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Novelty detection is a fundamental biological problem that organisms must solve to determine whether a given stimulus departs from those previously experienced. In computer science, this problem is solved efficiently using a data structure called a Bloom filter. We found that the fruit fly olfactory circuit evolved a variant of a Bloom filter to assess the novelty of odors. Compared with a traditional Bloom filter, the fly adjusts novelty responses based on two additional features: the similarity of an odor to previously experienced odors and the time elapsed since the odor was last experienced. We elaborate and validate a framework to predict novelty responses of fruit flies to given pairs of odors. We also translate insights from the fly circuit to develop a class of distance- and time-sensitive Bloom filters that outperform prior filters when evaluated on several biological and computational datasets. Overall, our work illuminates the algorithmic basis of an important neurobiological problem and offers strategies for novelty detection in computational systems.

Nuclear export of mRNA is a key transport process in eukaryotic cells. To investigate it, we labeled native mRNP particles in living Chironomus tentans salivary gland cells with fluorescent hrp36, the hnRNP A1 homolog, and the nuclear envelope by fluorescent NTF2. Using light sheet microscopy, we traced single native mRNA particles across the nuclear envelope. The particles were observed to often probe nuclear pore complexes (NPC) at their nuclear face, and in only 25% of the cases yielded actual export. The complete export process took between 65 ms up to several seconds. A rate-limiting step was observed, which could be assigned to the nuclear basket of the pore and might correspond to a repositioning and unfolding of mRNPs before the actual translocation. Analysis of single fluorescent Dbp5 molecules, the RNA helicase essential for mRNA export, revealed that Dbp5 most often approached the cytoplasmic face of the NPC, and exhibited a binding duration of approximately 55 ms. Our results have allowed a refinement of the current models for mRNA export.

Determining how cells distinguish between adaptive and maladaptive signals when they appear to share the same molecular pathways has been a vexing biological problem. The ability to identify distinctive features of a pathophysiological response compared with a physiological response would allow for the rational design of approaches to eliminate or diminish undesirable consequences of pathophysiological responses while preserving the beneficial effects of physiological signals. These issues are especially pertinent in the heart and in understanding the development of heart failure, for which >500,000 new cases are diagnosed in the United States each year. Major factors contributing to worsening heart failure include a number of compensatory neurohormonal signals intended to counteract decreased cardiac output, such as hyperadrenergic stimulation (1). In a recent issue of PNAS, Balijepalli et al. (2) provide new insight into how adrenergic signaling pathways are organized in the heart.