Spatially regulated editing of genetic information within a neuron

In eukaryotic cells, with the exception of the specialized genomes of mitochondria and plastids, all genetic information is sequestered within the nucleus. This arrangement imposes constraints on how the information can be tailored for different cellular regions, particularly in cells with complex morphologies like neurons. Although messenger RNAs (mRNAs), and the proteins that they encode, can be differentially sorted between cellular regions, the information itself does not change. RNA editing by adenosine deamination can alter the genome’s blueprint by recoding mRNAs; however, this process too is thought to be restricted to the nucleus. In this work, we show that ADAR2 (adenosine deaminase that acts on RNA), an RNA editing enzyme, is expressed outside of the nucleus in squid neurons. Furthermore, purified axoplasm exhibits adenosine-to-inosine activity and can specifically edit adenosines in a known substrate. Finally, a transcriptome-wide analysis of RNA editing reveals that tens of thousands of editing sites (>70% of all sites) are edited more extensively in the squid giant axon than in its cell bodies. These results indicate that within a neuron RNA editing can recode genetic information in a region-specific manner.

Stability Analysis of FitzHugh-Nagumo with Smooth Periodic Forcing

Alan Lloyd Hodgkin and Andrew Huxley received the 1963 Nobel Prize in Physiology for their work describing the propagation of action potentials in the squid giant axon. Major analysis of their system of differential equations was performed by Richard FitzHugh, and later by Jin-Ichi Nagumo who created a tunnel diode circuit based upon FitzHugh’s work. The resulting differential model, known as the FitzHugh-Nagumo (FH-N) oscillator, represents a simplification of the Hodgkin-Huxley (H-H) model, but still replicates the original neuronal dynamics (Izhikevich, 2010). We begin by providing a thorough grounding in the physiology behind the equations, then continue by introducing some of the results established by Kostova et al. for FH-N without forcing (Kostova et al., 2004). Finally, this sets up our own exploration into stimulating the system with smooth periodic forcing. Subsequent quantification of the chaotic phase portraits using a Lyapunov exponent are discussed, as well as the relevance of these results to electrocardiography.