Interpreting Sherlock Mycobacteria Identification System Reports
Technical notes | 2006 | MIDIInstrumentation
Reliable identification of mycobacteria is essential for clinical diagnosis quality control and environmental monitoring. The method based on mycolic acid analysis provides species level discrimination supporting accurate therapy decisions and epidemiological studies.
This technical note explains how to interpret reports generated by the Sherlock Mycobacteria Identification System. It outlines the production of chromatographic and composition reports the library search process and result interpretation.
The system uses high performance liquid chromatography with fluorescence detection. Samples are injected into an HPLC column and separated based on mycolic acid profiles. The ChemStation software collects raw data generating chromatograms with retention times widths and peak heights. Sherlock software processes these data assigns peaks by equivalent chain length and compares the profile against a curated mycobacteria library.
Future developments may include expansion of the mycobacteria library integration with mass spectrometry based lipid profiling automation through machine learning and cloud based analytics to further improve speed and accuracy.
The Sherlock system offers a robust workflow for mycobacteria identification by combining chromatographic profiling with software assisted library matching enabling fast reliable results.
Technical Note 105 Sherlock Mycobacteria Identification System Reports MIDI Inc 2006
Software
IndustriesManufacturerMIDI
Summary
Significance of the Topic
Reliable identification of mycobacteria is essential for clinical diagnosis quality control and environmental monitoring. The method based on mycolic acid analysis provides species level discrimination supporting accurate therapy decisions and epidemiological studies.
Objectives and Study Overview
This technical note explains how to interpret reports generated by the Sherlock Mycobacteria Identification System. It outlines the production of chromatographic and composition reports the library search process and result interpretation.
Methodology and Instrumentation
The system uses high performance liquid chromatography with fluorescence detection. Samples are injected into an HPLC column and separated based on mycolic acid profiles. The ChemStation software collects raw data generating chromatograms with retention times widths and peak heights. Sherlock software processes these data assigns peaks by equivalent chain length and compares the profile against a curated mycobacteria library.
Main Results and Discussion
- Chromatographic Report provides a visual plot of fluorescence signal versus retention time and lists key peak parameters
- Composition Report details the distribution of mycolic acid components of the unknown sample
- Library Search Report identifies likely matches with similarity indices representing compositional distance
- Visual Confirmation feature overlays reference and unknown chromatograms for manual validation
Benefits and Practical Applications
- Rapid identification within minutes after HPLC run completion
- High specificity even among closely related strains
- Supports QA QC workflows in clinical and industrial laboratories
- Enables epidemiological tracking and research applications
Future Trends and Potential Applications
Future developments may include expansion of the mycobacteria library integration with mass spectrometry based lipid profiling automation through machine learning and cloud based analytics to further improve speed and accuracy.
Conclusion
The Sherlock system offers a robust workflow for mycobacteria identification by combining chromatographic profiling with software assisted library matching enabling fast reliable results.
Reference
Technical Note 105 Sherlock Mycobacteria Identification System Reports MIDI Inc 2006
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