3. Inject 10–20 μg of the lipid extract of interest resuspended in
10–20 μL of chloroform:methanol 1:1 (v:v) or solvent A (see
Note 13). If needed, centrifuge samples at 2000 Â g for 5 min
to remove potential insoluble residues before injection.
4. If semi-quantitative comparative analysis is the goal, determine
the quantity of lipid extract to be injected for a linear response
of the different lipid families to be screened and compared (see
Note 16):
(a) Inject a range from 0 to 20 μg of reference lipid extract.
(b) Extract ion chromatograms for each lipid of interest and
integrate area under the chromatograms.
(c) Plot the curve of chromatogram area versus injected quantity of sample for the different lipid families of interest.
(d) Determine the injection quantity range over which the
majority of lipids show a linear response.
3.3 Targeted
Screening
and Comparative
Analysis
3.3.1 Semi-automated
Screening of Mycobacterial
Lipid Families
Once the map of detected lipids is established, routine screening of
these families can be undertaken. For a moderate number of analyses, one of the easiest ways is to use the data acquisition and
visualization software associated with the spectrometer and to
extract the ion chromatograms at the expected m/z for representative or all acyl-forms of the lipid families (see Note 14), with a
tolerance within the mass spectrometer mass accuracy
(1–10 ppm). It is often possible to preregister a list of m/z for
the simultaneous extraction of the ion chromatograms of all the
lipids of interest.
3.3.2 Automated Lipid
Annotation
For a large number of samples such as biological fluids from patient
cohorts or a mycobacteria library, it can be envisaged to set up a
bioinformatic workflow for the extraction of all the chromatograms
of the generated datasets using an appropriate peak picking algorithm and/or to carry out an automatic annotation with software
integrating the available databases, MycoMass [12] or Mtb
LipidDB [30] (see Table 2 and Note 17), such as the MS-LAMP
software [33].
Several lipidomic data processing software packages have been
developed for filtering, peak picking, and peak integration and
alignment, such as the online XCMS platform (https://
xcmsonline.scripps.edu) [34], MZmine 2, [35] or MS-DIAL
[36]. Each requires converting the raw MS files in mzXML format,
which can be performed either with the data export module of the
mass spectrometer data acquisition software (such as Agilent MassHunter) or using msConvert ProteoWizard [37, 38]. Processed
data can then be exported toward data annotation software.
568
Emilie Layre
10–20 μL of chloroform:methanol 1:1 (v:v) or solvent A (see
Note 13). If needed, centrifuge samples at 2000 Â g for 5 min
to remove potential insoluble residues before injection.
4. If semi-quantitative comparative analysis is the goal, determine
the quantity of lipid extract to be injected for a linear response
of the different lipid families to be screened and compared (see
Note 16):
(a) Inject a range from 0 to 20 μg of reference lipid extract.
(b) Extract ion chromatograms for each lipid of interest and
integrate area under the chromatograms.
(c) Plot the curve of chromatogram area versus injected quantity of sample for the different lipid families of interest.
(d) Determine the injection quantity range over which the
majority of lipids show a linear response.
3.3 Targeted
Screening
and Comparative
Analysis
3.3.1 Semi-automated
Screening of Mycobacterial
Lipid Families
Once the map of detected lipids is established, routine screening of
these families can be undertaken. For a moderate number of analyses, one of the easiest ways is to use the data acquisition and
visualization software associated with the spectrometer and to
extract the ion chromatograms at the expected m/z for representative or all acyl-forms of the lipid families (see Note 14), with a
tolerance within the mass spectrometer mass accuracy
(1–10 ppm). It is often possible to preregister a list of m/z for
the simultaneous extraction of the ion chromatograms of all the
lipids of interest.
3.3.2 Automated Lipid
Annotation
For a large number of samples such as biological fluids from patient
cohorts or a mycobacteria library, it can be envisaged to set up a
bioinformatic workflow for the extraction of all the chromatograms
of the generated datasets using an appropriate peak picking algorithm and/or to carry out an automatic annotation with software
integrating the available databases, MycoMass [12] or Mtb
LipidDB [30] (see Table 2 and Note 17), such as the MS-LAMP
software [33].
Several lipidomic data processing software packages have been
developed for filtering, peak picking, and peak integration and
alignment, such as the online XCMS platform (https://
xcmsonline.scripps.edu) [34], MZmine 2, [35] or MS-DIAL
[36]. Each requires converting the raw MS files in mzXML format,
which can be performed either with the data export module of the
mass spectrometer data acquisition software (such as Agilent MassHunter) or using msConvert ProteoWizard [37, 38]. Processed
data can then be exported toward data annotation software.
568
Emilie Layre