Trends in high-throughput and functional neuroimaging in Caenorhabditis elegans.

The nervous system of Caenorhabditis elegans is an important model system for understanding the development and function of larger, more complex nervous systems. It is prized for its ease of handling, rapid life cycle, and stereotyped, well-cataloged development, with the development of all 302 neurons mapped all the way from zygote to adult. The combination of easy genetic manipulation and optical transparency of the worm allows for the direct imaging of its interior with fluorescent microscopy, without physically compromising the normal physiology of the animal itself. By expressing fluorescent markers, biologists study many developmental and cell biology questions in vivo; by expressing genetically encoded fluorescent calcium indicators within neurons, it is also possible to monitor their dynamic activity, answering questions about the structure and function of neural microcircuitry in the worm. However, to successfully image the worm it is necessary to overcome a number of experimental challenges. It is necessary to hold worms within the field of view, collect images efficiently and rapidly, and robustly analyze the data obtained. In recent years, a trend has developed toward imaging a large number of worms or neurons simultaneously, directly exploiting the unique properties of C. elegans to acquire data on a scale, which is not possible in other organisms. Doing this has required the development of new experimental tools, techniques, and data analytic approaches, all of which come together to open new perspectives on the field of neurobiology in C. elegans, and neuroscience in general. WIREs Syst Biol Med 2017, 9:e1376. doi: 10.1002/wsbm.1376 For further resources related to this article, please visit the WIREs website.

Behavioral relevance helps untangle natural vocal categories in a specific subset of core auditory cortical pyramidal neurons.

Sound categorization is essential for auditory behaviors like acoustic communication, but its genesis within the auditory pathway is not well understood-especially for learned natural categories like vocalizations, which often share overlapping acoustic features that must be distinguished (e.g., speech). We use electrophysiological mapping and single-unit recordings in mice to investigate how representations of natural vocal categories within core auditory cortex are modulated when one category acquires enhanced behavioral relevance. Taking advantage of a maternal mouse model of acoustic communication, we found no long-term auditory cortical map expansion to represent a behaviorally relevant pup vocalization category-contrary to expectations from the cortical plasticity literature on conditioning with pure tones. Instead, we observed plasticity that improved the separation between acoustically similar pup and adult vocalization categories among a physiologically defined subset of late-onset, putative pyramidal neurons, but not among putative interneurons. Additionally, a larger proportion of these putative pyramidal neurons in maternal animals compared with nonmaternal animals responded to the individual pup call exemplars having combinations of acoustic features most typical of that category. Together, these data suggest that higher-order representations of acoustic categories arise from a subset of core auditory cortical pyramidal neurons that become biased toward the combination of acoustic features statistically predictive of membership to a behaviorally relevant sound category.

The interaction of CRM1 and the nuclear pore protein Tpr.

While much has been devoted to the study of transport mechanisms through the nuclear pore complex (NPC), the specifics of interactions and binding between export transport receptors and the NPC periphery have remained elusive. Recent work has demonstrated a binding interaction between the exportin CRM1 and the unstructured carboxylic tail of Tpr, on the nuclear basket. Strong evidence suggests that this interaction is vital to the functions of CRM1. Using molecular dynamics simulations and a newly refined method for determining binding regions, we have identified nine candidate binding sites on CRM1 for C-Tpr. These include two adjacent to RanGTP--from which one is blocked in the absence of RanGTP--and three next to the binding region of the cargo Snurportin. We report two additional interaction sites between C-Tpr and Snurportin, suggesting a possible role for Tpr import into the nucleus. Using bioinformatics tools we have conducted conservation analysis and functional residue prediction investigations to identify which parts of the obtained binding sites are inherently more important and should be highlighted. Also, a novel measure based on the ratio of available solvent accessible surface (RASAS) is proposed for monitoring the ligand/receptor binding process.

An online bioinformatics tool predicts zinc finger and TALE nuclease off-target cleavage.

Although engineered nucleases can efficiently cleave intracellular DNA at desired target sites, major concerns remain on potential 'off-target' cleavage that may occur throughout the genome. We developed an online tool: predicted report of genome-wide nuclease off-target sites (PROGNOS) that effectively identifies off-target sites. The initial bioinformatics algorithms in PROGNOS were validated by predicting 44 of 65 previously confirmed off-target sites, and by uncovering a new off-target site for the extensively studied zinc finger nucleases (ZFNs) targeting C-C chemokine receptor type 5. Using PROGNOS, we rapidly interrogated 128 potential off-target sites for newly designed transcription activator-like effector nucleases containing either Asn-Asn (NN) or Asn-Lys (NK) repeat variable di-residues (RVDs) and 3- and 4-finger ZFNs, and validated 13 bona fide off-target sites for these nucleases by DNA sequencing. The PROGNOS algorithms were further refined by incorporating additional features of nuclease-DNA interactions and the newly confirmed off-target sites into the training set, which increased the percentage of bona fide off-target sites found within the top PROGNOS rankings. By identifying potential off-target sites in silico, PROGNOS allows the selection of more specific target sites and aids the identification of bona fide off-target sites, significantly facilitating the design of engineered nucleases for genome editing applications.