Purification of neural precursor cells reveals the presence of distinct, stimulus-specific subpopulations of quiescent precursors in the adult mouse hippocampus.

The activity of neural precursor cells in the adult hippocampus is regulated by various stimuli; however, whether these stimuli regulate the same or different precursor populations remains unknown. Here, we developed a novel cell-sorting protocol that allows the purification to homogeneity of neurosphere-forming neural precursors from the adult mouse hippocampus and examined the responsiveness of individual precursors to various stimuli using a clonal assay. We show that within the Hes5-GFP(+)/Nestin-GFP(+)/EGFR(+) cell population, which comprises the majority of neurosphere-forming precursors, there are two distinct subpopulations of quiescent precursor cells, one directly activated by high-KCl depolarization, and the other activated by norepinephrine (NE). We then demonstrate that these two populations are differentially distributed along the septotemporal axis of the hippocampus, and show that the NE-responsive precursors are selectively regulated by GABA, whereas the KCl-responsive precursors are selectively modulated by corticosterone. Finally, based on RNAseq analysis by deep sequencing, we show that the progeny generated by activating NE-responsive versus KCl-responsive quiescent precursors are molecularly different. These results demonstrate that the adult hippocampus contains phenotypically similar but stimulus-specific populations of quiescent precursors, which may give rise to neural progeny with different functional capacity.

Immature doublecortin-positive hippocampal neurons are important for learning but not for remembering.

It is now widely accepted that hippocampal neurogenesis underpins critical cognitive functions, such as learning and memory. To assess the behavioral importance of adult-born neurons, we developed a novel knock-in mouse model that allowed us to specifically and reversibly ablate hippocampal neurons at an immature stage. In these mice, the diphtheria toxin receptor (DTR) is expressed under control of the doublecortin (DCX) promoter, which allows for specific ablation of immature DCX-expressing neurons after administration of diphtheria toxin while leaving the neural precursor pool intact. Using a spatially challenging behavioral test (a modified version of the active place avoidance test), we present direct evidence that immature DCX-expressing neurons are required for successful acquisition of spatial learning, as well as reversal learning, but are not necessary for the retrieval of stored long-term memories. Importantly, the observed learning deficits were rescued as newly generated immature neurons repopulated the granule cell layer upon termination of the toxin treatment. Repeat (or cyclic) depletion of immature neurons reinstated behavioral deficits if the mice were challenged with a novel task. Together, these findings highlight the potential of stimulating neurogenesis as a means to enhance learning.

A comparative study of techniques for differential expression analysis on RNA-Seq data.

Recent advances in next-generation sequencing technology allow high-throughput cDNA sequencing (RNA-Seq) to be widely applied in transcriptomic studies, in particular for detecting differentially expressed genes between groups. Many software packages have been developed for the identification of differentially expressed genes (DEGs) between treatment groups based on RNA-Seq data. However, there is a lack of consensus on how to approach an optimal study design and choice of suitable software for the analysis. In this comparative study we evaluate the performance of three of the most frequently used software tools: Cufflinks-Cuffdiff2, DESeq and edgeR. A number of important parameters of RNA-Seq technology were taken into consideration, including the number of replicates, sequencing depth, and balanced vs. unbalanced sequencing depth within and between groups. We benchmarked results relative to sets of DEGs identified through either quantitative RT-PCR or microarray. We observed that edgeR performs slightly better than DESeq and Cuffdiff2 in terms of the ability to uncover true positives. Overall, DESeq or taking the intersection of DEGs from two or more tools is recommended if the number of false positives is a major concern in the study. In other circumstances, edgeR is slightly preferable for differential expression analysis at the expense of potentially introducing more false positives.

Fruit fly bioassay to distinguish "sweet" sugar structures.

Palatable response to dietary sugars plays a significant role in influencing metabolic health. New structures are being explored with beneficial health properties, although consumer acceptance relies heavily on desirable sensory properties. Despite the importance of behavioral responses, the ability to elucidate structure-preference relationships of sugars is lacking. A wild population of Drosophila melanogaster was used as a model to perform pairwise comparisons across structural groups to characterize a fruit fly bioassay for assessing sugar preference. Preference was successfully described in structurally relevant terms, particularly through the ability to directly test sugars of related structures in addition to standard sucrose comparisons. The fruit fly bioassay also provided the first report on the relative preference for the ß-linked sugar alcohol, gentiobiitol. In making reference to well-known human preferences, the bioassay also raises opportunities for greater understanding of behavioral response to sugar structures in general.