Immediate‐early gene Homer1a intranuclear transcription focus intensity as a measure of relative neural activation

Abstract

Immediate‐early genes (IEGs) exhibit a rapid, transient transcription response to neuronal activation. Fluorescently labeled mRNA transcripts appear as bright intranuclear transcription foci (INF), which have been used as an all‐or‐nothing indicator of recent neuronal activity; however, it would be useful to know whether INF fluorescence can be used effectively to assess relative activations within a neural population. We quantified the Homer1a (H1a) response of hippocampal neurons to systematically varied numbers of exposures to the same places by inducing male Long‐Evans rats to run laps around a track. Previous studies reveal relatively stable firing rates across laps on a familiar track. A strong linear trend (r2 > 0.9) in INF intensity was observed between 1 and 25 laps, after which INF intensity declined as a consequence of dispersion related to the greater elapsed time. When the integrated fluorescence of the entire nucleus was considered instead, the linear relationship extended to 50 laps. However, there was only an approximate doubling of H1a detected for this 50‐fold variation in total spiking. Thus, the intranuclear H1a RNA fluorescent signal does provide a relative measure of how many times a set of neurons was activated over a ~10 min period, but the dynamic range and hence signal‐to‐noise ratios are poor. This low dynamic range may reflect previously reported reductions in the IEG response during repeated episodes of behavior over longer time scales. It remains to be determined how well the H1a signal reflects relative firing rates within a population of neurons in response to a single, discrete behavioral event.

Behavioral and Cellular Tagging in Young and in Early Cognitive Aging

“…The volume of H1a and the Arc mRNA signal in foci have previously shown to reflect synaptic maturation ( Montes-Rodríguez et al, 2013 ) and the relative firing rates within a population of neurons in response to a behavioral event ( Miyashita et al, 2009 ; Witharana et al, 2018 ). To visualize if the memory events in epoch 1 or in epoch 2 would increase the IEG expression, the fluorescent signals in the nuclei were quantified ( Figure 7 ).…”

“…The size and the intensity of H1a foci signal detection by FISH reflect the amount of mRNA present in single neurons ( Montes-Rodríguez et al, 2013 ) and that these can change with behavioral experience ( Witharana et al, 2018 ). In our study, the exploration of a novel environment increases the proportion of Arc + neurons, as well as larger Arc + volumes in CA1.…”

Nonuniform allocation of hippocampal neurons to place fields across all hippocampal subfields

“…These data consist of subjects in the uncovered‐transport group reported in Witharana, (MSc Thesis, University of Lethbridge, Witharana, ). Naïve, male Long‐Evans ( n = 22) and Brown Norway ( n = 6) rats aged 3–7 months were divided into two test groups: one‐environment exposure (1E, n = 8), or five‐environment (5E, n = 8) exposure; and two control groups: home‐cage (HC, n = 6) or maximal electroconvulsive shock positive control (MECS, n = 6).…”

“…Study MP3 employed both methods. Since imaging settings such as laser intensity and offset parameters differed between experiments, the general acquisition protocols for studies MP1 and MP2 (Witharana, ); MP3 (Cardiff, ); CT5 (Xie, ) are previously described in the corresponding theses. Image settings for MP4 are included in Alme et al () and details for AB6 and AB7 are described in Montes‐Rodriguez et al ().…”

“…Image stacks from MP4 were reconstructed with Adobe Photoshop (Adobe Systems, San Jose, CA) to generate two‐dimensional images for reference, and then INFs were quantified manually (described in Alme et al, ). NanoZoomer images from studies MP1 and MP2, consisting of larger brain areas compared to confocal images, were analyzed by an automated H1a ‐INF detection program written in Visual Basic C++, “GreenDot,” also developed in Lethbridge (by V. Trivedi), the details of which are outlined in Witharana (). Confocal and nanozoomer images from MP3 were analyzed through automated H1a ‐INF characterization by a MatLab (The MathWorks Inc., Natick, MA) program (developed by J. Cardiff) and described in Cardiff ().…”