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. 2025 Mar 11;13:RP101173. doi: 10.7554/eLife.101173

Translatome analysis reveals cellular network in DLK-dependent hippocampal glutamatergic neuron degeneration

Erin M Ritchie 1,2, Dilan Acar 1, Siming Zhong 1, Qianyi Pu 1, Yunbo Li 1, Binhai Zheng 3, Yishi Jin 1,3,4,
Editors: Moses V Chao5, Sacha B Nelson6
PMCID: PMC11896613  PMID: 40067879

Abstract

The conserved MAP3K12/Dual Leucine Zipper Kinase (DLK) plays versatile roles in neuronal development, axon injury and stress responses, and neurodegeneration, depending on cell-type and cellular contexts. Emerging evidence implicates abnormal DLK signaling in several neurodegenerative diseases. However, our understanding of the DLK-dependent gene network in the central nervous system remains limited. Here, we investigated the roles of DLK in hippocampal glutamatergic neurons using conditional knockout and induced overexpression mice. We found that dorsal CA1 and dentate gyrus neurons are vulnerable to elevated expression of DLK, while CA3 neurons appear less vulnerable. We identified the DLK-dependent translatome that includes conserved molecular signatures and displays cell-type specificity. Increasing DLK signaling is associated with disruptions to microtubules, potentially involving STMN4. Additionally, primary cultured hippocampal neurons expressing different levels of DLK show altered neurite outgrowth, axon specification, and synapse formation. The identification of translational targets of DLK in hippocampal glutamatergic neurons has relevance to our understanding of selective neuron vulnerability under stress and pathological conditions.

Research organism: Mouse

Introduction

The mammalian Mitogen Activated Protein Kinase Kinase Kinase (MAP3K12) Dual Leucine Zipper Kinase (DLK) is broadly expressed in the nervous system from early development to mature adults. DLK exerts its effects primarily through signal transduction cascades involving downstream MAP2Ks (MKK4, MKK7) and MAPKs (JNK, p38, ERK), which then phosphorylate many proteins, such as transcription factors including c-Jun, to regulate cellular responses (Asghari Adib et al., 2018; Hirai et al., 2006; Huang et al., 2017; Itoh et al., 2009; Jin and Zheng, 2019; Tedeschi and Bradke, 2013). In cultured neurons, DLK is localized to axons (Hirai et al., 2005; Lewcock et al., 2007), dendrites (Pozniak et al., 2013), and the Golgi apparatus (Hirai et al., 2002). DLK is also associated with transporting vesicles, which are considered platforms for DLK to serve as a sensor of neuronal stress or injury (Holland et al., 2016; Tortosa et al., 2022). Despite broad expression, functional investigations of DLK have been limited to a few cell types under specific conditions.

Constitutive DLK knockout (KO) mice, generated by removing the N-terminus of DLK, including the ATP binding motif of the kinase domain (Hirai et al., 2006), or by deleting the entire kinase domain (Ghosh et al., 2011), die perinatally. The development of the embryonic nervous system is largely normal, with mild defects in radial migration and axon track formation in the developing cortex (Hirai et al., 2006) and neuronal apoptosis during development of spinal motor neurons and dorsal root ganglion (DRG) neurons (Ghosh et al., 2011; Itoh et al., 2011). Selective removal of DLK in layer 2/3 cortical neurons starting at E16.5 results in increased dendritic spine volume (Pozniak et al., 2013). Induced deletion of DLK in adult mice causes no obvious brain structural defects; synapse size and density in hippocampus and cortex appear unaltered, although basal synaptic strength is mildly increased (Pozniak et al., 2013). In contrast, under injury or stress conditions, DLK exhibits critical context-specific roles. In DRG neurons, DLK is required for nerve growth factor withdrawal induced death, promotes neurite regrowth, and is also involved in retrograde injury signaling (Ghosh et al., 2011; Holland et al., 2016; Itoh et al., 2009; Shin et al., 2012). In a spinal cord injury model, DLK is required for Pten deletion-induced axon regeneration and sprouting as well as spontaneous sprouting of uninjured corticospinal tract neurons (Saikia et al., 2022). In optic nerve crush assay, DLK is necessary for Pten deletion-induced axon regeneration of retinal ganglion cells (RGC), but also contributes to injury-induced RGC death (Watkins et al., 2013). In a mouse model of stroke, increased DLK expression is associated with motor recovery following knockdown of the CCR5 chemokine receptor (Joy et al., 2019). These studies reveal critical roles of DLK in development, maintenance, and repair of neuronal circuits.

DLK is known to be expressed in hippocampal neurons (Blouin et al., 1996; Hirai et al., 2005; Mata et al., 1996). Loss of DLK, either constitutively or in adult animals, causes no discernable effect on hippocampal morphology (Hirai et al., 2006; Pozniak et al., 2013). Microarray-based gene expression analysis did not detect significant changes associated with loss of DLK in the hippocampus (Pozniak et al., 2013). However, following exposure to kainic acid, loss of DLK, or preventing phosphorylation of the downstream transcription factor c-Jun, significantly reduces neuron death in hippocampus (Behrens et al., 1999; Pozniak et al., 2013). Additionally, elevated levels of p-c-Jun are observed in hippocampus of patients with Alzheimer’s disease (Le Pichon et al., 2017). Induced human neurons treated with ApoE4, a prevalent ApoE variant associated with Alzheimer’s disease, also show upregulation of DLK, which leads to enhanced transcription of APP and thus Aβ levels (Huang et al., 2017). These data suggest that transcriptional changes downstream of DLK may be an important aspect of its signaling in hippocampal neuron degeneration under pathological conditions.

Here, we investigate the DLK-dependent molecular and cellular network in hippocampal glutamatergic neurons, which show selective vulnerability in Alzheimer’s disease, ischemic stroke, and excitotoxic injury. Using DLK conditional knockout and overexpression mice, we reveal hippocampal regional differences in neuronal death upon elevated DLK signaling. We describe translational changes in hippocampal glutamatergic neurons using RiboTag-seq analysis. We show that the key transcription factor c-Jun and a member of the stathmin family, STMN4, display DLK-dependent translation. Our analyses on hippocampal tissues and cultured neurons support the conclusion that the DLK-dependent signaling network has important roles in the regulation of microtubule homeostasis, neuritogenesis, and synapse formation.

Results

DLK conditional knockout in differentiating and mature glutamatergic neurons does not alter gross morphology of hippocampus

As a first step to define the roles of DLK in hippocampal glutamatergic neurons, we verified DLK expression (encoded by Map3k12) in hippocampal tissue by RNAscope analysis. We observed strong signals in the glutamatergic pyramidal cells and granule cells in P15 mice (Figure 1—figure supplement 1A), consistent with prior in situ data (Blouin et al., 1996; Lein et al., 2007; Mata et al., 1996). To selectively delete DLK in glutamatergic neurons, we generated Slc17a7Cre/+;Map3k12fl/fl mice (DLK(cKO)). Map3k12fl/fl have LoxP sites flanking the exon encoding the initiation ATG and the first 149 amino acids (Figure 1—figure supplement 1C; Chen et al., 2016; Li et al., 2021; Saikia et al., 2022). In hippocampus Slc17a7Cre (encoding VGLUT1) express Cre recombinase strongly in CA3 and in a subset of pyramidal neurons close to stratum oriens in CA1 at P4, with broad expression in both CA1 and CA3 by P14 (Harris et al., 2014). In dentate gyrus, expression of Slc17a7Cre begins in neurons nearer the molecular layer around P4, with expression spreading towards the polymorph layer gradually during the first two postnatal months. By western blot analysis of hippocampal protein extracts, we found that full-length DLK protein was significantly reduced in DLK(cKO) (Figure 1A and B). The DLK antibody also detected a protein product of lower molecular weight at much reduced levels (Figure 1—figure supplement 1B). As Map3k12 mRNA lacking the floxed exon was expressed (Figure 1—figure supplement 1C), this lower-molecular weight protein could be produced by using a downstream alternative start codon (Figure 1—figure supplement 1C1), but would lack the N-terminal palmitoylation motif and ATP-binding site that are essential for DLK activity (Holland et al., 2016; Huntwork-Rodriguez et al., 2013). These data provide validation for knockout of functional DLK protein in hippocampal glutamatergic neurons in DLK(cKO) mice.

Figure 1. Deletion of DLK in postmitotic glutamatergic neurons does not alter gross morphology of hippocampus.

(A) Western blot of DLK and β-actin in protein extracts of hippocampal tissue of Slc17a7Cre/+;Map3k12fl/fl and Map3k12fl/fl littermate controls (age P60, each lane representing individual mice, N=3 mice/genotype). (B) Quantification of DLK protein level normalized to β-actin. Statistics: Unpaired t-test, *** p<0.001. Error bars represent SEM. (C) Confocal z-stack (max projection) images of NeuN immunostaining of coronal sections of the dorsal hippocampus in P15 and P60 mice of genotype indicated, respectively. Dashed boxes in CA1 pyramidal layers are enlarged below. Scale bar, 1000 μm in hippocampi; 100 μm in CA1 layer. (D) Quantification of CA1 pyramidal layer thickness. Each dot represents averaged thickness from 3 sections per mouse; N≥4 mice/genotype per timepoint. Statistics: Two-way ANOVA with Holm-Sidak multiple comparison test; ns, not significant. Error bars represent SEM. (E) Confocal z-stack (max projection) images of Tuj1 immunostaining of hippocampus CA1, CA3, and DG regions in control and Slc17a7Cre/+;Map3k12fl/fl mice (age P60). Dashed outlines mark ROI (region of interest) for fluorescence intensity quantification. Scale bar, 100 μm. (F, G, H) Tuj1 mean fluorescence intensity (MFI) after thresholding signals in dendritic regions in each hippocampal area. Each dot represents averaged intensity from 3 sections per mouse; N=4 control, 5 Slc17a7Cre/+;Map3k12fl/fl. Statistics: Unpaired t-test. ns, not significant. Error bars represent SEM.

Figure 1—source data 1. Original western blots for images shown in Figure 1A.
Figure 1—source data 2. PDF showing original western blots for images shown in Figure 1A, along with relevant bands and genotypes.
Original membranes corresponding to Panel A. Molecular weights shown using PageRuler Plus Prestained Protein Ladder. See Figure 1—figure supplement 1—source data 2 for more details. Each lane represents a separate mouse. Lanes 1–3 show control samples, lanes 4–6 show DLK(cKO).

Figure 1.

Figure 1—figure supplement 1. Additional evidence for expression levels of DLK and effects on hippocampal morphology at 1 year of age.

Figure 1—figure supplement 1.

(A) Confocal images of Map3k12 (DLK) and Slc17a7 (VGLUT1) RNAscope analysis in hippocampal glutamatergic neurons at P15. Scale bar 1000 μm, 10 μm zoomed ROI. (B) Western blot of DLK and β-actin from protein extracts of hippocampal tissue of genotype indicated (age P60, each lane representing individual mice, N=3 mice/genotype). Arrow points to faint band of lower molecular weight in DLK(cKO) that is visible only under longer exposure, which may represent N-terminal truncated DLK produced using an alternative start codon (see C1). (C) IGV visual representation of RiboTag reads of Map3k12 (DLK) in Slc17a7Cre/+ and Slc17a7Cre/+;Map3k12fl/fl, showing that mRNA for the floxed exon is reduced to ~1/3 level of control, while mRNA for other exons remained at a similar level as control. Dark blue illustration shows Map3k12 exon-intron structure, with pink triangles denoting loxP sites. Height of reads (y-axis) in gray or blue represents number of reads for the respective sequence. (C1) Enlarged view of the dashed box in C, corresponding to the floxed exon and exons encoding the kinase domain shown in orange with red marking ATP binding site and green marking DLK palmitoylation site. Start ATG shown in bold, and candidate downstream alternative start ATGs labeled with arrows. (D) Illustration of DLK overexpression transgene. (E,F) Confocal z-stack images of NeuN immunostaining and DAPI of coronal sections of dorsal hippocampus in mice of genotype indicated, with enlarged view of CA1, CA3, and DG (dashed boxes, respectively). ~1-year-old control and Slc17a7Cre/+;Map3k12fl/fl mice for (E); 44–46 weeks old, control and Slc17a7Cre/+;H11-DLK(iOE)/+ mice for (F). Scale bar hippocampus 1000 μm, enlarged view 50 μm. (G, H, I) Quantification of cross-sectional area from CA1, CA3, or DG in dorsal hippocampus, respectively (as outlined in Figure 1—figure supplement 2A and C). Data points represent individual mice, averaged across 3 sections per mouse, N≥3 mice/genotype. Statistics: One way ANOVA with Dunnett’s multiple comparison test. ns, not significant; **** p<0.0001. Error bars represent SEM.
Figure 1—figure supplement 1—source data 1. Original western blots for images shown in Figure 1—figure supplement 1B.
Figure 1—figure supplement 1—source data 2. PDF showing original western blots for images shown in Figure 1—figure supplement 1B, along with relevant bands and genotypes.
Original membranes corresponding to Panel B. Molecular weights shown using PageRuler Plus Prestained Protein Ladder. 10 min exposure (uncut membrane) was taken prior to 2 min exposure. Following 10 min exposure, membrane was cut and reprobed for DLK for 2 min exposure. Each lane represents a separate mouse. Lanes 1–3 show control samples, lanes 4–6 show DLK(cKO).
Figure 1—figure supplement 2. Hemibrain images across timepoints.

Figure 1—figure supplement 2.

Shown are lower magnification confocal images of NeuN staining of coronal sections of mice of genotype and age indicated. (A) ~1-year-old control and Slc17a7Cre/+;Map3k12fl/fl animals. (B) P10, P15, and P60 control and Slc17a7Cre/+;H11-DLK(iOE)/+ nimals. P60 tissue sections were stained at different time from those at P10, P15. (C) ~44–46 week old control and Slc17a7Cre/+;H11-DLK(iOE)/+ animals. Arrows point to cortical thinning and ventricle expansion observed in some animals. Scale bar: 1000 μm.

The DLK(cKO) mice were indistinguishable from control littermate mice in behavior and appearance from birth to about one year of age. We examined tissue sections of hippocampus in P15 and P60 mice. Hippocampal sections stained with NeuN, a marker of neuronal nuclei (Mullen et al., 1992), showed no significant difference in overall position of neuronal soma or thickness of the CA1 pyramidal cell layer at either timepoint (Figure 1C and D). Neuronal morphology visualized by immunostaining with Tuj1, labeling neuron-specific β-III tubulin, also showed no detectable differences in the pattern and intensity of microtubules in DLK(cKO) mice, compared to control (Figure 1E–H). Gross morphology of hippocampus and surrounding tissues in 1-year-old DLK(cKO) mice was indistinguishable from controls (Figure 1—figure supplement 1E, G-I, Figure 1—figure supplement 2A). These results show that DLK does not have essential roles in post-mitotic hippocampal glutamatergic neuron maintenance.

Increasing expression levels of DLK leads to hippocampal neuron death, with dorsal CA1 neurons showing selective vulnerability

Several studies have reported that DLK protein levels increase under a variety of conditions, including optic nerve crush (Watkins et al., 2013), NGF withdrawal (~twofold; Huntwork-Rodriguez et al., 2013; Larhammar et al., 2017), and sciatic nerve injury (Larhammar et al., 2017). Induced human neurons show increased DLK abundance about ~fourfold in response to ApoE4 treatment (Huang et al., 2019). Increased expression of DLK can lead to its activation through dimerization and autophosphorylation (Nihalani et al., 2000). We thus asked how increased DLK signaling affects hippocampal glutamatergic neurons. We previously described a transgenic mouse, H11-DLK(iOE), which allows Cre-dependent DLK overexpression (Li et al., 2021). The DLK transgene is coexpressed with tdTomato through a T2A peptide (Figure 1—figure supplement 1D). By RNAscope analysis, compared to control, we observed increased Map3k12 mRNAs in glutamatergic neurons in CA1, CA3, and DG at P15 in Slc17a7 Cre/+;H11-DLK(iOE)/+ mice (referred to as DLK(iOE)) (Figure 2—figure supplement 1A and B). By immunostaining hippocampal sections with anti-DLK antibodies, we observed increased protein levels particularly in regions with pyramidal neuron dendrites in DLK(iOE), compared to control mice (Figure 2—figure supplement 1C–E). Additional analysis at the mRNA level (Supplementary file 2 WT vs DLK(iOE) DEGs) and at the protein level (Figure 4—figure supplement 1E) suggest that the increase in DLK abundance was around three times the control level. The localization patterns of DLK protein appeared to vary depending on region of hippocampus and age of animals in both control and DLK(iOE) mice (Figure 2—figure supplement 1C).

DLK(iOE) mice were born normally, and developed noticeable progressive motor deficits around four months of age, which became worse by one year of age. We stained brain sections for NeuN at P10, P15, P60, and 1 year of age and observed a progressive reduction in brain size of these mice, compared to controls (Figure 1—figure supplement 2B and C). At P10, the dorsal hippocampus in DLK(iOE) was indistinguishable from control (Figure 2A, B, Figure 1—figure supplement 2B). By P15, the DLK(iOE) mice showed significant thinning of the CA1 pyramidal layer. We detected increased TUNEL staining signals in CA1 pyramidal layer, compared to control (Figure 2—figure supplement 3F and G). By P60, most CA1 pyramidal neurons were lost, while DG began to show thinning, which continued to worsen at 1 year of age (Figure 2A, B, Figure 1—figure supplement 1F, I, Figure 1—figure supplement 2B and C). In contrast, neurons in CA3 appeared less affected, even at 1 year of age (Figure 2A, Figure 1—figure supplement 1F, H, Figure 1—figure supplement 2C). Additionally, in P60, dorsal CA1 showed significantly fewer surviving neurons, while ventral CA1 pyramidal layer thickness appeared more similar to control than dorsal regions (Figure 2—figure supplement 2A and B). Neuronal death generally induces reactive astrogliosis. We stained for GFAP, a marker of astrocyte reactivity. We found increased GFAP staining in DLK(iOE), specifically in CA1 at P15, and at P60 in CA1 and DG, but not as strongly in CA3, compared to control mice (Figure 2—figure supplement 3A–D). We also stained for IBA1, a marker of microglia, and found that DLK(iOE) mice showed increased IBA1 staining around the CA1 region, compared to control mice (Figure 2—figure supplement 3E). Microglia appeared ramified in control mice and more reactive-looking in DLK(iOE) mice (Figure 2—figure supplement 3E). Together, these data reveal that dorsal CA1 neurons show vulnerability to elevated DLK expression, while CA3 neurons appear less vulnerable to DLK overexpression.

Figure 2. Induced DLK overexpression in hippocampal glutamatergic neurons causes degeneration of CA1 neurons.

(A) Confocal z-stack (max projection) images of NeuN immunostaining of coronal sections from dorsal hippocampus in P10, P15, and P60 mice of genotype indicated. Dashed boxes mark CA1 pyramidal layers enlarged below. P60 images shown under different settings compared to P10 and P15 due to older staining. Scale bar, 1,000 μm in hippocampi; 100 μm in CA1 layer. (B) Quantification of CA1 pyramidal layer thickness. Data points represent averaged measurement from 3 sections per mouse, N≥4 mice/genotype at each timepoint. Statistics: Two-way ANOVA with Holm-Sidak multiple comparison test. ns, not significant; *** p<0.001; **** p<0.0001. Error bars represent SEM.

Figure 2.

Figure 2—figure supplement 1. Evidence for induced DLK expression visualized at RNA and protein levels.

Figure 2—figure supplement 1.

(A) Confocal z-stack images of Slc17a7 and Map3k12 mRNAs at P15 in control and Slc17a7Cre/;H11-DLK(iOE)/+ mice. Scale bar: 1000 μm. Inset shows single slice image of CA1 neurons, with dashed line showing individual nuclei as used for quantification. Scale bar: 10 μm. (B) Quantification of RNAscope puncta shown as ratio of Map3k12 to Slc17a7 within individual CA1 neuron nuclei. Data points represent individual mice, averaged across 3 sections per mouse, ≥50 cells per genotype, N=5, 3 mice. Statistics: Mann-Whitney U test. ** p<0.01. Error bars represent SEM. (C) Confocal z-stack images of control and Slc17a7Cre/+;H11-DLK(iOE)/+ mice immunostained for DLK protein (P15, P60,~1 year) or no primary or LZK antibody control (P15) Dashed boxes are enlarged to the right. Individual strata are labeled in CA1, CA3; stratum pyramidale (SP), stratum radiatum (SR), stratum oriens (SO), stratum lacunosum-moleculare (SLM), stratum lucidum (SL). Scale bar 500 μm in hippocampi, 100 μm in CA1 and CA3. (D, E) Quantification of DLK mean fluorescence intensity from all layers in CA1, CA3, and DG at P10 (D) and P15 (E). N=4 mice/genotype for each timepoint. Statistics: Unpaired t-test. ns, not significant; * p<0.05. Error bars represent SEM.
Figure 2—figure supplement 2. Regional vulnerability observed with increased DLK expression.

Figure 2—figure supplement 2.

(A) Confocal z-stack images of NeuN immunostaining in ventral hippocampus in control and Slc17a7Cre/+;H11-DLK(iOE)/+ mice (P60). Dashed line regions are enlarged to the right, showing dorsal (posterior) CA1 neurons (top) with some thinning of pyramidal layer in mice with increased DLK, and ventral CA1 neurons (bottom) appearing similar between genotypes. Scale bar: 1000 μm in hippocampi; 100 μm in CA1 layer. (B) Quantification of pyramidal layer thickness across CA1, with CA1 dorsal (anterior) data from Figure 1B. Data points represent individual mice, averaged across 2–3 sections per mouse. Statistics: Unpaired t-test. ns, not significant; **** p<0.0001. Error bars represent SEM. (C) Confocal z-stack images of p-c-Jun immunostaining in dorsal and ventral hippocampus of mice of indicated genotype at P60. Dashed line regions are enlarged to the right. Scale bar: 1000 μm in hippocampi; 100 μm in CA1 layer.
Figure 2—figure supplement 3. Additional evidence for DLK(iOE) induced hippocampal neuron death.

Figure 2—figure supplement 3.

(A) Confocal z-stack imaging of GFAP immunostaining of hippocampus in mice of genotype indicated at P15 and P60, with enlarged view of the dashed boxes for CA1, CA3 shown below. Scale bar: 500 μm in hippocampi, 100 μm in CA1 and CA3. (B–D) Mean fluorescent intensity of GFAP in CA1, CA3, and DG regions (boxed area in A), respectively at P15. N=5, 4 mice, quantified from 3 sections per mouse. Statistics: Unpaired t-test. ns, not significant; * p<0.05. Error bars represent SEM. P15, P60 GFAP animals imaged under separate conditions due to staining at different times. (E) Confocal z-stack images of IBA1 immunostaining of hippocampus in mice of genotype indicated at P15 and P60. Boxed microglia for CA1 and CA3 are enlarged below. Scale bar 100 μm in CA1 and CA3 top, 10 μm in individual microglia bottom. (F) Confocal single-slice images showing TUNEL positive CA1 pyramidal neuron in P15 Slc17a7Cre/+;H11-DLK(iOE)/+ overlapping with tdTomato expressed from DLK(iOE) transgene and pyknotic nuclei (DAPI). Scale bar, 25 μm. (G) Quantification of TUNEL positive neurons in CA1 pyramidal layer in genotype indicated. Data points represent individual mice, averaged across 3 sections per mouse, N=4 mice. Statistics: Unpaired t-test. ** p<0.01. Error bars represent SEM.

DLK dependent translated genes are enriched in synapse formation and function

To gain understanding of molecular changes associated with DLK expression levels in glutamatergic neurons, we next conducted translating ribosome profiling and RNA sequencing (RiboTag profiling) using Rpl22HA mice, which enables Cre-dependent expression of an HA tagged RPL22, a component of the ribosome, from its endogenous locus (Sanz et al., 2009). We generated Slc17a7Cre/+;H11-DLK(iOE)/+;Rpl22HA/+, Slc17a7Cre/+;Map3k12fl/fl;Rpl22HA/+, and their respective Slc17a7Cre/+;Rpl22HA/+ sibling controls. We made protein extracts from dissected hippocampi of P15 mice, a time point when some CA1 neuron degeneration induced by DLK overexpression was visible. We obtained affinity purified HA-immunoprecipitates with the associated actively translated RNAs (Figure 3—figure supplement 1A) (n=3 DLK(iOE)/3 WT, n=4 DLK(cKO)/4 WT) and verified purity of the isolated RNA samples by qRT-PCR (Figure 3—figure supplement 1B). We mapped >24 million deep sequencing reads per sample to approximately 14,000 genes. We found 260 genes that were differentially expressed and translated in DLK(iOE) neurons, including 114 up- and 146 down-regulated genes, compared to control (Figure 3A, using the cutoff of padj <0.05, Supplementary file 2 WT vs DLK(iOE) DEGs). 36 genes showed significant changes in DLK(cKO) neurons, including 12 up- and 24 down-regulated genes, compared to control (Figure 3B, padj <0.05, Supplementary file 1 WT vs DLK(cKO) DEGs). Among genes with statistically significant changes, 17 were detected in both DLK(cKO) and DLK(iOE) (Figure 3—figure supplement 1C), of which 13 were upregulated in DLK(iOE) and downregulated in DLK(cKO), and 3 were downregulated in DLK(iOE) and upregulated in DLK(cKO) (Figure 3—figure supplement 1D and E). The most significant differentially expressed genes included Jun, encoding the DLK downstream transcription factor c-Jun, Stmn4, encoding a member of the Stathmin tubulin-binding protein family, and Sh2d3c, encoding a SH2-domain cytoplasmic signaling protein (Dodelet et al., 1999; Vervoort et al., 2007). One gene, Slc25a17, a peroxisomal transporter for cofactors FAD, CoA, and others (Agrimi et al., 2012) and broadly implicated in oxidative stress, was upregulated in both DLK(cKO) and DLK(iOE), compared to control, though the relevance of this change may require further investigation. To systematically compare whether DLK regulates the translatome in a coordinated manner, we performed rank-rank hypergeometric overlap (RRHO) analysis (Plaisier et al., 2010) on the entire translated mRNAs detected in DLK(iOE) and DLK(cKO). We found that RRHO detected significant overlap in genes that were upregulated in DLK(iOE) and downregulated in DLK(cKO) as well as the reverse (Figure 3C), supporting a conclusion that expression of many of the same genes are dependent on DLK.

Figure 3. Differentially expressed genes revealed by RiboTag analysis of hippocampal glutamatergic neurons in DLK(cKO) and DLK(iOE) mice.

(A) Volcano plot showing RiboTag analysis in Slc17a7Cre/+;H11-DLK(iOE)/+;Rpl22HA/+vs Slc17a7Cre/+;Rpl22HA/+ (age P15). 260 genes (red) show differential expression with adjusted p-values <0.05 in Slc17a7Cre/+;H11-DLK(iOE)/+, compared to control; names of genes with p<1E-10 are labeled. (B) Volcano plot showing RiboTag analysis in Slc17a7Cre/+;Map3k12fl/fl;Rpl22HA/+ vs Slc17a7Cre/+;Rpl22HA/+ (age P15). 36 genes (blue) show differential expression with adjusted p-values <0.05; names of genes with p<1E-10 are labeled. (C) Rank-rank hypergeometric overlap (RRHO) comparison of gene expression in DLK(cKO) and DLK(iOE) RiboTag datasets shows enrichment of similar genes when DLK is low or high, respectively. Color represents the -log transformed hypergeometric p-values (blue for weaker p-value, red for stronger p-value). (D, E) Gene ontology (GO) analysis of significantly up- or down-regulated genes in hippocampal glutamatergic neurons of DLK(iOE) mice compared to the control. Colors correspond to p-values; circle size represents fold enrichment for the GO term; X position shows # of genes significantly enriched in the GO term. (F) SynGO sunburst plot shows enrichment of 42 differentially expressed genes from hippocampal glutamatergic neurons of DLK(iOE) mice, with color corresponding to significance. (G, H) Pie charts show distribution of the 42 synaptic genes up- or down- regulated in DLK(iOE), respectively, in CA1, CA3, and DG in dorsal hippocampus, based on in situ data (P56) in the Allen Mouse Brain Atlas.

Figure 3.

Figure 3—figure supplement 1. Evidence for RiboTag immunoprecipitated samples and additional analysis of genes showing differential dependence on DLK expression levels.

Figure 3—figure supplement 1.

(A) Western blot of HA-tagged Rpl22 immunoprecipitates. (B) qRT-PCR analysis of Slc17a7 (glutamatergic neurons), Wfs1 (CA1), Vgat (inhibitory neurons), Gfap (astrocytes) shows expression of transcripts for glutamatergic neurons and depletion of non-glutamatergic neuron transcripts. N=3 biological replicates, data shown as expression fold change for marker genes in immunoprecipitated glutamatergic neuron RNAs relative to whole hippocampal RNAs, normalized to Gapdh. (C) Venn diagram showing overlap of statistically significant differentially expressed genes by RiboTag analysis of glutamatergic neurons in DLK(cKO) and DLK(iOE). (D, E) Heatmaps of the differentially expressed genes in glutamatergic neurons in DLK(cKO) and DLK(iOE). Columns represent expression levels in individual mice; rows represent individual genes, and the right-hand labels the RiboTag dataset where a given gene shows statistical significance. Data were normalized by row, with color keys shown above the heatmap. (F, G, H, I) Pie charts show distribution of differentially expressed genes detected in DLK(iOE) or DLK(cKO) in hippocampal neurons, based on in situ data in the Allen Mouse Brain Atlas (P56 mice). (J) SynGO sunburst plot shows enrichment of 10 differentially expressed genes from hippocampal glutamatergic neurons of DLK(cKO) mice, with color corresponding to significance. (K, L) GSEA enrichment plots show distribution of CA1 or CA3 genes from higher expression in WT to higher expression in DLK(cKO). Entire list of translated genes is represented by red to blue spectrum, genes expressed higher in WT in red, genes expressed higher in DLK(cKO) in blue (Supplementary file 1. WT vs DLK(cKO) DEGs). Vertical black lines (middle) represent genes in the respective gene set and where each lies along the spectrum from genes higher in WT to genes higher in DLK(cKO). Gene set for (K) CA1 genes (enriched in CAMK2 vs GRIK4 neurons); (L) CA3 genes (enriched in GRIK4 vs CAMK2 neurons) (Supplementary file 3 CamK2 Grik4 enriched genes). Green line reflects running enrichment score (negative value representing CA1 genes tending to be more expressed in DLK(cKO)). Dashed box highlights region contributing to enrichment score. (K) Normalized enrichment score –1.89. False discovery rate q-value: 0.000; (L) Normalized enrichment score 1.42. False discovery rate q-value: 0.030.
Figure 3—figure supplement 1—source data 1. Original western blots for images shown in Figure 3—figure supplement 1A.
Figure 3—figure supplement 1—source data 2. PDF showing original western blot for image shown in Figure 3—figure supplement 1A, along with relevant band and genotype.
Original membranes corresponding to Panel A. Molecular weights shown using Precision Plus Protein Dual Color Ladder. Rpl22-HA is 23 kDa protein.
Figure 3—figure supplement 2. Levels of c-Jun and p-c-Jun show dependency on expression levels of DLK.

Figure 3—figure supplement 2.

(A,B) Confocal z-stack images of c-Jun (A) and p-c-Jun (B) immunostaining in CA1, CA3, and DG in control and Slc17a7Cre/+;H11-DLK(iOE)/+ mice (P10). Dashed lines in corresponding DAPI staining outline region used for quantification. Scale bar 50 μm. Graphs below image panels show quantification of MFI of c-Jun (A) or p-c-Jun nuclei above intensity threshold per 100 μm of pyramidal or granule cell layer (B). Data points represent individual mice. 3 sections per mouse, N=4,5 mice for (A); N=4,4 mice for (B). Statistics: Unpaired t-test. ns, not significant, * p<0.05, ** p<0.01. (C, D) Confocal z-stack images of c-Jun (C) and p-c-Jun (D) immunostaining in CA1, CA3, and DG in control and Slc17a7Cre/+;H11-DLK(iOE)/+ mice (P15). Dashed lines in corresponding DAPI staining outline region used for quantification. Scale bar 50 μm. Graphs below image panels show quantification of MFI of c-Jun (C) or p-c-Jun nuclei above intensity threshold per 100 μm of pyramidal or granule cell layer (D). Data points represent individual mice. 3 sections per mouse, N=7,8 mice for (C); N=3,5 mice for (D). Statistics: Unpaired t-test. ns, not significant; * p<0.05; ** p<0.01; **** p<0.0001. (E) Confocal z-stack images of c-Jun (E) and p-c-Jun (F) immunostaining in CA1, CA3, and DG in control and Slc17a7Cre/+;Map3k12fl/fl mice (P60). Dashed lines in corresponding DAPI staining outline region used for quantification. Scale bar 50 μm. Graphs below image panels show quantification of mean fluorescence intensity (MFI) of c-Jun and p-c-Jun in pyramidal or granule cell layer of each region. Data points represent MFI of individual mice. 3 sections per mouse, N=4,4 mice for (E); N=6, 7 mice for (F). Statistics: Unpaired t-test. ns, not significant; * p<0.05. All error bars represent SEM.

To gain understanding of DLK-dependent signaling network, we performed gene ontology (GO) analysis on the 260 genes differentially translated in DLK(iOE) neurons, as this dataset gave greater ability to detect significant GO terms than using the 36 genes differentially expressed in DLK(cKO). The genes upregulated in DLK(iOE) (114) had enrichment in GO terms related to apoptosis, cell migration, cell adhesion, and the extracellular matrix organization (Figure 3D), whereas the genes downregulated (146) had GO terms related to synaptic communication and ion transport (Figure 3E). Similar GO terms were also identified using the list of genes coordinately regulated by DLK, derived from our RRHO analysis. Among the genes upregulated in DLK(iOE), some were known to be involved in neurite outgrowth (Plat, Tspan7, Hap1), endocytosis or endosomal trafficking (Snx16, Ston2, Hap1), whereas the genes down-regulated in DLK(iOE) included ion channel subunits (Cacng8, Cacng3, Grin2b, Scn1a) and those in exocytosis and calcium related proteins (Doc2b, Hpca, Cadps2, Rab3c, Rph3a). A significant cluster of differentially expressed genes in DLK(iOE) included those that regulate AMPA receptors (Nptx1, Nptxr, Cnih3, Gpc4, Arc, Tspan7) and cell adhesion molecules (Nectin1, Flrt3, Pcdh8, Plxnd1). A further survey using SynGO, a curated resource for genes related to synapse formation and function (Koopmans et al., 2019), revealed 42 of 260 differentially expressed genes in DLK(iOE) showed significant enrichment in synaptic organization and postsynaptic receptor signaling processes (Figure 3F). Conversely, 10 of the 36 differentially expressed genes in DLK(cKO) were annotated to function in similar synaptic processes as in DLK(iOE) (Figure 3—figure supplement 1J). The bioinformatic analysis suggests that increased DLK expression can promote translation of genes related to neurite outgrowth and branching and reduce those related to the maturation and function of synapses.

The hippocampus is comprised of multiple glutamatergic neuron types with distinct spatial patterns of gene expression (Lein et al., 2004). As we observed regional vulnerability to DLK overexpression, we next asked if the differentially expressed genes associated with DLK(iOE) might show correlation to the neuronal vulnerability. We first surveyed the endogenous expression pattern of the 260 significantly changed genes in DLK(iOE) in hippocampus using in situ data from 8-week-old mice from the Allen Brain Atlas (Lein et al., 2007). We found that about a third of the genes downregulated in DLK(iOE) showed enriched expression in CA1 (Figure 3—figure supplement 1G), and some of these genes, including Tenm3, Lamp5, and Mpped1, were up-regulated in DLK(cKO) (Figure 3—figure supplement 1H and I). In comparison, about 50% of the genes upregulated in DLK(iOE) showed comparable expression among hippocampal cell types (Figure 3—figure supplement 1F). Additionally, among the 42 synaptic genes that were differentially expressed in DLK(iOE), a notable portion of the downregulated genes showed enriched expression in CA1 (Figure 3H), while the upregulated genes were expressed in all regions (Figure 3G).

Additionally, we compared our Slc17a7-RiboTag datasets with CamK2-RiboTag and Grik4-RiboTag datasets from 6-week-old wild type mice reported by Traunmüller et al., 2023; GSE209870. We defined a list of genes enriched in CamK2-expressing CA1 neurons relative to Grik4-expressing CA3 neurons (CA1 genes), and those enriched in Grik4-expressing CA3 neurons (CA3 genes) (Supplementary file 3). When compared with the entire list of Slc17a7-RiboTag profiling in our control and DLK(cKO), we found CA1 genes tended to be expressed more in DLK(cKO), compared to control (Figure 3—figure supplement 1K), while CA3 genes showed a slight enrichment in control though the trend was less significant and less clustered towards one genotype (Figure 3—figure supplement 1L). Moreover, many CA1 genes related to cell-type specification, such as Foxp1, Satb2, Wfs1, Gpr161, Adcy8, Ndst3, Chrna5, Ldb2, Ptpru, and Ntm, did not show significant downregulation when DLK was overexpressed. These observations imply that DLK likely specifically down-regulates CA1 genes both under normal conditions and when overexpressed, with a stronger effect on CA1 genes, compared to CA3 genes. Overall, the informatic analysis suggests that decreased expression of CA1 enriched genes may contribute to CA1 neuron vulnerability to elevated DLK, although it is also possible that the observed down-regulation of these genes is a secondary effect associated with CA1 neuron degeneration.

DLK regulates translation of JUN and STMN4

The transcription factor c-Jun is a key downstream factor in DLK and JNK signaling (Hirai et al., 2006; Itoh et al., 2009; Welsbie et al., 2017). Our RiboTag analysis suggests that expression and translation of Jun mRNA to be significantly dependent on DLK expression levels (Figure 3A and B). To further test this observation, we performed immunostaining of hippocampal tissues using an antibody recognizing total c-Jun. In control mice, glutamatergic neurons in CA1 had low but detectable c-Jun immunostaining at P10 and P15, but reduced intensity at P60; those in CA3 showed an overall low level of c-Jun immunostaining at P10, P15, and P60; and those in DG showed a low level of c-Jun immunostaining at P10 and P15, and an increased intensity at P60 (Figure 3—figure supplement 2A, C and E). In DLK(iOE) mice at P10 when no discernable neuron degeneration was seen in any regions of hippocampus, only CA3 neurons showed a significant increase of immunostaining intensity of c-Jun, compared to control (Figure 3—figure supplement 2A). In P15 mice, we observed further increased immunostaining intensity of c-Jun in CA1, CA3, and DG, with the strongest increase (~fourfold) in CA1, compared to age-matched control mice (Figure 3—figure supplement 2C). The overall increased c-Jun staining is consistent with RiboTag analysis. We also analyzed DLK(cKO) mice at P60, and observed a trend for decreased c-Jun in CA3 (Figure 3—figure supplement 2E); the modest effects of DLK(cKO) on c-Jun proteins could be due to detection limitations for low levels of c-Jun. As phosphorylation of c-Jun (p-c-Jun) is known to reflect activation of DLK and JNK signaling (Hirai et al., 2006), we further investigated p-c-Jun levels in these mice. In control mice at P10, P15, only a few neuronal nuclei showed strong staining with p-c-Jun in CA1, CA3 and DG. In DLK(iOE) mice, we observed increased p-c-Jun-positive nuclei in CA1 at P10, and strong increase in CA1 (~tenfold), CA3 (~sixfold), and DG (~eightfold) at P15 (Figure 3—figure supplement 2B and D). The levels of p-c-Jun remained elevated in the surviving neurons in all three regions of DLK(iOE) mice at P60 (Figure 2—figure supplement 2C). In DLK(cKO) mice, p-c-Jun levels in CA3 showed a significant reduction, with the trend of reduced levels in CA1 and DG, compared to control mice (Figure 3—figure supplement 2F, P60). These results are consistent with a conclusion that translation of Jun mRNAs and phosphorylation of c-Jun show dependency on levels of DLK, with CA1 neurons showing higher dependence upon DLK overexpression.

The Stathmin family of proteins is thought to regulate microtubules through sequestering tubulin dimers (Charbaut et al., 2001; Chauvin and Sobel, 2015). This family of proteins includes four genes, all of which were identified in our hippocampal glutamatergic neuron translatome (Figure 4—figure supplement 1A), and only Stmn4 showed significant up-regulation in DLK(iOE) and down-regulation in DLK(cKO), respectively (Figure 3A and B). We verified STMN4 protein expression by western blot analysis of hippocampal protein extracts. In control mice, we detected the levels of STMN4 to peak around P8 (Figure 4—figure supplement 1B, C, F and G). The abundance of STMN4 in DLK(cKO) and DLK(iOE) was subtly altered, which could be due to broad expression of STMN4 in hippocampus masking specific changes in glutamatergic neurons. We thus examined Stmn4 mRNAs in hippocampus by RNAscope. Stmn4 mRNAs were present in glutamatergic neurons across all regions of the hippocampus, with strongest expression in CA1 pyramidal neurons. While Stmn4 mRNA puncta number in these neurons was comparable between DLK(cKO) mice and control, in DLK(iOE) mice, glutamatergic neurons in CA1, CA3, and DG all showed upregulation of Stmn4, compared to control (Figure 4A–C, Figure 4—figure supplement 2A, C). These data support a role of DLK in modulating expression and translation of Stmn4.

Figure 4. Stmn4 and microtubule homeostasis show dependency on the expression levels of DLK.

(A) Confocal single-slice image of RNAscope analysis of Stmn4 and Slc17a7 mRNAs in hippocampal neurons. Dashed circle outlines single nuclei. Scale bar, 10 μm. (B, C) Quantification of the ratio of Stmn4 to Slc17a7 RNAscope puncta in same nuclei of CA1 and CA3 neurons, respectively. N=6,3,3 mice of respective genotypes, quantified from >50 cells per genotype from 4 sections per mouse. Statistics: One way ANOVA with Dunnett’s multiple comparison test, ns, not significant; * p<0.05; ** p<0.01. (D–F) Confocal z-stack (max projection) images of CA1 immunostained for Tuj1, tyrosinated tubulin, and acetylated tubulin, respectively, in control and Slc17a7Cre/+;H11-DLK(iOE)/+ mice of P15. SR: stratum radiatum. (G, H) Normalized mean fluorescence intensity (MFI) of tyrosinated and acetylated tubulin, respectively, after thresholding signals in SR in CA1 (dashed outlines on images in E-F). N=9, 6 mice, 3 sections averaged per mouse in (G); N=6, 4 mice, 3 sections averaged per mouse in (H). (I–K) Confocal z-stack (max projection) images of immunostained CA1 sections for Tuj1, tyrosinated tubulin, and acetylated tubulin, respectively, in control and Slc17a7Cre/+;H11-DLK(iOE)/+ mice of P60. (L, M) Normalized MFI of tyrosinated and acetylated tubulin, respectively, after thresholding signal in SR in CA1 (dashed outlines on images in J-K). N=9, 9 mice, 3 sections averaged per mouse in L; N=6, 6 mice, 3 sections averaged per mouse in M. (N–P) Confocal z-stack (max projection) images of immunostained CA1 sections for Tuj1, tyrosinated tubulin, and acetylated tubulin, respectively, in control and Slc17a7Cre/+;Map3k12fl/fl mice of P60. (Q, R) Normalized MFI for tyrosinated and acetylated tubulin, respectively, after thresholding signal in SR in CA1 (dashed outlines on images in O-P). N=5, 7 mice, 3 sections averaged per mouse in Q; N=6, 7 mice, 3 sections averaged per mouse in R. All tubulin images shown as maximum projection of z-stack. Scale bar, 10 μm. In I-J, arrows point to apical dendrites with elevated immunostaining signal; arrowheads point to thin neurites with elevated signal. Statistics in (G, H, L, M, Q, R): Unpaired t-test. ns, not significant; * p<0.05. All error bars represent SEM.

Figure 4.

Figure 4—figure supplement 1. Stathmin transcript abundance and western blot analysis of DLK, STMN4 in mice aged P10 to 1 yr.

Figure 4—figure supplement 1.

(A) RiboTag analysis of Stathmin family members, shown as transcripts per million (TPM). Differential expression analysis significance shown (padj). ns, not significant; **** p<0.0001. Stmn2 and Stmn4 appear to have comparable reads, however, this includes reads in a retained intron in Stmn2, which increases the reference gene length used for the TPM calculation for Stmn2. The significance of this intron retention may need further study. (B, C) Western blots of protein extracts from hippocampal tissue from P1, P8, P15, P60, and ~1-year-old mice, blotted for DLK, Flag, STMN4, STMN2, and actin in Slc17a7Cre/+;Map3k12fl/fl (B) and Slc17a7Cre/+;H11-DLK(iOE)/+ (C), respectively. Larger molecular weight band of DLK in Slc17a7Cre/+;H11-DLK(iOE)/+ would match the predicted molecular weight of DLK-T2A-tdTomato if T2A-peptide induced ‘self-cleavage’ due to ribosomal skipping is ineffective (Figure 1—figure supplement 1D). (D, E) Relative DLK protein level normalized to actin and P1 control. N=3 mice/genotype. (F, G) Relative STMN4 protein level normalized to actin and P1 control. N=3 mice/genotype. Statistics: Two-way ANOVA with Sidak multiple comparisons test. ns, not significant; * p<0.05. All error bars represent SEM.
Figure 4—figure supplement 1—source data 1. Original western blots for images shown in Figure 4—figure supplement 1B and C.
Figure 4—figure supplement 1—source data 2. PDF showing original western blots for images shown in Figure 4—figure supplement 1B and C, along with relevant bands and genotypes.
Pg.1 Original membranes corresponding to Panel B. Molecular weights shown using PageRuler Plus Prestained Protein Ladder. Each lane represents a separate mouse. Lanes 1,3,5,7,9 show control samples, lanes 2,4,6,8,10 show DLK(cKO) at P1, P8, P15, P60, and 1 year timepoints. Dotted lines indicate locations where membrane was cut and labeled with separate antibodies. Pg.2 Original membranes corresponding to Panel C. Molecular weights shown using Precision Plus Protein Dual Color Ladder. Each lane represents a separate mouse. Lanes 1,3,5,7,9 show control samples, lanes 2,4,6,8,10 show DLK(iOE) at P1, P8, P15, P60, and ~1 year timepoints. Dotted lines indicate locations where membrane was cut and labeled with separate antibodies. Samples were split, with half of each prepped sample loaded onto two membranes (membrane 1&2). Smaller molecular weight band matches expected size of DLK protein (and flag tagged DLK). Larger molecular weight band of DLK in Vglut1Cre/+;H11-DLKiOE/+ would match the predicted molecular weight of DLK-T2A-tdTomato if T2A-peptide induced ‘self- cleavage’ due to ribosomal skipping is ineffective. Pg.3 Original membranes corresponding to Panel C. Molecular weights shown using Precision Plus Protein Dual Color Ladder. Each lane represents a separate mouse. Lanes 1,3,5,7,9 show control samples, lanes 2,4,6,8,10 show DLK(iOE) at P1, P8, P15, P60, and ~1 year timepoints.
Figure 4—figure supplement 2. Additional evidence for Stmn4 and microtubule expression in DLK(cKO) and DLK(iOE) in hippocampus.

Figure 4—figure supplement 2.

(A–D) Confocal single-slice images of Stmn4 and Slc17a7 RNAscope stained sections from (A, B) CA3 and (C, D) DG in DLK(iOE) (A, C) and DLK(cKO) (B, D) mice at P15. Scale bar 10 μm. (E) Confocal z-stack images of Tuj1 immunostaining in CA1, CA3, and DG of mice genotype indicated at P15. Scale bar 50 μm. (F) Confocal z-stack images of MAP2 immunostaining of CA1 pyramidal layer from control and Slc17a7Cre/+;H11-DLK(iOE)/+ mice at P60. Arrows point to apical dendrites with elevated signal. Arrowheads point to thin neurites with elevated signal. Scale bar 10 μm. (G) Normalized MAP2 MFI after thresholding signal in SR (dashed outlines on images in F). N=9, 9 mice, 3 sections averaged per mouse. Statistics: Unpaired t-test. ns, not significant. Error bars represent SEM.

Elevated DLK signaling may disrupt microtubule homeostasis in hippocampal CA1 neurons

Substantial studies from other types of neurons in mice and invertebrate animals have linked DLK signaling with the regulation of microtubule cytoskeleton (Asghari Adib et al., 2018; Jin and Zheng, 2019; Tedeschi and Bradke, 2013). To assess whether DLK affects microtubules in hippocampal glutamatergic neurons, we performed Tuj1 immunostaining. We did not detect obvious changes in DLK(cKO) when compared to controls at P60 (Figure 1E). In DLK(iOE) mice at P15, expression levels and patterns of neuronal microtubules in each region of hippocampus appeared similar to control (Figure 4D, Figure 4—figure supplement 2E), although we found the overall Tuj1 staining pattern at P15 to be less defined and consistent. By P60, many CA1 neurons died and the hippocampus exhibited thinning of all strata within CA1, and the Tuj1 staining pattern became less organized in parallel dendrites in the stratum radiatum (SR) region of CA1 (Figure 4I). Increased Tuj1 staining in thin branches extended in varied directions, with bright staining seen in the apical dendrites near the pyramidal neuron cell body.

Several post-translational modifications of microtubules are thought to correlate with stable or dynamic state of microtubules. To explore whether DLK expression levels affected microtubule post-translational modifications, we performed immunostaining for acetylated tubulin, a modification generally associated with stable, longer-lived microtubules, and tyrosinated tubulin, a terminal amino acid that can be removed and is typically found on dynamic microtubules (Janke and Magiera, 2020). We detected no significant difference in the staining pattern and intensity of either tyrosinated tubulin or acetylated tubulin in DLK(cKO) mice, compared with age-matched control mice (Figure 4N–R). In DLK(iOE) mice at P15, both tubulin modifications showed no significant differences in pattern or intensity in CA1 SR, compared to age-matched control mice (Figure 4E–H), despite neuron death beginning in CA1. By P60, we observed increased staining intensity of acetylated tubulin and tyrosinated tubulin in the apical dendrites of surviving neurons in DLK(iOE) mice, particularly with tyrosinated tubulin staining revealing bright signals on small, thin branches (Figure 4J–M). To discern whether such microtubule modification changes were from neurons, we immunostained tissue sections with antibodies for MAP2, a neuron specific microtubule associated protein. We observed bright MAP2 signal in thin branches extending in varied directions in DLK(iOE) mice, compared to age-matched control mice (Figure 4—figure supplement 2F and G). Together this analysis suggests increased DLK expression may likely alter neuronal microtubule homeostasis and/or integrity.

Increasing DLK expression alters synapses in dorsal CA1

A theme revealed in our hippocampal glutamatergic neuron RiboTag profiling suggests that translation of synaptic proteins may depend on the expression levels of DLK. To evaluate this observation, we examined synapses in the hippocampus by immunostaining for Bassoon, a core protein in the presynaptic active zone, Vesicular Glutamate Transporter 1 (VGLUT1) for synaptic vesicles, and Homer1, a post-synaptic scaffolding protein. In control mice and DLK(cKO) at P60, Bassoon staining in stratum radiatum (SR) of dorsal CA1, where CA3 neurons synapse onto CA1 dendrites, showed discrete puncta that were mostly apposed to the postsynaptic marker Homer1, representing properly formed synapses (Figure 5A). We measured size and density by counting Bassoon and Homer1 puncta and the sites where Bassoon and Homer1 overlap, a proxy for synapses. We detected no significant difference in DLK(cKO), compared to control (Figure 5A–F). To assess effects of DLK overexpression on synapses, we immunostained hippocampal sections from both P10 and P15, with age-matched littermate controls. Quantification of Bassoon and Homer1 immunostaining revealed no significant differences in CA1 SR and CA3 SR and SL in P10 mice of DLK(iOE) and control (Figure 5—figure supplement 2A–F, Figure 5—figure supplement 3A–J). In P15, Bassoon density and size in CA1 SR were comparable in both mice (Figure 5G, H and K), while Homer1 density and size were reduced in DLK(iOE) (Figure 5G, I and L). Overall synapse number in CA1 SR was similar in DLK(iOE) and control mice (Figure 5J). Similar analysis on CA3 SR and SL detected no significant difference from control (Figure 5—figure supplement 3M–V). Staining of VGLUT1 protein showed less discrete puncta than those of Bassoon or Homer1, with small puncta and larger clusters of puncta close together (Figure 5—figure supplement 1A and D). In DLK(cKO) we observed a trend towards an increased number of VGLUT1 puncta (p=0.0653) with no change to puncta size (Figure 5—figure supplement 1A–C). In DLK(iOE) we observed fewer VGLUT1 puncta in SR, consistent with the analysis on Homer1 at P15, with no significant change to puncta size (Figure 5—figure supplement 1D–F). These data reveal that while conditional knockout of DLK may not have a strong effect on glutamatergic synapses, increased expression of DLK leads to mild alteration in the CA1 region at P15, correlating with the onset of CA1 neurodegeneration.

Figure 5. Hippocampal dorsal CA1 glutamatergic neurons show altered synapses following increased DLK expression.

(A) Confocal single-slice images of Bassoon and Homer1 immunostaining in CA1 stratum radiatum (SR) of control and Slc17a7Cre/+;Map3k12fl/fl mice of P60. (B, C) Quantification of Bassoon and Homer1 puncta density, respectively. (D) Quantification of co-localization of Bassoon and Homer1. (E, F) Quantification of Bassoon and Homer1 puncta size. Data points represent average values per mouse from 3 sections. N=7 control, and 8 Slc17a7Cre/+;Map3k12fl/fl mice. Statistics: unpaired t-test or Mann-Whitney U test if not passing normality. ns, not significant. (G) Confocal single-slice images of Bassoon and Homer1 immunostaining in CA1 SR of control and Slc17a7Cre/+;H11-DLK(iOE)/+ mice of P15. (H–I) Quantification of Bassoon and Homer1 puncta density, respectively. (J) Quantification of co-localization of Bassoon and Homer1. (K, L) Quantification of Bassoon and Homer1 puncta size. Data points represent average values per mouse from 3 sections, N=9 control, and 6 Slc17a7Cre/+;H11-DLK(iOE)/+ mice. Statistics: unpaired t-test or Mann-Whitney U test if not passing normality. ns, not significant; ** p<0.01. Scale bars, 5 μm in panel images, and 1 μm in enlarged images. All error bars represent SEM.

Figure 5.

Figure 5—figure supplement 1. VGLUT1 pattern in dorsal CA1 in DLK(cKO) and DLK(iOE).

Figure 5—figure supplement 1.

(A) Confocal single-slice image of VGLUT1 immunostaining of CA1 SR in control and Slc17a7Cre/+;Map3k12fl/fl mice at P60. Scale bar 5 μm, inset scale bar 1 μm. (B, C) Quantification of VGLUT1 puncta density and size. Data points represent averages from individual mice across 3 sections per mouse. N=5 control, and 8 Slc17a7Cre/+;Map3k12fl/fl mice. (D) Confocal single-slice image of VGLUT1 immunostaining of CA1 SR in control and Slc17a7Cre/+;H11-DLK(iOE)/+ mice at P15. Scale bar 5 μm, inset scale bar 1 μm. (E, F) Quantification of VGLUT1 puncta density (E) and size (F). Data points represent averages from individual mice across 3 sections per mouse, N=9 control, and 8 Slc17a7Cre/+;H11-DLK(iOE)/+ mice. Statistics: unpaired t-test. ns, not significant; * p<0.05. All error bars represent SEM.
Figure 5—figure supplement 2. Analysis of Bassoon and Homer1 immunostaining in dorsal CA1 in P10 of DLK(iOE).

Figure 5—figure supplement 2.

(A) Confocal single-slice images of Bassoon and Homer1 immunostaining in CA1 SR of control and Slc17a7Cre/+;H11-DLK(iOE)/+ mice at P10. Scale bars, 5 μm in panel images, and 1 μm in enlarged images. (B, C) Quantification of Bassoon and Homer1 puncta density, respectively. (D) Quantification of synapses displaying co-localization of Bassoon and Homer1. (E, F) Quantification from control and Slc17a7Cre/+;H11-DLK(iOE)/+ mice for (E) Bassoon puncta size, (F) Homer1 puncta size. Data points represent average values per mouse from 3 sections. N=4 control, and 7 Slc17a7Cre/+;H11-DLK(iOE)/+ mice. Statistics: unpaired t-test. ns, not significant. All error bars represent SEM.
Figure 5—figure supplement 3. Analysis of Bassoon and Homer1 immunostaining in CA3 synapses of DLK(iOE) at P10 and P15.

Figure 5—figure supplement 3.

(A) Confocal single-slice images of Bassoon and Homer1 immunostaining in CA3 SR of control and Slc17a7Cre/+;H11-DLK(iOE)/+ mice at P10. Scale bars, 5 μm in panel images, and 1 μm in enlarged images. (B, C) Quantification of Bassoon and Homer1 puncta density, respectively. (D) Quantification of synapses displaying co-localization of Bassoon and Homer1. (E, F) Quantification from control and Slc17a7Cre/+;H11-DLK(iOE)/+ mice for (E) Bassoon puncta size, (F) Homer1 puncta size. Data points represent average values per mouse from 3 sections. N=4 control, and 7 Slc17a7Cre/+;H11-DLK(iOE)/+ mice. Statistics: unpaired t-test. ns, not significant. (G) Confocal single-slice images of Bassoon and Homer1 immunostaining in CA3 SL of control and Slc17a7Cre/+;H11-DLK(iOE)/+ mice at P10. Scale bars, 5 μm in panel images, and 1 μm in enlarged images. (H, I) Quantification of Bassoon and Homer1 puncta density, respectively. (J) Quantification of synapses displaying co-localization of Bassoon and Homer1. (K, L) Quantification from control and Slc17a7Cre/+;H11-DLK(iOE)/+ mice for (K) Bassoon puncta size, (L) Homer1 puncta size. Data points represent average values per mouse from 3 sections. N=4 control, and 7 Slc17a7Cre/+;H11-DLK(iOE)/+ mice. Statistics: unpaired t-test. ns, not significant. (M) Confocal single-slice images of Bassoon and Homer1 immunostaining in CA3 SR of control and Slc17a7Cre/+;H11-DLK(iOE)/+ mice at P15. Scale bars, 5 μm in panel images, and 1 μm in enlarged images. (N, O) Quantification of Bassoon and Homer1 puncta density, respectively. (P) Quantification of synapses displaying co-localization of Bassoon and Homer1. (Q, R) Quantification from control and Slc17a7Cre/+;H11-DLK(iOE)/+ mice for (Q) Bassoon puncta size, (R) Homer1 puncta size. Data points represent average values per mouse from 3 sections. N=9 control, and 6 Slc17a7Cre/+;H11-DLK(iOE)/+ mice. Statistics: unpaired t-test. ns, not significant. (S) Confocal single-slice images of Bassoon and Homer1 immunostaining in CA3 SL of control and Slc17a7Cre/+;H11-DLK(iOE)/+ mice at P15. Scale bars, 5 μm in panel images, and 1 μm in enlarged images. (T, U) Quantification of Bassoon and Homer1 puncta density, respectively. (V) Quantification of synapses displaying co-localization of Bassoon and Homer1. (W, X) Quantification from control and Slc17a7Cre/+;H11-DLK(iOE)/+ mice for (W) Bassoon puncta size, (X) Homer1 puncta size. Data points represent average values per mouse from 3 sections. N=9 control, and 6 Slc17a7Cre/+;H11-DLK(iOE)/+ mice. Statistics: unpaired t-test. ns, not significant. All error bars represent SEM.

High levels of DLK cause short neurite formation in primary hippocampal neurons

To gain better resolution on how DLK expression levels affect glutamatergic neuron morphology and synapses, we next turned to primary hippocampal cultures. To enable visualization of Slc17a7-positive neurons, we introduced a floxed Rosa26-tdTomato reporter (Madisen et al., 2010) into Slc17a7Cre/+, Slc17a7Cre/+;Map3k12fl/fl, and Slc17a7Cre/+;H11-DLK(iOE)/+ mice. We prepared primary hippocampal neurons from P1 pups of respective crosses (Materials and methods), so around 1⁄4 of glutamatergic (Slc17a7-Cre) neurons in the cultures had both tdTomato and the genotype of interest (Map3k12fl/fl, WT, or H11-DLK(iOE)/+). We did not notice an obvious effect of DLK(iOE) or DLK(cKO) on neuron density in cultures at DIV2. To assess neuronal type distribution in our cultures, we immunostained DIV14 neurons with antibodies for Satb2, as a CA1 marker (Nielsen et al., 2010), and Prox1, as a marker of DG neurons (Iwano et al., 2012). We did not observe significant differences in the proportion of cells labeled with each marker in DLK(cKO) or DLK(iOE) cultures (Figure 6—figure supplement 1E). These data are consistent with the idea that DLK signaling does not have a strong role in neuron-type specification both in vivo and in vitro.

We verified DLK protein pattern and levels by immunostaining with DLK antibodies (Figure 6A). In DIV2 neurons from control mice, DLK was present in cell soma, likely reflecting Golgi apparatus localization as reported (Hirai et al., 2002), and showed a punctate pattern in neurites, particularly the axon growth cone regions. We also immunostained for STMN4 and observed a similar punctate localization in the cell soma, neurites, and growth cones (Figure 6A), in line with published data (Chauvin et al., 2008; Gavet et al., 2002). STMN4 puncta appeared to be non-overlapping with DLK (Figure 6—figure supplement 1B). In DIV2 neurons from DLK(cKO), STMN4 exhibited a similar punctate pattern, with intensity comparable to that in control neurons. In neurons from DLK(iOE), DLK levels were increased, and STMN4 levels were also increased (Spearman correlation r=0.7454) (Figure 6A and B), supporting our RiboTag analysis. Expression of another member of Stathmin, STMN2, is associated with DLK-dependent responses in DRG neurons (Summers et al., 2020; Thornburg-Suresh et al., 2023). Although our RiboTag analysis did not identify significant changes of Stmn2 (Figure 4—figure supplement 1A), we tested whether STMN2 protein levels could be altered in our cultured hippocampal neurons. In DIV2 control neurons STMN2 staining showed punctate localization in the perinuclear region (Gavet et al., 2002; Lutjens et al., 2000), along with punctate signals in neurites and growth cones, similar to STMN4. By co-immunostaining analysis of DLK and STMN2, we detected a positive correlation between DLK and STMN2 (Figure 6—figure supplement 1C and D, Spearman correlation r=0.4693), albeit to a moderate level in comparison to that of DLK and STMN4. These data suggest that in hippocampal glutamatergic neurons DLK has a stronger effect on STMN4 levels but may also regulate protein levels of STMN2.

Figure 6. DLK promotes short neurite formation in primary cultured hippocampal neurons.

(A) Confocal images of DIV2 primary hippocampal glutamatergic neurons immunostained with DLK and STMN4. Neurons with indicated genotypes are labeled by tdTomato from Cre-dependent Rosa26-tdTomato, generated from hippocampi in P1 pups from the following crosses: for control: Slc17a7Cre/+ X Rosa26tdT/+; for DLK(cKO): Slc17a7Cre/+;Map3k12fl/fl X Map3k12fl/fl;Rosa26tdT/+; for DLK(iOE): H11-DLK(iOE)/H11-DLK(iOE) X Slc17a7 Cre/+;Rosa26tdT/+. Orange arrows point to some of the thin neurites from neurons overexpressing DLK. Red dashes outline enlarged view of neurites. Scale bar, 10 μm neuron, 1 μm enlarged view. (B) Graph shows positive correlation between STMN4 immunostaining, measured as integrated density (Area X MFI) in neuronal soma, to integrated density of DLK immunostaining. N≥3 cultures/genotype,≥60 cells/genotype. Spearman correlation r=0.7454. (C) Quantification of percentage of neurons with no, one, or more than one axon (defined by neurites longer than 90 μm) in each genotype. Number of neurons: 47 from 3 Slc17a7Cre (control) cultures, 49 from 3 DLK(cKO) cultures, 42 from 4 DLK(iOE) cultures. Statistics: Fisher’s exact test shows significance (p<0.0001) between genotype and number of axons. Pairwise comparisons with Fisher’s exact test: Axon formation in control vs DLK(cKO): p=0.1857. Formation of multiple axons in control vs DLK(cKO): p>0.9999. Axon formation in control vs DLK(iOE): p=0.0042. Formation of multiple axons in control vs DLK(iOE): p=0.0001. (D) Quantification of number of primary neurites, which include both branches and filopodia, per neuron. Number of neurons: 55 from 4 Slc17a7Cre (control) cultures, 70 from 4 DLK(cKO) cultures, 45 from 5 DLK(iOE) cultures. Statistics, Kruskal-Wallis test with Dunn’s multiple comparison test. **** p<0.0001. Error bars represent SEM. (E) Confocal z-stack images of tyrosinated tubulin immunostaining from DIV2 cultures of genotypes indicated, showing that filopodia structures (arrows) around the soma and axons of neurons with high expression of DLK have tyrosinated tubulin. (F) Confocal z-stack images of acetylated tubulin immunostaining from DIV2 cultures of genotypes indicated, showing that filopodia structures (arrows) around the soma and axons of neurons with high expression of DLK do not have acetylated tubulin. Asterisks indicate stable branches containing acetylated tubulin. Scale bar in E, F, 10 μm. Tyrosinated tubulin and acetylated tubulin staining shows saturated appearance to visualize staining in thin neurites.

Figure 6.

Figure 6—figure supplement 1. Analysis of Stathmins in primary cultured hippocampal neurons from DLK(cKO) and DLK(iOE).

Figure 6—figure supplement 1.

(A) Confocal z-stack images of neuron morphology at DIV2 from mice of genotype indicated, visualized by tdTomato from Rosa26-tdTomato. Neurons with indicated genotypes are labeled by tdTomato from Cre-dependent Rosa26-tdTomato generated from the following crosses: for control: Slc17a7Cre/+ X Rosa26tdT/+; for DLK(cKO): Slc17a7Cre/+;Map3k12fl/fl X Map3k12fl/fl;Rosa26tdT/+; for DLK(iOE): H11-DLK(iOE)/H11-DLK(iOE) X Slc17a7 Cre/+;Rosa26tdT/+. Red arrowheads point to long processes considered as axons. Scale bar 100 μm. (B) Co-immunostaining of DLK and STMN4 in DIV2 control cultured neuron growth cone shows non-overlapping puncta. (C) Confocal z-stack images of DLK and STMN2 co-immunostaining of DIV2 primary hippocampal neurons from genotypes indicated; neurons are labeled with tdTomato from Rosa26-tdTomato. Scale bar 10 μm. (D) Quantification of association between DLK level and STMN2 in cell soma. N=3 cultures/genotype, ≥45 cells/genotype. Spearman correlation r=0.4693. (E) Analysis of cell types in culture at DIV14 using Prox1 and Satb2 markers. Quantification from N=3 cultures/genotype, ≥200 cells/genotype. Statistics: Two-way ANOVA with Dunnett’s multiple comparison test. ns, not significant. Error bars represent SEM.
Figure 6—figure supplement 2. Comparison of STMN2 and STMN4 antibodies.

Figure 6—figure supplement 2.

(A) Confocal single-slice images of STMN2 and STMN4 immunostaining using two independent antibodies on control primary hippocampal neurons DIV3. Dashed boxes are enlarged below. Scale bar,10μm full cell, 1 μm enlarged region. Line scan below reflects normalized intensity, with asterisks reflecting overlapping peaks. (B) Western blots of protein extracts from P15 hippocampal tissue of genotype indicated for STMN2 and STMN4 antibodies. Lanes 1–3 are littermate controls (+) for lanes 4–6 Slc17a7Cre/+;H11-DLK(iOE)/+, referred to as ‘Tg’; and lanes 7–9 are littermate controls (+) for lanes 10–12 Slc17a7Cre/+;Map3k12fl/fl, referred to as ‘-’. (C) Quantification of STMN2 or STMN4 protein level normalized to actin. N=3 mice/genotype. Statistics: One way ANOVA with Sidak’s multiple comparison test. ns, not significant; * p<0.05. Error bars represent SEM.
Figure 6—figure supplement 2—source data 1. Original western blots for images shown in Figure 6—figure supplement 2B.
Figure 6—figure supplement 2—source data 2. PDF showing original western blots for images shown in Figure 6—figure supplement 2B, along with relevant bands and genotypes.
Pg. 1 Original membranes corresponding to Panel B. Molecular weights shown using Precision Plus Protein Dual Color Ladder. Each lane represents a separate mouse. Lanes 1–3 show control samples (from DLK(iOE) sibs), lanes 4–6 show DLK(iOE), lanes 7–9 show control samples (from DLK(cKO) sibs), lanes 10–12 show DLK(cKO). All from P15 timepoint. Dotted lines indicate locations where membrane was cut for labeling with separate antibodies. Samples were split, with half of each prepped sample loaded onto two membranes (membrane 1&2). Pg. 2 Original membranes corresponding to Panel B. Molecular weights shown using Precision Plus Protein Dual Color Ladder. Each lane represents a separate mouse. Lanes 1–3 show control samples (from DLK(iOE) sibs), lanes 4–6 show DLK(iOE), lanes 7–9 show control samples (from DLK(cKO) sibs), lanes 10–12 show DLK(cKO). All from P15 timepoint. Dotted lines indicate locations where membrane was cut for labeling with separate antibodies. Samples were split, with half of each prepped sample loaded onto two membranes (membrane 1&2).

In hippocampal cultures at DIV2 neurites are actively growing and establish thicker branches, which form dendrites and axons (Dotti et al., 1988). In our control cultures at DIV2, the majority of tdTomato labeled neurons developed multiple neurites from the cell soma, with one neurite developing into an axon, defined here as a neurite longer than 90 µm (Figure 6—figure supplement 1A). Additionally, thin, often short, neurites were observed branching off from the cell soma, axons, dendrites, and growth cones. In DLK(cKO) cultures at DIV2, we observed a trend of more neurons without an axon (Figure 6C), though the differentiated axons appeared morphologically indistinguishable from control. The total number of neurites around the cell soma in DLK(cKO) neurons was significantly reduced, compared to control (Figure 6A and D). In DLK(iOE) cultures at DIV2, we observed a significant increase in the percentage of neurons without an axon and also neurons with multiple axons, compared to control cultures (Figure 6C, Figure 6—figure supplement 1A). Moreover, neurons expressing high levels of DLK protein displayed an increased number of neurites either around the cell soma as primary neurites or as secondary neurites, compared to control (Figure 6A and D). Such neurites were typically thin, and frequently appeared short, like filopodia. These thin neurites sometimes developed a rounded tip and showed beading appearance, resembling degeneration (Figure 6A and E). These data suggest a role for DLK in neurite formation and axon specification in cultured hippocampal glutamatergic neurons.

We further analyzed microtubules in individual neurites of the DIV2 neurons. Control neurons exhibited staining for tyrosinated tubulin in differentiated axons and dendrites as well as filopodia and towards peripheral regions of growth cones (Figure 6E). Acetylated tubulin was present in differentiated axons and dendrites and in the central region of growth cones where stable microtubules were present (Figure 6F), and was absent from filopodia and microtubules in the peripheral regions of growth cones. The thin neurites in neurons expressing very high levels of DLK appeared to have thin bundles of microtubules, and these neurites generally were not associated with a growth cone or microtubules splaying apart at the end as was common in WT growth cones (Figure 6E). Neurites from neurons with high DLK expression also had tyrosinated tubulin, while acetylated tubulin was frequently absent (Figure 6E and F). Additionally, STMN4 was present in the thin neurites, especially in those with high levels of DLK (Figure 6A), suggesting the thin neurites may likely be dynamic in nature. These results suggest that in cultured hippocampal neurons high levels of DLK promotes formation of short, thin, dynamic branches.

Increased DLK expression alters synapses in primary hippocampal neurons

Our RiboTag data showed enrichment of synaptic genes in both DLK(cKO) and DLK(iOE) (Figure 3F, Figure 3—figure supplement 1J, Supplementary file 1 WT vs DLK(cKO) DEGs, Supplementary file 2 WT vs DLK(iOE) DEGs). Some of these genes function in cell adhesion, calcium signaling, and AMPA receptor expression, which may affect dendritic spine morphology and synaptic connections. Increased DLK levels led to reduced Homer1 density in hippocampal tissue (Figure 5I). To further investigate the effects of DLK on synapses, we immunostained the cultured hippocampal neurons at DIV14 with Bassoon. The control neurons showed discrete Bassoon puncta in axons (Figure 7A–C). DLK(cKO) neurons showed no significant change in Bassoon puncta size or density. In contrast, DLK(iOE) neurons showed abnormal Bassoon staining that was larger and irregular in shape (Figure 7A–C), suggesting that high levels of DLK disrupted presynaptic active zones.

Figure 7. Increasing DLK expression alters synapse formation in primary cultured hippocampal neurons.

Figure 7.

(A) Confocal images of axons of DIV14 neurons of indicated genotype, co-stained with Bassoon and DLK. Neurons with indicated genotypes are labeled by tdTomato from Cre-dependent Rosa26-tdTomato generated from the following crosses: for control: Slc17a7Cre/+ X Rosa26tdT/+; for DLK(cKO): Slc17a7Cre/+;Map3k12fl/fl X Map3k12fl/fl;Rosa26tdT/+; for DLK(iOE): H11-DLK(iOE)/H11-DLK(iOE) X Slc17a7 Cre/+;Rosa26tdT/+. Scale bar, 1 μm. (B) Quantification of bassoon puncta density. (C) Quantification of average bassoon puncta size from individual neurons. Number of neurons: 30 from 3 Slc17a7-cre (control) cultures, 41 from 3 DLK(cKO) cultures, 46 from 4 DLK(iOE) cultures. Statistics: One way ANOVA with Dunnett’s multiple comparison test. ns, not significant; * p<0.05. (D) Confocal z-stack images of DIV14 neurons of indicated genotype, labeled by Rosa26-tdTomato. Dashed boxes outline dendrites enlarged below for dendritic spines. Asterisks provide some examples of spine types; long thin with purple; thin with blue; mushroom with white; stubby with yellow. Scale bar, 10 μm top, 5 μm bottom. (E) Quantification of dendritic spine density. (F) Quantification of mushroom spine density. (G) Distribution of spine types. (E–G) Number of neurons: 35 from 3 Slc17a7-cre (control) cultures, 31 from 3 DLK(cKO) cultures, 31 from 3 DLK(iOE) cultures. Statistics: One way ANOVA with Dunnett’s multiple comparison test. * p<0.05; ** p<0.01. All error bars represent SEM.

Morphology of dendritic spines is associated with differences in maturity, with mushroom spines representing a more mature morphology than thin spines (Yoshihara et al., 2009). To assess how DLK expression levels affect dendritic spine morphology and frequency in cultured neurons, we evaluated both the density and type of dendritic spines formed at DIV14 on neurons with spines, visualized by tdTomato. We categorized spine morphology in different types, following previous studies (Risher et al., 2014). Neurons from DLK(cKO) showed spines at a higher density than control neurons, with significantly more mushroom spines (Figure 7D–G). In contrast, neurons from DLK(iOE) cultures had a reduced density of dendritic spines compared to control neurons (Figure 7D and E). DLK(iOE) neurons also formed spines that tended to be more immature, with significantly fewer mushroom spines and a higher percentage of thin spines (Figure 7D, F and G). These results reveal that expression levels of DLK appear to be inversely correlated with spine density and maturity.

Discussion

Selective vulnerability of hippocampal glutamatergic neurons to increased DLK expression

Under normal conditions, the abundance of endogenous DLK in many parts of the brain is generally kept at a low level. Elevated DLK signaling has been associated with traumatic injury and implicated in Alzheimer’s disease and other neurodegenerative conditions (Asghari Adib et al., 2018; Huang et al., 2017; Jin and Zheng, 2019; Le Pichon et al., 2017; Tedeschi and Bradke, 2013). Despite its broad expression, we know little about DLK’s role in the central nervous system. In this study, we combined conditional knockout and overexpression of DLK to uncover its roles in the hippocampal glutamatergic neurons. Our finding that conditional deletion of DLK in the glutamatergic neurons using Slc17a7Cre in late embryonic development does not cause discernable morphological defects is consistent with the previous reports that hippocampal neurons are largely normal in constitutive knockout of DLK (Hirai et al., 2006; Hirai et al., 2011). In contrast, induced overexpression of DLK, which leads to activation of JNK signaling evidenced by increased p-c-Jun, causes the glutamatergic neurons in dorsal CA1 and dentate gyrus to undergo pronounced death, while CA3 neurons appear less vulnerable even under chronic elevated DLK expression. The levels of DLK in our DLK(iOE) mice model appear comparable to those reported under traumatic injury and chronic stress. The pattern of DLK-induced neuronal death shares similarity to the differential vulnerability of CA1 and CA3 neurons reported in patients with Alzheimer’s disease (West et al., 1994), and animal models of oxidative stress (Wilde et al., 1997), ischemia (Smith et al., 1984), and glutamate excitotoxicity from NMDA (Vornov et al., 1991). The dorsal-ventral hippocampal neuron death pattern associated with increased expression of DLK is also similar to that observed in animal models of ischemia (Smith et al., 1984). Such regional differences of hippocampal neurons in response to insults or genetic manipulation may be attributed to multiple factors, such as the nature of the neural network (Viana da Silva et al., 2024), intrinsic differences between CA1 and CA3 neurons in their abilities to buffer calcium changes, mitochondrial stress, protein homeostasis, glutamate receptor distribution (Schmidt-Kastner, 2015), and as discussed further, the degree to which transcription factors, such as p-c-Jun or other AP1 factors, are activated under different conditions.

DLK-dependent cellular network exhibits commonality and cell-type specificity

DLK to JNK signaling is known to lead to transcriptional regulation. Several studies have used transcriptomic profiling to reveal DLK-dependent gene expression in different regions of the brain, such as cerebellum and forebrain, and in specific neuron types, such as DRG neurons and RGC neurons following axon injury or nerve growth factor withdrawal (Goodwani et al., 2020; Hu et al., 2019; Larhammar et al., 2017; Le Pichon et al., 2017; Shin et al., 2019; Watkins et al., 2013). One recent study reported RiboTag profiling of the DLK-dependent gene network in axotomized spinal cord motor neurons (Asghari Adib et al., 2024). In agreement with the overall findings from these studies, we find that loss of DLK in hippocampal glutamatergic neurons results in modest expression changes in a small number of genes, while overexpression of DLK leads to expression changes in a larger set of genes. Gene ontology analysis of our hippocampal glutamatergic neuron translatome reveals a similar set of terms as found in the other expression studies, including neuron differentiation, apoptosis, ion transport, and synaptic regulation.

Comparison of the translational targets of DLK in our study with these prior analyses also shows notable differences that are likely specific to neuron-type and contexts of experimental manipulations. For example, we find a strong induction of Jun translation associated with increased expression of DLK, but no significant changes in Atf3 or Atf4 translation, which were reported to show DLK-dependent increases in axotomized spinal cord motoneurons, and injured RGCs and DRGs (Asghari Adib et al., 2024; Larhammar et al., 2017; Shin et al., 2019; Watkins et al., 2013). Most ATF4 target genes (Somasundaram et al., 2023) also show no significant changes in our hippocampal glutamatergic neuron translatome. Moreover, we find a cohort of synaptic genes showing expression dependency on DLK (such as Tenm3, Nptx1, and Nptxr), but not any of the complement genes (C1qa, C1qb, C1qc), which are up-regulated in the regenerating spinal cord motor neurons where neuron-immune cell interaction has a critical role (Asghari Adib et al., 2024). Genomic structure and regulation intrinsic to the cell type may be a major factor underlying the gene expression differences in ours and other studies. Elevated DLK signaling in axotomized neurons may promote a strong regenerative response through activation of transcription factors, such as ATF3 and ATF4, whereas JUN and others that are actively expressed in hippocampal neurons may lead to a strong effect on refining synapses in response to DLK signaling. Overall, ours and the previous studies underscore the importance of systematic dissection of molecular pathways to understand neuron-type specific functionality to DLK signaling.

Our analysis of the spatial expression patterns of genes that showed association with DLK expression levels provides molecular insight to the differential vulnerability of hippocampal glutamatergic neurons under neurodegenerative conditions. We find that a select set of genes enriched in CA1 are up-regulated in DLK knockout and down-regulated upon DLK overexpression. The c-Jun transcription factor has a key role in hippocampal cell death responses as mutations preventing c-Jun phosphorylation led to decreased neuronal apoptosis in the hippocampus following treatment with kainic acid (Behrens et al., 1999). Basal levels of c-Jun and phosphorylated c-Jun in hippocampus are generally low (Goodwani et al., 2020; Pozniak et al., 2013). We find modest reductions in p-c-Jun in DLK(cKO) glutamatergic neurons, consistent with previous studies of the constitutive knockout of DLK (Hirai et al., 2006). In contrast, in DLK(iOE) neurons, translation of c-Jun and phosphorylation of c-Jun are increased, with CA1 neurons exhibiting higher increase than CA3 neurons. The c-Jun promoter has consensus AP1 sites, and c-Jun can regulate its own expression levels in cancer cell lines (Angel et al., 1988), NGF-deprived sympathetic neurons (Eilers et al., 1998) and kainic acid treated hippocampus (Mielke et al., 1999). While our data does not pinpoint the molecular changes explaining why CA3 would show less vulnerability to increased DLK, we may speculate that DLK(iOE) induced signal transduction amplification may differ in CA1 vs CA3. CA1 genes appear to be more strongly regulated than CA3 genes, consistent with our observation that increased c-Jun expression in CA1 is greater than that in CA3. Other parallel molecular factors may also contribute to resilience of CA3 neurons to DLK(iOE), such as HSP70 chaperones, different JNK isoforms, and phosphatases, some of which showed differential expression in our RiboTag analysis of DLK(iOE) vs WT (Supplementary file 2 WT vs DLK(iOE) DEGs). Together with other genes that show dependency on DLK, the DLK and Jun regulatory network contributes to the regional differences in hippocampal neuronal vulnerability under pathological conditions.

Conserved functions of DLK in regulating Stathmins

Stathmins are tubulin binding proteins broadly expressed in many types of neurons. Several studies have reported that DLK can regulate the expression of different Stathmin isoforms in multiple neuron types under injury conditions (Asghari Adib et al., 2024; DeVault et al., 2024; Hu et al., 2019; Larhammar et al., 2017; Le Pichon et al., 2017; Shin et al., 2019). In the hippocampus Stmn2 is expressed at a higher level than Stmn4, with the relative ratios of Stmn4:Stmn2 in hippocampus much higher than in DRGs (Zeisel et al., 2018). We find that DLK can modulate expression and translation of Stmn4 in hippocampal neurons. ChIP-seq data for Jun from ENCODE (ENCSR000ERO) suggest a possible binding site in the promoter region of Stmn4 (The ENCODE Project Consortium, 2012; Luo et al., 2020). STMN4 expression in hippocampus peaks around P8, correlating to neurite outgrowth and synapse formation and pruning (Paolicelli et al., 2011). At the level of hippocampal tissue, loss of DLK causes no detectable changes to microtubules, while increased levels of DLK appear to alter microtubule homeostasis in dendrites, with generally increased levels of both stable and dynamic microtubule markers. The CA1 neurons in DLK(iOE) also show fewer parallel microtubule arrays of apical dendrites, with short branches extending in varied directions. Our results from primary hippocampal neurons support roles for DLK in both short neurite and axon formation, similar to observations in cortical neurons, where DLK contributes to stage specific regulation of microtubules (Hirai et al., 2011). In primary cortical neurons overexpression of STMN4 can increase neurite length and branching when an epigenetic cofactor regulating MT dynamics was knocked down (Tapias et al., 2021). We speculate that DLK-dependent regulation of STMN4 and other STMNs may have a critical role in the long-term cytoskeletal rearrangements for neuronal morphology and synapse formation or stability. Nonetheless, as Stmns have considerable redundancy in expression and function, changes in STMN4 alone are unlikely to be a major factor for the observed hippocampal regional neuron death.

Conserved roles of DLK in synapse formation and maintenance

The in vivo functions of the DLK family of proteins were first revealed in studies of synapse formation in C. elegans and Drosophila (Collins et al., 2006; Nakata et al., 2005). Our hippocampal glutamatergic neuron translatomic data extends this function by revealing a strong theme of DLK-dependent network in synapse organization, adhesion molecules and regulation of trans-synaptic signaling, especially related to AMPA receptor expression and calcium signaling, such as Neuronal Pentraxin 1 and Neuronal Pentraxin Receptor Nptx1 and Nptxr (Gómez de San José et al., 2022). From our synapse analysis in culture, we find increased DLK alters pattern of presynaptic protein Bassoon, consistent with the findings on C. elegans and Drosophila synapses (Nakata et al., 2005; Collins et al., 2006). We also find DLK regulates dendritic spine morphology, with loss of DLK associated with a greater number of spines with more mature spine morphology, while increased DLK was associated with fewer and less mature spines. These results are similar to that observed in layer 2/3 cortical neurons where loss of DLK is associated with larger dendritic spines in developing neurons and higher density of spines when exposed to Aβ plaques, which lead to loss of nearby spines (Le Pichon et al., 2017; Pozniak et al., 2013). In CA1 dendritic regions, DLK overexpression reduced Homer1 density, suggesting synaptic defects may correlate with the onset of degeneration. In axotomized spinal cord motor neurons DLK induces activation of complement, leading to microglial pruning of synapses in injured motoneurons (Asghari Adib et al., 2024). These data support a conserved role of DLK in synapse formation and maintenance, through regulating the translation of genes involved in neuron outgrowth, synaptic adhesion, and synapse activity.

Limitation of our study

We have investigated roles of DLK in hippocampal glutamatergic neuron development, synapse regulation, and neuron death processes. We infer that DLK-dependent expression and translation of CA1 enriched genes may likely play roles in regional vulnerability to increased DLK signaling. However, our RiboTag profiling was performed with whole hippocampus at time when CA1 death was noticeable. Our analysis of spatial expression patterns of DLK-dependent genes relies on available data from adult animals, which may not reflect the patterns at P15, or in response to altered DLK. We cannot rule out that some of the decreased expression of CA1 enriched genes in DLK(iOE) could be secondary due to neuronal death that could result in fewer CA1 neurons present in our mRNA samples. Our analysis also does not directly address why CA3 neurons are less vulnerable to increased DLK expression. Future studies using cell-type specific RiboTag profiling and other methods at a refined time window will be required to address how DLK-dependent signaling interacts with other networks underlying hippocampal regional neuron vulnerability to pathological insults. While we find evidence for apoptosis, other forms of cell death may also occur. Additional experiments will be needed to elucidate in vivo roles of STMN4 and its interaction with other STMNs. It is worth noting that a systematic analysis of gene networks in neuron types selectively vulnerable to Alzheimer’s disease has suggested processes related to axon plasticity and synaptic vesicle transmission, particularly with relation to microtubule dynamics, may be involved in the neuronal vulnerability (Roussarie et al., 2020). Combining gene profiling of specific cell types in hippocampus with advanced technology in function dissection will continue to provide clarification to roles of DLK in the central nervous system under normal and pathological conditions.

Materials and methods

Key resources table.

Reagent type (species) or resource Designation Source or reference Identifiers Additional information
Genetic reagent (Mus musculus) Conditional DLK knockout:
Map3k12fl/fl
PMID:33475086;
27511108; 35361703
housed in UCSD vivarium
Genetic reagent (M. musculus) Inducible DLK overexpression:
H11-DLK(iOE)
PMID:33475086 housed in UCSD vivarium
Genetic reagent (M. musculus) Slc17a7Cre The Jackson Laboratory Strain #023527;
RRID:IMSR_JAX:023527
B6;129S-Slc17a7tm1.1(cre)Hze/J
Genetic reagent (M. musculus) Rpl22HA The Jackson Laboratory Strain #029977;
RRID:IMSR_JAX:029977
B6J.129(Cg)-Rpl22tm1.1Psam/SjJ
Genetic reagent (M. musculus) Rosa26tdT The Jackson Laboratory Strain #007914;
RRID:IMSR_JAX:007914
B6.Cg-Gt(ROSA)26Sortm
14(CAG-tdTomato)Hze/J
Antibody Rabbit polyclonal
anti-Map3k12 antibody
Genetex GTX124127;
RRID:AB_11170703
IF (1:250) tissue, (1:1000) cells, WB (1:1000);
Lot #40653
Antibody Rabbit monoclonal anti-p-c-Jun
(Ser73) (D47G9) antibody
Cell signaling 3270;
RRID:AB_2129575
IF (1:200) tissue, Lot #5
Antibody Rabbit polyclonal
anti-GFAP antibody
Dako Z0334;
RRID:AB_10013382
IF: (1:500); Lot #20049469
Antibody Rabbit polyclonal anti-IBA1 Wako 019–19741;
RRID:AB_839504
IF: (1:1000)
Antibody Rat monoclonal anti-HA High Affinity Roche 11867423001;
RRID:AB_390918
IP (5 ug); Lot #47877600
Antibody Rabbit monoclonal anti-HA (C29F4) Cell Signaling 3724;
RRID:AB_1549585
WB (1:1000); Lot #8
Antibody Mouse monoclonal anti-NeuN Millipore MAB377;
RRID:AB_2298772
IF (1:200);
Lot #3104227/3808682
Antibody Mouse monoclonal anti-Tubb3 (Tuj1) Biolegend 801202;
RRID:AB_2313773
IF (1:1000) tissue, (1:5000) cells;
Lot #B249869
Antibody Rabbit polyclonal anti-Tubb3 Sigma-Aldrich T2200;
RRID:AB_262133
IF (1:500) cells;
Lot #21190649
Antibody Mouse monoclonal
anti-Acetyl-Tubulin (6-11b-1)
Sigma-Aldrich T7451;
RRID:AB_609894
IF (1:500) tissue, (1:3000) cells;
WB (1:1000)
Antibody Mouse monoclonal anti-Stmn4 Santa Cruz Biotechnology Sc-376936 IF (1:250) cells; WB (1:50);
Lot # E3012
Antibody Rabbit polyclonal anti-Stmn4 Proteintech 12027–1-AP;
RRID:AB_2197401
IF (1:400) cells; WB (1:1000);
Lot#00005750
Antibody Mouse monoclonal anti-Stmn2 R&D Systems MAB6930;
RRID:AB_10972937
IF (1:1000) cells; WB (0.4 ng/mL); Lot#CFIL052310A
Antibody Rabbit polyclonal anti-Stmn2 Proteintech 10586–1-AP;
RRID:AB_2197283
IF (1:400) cells; WB (1:2000);
Lot#00124321
Antibody Mouse monoclonal
anti-Tyrosinated Tubulin (TUB1A2)
Sigma-Aldrich T9028;
RRID:AB_261811
IF (1:1000) tissue, (1:5000) cells; WB (1:1000);
Lot #22181017
Antibody Rabbit polyclonal anti-Vglut1 Synaptic Systems 135 302;
RRID:AB_887877
IF (1:1000) tissue; Lot #1–53
Antibody Rabbit monoclonal anti-c-Jun (60 A8) Cell Signaling 9165;
RRID:AB_2130165
IF (1:200) tissue, (1:1000) cells; Lot #11
Antibody Mouse monoclonal anti-Bassoon (SAP7F407) Novus NB120-13249;
RRID:AB_788125
IF (1:500) tissue, cells; Lot #06082117
Antibody Chicken polyclonal anti-MAP2 Abcam Ab5392;
RRID:AB_2138153
IF (1:5,000) cells; Lot #1012833–1
Antibody Monoclonal mouse anti-beta actin ABclonal AC004;
RRID:AB_2737399
WB (1:5000); Lot #3500100012
Antibody Mouse monoclonal anti-Flag M2 Sigma-Aldrich F1804;
RRID:AB_262044
WB (1:500)
Antibody Rabbit polyclonal anti-Homer1 Synaptic systems 160–003;
RRID:AB_887730
IF (1:500) tissue
Antibody Mouse monoclonal anti-Satb2 Abcam Ab51502;
RRID:AB_882455
IF (1:500) cells
Antibody Goat polyclonal anti-Prox1 R&D Systems AF2727;
RRID:AB_2170716
IF (4 µg/mL)
Antibody Rabbit polyclonal anti-Map3k13 Sigma-Aldrich HPA016497;
RRID:AB_10670027
IF (1:200) tissue
Antibody Alexafluor488 goat anti mouse IGG (H+L) Invitrogen A11001;
RRID:AB_2534069
IF (1:500) tissue, (1:2000) cells;
Lot #745480
Antibody Alexafluor488 donkey anti mouse IGG (H+L) Invitrogen A21202;
RRID:AB_141607
IF (1:500) tissue, (1:2000) cells;
Lot #2266877
Antibody Alexafluor647 goat anti rabbit IGG (H+L) Invitrogen A21245;
RRID:AB_2535813
IF (1:500) tissue, (1:2000) cells;
Lot #2299231
Antibody Alexafluor488 donkey anti rabbit IGG (H+L) Invitrogen A21206;
RRID:AB_2535792
IF (1:500) tissue, (1:2000) cells;
Lot #2376850
Antibody Alexafluor647 goat anti mouse IGG (H+L) Invitrogen A21236;
RRID:AB_2535805
IF (1:500) tissue, (1:2000) cells;
Lot #2300995
Antibody Alexa Fluor 647 goat anti chicken IgG (H+L) Invitrogen A21449;
RRID:AB_2535866
IF (1:2000) cells; Lot #2079903
Antibody Anti-rabbit: ECL Anti-Rabbit lgG, HRP Cytiva NA934V;
RRID:AB_772206
WB (1:5000); Lot #17624274
Antibody Anti-mouse: ECL Anti-mouse lgG, HRP Cytiva NXA931V;
RRID:AB_772209
WB (1:5000); Lot #17675041
Antibody Stabilized goat anti-rabbit HRP conjugated Pierce 1858415 WB (1:5000); Lot # HE104909
Sequence-based reagent RNAscope probe MAP3K12-C2 ACD ACD:458151 C2
Sequence-based reagent RNAscope probe Slc17a7-C3 ACD ACD:416631 C3
Sequence-based reagent RNAscope probe Gfap-C2 ACD ACD:313211 C2
Sequence-based reagent RNAscope probe Stmn4 ACD ACD:537541
Commercial assay or kit DeadEnd Fluorometric TUNEL System Promega G3250
Commercial assay or kit RNAeasy Minikit Qiagen 74104
Commercial assay or kit Superscript III First Strand Synthesis System Invitrogen 18080051
Commercial assay or kit iQ Sybr Green Supermix Bio-Rad 1708880
Commercial assay or kit Pierce BCA Protein Assay Kits Thermo Scientific 23227
Commercial assay or kit RNAscope Fluorescent Multiplex Reagent kit ACD 320850 Amp 4 Alt A-FL
Chemical compound, drug Cycloheximide Sigma-Aldrich C4859
Software, algorithm Galaxy PMID:29790989 RRID:SCR_006281 https://usegalaxy.org/
Software, algorithm FastQC Babraham Bioinformatics RRID:SCR_014583 https://github.com/s-andrews/FastQC
Software, algorithm STAR aligner PMID:23104886 RRID:SCR_004463 https://github.com/alexdobin/STAR
Software, algorithm FeatureCounts PMID:24227677 RRID:SCR_012919 https://subread.sourceforge.net/
Software, algorithm RStudio Posit RRID:SCR_000432 https://posit.co/download/rstudio-desktop/
Software, algorithm ggplot2 Wickham, 2016 RRID:SCR_014601 https://ggplot2.tidyverse.org/
Software, algorithm DAVID PMID:19131956 RRID:SCR_001881 https://david.ncifcrf.gov/home.jsp
Software, algorithm Rank Rank Hypergeometric Overlap PMID:20660011 RRID:SCR_014024 https://systems.crump.ucla.edu/rankrank/rankranksimple.php
Software, algorithm SynGO PMID:31171447 RRID:SCR_017330 https://www.syngoportal.org/
Software, algorithm GSEA PMID:16199517 RRID:SCR_003199 https://www.gsea-msigdb.org/gsea/index.jsp
Software, algorithm Fiji PMID:22743772 RRID:SCR_002285 https://imagej.net/software/fiji/
Software, algorithm GraphPad Prism GraphPad Software RRID:SCR_002798 http://www.graphpad.com
Other Protein G Dynabeads Invitrogen 10003D
Other DAPI Invitrogen D1306
Other B27 Gibco 17504–044
Other RNAse inhibitor, murine New England Biolabs M0314

Experimental mice

All animal protocols were approved by the Animal Care and Use Committee of the University of California San Diego. Map3k12fl (Map3k12fl/fl) allele was made by Dr. Lawrence B. Holzman (Univ. Penn) and reported in Chen et al., 2016; Li et al., 2021; Saikia et al., 2022. Map3k12 (H11-DLK(iOE)) transgene was described in Li et al., 2021. Slc17a7Cre allele (JAX stock #023527) was described in Harris et al., 2014. RiboTag allele (JAX stock #029977) was described in Sanz et al., 2009. ROSA26-loxP-STOP-loxP-tdTomato fl/fl reporter line (JAX stock #007914) was constructed in Madisen et al., 2010. Standard mating procedure was followed to generate Slc17a7Cre/+;Map3k12fl/fl and Slc17a7 Cre/+;H11-DLK(iOE)/+ experimental mice. Genotyping primers are in Supplementary file 4. Sibling control mice had either Slc17a7Cre/+ or Map3k12fl/fl or H11-DLK(iOE)/+ allele alone. All experiments used both male and female mice. Slc17a7 Cre dependent tdTomato expression from H11-DLK(iOE) transgene was observed in most or all CA3, many CA1 neurons, with limited number of DG neurons at P15, similar to the described Slc17a7 Cre reporter line (Harris et al., 2014), and was throughout all regions by P60. Slc17a7 Cre/+;H11-DLK(iOE)/+ mice around 4 months of age developed noticeable progressive motor deficits, which were likely unrelated to hippocampal glutamatergic neuron death, and were not studied further.

Western blotting

Isolated hippocampal tissue was lysed in ice-cold RIPA buffer (50 mM Tris/HCl pH 7.4, 150 mM NaCl, 0.5% DOC, 0.1% SDS, 1% NP-40 freshly supplemented with protease inhibitor cocktail and 1 mM PMSF). Tissues were homogenized by Dounce homogenization using 30 passes pestle A and 30 passes pestle B. Samples were spun down at 13,000 x g for 10 min at 4 C. Supernatants were collected, and protein concentration was determined using the BCA assay (Thermo Fisher Scientific, 23227). Equal concentration of proteins (~10–20 ng) were run on NuPAGE 4–12% Bis-Tris Gel, 1.0 mm (Invitrogen, NP0322BOX) with 20X NuPAGE MES SDS Running Buffer (Invitrogen, NP0002). Protein samples were transferred by wet transfer to a PVDF membrane (0.2 μm, Bio-RAD, 1620177) by Mini Trans-Blot Cell at 100 mA for 1 hr at 4 °C. Membranes were blocked in 5% skim milk in TBST for 1 hr at room temperature, and then incubated with primary antibody in 3% BSA or 5% skim milk in TBST at 4 °C overnight. Membranes were washed 3x10 min in TBST and incubated with 1:5000 of the appropriate HRP-conjugated secondary antibody in 3% BSA in TBST at room temperature for 1 hr, then washed 3x10 min in TBST. Bands were detected using enhanced chemiluminescence (ECL) reagents (GE Healthcare, RPN2106) or Pico PLUS Chemiluminescent Substrate (Thermo Fisher Scientific, 34580) using a Licor Odyssey XF Imager. Molecular weight markers were PageRuler Plus Prestained Protein Ladder (Thermo Fisher Scientific, 26619) or Precision Plus Protein Ladder (Bio-Rad, 1610374).

Quantification of western blot images was performed by measuring identical size regions from each band, subtracting the background signal, and normalizing to internal actin controls for each sample. Time course analysis was further normalized to P1 WT protein levels. All images shown had N=3 biological replicates.

STMN2/STMN4 antibody specificity

Given their highly similar protein size and sequences, we wanted to evaluate STMN2 and STMN4 antibody specificity. We used two antibodies for each. STMN2 antibodies were a mouse monoclonal anti-STMN2 (R&D Systems, MAB6930) and a rabbit polyclonal anti-STMN2 (Proteintech, 10586–1-AP). STMN4 antibodies were a mouse monoclonal anti-STMN4 (Santa Cruz, Sc-376936) and a rabbit polyclonal anti-STMN4 (Proteintech, 12027–1-AP). We tested the specificity of STMN2 and STMN4 antibodies by co-staining for STMN2 and STMN4, or with two separate STMN2 or STMN4 antibodies. In each case, antibody signal overlapped in the cell soma, presumably at the Golgi, as well as larger puncta elsewhere, with some overlapping small puncta, and some non-overlapping small puncta (Figure 6—figure supplement 1A). Overlapping and non-overlapping signal was also visualized by plotting intensity of signal along the neurite. By western blot STMN2 and STMN4 were highly similar at the protein MW and levels, though the STMN4 antibodies tested detected a larger MW band specific to STMN4, suggesting some specificity. The STMN2 antibodies also occasionally recognized a smaller MW band only recognized with the Proteintech STMN4 antibody but not the Santa Cruz STMN4 antibody (Figure 6—figure supplement 1B). Furthermore, while STMN4 protein levels increased relative to β-actin in mice with increased DLK, STMN2 protein levels did not show significant increases. These different expression patterns validated some degree of specificity with these antibodies. Based on our analysis, the STMN4 Santa Cruz antibody (Sc-376936) may be more specific to STMN4 than the STMN4 Proteintech antibody (12027–1-AP) though it appears less sensitive. The STMN2 antibodies showed strongest overlap of puncta and similar MW proteins, thus we were unable to detect differences in specificity. Whether the antibodies may also detect some of the same isoforms is not clear without further analysis.

Immunofluorescence of hippocampal tissues

Mice were transcardially perfused with saline solution followed by 4% PFA in PBS. Brains were dissected and post-fixed overnight in 4% PFA at 4 °C, then washed with PBS and transferred to 30% sucrose in PBS for at least three days. Brains were mounted coronally for cryosectioning in OCT Compound (Fisher HealthCare, 4585) on dry ice. Sections were cut to 25 µm thickness, divided evenly among six wells, and stored in PBS with 0.01% sodium azide at 4 °C until staining. For immunostaining, free floating sections were washed 3 times in 0.2% Triton X-100 in PBS, blocked for 1 hr at room temperature in 5% donkey serum in 0.4% Triton X-100 in PBS, then incubated with primary antibodies in 2% donkey serum in 0.4% Triton X-100 in PBS overnight at 4 °C rocking. Following three washes with 0.2% Triton in PBS, sections were incubated with secondary antibodies in 2% donkey serum in 0.4% Triton X-100 in PBS for 1 hr at room temperature. Sections were again washed three times with 0.2% Triton X-100 in PBS, stained with DAPI for 10 min (14.3 mM in PBS) and washed three times in PBS before mounting on glass slides using Prolong Diamond Antifade Mountant. TUNEL staining was performed using the DeadEnd Fluorometric TUNEL System (Promega, G3250) with a modified protocol as described previously (Li et al., 2021).

Immunoprecipitation and isolation of ribosome associated mRNA

Immunoprecipitation of HA-tagged ribosomes was conducted following the protocol described in Sanz et al., 2019. Briefly, hippocampi from both hemispheres were dissected in ice cold PBS from mice of desired genotypes at postnatal day 15, and were stored at –80 °C before further processing. Frozen tissues were homogenized by Dounce homogenization using 30 passes pestle A and 30 passes pestle B in 1.5 mL homogenization buffer (50 mM Tris, pH 7.5, 1% NP-40, 100 mM KCl, 12 mM MgCl2, 100 μg/mL cycloheximide, cOmplete EDTA-free protease inhibitor cocktail (Roche), 1 mg/mL heparin, 200 U/mL RNasin, 1 mM DTT). Following centrifugation at 10,000 x g for 10 min at 4 °C, 5 µg anti-HA high affinity (Roche) were added to the supernatant and incubated 4 hours rotating end-over-end at 4 °C. The entire antibody-lysate solution was added to 400 µl Protein G Dynabeads per sample overnight rotating end-over-end at 4 °C. High salt buffer was prepared (50 mM Tris, pH 7.5, 1% NP-40, 300 mM KCl, 12 mM MgCl2, 100 µg/mL cycloheximide, 0.5 mM DTT), and beads were washed 3x10 min using a magnetic tube rack. During the final wash, samples were transferred to a new tube, and beads were eluted in 350 µl of RLT buffer (from the Qiagen RNAeasy Minikit) supplemented with 1% β-mercaptoethanol. RNA was extracted following manufacturer’s instructions in the RNAeasy Minikit (QIAGEN). RNA integrity was measured using an Agilent TapeStation conducted at the IGM Genomics Center, University of California, San Diego, La Jolla, CA. All RNA for sequencing had RIN ≥8.0, 28 S/18S≥1.0.

To confirm immunoprecipitation in RiboTag IP samples, 10% of IP sample was isolated after final wash in high salt buffer. After removal of high salt buffer, proteins were eluted in 2X RIPA buffer and 4X Laemmli Sample Buffer (Bio-Rad, 161–0747) by heating 10 min at 50 °C. Beads were separated using a magnetic tube rack, the supernatant was isolated and beta-mercaptoethanol was added. Samples were boiled at 95 °C for 10 min and centrifuged 5 min at 13,000 x g. Immunoprecipitated samples were separated by SDS-PAGE using Any kD Mini-PROTEAN TGX Precast Protein Gels (Bio-Rad, 4569034).

To ensure appropriate depletion of transcripts from non-Slc17a7 expressing cells, we performed qRT-PCR analysis on representative marker genes for cell types in immunoprecipitated glutamatergic neuron RNA relative to whole hippocampal RNA. Briefly, RNAs isolated from whole hippocampi and immuoprecipitated from glutamatergic neurons were reverse transcribed to cDNA using Superscript III First Strand Synthesis System (Invitrogen, cat#18080051) following the manufacturer’s protocol. 100 ng RNA/sample was reverse transcribed with random hexamers. iQ Sybr Green Supermix (Bio-Rad, #1708880) was used for qPCR, and mRNA levels of marker genes (Slc17a7 (glutamatergic neurons), Wfs1 (CA1 neurons), Gfap (Astrocytes), and Vgat (inhibitory neurons)) were normalized to Gapdh expression. Expression levels of qRT-PCR samples were analyzed using the CFX Real-Time PCR Detection System and CFX Manager Software (Bio-Rad). Relative enrichment of marker genes was evaluated using the comparative CT method. All samples were run in triplicate. Primers for Gapdh, Slc17a7, Wfs1, Gfap, and Vgat are from Furlanis et al., 2019; Supplementary file 4.

Sequencing

Library preparation and sequencing for ribosome associated mRNAs were performed by the UCSD IGM Genomics Center using Illumina Stranded mRNA Prep. Sequencing was performed on NovaSeq S4 with PE100 reads.

Read mapping

Following paired end RNA sequencing of isolated RNA, >24 million reads per sample were obtained (n=3DLK(iOE)/3 WT, n=4 DLK(cKO)/4 WT). The Galaxy platform was used for read mapping and differential expression analysis (Afgan et al., 2018). Read quality was checked using FastQC (version 0.11.8). Reads were mapped to the mouse reference genome (mm10) using STAR galaxy version 2.6.0b-1 with default settings (Dobin et al., 2013). Four DLK(cKO) and controls included 2 male and 2 female. For DLK (iOE), one female sample was removed from each genotype control and DLK (iOE) due to read mapping variability/read quality, resulting in N=3 per genotype (2 male/1 female). Mapped reads were assigned to genes using featureCounts version 1.6.3 (Liao et al., 2014). High Pearson correlation (r>0.99) was observed between all Slc17a7Cre/+;Map3k12fl/fl;Rpl22HA/+ or Slc17a7Cre/+;H11-DLK(iOE)/+;Rpl22HA/+ samples and their respective littermate controls. Differential gene expression analysis was conducted using DESeq2 galaxy version 2.11.40.2 (Love et al., 2014) with genotype, sex, and batch included as factors in the analysis. Generation of volcano plots was performed in RStudio version 1.2.1335 using the ggplot2 package version 3.3.5 (Wickham, 2016). Heatmaps were generated using the heatmap.2 function on Galaxy (Galaxy version 3.0.1) using normalized gene counts with a log2 transformation and scaling by row.

Gene ontology

Gene ontology analysis was performed using DAVID 2021 version (Huang et al., 2009; Sherman et al., 2022) on genes found to be differentially expressed with <0.05. For gene ontology and pathway analysis, background gene lists were generated by removing any gene with a base mean from DEseq2 normalization less than 1. Gfap was removed from GO and pathway analysis as a differentially expressed gene as it likely reflected a small amount of contamination from non-Slc17a7-positive cells. DAVID analysis was performed using default thresholds, and Benjamini corrected p-values are reported. GO terms displayed in figures were chosen from top terms reaching significance related to biological processes or cellular components (BP5, CC4 or CC5) categories after filtering terms for semantic similarity. For SynGO analysis, mouse genes detected as differentially expressed were converted to human IDs using the ID conversion tool, and analysis was performed using the brain expressed background gene list provided by SynGO (Koopmans et al., 2019; Version/release 20210225).

Rank rank hypergeometric overlap (RRHO) analysis for correlation of gene expression patterns

We used Rank Rank Hypergeometric overlap (https://systems.crump.ucla.edu/rankrank/rankranksimple.php) to compare DLK(iOE) and DLK(cKO) translatome datasets (Plaisier et al., 2010). Input gene lists included 12740 genes which were expressed across all samples. For each gene, the -Log10Padj was multiplied by the sign of the fold change to obtain the metric used for ranking. Both DLK(iOE) and DLK(cKO) datasets were ranked in order to have increasing DLK along the x and y axis. RRHO was run using a step size of 100 genes. The Benjamini-Yekutieli corrected graph is shown.

Hippocampal spatial expression analysis

Comparison with gene expression databases: False color expression images from the Allen Mouse Brain Atlas were used for evaluating expression pattern, and numbers were assigned based on color in dorsal hippocampus (Red = 3, Yellow = 2, Blue/Green = 1, No = 0). When intensity varied across sections or intensity was in-between two categories, preference was given to depicting general patterns of relative expression over absolute signal. When in situ data was not available, or expression patterns were unclear, we used additional transcriptomic data to assess spatial expression (Habib et al., 2016; Zeisel et al., 2018), and values were chosen to reflect relative expression. Generally, the following scale was used for Habib et al., 2016 data through the Single Cell Portal: 0 if next to no signal, 1 if expression in some cells, but average was still zero, 2 if quartile 3 value in violin plot is >0, 3 if higher average signal, again values were chosen to reflect relative expression. Genes were categorized as enriched in a region/s if one or two regions show higher values than another region. If two regions show different expression levels but are two levels above third region, the gene is considered as enriched in both (i.e. CA1=2, CA3=3, DG = 0, considered as CA1, CA3 enriched). If only one level above other regions, the gene is enriched only in the region with strongest expression (i.e. CA1=3, CA3=2, DG = 1, considered as CA1 enriched). Most expressed elsewhere in hippocampus used when the strongest expression is found in another region/cell type, and other descriptions do not explain where most of the signal is.

Comparison with CamK2-RiboTag and Grik4-RiboTag data: Gene set enrichment analysis (GSEA) (4.2.2) (Subramanian et al., 2005) was performed on Slc17a7-RiboTag expression data after filtering lowly expressed genes using normalized counts. Analysis was conducted using the parameters: 1000 permutations, no collapse gene set, and permutation type gene set, with all other settings as default. To define gene sets for CA1 or CA3 enriched genes, we analyzed RiboTag datasets (Traunmüller et al., 2023; GSE209870) in wild type 6-week-old CA1 and CA3 neurons, from CamK2-cre and Grik4-cre mice, respectively. We compared the CamK2-RiboTag dataset and Grik4-RiboTag dataset to identify genes which were enriched in CA1 compared to CA3 or vice versa, applying an expression filter (average of at least 50 reads/animal) to ensure genes enriched in a particular region were expressed. The top 100 genes enriched in CamK2-RiboTag relative to Grik4-RiboTag were considered ‘CA1 genes’. The top 100 genes enriched in Grik4-RiboTag relative to CamK2-RiboTag were considered ‘CA3 genes’. 82 out of 100 GRIK4 (CA3) and 83 out of 100 CAMK2 (CA1) enriched genes were expressed in both our WT and DLK(cKO) samples (Supplementary file 3 CamK2 Grik4 enriched genes).

RNAscope analysis

The RNAscope Fluorescent Multiplex Reagent kit (Amp 4 Alt A-FL, Cat. #320850) (Wang et al., 2012) with probes from Advanced Cell Diagnostics were used. The protocol was carried out under RNase-free conditions and following the manufacturer’s instructions. Mice were anesthetized with isoflurane prior to decapitation. Brains were dissected immediately and flash frozen in OCT at –80 °C. Fresh-frozen tissue was cryosectioned coronally to 20 µm, collected on glass slides (Superfrost Plus), and stored at –80 °C. Slides were fixed with 4% paraformaldehyde, dehydrated with 50% ethanol, 70% ethanol, and 2 x washes in 100% ethanol for 5 min each at RT, followed by incubation in Protease IV reagent for 30 min at 40 °C. Hybridization with target probes was performed at 40 °C for 2 hr in a humidified slide box in an incubator followed by wash and amplification steps according to the manufacturer’s protocol. Finally, tissue was counterstained with DAPI, and mounted with Prolong diamond antifade mountant. All target probes were multiplexed with probes for Slc17a7 to label glutamatergic neurons.

Primary hippocampal neuron cultures and immunostaining

Prior to preparing cultures, Poly-D-Lysine (Corning, Cat#354210) was coated on 12 mm glass coverslips (0.2 mg/mL) or six-well plates (0.05 mg/ml) for 2 days at 37 °C. Neurons with indicated genotypes were labeled by tdTomato from Cre-dependent Rosa26-tdTomato generated from the following crosses: for control: Slc17a7Cre/+ X Rosa26tdT/+; for DLK(cKO): Slc17a7Cre/+;Map3k12fl/fl X Map3k12fl/fl;Rosa26tdT/+; for DLK(iOE): H11-DLK(iOE)/H11-DLK(iOE) X Slc17a7 Cre/+;Rosa26tdT/+. Primary neurons were generated from hippocampi of P1 pups. Mice were rapidly decapitated, then brains were removed, placed into ice cold HBSS (calcium- and magnesium-free) supplemented with 10 mM HEPES for removal of meninges and dissection of hippocampi (Kaech and Banker, 2006). Dissected hippocampi were dissociated in HBSS with HEPES in 0.25% trypsin for 15 min at 37 °C, and were then washed 3 times with 5 ml of 20% Fetal bovine serum in HBSS. Dissociated cells from a litter were pooled into the same culture. Cells were triturated in Opti-MEM supplemented with 20 mM glucose by five passes with an unpolished glass pipette and five to ten passes using a fire polished glass pipette. Cells were counted using a hemocytometer, and 60,000 cells were plated per coverslip into a 24-well plate or 300,000 per well of a six-well dish. Cultures were kept in an incubator at 37 °C with 5% CO2. After 4 hr, plating media was replaced with prewarmed Neurobasal Medium supplemented with glutamine, penicillin/streptomycin, and B27. Cells were fixed after 48 hr (DIV2) or on DIV14 with prewarmed 4% PFA/4% sucrose in PBS for 20 min at room temperature followed by three washes with PBS. Media were changed carefully to minimize impacts to growth cone morphology.

Staining of fixed neurons was performed in 24-well plates. Coverslips were incubated in 50 mM ammonium chloride for 10 min, followed by three washes PBS, 5 min 0.1% Triton X-100 in PBS, and blocking in 30 mg/ml Bovine serum albumin (BSA) in 0.1% Triton in PBS for 30 min. Coverslips were incubated in primary antibody diluted in 30 mg/ml BSA in 0.1% Triton in PBS according to antibody table for 90 min at room temperature followed by four washes in 0.1% Triton in PBS. Secondary antibodies were diluted in 30 mg/ml BSA in 0.1% Triton in PBS with 1% donkey serum according to antibody table, and incubated for 60 min at room temperature. Finally, coverslips were washed three times in 0.2% Triton in PBS, stained with DAPI, washed three times with PBS, and mounted using Prolong Diamond Antifade Mountant. For an unknown reason, co-immunostaining of DLK and tyrosinated tubulin led to a pattern of DLK staining different from the punctate appearance of DLK observed in other conditions. The typical appearance of DLK could still be observed in cells with high levels of DLK. This altered appearance was not observed during co-immunostaining of DLK and acetylated tubulin.

Confocal imaging and quantification

Fluorescent images were acquired using a Zeiss LSM800 confocal microscope using a 10x, 20x, or 63x objective. All tissue sections and neurons within the same experiment were imaged under identical conditions. For brain tissue, three sections per mouse were imaged with a minimum of three mice per genotype for data analysis. Dorsal hippocampal images were taken from approximately bregma –1.5 mm to –2.3 mm. For image analysis, the quantification was performed blind to genotype or in an automated manner when possible. All image processing and analysis was performed using Fiji distribution of ImageJ unless otherwise specified (Schindelin et al., 2012).

For quantification of mRNA puncta, ROI were drawn to count puncta overlapping with nuclei of Slc17a7-positive cells. Individual puncta were counted from >50 cells per genotype in a blinded manner. Puncta counts were normalized to Slc17a7 puncta counts to control for variability in staining or preservation of RNA. Three to four sections per mouse were quantified and three mice per genotype were stained with each probe.

Pyramidal cell layer thickness was measured across CA1 by averaging the lengths of three perpendicular lines extending across the maximum projected z-stack of the pyramidal cell layer for each section. Three sections were averaged per mouse from dorsal hippocampus. For sections including ventral hippocampus, cell layer thickness of CA1 was measured using three lines either above the ventral edge of the suprapyramidal blade of dentate gyrus (Dong et al., 2009) for dorsal hippocampus (posterior) quantifications or below the ventral edge of the DG for ventral CA1 quantifications. Hippocampal cross-sectional area was measured by tracing outlines of CA1, CA3, or DG (including dendritic layers) in dorsal hippocampus sections.

DLK signal intensity in immunofluorescence images was quantified by drawing an outline around CA1, CA3, or DG (all cell layers), and measuring the mean fluorescence intensity.

Tuj1, tyrosinated tubulin, acetylated tubulin, and MAP2 intensities were measured using the mean gray value from auto thresholding (default) over stratum radiatum of CA1, the molecular layer of DG, or stratum lacunosum-moleculare, stratum radiatum, and stratum lucidum of CA3.

Staining of p-c-Jun in P60 animals and c-Jun from all timepoints was quantified from 20x images using mean gray values of ROIs for each brain slice cropped around the pyramidal cell or granule cell layers with background subtraction of non-nuclear signal from dendritic regions. Analysis of p-c-Jun-positive nuclei in DLK(iOE) mice was counted from 10x images with using an intensity threshold of 20000 (P10) or 110 or 140 (P15) depending on imaging conditions. Nuclei were separated using a watershed, and all nuclei larger than 10 µm2 were counted.

TUNEL positive signals were counted as fluorescent signals overlapping with the pyramidal cell or dentate granule cell layer in each region from 10x tile scan images of dorsal hippocampus. Z-stacks covering the entire section were max projected for quantification.

VGLUT1, Bassoon, and Homer1 puncta were quantified from stratum radiatum of dorsal CA1. Images were quantified using a single slice image, and a 25x25 µm ROI was chosen to minimize absence of puncta due to cell bodies. A gaussian filter of 1 pixel was applied to the image. Background subtraction was performed using a rolling ball radius of 10 pixels, and an automated threshold was applied to the image using the Otsu method followed by a watershed to separate clustered puncta. Puncta larger than 2 pixels were counted for individual proteins. Overlap of Bassoon and Homer1 puncta of any size were counted. The number and average size of puncta were recorded from two images per brain section and three sections per mouse.

GFAP mean fluorescence intensity was quantified in a 312µm x 312µm box around the pyramidal cell or granule cell layers of CA1, CA3, and DG with background intensity subtracted after measuring from an area without GFAP signal.

Neurons were selected for neurite outgrowth and axon analysis after confirming DLK protein level by antibody staining and measurement of DLK fluorescence intensity in cell soma at DIV2. While we used tdTomato as a reporter for Slc17a7-positive neurons, not all tdTomato-positive neurons showed detectable differences in DLK levels at this early (DIV2) timepoint. Cell somas were outlined using tdTomato, and DLK integrated density was measured. Integrated density reflected the mean gray value multiplied by the area. Slc17a7Cre/+ control cells were selected for further analysis if DLK integrated density was 4000–8500. Cells from DLK(cKO) cultures with integrated density values of DLK less than 4000 were selected for further analysis as ‘DLK(cKO)’ and cells from DLK(iOE) with integrated density values of greater than 8500 were selected for further analysis as ‘DLK(iOE)’. While we observed variably increased DLK signals in DLK(iOE) neurons from moderate to strong, all DLK(iOE) neurons with increased levels above the set threshold were grouped together in quantifications due to limited numbers of neurons. Primary neurites were counted in a blinded manner from tdTomato channel, counting both branches and filopodia originating from cell soma region. Neurites were considered as axons in axon specification analysis if longer than 90 µm.

Bassoon puncta in cell culture were quantified from 20 µm stretches of neurites. Regions for analysis were selected based on tdTomato-positive signal on thin processes without dendritic spines exhibiting Bassoon signal, that was not in a region densely populated by Bassoon signal from other neurites. DLK levels were also used to select ROIs. Signal from tdTomato was used to create a 10 pixel ROI along the neurite. Bassoon puncta were identified in a blinded manner by smoothing the image, applying a triangle threshold, and manually dividing merged puncta based on bassoon intensity. All puncta 5 pixels or larger and overlapping with tdTomato signal were analyzed for puncta size and density.

Dendritic spines were quantified from a 20 µm countable and representative stretch of dendrite within 75 µm of the neuron soma from one of the three largest dendrites. Spine density was counted using tdTomato signal, and calculated by counting total dendritic spines divided by the traced length of dendrite. Spines were manually categorized following measurements in Risher et al., 2014. Filopodia (>2 µm) are not included in spine density counts. Spines were quantified from independent cultures per genotype with 8–16 neurons per culture.

Stastical analysis

All statistical analysis shown in graphs was performed using GraphPad Prism 9.4.0. Points represent individual values, with bars reflecting mean values, and error bars plotting standard error of the mean (SEM).

Acknowledgements

We thank members of our labs for their support and valuable discussion throughout this work. We are grateful to Emily Griffin in Susan Ackerman’s lab and Caitlin Rodriguez in Aaron Gitler’s lab for advice on troubleshooting immunoprecipitation of ribosomes for RiboTag, to Brenda Bloodgood for advice with RNAscope experiments, Gentry Patrick, Lara Dozier, and Frank Bradke for their guidance in primary hippocampal cultures, Megan Williams and Stacey Glasgow for advice and CA1 and CA3 neuron antibodies, and Gareth Thomas for discussion and comments. This publication includes data generated at the UC San Diego IGM Genomics Center utilizing an Illumina NovaSeq 6000 that was purchased with funding from a National Institutes of Health SIG grant (#S10 OD026929). DA was supported by the TÜBİTAK 2214 A International Research Fellowship Programme. EMR received an Innovative Research Grant from the Kavli Institute for Brain and Mind. This work was supported by a grant from NIH (NS R35 127314 to YJ).

Funding Statement

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Contributor Information

Yishi Jin, Email: yijin@ucsd.edu.

Moses V Chao, New York University Langone Medical Center, United States.

Sacha B Nelson, Brandeis University, United States.

Funding Information

This paper was supported by the following grants:

  • National Institute of Neurological Disorders and Stroke R35 127314 to Yishi Jin.

  • Kavli Institute for Brain and Mind, University of California, San Diego 2020-1711 to Erin M Ritchie.

  • TÜBİTAK 2214-A to Dilan Acar.

Additional information

Competing interests

No competing interests declared.

Author contributions

Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Writing – original draft, Writing – review and editing.

Formal analysis, Investigation.

Formal analysis, Investigation.

Formal analysis, Investigation.

Methodology.

Resources, Writing – review and editing.

Conceptualization, Resources, Funding acquisition, Investigation, Writing – original draft, Project administration, Writing – review and editing.

Ethics

All of the animals were handled according to approved institutional animal care and use committee (IACUC) protocols (#S13072) of the University of California San Diego.

Additional files

Supplementary file 1. Excel file containing DLK(cKO) differentially expressed genes.

File containing differential expression results from DLK(cKO) compared to control and their regional enrichment. Highlighted columns show gene symbols of differentially expressed genes (padj <0.05), Log2 fold change, and adjusted p-values. Sheets show genes sorted by all differentially expressed genes, upregulated genes, downregulated genes, and synaptic genes.

elife-101173-supp1.xlsx (4.7MB, xlsx)
Supplementary file 2. Excel file containing DLK(iOE) differentially expressed genes.

File containing differential expression results from DLK(iOE) compared to control and their regional enrichment. Highlighted columns show gene symbols of differentially expressed genes (padj <0.05), Log2 fold change, and adjusted p-values. Sheets show genes sorted by all differentially expressed genes, regional expression, upregulated genes, downregulated genes, and synaptic genes.

elife-101173-supp2.xlsx (4.8MB, xlsx)
Supplementary file 3. Excel file containing CamK2 and Grik4 RiboTag enriched genes.

File containing top 100 genes enriched in CamK2-RiboTag compared to Grik4-RiboTag and vice versa (Traunmüller et al., 2023; GSE209870) as described in methods.

elife-101173-supp3.xlsx (27.9KB, xlsx)
Supplementary file 4. Primers used for genotyping and qRT-PCR.

File containing primer sequences used for genotyping and qRT-PCR.

elife-101173-supp4.docx (17.1KB, docx)
MDAR checklist

Data availability

Sequencing data have been deposited in GEO under accession code GSE266662.

The following dataset was generated:

Ritchie EM, Jin Y. 2025. DLK-dependent protein network regulates hippocampal glutamatergic neuron degeneration. NCBI Gene Expression Omnibus. GSE266662

The following previously published dataset was used:

Traunmueller L, Scheiffele P. 2022. Trans-cellular regulation of synaptic properties by neuron-specific alternative splicing. NCBI Gene Expression Omnibus. GSE209870

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eLife Assessment

Moses V Chao 1

This manuscript describes the impact of modulating signaling by a key regulatory enzyme, Dual Leucine Zipper Kinase (DLK), on hippocampal neurons. The results are interesting and will be important for scientists interested in synapse formation, axon specification, and cell death. The authors have carefully addressed the comments made by the reviewers and the findings are convincing in large part due to the use of extensive mouse genetics, detailed gene expression of enriched genes, and recognition of neuron vulnerability.

Reviewer #1 (Public review):

Anonymous

Summary:

In this work Ritchie and colleagues explore functional consequences of neuronal over-expression or deletion of the MAP3K DLK that their labs and others have strongly implicated in both axon degeneration, neuronal cell death, and axon regeneration. Their recent work in eLife (Li, 2021) showed that inducible over-expression of DLK (or the related LZK) induces neuronal death in the cerebellum. Here, they extend this work to show that inducible over-expression in Vglut1+ neuron also kills excitatory neurons in hippocampal CA1, but not CA3. They complement this very interesting finding with translatomics to quantify genes whose mRNAs are differentially translated in the context of DLK over-expression or knockout, the latter manipulation having little to no effect on the phenotypes measured. The authors note that several genes and pathways are differentially regulated according to whether DLK is over-expressed or knocked out. They note DLK-dependent changes in genes related to synaptic function and to the cytoskeleton and ultimately relate this in cultured neurons to findings that DLK over-expression negatively impacts synapse number and changes microtubules and neurites, though with a less obvious correlation.

Strengths:

Where this work represents a conceptual advance is in defining DLK-dependent changes in translation. Moreover, the finding that DLK may differentially impact neuronal death will become the basis for future studies exploring whether DLK contributes to differential neuronal susceptibility to death, which is a broadly important topic.

Comments on the latest version:

The addition of the P10 data is an important advance. With this, the authors have satisfactorily addressed the concerns that I raised.

Reviewer #2 (Public review):

Anonymous

This manuscript describes the impact of deleting or enhancing the expression of the neuronal-specific kinase DLK in glutamatergic hippocampal neurons using clever genetic strategies, which demonstrates that DLK deletion had minimal effects while overexpression resulted in neurodegeneration in vivo. To determine the molecular mechanisms underlying this effect, ribotag mice were used to determine changes in active translation which identified Jun and STMN4 as DLK-dependent genes that may contribute to this effect. Finally, experiments in cultured neurons were conducted to better understand the in vivo effects. These experiments demonstrated that DLK overexpression resulted in morphological and synaptic abnormalities.

Strengths:

This study provides interesting new insights into the role of DLK in the normal function of hippocampal neurons. Specifically, the study identifies:

(1) CA1 vs CA3 hippocampal neurons have differing sensitivity to increased DLK signaling.

(2) DLK-dependent signaling in these neurons is similar to but distinct from the downstream factors identified in other cell types, highlighted by the identification of STMN4 as a downstream signal.

(3) DLK overexpression in hippocampal neurons results in signaling that is similar to that induced by neuronal injury.

The study also provides confirmatory evidence that supports previously published work through orthogonal methods, which adds additional confidence to our understanding of DLK signaling in neurons. Taken together, this is a useful addition to our understanding of DLK function.

Comments on the latest version:

The authors have sufficiently addressed all issues raised with the initial manuscript.

eLife. 2025 Mar 11;13:RP101173. doi: 10.7554/eLife.101173.3.sa3

Author response

Erin M Ritchie 1, Dilan Acar 2, Siming Zhong 3, Qianyi Pu 4, Yunbo Li 5, Binhai Zheng 6, Yishi Jin 7

The following is the authors’ response to the original reviews.

eLife Assessment

This manuscript describes the impact of modulating signaling by a key regulatory enzyme, Dual Leucine Zipper Kinase (DLK), on hippocampal neurons. The results are interesting and will be important for scientists interested in synapse formation, axon specification, and cell death. The methods and interpretation of the data are solid, but the study can be further strengthened with some additional studies and controls.

We greatly appreciate the thorough review and thoughtful suggestions from the reviewers and editors on our original manuscript. We provide point-to-point response below. We added new studies on P10 mice and controls as suggested, and made revision of figures and texts for clarification. The revised manuscript includes three new supplemental figures; major text revision is copied under response.

Reviewer #1 (Public Review):

Summary:

In this work, Ritchie and colleagues explore functional consequences of neuronal over-expression or deletion of the MAP3K DLK that their labs and others have strongly implicated in both axon degeneration, neuronal cell death, and axon regeneration. Their recent work in eLife (Li, 2021) showed that inducible over-expression of DLK (or the related LZK) induces neuronal death in the cerebellum. Here, they extend this work to show that inducible over-expression in Vglut1+ neurons also kills excitatory neurons in hippocampal CA1, but not CA3. They complement this very interesting finding with translatomics to quantify genes whose mRNAs are differentially translated in the context of DLK over-expression or knockout, the latter manipulation having little to no effect on the phenotypes measured. The authors note that several genes and pathways are differentially regulated according to whether DLK is over-expressed or knocked out. They note DLK-dependent changes in genes related to synaptic function and the cytoskeleton and ultimately relate this in cultured neurons to findings that DLK over-expression negatively impacts synapse number and changes microtubules and neurites, though with a less obvious correlation.

Strengths:

This work represents a conceptual advance in defining DLK-dependent changes in translation. Moreover, the finding that DLK may differentially impact neuronal death will become the basis for future studies exploring whether DLK contributes to differential neuronal susceptibility to death, which is a broadly important topic.

We thank the reviewer for the comments on the value of our work.

Weaknesses:

This seems like two works in parallel that the authors have not yet connected. First is that DLK affects the translation of an interesting set of genes, and second, that DLK(OE) kills some neurons, disrupts their synapses, and affects neurite growth in culture.

Specific questions:

(1) Is DLK effectively knocked out? The authors reference the floxxed allele in their 2016 work (PMID: 27511108), however, the methods of this paper say that the mouse will be characterized in a future publication. Has this ever been published? The major concern is that here the authors show that Cre-mediated deletion results in a smaller molecular weight protein and the maintenance of mRNA levels.

We apologize for out-of-date citation of the DLK(cKO)fl/fl mice. The DLK(cKO)fl/fl mice have been published in (Li et al., 2021; Saikia et al., 2022); excision of the flox-ed exon was verified using several Cre drivers (Pv-Cre, AAV-Cre, and VGlut1-Cre in this study). The flox-ed exon contains the initiation ATG and 148 amino acids. By western blot analysis using antibodies against C-terminal peptides of DLK on cerebellar extracts (in Li et al., 2021) and hippocampal extracts (this study), the full-length DLK protein was significantly reduced (Fig 1A-B); DLK is expressed in other hippocampal cells, in addition to glutamatergic neurons, explaining remaining full-length DLK detected.

Our Ribo-seq of VGlut1-Cre; DLK(cKO)fl/fl detected remaining Dlk mRNAs lacking the floxed exon (Fig.S1C), which has several candidate ATG at amino acid 223 and after (Fig.S1C1). We detected a very faint band for smaller molecular weight proteins on western blots, only when the membrane was exposed under 5X longer exposure using Pico PLUS Chemiluminescent Substrate (Thermo Scientific, 34580) and a Licor Odyssey XF Imager (revised Fig. S1B). This smaller molecular weight protein might be produced using any candidate ATGs, but would represent an N-terminal truncated DLK protein lacking the ATP binding site and ~1/4 of the kinase domain, i.e. not a functional kinase.

The revised manuscript has updated citation for DLK(cKO)fl/fl. Revised Fig.S1B includes images of a western blot under normal exposure vs longer exposure of western blots using anti-DLK antibodies. New Fig.S1C1 shows effects of floxed exon on DLK.

(2) Why does DLK(OE) not kill CA3 neurons? The phenomenon is clear but there is no link to gene expression changes. In fact, the highlighted transcript in this work, Stmn4, changes in a DLK-dependent manner in CA3.

We agree that this is a very interesting question not answered by our gene expression analysis. While we verified Stmn4 expression levels to correlate to the levels of DLK, we do not think that increased Stmn4 per se in DLK(iOE) is a major factor accounting for CA1 death vs CA3 survival. Several published studies have also reported regulation of Stmn4 mRNAs in other cell types, in the contexts of cell death (Watkins et al., 2013; Le Pichon et al., 2017) and axon regeneration and cytoskeleton disruption (Asghari Adib et al., 2024; DeVault et al., 2024; Hu et al., 2019; Shin et al., 2019). As Stmns have significant expression and function redundancy, conventional knockdown or overexpression of individual Stmn generally does not lead to detectable effects on cellular function. As CA3 neurons are widely known for their dense connections and show resilience to NMDA-mediated neurotoxicity (Sammons et al., 2024; Vornov et al., 1991), we speculate that the differential vulnerability of CA1 and CA3 under DLK(iOE) is a reflection of both the intrinsic property, such as gene expression, and also their circuit connection.

In the revised manuscript, we have included following statement on pg 18:

‘While our data does not pinpoint the molecular changes explaining why CA3 would show less vulnerability to increased DLK, we may speculate that DLK(iOE) induced signal transduction amplification may differ in CA1 vs CA3. CA1 genes appear to be more strongly regulated than CA3 genes, consistent with our observation that increased c-Jun expression in CA1 is greater than that in CA3. Other parallel molecular factors may also contribute to resilience of CA3 neurons to DLK(iOE), such as HSP70 chaperones, different JNK isoforms, and phosphatases, some of which showed differential expression in our RiboTag analysis of DLK(iOE) vs WT (shown in File S2. WT vs DLK(iOE) DEGs). Together with other genes that show dependency on DLK, the DLK and Jun regulatory network contributes to the regional differences in hippocampal neuronal vulnerability under pathological conditions.’

Further we state in ‘Limitation of our study’ on pg 20:

‘Our analysis also does not directly address why CA3 neurons are less vulnerable to increased DLK expression. Future studies using cell-type specific RiboTag profiling and other methods at a refined time window will be required to address how DLK dependent signaling interacts with other networks underlying hippocampal regional neuron vulnerability to pathological insults.’

We hope our data will stimulate continued interests for testable hypothesis in future studies.

(3) Why are whole hippocampi analyzed to IP ribosome-associated mRNAs? The authors nicely show a differential effect of DLK on CA1 vs CA3, but then - at least according to their methods ¬- lyse whole hippocampi to perform IP/sequencing. Their data are therefore a mix of cells where DLK does and does not change cell death. The key issue is whether DLK does/does not have an effect based on the expression changes it drives.

At the time of planning the Ribo-Tag experiment several years ago, we focused on the hippocampal glutamatergic neurons. Due to technical difficulty in micro-dissecting individual hippocampal regions from this early timepoint, we opted to use whole hippocampi to isolate ribosome-associated mRNAs. We agree with the reviewer that it is important to sort out DLK-dependent general gene expression changes vs those specific to a particular cell type where DLK impacts its survival. With emerging CA1, CA3 and other cell-type specific Cre drivers and advanced RNAseq technology, we hope that our work will stimulate broad interest in these questions in future studies.

In the revised manuscript, we have included new analysis comparing our Vglut1-RiboTag profiling (P15) with CamK2-RiboTag (for CA1) and Grik4-RiboTag (for CA3) (P42) published in Traunmüller et al., 2023 (GSE209870). We find that >80% of the top ranked genes in their CamK2-RiboTag (for CA1) and Girk4-RiboTag (for CA3) were detected in our VGlut1-RiboTag (revised methods and Supplemental Excel File S3). CA1-enriched genes tended to be expressed higher in DLK(cKO), compared to control, whereas CA3-enriched genes showed less significant correlation to DLK expression levels. Additionally, many genes known to specify CA1 fate do not show significant downregulation in DLK(iOE). This analysis, along with other data in our manuscript, is consistent with an idea that DLK does not regulate neuronal fate.

In the revised manuscript, we presented this additional analysis in Fig. S6K-L, and expanded text description on page 9:

‘Additionally, we compared our Vglut1-RiboTag datasets with CamK2-RiboTag and Grik4-RiboTag datasets from 6-week-old wild type mice reported by (Traunmüller et al., 2023; GSE209870). We defined a list of genes enriched in CamK2-expressing CA1 neurons relative to Grik4-expressing CA3 neurons (CA1 genes), and those enriched in Grik4-expressing CA3 neurons (CA3 genes) (File S3). When compared with the entire list of Vglut1-RiboTag profiling in our control and DLK(cKO), we found CA1 genes tended to be expressed more in DLK(cKO) mice, compared to control (Fig.S6K), while CA3 genes showed a slight enrichment in control though the trend was less significant, and were less clustered towards one genotype (Fig.S6L). Moreover, many CA1 genes related to cell-type specification, such as FoxP1, Satb2, Wfs1, Gpr161, Adcy8, Ndst3, Chrna5, Ldb2, Ptpru, and Ntm, did not show significant downregulation when DLK was overexpressed. These observations imply that DLK likely specifically down-regulates CA1 genes both under normal conditions and when overexpressed, with a stronger effect on CA1 genes, compared to CA3 genes. Overall, the informatic analysis suggests that decreased expression of CA1 enriched genes may contribute to CA1 neuron vulnerability to elevated DLK, although it is also possible that the observed down-regulation of these genes is a secondary effect associated with CA1 neuron degeneration’.

(4) Is the subtle decrease in synapse number (Basson/Homer co-loc.) in the DLK (OE) simply a function of neurons (and their synapses, presumably) having died? At the P15 time point that the authors choose because cell death is minimal, there is still a ~25% reduction in CA1 thickness (Figure 2B), which is larger than the ~15% change in synapses (Figure 5H) they describe.

We thank reviewer for the question. To address this, we have analyzed synapses in the CA1 region at P10 in DLK(iOE) mice when there was no detectable loss of neurons. At P10, we did not detect significant changes in Bassoon, Homer1, or colocalized puncta in CA1 (Fig.S11A-F). In P15 DLK(iOE) mice, Homer1 puncta were slightly smaller (Fig.5L) and showed a significant decrease in CA1 SR (Fig.5I).

In the revised manuscript we have also redone our statistical analysis of synapses, using mice rather than ROIs (revised Fig. 5), as recommended by R3. We also analyzed synapses in CA3, and found no significant differences in P10 or P15 (Fig.S12). We would interpret the data to mean that the effects of DLK(OE) on synapses in CA1 may represent an early step in neuronal death. We hope that future studies will shed clarity on this question.

Reviewer #2 (Public Review):

This manuscript describes the impact of deleting or enhancing the expression of the neuronal-specific kinase DLK in glutamatergic hippocampal neurons using clever genetic strategies, which demonstrates that DLK deletion had minimal effects while overexpression resulted in neurodegeneration in vivo. To determine the molecular mechanisms underlying this effect, ribotag mice were used to determine changes in active translation which identified Jun and STMN4 as DLK-dependent genes that may contribute to this effect. Finally, experiments in cultured neurons were conducted to better understand the in vivo effects. These experiments demonstrated that DLK overexpression resulted in morphological and synaptic abnormalities.

Strengths:

This study provides interesting new insights into the role of DLK in the normal function of hippocampal neurons. Specifically, the study identifies:

(1) CA1 vs CA3 hippocampal neurons have differing sensitivity to increased DLK signaling.

(2) DLK-dependent signaling in these neurons is similar to but distinct from the downstream factors identified in other cell types, highlighted by the identification of STMN4 as a downstream signal.

(3) DLK overexpression in hippocampal neurons results in signaling that is similar to that induced by neuronal injury.

The study also provides confirmatory evidence that supports previously published work through orthogonal methods, which adds additional confidence to our understanding of DLK signaling in neurons. Taken together, this is a useful addition to our understanding of DLK function.

We thank the reviewer for careful reading and positive comments.

Weaknesses:

There are a few weaknesses that limit the impact of this manuscript, most of which are pointed out by the authors in the discussion. Namely:

(1) It is difficult to distinguish whether the changes in the translatome identified by the authors are DLK-dependent transcriptional changes, DLK-dependent post-transcriptional changes or secondary gene expression changes that occur as a result of the neurodegeneration that occurs in vivo. Additional expression analysis at earlier time points could be one method to address this concern.

We appreciate the reviewer’s comment, and have performed new analysis on c-Jun and p-c-Jun levels in CA1, CA3, and DG in P10 DLK(OE) mice. Our data suggest that in CA3 elevations in p-c-Jun and c-Jun occur separately from cell death in a DLK-dependent manner, though the high elevation of both p-c-Jun and c-Jun in CA1 correlates with cell death.

The data is presented in revised Fig.S7A,B, and described in revised text on pg 9-10:

‘In control mice, glutamatergic neurons in CA1 had low but detectable c-Jun immunostaining at P10 and P15, but reduced intensity at P60; those in CA3 showed an overall low level of c-Jun immunostaining at P10, P15 and P60; and those in DG showed a low level of c-Jun immunostaining at P10 and P15, and an increased intensity at P60 (Fig.S7A,C,E). In Vglut1Cre/+;H11-DLKiOE/+ mice at P10 when no discernable neuron degeneration was seen in any regions of hippocampus, only CA3 neurons showed a significant increase of immunostaining intensity of c-Jun, compared to control (Fig.S7A). In P15 mice, we observed further increased immunostaining intensity of c-Jun in CA1, CA3, and DG, with the strongest increase (~4-fold) in CA1, compared to age-matched control mice (Fig.S7C). The overall increased c-Jun staining is consistent with RiboTag analysis.’

Also, on pg.10:

In Vglut1Cre/+;H11-DLKiOE/+ mice, we observed increased p-c-Jun positive nuclei in CA1 at P10, and strong increase in CA1 (~10-fold), CA3 (~6-fold), and DG (~8-fold) at P15 (Fig.S7B,D).

(2) Related to the above, it is difficult to conclusively determine from the current data whether the changes in synaptic proteins observed in vivo are a secondary result of neuronal degeneration or a primary impact on synapse formation. The in vitro studies suggest this has the potential to be a primary effect, though the difference in experimental paradigm makes it impossible to determine whether the same mechanisms are present in vitro and in vivo.

We appreciate the comment, which is related to R1 point 4. We have performed further analysis and revised the text on pg.12 with the following text:

‘To assess effects of DLK overexpression on synapses, we immunostained hippocampal sections from both P10 and P15, with age-matched littermate controls. Quantification of Bassoon and Homer1 immunostaining revealed no significant differences in CA1 SR and CA3 SR and SL in P10 mice of _<_i>Vglut1Cre/+;H11-DLKiOE/+ and control (Fig.S11A-F, S12A-J). In P15, Bassoon density and size in CA1 SR were comparable in both mice (Fig 5G, H, K), while Homer1 density and size were reduced in DLK (iOE) (Fig.5G,I, L). Overall synapse number in CA1 SR was similar in DLK (iOE) and control mice (Fig.5J). Similar analysis on CA3 SR and SL detected no significant difference from control (Fig.S12M-V).’

We would interpret the data to mean that the effects of DLK (OE) on synapses in CA1 may represent an early step in neuronal death. We hope that future studies will shed clarity on this question.

Additionally, to address whether the same mechanisms are present in vitro, we have performed further analysis on cultured hippocampal neurons. As described in the Methods, we made hippocampal neuron cultures from P1 pups of the following crosses:

For control: Vglut1Cre/+ X Rosa26tdT/+

For DLKcKO: Vglut1Cre/+;DLK(cKO)fl/fl X Vglut1Cre/+;DLK(cKO)fl/fl;Rosa26tdT/+

For DLKiOE: H11-DLKiOE/iOE X Vglut1Cre/+;Rosa26tdT/+

Dissociated cells from a given litter were pooled into the same culture. Because there were different proportions of neurons with our genotype of interest in each culture, it is not simple to know whether DLK was causing significant cell death.

On pg 13, we stated our observation:

‘We did not notice an obvious effect of DLK(iOE) or DLK(cKO) on neuron density in cultures at DIV2. To assess neuronal type distribution in our cultures, we immunostained DIV14 neurons with antibodies for Satb2, as a CA1 marker (Nielsen et al., 2010), and Prox1, as a marker of DG neurons (Iwano et al., 2012). We did not observe significant differences in the proportion of cells labeled with each marker in DLK(cKO) or DLK(iOE) cultures (Fig.S13E). These data are consistent with the idea that DLK signaling does not have a strong role in neuron-type specification both in vivo and in vitro.

(3) The phenotype of DLK cKO mice is very subtle (consistent with previous reports) and while the outcome of increased DLK levels is interesting, the relevance to physiological DLK signaling is less clear. What does seem possible is that increased DLK may phenocopy other neuronal injuries but there are no real comparisons to directly address this in the manuscript. It would be helpful for the authors to provide this analysis as well as a table with all of the translational changes along with fold changes.

Thank you for the suggestion. The fold changes of genes showing significantly altered expression in DLK(cKO) and DLK(iOE) are provided in the excel files (Supplementary excel File S1 WT vs DLK(cKO) DEGs and File S2. WT vs DLK(iOE) DEGs, highlighted columns B and F).

On pg 6, we revised the text as following to include comparison of DLK levels in other physiological conditions and our mice:

‘Several studies have reported that DLK protein levels increase under a variety of conditions, including optic nerve crush (Watkins et al., 2013), NGF withdrawal (~2 fold) (Huntwork-Rodriguez et al., 2013; Larhammar et al., 2017), and sciatic nerve injury (Larhammar et al., 2017). Induced human neurons show increased DLK abundance about ~4 fold in response to ApoE4 treatment (Huang et al., 2019). Increased expression of DLK can lead to its activation through dimerization and autophosphorylation (Nihalani et al., 2000)’.

And,

‘Additional analysis at the mRNA level (supplemental excel, File S2. WT vs DLK(iOE) DEGs) and at the protein level (Fig.S8E) suggest that the increase in DLK abundance was around 3 times the control level. The localization patterns of DLK protein appeared to vary depending on region of hippocampus and age of animals in both control and Vglut1Cre/+;H11-DLKiOE/+ mice (Fig.S3C).’

In Discussion, we state (pg. 16): ‘The levels of DLK in our DLK(iOE) mice model appear comparable to those reported under traumatic injury and chronic stress.’

(4) For the in vivo experiments, it is unclear whether multiple sections from each animal were quantified for each condition. More information here would be helpful and it is important that any quantification takes multiple sections from each animal into account to account for natural variability.

We apologize this was unclear in the original manuscript.

In the revised methods, under Confocal imaging and quantification (pg 33), we stated: “For brain tissue, three sections per mouse were imaged with a minimum of three mice per genotype for data analysis.”

In revised figure legends, we made it clear that multiple sections from each animal have been used for quantification in all instances, i.e. “Each dot represents averaged thickness from 3 sections per mouse, N≥4 mice/genotype per timepoint.”

In Fig.1F-H: “Each dot represents averaged intensity from 3 sections per mouse”

In Fig.S3B “Data points represent individual mice, averages taken across 3 sections per mouse”

Reviewer #3 (Public Review):

Dr Jin and colleagues revisit DLK and its established multifactorial roles in neuronal development, axonal injury, and neurodegeneration. The ambitious aim here is to understand the DLK-dependent gene network in the brain and, to pursue this, they explore the role of DLK in hippocampal glutamatergic neurons using conditional knockout and induced overexpression mice. They produce evidence that dorsal CA1 and dentate gyrus neurons are vulnerable to elevated expression of DLK, while CA3 neurons appear unaffected. Then they identify the DLK-dependent translatome featured by conserved molecular signatures and cell-type specificity. Their evidence suggests that increased DLK signaling is associated with possible STMN4 disruptions to microtubules, among else. They also produce evidence on cultured hippocampal neurons showing that expression levels of DLK are associated with changes in neurite outgrowth, axon specification, and synapse formation. They posit that downstream translational events related to DLK signaling in hippocampal glutamatergic neurons are a generalizable paradigm for understanding neurodegenerative diseases.

Strengths

This is an interesting paper based on a lot of work and a high number of diverse experiments that point to the pervasive roles of DLK in the development of select glutamatergic hippocampal neurons. One should applaud the authors for their work in constructing sophisticated molecular cre-lox tools and their expert Ribotag analysis, as well as technical skill and scholarly treatment of the literature. I am somewhat more skeptical of interpretations and conclusions on spatial anatomical selectivity without stereological approaches and also going directly from (extremely complex) Ribotag profiling patterns to relevance based on immunohistochemistry and no additional interventions to manipulate (e.g. by knocking down or blocking) their top Ribotag profile hits. Also, it seems to this reviewer that major developmental claims in the paper are based on gene translational profiling dependent on DLK expression, not DLK activation, despite some evidence in the paper that there is a correlation between the two. Therefore, observed patterns and correlations may or may not be physiologically or pathologically relevant. Generalizability to neurodegenerative diseases is an overreach not justified by the scope, approach, and findings of the paper.

We thank the reviewer for the encouraging and constructive comments on the manuscript.

Weaknesses and Suggestions:

The authors state that the rationale for the translatomic studies is to "to gain molecular understanding of gene expression associated with DLK in glutamatergic neurons" and to characterize the "DLK-dependent molecular and cellular network", However, a problem with the experimental design is the selection of an anatomical region at a time point featured by active neurodegeneration. Therefore, it is not straightforward that the differentially expressed genes or pathways caused by DLK overexpression changes could be due to processes related to neurodegeneration. Indeed, the authors find enrichment of signals related to pathways involved in extracellular matrix organization, apoptosis, unfolded protein responses, the complement cascade, DNA damage responses, and depletion of signals related to mitochondrial electron transport, etc., all of which could be the consequence of neurodegeneration regardless of cause. A more appropriate design to discover DLK-dependent pathways might be to look at a region and/or a time point that is not confounded by neurodegeneration.

We appreciate reviewer’s comment. We included our thoughts in ‘Limitation of the study’ (pg 20):

‘Future studies using cell-type specific RiboTag profiling and other methods at a refined time window will be required to address how DLK dependent signaling interacts with other networks underlying hippocampal regional neuron vulnerability to pathological insults.’

In a related vein, the authors ask "if the differentially expressed genes associated with DLK(iOE) might show correlation to neuronal vulnerability" and, to answer this question, they select the set of differentially expressed genes after DLK overexpression and assess their expression patterns in various regions under normal conditions. It looks to me that this selection is already confounded by neurodegeneration which could be the cause for their downregulation. Therefore, such gene profiles may not be directly linked to neuronal vulnerability. A similar issue also relates to the conclusion that "...the enrichment of DLK-dependent translation of genes in CA1 suggests that the decreased expression of these genes may contribute to CA1 neuron vulnerability to elevated DLK".

We agree with the reviewer’s concern that it is difficult to separate neurodegenerative consequences from changes caused by DLK solely based on our translatomics studies on P15 DLK(iOE) mice. As responded to reviewer 1 (point 4) and reviewer 2 (point 1), we have included new analysis of P10 mice (Fig.S7A,B) when neurons did not show detectable sign of degeneration.

We consider several lines of evidence supporting that some differentially expressed genes in DLK(iOE) vs control may likely be specific for increased DLK signaling.

First, the genes identified in DLK(iOE) vs control represent a small set of genes (260), which is comparable to other DLK dependent datasets (Asghari Adib et al., 2024) but shows cell-type specificity.

Second, our analysis using rank-rank hypergeometric overlap (RRHO) detects a significant correlation between upregulated genes from DLK(iOE) vs downregulated genes in DLK(cKO), and vice versa, suggesting that expression of a similar set of genes is depended on DLK (Fig.3C, S6C-E). Consistently, GO term analysis using the list of genes coordinately regulated by DLK, derived from our RRHO analysis, leads to identification of similar GO terms related to up- and downregulated genes as using DLK(iOE)-RiboTag data alone. SynGO analysis of DLK(iOE) regulated genes and DLK(cKO) regulated genes also identified similar synaptic processes regulated by significantly regulated genes (Fig.3F and S6J).

Third, we performed additional analysis comparing our Vglut1-RiboTag dataset with CamK2-RiboTag and Grik4-RiboTag datasets from 6-week-old wild type mice reported by (Traunmüller et al., 2023; GSE209870). We observed >80% overlap among the top ranked genes (revised Methods). We described this analysis on pg 9 and Fig. S6K-L (and Supplemental Excel File S3):

‘Additionally, we compared our Vglut1-RiboTag datasets with CamK2-RiboTag and Grik4-RiboTag datasets from 6-week-old wild type mice reported by (Traunmüller et al., 2023; GSE209870). We defined a list of genes enriched in CamK2-expressing CA1 neurons relative to Grik4-expressing CA3 neurons (CA1 genes), and those enriched in Grik4-expressing CA3 neurons (CA3 genes) (File S3). When compared with the entire list of Vglut1-RiboTag profiling in our control and DLK(cKO), we found CA1 genes tended to be expressed more in DLK(cKO) mice, compared to control (Fig.S6K), while CA3 genes showed a slight enrichment in control though the trend was less significant, and were less clustered towards one genotype (Fig.S6L). Moreover, many CA1 genes related to cell-type specification, such as FoxP1, Satb2, Wfs1, Gpr161, Adcy8, Ndst3, Chrna5, Ldb2, Ptpru, and Ntm, did not show significant downregulation when DLK was overexpressed. These observations imply that DLK likely specifically down-regulates CA1 genes both under normal conditions and when overexpressed, with a stronger effect on CA1 genes, compared to CA3 genes. Overall, the informatic analysis suggests that decreased expression of CA1 enriched genes may contribute to CA1 neuron vulnerability to elevated DLK, although it is also possible that the observed down-regulation of these genes is a secondary effect associated with CA1 neuron degeneration.’

To understand the role and relevance of the DLK overexpression model, there should be a discussion of to what extent it corresponds to endogenous levels of DLK expression or DLK-MAPK pathway activation under baseline or pathological conditions.

We appreciate the suggestion, which is similar to R2 point 3. We have revised the text and discussion to include how DLK levels may be altered in other physiological conditions vs our mice.

Pg. 6: ‘Several studies have reported that DLK protein levels increase under a variety of conditions, including optic nerve crush (Watkins et al., 2013), NGF withdrawal (~2 fold) (Huntwork-Rodriguez et al., 2013; Larhammar et al., 2017), and sciatic nerve injury (Larhammar et al., 2017). Induced human neurons show increased DLK abundance about ~4 fold in response to ApoE4 treatment (Huang et al., 2019). Increased expression of DLK can lead to its activation through dimerization and autophosphorylation (Nihalani et al., 2000)’.

And,

‘Additional analysis at the mRNA level (supplemental excel, File S2. WT vs DLK(iOE) DEGs) and at the protein level (Fig.S8E) suggest that the increase in DLK abundance was around 3 times the control level. The localization patterns of DLK protein appeared to vary depending on region of hippocampus and age of animals in both control and Vglut1Cre/+;H11-DLKiOE/+ mice (Fig.S3C).’

In Discussion (pg. 16): ‘The levels of DLK in our DLK(iOE) mice model appear comparable to those reported under traumatic injury and chronic stress.’

The authors posit that "dorsal CA1 neurons are vulnerable to elevated DLK expression, while neurons in CA3 appear largely resistant to DLK overexpression". This statement assumes that DLK expression levels start at a similar baseline among regions. Do the authors have any such data? Ideally, they should show whether DLK expression and p-c-Jun (as a marker of downstream DLK signaling) are the same or different across regions in both WT and overexpression mice. For example, what are the DLK/p-c-Jun expression levels in regions other than CA1 in Supplementary Figures 2-3 and how do they compare with each other? Normalization to baseline for each region does not allow such a comparison. Also, in Supplementary Figure 6, analyses and comparisons between regions are done at a time point when degeneration has already started. Ideally, these should be done at P10.

We thank the reviewer for raising these points. In the revised manuscript we have included protein expression analysis of DLK (Fig S3), c-Jun, and p-c-Jun at P10 (Fig. S7).

We provided a quantification of DLK immunostaining intensity in CA1 and CA3 in Fig.S3D,E and find roughly comparable levels between regions.

Pg. 6: ‘Additional analysis at the mRNA level (supplemental excel, File S2. WT vs DLK(iOE) DEGs) and at the protein level (Fig.S8E) suggest that the increase in DLK abundance was around 3 times the control level. The localization patterns of DLK protein appeared to vary depending on region of hippocampus and age of animals in both control and Vglut1Cre/+;H11-DLKiOE/+ mice (Fig.S3C).’

We provided our quantifications without normalization to baseline in each region for c-Jun and p-c-Jun, and revised the text accordingly:

Pg. 9-10: ‘In control mice, glutamatergic neurons in CA1 had low but detectable c-Jun immunostaining at P10 and P15, but reduced intensity at P60; those in CA3 showed an overall low level of c-Jun immunostaining at P10, P15 and P60; and those in DG showed a low level of c-Jun immunostaining at P10 and P15, and an increased intensity at P60 (Fig.S7A,C,E). In Vglut1Cre/+;H11-DLKiOE/+ mice at P10 when no discernable neuron degeneration was seen in any regions of hippocampus, only CA3 neurons showed a significant increase of immunostaining intensity of c-Jun, compared to control (Fig.S7A). In P15 mice, we observed further increased immunostaining intensity of c-Jun in CA1, CA3, and DG, with the strongest increase (~4-fold) in CA1, compared to age-matched control mice (Fig.S7C). The overall increased c-Jun staining is consistent with RiboTag analysis’.

Pg. 10: ‘In Vglut1Cre/+;H11-DLKiOE/+ mice, we observed increased p-c-Jun positive nuclei in CA1 at P10, and strong increase in CA1 (~10-fold), CA3 (~6-fold), and DG (~8-fold) at P15 (Fig.S7B,D).

Illustration of proposed selective changes in hippocampal sector volume needs to be very carefully prepared in view of the substantial claims on selective vulnerability. In 2A under P15 and especially P60, it is difficult to see the difference - this needs lower magnification and a lot of care that anteroposterior levels are identical because hippocampal sector anatomy and volumes of sectors vary from level to level. One wonders if the cortex shrinks, too. This is important.

Thank you for raising the point. We have provided images to view the anteroposterior level in Fig.S2A-C. We have noticed cortex in DLK(OE) mice to become thinner, along with expansion of ventricles in some animals at later timepoints (Fig.S2C).

One cannot be sure that there is selective death of hippocampal sectors with DLK overexpression versus, say, rearrangement of hippocampal architecture. One may need stereological analysis, otherwise this substantial claim appears overinterpreted.

We appreciate the comment.

In the revised manuscript, we included a new supplemental figure (Fig. S2) showing lower magnification images of coronal sections, and used cautionary wording, such as ‘CA3 is less vulnerable, compared to CA1’, to minimize the impression of over-interpretation. By NeuN staining, at P10, P15, P60, we did not observe detectable difference in overall hippocampus architecture, apart from noted cell death of CA1 and DG and associated thinning of each of the layers. At 46 weeks, some animals showed differences in the overall shape of dorsal hippocampus, though this appeared to reflect a disproportionately large CA3 region compared to other regions (Fig S2). Increased GFAP staining (Fig.S5A-C) was detected in CA1 but not in CA3, and microglia by IBA1 staining (Fig.S5E) also displayed less reactivity in CA3, compared to CA1. Thus, based on NeuN staining, GFAP staining, IBA1 staining and analysis of the differentially regulated genes, we infer that the effect of DLK(iOE) in CA1 is different than the effect on CA3.

Is the GFAP excess reflective of neuroinflammation? What do microglial markers show? The presence of neuroinflammation does not bode well with apoptosis. Speaking of which, TUNEL in one cell in Supplementary Figure 4E is not strong evidence of a more widespread apoptotic event in CA1.

We have included staining data for the microglia marker IBA1. Both GFAP and IBA1 showed evidence of reactivity particularly in the CA1 region (S5A-E), supporting the differential vulnerability in different regions, though whether cell death is primarily due to apoptosis is unclear.

We agree that our data of sparse TUNEL staining at P15 (Fig S5F,G) do not rule out whether other mechanisms of cell death may also occur. We have included this in our limitations (pg.20) “While we find evidence for apoptosis, other forms of cell death may also occur.”

In several places in the paper (as illustrated in Figure 4B, Supplementary Figure 2B, etc.): the unit of biological observation in animal models is typically not a cell, but an organism, in which averaged measures are generated. This is a significant methodological problem because it is not easy to sample neurons without involving stereological methods. With the approach taken here, there is a risk that significance may be overblown.

We appreciate the reviewer’s point. We used same region for quantification of RNAscope, genotype-blind when possible. We revised the graphs to show mean values for individual mice in Fig.4B, 4C, and Fig.S3B (previously Fig.S2B).

Other Comments and Questions:

Supplementary Figure 9: The authors state that data points are shown for individual ROIs - ideally, they should also show averages for biological replicates. Can the authors confirm that statistical analyses are based on biological replicates (mice) and not ROIs?

We have revised the graphs to show averages from individual mice in Fig.5B-D, F5E-F (previously Fig.S9G-I), Fig.5H-J, and Fig.5K-L (previously Fig.S9J-L) and Fig.S10B,C,E,F (previously Fig.S9B,C, E,F). The statistical analyses are based on biological replicates of mice.

For in vitro experiments, what is the effect of DLK overexpression on neuronal viability and density? Could these variables confound effects on synaptogenesis/synapse maturation?

As described in the Methods, we made hippocampal neuron cultures from P1 pups of the following crosses:

For control: Vglut1Cre/+ X Rosa26tdT/+

For DLKcKO: Vglut1Cre/+;DLK(cKO)fl/fl X Vglut1Cre/+;DLK(cKO)fl/fl;Rosa26tdT/+

For DLKiOE: H11-DLKiOE/iOE X Vglut1Cre/+;Rosa26tdT/+

Dissociated cells from a given litter were pooled into the same culture. Because there were different proportions of neurons with our genotype of interest in each culture, it is not simple to know whether DLK was causing significant cell death.

On pg 13, we stated our observation:

‘We did not notice an obvious effect of DLK(iOE) or DLK(cKO) on neuron density in cultures at DIV2. To assess neuronal type distribution in our cultures, we immunostained DIV14 neurons with antibodies for Satb2, as a CA1 marker (Nielsen et al., 2010), and Prox1, as a marker of DG neurons (Iwano et al., 2012). We did not observe significant differences in the proportion of cells labeled with each marker in DLK(cKO) or DLK(iOE) cultures (Fig.S13E). These data are consistent with the idea that DLK signaling does not have a strong role in neuron-type specification both in vivo and in vitro.

We cannot rule out whether variable factors in our cultures may confound effects on synaptogenesis/synapse maturation, and would hope future studies will shed clarity.

Correlations between c-jun expression and phosphorylation are extremely important and need to be carefully and convincingly documented. I am a bit concerned about Supplementary Figure 6 images, especially 6B-CA1 (no difference between control and KO, too small images) and 6D (no p-c-Jun expression at all anywhere in the hippocampus at P15?).

At P10, P15, and P60 we stained for p-c-Jun using the Rabbit monoclonal p-c-Jun (Ser73) (D47G9) antibody from Cell Signaling (cat# 3270) at a 1:200 dilution and imaged using an LSM800 confocal microscope with a 20x objective. We observed p-c-Jun to be quite low generally in control animals. We have replaced the images in Fig.S7F (previously S6D), and adjusted the brightness/contrast to enable better visualization of the low signal in Fig.S7B,D,F (previously Fig.S6B,D).

We revised our text to present the data carefully as stated above:

Pg. 9-10: ‘In control mice, glutamatergic neurons in CA1 had low but detectable c-Jun immunostaining at P10 and P15, but reduced intensity at P60; those in CA3 showed an overall low level of c-Jun immunostaining at P10, P15 and P60; and those in DG showed a low level of c-Jun immunostaining at P10 and P15, and an increased intensity at P60 (Fig.S7A,C,E). In Vglut1Cre/+;H11-DLKiOE/+ mice at P10 when no discernable neuron degeneration was seen in any regions of hippocampus, only CA3 neurons showed a significant increase of immunostaining intensity of c-Jun, compared to control (Fig.S7A). In P15 mice, we observed further increased immunostaining intensity of c-Jun in CA1, CA3, and DG, with the strongest increase (~4-fold) in CA1, compared to age-matched control mice (Fig.S7C). The overall increased c-Jun staining is consistent with RiboTag analysis’.

Pg. 10: ‘In Vglut1Cre/+;H11-DLKiOE/+ mice, we observed increased p-c-Jun positive nuclei in CA1 at P10, and strong increase in CA1 (~10-fold), CA3 (~6-fold), and DG (~8-fold) at P15 (Fig.S7B,D).

Recommendations for the authors:

Several major and minor reservations were raised. The major issues are the need for more information about the over-expression of DLK and a need to extrapolate to an in vivo condition with DLK. A considerable amount of useful information is presented with some very nicely done experiments but it is not yet a coherent or integrated story. The lack of impact of DLK overexpression in some neurons is perhaps the most impactful observation of the study and would be great to have more information around the differential transcriptional/signaling response in these cell types. There is also a need for more experimental details and to address several questions about the mouse genetic and translatome analysis. They are valid concerns that require attention by the authors.

We thank the editors and reviewers for their thoughtful evaluation and suggestions. We hope that the editors and reviewers find that the new data and text changes in our revised manuscript, along with above point-to-point response, have addressed the concerns and strengthened our findings.

Minor points:

(1)The authors state that deletion of DLK has no effect on CA1 at 1yr, however, the image of CA1 in Figure S1D shows substantially fewer NeuN+ neurons. Is this a representative field of view?

We have re-examined images, and observed no effect on hippocampal morphology at 1 yr. We now included representative images in the revised Fig S1D.

(2) Is the DLK protein section staining in Figure 2C a real signal? The staining looks like speckles and is purely somatic. Axonal staining is widely expected based on the literature and the authors' own work. There should be a specificity control.

To our knowledge, axonal staining of DLK reported in the literature is mostly based on cultured DRG neurons. In addition to the reported axonal localization, DLK is present in the cell soma, near the golgi (Hirai et al., 2002), and in the post-synaptic density (Pozniak et al., 2013).

In the revised manuscript, we addressed this point by including controls with no primary antibody, and using an antibody against the closely related kinase, LZK. These additional data are shown in (Fig.S3C,D) (previously Fig.S2C), supporting that DLK protein staining represents real signal. At P10 and P15, DLK immunostaining around CA3 showed axonal staining of the mossy fibers, as well as in the soma and dendritic layers (Fig.S3C,D). A similar pattern was also seen in primary cultured neurons (Fig 6A).

(3) The protein expression of DLK in the transgenic overexpressor (Figure S7C) looks, to the resolution of this blot, to be at least 50kD heavier than 'WT' DLK. Can the authors explain this discrepancy?

The Cre-induced DLK(iOE) transgene has T2A and tdTomato in-frame to C-terminus of DLK. It is known that T2A ‘self-cleavage’ is often incomplete. DLK-T2A-tdTomato would be about 50 kD bigger than WT DLK. We now include the transgene design in revised Fig S1D, and also stated in figure legend of Fig.S8C (previously S7C) that ‘Larger molecular weight band of DLK in Vglut1Cre/+;H11-DLKiOE/+ would match the predicted molecular weight of DLK-T2A-tdTomato if T2A-peptide induced ‘self-cleavage’ due to ribosomal skipping is ineffective (Fig.S1D).’

(4) Expression changes in DLK affect various aspects of neurites in CA1 cultures (Figure 6), and changes in DLK also modestly affect STMN4 (and 2, perhaps indirectly) levels (Figure S7C), but there is no indication that DLK acts via STMN4 to cause these changes. It is not clear what to make of these data. Of note, Stmn4 levels change in response to DLK in CA3, without DLK affecting cell death in this region.

We appreciate and agree with the comment. Other studies (Asghari Adib et al., 2024; DeVault et al., 2024; Hu et al., 2019; Larhammar et al., 2017; Le Pichon et al., 2017; Shin et al., 2019; Watkins et al., 2013) reported expression changes in Stmn4 mRNAs in other cell types and cellular contexts, which appeared to depend on DLK. Hippocampal neurons express multiple Stmns (Fig.S8A). While we present our analysis on the effects of DLK dosage on Stmn4, and also Stmn2, we do not think that DLK-induced changes of Stmn4 expression per se is a major factor underlying CA1 cell death vs CA3 survival.

In the revised manuscript, we addressed this point in ‘Limitation of our study’ (pg 20):

‘Additional experiments will be needed to elucidate in vivo roles of STMN4 and its interaction with other STMNs’.

Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Data Citations

    1. Ritchie EM, Jin Y. 2025. DLK-dependent protein network regulates hippocampal glutamatergic neuron degeneration. NCBI Gene Expression Omnibus. GSE266662 [DOI] [PubMed]
    2. Traunmueller L, Scheiffele P. 2022. Trans-cellular regulation of synaptic properties by neuron-specific alternative splicing. NCBI Gene Expression Omnibus. GSE209870

    Supplementary Materials

    Figure 1—source data 1. Original western blots for images shown in Figure 1A.
    Figure 1—source data 2. PDF showing original western blots for images shown in Figure 1A, along with relevant bands and genotypes.

    Original membranes corresponding to Panel A. Molecular weights shown using PageRuler Plus Prestained Protein Ladder. See Figure 1—figure supplement 1—source data 2 for more details. Each lane represents a separate mouse. Lanes 1–3 show control samples, lanes 4–6 show DLK(cKO).

    Figure 1—figure supplement 1—source data 1. Original western blots for images shown in Figure 1—figure supplement 1B.
    Figure 1—figure supplement 1—source data 2. PDF showing original western blots for images shown in Figure 1—figure supplement 1B, along with relevant bands and genotypes.

    Original membranes corresponding to Panel B. Molecular weights shown using PageRuler Plus Prestained Protein Ladder. 10 min exposure (uncut membrane) was taken prior to 2 min exposure. Following 10 min exposure, membrane was cut and reprobed for DLK for 2 min exposure. Each lane represents a separate mouse. Lanes 1–3 show control samples, lanes 4–6 show DLK(cKO).

    Figure 3—figure supplement 1—source data 1. Original western blots for images shown in Figure 3—figure supplement 1A.
    Figure 3—figure supplement 1—source data 2. PDF showing original western blot for image shown in Figure 3—figure supplement 1A, along with relevant band and genotype.

    Original membranes corresponding to Panel A. Molecular weights shown using Precision Plus Protein Dual Color Ladder. Rpl22-HA is 23 kDa protein.

    Figure 4—figure supplement 1—source data 1. Original western blots for images shown in Figure 4—figure supplement 1B and C.
    Figure 4—figure supplement 1—source data 2. PDF showing original western blots for images shown in Figure 4—figure supplement 1B and C, along with relevant bands and genotypes.

    Pg.1 Original membranes corresponding to Panel B. Molecular weights shown using PageRuler Plus Prestained Protein Ladder. Each lane represents a separate mouse. Lanes 1,3,5,7,9 show control samples, lanes 2,4,6,8,10 show DLK(cKO) at P1, P8, P15, P60, and 1 year timepoints. Dotted lines indicate locations where membrane was cut and labeled with separate antibodies. Pg.2 Original membranes corresponding to Panel C. Molecular weights shown using Precision Plus Protein Dual Color Ladder. Each lane represents a separate mouse. Lanes 1,3,5,7,9 show control samples, lanes 2,4,6,8,10 show DLK(iOE) at P1, P8, P15, P60, and ~1 year timepoints. Dotted lines indicate locations where membrane was cut and labeled with separate antibodies. Samples were split, with half of each prepped sample loaded onto two membranes (membrane 1&2). Smaller molecular weight band matches expected size of DLK protein (and flag tagged DLK). Larger molecular weight band of DLK in Vglut1Cre/+;H11-DLKiOE/+ would match the predicted molecular weight of DLK-T2A-tdTomato if T2A-peptide induced ‘self- cleavage’ due to ribosomal skipping is ineffective. Pg.3 Original membranes corresponding to Panel C. Molecular weights shown using Precision Plus Protein Dual Color Ladder. Each lane represents a separate mouse. Lanes 1,3,5,7,9 show control samples, lanes 2,4,6,8,10 show DLK(iOE) at P1, P8, P15, P60, and ~1 year timepoints.

    Figure 6—figure supplement 2—source data 1. Original western blots for images shown in Figure 6—figure supplement 2B.
    Figure 6—figure supplement 2—source data 2. PDF showing original western blots for images shown in Figure 6—figure supplement 2B, along with relevant bands and genotypes.

    Pg. 1 Original membranes corresponding to Panel B. Molecular weights shown using Precision Plus Protein Dual Color Ladder. Each lane represents a separate mouse. Lanes 1–3 show control samples (from DLK(iOE) sibs), lanes 4–6 show DLK(iOE), lanes 7–9 show control samples (from DLK(cKO) sibs), lanes 10–12 show DLK(cKO). All from P15 timepoint. Dotted lines indicate locations where membrane was cut for labeling with separate antibodies. Samples were split, with half of each prepped sample loaded onto two membranes (membrane 1&2). Pg. 2 Original membranes corresponding to Panel B. Molecular weights shown using Precision Plus Protein Dual Color Ladder. Each lane represents a separate mouse. Lanes 1–3 show control samples (from DLK(iOE) sibs), lanes 4–6 show DLK(iOE), lanes 7–9 show control samples (from DLK(cKO) sibs), lanes 10–12 show DLK(cKO). All from P15 timepoint. Dotted lines indicate locations where membrane was cut for labeling with separate antibodies. Samples were split, with half of each prepped sample loaded onto two membranes (membrane 1&2).

    Supplementary file 1. Excel file containing DLK(cKO) differentially expressed genes.

    File containing differential expression results from DLK(cKO) compared to control and their regional enrichment. Highlighted columns show gene symbols of differentially expressed genes (padj <0.05), Log2 fold change, and adjusted p-values. Sheets show genes sorted by all differentially expressed genes, upregulated genes, downregulated genes, and synaptic genes.

    elife-101173-supp1.xlsx (4.7MB, xlsx)
    Supplementary file 2. Excel file containing DLK(iOE) differentially expressed genes.

    File containing differential expression results from DLK(iOE) compared to control and their regional enrichment. Highlighted columns show gene symbols of differentially expressed genes (padj <0.05), Log2 fold change, and adjusted p-values. Sheets show genes sorted by all differentially expressed genes, regional expression, upregulated genes, downregulated genes, and synaptic genes.

    elife-101173-supp2.xlsx (4.8MB, xlsx)
    Supplementary file 3. Excel file containing CamK2 and Grik4 RiboTag enriched genes.

    File containing top 100 genes enriched in CamK2-RiboTag compared to Grik4-RiboTag and vice versa (Traunmüller et al., 2023; GSE209870) as described in methods.

    elife-101173-supp3.xlsx (27.9KB, xlsx)
    Supplementary file 4. Primers used for genotyping and qRT-PCR.

    File containing primer sequences used for genotyping and qRT-PCR.

    elife-101173-supp4.docx (17.1KB, docx)
    MDAR checklist

    Data Availability Statement

    Sequencing data have been deposited in GEO under accession code GSE266662.

    The following dataset was generated:

    Ritchie EM, Jin Y. 2025. DLK-dependent protein network regulates hippocampal glutamatergic neuron degeneration. NCBI Gene Expression Omnibus. GSE266662

    The following previously published dataset was used:

    Traunmueller L, Scheiffele P. 2022. Trans-cellular regulation of synaptic properties by neuron-specific alternative splicing. NCBI Gene Expression Omnibus. GSE209870


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