The long-term goal of this application is to use a cost effective high-throughput approach to identify cell types and map projections that are selectively vulnerable in the progression of aging and Alzheimer's Disease (AD). It is to test the hypothesis that there are concurrent or sequential vulnerabilities in neuroanatomical and protein-interacting network/signaling pathways at critical stages in the progression of aging and AD. A large body of evidence demonstrates that AD is a heterogeneous, multifactorial disease that selectively affects certain regions of the brain, e.g. the entorhinal cortex (EC), while other areas, such as the cerebellum, remain unaffected. Recent studies on the staging of AD neuropathology showed AD-related neuropathology begins in the locus coeruleus (LC) or the EC, followed by the hippocampus (HC) and then the prefrontal cortex (PFC). But cell types, their associated projections and molecular/signaling pathways that are selectively vulnerable at the single neurons level are not well understood. Aging is a major risk factor for AD. Thus, it is important to understand whether there are distinct, similar or overlapping selective vulnerabilities in the progression between aging and AD. Neuronal projections have only been systematically mapped using bulk labeling techniques, e.g., dye tracers, which obscure the diverse projections of intermingled single neurons. This bulk labeling approach to obtain whole brain connectomes requires a large number of animals and is low throughput, labor intensive and expensive. Recently, the MAPseq (Multiplexed Analysis of Projections by Sequencing) approach from one or multiple brain nuclei/sources has been developed to map the projections of thousands or even millions of single neurons by labeling large sets of neurons with random RNA sequences (``barcodes'') in a single brain. Axons are filled with barcode mRNA, each putative projection area is dissected, and the barcode mRNA is extracted and sequenced. Furthermore, each barcoded neuron is also labeled with GFP, enabling fluorescence-activated cell sorting of individual neurons for single cell (nc) RNAseq to obtain transcriptomic information that allows cell type classification and the analysis of biochemical/signaling pathways. A longitudinal study with this MAPseq coupled with scRNAseq will provide unprecedented data informing the cause for the initiation of or contribution to the exacerbation of aging and AD. The multiple source MAPseq coupled with nc-RNAseq will be employed to map the projections and to identify cell types in four brain regions, namely the LC, EC, HC and PFC. The LC provides the major noradrenergic inputs throughout the entire brain. The EC provides key cortical inputs to the HC, which is essential in learning memory. The PFC provides the top-down regulation on various higher order functions, including learning and memory. Both male and female wild-type mice and the APPNLF line of AD mouse, which carries knockin human Swedish and Iberia mutations in the amyloid precursor protein and, importantly, expresses physiological levels of A? and exhibited age-related neuropathology and cognitive impairment, mimicking late onset AD, will be used.
The long-term goal of this application is to use a cost effective high-throughput approach to identify cell types and map projections that are selectively vulnerable in the progression of aging and Alzheimer's Disease (AD). It is to test the hypothesis that there are con-current or sequential vulnerabilities in neuroanatomical and protein-interacting network/signaling pathways at critical stages in the progression of aging and AD. A longitudinal study with this MAPseq coupled with scRNAseq will provide unprecedented data informing the cause for the initiation of or contribution to the exacerbation of aging and AD.
