understanding of mycobacterial physiology (recently reviewed in
Refs. 2, 3). Top-down proteomics refer to the analysis of intact
proteins to gain insight into the range of protein variation, including posttranslational modifications (PTMs) and isoforms. For
instance, in M. tuberculosis top-down proteomics have been used
to characterize the heterogeneous and extensive glycosylation of
the 19 kDa antigen, LpqH [4]. Finally, targeted proteomics refers
to the selected detection and quantification of a subset of predefined proteins. Given its increased sensitivity, targeted proteomics
(e.g., multiple reaction monitoring, MRM) has successfully been
used in biomarker discovery studies to detect M. tuberculosis proteins in serum extracellular vesicles of TB patients [5–7]. Sample
processing for both shotgun and targeted proteomics requires the
enzymatic digestion of a protein sample, followed by desalting and
concentration of the resulting peptide mixture. In contrast, sample
processing of proteins for top-down proteomics does not involve
any enzymatic digestion, and protein mixtures are prefractionated,
followed by injection either via online liquid chromatography or
direct injection into the mass spectrometer. In this chapter, we
provide protocols for sample processing for all three types of proteomic analyses so that the final product aligns with the requirements for most commonly used mass spectrometers (Fig. 1). For
this reason, we will limit our sample processing for top-down
proteomics to that used for direct injection into the mass spectrometer. Please refer to the recent methods review by Donnelly et al. for
a comprehensive protocol resource for top down proteomics sample processing methods [8]. Data analysis of the resultant spectra is
dependent on both the type of mass spectrometer used and preferred or available software pipelines for each specific laboratory;
accordingly, specific data analysis protocols are out of the scope of
this chapter. Rather, we would like to bring the reader’s attention to
some important aspects of data analysis that need to be taken into
consideration regardless of instrument type and bioinformatic
pipeline.
The proteomics community through the Proteomics Standards
Initiative from the Human Proteome Organization has established
the Minimum Information about a Proteomics Experiment
(MIAPE), including Mass Spectrometry Informatics (MIAPEMSI) and Mass Spectrometry Quantification (MIAPE-Quant)
guidelines, which, as the name indicates, details the minimum
information that should be provided when publishing proteomics
experiments so that study design rigor, quality of mass spectra, and
results from mass spectra data can be independently and reproducibly assessed [9–13]. Additional information about MIAPE can be
found at www.psidev.info/miape.
Proteomics analysis is commonly used to compare samples, for
example, our efforts compare clinical samples isolated from the
same patient before and during drug treatment for tuberculosis
534
Carolina Mehaffy et al.
Refs. 2, 3). Top-down proteomics refer to the analysis of intact
proteins to gain insight into the range of protein variation, including posttranslational modifications (PTMs) and isoforms. For
instance, in M. tuberculosis top-down proteomics have been used
to characterize the heterogeneous and extensive glycosylation of
the 19 kDa antigen, LpqH [4]. Finally, targeted proteomics refers
to the selected detection and quantification of a subset of predefined proteins. Given its increased sensitivity, targeted proteomics
(e.g., multiple reaction monitoring, MRM) has successfully been
used in biomarker discovery studies to detect M. tuberculosis proteins in serum extracellular vesicles of TB patients [5–7]. Sample
processing for both shotgun and targeted proteomics requires the
enzymatic digestion of a protein sample, followed by desalting and
concentration of the resulting peptide mixture. In contrast, sample
processing of proteins for top-down proteomics does not involve
any enzymatic digestion, and protein mixtures are prefractionated,
followed by injection either via online liquid chromatography or
direct injection into the mass spectrometer. In this chapter, we
provide protocols for sample processing for all three types of proteomic analyses so that the final product aligns with the requirements for most commonly used mass spectrometers (Fig. 1). For
this reason, we will limit our sample processing for top-down
proteomics to that used for direct injection into the mass spectrometer. Please refer to the recent methods review by Donnelly et al. for
a comprehensive protocol resource for top down proteomics sample processing methods [8]. Data analysis of the resultant spectra is
dependent on both the type of mass spectrometer used and preferred or available software pipelines for each specific laboratory;
accordingly, specific data analysis protocols are out of the scope of
this chapter. Rather, we would like to bring the reader’s attention to
some important aspects of data analysis that need to be taken into
consideration regardless of instrument type and bioinformatic
pipeline.
The proteomics community through the Proteomics Standards
Initiative from the Human Proteome Organization has established
the Minimum Information about a Proteomics Experiment
(MIAPE), including Mass Spectrometry Informatics (MIAPEMSI) and Mass Spectrometry Quantification (MIAPE-Quant)
guidelines, which, as the name indicates, details the minimum
information that should be provided when publishing proteomics
experiments so that study design rigor, quality of mass spectra, and
results from mass spectra data can be independently and reproducibly assessed [9–13]. Additional information about MIAPE can be
found at www.psidev.info/miape.
Proteomics analysis is commonly used to compare samples, for
example, our efforts compare clinical samples isolated from the
same patient before and during drug treatment for tuberculosis
534
Carolina Mehaffy et al.