Note to the Reader A short report of a symposium at the 2001 IBANGS meeting.



Strength in Numbers: Chasing the Engram using Microarrays

Robert W. Williams, PhD
Center for Neuroscience
Center for Genomics and Bioinformatics
University of Tennessee, 855 Monroe Avenue, Memphis, Tennessee 38163 USA
 

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

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