Intermittent fasting enhances long-term memory consolidation, adult hippocampal neurogenesis and expression of longevity gene Klotho (Microarray dataset)

ABSTRACT Daily calorie restriction (CR) and intermittent fasting (IF) enhance longevity and cognition but the effects and mechanisms that differentiate these two paradigms are unknown. We examined whether IF in the form of every-other-day feeding enhances cognition and adult hippocampal neurogenesis (AHN) when compared to a matched 10% daily-CR intake and ad libitum conditions. After three months under IF, female C57BL6 mice exhibited improved long-term memory retention. IF increased the number of BrdU-labeled cells and neuroblasts in the hippocampus, and microarray analysis revealed that the longevity gene Klotho (Kl) was upregulated in the hippocampus by IF only. Furthermore, we found that down-regulating Kl in human hippocampal progenitor cells led to decreased neurogenesis whereas Kl overexpression increased neurogenesis. Finally, histological analysis of Kl knockout mice brains revealed that Kl is required for AHN, particularly in the dorsal hippocampus. These data suggest that IF is superior to 10% CR in enhancing memory and identifies Kl as a novel candidate molecule that regulates the effects of IF on cognition likely via AHN enhancement. GeneChip analysis<br>A list of genes that could be involved in the modulation of AHN was obtained using Affymetrix GeneChip technology. Briefly, genes were chosen on the basis of 1) most pronounced fold change in expression in the CR-and IF-fed groups relative to the AL control population, 2) the highest number of methods in which they appeared, and 3)background research carried out on potential genes, which included using PubMed for verifying their function in the central nervous system, as well as examining their in situ hybridization expression patterns using the Allen Brain Atlas (www.brainatlas.org) to confirm whether they were expressed in the dentate gyrus (DG). For each of the three dietary groups, the total RNA from three different mice was independently extracted from the whole hippocampi. The mRNA of each mouse was amplified, labelled and hybridized on Affymetrix GeneChip Mouse Genome 430 2.0 Arrays. The nine chips (three per each dietary group) were analyzed using four different complementary analytical tools and the levels of gene expression were compared between all three dietary groups. The remaining RNA was stored and used for quantitative RT-PCR to validate genes of interest. Briefly, the data were pre-processed using the Affymetrix Microarray Analysis Suite (MAS) and subsequently four analytical methods were used to analyze the GeneChip data: RMA (8, 9) and dChip (10), which both give an estimation of expression level and fold change, and the ‘PM-MM’ and ‘PM-only’ versions of the Drop Method (11), which return a confidence that there was a difference in expression, independent of magnitude. Relatively loose criteria were initially used to filter the data (to minimize analytical false negatives), but genes were required to pass these criteria for each of the four methods to be considered further (four out of four methods) to minimize analytical false positives. A fold change of 1.2 along with a t-test p-value of less than 0.05 was used in RMA and dChip, and a confidence of 50% or higher was used in the Drop Method. Most of the genes returned as candidates had fold changes and confidence values well above these thresholds. The use of loose criteria over multiple methods also allowed genes that met criteria in some but not all of the methods (i.e., three of four methods) to be reviewed with the understanding that they were more likely to be false positives. The combination of these methods has been shown to reduce both false positives and false negatives (11, 12). <br> 8. Irizarry RA, Bolstad BM, Collin F, Cope LM, Hobbs B, Speed TP. Summaries of Affymetrix GeneChip probe level data. Nucleic Acids Res. 2003;31(4):e15. 9. Tusher VG, Tibshirani R, Chu G. Significance analysis of microarrays applied to the ionizing radiation response. Proc Natl Acad Sci U S A. 2001;98(9):5116-21. 10. Li C, Hung Wong W. Model-based analysis of oligonucleotide arrays: model validation, design issues and standard error application. Genome Biol. 2001;2(8):RESEARCH0032. 11. Aimone JB, Gage FH. Unbiased characterization of high-density oligonucleotide microarrays using probe-level statistics. J Neurosci Methods. 2004;135(1-2):27-33.<br>