Biomedical Engineering Reference
In-Depth Information
Here, the researchers observed the effects induced at the transcriptional level by
rapamycin, a known immunosuppressant drug used to prevent rejection in organ
transplantation. Thanks to a comparison of the transcriptional profile induced by
the rapamycin treatment with that representing the metabolic response profile to
diauxic shift [80], the mechanism of resistance to the toxic agent was identified. In
particular, they showed how rapamycin inhibits Tor1p and Tor2p, ultimately result-
ing in cellular responses characteristic of nutrient deprivation through a mechanism
involving translational arrest. This suggested that Tor proteins modulate directly
the glucose activation and nitrogen discrimination pathways and the pathways that
respond to the diauxic shift (glycolysis and the citric acid cycle). Similarly impor-
tant was the contribution given by this approach to the assessment of the mode
of action of alkylating agents (e.g., methyl methanesulfonate) [83]. Treatment with
an alkylating agent yields dramatic changes in the expression of genes involved
in DNA repair and identified many genes not previously associated with DNA
repair processes. Responsive genes fall into several expected classes, such as stress
response/detoxification, DNA repair/replication, cell cycle, signal transduction, cell
wall biogenesis, and membrane transport, and many unexpected categories, such as
nitrogen and sulfur metabolism, carbohydrate metabolism/fermentation, and
m
RNA
processing. The same authors produced evidence for a cell program designed to elimi-
nate and replace alkylated proteins. Actually, proteins are known substrates for methyl
methanesulfonate alkylation. The fact that genes involved in protein degradation are
up-regulated in response to methyl methanesulfonate suggested that alkylated pro-
teins may be targeted for degradation and that their elimination may be important for
cellular recovery.
As for the identification of patterns responsive to chemical perturbation, genome-
wide gene expression patterns have been used to validate drug targets and to identify
secondary drug targets [32,84]. Marton et al. [84] used DNA microarrays to compare
genome-wide gene expression patterns in wild-type and mutant yeast cells to identify
primary drug targets as well as the secondary cellular consequences of drug exposure.
The logic behind the Marton et al. study is that the cellular consequences of genetic
and pharmacological inhibition should be very similar; that is, removing the gene
from the genome and chemically inhibiting the activity of the protein product of that
gene should be functionally equivalent. Thus, by comparing chemically induced gene
expression profiles of wild-type yeast with the profiles of many genetic deletion strains
should allow for identification of the primary target of the drug. The method has been
validated by treating yeast mutant strains defective in calcineurin, immunophilins, or
other genes with the immunosuppressants cyclosporin A or FK506. The presence or
absence of the characteristic drug “signature” pattern of altered gene expression in
drug-treated cells with a mutation in the gene encoding a putative target established
whether or not that target was required to generate the drug signature. By analyzing
multidrug resistance yeast mutants (
PDR1-3
and/or
PDR3-7
) with DNAmicroarrays,
De Risi et al. identified all target genes that appeared to be involved in transport or in
membrane lipids and cell wall biosynthesis [32]. Several targets seem to contribute
to protect the cell from a variety of stresses. This work illustrated the coordinated
use of genome-based and biochemical approaches to delineate a cellular pathway
