4.7 Article

Reliable Genetic Labeling of Adult-Born Dentate Granule Cells Using Ascl1CreERT2 and GlastCreERT2 Murine Lines

Journal

JOURNAL OF NEUROSCIENCE
Volume 35, Issue 46, Pages 15379-15390

Publisher

SOC NEUROSCIENCE
DOI: 10.1523/JNEUROSCI.2345-15.2015

Keywords

adult neurogenesis; electrophysiology; hippocampus; neural circuits; synaptogenesis; transgenic mice

Categories

Funding

  1. Consejo Nacional de Investigaciones Cientificas y Tecnicas fellowships
  2. Argentine Agency for the Promotion of Science and Technology [PICT2010-1798]
  3. National Institutes of Health [FIRCA R03TW008607-01]
  4. Howard Hughes Medical Institute SIRS [55007652]

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Newly generated dentate granule cells (GCs) are relevant for input discrimination in the adult hippocampus. Yet, their precise contribution to information processing remains unclear. To address this question, it is essential to develop approaches to precisely label entire cohorts of adult-born GCs. In this work, we used genetically modified mice to allow conditional expression of tdTomato (Tom) in adult-born GCs and characterized their development and functional integration. Ascl1(CreERT2); CAG(floxStopTom) and Glast(CreERT2); CAG(floxStopTom) mice resulted in indelible expression of Tom in adult neural stem cells and their lineage upon tamoxifen induction. Whole-cell recordings were performed to measure intrinsic excitability, firing behavior, and afferent excitatory connectivity. Developing GCs were also staged by the expression of early and late neuronal markers. The slow development of adult-born GCs characterized here is consistent with previous reports using retroviral approaches that have revealed that a mature phenotype is typically achieved after 6-8 weeks. Our findings demonstrate that Ascl1(CreERT2) and Glast(CreERT2) mouselines enable simple and reliable labeling of adult-born GC lineages within restricted time windows. Therefore, these mice greatly facilitate tagging new neurons and manipulating their activity, required for understanding adult neurogenesis in the context of network remodeling, learning, and behavior.

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