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Chapter 17 : Mycobacterial Lipidomics

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Abstract:

Genomics, transcriptomics, proteomics, and metabolomics are disciplines that broadly measure an organism's molecular repertoire to provide a portrait of that organism at an instant in time or a series of pictures to describe organism response. Working downstream from genes and enzymes, metabolites comprise the majority of the nonwater biomass of the cell. Transcriptomics and proteomics study linear polymers, so the key information is the sequence of building blocks comprised of nucleotides or amino acids. Accordingly, proteins, DNA, or RNA can be studied by applying one detection method to one general type of molecule to determine its sequence.

Citation: Layre E, Al-mubarak R, Belisle J, Moody D. 2014. Mycobacterial Lipidomics, p 341-360. In Hatfull G, Jacobs W (ed), Molecular Genetics of Mycobacteria, Second Edition. ASM Press, Washington, DC. doi: 10.1128/microbiolspec.MGM2-0033-2013

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Figure 1

Lipidomics versus metabolomics. doi:10.1128/microbiolspec.MGM2-0033-2013.f1

Citation: Layre E, Al-mubarak R, Belisle J, Moody D. 2014. Mycobacterial Lipidomics, p 341-360. In Hatfull G, Jacobs W (ed), Molecular Genetics of Mycobacteria, Second Edition. ASM Press, Washington, DC. doi: 10.1128/microbiolspec.MGM2-0033-2013
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Figure 2

LIPID MAPS classification system. doi:10.1128/microbiolspec.MGM2-0033-2013.f2

Citation: Layre E, Al-mubarak R, Belisle J, Moody D. 2014. Mycobacterial Lipidomics, p 341-360. In Hatfull G, Jacobs W (ed), Molecular Genetics of Mycobacteria, Second Edition. ASM Press, Washington, DC. doi: 10.1128/microbiolspec.MGM2-0033-2013
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Figure 3

Atypical lipids produced by . doi:10.1128/microbiolspec.MGM2-0033-2013.f3

Citation: Layre E, Al-mubarak R, Belisle J, Moody D. 2014. Mycobacterial Lipidomics, p 341-360. In Hatfull G, Jacobs W (ed), Molecular Genetics of Mycobacteria, Second Edition. ASM Press, Washington, DC. doi: 10.1128/microbiolspec.MGM2-0033-2013
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Figure 4

Comparative lipidomic analysis workflow. doi:10.1128/microbiolspec.MGM2-0033-2013.f4

Citation: Layre E, Al-mubarak R, Belisle J, Moody D. 2014. Mycobacterial Lipidomics, p 341-360. In Hatfull G, Jacobs W (ed), Molecular Genetics of Mycobacteria, Second Edition. ASM Press, Washington, DC. doi: 10.1128/microbiolspec.MGM2-0033-2013
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Figure 5

Molecular features. Comparative lipidomics relies on data sets in which thousands of molecular features from each biological condition are aligned based on mass and retention time. For aligned features, intensity ratios are reported to describe changes in abundance for each compound. Molecular features are also known as molecular events or linked accurate mass retention time intensity values. doi:10.1128/microbiolspec.MGM2-0033-2013.f5

Citation: Layre E, Al-mubarak R, Belisle J, Moody D. 2014. Mycobacterial Lipidomics, p 341-360. In Hatfull G, Jacobs W (ed), Molecular Genetics of Mycobacteria, Second Edition. ASM Press, Washington, DC. doi: 10.1128/microbiolspec.MGM2-0033-2013
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Figure 6

cell wall organization. doi:10.1128/microbiolspec.MGM2-0033-2013.f6

Citation: Layre E, Al-mubarak R, Belisle J, Moody D. 2014. Mycobacterial Lipidomics, p 341-360. In Hatfull G, Jacobs W (ed), Molecular Genetics of Mycobacteria, Second Edition. ASM Press, Washington, DC. doi: 10.1128/microbiolspec.MGM2-0033-2013
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Figure 7

Structural diversity of glycerophosphoinositolmannosides. doi:10.1128/microbiolspec.MGM2-0033-2013.f7

Citation: Layre E, Al-mubarak R, Belisle J, Moody D. 2014. Mycobacterial Lipidomics, p 341-360. In Hatfull G, Jacobs W (ed), Molecular Genetics of Mycobacteria, Second Edition. ASM Press, Washington, DC. doi: 10.1128/microbiolspec.MGM2-0033-2013
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Figure 8

produces diverse trehalose esters. doi:10.1128/microbiolspec.MGM2-0033-2013.f8

Citation: Layre E, Al-mubarak R, Belisle J, Moody D. 2014. Mycobacterial Lipidomics, p 341-360. In Hatfull G, Jacobs W (ed), Molecular Genetics of Mycobacteria, Second Edition. ASM Press, Washington, DC. doi: 10.1128/microbiolspec.MGM2-0033-2013
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Figure 9

Fine mapping of lipid molecular species gives the relative ion intensity of chain length variant within each lipid class. doi:10.1128/microbiolspec.MGM2-0033-2013.f9

Citation: Layre E, Al-mubarak R, Belisle J, Moody D. 2014. Mycobacterial Lipidomics, p 341-360. In Hatfull G, Jacobs W (ed), Molecular Genetics of Mycobacteria, Second Edition. ASM Press, Washington, DC. doi: 10.1128/microbiolspec.MGM2-0033-2013
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Tables

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Table 1

Examples of lipidomic applications for targeted studies

Citation: Layre E, Al-mubarak R, Belisle J, Moody D. 2014. Mycobacterial Lipidomics, p 341-360. In Hatfull G, Jacobs W (ed), Molecular Genetics of Mycobacteria, Second Edition. ASM Press, Washington, DC. doi: 10.1128/microbiolspec.MGM2-0033-2013

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