 |
| |||||
 | ||||||
| ||||||||
|
| ||||||||
|
Home  Publications |
|
|
Note to the Reader A short report of a symposium at the 2001 IBANGS meeting.
Print Friendly The molecular traces of memories are subtle and the successful hunt for
these ghosts in the machine requires experimental finesse, tenacity, and
effective models (Mayford and Kandel (1999). The 2001 San Diego IBANGS
meeting opened with presentations by Mark Mayford (Scripps Research
Institute) and Josh Dubnau (Cold Spring Harbor) on the potential of
harnessing microarrays to reveal the molecular footprints of long term
memory. Dr. Mayford’s presentation (Microarrays, mutants and memory)
highlighted a number of the technical and conceptual hurdles that need to be
leapt over, or sidestepped, to define the set of genes whose expression is
modulated during learning. Dr. Dubnau’s presentation (“Functional genomics
of memory in Drosophila") evoked yet more fly envy among most mammals in the
audience and affirmed the statistical maxim of strength in numbers. The key technical issue can be crudely rephrased as questions about the
size and location of an engram. Is memory distributed or focal? Does long
term memory involve limited populations of cells and synpases—the sparse
encoding model—or does memory have a bulk cellular and synaptic impact that
can be detected by a transcriptome analysis of many thousands of neurons? If
laying down a new memory involves tweaking a few spines and synpases then
the typical “A versus B” whole tissue comparisons (chunks of amygdala/hippocampus
or the whole fly head in Drs. Mayford’s and Dubnau’s cases, respectively)
may be frustrating and unfruitful. RNA profiling would need to achieve
quantal levels of resolution and extraordinarily high signal-to-noise (S:N)
ratios. The Affymetrix microarrays used by both Drs. Mayford and Dubnau are
sensitive down to sub picomolar concentrations—five to ten transcripts per
cell—but data generated by single arrays are noisy, and detecting modulation
of low abundance transcripts requires a large population of responsive cells
and a large number of arrays. S:N ratios are a function of the square root
of N, and in those cases in which N is a $500 microarray one needs
conviction, deep pockets (with thanks to Helicon and GNF), and statistical
savvy to highlight the right set of genes. The lingering question is whether
strength in numbers will be sufficient to detect and read the engram’s
molecular signature. Dr. Mayford’s array experiments started with a well-designed fear
conditioning paradigm intended to trigger changes primarily in the
amygdalaor hippocampus. The experiments exploited four treatment groups— 1.
paired-Pavlovian tone and shock, 2. semi-random unpaired tone and shock, 3.
tone without shock, 4. handling control). This design enabled Mayford and
colleagues to dissociate stress, electrical shock, and conditioning to the
cue and its context (a box) at the transcript level. The scientific
hypothesis driving this research is that the transfer of a memory from short
term to long term memory involves gene transcription triggered by a CREB/calmodulin
binding protein-dependent pathway and a burst in nuclear calcium ion
concentration. The microarrays were run at least three times per treatment
using samples from lateral amygdala and hippocampus. The mildest treatment
(handling alone) is apparently sufficiently stressful to mice to modulate
gene expression in the amygdala. Surprisingly, the addition of a highly
aversive foot shock did not modulate gene expression any more than simple
handling. While 21 genes were nominated by the Pavlovian conditioning
paradigm using the criteria described by Sandberg and colleagues (2000,
>1.8X change in 3 of 4 arrays), unfortunately none of these candidates
survived a stringent secondary screen. The apparent lack of a significant
response may be due to sparse encoding of memory combined with still the low
S:N ratio of first generation microarray data generated using small numbers
of mice (~4 inbred mice per group). Dr. Josh Dubnau, an investigator working with Dr. Tim Tully at Cold
Spring Harbor Laboratory, provided a note of optimism. Thousands of flies
were taught simple odor discrimination tricks (motivated by shock) that
involve CREB-dependent cellular and synaptic changes in the mushroom body (Dubnau
et al., 2001). Pools of message extracted from ~1000 flash-frozen heads of
trained and untrained flies were hybridized to Affymetrix arrays that
measure ~1500 transcripts—10% of the fly genome. Realizing the high noise
level of single array data sets, Dubnau, Tully, and colleagues pooled data
from ten arrays per group; a tactic that allowed them to use conventional
parametric statistics to search for differences. An appreciable number of
transcripts (~176) were nominated in this process. A spot check of 21 of
these genes by quantitative PCR confirmed about ~30%. (Two learning
mutants—amnesiac and nalyot—were run in parallel studies to highlight known
and new memory-associated molecules.) Just over ten of the nominees
contained CRE promoter sites consistent with a role of CREB in the memory
consolidation process. Milord and approximately half of genes in the
extended milord network were highlighted by the analysis. Milord itself is
expressed in the mushroom bodies and calyces, a finding that makes sense
functionally and anatomically for an olfactory learning task. The power of
an array analysis of 1000 heads and 10 arrays is clearly sufficient to
generate highly informative lists of strong candidates involved in memory
consolidation. The hope among many of us is that there will be sufficient
conservation of memory networks that we will be able to carry out
comparisons of these same molecules and pathway in rodent models of learning
and memory. Mayford M, Kandel ER (1999) Genetic approaches to memory storage. Trends
Genet 15:463-70. Sandberg R, Yasuda R, Pankratz DG, Carter TA, Del Rio JA, Wodicka L,
Mayford M, Lockhart DJ, Barlow C (2000) Regional and strain-specific gene
expression mapping in the adult mouse brain. Proc Natl Acad Sci USA
97:11038-43. Dubnau J, Grady L, Kitamoto T, Tully T (2001) Disruption of
neurotransmission in mushroom body blocks retrieval but not acquisition of
memory. Nature 411:476-80
|
Neurogenetics at University of Tennessee Health Science Center
| Print Friendly | Top of Page |
Mouse Brain Library | Related Sites | Complextrait.org
