Early-Stage Staphylococcus aureus Bloodstream Infection Causes Changes in the Concentrations of Lipoproteins and Acute-Phase Proteins and Is Associated with Low Antibody Titers against Bacterial Virulence Factors.

Systemic and quantitative investigations of human plasma proteins (proteomics) and Staphylococcus aureus-specific antibodies (immunoproteomics) provide complementary information and hold promise for the discovery of biomarkers in Staphylococcus aureus bloodstream infection (SABSI). Usually, data-dependent acquisition (DDA) is used for proteome analysis of serum or plasma, but data-independent acquisition (DIA) is more comprehensive and reproducible. In this prospective cohort study, we aimed to identify biomarkers associated with the early stages of SABSI using a serum DIA proteomic and immunoproteomic approach. Sera from 49 SABSI patients and 43 noninfected controls were analyzed. In total, 608 human serum proteins were identified with DIA. A total of 386 proteins could be quantified, of which 9 proteins, mainly belonging to acute-phase proteins, were significantly increased, while 7 high-density lipoproteins were lower in SABSI. In SABSI, total anti-S. aureus serum IgG was reduced compared with controls as shown by immunoproteomic quantification of IgG binding to 143 S. aureus antigens. IgG binding to 48 of these anti-S. aureus proteins was significantly lower in SABSI, while anti-Ecb IgG was the only one increased in SABSI. Serum IgG binding to autoinducing peptide MsrB, FadB, EsxA, Pbp2, FadB, SspB, or SodA was very low in SABSI. This marker panel discriminated early SABSI from controls with 95% sensitivity and 100% specificity according to random forest prediction. This holds promise for patient stratification according to their risk of S. aureus infection, underlines the protective function of the adaptive immune system, and encourages further efforts in the development of a vaccine against S. aureus IMPORTANCE S. aureus sepsis has a high complication and mortality rate. Given the limited therapeutic possibilities, effective prevention strategies, e.g., a vaccine, or the early identification of high-risk patients would be important but are not available. Our study showed an acute-phase response in patients with S. aureus bloodstream infection and evidence that lipoproteins are downregulated in plasma. Using immunoproteomics, stratification of patients appears to be achievable, since at the early stages of systemic S. aureus infection patients had low preexisting anti-S. aureus antibody levels. This strengthens the notion that a robust immune memory for S. aureus protects against infections with the pathogen.

A global Staphylococcus aureus proteome resource applied to the in vivo characterization of host-pathogen interactions.

Data-independent acquisition mass spectrometry promises higher performance in terms of quantification and reproducibility compared to data-dependent acquisition mass spectrometry methods. To enable high-accuracy quantification of Staphylococcus aureus proteins, we have developed a global ion library for data-independent acquisition approaches employing high-resolution time of flight or Orbitrap instruments for this human pathogen. We applied this ion library resource to investigate the time-resolved adaptation of S. aureus to the intracellular niche in human bronchial epithelial cells and in a murine pneumonia model. In epithelial cells, abundance changes for more than 400 S. aureus proteins were quantified, revealing, e.g., the precise temporal regulation of the SigB-dependent stress response and differential regulation of translation, fermentation, and amino acid biosynthesis. Using an in vivo murine pneumonia model, our data-independent acquisition quantification analysis revealed for the first time the in vivo proteome adaptation of S. aureus. From approximately 2.15 × 105 S. aureus cells, 578 proteins were identified. Increased abundance of proteins required for oxidative stress response, amino acid biosynthesis, and fermentation together with decreased abundance of ribosomal proteins and nucleotide reductase NrdEF was observed in post-infection samples compared to the pre-infection state.

Cross-Sectional Association of Salivary Proteins with Age, Sex, Body Mass Index, Smoking, and Education.

Whole saliva is gaining more and more attention as a diagnostic tool to study disease-specific changes in human subjects. Prior to the actual disease-related analyses, it is important to understand the influence of various demographic variables and coupled phenotypes on salivary protein signatures. In a cross-sectional approach, we analyzed the influence of age, sex, body mass index (BMI), smoking, and education on salivary protein signatures in whole saliva samples of 187 individuals. Subjects were randomly selected from the population-based Study of Health in Pomerania (SHIP-Trend). Stimulated whole saliva was collected, and proteins were precipitated and proteolytically digested. Samples were analyzed by label-free tandem mass spectrometry. Of the 602 human proteins identified in at least 40% of the saliva samples, we used 304 proteins, which could be identified with at least two unique peptides, for statistical analyses. Univariate and multivariate linear models were used to reveal associations with the phenotypes. The largest number of proteins was associated with smoking status. Moreover, age had a distinct influence on the salivary protein composition. The study discloses the influence of common phenotypes on the salivary protein pattern of human subjects. These results should be considered when studying disease-related proteome signatures in saliva.

Comparative evaluation of peptide desalting methods for salivary proteome analysis.

BACKGROUND: Reliability and reproducibility are common requirements for high-quality generation of proteome data using mass spectrometry. The aim of this study was to compare four single-step desalting devices to provide a reproducible, high-recovery method for concentrating and purifying tryptic peptides before LC-MS/MS measurements. MATERIAL AND METHODS: Four different methods for peptide purification prior LC-MS/MS analyses (µC18 ZipTip® pipette tips, C18 ZipTip® pipette tips, TopTip C-18 and OASIS® HLB µElution Plate) were tested using whole saliva from healthy volunteers. A number of protein identifications and salivary protein patterns were analyzed comparatively. RESULTS: Each desalting device facilitated the identification of about 340 proteins. Purification-method dependent variations in protein composition were observed. Nevertheless, the overall inter-approach Pearson correlation coefficients of >0.95 indicate high reproducibility, reliability and recovery of proteins. CONCLUSION: The applied devices performed equally well in the removal of low molecular weight contaminants and provide high-quality data for quantitative proteomic analysis. Thus, selection should be primarily based on the amount of peptide extract available and the number of samples to be processed.

Identification of periodontitis associated changes in the proteome of whole human saliva by mass spectrometric analysis.

AIM: Interest in human saliva proteomics for disease-specific biomarker screening increased in the last decade. We used whole saliva samples from periodontally healthy and diseased subjects with chronic periodontitis to screen for disease-associated differences in the protein pattern. MATERIAL AND METHODS: We selected 20 periodontally healthy and 20 periodontally diseased subjects from the population-based cross-sectional Study of Health in Pomerania (SHIP-2 and SHIP-Trend). Saliva collection was performed with commercially available Salivette(®) (Sarstedt, Nümbrecht, Germany). Whole saliva proteins were analysed after trichloroacetic acid (TCA) precipitation and proteolytic digestion with trypsin by LC-MS/MS. MS-data were analysed and quantified using the Rosetta Elucidator software package. RESULTS: In whole saliva we identified 344 human protein groups across all samples. For label free quantitation we only considered 152 proteins identified with more than one unique peptide. In total, 20 proteins showed 1.5-fold difference in abundance between controls and patients (p < 0.05); the majority of these proteins showed higher abundance in the periodontally diseased subjects. Functional annotation of proteins linked the periodontally diseased status with acute phase response and inflammatory processes. CONCLUSION: Label free proteomic analysis of whole saliva is a powerful tool to characterize the periodontal disease status and differentiate between healthy and periodontally diseased subjects.