TY - JOUR T1 - Serial Analysis of Gene Expression Identifies Metallothionein-II as Major Neuroprotective Gene in Mouse Focal Cerebral Ischemia JF - The Journal of Neuroscience JO - J. Neurosci. SP - 5879 LP - 5888 DO - 10.1523/JNEUROSCI.22-14-05879.2002 VL - 22 IS - 14 AU - George Trendelenburg AU - Konstantin Prass AU - Josef Priller AU - Krisztian Kapinya AU - Andreas Polley AU - Claudia Muselmann AU - Karsten Ruscher AU - Ute Kannbley AU - Armin O. Schmitt AU - Stefanie Castell AU - Frank Wiegand AU - Andreas Meisel AU - André Rosenthal AU - Ulrich Dirnagl Y1 - 2002/07/15 UR - http://www.jneurosci.org/content/22/14/5879.abstract N2 - We applied serial analysis of gene expression (SAGE) to study differentially expressed genes in mouse brain 14 hr after the induction of focal cerebral ischemia. Analysis of >60,000 transcripts revealed 83 upregulated and 94 downregulated transcripts (more than or equal to eightfold). Reproducibility was demonstrated by performing SAGE in duplicate on the same starting material. Metallothionein-II (MT-II) was the most significantly upregulated transcript in the ischemic hemisphere. MT-I and MT-II are assumed to be induced by metals, glucocorticoids, and inflammatory signals in a coordinated manner, yet their function remains elusive. Upregulation of both MT-I and MT-II was confirmed by Northern blotting. MT-I and MT-II mRNA expression increased as early as 2 hr after 2 hr of transient ischemia, with a maximum after 16 hr. Western blotting and immunohistochemistry revealed MT-I/-II upregulation in the ischemic hemisphere, whereas double labeling demonstrated the colocalization of MT with markers for astrocytes as well as for monocytes/macrophages. MT-I- and MT-II-deficient mice developed approximately threefold larger infarcts than wild-type mice and a significantly worse neurological outcome.For the first time we make available a comprehensive data set on brain ischemic gene expression and underscore the important protective role of metallothioneins in ischemic damage of the brain. Our results demonstrate the usefulness of SAGE to screen functionally relevant genes and the power of knock-out models in linking function to expression data generated by high throughput techniques. ER -