Dataset Information

Rapid etiological classification of meningitis by NMR spectroscopy based on metabolite profiles and host response.

ABSTRACT: Bacterial meningitis is an acute disease with high mortality that is reduced by early treatment. Identification of the causative microorganism by culture is sensitive but slow. Large volumes of cerebrospinal fluid (CSF) are required to maximise sensitivity and establish a provisional diagnosis. We have utilised nuclear magnetic resonance (NMR) spectroscopy to rapidly characterise the biochemical profile of CSF from normal rats and animals with pneumococcal or cryptococcal meningitis. Use of a miniaturised capillary NMR system overcame limitations caused by small CSF volumes and low metabolite concentrations. The analysis of the complex NMR spectroscopic data by a supervised statistical classification strategy included major, minor and unidentified metabolites. Reproducible spectral profiles were generated within less than three minutes, and revealed differences in the relative amounts of glucose, lactate, citrate, amino acid residues, acetate and polyols in the three groups. Contributions from microbial metabolism and inflammatory cells were evident. The computerised statistical classification strategy is based on both major metabolites and minor, partially unidentified metabolites. This data analysis proved highly specific for diagnosis (100% specificity in the final validation set), provided those with visible blood contamination were excluded from analysis; 6-8% of samples were classified as indeterminate. This proof of principle study suggests that a rapid etiologic diagnosis of meningitis is possible without prior culture. The method can be fully automated and avoids delays due to processing and selective identification of specific pathogens that are inherent in DNA-based techniques.

SUBMITTER: Himmelreich U

PROVIDER: S-EPMC2669500 | biostudies-literature | 2009

REPOSITORIES: biostudies-literature

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Rapid etiological classification of meningitis by NMR spectroscopy based on metabolite profiles and host response.

Himmelreich Uwe U Malik Richard R Kühn Till T Daniel Heide-Marie HM Somorjai Ray L RL Dolenko Brion B Sorrell Tania C TC

PloS one 20090424 4

Bacterial meningitis is an acute disease with high mortality that is reduced by early treatment. Identification of the causative microorganism by culture is sensitive but slow. Large volumes of cerebrospinal fluid (CSF) are required to maximise sensitivity and establish a provisional diagnosis. We have utilised nuclear magnetic resonance (NMR) spectroscopy to rapidly characterise the biochemical profile of CSF from normal rats and animals with pneumococcal or cryptococcal meningitis. Use of a mi ...[more]

PMID: 19390697

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Project description:A current challenge in metabolomics is the reliable quantitation of many metabolites. Limited resolution and sensitivity combined with the challenges associated with unknown metabolite identification have restricted both the number and the quantitative accuracy of blood metabolites. Focused on alleviating this bottleneck in NMR-based metabolomics, investigations of pooled human serum combining an array of 1D/2D NMR experiments at 800 MHz, database searches, and spiking with authentic compounds enabled the identification of 67 blood metabolites. Many of these (?1/3) are new compared with those reported previously as a part of the Human Serum Metabolome Database. In addition, considering both the high reproducibility and quantitative nature of NMR as well as the sensitivity of NMR chemical shifts to altered sample conditions, experimental protocols and comprehensive peak annotations are provided here as a guide for identification and quantitation of the new pool of blood metabolites for routine applications. Further, investigations focused on the evaluation of quantitation using organic solvents revealed a surprisingly poor performance for protein precipitation using acetonitrile. One-third of the detected metabolites were attenuated by 10-67% compared with methanol precipitation at the same solvent-to-serum ratio of 2:1 (v/v). Nearly 2/3 of the metabolites were further attenuated by up to 65% upon increasing the acetonitrile-to-serum ratio to 4:1 (v/v). These results, combined with the newly established identity for many unknown metabolites in the NMR spectrum, offer new avenues for human serum/plasma-based metabolomics. Further, the ability to quantitatively evaluate nearly 70 blood metabolites that represent numerous classes, including amino acids, organic acids, carbohydrates, and heterocyclic compounds, using a simple and highly reproducible analytical method such as NMR may potentially guide the evaluation of samples for analysis using mass spectrometry.

Dataset Information

Rapid etiological classification of meningitis by NMR spectroscopy based on metabolite profiles and host response.

Publications

Rapid etiological classification of meningitis by NMR spectroscopy based on metabolite profiles and host response.

Similar Datasets

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