Jan Muntel1, Michael Hecker, Dörte Becher. 1. Institute for Microbiology, Ernst Moritz Arndt University Greifswald, Friedrich-Ludwig-Jahn-Str. 15, D-17489, Greifswald, Germany.
Abstract
RATIONALE: Label-based mass spectrometry is a powerful tool for large-scale protein identification and quantification. However, it requires the chemical or metabolic incorporation of the labeled compound(s) which can be difficult to attain, e.g. for non-cultivable organisms or scarce sample, such as biopsies. Therefore, we set out to develop and validate an efficient label-free liquid chromatography/tandem mass spectrometry (LC/MS/MS) workflow based on optimized instrument settings and incremental exclusion lists. METHODS: To increase the number of quantified peptides an incremental exclusion list was incorporated along with optimized instrument settings for the used LTQ Orbitrap. As a proof of concept, label-free quantification data from this optimized approach were compared to the results of control measurements without exclusion lists and of an in vivo metabolic labeling GeLC/MS/MS experiment. The data were drawn from Staphylococcus aureus whole cell lysates of non-stressed and nitric oxide (NO)-stressed cells. RESULTS: Compared to MS analysis without exclusion lists the new approach resulted in an increased number of identified peptides, enabling label-free quantification of more than 990 S. aureus proteins. With respect to the number of quantified proteins and differences in protein levels between the control and NO-treated samples the results of the new method were consistent with those of the GeLC/MS/MS experiment. CONCLUSIONS: The application of exclusion lists and optimized instrument settings in LC/MS/MS analysis significantly enhances the sensitivity and resolution of label-free protein identification and quantification. Therefore, the new workflow is a powerful alternative to label-based quantification methods.
RATIONALE: Label-based mass spectrometry is a powerful tool for large-scale protein identification and quantification. However, it requires the chemical or metabolic incorporation of the labeled compound(s) which can be difficult to attain, e.g. for non-cultivable organisms or scarce sample, such as biopsies. Therefore, we set out to develop and validate an efficient label-free liquid chromatography/tandem mass spectrometry (LC/MS/MS) workflow based on optimized instrument settings and incremental exclusion lists. METHODS: To increase the number of quantified peptides an incremental exclusion list was incorporated along with optimized instrument settings for the used LTQ Orbitrap. As a proof of concept, label-free quantification data from this optimized approach were compared to the results of control measurements without exclusion lists and of an in vivo metabolic labeling GeLC/MS/MS experiment. The data were drawn from Staphylococcus aureus whole cell lysates of non-stressed and nitric oxide (NO)-stressed cells. RESULTS: Compared to MS analysis without exclusion lists the new approach resulted in an increased number of identified peptides, enabling label-free quantification of more than 990 S. aureus proteins. With respect to the number of quantified proteins and differences in protein levels between the control and NO-treated samples the results of the new method were consistent with those of the GeLC/MS/MS experiment. CONCLUSIONS: The application of exclusion lists and optimized instrument settings in LC/MS/MS analysis significantly enhances the sensitivity and resolution of label-free protein identification and quantification. Therefore, the new workflow is a powerful alternative to label-based quantification methods.
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