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MLibrary overview Print

The problem

The use of forbidden androgenic anabolic steroids (AAS) and hormones to enhance athletic performance has important health and social implications. Their use was first introduced in sports as agents supporting the athlete recuperation after extreme stress and fatigue, but rapidly became the main group in doping abuse [1]. Nowadays, this class of drugs is a major group included in the prohibited list of the world anti-doping agency (WADA) as well as of major sports authorities [2-5]. In the WADA statistic report for 2009, the AAS represented 64.9 % of all adverse analytical findings reported by WADA accredited laboratories [6].

Although most methods for routine detection of these compounds and their metabolites, comprising both screening and confirmatory analysis, are based in gas chromatography coupled with mass spectrometry (GC-MS) techniques [7-11], the long separation times of chromatographic techniques and the increasing workloads within anti-doping laboratories, expose an urgent need for an analytical technique allowing simplicity, speed and high throughput for the screening of the huge number of banned compounds, particularly the AAS.

 

State of the art

Recently, the use of MALDI-MS(/MS) for the analysis of small molecules has grown considerably, which is reflected by the increasing number of studies reported in the literature [12-16]. Moreover, it appears extremely promising for high-throughput, which is a major demand for future anti-doping methods.

In light of the latest technological improvements of this analytical technique we have developed an analytical methodology for the analysis of AAS. The matrix 2-(4-hydroxyphenylazo)-benzoic acid (HABA) was found to be the most robust for the analysis of these compounds, after a derivatisation step with the reagent Girard T hydrazine. In the aforementioned work it was demonstrated that positive identification of the characteristic peaks for all the compounds studied is possible for a sample concentration of 10 ng/mL in the MALDI sample plate. The sensitivity achieved with the HABA matrix after derivatisation was similar to that achieved by GC/MS – around 4–10 ng/mL in the single ion monitoring mode.

 

The software

The software MLibrary was developed to assist the user in the detection and identification of AASs and its metabolites. It allows the rapid interpretation of the experimental data, which is a vital step for the implementation of the aforementioned methodology in anti-doping laboratories. The MLibrary operates on comma-separated-values (CSV) files with centroid mass and relative intensity data extracted from the instrument software (Data ExplorerTM Software, version 4.5). This data can be analysed and compared with the compound data stored in the MLibrary repository, which contains the characteristic mass values of the molecular ion and the fragmentation ions for each target AAS in separated databases. For each database created and stored in the MLibrary repository, the user may include standard modification mass variations corresponding to specific derivatisation reagents and the consequent MS/MS spectra for each AAS presenting that particular modification. The MLibrary repository comprises also MS/MS compound markers. The MLibrary repository is stored in a single standard XML file, which can be easily modified with any plain text editor.

 

The experimental workflow

A schematic diagram illustrating the sequential steps of the sample treatment workflow is presented in Fig. 1. Urine samples were hydrolysed with the enzyme β-glucuronidase. After a step of liquid-liquid extraction, the extracted organic layer was dried under a gentle nitrogen stream and derivatised with Girard reagent´s T (GT). After derivatisation, the steroid GT hydrazones were separated from un-reacted GT hydrazine reagent by SPE in a C18 cartridge. The collected sample solution was mixed with an equal volume of the MALDI matrix solution and hand-spotted onto the MALDI sample plate.

The AASs detection process starts with the acquisition of single MS spectra in the MALDI-MS(/MS) equipment. The experimental data obtained is loaded in MLibrary software and the user can perform a compound search, in order to identify which AAS are present in the loaded data. The search retrieves the mass values that matched between the experimental data and the database values, showing both experimental and theoretic values as well as the name of the compound and the experimental peak intensity.

Following the first analysis in single MS mode, the ions detected by the MLibrary are selected for fragmentation in a second round of MS analysis, in which MS/MS spectra are acquire. Each AAS compound presents a characteristic MS/MS fragmentation pattern that will be used by the MLibrary as a signature of that compound. As before, the process starts with the data loading. After loading the sample spectrum, the user can perform three distinct operations. The first one is the “MS/MS Library Analysis” operation, which compares the experimental data with the characteristic MS/MS spectra of the AAS compounds stored in the MLibrary databases. The second MS/MS operation within the MLibrary software is the “MS/MS Std. Match Analysis” operation. With this tool the user can compare two experimental spectra, which is extremely important if we are working at different conditions than the one recorded in the MLibrary MS/MS database. By adding a standard solution of a specific compound to the MALDI analysis and comparing the two spectra using the MLibrary, the user can confirm the identity of this compound. The third MS/MS Analysis tool available in the MLibrary software is the “MS/MS Marker Analysis” operation that allows the user to locate concrete biomarkers into the loaded MS/MS data. This feature is particularly important for the analysis of isobaric compounds having very similar MS/MS fragments or compounds having poor fragmentation pattern.

Steps of the sample treatment workflow.

Fig. 1. Steps of the sample treatment workflow.

 

References

  1. Thieme D., Hemmersbach P. Doping in Sports. In Handbook of Experimental Pharmacology (Eds.) Springer, Berlin, 2009.

  2. World Anti-Doping Agency (WADA). The World Anti-Doping Code, The 2010 Prohibited List. WADA: Montreal, 2010. See also: www.wada-ama.org (last accessed 5 April 2011).

  3. L. Hintikka, T. Kuuranne, A. Leinonen, M. Thevis, W. Schanzer, J. Halket, D. Cowan, J. Grosse, P. Hemmersbach, M. W. F. Nielen, R. Kostiainen, Journal of Mass Spectrometry 43 (2008) 965.

  4. M.W.F. Nielen, T.F.H. Bovee, M.C. van Engelen, P. Rutgers, A.R.M. Hamers, I.H.A. van Rhijn, L. Hoogenboom, Analytical Chemistry 78 (2006) 424.

  5. G. Vogel, Science 305 (2004) 632.

  6. World Anti-Doping Agency (WADA). Adverse Analytical Findings Reported by Accredited Laboratories. WADA: Montreal, 2010. See also: www.wada-ama.org (last accessed 5 April 2011).

  7. C. Jimenez, R. Ventura, J. Segura, Journal of Chromatography B-Analytical Technologies in the Biomedical and Life Sciences 767 (2002) 341.

  8. O.J. Pozo, P. Van Eenoo, K. Deventer, F.T. Delbeke, Trac-Trends in Analytical Chemistry 27 (2008) 657.

  9. M. Saugy, C. Cardis, N. Robinson, C. Schweizer, Best Practice & Research Clinical Endocrinology & Metabolism 14 (2000) 111.

  10. W. Schanzer, M. Donike, Analytica Chimica Acta 275 (1993) 23.

  11. F. Botre, Journal of Mass Spectrometry 43 (2008) 903.

  12. P. Hatsis, S. Brombacher, J. Corr, P. Kovarik, D.A. Volmer, Rapid Communications in Mass Spectrometry 17 (2003) 2303.

  13. M.A. Khan, Y.Q. Wang, S. Heidelberger, G. Alvelius, S.Y. Liu, J. Sjovall, W.J. Griffiths, Steroids 71 (2006) 42.

  14. W.J. Griffiths, S. Liu, G. Alvelius, J. Sjovall, Rapid Communications in Mass Spectrometry 17 (2003) 924.

  15. L.J. Soltzberg, P. Patel, Rapid Communications in Mass Spectrometry 18 (2004) 1455.

  16. C.S. Pan, S.Y. Xu, L.G. Hu, X.Y. Su, J.J. Ou, H.F. Zou, Z. Guo, Y. Zhang, B.C. Guo, Journal of the American Society for Mass Spectrometry 16 (2005) 883.