Age-Dependent Changes in Perineuronal Nets and Associated Parvalbumin Interneurons in the 5XFAD Amyloidosis Mouse Model 公开

Nelson, Ruth (Summer 2023)

Permanent URL: https://etd.library.emory.edu/concern/etds/6m311q63p?locale=zh
Published

Abstract

Perineuronal nets (PNNs) are extracellular matrix structures that surround neurons and proximal dendrites and regulate synaptic transmission, plasticity, and several facets of memory. PNNs are commonly associated with parvalbumin-positive (PV+) fast-spiking interneurons which are hypothesized to play physiological roles in memory and cognition. Despite a growing literature related to PNNs and PV+ neurons’ roles in synaptic maintenance and memory, much remains unknown regarding how these structures are affected in neurodegenerative diseases such as Alzheimer’s Disease (AD). In this study, we used the 5XFAD amyloidosis mouse model to investigate how AD-like pathology affects PNNs and PV+ neurons. Using immunofluorescence microscopy, we stained 5XFAD and Wild Type (WT) mice at 1.8, 3, 6, and 10 months of age. We stained for PV+ neurons (using anti-PV antibody), PNNs (using a WFA antibody), and for Amyloid-Beta (Aβ) plaques (using a 4G8 antibody). Images were then processed using ImageJ to quantify the presence of PV+ neurons, PNNs, and the association between them in several regions of interest across genotypes and age groups. We found that PNNs, but not PV+ neurons, are significantly depleted in the anterior cortex, posterior cortex, and subiculum of the 5XFAD mice in early amyloidosis (3-6 month old 5XFAD mice). Furthermore, analyses investigating the co-localization of PNNs and PV+ neurons in these regions found that PNNs were depleted surrounding PV+ neurons in an age-dependent manner in the 5XFAD mice compared to WT. Specifically, in early amyloidosis (3-6 months) there was a general depletion of PNNs, but in later amyloidosis (6 -10 months) the depletion of PNNs was preferentially surrounding PV+ neurons. Finally, assessing the relationship between Aβ plaque proximity and the co-localization between PNNs and PV+ neurons revealed that PNNs closer to Aβ plaques were more likely to be associated with PV+ neurons. Collectively, these findings may indicate the time-dependent impact of Aβ pathology on PNNs, both in general and specifically surrounding PV+ neurons.

Table of Contents

Introduction 1

PNN Composition 1

An Overview of PNN Functions 2

PNNs and Parvalbumin Interneurons 4

PNNs and Memory 5

PNNs in AD brains 7

Goal of Present Study 8

Materials and Methods 10

Subjects 10

Tissue Staining 11

Immunostaining Optimization 12

Image Acquisition 13

Image Processing 14

Data Integration and Analyses 16

Results and Discussion 18

Limitations 24

Future Directions 24

Conclusions 26

Figures and Tables 27

Figure 1. Study Workflow. 27

Figure 2. PV+ Neuron and WFA+ PNN Counts in the Anterior Cortex. 28

Figure 3. %PNN+ PVs and %PV+ PNNs in the Anterior Cortex. 29

Figure 4. PV+ Neuron and WFA+ PNN Counts in the Posterior Cortex. 30

Figure 5. %PNN+ PVs and %PV+ PNNs in the Posterior Cortex 31

Figure 6. PV+ Neuron and WFA+ PNN Counts in the Subiculum 32

Figure 7. %PNN+ PVs and %PV+ PNNs in the Subiculum 33

Figure 8. %PNN+ PVs by Age and Genotype in 6 and 10-month mice 34

Table 1. Logistic Regression for Age and Genotype on the Probability that a PV+ Neuron is Surrounded by WFA+ PNN 34

Figure 9. %PV+ PNNs by Age and Genotype in 6 and 10-month mice. 35

Table 2. Logistic Regression for Age and Genotype on the Probability that a WFA+ PNN Surrounds a PV+ Neuron 35

Figure 10. Proximity to Plaque and Probability that PV+ Neuron is Associated with a PNN 36

Table 3. Logistic Regression for Plaque Proximity on Probability that PV+ Neuron is associated with a PNN 36

Figure 11. Proximity to Plaque and Probability that WFA+ PNN is Associated with a PV+ Neuron. 37

Table 4. Logistic Regression for Plaque Proximity on Probability that WFA+ PNN is associated with a PV+ Neuron. 37

Appendix 38

Appendix A: ANOVA Outputs for Figures 2-7 38

Appendix B: R Code used to Integrate and Analyze Data 44

References 50

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