Differentiation of oral bacteria in in vitro cultures and human saliva by secondary electrospray ionization - mass spectrometry.
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ABSTRACT:
SUBMITTER: Bregy L
PROVIDER: S-EPMC4609958 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:We propose a novel application of secondary electrospray ionization-mass spectrometry (SESI-MS) as a real-time clinical diagnostic tool for bacterial infection. It is known that volatile organic compounds (VOCs), produced in different combinations and quantities by bacteria as metabolites, generate characteristic odors for certain bacteria. These VOCs comprise a specific metabolic profile that can be used for species or serovar identification, but rapid and sensitive analytical methods are required for broad utility. In this study, the VOC profiles of five bacterial groups from four genera, Pseudomonas aeruginosa, Staphylococcus aureus, Escherichia coli, Salmonella enterica serovar Typhimurium, and Salmonella enterica serovar Pullorum, were characterized by SESI-MS. Thirteen compounds were identified from these bacterial cultures, and the combination of these VOCs creates a unique pattern for each genus. In addition, principal component analysis (PCA) was applied for the purpose of species or serovar discrimination. The first three principal components exhibit a clear separation between the metabolic volatile profiles of these five bacterial groups that is independent of the growth medium. As a first step toward addressing the complexity of clinical application, in vitro tests for mixed cultures were conducted. The results show that individual species or serovars in a mixed culture are identifiable among a biological VOC background, and the ratios of the detected volatiles reflect the proportion of each bacterium in the mixture. Our data confirm the utility of SESI-MS in real-time identification of bacterial species or serovars in vitro, which, in the future, may play a promising clinical role in diagnosing infections.
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Project description:Biofilms in the oral cavity can be visualized by fluorescence and a common assumption is that the endogenously produced porphyrins in certain bacteria give rise to this fluorescence. Porphyrin content in oral bacteria has been sparingly investigated, and non-selective detection techniques such as utilizing the Soret fluorescence band of porphyrins are often used. In the present study, a quantitative and selective method for the determination of porphyrins in oral bacteria has been developed and validated using high performance liquid chromatography-tandem mass spectrometry. Lysis of bacteria using Tris-EDTA buffer together with ultrasonication showed high microbial killing efficiency ≥99.98%, and sample clean-up using C18-solid phase extraction resulted in low matrix effects ≤14% for all analytes. Using this method, the porphyrin content was determined in the two oral pathogens Aggregatibacter actinomycetemcomitans and Porphyromonas gingivalis, as well as for baker's yeast, Saccharomyces cerevisiae. Uroporphyrin, 7-carboxylporphyrin, 6-carboxylporphyrin, coproporphyrin, and protoporphyrin IX were identified in the investigated microorganisms, and it was shown that the porphyrin profile differs between the two bacteria, as well as for S. cerevisiae. To our knowledge, this is the first time the porphyrin profile has been determined for the bacterium A. actinomycetemcomitans.
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Project description:Identifying and differentiating bacteria based on their emitted volatile organic compounds (VOCs) opens vast opportunities for rapid diagnostics. Secondary electrospray ionization high-resolution mass spectrometry (SESI-HRMS) is an ideal technique for VOC-biomarker discovery because of its speed, sensitivity towards polar molecules and compound characterization possibilities. Here, an in vitro SESI-HRMS workflow to find biomarkers for cystic fibrosis (CF)-related pathogens P. aeruginosa, S. pneumoniae, S. aureus, H. influenzae, E. coli and S. maltophilia is described. From 180 headspace samples, the six pathogens are distinguishable in the first three principal components and predictive analysis with a support vector machine algorithm using leave-one-out cross-validation exhibited perfect accuracy scores for the differentiation between the groups. Additionally, 94 distinctive features were found by recursive feature elimination and further characterized by SESI-MS/MS, which yielded 33 putatively identified biomarkers. In conclusion, the six pathogens can be distinguished in vitro based on their VOC profiles as well as the herein reported putative biomarkers. In the future, these putative biomarkers might be helpful for pathogen detection in vivo based on breath samples from patients with CF.
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Project description:A 193-nm wavelength deep ultraviolet laser was used for ambient laser ablation electrospray ionization mass spectrometry of biological samples. A pulsed ArF excimer laser was used to ablate solid samples, and the resulting plume of the desorbed material merged with charged electrospray droplets to form ions that were detected with a quadrupole time-of-flight mass spectrometer. Solutions containing peptide and protein standards up to 66-kDa molecular weight were deposited on a metal target, dried, and analyzed. No fragmentation was observed from peptides and proteins as well as from the more easily fragmented vitamin B12 molecule. The mass spectra contained peaks from multiply charged ions that were identical to conventional electrospray. Deep UV laser ablation of tissue allowed detection of lipids from untreated tissue. The mechanism of ionization is postulated to involve absorption of laser energy by a fraction of the analyte molecules that act as a sacrificial matrix or by residual water in the sample.
| S-EPMC6422691 | biostudies-literature
Project description:Single-cell mass spectrometry (MS) is a rapidly emerging field in metabolic investigations. The inherent chemical complexity of most biological samples poses analytical challenges when using MS platforms to measure sample content without prior chemical separation. Here, a single-cell capillary electrophoresis (CE) system was coupled with electrospray ionization (ESI) MS to enable the simultaneous measurement of a vast array of endogenous compounds in over 50 identified and isolated large neurons from the Aplysia californica central nervous system. More than 300 distinct ion signals (m/z values) were detected from a single neuron in the positive ion mode, 140 of which were selected for chemometric data analysis. Metabolic features were evaluated among six different neuron types (B1, B2, left pleural 1 (LPl1), metacerebral cell (MCC), R2, and R15) chosen for their various physiological functions. The results indicated chemical similarities among some neuron types (B1 to B2 and LPl1 to R2) and distinctive features for others (MCC and R15 cells). The quantitative nature of the MS platform allowed the comparison of metabolite levels for specific neurons. The CE-ESI-MS approach for examination of individual nanoliter-volume cells as described herein is readily adaptable to other volume-limited samples.
| S-EPMC3196347 | biostudies-literature
Project description:Despite the attractiveness of breath analysis as a non-invasive means to retrieve relevant metabolic information, its introduction into routine clinical practice remains a challenge. Among all the different analytical techniques available to interrogate exhaled breath, secondary electrospray ionization high-resolution mass spectrometry (SESI-HRMS) offers a number of advantages (e.g., real-time, yet wide, metabolome coverage) that makes it ideal for untargeted and targeted studies. However, so far, SESI-HRMS has relied mostly on lab-built prototypes, making it difficult to standardize breath sampling and subsequent analysis, hence preventing further developments such as multi-center clinical studies. To address this issue, we present here a number of new developments. In particular, we have characterized a new SESI interface featuring real-time readout of critical exhalation parameters such as CO2, exhalation flow rate, and exhaled volume. Four healthy subjects provided breath specimens over a period of 1 month to characterize the stability of the SESI-HRMS system. A first assessment of the repeatability of the system using a gas standard revealed a coefficient of variation (CV) of 2.9%. Three classes of aldehydes, namely 4-hydroxy-2-alkenals, 2-alkenals and 4-hydroxy-2,6-alkedienals-hypothesized to be markers of oxidative stress-were chosen as representative metabolites of interest to evaluate the repeatability and reproducibility of this breath analysis analytical platform. Median and interquartile ranges (IQRs) of CVs for CO2, exhalation flow rate, and exhaled volume were 3.2% (1.5%), 3.1% (1.9%), and 5.0% (4.6%), respectively. Despite the high repeatability observed for these parameters, we observed a systematic decay in the signal during repeated measurements for the shorter fatty aldehydes, which eventually reached a steady state after three/four repeated exhalations. In contrast, longer fatty aldehydes showed a steady behavior, independent of the number of repeated exhalation maneuvers. We hypothesize that this highly molecule-specific and individual-independent behavior may be explained by the fact that shorter aldehydes (with higher estimated blood-to-air partition coefficients; approaching 100) mainly get exchanged in the airways of the respiratory system, whereas the longer aldehydes (with smaller estimated blood-to-air partition coefficients; approaching 10) are thought to exchange mostly in the alveoli. Exclusion of the first three exhalations from the analysis led to a median CV (IQR) of 6.7 % (5.5 %) for the said classes of aldehydes. We found that such intra-subject variability is in general much lower than inter-subject variability (median relative differences between subjects 48.2%), suggesting that the system is suitable to capture such differences. No batch effect due to sampling date was observed, overall suggesting that the intra-subject variability measured for these series of aldehydes was biological rather than technical. High correlations found among the series of aldehydes support this notion. Finally, recommendations for breath sampling and analysis for SESI-HRMS users are provided with the aim of harmonizing procedures and improving future inter-laboratory comparisons. Graphical abstract.
| S-EPMC6611759 | biostudies-literature
Project description:Paper spray ionization mass spectrometry (PSI-MS) is a relatively new analytical technique allowing for rapid mass spectrometric analysis of biological samples with little or no sample preparation. The expeditious nature of the analysis and minimal requirement for sample preparation make PSI-MS a promising avenue for future clinical assays with one potential application in the identification of different types of bacteria. Although past PSI-MS studies have demonstrated the ability to distinguish between bacteria of different species and morphological classes, achieving within-species strain-level differentiation has never been performed. In this report, we demonstrate the first strain-level bacterial differentiation by PSI-MS with the mammalian intestinal bacterium Oxalobacter formigenes ( Oxf). This novel application holds promising clinical significance as it could be used to differentiate between pathogenic bacteria and their harmless, commensal relatives, saving time and money in clinical diagnostics. Both whole cells and cell lysates of Oxf strains HC1 and OxWR were analyzed using the Prosolia Velox 360TM PSI source coupled to a Thermo Scientific Q Exactive high-resolution mass spectrometer with a rapid 30 s analytical method. Multivariate statistical analysis followed by examination of significant features provided for and confirmed differentiation between Oxf HC1 and OxWR. We report a panel of strain-exclusive metabolites that could serve as potential strain-indicating biomarkers.
| S-EPMC6537876 | biostudies-literature
Project description:RATIONALE:Desorption electrospray ionization mass spectrometry (DESI-MS) has demonstrated utility in differentiating tumor from adjacent normal tissue in both urologic and neurosurgical specimens. We sought to evaluate if this technique had similar accuracy in differentiating oral tongue squamous cell carcinoma (SCC) from adjacent normal epithelium due to current issues with late diagnosis of SCC in advanced stages. METHODS:Fresh frozen samples of SCC and adjacent normal tissue were obtained by surgical resection. Resections were analyzed using DESI-MS sometimes by a blinded technologist. Normative spectra were obtained for separate regions containing SCC or adjacent normal epithelium. Principal Component Analysis and Linear Discriminant Analysis (PCA-LDA) of spectra were used to predict SCC versus normal tongue epithelium. Predictions were compared with pathology to assess accuracy in differentiating oral SCC from adjacent normal tissue. RESULTS:Initial PCA score and loading plots showed clear separation of SCC and normal epithelial tissue using DESI-MS. PCA-LDA resulted in accuracy rates of 95% for SCC versus normal and 93% for SCC, adjacent normal and normal. Additional samples were blindly analyzed with PCA-LDA pixel-by-pixel predicted classifications as SCC or normal tongue epithelial tissue and compared against histopathology. The m/z 700-900 prediction model showed a 91% accuracy rate. CONCLUSIONS:DESI-MS accurately differentiated oral SCC from adjacent normal epithelium. Classification of all typical tissue types and pixel predictions with additional classifications should increase confidence in the validation model.
| S-EPMC5757369 | biostudies-literature