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

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).

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.