Integrated Calendar

In animals, all microRNAs have potentially hundreds of targets, yet in all studied cases the phenotype associated with a particular miRNA is due to very few of its targets. In this talk I'll discuss this apparent contradiction and the approaches we take to resolve it.

In response to external stimuli, cells adjust their behavior to a changing environment – for example, they start to divide or migrate. In order to perform these actions, the protein content of the cell must change. To accomplish this, a cell must modify the levels at which the genes that code for these proteins are transcribed. These transcriptional responses to extracellular stimuli are regulated by tuning the rates of transcript production and degradation. I present here the results of a study aimed at deducing the dynamics of these two processes from measurements of the transcriptome, and to elucidate the operational strategy behind this dynamics.

By combining a simple theoretical model of transcription with simultaneous measurements of time-dependent precursor mRNA and mature mRNA abundances, we were able to infer unexpected complex stimulation-induced time-dependent transcript production and degradation. In particular, we found that production of many transcripts was characterized by a large dynamic range, which allowed these genes to exhibit an unexpectedly strong transient “production overshoot”, thereby accelerating their induction. Surprisingly, we found that the widely used assumption of close correspondence between mRNA abundance and production profiles is incorrect: timing of mRNA maxima does not allow inference of the production pulse. Finally, we discovered that mRNA degradation is regulated in a precisely timed and transcript specific manner.

The results were obtained on human mammary epithelial cells stimulated by EGF, exploring a signaling pathway that plays a central role in many cancers (work done in the Y. Yarden lab), and reconfirmed for murine dendritic cells exposed to LPS (done in the S. Jung lab) and for human embryonic stem cells responding to Retinoic Acid (done in the Y. Soen lab).

The question I will address in the lecture is how information is retrieved from memory when there are no precise item-specific cues. Real life examples are when you try to recall the names of your class-mates, or your favorite writers, or places to see in Rome. I hypothesize that in this situation, retrieval occurs in an associative manner, i.e. each recalled item is triggering the retrieval of a subsequent one. Mathematically this problem can be reduced to random graphs, and general results about the retrieval capacity of the recall can be derived. The main conclusion of the analysis is that retrieval capacity is severely limited, such that only a small fraction of items can be recalled, with characteristic power-law scaling with the total number of items in memory. Theoretical results can be compared to free recall experiments and surprisingly good agreement is observed