Hexapeptide libraries for enhanced protein PTM identification and relative abundance profiling in whole human saliva

Saliva biomarkers in oral disease

Saliva is a versatile biofluid that contains a wide variety of biomarkers reflecting both physiologic and pathophysiologic states. Saliva collection is noninvasive and highly applicable for tests requiring serial sampling. Furthermore, advances in test accuracy, sensitivity and precision for saliva has improved diagnostic performance as well as the identification of novel markers especially in oral disease processes. These include dental caries, periodontitis, oral squamous cell carcinoma (OSCC) and Sjögren's syndrome (SS). Numerous growth factors, enzymes, interleukins and cytokines have been identified and are the subject of much research investigation. This review highlights current procedures for successful determination of saliva biomarkers including preanalytical factors associated with sampling, storage and pretreatment as well as subsequent analysis. Moreover, it provides an overview of the diagnostic applications of these salivary biomarkers in common oral diseases.

A novel strategy for quantification of α2,3- and α2,6-linked sialic acids in sialylated glycoproteins

Sialic acid, a monosaccharide containing nine carbon atoms, is widely distributed in eukaryotic cells. The bound sialic acids are mainly present at the glycan ends of glycoconjugates via α2-3 or α2-6 glycosidic bonds, and alterations in their expression levels and linkage types are associated with the progress of many diseases and tumors. The present study provides a new strategy for quantification of α2,3- and α2,6-linked sialic acids in sialylated glycoproteins. In fact, quantification of α2,3-linked sialic acids were based on the difference of the bound sialic acids in the sample before and after treatment with α2-3 neuraminidase, whereas the α2,6-linked sialic acids were equal to the bound sialic acids in the α2-3 neuraminidase-treated sample. Subsequently, α2,3/6-linked sialic acids in salivary glycoproteins from healthy volunteers and diabetic patients were quantified in accordance with this method. This work provides an accurate method for the quantification of α2,3- and α2,6-linked sialic acids in the sialoglycoproteins, which is more instructive for understanding the biological roles of α2,3/6-linked sialic acid in sialoglycoproteins.

Salivary Glycopatterns as Potential Non-Invasive Biomarkers for Diagnosing and Reflecting Severity and Prognosis of Diabetic Nephropathy

Discriminating between diabetic nephropathy (DN) and non-diabetic renal disease (NDRD) can help provide more specific treatments. However, there are no ideal biomarkers for their differentiation. Thus, the aim of this study was to identify biomarkers for diagnosing and predicting the progression of DN by investigating different salivary glycopatterns. Lectin microarrays were used to screen different glycopatterns in patients with DN or NDRD. The results were validated by lectin blotting. Logistic regression and artificial neural network analyses were used to construct diagnostic models and were validated in in another cohort. Pearson's correlation analysis, Cox regression, and Kaplan-Meier survival curves were used to analyse the correlation between lectins, and disease severity and progression. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) and bioinformatics analyses were used to identify corresponding glycoproteins and predict their function. Both the logistic regression model and the artificial neural network model achieved high diagnostic accuracy. The levels of Aleuria aurantia lectin (AAL), Lycopersicon esculentum lectin (LEL), Lens culinaris lectin (LCA), Vicia villosa lectin (VVA), and Narcissus pseudonarcissus lectin (NPA) were significantly correlated with the clinical and pathological parameters related to DN severity. A high level of LCA and a low level of LEL were associated with a higher risk of progression to end-stage renal disease. Glycopatterns in the saliva could be a non-invasive tool for distinguishing between DN and NDRD. The AAL, LEL, LCA, VVA, and NPA levels could reflect the severity of DN, and the LEL and LCA levels could indicate the prognosis of DN.

Metaproteome and metabolome of oral microbial communities

The emergence of high-throughput technologies for the comprehensive measurement of biomolecules, also referred to as "omics" technologies, has helped us gather "big data" and characterize microbial communities. In this article, we focus on metaproteomic and metabolomic approaches that support hypothesis-driven investigations on various oral biologic samples. Proteomics reveals the working units of the oral milieu and metabolomics unveils the reactions taking place; and so these complementary techniques can unravel the functionality and underlying regulatory processes within various oral microbial communities. Current knowledge of the proteomic interplay and metabolic interactions of microorganisms within oral biofilm and salivary microbiome communities is presented and discussed, from both clinical and basic research perspectives. Communities indicative of, or from, health, caries, periodontal diseases, and endodontic lesions are represented. Challenges, future prospects, and examples of best practice are given.

Integrated glycomics strategy for the evaluation of glycosylation alterations in salivary proteins associated with type 2 diabetes mellitus

Glycosylation is involved in several biological processes, and its alterations can reflect the process of certain diseases. Type 2 diabetes mellitus (T2DM) has attained the status of a global pandemic; however, the difference in salivary protein glycosylation between healthy subjects and patients with T2DM has not been fully understood. In the present study, salivary specimens from patients with T2DM (n = 72) and healthy volunteers (HVs, n = 80) were enrolled and divided into discovery and validation cohorts. A method combining the lectin microarray and lectin blotting was employed to investigate and confirm the altered glycopatterns in salivary glycoproteins. Then, lectin-mediated affinity capture of glycoproteins and MALDI-TOF/TOF-MS were performed to obtain the precise structural information of the altered glycans. As a result, the glycopatterns recognized by 5 lectins (LEL, VVA, Jacalin, RCA120 and DSA) showed significant alteration in the saliva of T2DM patients. Notably, the glycopattern of Galβ-1,4GlcNAc (LacNAc) recognized by LEL exhibited a significant increase in T2DM patients compared to HVs in both discovery and validation cohorts. The MALDI-TOF/TOF-MS results indicated that there were 10 and 7 LacNAc-containing N/O-glycans (e.g. m/z 1647.586, 11 688.613 and 1562.470) that were identified only in T2DM patients. Besides, the relative abundance of 3 LacNAc-containing N-glycans and 10 LacNAc-containing O-glycans showed an increase in the glycopattern in T2DM patients. These results indicated that the glycopattern of LacNAc is increased in salivary glycoproteins from T2DM patients, and an increase in LacNAc-containing N/O-glycans may contribute to this alteration. Our findings provide useful information to understand the complex physiological changes in the T2DM patients.

Agonists of Orally Expressed TRP Channels Stimulate Salivary Secretion and Modify the Salivary Proteome

Natural compounds that can stimulate salivary secretion are of interest in developing treatments for xerostomia, the perception of a dry mouth, that affects between 10 and 30% of the adult and elderly population. Chemesthetic transient receptor potential (TRP) channels are expressed in the surface of the oral mucosa. The TRPV1 agonists capsaicin and piperine have been shown to increase salivary flow when introduced into the oral cavity but the sialogogic properties of other TRP channel agonists have not been investigated. In this study we have determined the influence of different TRP channel agonists on the flow and protein composition of saliva. Mouth rinsing with the TRPV1 agonist nonivamide or menthol, a TRPM8 agonist, increased whole mouth saliva (WMS) flow and total protein secretion compared with unstimulated saliva, the vehicle control mouth rinse or cinnamaldehyde, a TRPA1 agonist. Nonivamide also increased the flow of labial minor gland saliva but parotid saliva flow rate was not increased. The influence of TRP channel agonists on the composition and function of the salivary proteome was investigated using a multi-batch quantitative MS method novel to salivary proteomics. Inter-personal and inter-mouth rinse variation was observed in the secreted proteomes and, using a novel bioinformatics method, inter-day variation was identified with some of the mouth rinses. Significant changes in specific salivary proteins were identified after all mouth rinses. In the case of nonivamide, these changes were attributed to functional shifts in the WMS secreted, primarily the over representation of salivary and nonsalivary cystatins which was confirmed by immunoassay. This study provides new evidence of the impact of TRP channel agonists on the salivary proteome and the stimulation of salivary secretion by a TRPM8 channel agonist, which suggests that TRP channel agonists are potential candidates for developing treatments for sufferers of xerostomia.

Tracking the functional meaning of the human oral-microbiome protein-protein interactions

The interactome - the network of protein-protein interactions (PPIs) within a cell or organism - is technically difficult to assess. Bioinformatic tools can, not only, identify potential PPIs that can be later experimentally validated, but also be used to assign functional meaning to PPIs. Saliva's potential as a non-invasive diagnostic fluid is currently being explored by several research groups. But, in order to fully attain its potential, it is necessary to achieve the full characterization of the mechanisms that take place within this ecosystem. The onset of omics technologies, and specifically of proteomics, delivered a huge set of data that is largely underexplored. Quantitative information relative to proteins within a given context (for example a given disease) can be used by computational algorithms to generate information regarding PPIs. These PPIs can be further analyzed concerning their functional meaning and used to identify potential biomarkers, therapeutic targets, defense and pathogenicity mechanisms. We describe a computational pipeline that can be used to identify and analyze PPIs between human and microbial proteins. The pipeline was tested within the scenario of human PPIs of systemic (Zika Virus infection) and of oral conditions (Periodontal disease) and also in the context of microbial interactions (Candida-Streptococcus) and showed to successfully predict functionally relevant PPIs. The pipeline can be applied to different scientific areas, such as pharmacological research, since a functional meaningful PPI network can provide insights on potential drug targets, and even new uses for existing drugs on the market.

N-GlycositeAtlas: a database resource for mass spectrometry-based human N-linked glycoprotein and glycosylation site mapping

BACKGROUND

N-linked glycoprotein is a highly interesting class of proteins for clinical and biological research. The large-scale characterization of N-linked glycoproteins accomplished by mass spectrometry-based glycoproteomics has provided valuable insights into the interdependence of glycoprotein structure and protein function. However, these studies focused mainly on the analysis of specific sample type, and lack the integration of glycoproteomic data from different tissues, body fluids or cell types.

METHODS

In this study, we collected the human glycosite-containing peptides identified through their de-glycosylated forms by mass spectrometry from over 100 publications and unpublished datasets generated from our laboratory. A database resource termed N-GlycositeAtlas was created and further used for the distribution analyses of glycoproteins among different human cells, tissues and body fluids. Finally, a web interface of N-GlycositeAtlas was created to maximize the utility and value of the database.

RESULTS

The N-GlycositeAtlas database contains more than 30,000 glycosite-containing peptides (representing > 14,000 N-glycosylation sites) from more than 7200 N-glycoproteins from different biological sources including human-derived tissues, body fluids and cell lines from over 100 studies.

CONCLUSIONS

The entire human N-glycoproteome database as well as 22 sub-databases associated with individual tissues or body fluids can be downloaded from the N-GlycositeAtlas website at http://nglycositeatlas.biomarkercenter.org.

Mapping human N-linked glycoproteins and glycosylation sites using mass spectrometry

N-linked glycoprotein is a highly interesting class of proteins for clinical and biological research. Over the last decade, large-scale profiling of N-linked glycoproteins and glycosylation sites from biological and clinical samples has been achieved through mass spectrometry-based glycoproteomic approaches. In this paper, we reviewed the human glycoproteomic profiles that have been reported in more than 80 individual studies, and mainly focused on the N-glycoproteins and glycosylation sites identified through their deglycosylated forms of glycosite-containing peptides. According to our analyses, more than 30,000 glycosite-containing peptides and 7,000 human glycoproteins have been identified from five different body fluids, twelve human tissues (or related cell lines), and four special cell types. As the glycoproteomic data is still missing for many organs and tissues, a systematical glycoproteomic analysis of various human tissues and body fluids using a uniform platform is still needed for an integrated map of human N-glycoproteomes.

Salivary Glycopatterns as Potential Biomarkers for Screening of Early-Stage Breast Cancer

OBJECTIVE

We systematically investigated and assessed the alterations of salivary glycopatterns and possibility as biomarkers for diagnosis of early-stage breast cancer.

DESIGN

Alterations of salivary glycopatterns were probed using lectin microarrays and blotting analysis from 337 patients with breast benign cyst or tumor (BB) or breast cancer (I/II stage) and 110 healthy humans. Their diagnostic models were constructed by a logistic stepwise regression in the retrospective cohort. Then, the performance of the diagnostic models were assessed by ROC analysis in the validation cohort. Finally, a double-blind cohort was tested to confirm the application potential of the diagnostic models.

RESULTS

The diagnostic models were constructed based on 9 candidate lectins (e.g., PHA-E+L, BS-I, and NPA) that exhibited significant alterations of salivary glycopatterns, which achieved better diagnostic powers with an AUC value >0.750 (p<0.001) for the diagnosis of BB (AUC: 0.752, sensitivity: 0.600, and specificity: 0.835) and I stage breast cancer (AUC: 0.755, sensitivity: 0.733, and specificity: 0.742) in the validation cohort. The diagnostic model of I stage breast cancer exhibited a high accuracy of 0.902 in double-blind cohort.

CONCLUSIONS

This study could contribute to the screening for patients with early-stage breast cancer based on precise alterations of salivary glycopatterns.

Influence of different sample preparation strategies on the proteomic identification of stress biomarkers in porcine saliva

Background

The influence of two different sample treatments comprising the enrichment of glycoproteins by boronic acid and dynamic range compression by hexapeptide libraries, on the detection of stress markers in saliva of pigs was evaluated in this study. For this purpose, saliva samples collected before and after the application of an acute stress model consisting of nasal restraining in pigs were processed without any treatment and with the two different treatments mentioned above. Protein separation by two-dimensional gel electrophoresis (2-DE) followed by identification of proteins using MALDI-TOF/TOF mass spectrometry (MS) was used as proteomic technique.

Results

The application of each of the two different sample treatment protocols allowed the identification of unique proteins that could be potential salivary acute stress markers in pigs: lipocalin 1, protein S100-A8 and immunoglobulin M by enrichment of glycoproteins; protein S100-A9, double headed protease inhibitor submandibular gland, and haemoglobin by dynamic range compression; and protein S100-A12 by both protocols. Salivary lipocalin, prolactin inducible protein, light chain of immunoglobulins, adenosine deaminase and carbonic anhydrase VI were identified as potential markers in untreated saliva as well as one of the other treatments.

Conclusion

The use of different procedures allowed the detection of different potential stress markers. Although from a practical point of view, the use of saliva without further treatment as well as the enrichment of glycoproteins are less expensive and easy to do procedures.

Enrichment and identification of glycoproteins in human saliva using lectin magnetic bead arrays

Aberrant glycosylation of proteins is a hallmark of tumorigenesis and could provide diagnostic value in cancer detection. Human saliva is an ideal source of glycoproteins due to the relatively high proportion of glycosylated proteins in the salivary proteome. Moreover, saliva collection is noninvasive and technically straightforward, and the sample collection and storage is relatively easy. Although differential glycosylation of proteins can be indicative of disease states, identification of differential glycosylation from clinical samples is not trivial. To facilitate salivary glycoprotein biomarker discovery, we optimized a method for differential glycoprotein enrichment from human saliva based on lectin magnetic bead arrays (saLeMBA). Selected lectins from distinct reactivity groups were used in the saLeMBA platform to enrich salivary glycoproteins from healthy volunteer saliva. The technical reproducibility of saLeMBA was analyzed with liquid chromatography-tandem mass spectrometry (LC-MS/MS) to identify the glycosylated proteins enriched by each lectin. Our saLeMBA platform enabled robust glycoprotein enrichment in a glycoprotein- and lectin-specific manner consistent with known protein-specific glycan profiles. We demonstrated that saLeMBA is a reliable method to enrich and detect glycoproteins present in human saliva.

Mass spectrometry-based analyses showing the effects of secretor and blood group status on salivary N-glycosylation

Background

The carbohydrate portions of salivary glycoproteins play important roles, including mediating bacterial and leukocyte adhesion. Salivary glycosylation is complex. Many of its glycoproteins present ABO and Lewis blood group determinants. An individual’s genetic complement and secretor status govern the expression of blood group antigens. We queried the extent to which salivary glycosylation varies according to blood group and secretor status. First, we screened submandibular/sublingual and parotid salivas collected as ductal secretions for reactivity with a panel of 16 lectins. We selected three lectins that reacted with the largest number of glycoproteins and one that recognized uncommon lactosamine-containing structures. Ductal salivas representing a secretor with complex blood group expression and a nonsecretor with a simple pattern were separated by SDS-PAGE. Gel slices were trypsin digested and the glycopeptides were individually separated on each of the four lectins. The bound fractions were de-N-glycosylated. LC–MS/MS identified the original glycosylation sites, the peptide sequences, and the parent proteins.

Results

The results revealed novel salivary N-glycosites and glycoproteins not previously reported. As compared to the secretor, nonsecretor saliva had higher levels of N-glycosylation albeit with simpler structures.

Conclusions

Together, the results suggested a molecular basis for inter-individual variations in salivary protein glycosylation with functional implications for oral health.

Electronic supplementary material

The online version of this article (doi:10.1186/s12014-015-9100-y) contains supplementary material, which is available to authorized users.

Avian influenza virus infection risk in humans with chronic diseases

Saliva proteins may protect older people from influenza, however, it is often noted that hospitalizations and deaths after an influenza infection mainly occur in the elderly population living with chronic diseases, such as diabetes and cancer. Our objective was to investigate the expression level of the terminal α2-3- and α2-6-linked sialic acids in human saliva from type 2 diabetes mellitus (T2DM), liver disease and gastric cancer (GC) patients and assess the binding activity of these linked sialic acids against influenza A viruses (IAV). We observed that the expression level of the terminal α2-3-linked sialic acids of elderly individuals with T2DM and liver disease were down-regulated significantly, and the terminal α2-6 linked sialic acids were up-regulated slightly or had no significant alteration. However, in the saliva of patients with GC, neither sialic acid was significantly altered. These findings may reveal that elderly individuals with chronic diseases, such as diabetes and liver disease, might be more susceptible to the avian influenza virus due to the decreased expression of terminal α2-3-linked sialic acids in their saliva.

Dynamic range compression with ProteoMiner™: principles and examples

One of the main challenges in proteomics investigation, protein biomarker research, and protein purity and contamination analysis is how to efficiently enrich and detect low-abundance proteins in biological samples. One approach that makes the detection of rare species possible is the treatment of biological samples with solid-phase combinatorial peptide ligand libraries, ProteoMiner. This method utilizes hexapeptide bead library with huge diversity to bind and enrich low-abundance proteins but remove most of the high-abundance proteins, therefore compresses the protein abundance range in the samples. This work describes optimized protocols and highlights on the successful application of ProteoMiner to protein identification and analysis.

Analysis of age and gender associated N-glycoproteome in human whole saliva

Background

Glycoproteins comprise a large portion of the salivary proteome and have great potential for biomarker discovery and disease diagnosis. However, the rate of production and the concentration of whole saliva change with age, gender and physiological states of the human body. Therefore, a thorough understanding of the salivary glycoproteome of healthy individuals of different ages and genders is a prerequisite for saliva to have clinical utility.

Methods

Formerly N-linked glycopeptides were isolated from the pooled whole saliva of six age and gender groups by hydrazide chemistry and hydrophilic affinity methods followed by mass spectrometry identification. Selected physiochemical characteristics of salivary glycoproteins were analyzed, and the salivary glycoproteomes of different age and gender groups were compared based on their glycoprotein components and gene ontology.

Results and discussion

Among 85 N-glycoproteins identified in healthy human saliva, the majority were acidic proteins with low molecular weight. The numbers of salivary N-glycoproteins increased with age. Fifteen salivary glycoproteins were identified as potential age- or gender-associated glycoproteins, and many of them have functions related to innate immunity against microorganisms and oral cavity protection. Moreover, many salivary glycoproteins have been previously reported as disease related glycoproteins. This study reveals the important role of salivary glycoproteins in the maintenance of oral health and homeostasis and the great potential of saliva for biomarker discovery and disease diagnosis.

Identification of salivary N-glycoproteins and measurement of glycosylation site occupancy by boronate glycoprotein enrichment and liquid chromatography/electrospray ionization tandem mass spectrometry

RATIONALE

Diseases including cancer and congenital disorders of glycosylation have been associated with changes in the site-specific extent of protein glycosylation. Saliva can be non-invasively sampled and is rich in glycoproteins, giving it the potential to be a useful biofluid for the discovery and detection of disease biomarkers associated with changes in glycosylation.

METHODS

Saliva was collected from healthy individuals and glycoproteins were enriched using phenylboronic acid based glycoprotein enrichment resin. Proteins were deglycosylated with peptide-N-glycosidase F and digested with AspN or trypsin. Desalted peptides and deglycosylated peptides were separated by reversed-phase liquid chromatography and detected with on-line electrospray ionization quadrupole-time-of-flight mass spectrometry using a 5600 TripleTof instrument. Site-specific glycosylation occupancy was semi-quantitatively determined from the abundance of deglycosylated and nonglycosylated versions of each given peptide.

RESULTS

Glycoprotein enrichment identified 67 independent glycosylation sites from 24 unique proteins, a 3.9-fold increase in the number of glycosylation sites identified. Enrichment of glycoproteins rather than glycopeptides allowed detection of both deglycosylated and nonglycosylated versions of each peptide, and thereby robust measurement of site-specific occupancy at 21 asparagines. Healthy individuals showed limited biological variability in occupancy, with partially modified sites having characteristics consistent with inefficient glycosylation by oligosaccharyltransferase. Inclusion of negative controls without enzymatic deglycosylation controlled for spontaneous chemical deamidation, and identified asparagines previously incorrectly annotated as glycosylated.

CONCLUSIONS

We developed a sample preparation and mass spectrometry detection strategy for rapid and efficient measurement of site-specific glycosylation occupancy on diverse salivary glycoproteins suitable for biomarker discovery and detection of changes in glycosylation occupancy in human disease.

Salivary proteomics in bisphosphonate-related osteonecrosis of the jaw

OBJECTIVE

The objective of this study was to identify differentially expressed salivary proteins in bisphosphonate-related osteonecrosis of the jaw (BRONJ) patients that could serve as biomarkers for BRONJ diagnosis.

SUBJECTS AND METHODS

Whole saliva obtained from 20 BRONJ patients and 20 controls were pooled within groups. The samples were analyzed using iTRAQ-labeled two-dimensional liquid chromatography-tandem mass spectrometry.

RESULTS

Overall, 1340 proteins were identified. Of these, biomarker candidates were selected based on P-value (<0.001), changes in protein expression (≥1.5-fold increase or decrease), and unique peptides identified (≥2). Three comparisons made between BRONJ and control patients identified 200 proteins to be differentially expressed in BRONJ patients. A majority of these proteins were predicted to have a role in drug metabolism and immunological and dermatological diseases. Of all the differentially expressed proteins, we selected metalloproteinase-9 and desmoplakin for further validation. Immunoassays confirmed increased expression of metalloproteinase-9 in individual saliva (P = 0.048) and serum samples (P = 0.05) of BRONJ patients. Desmoplakin was undetectable in saliva. However, desmoplakin levels tended to be lower in BRONJ serum than controls (P = 0.157).

CONCLUSIONS

Multiple pathological reactions are involved in BRONJ development. One or more proteins identified by this study may prove to be useful biomarkers for BRONJ diagnosis. The role of metalloproteinase-9 and desmoplakin in BRONJ requires further investigation.

Age- and sex-associated differences in the glycopatterns of human salivary glycoproteins and their roles against influenza A virus

Recent studies have elucidated that expression of certain glycoproteins in human saliva is increased or decreased according to age; meanwhile, human saliva may inhibit viral infection and prevent viral transmission. However, little is known about the age- and sex-associated differences in the glycopatterns of human salivary glycoproteins and their significant roles against influenza A virus (IVA). Here, we investigate the glycopatterns of human salivary glycoproteins with 180 healthy saliva samples divided into six age/sex groups using lectin microarrays and fabricate saliva microarrays to validate the terminal carbohydrate moieties of glycoproteins in individual saliva samples. Furthermore, we assess the inhibiting and neutralizing activity of saliva against two strains of influenza A (H9N2) virus. We find that seven lectins (e.g., MAL-II and SNA) show significant age differences in both females and males, and seven lectins (e.g., WFA and STL) show significant sex differences in children, adults and elderly people. Interestingly, we observe that elderly individuals have strongest resistance to IVA partly by presenting more terminal α2-3/6-linked sialic acid residues in their saliva, which bind with the influenza viral hemagglutinations. We conclude that age- and sex-associated differences in the glycopatterns of human salivary glycoproteins may provide pivotal information to help understand some age related diseases and physiological phenomena.

Oral fluids that detect cardiovascular disease biomarkers

OBJECTIVE

The aim of this study was to determine the utility of oral fluids for assessment of coronary and cardiovascular (CV) health.

STUDY DESIGN

Twenty-nine patients with preexisting CV disease underwent an invasive cardiac procedure (alcohol septal ablation or percutaneous coronary intervention) and provided unstimulated whole saliva (UWS), sublingual swabs (LS), gingival swabs (GS) and serum at 0, 8, 16, 24, and 48 hours. Concentrations of 13 relevant biomarkers were determined and correlated with levels in serum and the oral fluids.

RESULTS

Concentrations of the majority of biomarkers were higher in UWS than in LS and GS. Coronary and CV disease biomarkers in UWS correlated better with serum than with LS and GS based on group status and measures of time effect. Seven biomarkers demonstrated time effect changes consistent with serum biomarkers, including C-reactive protein and troponin I.

CONCLUSIONS

Changes in serum biomarker profiles are reflected in oral fluids suggesting that oral fluid biomarkers could aid in the assessment of cardiac ischemia/necrosis.

Quantitative analysis of the intra- and inter-subject variability of the whole salivary proteome

BACKGROUND AND OBJECTIVE

Interest in human saliva is increasing for disease-specific biomarker discovery studies. However, protein composition of whole saliva can grossly vary with physiological and environmental factors over time and it comprises human as well as bacterial proteins.

MATERIAL AND METHODS

We compared intra- and inter-subject variabilities using complementary gel-based (two-dimensional difference gel electrophoresis, 2-D DIGE) and gel-free (liquid chromatography tandem mass spectrometry, LC-MS/MS) proteomics profiling of saliva. Unstimulated whole saliva of four subjects was examined at three different time-points (08.00 h, 12.00 h and 17.00 h) and variability of the saliva proteome was analyzed on two successive days by LC-MS/MS.

RESULTS

In the 2-D DIGE experiment, the median coefficient of variation (CV) for intra-subject variability was significantly lower (CV of 0.39) than that for inter-subject variability (CV of 0.57; CV of technical replicates 0.17). LC-MS/MS data confirmed the significantly lower variation within subjects over time (CV of 0.37) than the inter-subject variability (CV of 0.53; CV of technical replicates 0.11), and that the inter-subject variability was not time-dependent.

CONCLUSION

Both techniques revealed similar trends of variations on technical, intra- and inter-subject level but provided peptide and protein focused information and should thus be used as complementary approaches. The data presented indicate that 2-D DIGE as well as LC-MS/MS approaches are suitable for biomarker screening in saliva.

One decade of salivary proteomics: current approaches and outstanding challenges

Efforts have been made in the last decade towards the complete characterization of saliva proteome using gel-based and gel-free approaches. The combination of these strategies resulted in the increment of the dynamic range of saliva proteome, which yield in the identification of more than 3,000 different protein species. Comparative protein profiling using isotope labeling and label free approaches has been used for the identification of novel biomarkers for oral and related diseases. Although progresses have been made in saliva proteome characterization, the comparative profiling in different pathophysiological conditions is still at the beginning if compared to other bodily fluids. The potential biomarkers identified so far lack specificity once common differentially expressed proteins were detected in the saliva of patients with distinct diseases. In addition, recent research works focused on saliva peptidome profiling already allowed a better understanding of peptides' physiological role in oral cavity. This review provides an overview of the major achievements in saliva proteomics giving emphasis to methodological concerns related with saliva collection, treatment and analysis, as well as the main advantages and pitfalls underlying salivary proteomic strategies and potential clinical outcomes.

Salivary biomarkers associated with myocardial necrosis: results from an alcohol septal ablation model

OBJECTIVE

To determine if salivary biomarkers demonstrate utility for identifying aspects of myocardial necrosis.

METHODS

Twenty-one patients undergoing alcohol septal ablation (ASA) for treatment of hypertrophic cardiomyopathy provided serum and unstimulated whole saliva at baseline and incremental time points post-ASA. Samples were analyzed for seven biomarkers related to myocardial damage, inflammation, and tissue remodeling using immunosorbent assays. Levels were compared with baseline and levels observed in 97 healthy controls.

RESULTS

Biomarkers of myocardial damage and inflammation (ie, troponin I, creatine kinase-MB, myoglobin, C-reactive protein) rose in serum 2- to 812-fold after ASA (P < .01). Significant elevations of 2.0- to 3.5-fold were observed with C-reactive protein and troponin I in saliva (P < .02). Significant correlations between levels in serum and saliva were observed for C-reactive protein, matrix metalloproteinase-9, and myeloperoxidase (P < .001).

CONCLUSIONS

Select salivary biomarkers reflect changes that occur during, and subsequent to, myocardial necrosis caused by ASA.

Characterization of the human submandibular/sublingual saliva glycoproteome using lectin affinity chromatography coupled to multidimensional protein identification technology

In-depth analysis of the salivary proteome is fundamental to understanding the functions of salivary proteins in the oral cavity and to reveal disease biomarkers involved in different pathophysiological conditions, with the ultimate goal of improving patient diagnosis and prognosis. Submandibular and sublingual glands contribute saliva rich in glycoproteins to the total saliva output, making them valuable sources for glycoproteomic analysis. Lectin-affinity chromatography coupled to mass spectrometry-based shotgun proteomics was used to explore the submandibular/sublingual (SM/SL) saliva glycoproteome. A total of 262 N- and O-linked glycoproteins were identified by multidimensional protein identification technology (MudPIT). Only 38 were previously described in SM and SL salivas from the human salivary N-linked glycoproteome, while 224 were unique. Further comparison analysis with SM/SL saliva of the human saliva proteome, revealed 125 glycoproteins not formerly reported in this secretion. KEGG pathway analyses demonstrated that many of these glycoproteins are involved in processes such as complement and coagulation cascades, cell communication, glycosphingolipid biosynthesis neo-lactoseries, O-glycan biosynthesis, glycan structures-biosynthesis 2, starch and sucrose metabolism, peptidoglycan biosynthesis or others pathways. In summary, lectin-affinity chromatography coupled to MudPIT mass spectrometry identified many novel glycoproteins in SM/SL saliva. These new additions to the salivary proteome may prove to be a critical step for providing reliable biomarkers in the diagnosis of a myriad of oral and systemic diseases.

Improvements in proteomic metrics of low abundance proteins through proteome equalization using ProteoMiner prior to MudPIT

Ideally, shotgun proteomics would facilitate the identification of an entire proteome with 100% protein sequence coverage. In reality, the large dynamic range and complexity of cellular proteomes results in oversampling of abundant proteins, while peptides from low abundance proteins are undersampled or remain undetected. We tested the proteome equalization technology, ProteoMiner, in conjunction with Multidimensional Protein Identification Technology (MudPIT) to determine how the equalization of protein dynamic range could improve shotgun proteomics methods for the analysis of cellular proteomes. Our results suggest low abundance protein identifications were improved by two mechanisms: (1) depletion of high abundance proteins freed ion trap sampling space usually occupied by high abundance peptides and (2) enrichment of low abundance proteins increased the probability of sampling their corresponding more abundant peptides. Both mechanisms also contributed to dramatic increases in the quantity of peptides identified and the quality of MS/MS spectra acquired due to increases in precursor intensity of peptides from low abundance proteins. From our large data set of identified proteins, we categorized the dominant physicochemical factors that facilitate proteome equalization with a hexapeptide library. These results illustrate that equalization of the dynamic range of the cellular proteome is a promising methodology to improve low abundance protein identification confidence, reproducibility, and sequence coverage in shotgun proteomics experiments, opening a new avenue of research for improving proteome coverage.

Large-scale phosphoproteomics analysis of whole saliva reveals a distinct phosphorylation pattern

In-depth knowledge of bodily fluid phosphoproteomes, such as whole saliva, is limited. To better understand the whole saliva phosphoproteome, we generated a large-scale catalog of phosphorylated proteins. To circumvent the wide dynamic range of phosphoprotein abundance in whole saliva, we combined dynamic range compression using hexapeptide beads, strong cation exchange HPLC peptide fractionation, and immobilized metal affinity chromatography prior to mass spectrometry. In total, 217 unique phosphopeptides sites were identified representing 85 distinct phosphoproteins at 2.3% global FDR. From these peptides, 129 distinct phosphorylation sites were identified of which 57 were previously known, but only 11 of which had been previously identified in whole saliva. Cellular localization analysis revealed salivary phosphoproteins had a distribution similar to all known salivary proteins, but with less relative representation in "extracellular" and "plasma membrane" categories compared to salivary glycoproteins. Sequence alignment showed that phosphorylation occurred at acidic-directed kinase, proline-directed, and basophilic motifs. This differs from plasma phosphoproteins, which predominantly occur at Golgi casein kinase recognized sequences. Collectively, these results suggest diverse functions for salivary phosphoproteins and multiple kinases involved in their processing and secretion. In all, this study should lay groundwork for future elucidation of the functions of salivary protein phosphorylation.