221 : IPI00921945.1 cDNA FU57374

Protein # 270: IPI00984835.1 16 kDa protein

Protein # 273: IPI00985334.2 titin isoform N2-B Protein # 297: IPI01015921.1 cDNA FU55361, highly similar to Nucleolar protein 11

Uncharacterized protein TP_0451 OS=Treponema pallidum (strain Nichols)

Protein # 309: 083465 GN=TP_0451 PE=4 SV=1 - [Y451_TREPA]

CLUSTER ID

Protein # 212: IPI00909737.1 cDNA FU55140, highly similar to SPARC-like protein 1

SUPPLEMENTARY TABLE 8

CLUSTER 1A4

CLUSTER 1A5

SUPPLEMENTAL TABLE 11

Histone H2B type 2-E IPI00003935.6 HIST2H2BE Histone H2B type 2-E

Neutrophil defensin 1 IPI00005721.1 DEFA1 Neutrophil defensin 1

Protein S100-A8 IPI00007047.1 S100A8 Protein S100-A8

Arylsulfatase F IPI00008405.5 ARSF Arylsulfatase F

Epithelial membrane protein

Epithelial membrane protein 2 IPI00008895.1 EMP2 2

Plastin-2 IPI00010471.6 LCP1 Plastin-2

Isoform 1 of 14-3-3 protein

Isoform 1 of 14-3-3 protein sigma IPI00013890.2 SFN sigma

Protein S100-A11 IPI00013895.1 S100A11 Protein S100-A11

Protein S100-P IPI00017526.1 S100P Protein S100-P

Lysozyme C IPI00019038.1 LYZ Lysozyme C

Isoform 1 of Myosin-9 IPI00019502.3 MYH9 Isoform 1 of Myosin-9

Alpha-l-acid glycoprotein 2 IPI00020091.1 ORM2 Alpha-l-acid glycoprotein 2

14-3-3 protein zeta/delta IPI00021263.3 YWHAZ 14-3-3 protein zeta/delta

Cystatin-B IPI00021828.1 CSTB Cystatin-B

Apolipoprotein A-I IPI00021841.1 APOA1 Apolipoprotein A-I

Alpha-l-acid glycoprotein 1 IPI00022429.3 ORM1 Alpha-l-acid glycoprotein 1

Serotransferrin IPI00022463.2 TF Serotransferrin

Hemopexin IPI00022488.1 HPX Hemopexin

Prolactin-inducible protein IPI00022974.1 PIP Prolactin-inducible protein

Protein S100-A9 IPI00027462.1 S100A9 Protein S100-A9

Protein S100-A6 IPI00027463.1 S100A6 Protein S100-A6

Matrix metalloproteinase-9 IPI00027509.5 MMP9 Matrix metalloproteinase-9

Neutrophil elastase IPI00027769.1 ELANE Neutrophil elastase

Cathepsin G IPI00028064.1 CTSG Cathepsin G

Cystatin-S IPI00032294.1 CST4 Cystatin-S

Uncharacterized protein IPI00037070.3 HSPA8 Uncharacterized protein

Isoform 4 of Interleukin-1 receptor Isoform 4 of Interleukin-1 antagonist protein IPI00174541.1 IL1RN receptor antagonist protein

Thymosin beta-4-like protein

Thymosin beta-4-like protein 3 IPI00180240.2 TMSL3 3

Profilin-1 IPI00216691.5 PFN1 Profilin-1

Keratin, type I cytoskeletal

Keratin, type I cytoskeletal 16 IPI00217963.3 KRT16 16

Protein S100-A12 IPI00218131.3 S100A12 Protein S100-A12

Annexin Al IPI00218918.5 ANXA1 Annexin Al

Glutathione S-transferase P IPI00219757.13 GSTP1 Glutathione S-transferase P

Keratin, type II cytoskeletal 1 IPI00220327.4 KRT1 Keratin, type II cytoskeletal 1

Isoform H14 of

Isoform H14 of Myeloperoxidase IPI00236554.1 MPO Myeloperoxidase

Keratin, type I cytoskeletal

Keratin, type I cytoskeletal 15 IPI00290077.3 KRT15 15

Fibrinogen beta chain IPI00298497.3 FGB Fibrinogen beta chain

Salivary acidic proline-rich Salivary acidic proline-rich phosphoprotein 1/2 IPI00299078.1 PRH1 phosphoprotein 1/2

Isoform 1 of Neutrophil

Isoform 1 of Neutrophil gelatinase- gelatinase-associated associated lipocalin IPI00299547.4 LCN2 lipocalin

Cystatin-SN IPI00305477.6 CST1 Cystatin-SN

Keratin, type I cytoskeletal

Keratin, type I cytoskeletal 14 IPI00384444.6 KRT14 14

Putative uncharacterized protein IPI00399007.7 IGHG2 Putative uncharacterized DKFZp686I04196 (Fragment) protein DKFZp686I04196

(Fragment)

Hemoglobin subunit alpha IPI00410714.5 HBA1 Hemoglobin subunit alpha

Peptidyl-prolyl cis-trans

Peptidyl-prolyl cis-trans isomerase A IPI00419585.9 PPIA isomerase A

Putative uncharacterized

Putative uncharacterized protein protein DKFZp686G21220 DKFZp686G21220 (Fragment) IPI00423460.3 IGHA1 (Fragment)

31 kDa protein IPI00431645.2 HPR 31 kDa protein

44 kDa protein IPI00448925.6 IGHG1 44 kDa protein

Histone H4 IPI00453473.6 HIST4H4 Histone H4

Isoform alpha-enolase of Alpha- Isoform alpha-enolase of enolase IPI00465248.5 ENOl Alpha-enolase

Fructose-bisphosphate

Fructose-bisphosphate aldolase A IPI00465439.5 ALDOA aldolase A

haptoglobin isoform 2 haptoglobin isoform 2 preproprotein IPI00478493.3 HPR preproprotein

Isoform M2 of Pyruvate kinase Isoform M2 of Pyruvate isozymes M1/M2 IPI00479186.7 PKM2 kinase isozymes M1/M2

Uncharacterized protein IPI00552768.1 TXN Uncharacterized protein

Haptoglobin IPI00641737.2 HP Haptoglobin

Hemoglobin subunit beta IPI00654755.3 HBB Hemoglobin subunit beta

Isoform 1 of Serum albumin IPI00745872.2 ALB Isoform 1 of Serum albumin

Actin-like protein (Fragment) IPI00748022.2 LOC727848 Actin-like protein (Fragment)

Isoform

Cytoplasmic+peroxisomal of

Isoform Cytoplasmic+peroxisomal of Peroxiredoxin-5,

Peroxiredoxin-5, mitochondrial IPI00759663.1 PRDX5 mitochondrial

Complement C3 (Fragment) IPI00783987.2 C3 Complement C3 (Fragment)

Putative uncharacterized protein Putative uncharacterized DKFZp686L19235 IPI00784950.1 IGHA2 protein DKFZp686L19235

IGK@ protein IPI00784985.1 IGK@ IGK@ protein

Isoform 1 of Triosephosphate Isoform 1 of

isomerase IPI00797270.4 TPI1P1 Triosephosphate isomerase

FGB protein (Fragment) IPI00816687.1 FGB FGB protein (Fragment)

Uncharacterized protein IPI00853525.1 APOA1 Uncharacterized protein

Protein IPI00879437.1 P4HB Protein

Uncharacterized protein IPI00893981.1 ACTB Uncharacterized protein

FGA protein (Fragment) IPI00902755.1 FGA FGA protein (Fragment) cDNA FU36533 fis, clone cDNA FU36533 fis, clone TRACH2004428, highly TRACH2004428, highly similar to similar to Lactotransferrin Lactotransferrin (Fragment) IPI00903112.1 LTF (Fragment)

cDNA FU51275 IPI00908402.1 CRNN cDNA FU51275

Glucose-6-phosphate

Glucose-6-phosphate isomerase IPI00908881.3 GPI isomerase

cDNA FU52843, highly similar to cDNA FLJ52843, highly Histone H3.3 IPI00909530.1 LOC644914 similar to Histone H3.3

Peptidyl-prolyl cis-trans

Peptidyl-prolyl cis-trans isomerase IPI00910407.1 PPIA isomerase

cDNA FLJ54408, highly cDNA FU54408, highly similar to Heat similar to Heat shock 70 kDa shock 70 kDa protein 1 IPI00911039.1 HSPA1A protein 1

Histone H2A IPI00927887.1 H2AFV Histone H2A

Putative uncharacterized protein Putative uncharacterized DKFZp686M24218 IPI00930442.1 IGHG4 protein DKFZp686M24218

10 kDa protein IPI00939521.1 10 kDa protein cDNA FU36348 fis, clone cDNA FU36348 fis, clone THYMU2007025, highly similar to THYMU2007025, highly TRANSKETOLASE IPI00940673.2 TKT similar to TRANSKETOLASE Isoform 1 of Actin-related

Isoform 1 of Actin-related protein 3C IPI00946655.1 ACTR3C protein 3C

fibrinogen beta chain isoform 2 fibrinogen beta chain isoform preproprotein IPI00965713.3 FGB 2 preproprotein

Lambda light chain of human

Lambda light chain of human immunoglobulin surface immunoglobulin surface antigen- antigen-related protein related protein (Fragment) IPI00972963.1 IgLC-rG (Fragment)

Vimentin variant 3 IPI00975690.1 VIM Vimentin variant 3

Uncharacterized protein IPI00980674.1 CA1 Uncharacterized protein

Similar to Cold agglutinin FS-

Similar to Cold agglutinin FS-1 H-chain IPI00981659.1 IGH@ 1 H-chain

Transaldolase IPI00982472.1 TALDOl Transaldolase titin isoform N2-B IPI00985334.2 TTN titin isoform N2-B

Uncharacterized protein IPI01011344.1 ACTG1 Uncharacterized protein

6-phosphogluconate

6-phosphogluconate dehydrogenase, dehydrogenase, decarboxylating IPI01011970.1 PGD decarboxylating

Uncharacterized protein IPI01013112.1 ARHGDIB Uncharacterized protein

Uncharacterized protein IPI01013441.1 PRTN3 Uncharacterized protein

Triosephosphate isomerase IPI01013543.1 TPI1 Triosephosphate isomerase

Uncharacterized protein IPI01014975.1 TLN1 Uncharacterized protein

Uncharacterized protein IPI01015050.2 GSN Uncharacterized protein

Ig lambda-3 chain C regions IPI01018060.1 IGLC3 Ig lambda-3 chain C regions cDNA FLJ55805, highly cDNA FU55805, highly similar to similar to Keratin, type II Keratin, type II cytoskeletal 4 IPI01022175.1 KRT4 cytoskeletal 4

SUPPLEMENTAL TABLE 12

GCF Biological process Count (genes) P-value

cytoskeleton organization 29 1.90E-12 glucose catabolic process 12 1.60E-10 actin cytoskeleton organization 19 7.50E-10 hexose catabolic process 12 1.20E-09 monosaccharide catabolic process 12 1.60E-09 actin filament-based process 19 2.10E-09 alcohol catabolic process 12 6.70E-09 glycolysis 10 7.20E-09 organelle organization 44 1.10E-08 cellular carbohydrate catabolic process 12 1.10E-08 defense response 28 2.30E-08 ectoderm development 16 4.40E-08 response to stimulus 79 6.40E-08 cellular component organization 63 7.00E-08 carbohydrate catabolic process 12 1.60E-07 cellular component assembly 31 1.10E-06 response to stress 46 1.20E-06 tissue development 26 1.40E-06 response to external stimulus 31 1.90E-06 Saliva Biological process Count (genes) P-value defense response 32 1.60E-10 glucose catabolic process 11 4.40E-09 response to stimulus 83 1.50E-08 cellular carbohydrate catabolic process 12 1.70E-08 carbohydrate catabolic process 13 2.40E-08 hexose catabolic process 11 2.50E-08 monosaccharide catabolic process 11 3.30E-08 response to stress 50 8.60E-08 response to inorganic substance 16 1.10E-07 alcohol catabolic process 11 1.20E-07 response to wounding 25 1.70E-07 glycolysis 9 1.80E-07 inflammatory response 19 3.70E-07 response to external stimulus 33 4.80E-07 tissue development 27 8.60E-07 actin cytoskeleton organization 15 2.10E-06 defense response to bacterium 11 2.50E-06 ectoderm development 14 2.80E-06 immune system process 33 3.20E-06

Claims

CLAIMS:

1. A method for diagnosing the status of periodontitis disease, comprising:

providing at least one of a gingival crevicular fluid (GCF) sample and a saliva sample;

selecting a set of protein biomarkers for identifying a particular state of periodontitis; and

determining the expression levels in the selected set of protein biomarkers to diagnose the status of periodontitis disease.

2. The method according to claim 1, wherein the set of protein biomarkers is selected for distinguishing between a gingivitis state and a periodontitis state.

3. The method according to claim 1, wherein the set of protein biomarkers is selected for distinguishing between a periodontal health and a disease state.

4. The method according to claim 1, wherein the set of protein biomarkers is selected for distinguishing between a mild periodontitis state and a severe periodontitis state.

5. The method according to any one of claims 1-4, wherein the set of protein biomarkers includes at least one protein selected from the group consisting of haemoglobin chains alpha and beta, carbonic anhydrase 1 (International Protein Index or "IPI" #IPI00980674), and plastin-1.

6. The method according to any one of claims 1-4, wherein the set of protein biomarkers includes at least one protein selected from the group consisting of S100-P, transaldolase, S100-A8 (calgranulin-A), myosin-9, Haemoglobin Alpha, and Haemoglobin Beta.

7. The method according to any one of claims 1-4, wherein the set of protein biomarkers includes at least one protein selected from the group consisting of Alpha- 1 -acid glycoprotein 1 and 2, matrix metalloproteinase-9, Peptidyl-prolyl cis-trans isomerase A, and Haptoglobin-related protein (IPI00431645.1).

8. The method according to any one of claims 1-4, wherein the set of protein biomarkers includes at least one protein selected from the group consisting of NADPH oxidase and Alpha-N-acetylgalactosaminidase.

9. The method according to any one of claims 1-4, wherein the set of protein biomarkers includes Alpha-N-acetylgalactosaminidase.

10. The method according to any one of claims 1-4, wherein the set of protein biomarkers includes at least one protein selected from the group consisting of Protein SI 00- Al l (IPI00013895.1), Protein IPI00037070.3, catalase (IPI00465436.4), Choline transporterlike protein 2 derivative (IPI00903245.1), and titin isoform N2-B (IPI00985334.2).

11. The method according to any one of claims 5-8 and 10, wherein the set of protein biomarkers includes two or more biomarkers.

12. A kit for diagnosing the status of periodontitis disease, comprising a set of protein biomarkers selected to distinguish between gingivitis and periodontitis.

13. The kit according to claim 12, wherein the set of protein biomarkers includes at least one protein selected from the group consisting of haemoglobin chains alpha and beta, carbonic anhydrase 1 (International Protein Index or "IPI" #IPI00980674), and plastin 1.

14. The kit according to claim 12, wherein the kit diagnoses gingivitis or mild periodontitis, and the set of protein biomarkers further includes at least one protein biomarkers from saliva data clusters IB, ID, 1A4, and 1 A5.

15. The method according to any one of claims 1-1 1, further including, further including:

providing both the GCF sample and saliva sample;

generating a first and second protein profile by analyzing the proteome of a GCF sample and a saliva sample;

determining an overlap region between the first and second protein profiles; wherein selecting the set of protein biomarkers for distinguishing between particular states of periodontitis includes calculating a change in abundance of proteins within the overlap region during different stages of periodontitis and selecting those proteins which are under or over expressed during a single state of periodontitis.

16. The method according to any one of claims 1-11, further including:

generating a protein profile by analyzing the proteome of the at least one oral fluid sample; and

clustering the protein profile to determine a set of protein biomarkers.