RESUMO
Single-cell RNA sequencing (scRNA-seq) has transformed our ability to explore biological systems. Nevertheless, proficient expertise is essential for handling and interpreting the data. In this paper, we present scX, an R package built on the Shiny framework that streamlines the analysis, exploration, and visualization of single-cell experiments. With an interactive graphic interface, implemented as a web application, scX provides easy access to key scRNAseq analyses, including marker identification, gene expression profiling, and differential gene expression analysis. Additionally, scX seamlessly integrates with commonly used single-cell Seurat and Single-CellExperiment R objects, resulting in efficient processing and visualization of varied datasets. Overall, scX serves as a valuable and user-friendly tool for effortless exploration and sharing of single-cell data, simplifying some of the complexities inherent in scRNAseq analysis.
RESUMO
The aging brain presents a general decline in plasticity that also affects hippocampal neurogenesis. Besides the well-known reduction in the rate of neuronal generation, development of new neurons is largely delayed in the aging brain. We have recently shown that this slow development is accelerated when middle-aged mice perform voluntary exercise in a running wheel. It is unclear whether the effects of exercise on neurogenic plasticity are persistent in time in a manner that might influence neuronal cohorts generated over an extended time span. To clarify these issues, we examined the effects of exercise length in 3-week-old neurons and found that their development is accelerated only when running occurs for long (3-4 weeks) but not short periods (1 week). Furthermore, chronic running acted with similar efficiency on neurons that were born at the onset, within, or at the end of the exercise period, lasting until 3 months. Interestingly, no effects were observed on neurons born 1 month after exercise had ended. Our results indicate that multiple neuronal cohorts born throughout the exercise span integrate very rapidly in the aging brain, such that the effects of running will accumulate and expand network assembly promoted by neurogenesis. These networks are likely to be more complex than those assembled in a sedentary mouse due to the faster and more efficient integration of new neurons.
RESUMO
Synaptic modification in cortical structures underlies the acquisition of novel information that results in learning and memory formation. In the adult dentate gyrus, circuit remodeling is boosted by the generation of new granule cells (GCs) that contribute to specific aspects of memory encoding. These forms of plasticity decrease in the aging brain, where both the rate of adult neurogenesis and the speed of morphological maturation of newly generated neurons decline. In the young-adult brain, a brief novel experience accelerates the integration of new neurons. The extent to which such degree of plasticity is preserved in the aging hippocampus remains unclear. In this work, we characterized the time course of functional integration of adult-born GCs in middle-aged mice. We performed whole-cell recordings in developing GCs from Ascl1CreERT2;CAGfloxStopTom mice and found a late onset of functional excitatory synaptogenesis, which occurred at 4 weeks (vs. 2 weeks in young-adult mice). Overall mature excitability and maximal glutamatergic connectivity were achieved at 10 weeks. In contrast, large mossy fiber boutons (MFBs) in CA3 displayed mature morphological features including filopodial extensions at 4 weeks, suggesting that efferent connectivity develops faster than afference. Notably, new GCs from middle-aged mice exposed to enriched environment for 7 days showed an advanced degree of maturity at 3 weeks, revealed by the high frequency of excitatory postsynaptic responses, complex dendritic trees, and large size of MFBs with filopodial extensions. These findings demonstrate that adult-born neurons act as sensors that transduce behavioral stimuli into major network remodeling in the aging brain.
