Direct detection of Mycobacterium tuberculosis in sputum: A validation study using solid phase extraction-gas chromatography-mass spectrometry.

Tuberculosis (TB) remains a worldwide health problem, especially in developing countries. Correct identification of Mycobacterium tuberculosis (MTB) infection is extremely important for providing appropriate treatment and care to patients. Here we describe a solid phase extraction-gas chromatography-mass spectrometry method (SPE-THM-GC-MS) for the detection of five biomarkers for M. tuberculosis. The method for classification is developed and validated through the analysis of 112 sputum samples from patients suspected of having TB. Twenty of twenty-five MTB culture-positive sputum samples were correctly classified as positive by our improved SPE-THM-GC-MS method. Eighty-five of eighty-seven MTB culture-negative samples were also negative by SPE-THM-GC-MS. The overall sensitivity of the new SPE-THM-GC-MS method is 80% (20/25) and the specificity is 98% (85/87) compared with culture. The method proved to be reliable and, although complex in principle, easy to operate due to the high degree of automation.

Direct detection of Mycobacterium tuberculosis in sputum using combined solid phase extraction-gas chromatography-mass spectrometry.

Recently, thermally-assisted hydrolysis and methylation followed by gas chromatography-mass spectrometry (THM-GC-MS) in combination with chemometrics has been used to develop a 20-compound model for fast differentiation of Mycobacterium tuberculosis (MTB) from Non-tuberculous mycobacteria (NTM) in bacterial cultures. This model provided better than 95% accuracy. In our current work a hexane/methanol/water extraction followed by a solid phase extraction (SPE) clean-up procedure was developed for use before THM-GC-MS, to make the test suitable for the identification of mycobacteria in sputum. The 20 biomarker model had to be adapted since many compounds were also found in the sputum of non-tuberculosis patients. An algorithm was established based on tuberculostearic acid, hexacosanoic acid and mycoserosates. The detection limit of the method was approximately 1×10(4) bacteria/mL sputum. Sputum specimens from 32 patients from South Africa who were suspected of having tuberculosis were blindly tested using the new method. Eight of the nine culture-positive sputum specimens were detected by the new SPE-THM-GC-MS method, resulting in a sensitivity of 89%. The specimen that was missed by the new method was also microscopy negative. The specificity of the test was 100%; all 23 microscopy- and culture-negative specimens were correctly identified as negative by SPE-THM-GC-MS.

Rapid diagnosis of TB using GC-MS and chemometrics.

The search continues for a rapid diagnostic test for TB that has high sensitivity and specificity and is useable in sophisticated environments and in deprived regions with poor infrastructure. We discuss here the modern bioanalytical techniques that can be used to discover biomarkers of infection with Mycobacterium tuberculosis, focusing on techniques using GC. We will also discuss the use of GC-MS to identify volatile organic compounds in the headspace of bacterial culture or in samples of breath, serum or urine. Biomarkers discovered in the 'clean' environment of culture may differ from those in patients. A number of biomarkers have been found in patients, with little consistency in the various studies to date. Reproducibility is difficult; the impressive results found initially with a few patients are rarely repeatable when a larger sample series is tested. Mycobacterial lipids offer promise for distinguishing M. tuberculosis from nontuberculous mycobacteria directly in sputum.

Validation of biomarkers for distinguishing Mycobacterium tuberculosis from non-tuberculous mycobacteria using gas chromatography-mass spectrometry and chemometrics.

Tuberculosis (TB) remains a major international health problem. Rapid differentiation of Mycobacterium tuberculosis complex (MTB) from non-tuberculous mycobacteria (NTM) is critical for decisions regarding patient management and choice of therapeutic regimen. Recently we developed a 20-compound model to distinguish between MTB and NTM. It is based on thermally assisted hydrolysis and methylation gas chromatography-mass spectrometry and partial least square discriminant analysis. Here we report the validation of this model with two independent sample sets, one consisting of 39 MTB and 17 NTM isolates from the Netherlands, the other comprising 103 isolates (91 MTB and 12 NTM) from Stellenbosch, Cape Town, South Africa. All the MTB strains in the 56 Dutch samples were correctly identified and the model had a sensitivity of 100% and a specificity of 94%. For the South African samples the model had a sensitivity of 88% and specificity of 100%. Based on our model, we have developed a new decision-tree that allows the differentiation of MTB from NTM with 100% accuracy. Encouraged by these findings we will proceed with the development of a simple, rapid, affordable, high-throughput test to identify MTB directly in sputum.