# Targeting adult-born neurons to correct early deficits in pattern separation in the Tg2576 mouse model of Alzheimer's disease

Trinovita Andraini, Lola Mp Fauré, Lionel Mouledous, Sébastien Gauzin, Zahra Ghasemi, Camille Lejards, Cédrick Florian, Pascale Belenguer, Marie-Christine Miquel, Claire Rampon

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Trinovita Andraini, Lola Mp Fauré, Lionel Mouledous, Sébastien Gauzin, Zahra Ghasemi, et al. Targeting adult-born neurons to correct early deficits in pattern separation in the Tg2576 mouse model of Alzheimer's disease. Neurobiology of Disease, 2025, 217, pp.107158. 10.1016/j.nbd.2025.107158. hal-05376813

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# Targeting adult-born neurons to correct early deficits in pattern separation in the Tg2576 mouse model of Alzheimer's disease

Trinovita Andraini<sup>a,b</sup>, Lola MP Fauré<sup>a</sup>, Lionel Mouledous<sup>a</sup>, Sébastien Gauzin<sup>a</sup>, Zahra Ghasemi<sup>a</sup>, Camille Lejards<sup>a</sup>, Cédrick Florian<sup>a</sup>, Pascale Belenguer<sup>a</sup>, Marie-Christine Miquel<sup>a,1</sup>, Claire Rampon<sup>a,*1</sup>

## ARTICLE INFO

**Keywords:**

Hippocampus

Memory

Adult-born neuron

Dendritic spine

Mitochondria

NeuroD1

## ABSTRACT

Hippocampal adult neurogenesis in mammals generates a unique population of immature granule neurons that play a crucial role in memory, learning and spatial processing. In both Alzheimer's disease (AD) patients and mouse models, this neurogenic capacity of the dentate gyrus is reduced. Mouse models of AD have shown that hippocampal adult neurogenesis is altered early in the course of the disease, contributing to hippocampal-dependent memory impairments. Early stages of AD are also associated with mitochondrial dysfunction in adult-born neurons. While mitochondria have emerged as key regulators of adult neurogenesis, they have been found to be dysfunctional in AD context and to contribute to neurodegenerative diseases. In this study, we investigated the timing and nature of memory deficits in Tg2576 mice, a model of AD, focusing on tasks that depend on hippocampal neurons born in adulthood. We found that Tg2576 mice exhibit early deficits in pattern separation tasks. Notably, adult-born neurons in Tg2576 mice show reduced connectivity and mitochondrial content along with the first memory deficits. To mitigate these defects, we used NeuroD1, a potent neuronal transcription factor, to enhance the development of adult-born neurons in Tg2576 mice. Overexpression of NeuroD1 restored both mitochondrial content and spine density in these neurons to levels comparable to those in control mice. In addition, this intervention restored pattern separation performance in Tg2576 mice, highlighting the potential of strategies targeting mitochondria to correct adult neurogenesis-related memory deficits in the early stages of AD.

## 1. Introduction

Alzheimer's disease (AD) is an age-related disease, marked by progressive impairments in memory and cognition. Despite considerable research, there is still no cure for AD. Increasingly, attention has turned toward the early stages of AD physio-pathogeny to identify disease-modifying targets. Notably, pathogenic brain events begin long before cognitive symptoms emerge (DeTure and Dickson, 2019).

One of the earliest affected region is the hippocampus, particularly the dentate gyrus to CA3 pathway, which is critical for episodic memory. This circuit supports pattern separation, the process of transforming similar inputs into distinct memory representations, by integrating spatio-temporal and event-specific information from the entorhinal

cortex (Leutgeb and Leutgeb, 2007; Bakker et al., 2008; Yassa and Stark, 2011; Hunsaker and Kesner, 2013). Pattern separation declines with age and is altered in individuals with mild cognitive impairment (MCI), a prodromal stage of AD (Yassa et al., 2010, 2011; Stark et al., 2013; Laczó et al., 2021).

In AD, deficits in pattern separation arise early (Stark et al., 2013) and worsen as the disease progresses (Wesnes et al., 2014; Parizkova et al., 2020). Computational models and high-resolution functional MRI studies further highlight that the critical role of the dentate gyrus plays in limiting interference between similar memories (Becker, 2005; Yassa and Stark, 2011) and show that this region is particularly active when distinguishing overlapping inputs (Berron et al., 2016). Structural and functional disruption along the dentate gyrus to CA3 pathway have been

<footnote><sup>a</sup> Univ Toulouse, CNRS, Centre de Recherches sur la Cognition Animale (CRCA), Centre de Biologie Intégrative (CBI), Toulouse, France</footnote>

<footnote><sup>b</sup> Department of Medical Physiology and Biophysics, Faculty of Medicine, Universitas Indonesia, Jakarta, Indonesia</footnote>

<footnote>* Corresponding author at: UMR5169 CNRS, Centre de Recherches sur la Cognition Animale, Centre de Biologie Intégrative, Université de Toulouse, 118, route de Narbonne, 31062 Toulouse, Cedex 9, France.

E-mail address: claire.rampon@utoulouse.fr (C. Rampon).</footnote>

<footnote n="1">¹ Shared senior authorship.</footnote>
reported both in AD and MCI patients (Yassa et al., 2010, 2011).

In rodents, contextual and spatial pattern separation strongly rely on adult-born neurons generated in the dentate gyrus, which project to CA3 (Clelland et al., 2009; Sahay et al., 2011a, 2011b; Nakashiba et al., 2012; Niibori et al., 2012). When immature, these neurons are highly excit- able, more plastic, and efficiently integrate into existing circuits due to properties like GABA-induced depolarization and lower firing threshold (Schmidt-Hieber et al., 2004; Ge et al., 2007). Their sparse synaptic connections promote distinct, non-overlapping firing patterns, sup- porting the sparse coding required for pattern separation (Li et al., 2017). Moreover, because new neurons are recruited during a specific developmental window, they provide a "time stamp" that contributes to minimize the overlap between similar memories (Nakashiba et al., 2012; Kesner et al., 2014; Danielson et al., 2016).

Adult hippocampal neurogenesis is reduced in AD, in both in patients and in mouse models (Moreno-Jiménez et al., 2019; Verret et al., 2013). In amyloidogenic mouse models of AD, impairments in adult hippo- campal neurogenesis occur early in the course of the disease (Demars et al., 2010; Shruster et al., 2010; Faure et al., 2011; Verret et al., 2013). A key feature of this deficit is the poor synaptic integration of adult-born neurons, likely due to a severe reduction in dendritic spines. This compromised connectivity may reduce neuronal survival and, ulti- mately contribute to cognitive decline. Mitochondrial function and dy- namics are crucial for the proliferation, development and maturation of adult-born neurons (Steib et al., 2014; Beckervordersandforth et al., 2017; Kochan et al., 2024; Bonzano et al., 2024; Arrázola et al., 2019). In contrast, mitochondrial defects such as energetic failure, oxidative stress, mitochondrial dynamics unbalance and quality control impair- ments, observed in both patients and animal models (Wang et al., 2020; Misrani et al., 2021; Peggion et al., 2024; Skawratananond et al., 2025) could potentially disrupt adult neurogenesis. Our previous work iden- tified mitochondrial dysfunction as a key contributor of impaired adult neurogenesis in AD. We found that delivering the transcription factor NeuroD1 to neural progenitors of APPxPS1 mice enhances mitochon- drial biogenesis, which in turn promotes the synaptic integration of adult-born neurons (Richetin et al., 2017b).

Tg2576 mice are among the most widely studied mouse models of Alzheimer's disease owing to the progressive evolution of the age- related pathology, which closely mirrors the human condition. This makes Tg2576 mice very valuable to study the specific states that lead to the onset of cognitive symptoms. Typically, Tg2576 mice show no obvious memory deficits at 3 months of age (Hsiao et al., 1996; King and Arendash, 2002; Mitchell et al., 2009) although some studies have re- ported deficits in contextual fear conditioning (D'Amelio et al., 2011) and contextual pattern separation (Kim et al., 2021) in 3-4 month-old Tg2576 males. Spatial memory decline becomes evident around 6 months (Westerman et al., 2002), and worsens significantly by 9-10 months (Westerman et al., 2002; Jacobsen et al., 2006; Mouri et al., 2007; Lesné et al., 2008). Simultaneously, amyloid plaques appear around 9-10 months of age in the hippocampus (Kawarabayashi et al., 2001) and then spread throughout the neocortex and hippocampus after one year of age, when severe memory deficits occur (Verret et al., 2013).

In a previous work on Tg2576 mice, we found that although cell proliferation remains intact, significantly fewer new granule neurons are generated as early as 3 months of age, prior to amyloid deposition (Krezymon et al., 2013). These new neurons also exhibited reduced dendritic complexity, impaired axonal growth and a marked loss of dendritic spines, likely hindering their functional integration into hip- pocampal networks (Krezymon et al., 2013). Such early defects in adult neurogenesis may contribute to the memory deficits detected early in tasks sensitive to its disruption.

To directly test this hypothesis, we now assessed memory perfor- mance across key disease stages – preclinical (4 months), early onset (6 months) and symptomatic (9 months) - using object location and object- based pattern separation tasks. Given the essential role of mitochondrial function in supporting the maturation of adult-born neurons, we also

examined mitochondrial content in these cells. Finally, we investigated whether targeted NeuroD1 overexpression in adult-born neurons of Tg2576 mice would enhance spinogenesis and mitochondrial content, and whether these cellular improvements would be sufficient to rescue early deficits in pattern separation.

## 2. Materials and methods

### 2.1. Animals

We used the Tg2576 transgenic mouse model of Alzheimer's disease (developed by Hsiao et al., 1996) and their non-transgenic littermates (NTg). Tg2576 mice overexpress the "Swedish" mutation of the human APP695 protein (Lys670-Asn, Met671-Leu [K670N, M671L]), under the control of the hamster prion protein promoter. Tg2576 males were bred with C57B6/SJL F1 females (Charles River, L'Arbresle, France) and the offspring was genotyped for the hAPP transgene using PCR on DNA obtained from post-weaning tail biopsies. Due to the aggressive behavior that develops Tg2576 males with age, we used 4, 6 and 9-month-old (mo) females for behavioral analysis (total numbers: 4mo NTg = 11; Tg2576 = 12; 6 mo NTg = 11; Tg2576 = 10; 9 mo NTg = 9; Tg2576 = 8; 4 mo NTg-GFP = 12; Tg2567-GFP = 10, Tg2576-ND1 = 12), and 4 mo males for cellular analysis (total 16 mice, n = 4 per group). Females were not staged for estrous cycle phase and were not included in the morphological analyses. All mice were maintained on a 12 h light/12 h dark cycle with free access to food and water. A total number of 111 mice was used for the study. All experiments were conducted in accor- dance with European Union guidelines (2010/63/EU) for the care and use of laboratory animals. Our animal facility is fully accredited by the French Direction of Veterinary Services (E31-555-011, June 17th, 2021), and experimental procedures conducted in this study were authorized by local ethical committees and the French Ministry for Research (2023100310155057_v4#44099).

### 2.2. Behavioral testing

Three independent age groups of Tg2576 and non-transgenic (NTg) female mice were used to evaluate memory performances at 4, 6 and 9 months of age and to estimate the progression of memory capacities during aging. In each age group, mice were successively subjected to an object location task, a metric pattern separation task and a topologic pattern separation task. Three to five days before behavioral testing, mice were given daily handling sessions to habituate to the investigator. About 30 min before each experimental session, mice were brought in their home cage to the behavior room in dim light. For all tests and between trials, the arena and objects were thoroughly cleaned with 70% ethanol followed by distilled water to ensure the absence of olfactory cues. Different objects were used in the various tests, spaced at least two days apart.

#### 2.2.1. Object location task

The object location task addresses the ability of mice to discriminate between a new and a familiar spatial location. This task is impaired by dorsal hippocampus lesions (Ennaceur et al., 1997; Mumby and Glenn, 2000). Performance in this task is also sensitive to the depletion of adult hippocampal neurogenesis (Goodman et al., 2010). The test was per- formed using two identical objects, as previously described by Goodman et al. (2010). Twenty-four hours before the acquisition phase, mice (4 mo: NTg *n* = 11, Tg2576 *n* = 12; 6 mo: NTg *n* = 11, Tg2576 *n* = 10; 9 mo: NTg *n* = 9, Tg2576 *n* = 8) were habituated to the circular open-field arena (40 cm-high wall, 40 cm diameter, with a striped pattern on one side of the wall) for 10 min. During the acquisition phase, two identical objects were placed in the center of the arena, 20 cm apart, and each mouse was allowed to explore them for 10 min (Fig. 1a, Supplementary Fig. S1). The time spent exploring the 2 objects was scored manually using Ethoc software (CRCA, France). Object exploration was defined as
the time spent actively sniffing or interacting with the object at a distance of 2 cm or less.

Animals that did not reach 25 s of cumulative exploration time during the acquisition phase were excluded (final numbers: 4 mo: NTg n = 11, Tg2576 n = 11; 6 mo: NTg n = 9, Tg2576 n = 8; 9 mo: NTg n = 8, Tg2576 n = 8). Then, 24 h later, one of the objects (left or right pseudorandomly) was moved to a new position, closer to the striped pattern, while keeping a 20 cm distance from the unmoved object. Exploration time of each mouse was monitored for 10 min. Spatial memory was assessed using a preference index, calculated as the percentage of time spent exploring the moved object relative to the total time exploring both objects during the test phase (Fig. 1b).

### 2.2.2. Pattern separation tasks

The metric pattern separation task evaluates a form of spatial pattern separation that involves the ability to accurately assess spatial information such as the angles and distances that separate objects in an environment. This task strongly relies on the dentate gyrus of the dorsal hippocampus (Goodrich-Hunsaker et al., 2005, 2008) and implies the adult-born granule neurons (Kesner et al., 2014). Our protocol was based on the one described by Hunsaker et al. (2009) and consist for the mice to detect a minor change in distance between two objects in a rectangular arena (60 × 40 × 30 cm) without wall visual cues. Twenty-four hours before the task, each mouse was habituated to the empty arena for 5 min. During the sampling phase on the next day, each mouse was allowed to explore the objects placed 40 cm apart in the arena

(Fig. 2a) for 15 min. Then, the mouse was placed in a waiting cage (standard cage with bedding) for 20 min, and the objects were repositioned at a distance of 10 cm from each other (Fig. 2a). The mouse then returned to the arena for a 5 min test phase, during which it was free to re-explore the objects in their new metric configuration. We validated this task using 6 mo C57BL/6 mice tested in a protocol that included a test condition in which the two objects remained in the same configuration as during the sampling phase (Supplementary Fig. S2a). Time spent by the mouse exploring the objects was recorded manually using Ethoc software (CRCA, France), and locomotor activity was automatically video recorded using Ethovision software (Noldus, The Netherlands) during the sampling and test phases. Object exploration data were grouped into 5 min periods during the 15-min sampling phase to allow comparison with the 5 min test phase (Supplementary Fig. S2b, S2c, Fig. 2b, 2c), as explained below. Mice that did not reach a minimum of 20 s of total exploration time for both objects during the sampling phase were removed from the experiment (Fig. 2, final numbers: 4 mo: NTg n = 11, Tg2576 n = 12; 6 mo: NTg n = 9, Tg2576 n = 8; 9 mo: NTg n = 9, Tg2576 n = 8).

The topological pattern separation task was inspired by the work of Goodrich-Hunsaker et al. (2005, 2008) and relies on a neural network involving the hippocampus and the parietal cortex. In the spatial topological processing, the location of each object relative to the other is essential while the accuracy of the relationship is less important. Therefore, a striped pattern was placed on a wall of the rectangular arena used in the metric task, and two different objects were used.

<figure><img src="image_3.png" /><figcaption>**Fig. 1.** Tg2576 mice show age-related impairments in the object location task. (a). Schematic of the object location task. (b). Index of exploratory preference (in %) during the test phase of independent groups of non-transgenic (NTg) and Tg2576 mice at 4, 6 and 9 months of age. Data show the mean ± SEM, each dot represents an individual value. The dotted line indicates chance level (50 %) (index vs chance level: \* p < 0.05, \*\* p < 0.01, \*\*\* p < 0.001, one-sample t-test; 9 mo: \*\* p < 0.01, Bonferroni's test).</figcaption></figure>
<figure><img src="image_4.png" /><figcaption>**b** 4 months</figcaption></figure>

<figure><img src="image_5.png" /><figcaption>6 months</figcaption></figure>

<figure><img src="image_6.png" /><figcaption>9 months</figcaption></figure>

<figure><img src="image_7.png" /><figcaption>**c**</figcaption></figure>

<figure><img src="image_8.png" /></figure>

<figure><img src="image_9.png" /></figure>

<figure><img src="image_10.png" /></figure>

**Fig. 2.** Tg2576 mice show age-related deficits of metric pattern separation. (a) Protocol used to assess metric aspects in pattern separation. (b) Time spent by 4, 6 and 9 month-old (mo) NTg and Tg2576 mice exploring the objects during the 15-min sampling phase (***p < 0.001, repeated measures two-way ANOVA). Then, the exploration time during the test was compared to the last 5-min of sampling (*p* < 0.05, **p** < 0.001, two-way ANOVA followed by Bonferroni's multiple comparisons test). (c) Performance during the test is expressed as the mean exploration ratio of the group (± SEM) compared to chance level (50 %) indicated by the dotted line (##p < 0.01, ###p < 0.001, one-sample t-test). Finally, the performance of age-matched mice is compared between genotypes (*p* < 0.05, ***p* < 0.001, two-way ANOVA followed by Bonferroni's multiple comparisons test). Each dot represents an individual value. Data are mean ± SEM.

Mice were subjected to the topological pattern separation task (Fig. 3a), 48 h after the metric pattern separation task. Each mouse was placed in the arena containing the two objects located 30 cm apart and was free to explore them during 15 min (sampling phase), after which the mouse was returned to the waiting cage for 20 min. The same procedure (sampling phase + waiting cage) was repeated once. The object exploration data were grouped into 5-min periods during the 15-min

sampling phase. Then, for the test phase 20 min later, the mouse was placed in the arena containing the same objects, which positions were reversed (Fig. 3a). We validated this task using 6 mo C57BL/6 mice tested in a protocol that included a test condition in which the two objects remained in the same configuration as during the sampling phases (Supplementary Fig. S3a). Twenty min after the second sampling phase, the mouse was allowed to re-explore the objects for 5 min and its
exploration time was compared to exploration time during the last 5-min period of the second sampling phase (Fig. 3a, Supplementary Fig. S3a). Mice unable to reach 20 s of total exploration time of both objects during the first sampling phase were removed from the experiment (Fig. 3, final numbers: 4 mo: NTg n = 11; Tg2576 n = 11; 6 mo: NTg n = 11; Tg2576 n = 7; 9 mo: NTg n = 7; Tg2576 n = 8).

To assess the effect of NeuroD1, the topological pattern separation task was performed (Fig. 5) three weeks after bilateral injection of Retro-NeuroD1 or Retro-GFP viruses in the dentate gyrus of 12 weeks-old Tg2576 and NTg mice (final numbers: NTg-GFP n = 12; Tg2576-GFP n = 10; Tg2576-NeuroD1 n = 12). To better challenge Tg2576 mice and more clearly reveal their deficits in the topological pattern separation task, we slightly modified the previous protocol by shortening and repeating the exposure periods. The procedure (sampling 5 min + waiting cage 10 min) was repeated 3 times (trials 2, 3, 4). During the test

phase (5th trial), the positions of the two objects were reversed, and the mouse was allowed to re-explore the objects for 5 min. The exploration ratio was calculated as described below and histological controls were performed to ensure that injections sites were located in the dentate gyrus for all animals.

For both the metric (Fig. 2c) and topological (Fig. 3c) pattern separation tasks, an exploration ratio was calculated as in Goodrich-Hunsaker et al. (2005), as follows: (exploration during the 5-min test phase) / (exploration during the 5-min test phase + exploration during the final 5-min of the last sampling phase). This constrains the ratio between 0 and 1. A value greater than 0.5 indicates increased exploration during the test session, while a value below 0.5 reflects reduced exploration (or continued habituation).

<figure><img src="image_11.png" /><figcaption>**Fig. 3.** Tg2576 mice display an early reduction in their ability of topological pattern separation. (a) Protocol used for the topological pattern separation test. (b) Time spent by 4, 6 and 9 month-old (mo) NTg and Tg2576 mice exploring the objects is measured over the 15 min of sampling 2 (***p < 0.001, repeated measure two-way ANOVA). Then, the exploration time during the test is compared to the last 5-min of sampling 2 (p < 0.05, **p < 0.01, two-way ANOVA followed by Bonferroni's multiple comparisons test). (c) Performance during the test is expressed as the group mean exploration ratio (± SEM) compared to chance level (50 %) indicated by the dotted line (###p < 0.01, ###p < 0.001, one-sample t-test vs 0.5). Finally, the exploration ratio of age-matched mice is compared between genotypes (*p < 0.05, *p < 0.001, two-way ANOVA followed by Bonferroni's multiple comparisons test). Each dot represents an individual value. Data are mean ± SEM.</figcaption></figure>
## 2.3. Cellular and morphological analysis

### 2.3.1. Retroviral vectors injection through stereotaxic surgery

Retroviral vectors derived from Moloney murine Leukemia retroviruses, were used to specifically transduce proliferating cells as previously described (Lewis and Emerman, 1994). The control vector Retro-GFP (pCMMP-IRES2-eGFP-WPRE) (gift from L. Roybon and Y. Pomeshchik, Lund Univ., Sweden) leads to the expression of eGFP in adult-born cells and was used to label newly generated cells (Roybon et al., 2009). The Retro-mitoDsRed viral vector (gift from D.C. Lie, Friedrich-Alexander Universität, Germany) containing the mitochondria-targeted DsRed cDNA (pCMMP-IRES2-mDsRed-WPRE) specifically labeled mitochondria in adult-born neurons (Richetin et al., 2017a).

We also used the Retro-NeuroD1 vector (pCMMP-Neurod1-IRES2-eGFP-WPRE) (gift from L. Roybon and Y. Pomeshchik, Lund Univ., Sweden) to drive the expression of both eGFP and the transcription factor NeuroD1 in proliferating cells. Overexpression of NeuroD1 after injection of the same Retro-NeuroD1 was described in the seminal paper (Roybon et al., 2009). The final titer for each retrovirus ranged between 0.5 and $3 \times 10^9$ TU/mL.

Briefly, mice were anesthetized with a 4 % isoflurane induction followed by a reduced dose to 1–1.5 % for maintenance of anesthesia. After loss of consciousness, they were injected with 1 µL of a 1:1 retroviral mixture of Retro-GFP and Retro-mitoDsRed ($n = 12$ NTg and $n = 10$ Tg2576 mice), or Retro-NeuroD1 and Retro-mitoDsRed ($n = 12$ Tg2576 mice), at a rate of 0.1 mL/min bilaterally into the dentate gyrus according to stereotaxic coordinates (bregma: anteroposterior –2 mm; lateral ±1.6 mm; ventral –2.5 mm, as previously described (Richetin et al., 2015). After recovery in a heated chamber, mice were returned to their home cages.

### 2.3.2. Tissue processing and immunohistochemistry

Three weeks (21 days) after viral injection, mice were deeply anesthetized with pentobarbital (50–90 mg/kg BW, i.p.) and transcardially perfused with cold 0.1 M phosphate buffer (PB) followed by 4 % paraformaldehyde (PFA) in PB. Brains were harvested and fixed overnight in 4 % PFA, rinsed 24 h in PB and cryoprotected for 2 days in a 30 % sucrose solution in PB containing 0.1 % sodium azide at 4 °C. Then, brains were cut into 40 µm thick coronal sections using a freezing microtome (Leica) which were stored in the cryoprotectant solution at -20 °C until immunostaining. Before use, the floating sections were rinsed in phosphate-buffered saline containing 0.25 % Triton-X (PBST). Then, the sections were incubated in rabbit anti-GFP solution (1:500, Torrey Pines Biolabs, USA) overnight, rinsed three times in PBST and incubated for 120 min in Alexa Fluor-488-conjugated donkey anti-rabbit solution (1:500; Life Technologies) in PBST. Then, the sections were extensively rinsed in PBST-azide (0.1 %) and mounted on slides, coverslipped using Mowiol mixed with Hoechst (1:10000; Life Technologies) and stored at 4 °C.

### 2.3.3. Confocal microscopy and images processing

Based on their morphological characteristics, GFP-labeled (GFP+) cells in the dentate gyrus were identified as either glial cells or neurons. To analyze mitochondria and dendritic spines in adult-born neurons, we used images of $GFP^+$ neurons that were co-transfected with MitoDsRed, which specifically labels mitochondria (Steib et al., 2014). Images were captured with a Leica TCS SP8 confocal microscope (Heidelberg, Germany) equipped with $63 \times$ HCX PL APO (1.40 NA) objective (Toulouse Réseau Imagerie, FRBT-CBI). Images were taken in z-series at 0.20 mm intervals, with a x63 oil lens and a 6-digital zoom. The same settings for laser power, photomultiplier gain and offset were maintained for all images. Images were acquired with a resolution of $1024 \times 1024$ pixels, a 4-fold line and frame averaged and a scan rate of 8000 Hz. The 12-bit image stacks were then deconvoluted using Huygens Essential deconvolution software (SVI). All images were then analyzed using Imaris XT

3D software (Bitplane AG) for mitochondrial and spines parameters.

### 2.3.4. Mitochondrial biomass and index analysis

Mitochondria from GFP+ neurons were analyzed in the somatic, where they are generated, and in the distal dendritic compartments, where they are transported. The distal dendritic compartment was defined as the dendritic tree between the beginning of the middle molecular layer and the end of the outer molecular layer, comprising mainly the dendritic segments located after the second branch point. Total mitochondrial volume, total GFP compartment volume and dendritic length were estimated automatically with Imaris software. Mitochondrial biomass expressed as an index, is the ratio of the total mitochondria volume over the corresponding GFP compartment volume ($100 \ \mu m^3$ for the somas, $10 \ \mu m$ for the dendrites). We analyzed 20–22 somatic compartments and 31–39 distal dendrites per group, in equal proportion per mouse (4 mice/group).

### 2.3.5. Spine density and spine shape analysis

Spine analysis was performed from distal dendrites of GFP+ neurons and included spine density assessment (number of spines/10 µm dendritic length) and morphological classification of spines. The 3D reconstruction of dendrites was conducted with Imaris software. The volume and number of spines were measured with the Imaris surface tool module, while the dendritic length was measured with the Imaris Filament tracer module. Spine density was calculated by dividing the total number of spines by the dendritic segment length. For this analysis, four mice were included in each group, with 31–38 dendritic segments analyzed per group. Dendritic spines were categorized according to their volume and morphology, into four types, as in Petsophsakul et al. (2017): filopodia (protrusion with long neck and no head), thin (protrusion with a neck and head <0.1 mm³), stubby (protrusion with no obvious neck or head) or mushroom (protrusion with a neck and head >0.1 mm³ (Harris et al., 1992; Sorra and Harris, 2000).

### 2.3.6. Statistical analyses

**Behavioral data:** For all analyses, the observer did not know the identity of the samples. Data processing was performed using Prism software (GraphPad 10.0) and all data are reported as means and SEM. Object location data were evaluated using a one sample Student's t-test to compare the preference index to the chance level (50 %) followed by a two-way ANOVA test with Bonferroni post hoc analyses to compare aged-matched genotypes.

To assess the performance of mice in metric or topological pattern separation tasks, a two-way ANOVA with repeated measures was first used to assess the difference in exploration time between the three 5 min-periods of the sampling phase (i.e. habituation) across time and between genotypes. Then, mice exploration during the last 5 min of the sampling phase was compared to exploration during the test, using a repeated-measure ANOVA with 2 factors to evaluate the ability of mice of both genotypes to detect metric change. Then, the exploration ratio in metric or topological pattern separation tasks were evaluated using a one sample Student's t-test to compare the preference index to the chance level (0.5). This was followed by a two-way ANOVA test with post hoc analyses to compare age-matched genotypes, or a Student's t-test to compare between treatments and genotypes within an age group (Fig. 5). Mean ± SEM, appropriate analyses, parameters and *p* values are indicated in the results. For all comparisons, values to *p* < 0.05 were considered significant.

**Cellular data:** Morphological analyses were evaluated with two-way ANOVA test followed by Bonferroni's post hoc analyses, or Kruskal-Wallis test followed by Dunn's post hoc analyses when data distribution was not normal, to account for multiple comparisons between genotypes and treatment. Mean ± SEM, appropriate analyses, parameters and *p* values are indicated in the results. For all comparisons, values to *p* < 0.05 were considered significant.
### 3. Results

#### 1. At 9 months of age, Tg2576 mice have impaired spatial memory in the object location task

Hippocampal-dependent spatial memory was assessed in Tg2576 mice at different stages of the disease using the object location task. This test evaluates the ability of mice to distinguish a new location from a familiar location (Fig. 1a). During the acquisition phase, NTg and Tg2576 mice spent the same amount of time exploring each object and the cumulated exploration time was not different between groups, indicating that both genotypes had a similar interest for both objects (Supplementary Fig. S1). After 24 h, during the test phase, NTg mice of all tested ages (4, 6 and 9 month-old (mo)) explored the displaced object significantly more than the other object (4 mo: *p* = 0.0008 vs 50 %, *t* = 4.73, *df* = 10; 6 mo: *p* < 0.0001 vs 50 %, *t* = 7.32, *df* = 8; 9 mo: *p* = 0.0003 vs 50 %, *t* = 6.65, *df* = 7; one-sample t-test; Fig. 1b). While 4 and 6 mo Tg2576 mice also preferentially explored the moved object (4 mo: *p* = 0.0016 vs 50 %, *t* = 4.26, *df* = 10; 6 mo: *p* = 0.0319 vs 50 %, *t* = 2.67, *df* = 7; one-sample t-test; Fig. 1b), the older 9 mo Tg2576 mice showed no preference for the displaced object (Tg2576: *p* = 0.1326 vs 50 %, *t* = 1.70, *df* = 7; one-sample t-test; Fig. 1b) indicating that they were not able to discriminate between novel and familiar locations. In addition, at 9 mo, Tg2576 mice exhibited impaired performances compared with age-matched NTg mice (*p* = 0.01, *t* = 3.084, *df* = 49, Bonferroni's test), as opposed to mice of 4 and 6 mo (4 mo: *p* = 0.534, *t* = 1.366, *df* = 49; 6 mo: *p* = 0.058, *t* = 2.422, *df* = 49; Bonferroni's test) (Fig. 1b). Overall, these data indicate that at 9 months of age, Tg2576 mice are unable to discriminate a novel from a familiar location, while this spatial memory is preserved at earlier stages of the disease.

#### 2. From 6 months of age, Tg2576 mice show age-related impairment in metric pattern separation

We used the metric pattern separation task to evaluate the ability of mice to detect a minor change in distance between objects (Fig. 2a). Beforehand, we validated the use of the exploration ratio as a reliable parameter to evaluate spatial memory in this task (Supplementary Fig. S2), using two separate groups of C57BL/6 mice. Animals were subjected to a metric pattern separation protocol including a test in which the objects remained in the same configuration as during sampling phase (Supplementary Fig. S2a). This ensured that increased exploration during the test was due to the new configuration and not to the waiting cage. After habituation to the setup (Supplementary Fig. S2b), a group of mice (Lot 1) explored the objects in the same configuration (40 cm apart) as during sampling, and showed no renewed interest after 20 min in the waiting cage (Supplementary Fig. S2b). Their exploration ratio was 0.5 (Supplementary Fig. S2c). Mice in the other group (Lot 2) explored the objects placed closer together (10 cm apart) and showed an increased interest (Supplementary Fig. S2b). This confirms that an exploration ratio > 0.5 indicates the detection by the animal of a metric change (Supplementary Fig. S2c).

Following this validation, we submitted Tg2576 and NTg mice to this protocol (Fig. 2b). At all ages studied, mice of both genotypes demonstrated habituation, as indicated by the significant reduction in object exploration time during the 15-min sampling phase (4 mo: *p* < 0.0001, *F*<sub>(2,40)</sub> = 36.12; 6 mo: *p* < 0.0001, *F*<sub>(2,30)</sub> = 64.24; 9 mo: *p* = 0.0001, *F*<sub>(2,30)</sub> = 12.44; two-way repeated measures ANOVA over the 15 min exploration; Fig. 2b). There was no effect of genotype on exploration time over all 5-min periods (4 mo: *p* = 0.97, *F*<sub>(1,20)</sub> = 0.001; 6 mo: *p* = 0.32, *F*<sub>(1,15)</sub> = 1.04; 9 mo: *p* = 0.84, *F*<sub>(1,15)</sub> = 0.04; two-way repeated measures ANOVA, Fig. 2b). This indicates that all groups of mice habituated to the setup. Twenty minutes later, the ability of mice to distinguish a metric change was evaluated during a 5-min test performed after the repositioning of the objects (Test, Fig. 2b). We observed that 4 mo animals of both genotypes showed an increase in object

exploration (metric change effect: *p* < 0.0001, *F*<sub>(1,20)</sub> = 36.84, two-way ANOVA; Fig. 2b) and detected no effect of the genotype on performance (*p* = 0.14, *F*<sub>(1, 20)</sub> = 2.35) and no significant interaction between metric change and genotype (*p* = 0.13, *F*<sub>(1, 20)</sub> = 2.46). At 6 mo, we found an effect of metric change (*p* = 0.0027, *F*<sub>(1, 15)</sub> = 12.85) and a significant interaction was observed (*p* = 0.002, *F*<sub>(1, 15)</sub> = 14.14), while no effect of genotype was found (*p* = 0.12, *F*<sub>(1, 15)</sub> = 2.78). A similar observation was made for 9 mo mice (metric change *p* = 0.01, *F*<sub>(1, 15)</sub> = 8.72; interaction: *p* = 0.003, *F*<sub>(1, 15)</sub> = 12.15; genotype: *p* = 0.68, *F*<sub>(1, 15)</sub> = 0.17). In addition, at 4 mo, mice from both genotypes showed a significant increase in exploration during test phase (NTg: *p* < 0.0001, *t* = 5.401, *df* = 20; Tg2576: *p* < 0.0094, *t* = 3.182, *df* = 20, Fig. 2b). On the opposite, from 6 months of age, only NTg showed an increase in exploration time during test phase (at 6 mo NTg: *p* < 0.0002, *t* = 5.354, *df* = 15; Tg2576: *p* > 0.9999, *t* = 0.121, *df* = 15; at 9 mo NTg: *p* < 0.0006, *t* = 4.693, *df* = 15; Tg2576: *p* > 0.9999, *t* = 0.367, *df* = 15, Bonferroni's test, Fig. 2b).

Using an exploration ratio to compare between genotypes, we confirmed that 4 mo mice of both genotypes noticed the metric change, as evidenced by their exploration ratio significantly greater than 0.5, reflecting their increased interest in objects in their new configuration (NTg: 0.68 ± 0.04, *p* = 0.0005, *t* = 5.006, *df* = 10; Tg2576: 0.64 ± 0.02, *p* < 0.0001, *t* = 7.246, *df* = 11, one-sample t-test, Fig. 2c). This exploratory ratio remained stable for NTg mice at the older ages of 6 and 9 months (6 mo NTg: 0.62 ± 0.03, *p* = 0.0031, *t* = 4.180, *df* = 8; 9 mo NTg: 0.66 ± 0.02, *p* < 0.0001, *t* = 7.231, *df* = 8; one-sample t-test, Fig. 2c), reflecting the ability of these mice to detect the metric change. In contrast, Tg2576 mice at 6 and 9 mo, showed no increase in exploratory ratio (exploration ratio < 0.5) in the new metric configuration (6 mo: Tg2576: 0.49 ± 0.02, *p* = 0.7909, *t* = 0.2755, *df* = 7; 9 mo Tg2576: 0.48 ± 0.04, *p* = 0.6465, *t* = 0.4791, *df* = 7, one-sample t-test, Fig. 2c). Furthermore, if the exploratory ratio of 4 mo mice did not differ between genotypes, indicating that Tg2576 performed similarly to NTg (4 mo: *p* = 0.806, *t* = 1.118, *df* = 51), 6- and 9-mo Tg2576 mice showed a significantly lower exploratory ratio than age-matched NTg mice (6 mo: *p* = 0.0201, *t* = 2.826, *df* = 51; 9 mo: *p* = 0.0003, *t* = 4.197, *df* = 51, Bonferroni's test), indicative of an age-related impairment of Tg2576 mice in metric pattern separation, detectable as early as 6 mo. Altogether these data indicate that in contrast to aged-matched controls, 6 and 9 mo Tg2576 mice are unable to detect a change in distance between objects.

#### 3. As early as 4 months of age, Tg2576 mice show reduced performances in topological pattern separation

The topological pattern separation task evaluates mice ability to detect a minor change regarding the overall configuration of objects and their general relationships to each other. In this task, the position of objects is reversed between the sampling and testing phases (Fig. 3a). First, we validated our protocol by using two separate groups of C57BL/6 mice to a topological pattern separation task. This task included a test in which the objects remained in the same configuration as during sampling (Supplementary Fig. S3a). This ensured that increased exploration during the test was due to the new configuration. After habituation to the setup (Supplementary Fig. S3b), mice (Lot 1) tested with the same topological configuration showed no regain of exploration during test phase (Supplementary Fig. S3b), while mice (Lot 2) tested in the new topological configuration showed a pronounced increase in exploration (Supplementary Fig. S3c). These data validate that an exploration ratio > 0.5 indeed reflects the animal's detection of a topological change.

Next, we showed that Tg2576 and NTg mice of all ages displayed progressive habituation reflected by a decrease in exploration time over 5 min-periods during the second sampling phase (4 mo: *p* < 0.0001, *F*<sub>(2,42)</sub> = 32.05; 6 mo: *p* = 0.0006, *F*<sub>(2,32)</sub> = 9.44; 9 mo: *p* = 0.0001, *F*<sub>(2,26)</sub> = 23.59; two-ways repeated measure ANOVA, Fig. 3b). No effect of genotype was observed within age groups (4 mo: *p* = 0.69, *F*<sub>(1,21)</sub> = 0.15;
6 mo: *p* = 0.39, *F*<sub>(1,16)</sub> = 0.77; 9 mo: *p* = 0.32, *F*<sub>(1,13)</sub> = 1.06; two-ways repeated measure ANOVA, Fig. 3b), indicating similar habituation of mice, regardless of genotype or age. During the test phase, NTg mice of all ages displayed a statistically significant increase in exploration time (4 mo: *p* < 0.0001, *t* = 6.096, *df* = 20; 6 mo: *p* = 0.011, *t* = 3.19, *df* = 16; 9 mo: *p* < 0.0001, *t* = 6.414, *df* = 13; Bonferroni's test, Fig. 3b). Moreover, their exploration ratios were significantly greater than 0.5, indicating that NTg mice had a revived interest in exploring objects (4 mo NTg: *n* = 11, 0.78 ± 0.03, *p* < 0.0001; 6 mo NTg: *n* = 11, 0.63 ± 0.02, *p* < 0.0003; 9 mo NTg: *n* = 7, 0.73 ± 0.03, *p* < 0.0003; one-sample t-test, Fig. 3c). However, among Tg2576 mice, only 4 mo animals showed a significantly renewed interest in the objects, while 6 mo mice remained just below significance (4 mo: *p* < 0.0199, *t* = 2.848, *df* = 20; 6 mo: *p* = 0.052, *t* = 2.545, *df* = 16; 9 mo: *p* < 0.247, *t* = 1.647, *df* = 13; Bonferroni's test, Fig. 3b). This effect was further supported by the analysis of exploration ratios during the test phase, which were significantly greater than 0.5 only in the 4 mo Tg2576 group, indicating their revived interest in object exploration (4 mo Tg2576: *n* = 11, 0.65 ± 0.04, *p* < 0.002; 6 mo Tg2576: *n* = 7, 0.60 ± 0.04, *p* < 0.0595; 9 mo Tg2576: *n* = 8, 0.58 ± 0.04, *p* < 0.108; one-sample t-test, Fig. 3c). Comparison between genotypes indicates that at 4 and 9 mo, NTg mice showed significantly higher interest in the new configuration compared with their Tg2576 counterparts (4 mo: *p* = 0.0128, *t* = 2.99, *df* = 49; 9 mo: *p* = 0.0172, *t* = 2.88; *df* = 49; Bonferroni's test, Fig. 3c). This effect was not observed at 6 mo, probably because of the lower exploration ratio of NTg mice, which was similar to that of Tg2576 mice (6 mo: *p* > 0.999, *t* = 0.567, *df* = 49; Bonferroni's test).

## 4. Adult-born neurons of Tg2576 mice show mitochondrial deficits and reduced dendritic spine density which are corrected by NeuroD1 overexpression

Thus, Tg2576 mice show a reduction in their capacity to discriminate topological configurations, detectable as early as 4 months of age when compared to controls, an age when adult neurogenesis is already compromised in these mice (Krezymon et al., 2013). Since the development and maturation of new neurons during adulthood relies on healthy mitochondrial function (Beckervordersandforth et al., 2017; Steib et al., 2014), we next investigated whether impaired adult neurogenesis in Tg2576 mice is associated with altered mitochondrial content in adult-born neurons. Based on our work showing that NeuroD1 enhances spinogenesis and mitochondrial content in adult-born neurons (Richetin et al., 2015, 2017b), we further tested whether NeuroD1 could mitigate defects in hippocampal neurogenesis and pattern separation ability in Tg2576 mice.

Given that adult neurogenesis declines with age and that adult neurogenic processes are impaired in Tg2576 mice from young age (Krezymon et al., 2013), we assessed mitochondrial content and dendritic spine density in adult-born neurons of 4 mo Tg2576 and NTg mice. This was done using a retrovirus expressing MitoDsRed together with another expressing GFP in newly born neurons as in other studies including ours (Andraini et al., 2023; Jagasia et al., 2009; Steib et al., 2014; Zhao et al., 2006) (Fig. 4a). The effect of NeuroD1 overexpression in new neurons was investigated in Tg2576 and NTg mice using a retrovirus expressing MitoDsRed together with another expressing GFP alone or with NeuroD1. As mitochondria are generated in the soma before being distributed along neuronal processes, we generated 3D-reconstructions from confocal images (Fig. S4a, b) and distinctly assessed the somatic mitochondrial biomass index (Figs. 4b, d) and the distal dendritic mitochondrial biomass index of adult-generated neurons (Figs. 4d, e).

In GFP-labeled (GFP+) neurons of Tg2576 mice, the somatic mitochondrial biomass index was significantly decreased compared to NTg mice (NTg-GFP: 4.49 ± 0.19, Tg2576-GFP: 3.38 ± 0.02; *p* = 0.048, *t* = 2.724, *df* = 76, Bonferroni's test, Fig. 4d). Similar observations were made in the distal dendrites of GFP+ neurons from Tg2576 mice, where

the mitochondrial biomass index was reduced two-fold compared to NTg mice (NTg-GFP: 21.13 ± 1.67, Tg2576-GFP: 11.10 ± 1.2, *p* = 0.001, *Z* = 3.728, Dunn's test, Fig. 4e).

Remarkably, we found that NeuroD1 overexpression in adult-born neurons of both NTg and Tg2576 mice significantly increased the total volume of mitochondria in the soma (NTg-GFP: 4.49 ± 0.26; NTg-NeuroD1: 6.03 ± 0.39, *p* = 0.0025, *t* = 3.688, *df* = 76, Bonferroni's test; Tg2576-GFP: 3.38 ± 0.19; Tg2576-NeuroD1: 5.15 ± 0.31, *p* < 0.0001, *t* = 6.419, *df* = 76, Bonferroni's test, Fig. 4c). In the dendritic compartment however, the increase was statistically significant only in Tg2576 mice (NTg-GFP: 21.13 ± 1.67; NTg-NeuroD1: 29.46 ± 3.82, *p* > 0.999, *Z* = 0.505, Dunn's test; Tg2576-GFP: 11.10 ± 1.20; Tg2576-NeuroD1: 29.70 ± 2.25, *p* < 0.0001, *Z* = 4.29, Dunn's test, Fig. 4e). Interestingly, after NeuroD1 overexpression, the mitochondrial content of new neurons in Tg2576 mice was restored to the level of control mice (soma: NTg GFP: 4.49 ± 0.26; Tg2576 NeuroD1: 5.15 ± 0.31, *p* = 0.6526, *t* = 1.623, *df* = 76, Bonferroni's test, Fig. 4d); dendritic compartment: NTg-GFP: 21.13 ± 1.67; Tg2576-NeuroD1: 29.70 ± 2.25; *p* = 0.0808, *Z* = 2.471, Dunn's test, Fig. 4e).

Next, we showed that new neurons of 4 mo Tg2576 mice have a significantly reduced spines density compared to control mice (NTg-GFP: 8.99 ± 0.52, Tg2576-GFP: 3.49 ± 0.36; *p* < 0.0001, *Z* = 6.62; Dunn's test) (Fig. 4f). Then, we classified these spines into four morphological types based on their morphology: stubby, filopodia, thin and mushroom (see methods, Fig. S4c). We found that stubby spines (NTg-GFP: 0.416 ± 0.07, Tg2576-GFP: 0.131 ± 0.05; *p* = 0.002, *Z* = 3.59; Dunn's test) and mature spines, i.e. thin and mushroom subtypes, were significantly depleted on GFP-labeled neurons of Tg2576 mice compared to NTg animals (Thin: NTg-GFP: 6.98 ± 0.42, Tg2576-GFP: 2.61 ± 0.26; *p* < 0.0001, *Z* = 6.37; Mushroom: NTg-GFP: 1.27 ± 0.20, Tg2576-GFP: 0.47 ± 0.09; *p* = 0.0002, *Z* = 4.11; Dunn's test, Fig. 4g). We then observed that NeuroD1 induced a remarkable 2-fold increase in spine density on Tg2576 new neurons (Tg2576 GFP: 3.49 ± 0.36; Tg2576 NeuroD1: 7.59 ± 0.36, *p* < 0.0001, *Z* = 5.24; Dunn's test) (Fig. 4f), which thus reached a spine density similar to that of NTg neurons (NTg-GFP: 8.99 ± 0.52; Tg2576-NeuroD1: 7.59 ± 0.36, *p* = 0.619, *Z* = 1.63; Dunn's test). Noticeably, NeuroD1 overexpression had no effect on spine density in NTg mice (NTg-GFP: 8.99 ± 0.52; NTg-NeuroD1: 8.63 ± 0.36, *p* > 0.9999, *Z* = 0.273, Dunn's test) (Fig. 4f). Interestingly, the promoting effect of NeuroD1 in Tg2576 mice was distributed among stubby (Tg2576-GFP: 0.131 ± 0.05; Tg2576-NeuroD1: 0.458 ± 0.004, *p* < 0.0001, *Z* = 4.887, Dunn's test) and thin (Tg2576-GFP: 2.61 ± 0.26; Tg2576-NeuroD1: 6.02 ± 0.31, *p* < 0.0001, *Z* = 5.185, Dunn's test) spines, but less significantly on mushroom spines (Tg2576-GFP: 0.469 ± 0.10; Tg2576-NeuroD1: 0.804 ± 0.12, *p* = 0.1392, *Z* = 2.27, Dunn's test) (Fig. 4g).

## 5. Overexpression of NeuroD1 in adult-born neurons of Tg2576 mice restores topological pattern separation

Given NeuroD1's beneficial effects on the connectivity and mitochondrial content of adult-born neurons in Tg2576 mice, we asked whether these improvements could also restore the mice's performance in the topological pattern separation task. Thus, 21 days after Retro-NeuroD1 or Retro-GFP administration in the dentate gyrus, 4 mo mice were subjected to a topological pattern separation task (Fig. 5a). Mice of all groups showed progressive habituation as reflected by a decrease in exploration time over the 4 sampling sessions (sampling-session *x* group: *p* = 0.0350, *F*<sub>(6, 93)</sub> = 2.381; sampling-session: *p* < 0.0001, *F*<sub>(2, 297)</sub>, 71, 21) = 60.12; group: *p* = 0.131, *F*<sub>(2,31)</sub> = 2.167 two-ways repeated measure ANOVA, Fig. 5b). However, during the test, Tg2576-GFP mice showed no increase in exploration time (Tg2576-GFP: *p* = 0.8819, paired *t*-test sampling 4 vs Test, Fig. 5b) reflecting a deficit in topological pattern separation. In contrast, Tg2576-ND1 mice, like NTg-GFP, showed a significant increase in exploration time during the test (Tg2576-ND1: *p* = 0.002, NTg-GFP: *p* = 0.0157; paired *t*-test sampling 4 vs Test, Fig. 5b).
<figure><img src="image_12.png" /><figcaption>b</figcaption></figure>

Somatic compartment

<figure><img src="image_13.png" /><figcaption>d</figcaption></figure>

<figure><img src="image_14.png" /><figcaption>f</figcaption></figure>

<figure><img src="image_15.png" /><figcaption>c</figcaption></figure>

Distal dendritic compartment

<figure><img src="image_16.png" /><figcaption>e</figcaption></figure>

<figure><img src="image_17.png" /><figcaption>g</figcaption></figure>

<figure><img src="image_18.png" /></figure>

(caption on next page)
**Fig. 4.** Mitochondrial content and spine density of adult-born hippocampal neurons are altered in Tg2576 mice and corrected by NeuroD1 overexpression. (a) Adult-born neurons labeled with the GFP or NeuroD1-expressing retrovirus in the dentate gyrus of NTg or Tg2576 mice (bar = 20 µm). (b, c) 3D reconstructions depicting the somas and distal dendrites of 21 day-old GFP-labeled adult-born hippocampal neurons (GFP, green) and their mitochondrial content (MitoDsRed, red) in NTg and Tg2576 mice injected with GFP or NeuroD1 expressing retroviruses (scale bar = 2 µm). (d, e) Mitochondrial biomass index in soma and distal dendrites of 21 day-old GFP-labeled neurons. (d) Mitochondrial biomass index for the somatic compartment in Tg2576 compared to NTg mice and after NeuroD1 expression (*p* < 0.05, **p** < 0.01, ***p* < 0.001, two-way ANOVA test followed by Bonferroni *post hoc* multiple comparisons test). (e) Dendritic mitochondrial biomass index in Tg2576 mice compared to NTg and after NeuroD1 expression (**p* < 0.01, ***p* < 0.0001; Kruskal Wallis test and Dunn's *post hoc* multiple comparisons test). (f) Dendritic spine density in GFP-labeled adult-born hippocampal neurons from NTg and Tg2576 mice, and impact of NeuroD1 overexpression on spine density (***p* < 0.0001, two-way ANOVA and Bonferroni *post hoc* multiple comparisons test). (g) comparison of dendritic spine density by subtype in NTg and Tg2576 mice and the effect of NeuroD1 overexpression (*p* < 0.05, ****p* < 0.0001, Kruskal Wallis test and Dunn's *post hoc* multiple comparisons test). Data represent mean ± SEM. Dots represents individual cellular data. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

<figure><img src="image_19.png" /></figure>

<figure><img src="image_20.png" /></figure>

**Fig. 5.** NeuroD1 overexpression in adult-born neurons rescues topological pattern separation abilities in Tg2576 mice. (a) Protocol used for the topological pattern separation test. (b) Mean exploration time over successive trials. Time spent exploring the objects over the four sampling phases (***p* < 0.001, repeated measures two-way ANOVA). Then the exploration time during the test phase is compared to the last 5-min of sampling (*p* < 0.05, **p* < 0.01, paired t-test sampling 4 vs Test). (c) Performance during the test is expressed as group mean exploration ratio (± SEM) compared to chance level (50 %) indicated by the dotted line (#p < 0.01, ##p < 0.01, one-sample t-test vs 0.5). Last, the performance of age-matched mice is compared between genotypes and treatments (*p* < 0.05, unpaired t-test). Each dot represents an individual value. Data are mean ± SEM.

Similarly, the exploration ratio of Tg2576-GFP mice remained close to 0.5 (Tg2576-GFP: *n* = 10, 0.48 ± 0.07, *p* = 0.773, one sample t-test vs 0.5, Fig. 5c). In contrast, the exploration ratio of Tg2576-ND1 mice, like that of NTg-GFP, was significantly greater than 0.5, confirming their ability to detect the new configuration (Tg2576-NeuroD1: *n* = 12, 0.64 ± 0.04, *p* = 0.007; NTg-GFP: *n* = 12, 0.62 ± 0.05, *p* = 0.031, one-sample t-test, Fig. 5c). As expected, comparison between groups showed that NTg-GFP and Tg2576-NeuroD1 reached similar exploration ratio (NTg-GFP vs Tg2576-NeuroD1: *p* = 0.41, *t* = 0.22, *df* = 22; unpaired t-test, Fig. 5c) significantly different from that of Tg2576-GFP mice (NTg-GFP vs Tg2576-GFP: *p* = 0.048, *t* = 1.75, *df* = 20; Tg2576-NeuroD1 vs Tg2576-GFP: *p* = 0.025, *t* = 2.08, *df* = 20; unpaired t-test, Fig. 5c).

## 4. Discussion

In summary, our findings provide a systematic characterization of the onset and progression of memory deficits across successive stages of AD in the Tg2576 mouse model. By distinguishing among hippocampal-

dependent memory tasks—including spatial memory, metric and topological pattern separation—we show that cognitive impairments emerge as early as 4 months of age in Tg2576 mice, initially affecting topological pattern separation. At this early stage, Tg2576 mice also display a reduced number of new hippocampal neurons (Krezymon et al., 2013). We further identify mitochondrial deficits and decreased dendritic spine density in adult-born neurons as cellular correlates of these behavioral alterations. Notably, we demonstrate that overexpression of NeuroD1 in the dentate gyrus rescues mitochondrial content and spine density in adult-born neurons, while restoring cognitive function. These results establish a link between the plasticity gained through adult hippocampal neurogenesis and topological pattern separation performance. Together, our results provide novel insights into behavioral protocols allowing to reveal alteration of specific cognitive functions in the early stages of AD and further confirm the interest of targeting neural stem cells to reinstate hippocampal plasticity in diseased brains.

There is currently no cure for AD, and developing treatments that efficiently modify the course of the disease remains a major challenge.
To be effective, such treatments must target early stages of AD, ideally before mild cognitive impairment (MCI) stage, which can be revealed by patient's inability to accurately encode and discriminate similar spatial locations (Parizkova et al., 2020; Laczó et al., 2021). This process, called pattern separation, depends on the hippocampus and prevents interference between overlapping contexts or experiences (Bakker et al., 2008; Hunsaker and Kesner, 2013). Studies show that object-based pattern separation declines with aging in human (Kirwan and Stark, 2007; Toner et al., 2009; Yassa et al., 2011), more so in MCI (Stark et al., 2013) and AD patients (Wesnes et al., 2014). In rodents, as in humans, pattern separation is highly age-sensitive and particularly impaired in AD, linked to dysfunction in the entorhinal cortex-DG-CA3 pathway (Cès et al., 2018; Marrone et al., 2011; Reagh et al., 2018). While animal studies often use aversive conditioning protocols to assess pattern separation (Clelland et al., 2009; Sahay et al., 2011a; Tronel et al., 2012; Deng et al., 2013), we employed several non-aversive object-based tasks to better mirror protocols used in patients (Leal and Yassa, 2013; Reagh et al., 2018). Due to increased aggressiveness of Tg2576 males with age, only females were used for behavioral testing.

We found that deficits in these tasks emerged at different ages in Tg2576 female mice, reflecting disease progression. Indeed, these mice showed impaired performance in the topological pattern separation task as early as 4 months of age. By 6 months, Tg2576 mice also exhibited impairments in the metric pattern separation task, and by 9 months, deficits extended to the object location task. These findings suggest that topological pattern separation task is particularly sensitive to early stage of AD. Notably, Tg2576 mice do not exhibit elevated amyloid beta levels before 6 months (Kawarabayashi et al., 2001), indicating that these cognitive deficits occur before significant amyloid accumulation. However, we previously reported that Tg2576 mice show aberrant epileptiform activity as early as 1.5 months (B Szabo et al., 2023), possibly reflecting the hyperexcitability of dentate gyrus granule cells reported by Kim and colleagues, in association with contextual pattern separation deficits (Kim et al., 2021).

In the object location test, 4 and 6 mo Tg2576 mice could detect that an object was moved, but lost this ability by 9 months. This contrasts with a study showing intact memory in 16 mo Tg2576 mice (Good and Hale, 2007). However, our protocol included an interval of 24 h delay between the sampling/learning and testing phases, compared to their 2 min delay, and we used females while they tested males (Good and Hale, 2007). As in patients (review in Li and Singh, 2014), disease progression differs according to sex in several mouse models of AD (King et al., 1999; Clinton et al., 2007; Granger et al., 2016; Richetin et al., 2017b). From 12 months, Tg2576 females show greater reference memory deficits compared to males at comparable amyloid load (Schmid et al., 2019).

To assess finer spatial cognitive ability, we used a metric pattern separation task. From 6 months of age, Tg2576 mice, unlike controls, failed to detect spatial changes altering object metric relationships. In rodents, such deficits are typically linked to dorsal hippocampal lesions (Goodrich-Hunsaker et al., 2005). Moreover, disconnecting the hippocampus from the entorhinal cortex prevents the detection of these changes, indicating that hippocampal-entorhinal interactions are involved in detecting spatial changes (Parron et al., 2006). Importantly, these brain regions are among the earliest affected by amyloid pathology in AD patients. In Tg2576 mice, amyloid plaques first appear in the hippocampus by 9 months and later in the cortex at 12 months (Hsiao et al., 1996; Kawarabayashi et al., 2001).

Topological pattern separation involves detecting changes in the overall configuration of objects focusing on their general relationships rather than precise distance (Hunsaker et al., 2009). By 4 months, Tg2576 mice already performed worse than age-matched NTg, and by 6 months, they failed to detect objects rearrangements. This aligns with a study by Kim et al. (2021) showing that 2 mo Tg2576 mice fail to discriminate similar contexts in fear-based tasks. Spatial pattern separation allows to differentiate MCI patients with positive AD-biomarkers from those without, despite comparable performance on standard

cognitive tests (Laczó et al., 2021). Specifically, MCI with positive AD biomarkers (including CSF Abeta1-42, p-Tau) performed worse than both biomarker-negative MCI and cognitively normal participants, suggesting that spatial pattern separation may be sensitive to early AD-related changes (Laczó et al., 2021).

Regarding control animals, it is interesting to note that across all three pattern separation tasks, their performance remained stable between 4 and 9 months age, suggesting that this interval precedes the onset of cognitive aging in wild-type mice.

Although our study was not specifically designed to investigate sex differences, the absence of female data in the morphological analysis and male data in the behavioral analysis may limit the generalizability of our findings. We cannot rule out the possibility that the findings would differ for Tg2576 animals of the other sex. Further studies are needed to explore the influence of sex on cognitive decline and adult neurogenesis in AD, and to determine whether causal links exist.

Adult-born hippocampal neurons contribute to object location and contextual pattern separation in rodents (Clelland et al., 2009; Creer et al., 2010; Goodman et al., 2010; Kesner et al., 2014; Sahay et al., 2011a; Tronel et al., 2012). In AD mouse models, impaired hippocampal adult neurogenesis is an early cellular hallmark, alongside amyloid pathology. In Tg2576 mice, adult neurogenesis deficits are visible at young age (3 mo) and are characterized by reduced survival of newborn cells (50 %) and altered neuronal differentiation (Krezymon et al., 2013). These adult-born granule neurons also exhibit fewer dendritic spines and shorter axonal projections to CA3 (Krezymon et al., 2013). In line with Krezymon et al. (2013), we report here a three-fold reduction in dendritic spine density on adult-born neurons in 4 mo Tg2576 mice, particularly affecting mature spines, of thin and mushroom subtypes. Thus, the fact that hippocampal Tg2576 mice new neurons are less numerous and bear morphological alterations likely hinders their synaptic integration and contributes to memory deficits. In healthy brains, new neurons between 3 and 5 weeks of age undergo a critical period during which they express highly plastic properties and form synapses within hippocampal circuits (Schmidt-Hieber et al., 2004; Ge et al., 2007; Toni et al., 2007). During this time-window, their relative contribution to dentate gyrus function is particularly high, as they display low input specificity and are more easily activated than fully mature neurons (Marín-Burgin and Schinder, 2012). Our data show that overexpression of NeuroD1 promotes the structural maturation of newborn neurons, suggesting that this could enhance their probability of being recruited by entorhinal inputs to support memory processes. To test this hypothesis, memory assessment was performed three weeks after retroviral injection, when the relative contribution of newborn neurons to dentate gyrus function is expected to be particularly high.

Recent findings indicate that the morphological development of adult-born hippocampal neurons *in vivo* is closely linked to the remodeling of mitochondrial networks, including increased mitochondrial biogenesis and marked changes in mitochondrial distribution and morphology (Steib et al., 2014; Beckervordersandforth et al., 2017; Arrázola et al., 2019; Bonzano et al., 2024; Kochan et al., 2024). For instance, mitochondrial function is essential not only for the survival of neurons born in adulthood, but also contributes to their morphological differentiation such as dendritic growth and spine formation (Khacho and Slack, 2018; Coelho et al., 2022). Enhanced mitochondrial fusion during neuronal maturation facilitates dendritic elongation and promotes experience-driven spine remodeling, thereby contributing to the functional integration of new neurons (Kochan et al., 2024).

Mitochondrial dysfunction plays a critical role in AD, as in many neurodegenerative diseases (Panda et al., 2025). Impaired mitochondrial energetics and dynamics, increased oxidative stress, decreased mitophagy and biogenesis are consistent features of mitochondrial abnormalities in AD (Wang et al., 2020; Misrani et al., 2021; Peggion et al., 2024; Skawratananond et al., 2025). Interestingly, recent work revealed mitochondrial dysfunction in both pre- and post-synaptic compartments in cortical tissue from AD patients, potentially contributing to synaptic
dysfunction, a major correlate of cognitive decline in AD (Wang et al., 2023). Here, we report a significant reduction in dendritic spine density, accompanied with impaired mitochondrial biomass in the soma and dendrites of 21-day-old adult-born granule neurons in Tg2576 mice. This aligns with findings in the APPxPS1 mice, where similar deficits were reported in 14- and 21-day-old neurons (Richetin et al., 2017a). In primary neurons, the presence of mitochondria within spines correlates with their development and morphological plasticity (Li et al., 2004), and their stable positioning at the dendritic spine neck is necessary for supporting synaptic plasticity (Rangaraju et al., 2019; Duarte et al., 2023).

We next investigated whether NeuroD1 overexpression could
compensate for adult neurogenesis defects in Tg2576 mice. Our previous
findings demonstrate that the proneural transcription factor NeuroD1
promotes mitochondrial biogenesis and function, and favors the matu-
ration of adult-born neurons in 9 mo APPxPS1 mice (Richetin et al.,
2017a). As expected, NeuroD1 overexpression in cycling hippocampal
progenitors of Tg2576 mice restored both dendritic spine density and
morphology in adult-born neurons. This structural recovery was
accompanied by a normalization of mitochondrial content, bringing it to
levels comparable to control mice. Together, these changes likely
improved the functional integration of adult-born neurons into hippo-
campal circuits. We therefore hypothesized that mice would show
improved performance in topological pattern separation, and indeed,
NeuroD1 overexpression successfully rescued the deficits observed in
Tg2576 mice. Notably, this behavioral recovery occurred despite
transduction being restricted to a limited sub-population of newborn
cells arising from cells dividing at the time of retroviral injection. We
have no data indicating that the beneficial effect of NeuroD1 on memory
involves an increase in the number of new neurons. Incidentally, our
previous report showed that NeuroD1 can improve cognitive perfor-
mance without increasing the number of new neurons in APPxPS1 mice
(Richetin et al., 2015). Even a relatively small cohort of functionally
mature, adult-born neurons may exert a substantial influence on
cognitive function during their critical period of enhanced plasticity,
likely through preferential recruitment into the sparse coding network
of dentate gyrus neurons.

This may explain why 9 mo NTg mice retain their ability to perform
object location, metric and topological pattern separation tasks, despite
altered adult hippocampal neurogenesis (Krezymon et al., 2013). It re-
mains unclear why the topological pattern separation task is the first to
be impaired in Tg2576 mice. This suggests that the task imposes a
particularly high demand on the functional integration of adult-born
neurons. In future studies, it will be important to investigate whether
the beneficial effects of NeuroD1 extend to other types of memory that
rely on adult neurogenesis. For instance, it would be particularly
interesting to test whether NeuroD1 can rescue the impairment in
pattern separation of social information that we recently reported in
young Tg2576 mice (3 mo) (Fauré et al., 2025). To further evaluate the
therapeutic potential of NeuroD1 at different stages of disease progres-
sion, future experiments should also include testing of older animals.

One limitation of NeuroD1 is its short-lasting effect, as the supply of
highly plastic newborn neurons targeted by NeuroD1 will be available
for memory encoding when they are in their critical period, calling for
repeated injections over time. We focused on targeting proliferative
neural stem cells in the adult hippocampus. However, an alternative
strategy could involve targeting non-dividing neuronal precursors that
persist into adulthood in a state of arrested maturation (Bonfanti et al.,
2024). These late-maturing neurons could serve as a reservoir of highly
plastic cells, capable of being modified by experience to integrate neural
circuits and support memory. Further studies will be needed to explore
the functional contribution of these cells to adult brain plasticity and
cognitive functions. An additional avenue worth exploring is suggested
by studies showing that interventions like physical exercise enhance
adult neurogenesis (van Praag et al., 1999) and potentiate reciprocal
interactions between maturation of adult-born neurons and

mitochondria (Steib et al., 2014). Moreover, pharmacological inter-
vention with Mdivi, a mitochondrial fission inhibitor, has demonstrated
neuroprotective effects in an AD context (Wang et al., 2017; Misrani
et al., 2021). These findings suggest that investigating whether Mdivi
can increase the density of mitochondria in new neurons and compen-
sate for cognitive deficits would be worthwhile.

Overall, our behavioral findings demonstrate that distinct pattern separation paradigms can uncover memory deficits at progressive stages of AD pathology in Tg2576 mice. Notably, topological pattern separation detects early memory deficits, highlighting its potential as a valuable tool for the early detection of behavioral signs of AD. Moreover, the enhancement of mitochondrial content in adult-born neurons of Tg2576 mice was closely associated with the rescue of dendritic spine density and the restoration of performance in the topological pattern separation task. These findings provide compelling evidence that proper mitochondrial content and distribution in adult-born hippocampal neurons sustains neuronal maturation but also ameliorate cognitive deficits in AD mouse models. Altogether, our findings highlight the essential role of hippocampal adult-born neurons during the early stages of AD-related memory decline, pointing to their potential as early therapeutic targets.

Supplementary data to this article can be found online at https://doi.org/10.1016/j.nbd.2025.107158.

CRediT authorship contribution statement

**Trinovita Andraini:** Writing – review & editing, Writing – original draft, Project administration, Formal analysis, Data curation. **Lola MP Fauré:** Writing – review & editing, Formal analysis, Data curation. **Lionel Mouledous:** Writing – review & editing, Formal analysis, Data curation. **Sébastien Gauzin:** Writing – review & editing, Formal analysis, Data curation. **Zahra Ghasemi:** Writing – review & editing, Visualization, Data curation. **Camille Lejards:** Data curation. **Cédrick Florian:** Writing – review & editing, Formal analysis, Data curation. **Pascale Belenguer:** Writing – review & editing, Funding acquisition. **Marie-Christine Miquel:** Writing – review & editing, Writing – original draft, Supervision, Project administration, Methodology, Funding acquisition, Conceptualization. **Claire Rampon:** Writing – review & editing, Writing – original draft, Supervision, Project administration, Funding acquisition, Formal analysis, Data curation, Conceptualization.

Declaration of generative AI and AI-assisted technologies in the
writing process

During the preparation of this work the author(s) used ChatGPT (Open AI) and DeepL in order to improve the readability and language of the manuscript. After using this tool/service, the authors reviewed and edited the content as needed and take full responsibility for the content of the published article.

Funding

This work was supported by the Centre National de la Recherche Scientifique, the University of Toulouse 3, by Association France Alzheimer (AAP SM 2015 #377 to CR and MCM) and the Fédération de Recherche sur le Cerveau (AAP 2018 to CR and MCM).

Declaration of competing interest

The authors have nothing to declare.

Acknowledgements

The authors thank A Deleau, P Petsophonsakul and T Geraud for
technical help, S Pech for animal care, and L Roybon and Y Pomeshchik
for generous gift of the viruses. The authors greatly acknowledge the
Mouse Behavioral Core (MBC- CBI -ANEXPLO, Toulouse, France) for its
expertise and assistance in setting up behavioral apparatus and pro-
cedures, the CBI mouse facility from ANEXPLO Toulouse for housing
mice and Toulouse Réseau Imagerie, FRBT-CBI for the microscopic
platform.

Data availability

Data will be made available on request.

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