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SILAC (Stable Isotope Labeling
by Amino acids in Cell culture) |
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While an inventory of
proteins in an organelle is important to understand
its function, major functional insights are also likely
to emerge from understanding how its protein composition
changes over time in response to either metabolic stimuli
or other cellular signals. We have therefore developed
a quantitative proteomics method, based on Stable Isotope
Labeling by Amino acids in Cell culture (SILAC) 1,2, to
study organelle dynamics (e.g. to characterize the response
of the nucleolar proteome to transcription inhibition).
| Three populations of
a HeLa cell line can be metabolically labeled
with either normal arginine (12C6-Arg,
also referred to as Arg0), carbon substituted
arginine (13C6-Arg, also
referred to as Arg6) or carbon plus nitrogen substituted
arginine (13C615N4-Arg,
also referred to as Arg10) respectively, for at
least five cell doublings. This ‘triple
encoding’ procedure allows three cell states
to be measured in one experiment 3.
The cells are identical in all respects except
that peptides derived after proteolytic digestions
of the proteins can be distinguished in the mass
spectrometer by their offsets of either zero,
six or ten mass units. |
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1. S. E. Ong et
al., Mol Cell Proteomics 1, 376-86. (2002).
2. S. E. Ong, I. Kratchmarova, M. Mann, J Proteome Res
2, 173-81 (2003).
3. B. Blagoev, S. E. Ong, I. Kratchmarova, M. Mann,
Nature Biotech, accepted for publication (2004).
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Follow this link
for a step-by-step description of the SILAC approach
(Flash player required). |
This diagram outlines
the design of a typical SILAC experiment. In
this case the substituted arginine media is
used to distinguish different time points in
an assay of nucleoli purified from cells treated
with actinomycin D to inhibit transcription.
The analysis is repeated with a common zero
point and additional time points of transcription
inhibition to achieve higher time resolution.
For more information about this experimental
approach, visit the SILAC
page at the Center for Experimental Bioinformatics
website (Odense, Denmark). |
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