Multi-omic Analysis of a Mucolipidosis II Neuronal Cell Model Uncovers Involvement of Pathways Related to Neurodegeneration and Drug Metabolism

Abstract

Defining the molecular consequences of lysosomal dysfunction in neuronal cell types remains an area of investigation that is needed to understand many underappreciated phenotypes associated with lysosomal disorders. Here we characterize GNPTAB-knockout DAOY medulloblastoma cells using different genetic and proteomic approaches, with a focus on how altered gene expression and cell surface abundance of glycoproteins may explain emerging neurological issues in individuals with GNPTAB-related disorders, including mucolipidosis II (ML II) and mucolipidosis IIIα/β (ML IIIα/β). The two knockout clones characterized demonstrated all the biochemical hallmarks of this disease, including loss of intracellular glycosidase activity due to impaired mannose 6-phosphate-dependent lysosomal sorting, lysosomal cholesterol accumulation, and increased markers of autophagic dysfunction. RNA sequencing identified altered transcript abundance of several neuronal markers and genes involved in drug metabolism and transport, and neurodegeneration-related pathways. Using selective exo-enzymatic labeling (SEEL) coupled with proteomics to profile cell surface glycoproteins, we demonstrated altered abundance of several glycoproteins in the knockout cells. Most striking was increased abundance of the amyloid precursor protein and apolipoprotein B, indicating that loss of GNPTAB function in these cells corresponds with elevation in proteins associated with neurodegeneration. The implication of these findings on lysosomal disease pathogenesis and the emerging neurological manifestations of GNPTAB-related disorders is discussed.

Introduction

Mannose 6-phosphate (M6P)-dependent sorting of acid hydrolases to the lysosome remains one of the best examples of how carbohydrates mediate an essential biological process. Cell- and animal-based experiments that span five decades have delineated how the enzymes and proteins within this pathway work together to target over sixty soluble lysosomal hydrolases to their functional compartment in the cell ^1–3. The heterohexameric GlcNAc-1-phosphotransferase (GNPT) enzyme, encoded by GNPTAB and GNPTG, recognizes conformation-dependent determinants on the soluble acid hydrolases and modifies mannose residues on their N-linked sugar chains to initiate the formation of the M6P tag ^4–6. This recognition marker facilitates binding to the cation-dependent and -independent sorting receptors that deliver the hydrolases to late endosomes/lysosomes ^7,8. As evidenced by the profound skeletal manifestations in GNPTAB-related disorders mucolipidosis II (ML II) and mucolipidosis IIIα/β (ML IIIα/β), defects in this pathway significantly impact human health and development ^9–12. Recent studies have begun to uncover the complexity of disease pathogenesis in different affected tissues. However, the molecular and cellular basis for many phenotypes, especially within the central nervous system, are still incompletely understood ^13–15.

Neurological phenotypes are common in most lysosomal diseases and can represent the primary clinical manifestation of disease. Even conditions that have historically been viewed as skeletal disorders (such as MPS I) exhibit significant neurological consequences, many of which develop as patients age ^16,17. While skeletal and connective tissue symptoms of ML remain the primary concerns, neurological functions can also be impaired. Patients experience progressive neurodegeneration often arising from spinal cord compression ¹⁸. While postmortem analyses are very limited, studies in animal models have demonstrated abundant neurological and behavioral issues that resemble other lysosomal diseases ¹³. Despite this, little is known about the mechanisms driving the neurological issues in ML. This effort is complicated by the number of different lysosomal hydrolases that are impacted in this condition. The role of lysosomal enzymes in other neurodegenerative diseases like Alzheimer’s and Parkinson’s continue to emerge, with examples of lysosomal genes as significant disease modifiers. Genetic studies have identified enrichment of variants in lysosomal genes within affected populations, and work to better define the mechanistic contribution of enzyme deficiency in neurodegeneration is ongoing ^19–24. Perhaps best understood is the contribution of variants in GBA towards risk for Parkinson’s disease but the role of the lysosome and its enzymes in the processing of amyloid precursor protein (APP) has also been given substantial attention ^25–28.

In an effort to fill the gaps in our understanding of the neurological consequences associated with ML, we generated a new neuronal cell model using CRISPR-mediated GNPTAB disruption in DAOY medulloblastoma cells. Two knockout cell clones and a parental control were biochemically characterized and validated, followed by transcriptomic and proteomic profiling Transcriptomic profiling of cells has been employed in several prior studies as a means to uncover unrecognized aspects of pathogenesis associated with mucopolysaccharidosis (MPS) disorders ^29–34, supporting the rationale for multi-omic approaches in the context of ML. Transcript abundance of numerous genes involved in neuronal differentiation, lipid metabolism and pathways related to drug transport and metabolism were altered in GNPTAB-deficient cells. Labeling of cell surface glycoproteins show amyloid precursor protein (APP) and apolipoprotein B (APOB) are also substantially increased on the surface of mutant cells. The implications of these findings towards the pathogenesis of ML disease, the emerging neurological issues associated with ML, and the contribution of defects in the M6P pathway to neurodegenerative conditions like Alzheimer’s disease are discussed.

Materials and Methods

CRISPR-mediated knockout of GNPTAB in DAOY cells.

The GNPTAB knockout cell clones were generated by Synthego using DAOY medulloblastoma cells using a single guide RNA (CACGTAGAGCCCATACCTGT). Two cell clones (labeled D3 and E4) were identified following Sanger sequencing and shown to bear compound heterozygous alterations in GNPTAB, with clone D3 carrying multiple deletions (−2/−2/−1 bp)[934-935delCC + 933-934delTC + 933delT], while clone E4 harbors a single-nucleotide insertion and a single nucleotide deletion (−1/+1 bp) [934delC + 933_934insN].

SDS-PAGE and Western blotting.

Cells were harvested and lysed in Tris-Triton buffer (100 mM NaCl, 10 mM Tris-HCl pH 7.4, 1 mM EDTA pH 8, 0.1% sodium dodecyl sulfate (SDS), 1% igepal CA-630, 1% Triton X-100) containing protease inhibitor cocktail (Thermo Scientific, 88666). Samples were kept in ice for 30 minutes, homogenized and centrifuged for 10 minutes at 20,000 g at 4 °C. Protein concentration was determined by BCA protein assay (Thermo Scientific, 23235) and 50 μg of proteins per sample were loaded on Bis-Tris SDS-PAGE gels. Blots were probed with anti-LAMP2 antibody (1:1000, DSHB H4B4), anti-p62 antibody (1:1000, Abcam ab91526) or anti-LC3 antibody (1:1000, Novus Nb100-2331). HRP conjugated anti-biotin antibody (#200-032-211) was purchased from Jackson ImmunoResearch and anti-APP (anti-AICD, #171610) antibody was purchased from Sigma Aldrich. Blots were developed with Clarity Western ECL substrate (BioRad, 1705060) and analyzed on a Bio-Rad MP ChemiDoc system (BioRad, Hercules, CA, USA).

Lysosomal Glycosidase Activity Assay.

Lysosomal glycosidase activity assays were performed as previously described ³⁵. Briefly, lysates of DAOY GNPTAB KO and control cells were prepared by sonication in DPBS containing 0.1% Triton X-100 and protease inhibitor. Protein concentration was measured with BCA protein assay. Activity of β-galactosidase, β-hexosaminidase, β-glucuronidase and β-glucosidase was assayed using fluoresence-based 4-MU assays over 1 hour at 37°C. Substrates included 4-methylumbelliferyl (MU)-β-D-galactopyranoside, 4-MU-N-acetyl- β-D-glucosaminide, 4-MU-β-D-glucuronide and 4-MU-β-D-glucopyranoside. Fluorescent emission was measured with Cytation 5^™ Cell Imaging Multi-Mode Reader (BioTek, Winooski, VT, USA).

LysoTracker Red and Filipin-III staining and confocal imaging.

For Lysotracker Red (Invitrogen, L7528) and Filipin-III staining (Sigma-Aldrich, cat#F4767), cells were plated on coverslips in a 12 well plate. Cells were washed in Dulbecco’s phosphate-buffered saline (DPBS) (Gibco^™, cat# 14040117) and incubated with 100 nM LysoTracker Red for 30 minutes at 37 °C. After several DPBS, cells were fixed for 10 minutes in 3.7% and subsequently incubated with 0.05 mg/mL Filipin-III in DBPS containing 10% FBS (VWR, cat#97068-085) for 1 hour at room temperature in the dark. Coverslips were mounted in Prolong Gold Antifade mounting media (Invitrogen, cat#P36930). Stained cells were imaged on an Olympus FV3000 laser-scanning microscope equipped using a 63X (N.A 1.4) oil immersion objective.

Transcriptomic analysis.

For RNA sequencing, four independent biological replicates of each Daoy mutant clones and their parental control were collected. Cells were scraped in 1.5 mL Trizol reagent and flash frozen in liquid nitrogen. RNA sequencing (at a read depth of 50X) was performed by Azenta Life Sciences (Burlington, Massachusetts USA). Preliminary bioinformatic analyses was performed by Azenta. Additional differential expression analysis of both clones compared to parental cells was performed as follows: Genepattern server was used to normalize raw read counts obtained from Azenta with the VoomNormalize module before use of DESeq2 ^36,37. Pathway enrichment analysis of up- and down-regulated genes was performed via a statistical overrepresentation test against the PANTHER Pathways reference set using PantherDB version 19.0 ³⁸. For visualizing expression of individual genes found differentially expressed, normalized read counts described above were used. The average of parental cell read counts for each gene were set to 1, and fold changes of all individual sample read counts were calculated relative to that value. Plots of transcriptome data were generated in R and GrapPad Prism version 10.0 (GraphPad Software, Boston, Massachusetts USA). RNAseq data is accessible at GSE273794. To review GEO accession GSE273794, go to https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE273794, Enter token mrmtuqysnnypvwd into the box.

SEEL labeling and immunoprecipitation.

WT or GNPTAB KO (D3 or E4) DAOY cells were cultured in Dulbecco’s Modified Eagle’s Medium (DMEM) containing 10% FBS, Pen/Strep, 2mM L-glutamine in CO₂ incubator prior to labeling. Arthrobacter ureafaciens neuraminidase (#P0722L) and Streptavidin coated magnetic beads (S1420S) were purchased from NEB. These beads were pre-protected from trypsin digestion by following a reported protocol ³⁹. Sodium cyanoborohydride (#8180530010), 1,2-cyclohexadione (#C101400) were purchased from Sigma Aldrich. Formaldehyde (16%) was purchased from Pierce (#280908). CMP-sialic acid-biotin (CMP-Neu5-lk-biotin) was purchased from a commercial supplier. Cell surface glycoproteins were labeled with biotin using established methods as previously described [33] with slight modification. Briefly, WT or GNPTAB KO cells grown to 80 to 90 % confluency in 6 cm dishes were treated with SEEL labeling master mix solution (900 μL) containing CMP-sialic acid-biotin (100 μM), ST6Gal1 (37.5 μg) and Arthrobacter ureafaciens (1:1 in 50% glycerol, 6 μL) neuraminidase in serum free DMEM for 1hr. After 1hr, cells were washed with DPBS two times and harvested by on-plate lysis by scrapping with RIPA lysis buffer (50 mM Tris HCl, pH 8.0, 150 mM NaCl, 1.0 % NP-40, 0.5 % sodium deoxycholate, 0.1% SDS). The resulting cell lysate were collected and vortexed, and incubated on ice for 30 min followed by centrifugation at 20,000 g to remove insoluble debris. After protein concentration determination by BCA assay, immunoprecipitation was done by incubating each 500 μg of lysate (1mg/mL) from SEEL labeled cells or control cells with each 100 μL (suspension) of streptavidin-coated magnetic beads ³⁹. After overnight incubation of the lysate with beads, the resulting flowthrough was collected and the beads were washed five times with RIPA buffer.

Proteomic Analysis.

Beads were washed twice with 50 mM ammonium bicarbonate. Cysteines were reduced with 45 mM dithiothreitol and alkylated with 100 mM iodoacetamide. 100ng of trypsin-Lys C endoprotease solution was added to digest the enriched proteins directly off the beads overnight at 37°C with shaking at 300 rpm. The digestion was terminated with the addition of 10% trifluoroacetic acid solution. The supernatant containing the tryptic peptides was desalted using with 0.6 μL C18 ZipTips (Millipore) and dried under vacuum.

Peptides were separated and analyzed by LC-MS/MS on an EASY nLC 1200 System (Thermo Scientific) in-line with the Orbitrap Exploris 480 Mass Spectrometer (Thermo Scientific). Two μg of peptides were pressure loaded onto a C18 reversed phase column (Acclaim PepMap RSLC, 75 μm x 25 cm (2 μm, 100 Å) Thermo Scientific) thermostated at 45°C. The peptides were separated using a gradient of 0-35% B in 60 min (Solvent A: 5% acetonitrile, 0.1% formic acid; Solvent B: 80% acetonitrile, 0.1% formic acid) at a flow rate of 300 nL/min. Spray voltage was set at 2.2 kV and ion transfer tube temperature at 300°C. Mass spectra were acquired in data-dependent mode with a high resolution (60,000) full scan, mass range of m/z 375-1575, with an automatic gain control target value of 300% and a maximum injection time of 25 ms. The AGC target value for fragment spectra is set at 100%. Cycle time for MS2 scans was 3 s. The resolution was set at 15,000 with a max injection time of 50 ms. An HCD collision energy of 33% was used for peptide fragmentation. Dynamic exclusion of precursors was set to 20 s.

The raw files were searched in MaxQuant v2.4.2.0 (Max Planck Institute) against the reviewed human protein database (20,422 entries downloaded from Uniprot in March 2023). The search parameters allowed for two missed cleavages, fragment mass tolerances of 20 ppm, and a minimum of seven amino acids per peptide. Carbamidomethylation of cysteine was set as a fixed modification. Methionine oxidation and acetylation of the protein N-terminus were set as variable modifications. The false discovery rates for peptide spectral matches and protein identification were set to 1%. The search results were further analyzed and filtered in Perseus v. 1.6.15.0 (Max Planck Institute). Potential contaminants, reverse matches, and single hit proteins were removed. Only proteins with >2 peptides were retained. The protein intensities were log2 transformed and median normalized. To identify proteins with changes in relative abundance between conditions, two-sample Student’s t-tests were performed using a permutation-based false discovery rate (FDR) <0.05 with 250 randomizations and S0 fold change parameter of 0.1.

Results

Biochemical and genetic validation of GNPTAB-null DAOY cells.

To investigate the effects of GNPTAB deficiency in neuronal cells, GNPTAB was disrupted in the cerebellar medulloblastoma DAOY cell line using CRISPR -Cas9 system with a single guide RNA (sgRNA) targeting exon 1 (Figure 1A). Two independent knock-out clones, hereafter referred as clone D3 and clone E4, were identified and shown by Sanger sequencing to carry multiple indels. Both are compound heterozygotes, with clone D3 carrying multiple deletions and clone E4 harboring a single-nucleotide insertion and a single nucleotide deletion (Figure 1). In each mutant, the reported mutations are expected to disrupt the open reading frame creating an early protein truncation.

Figure 1-. Biochemical and genetic validation of GNPTAB-null DAOY cells.

(A)(top) Schematic of GNPTAB gene showing the sgRNA sequence (red) used for CRISPR/Cas9 mutagenesis and the annealing site on exon1. (bottom) Chromatograms of GNPTAB-KO clone D3 and clone E4 compared to DAOY control cells (WT) showing disruption of the gene sequence downstream CRISPR/Cas9 cleavage site (dotted line). (B) Graphs show reduced enzymatic activity of beta-galactosidase, beta-hexosaminidase and beta-glucuronidase in both mutant clones compared to control cells. Beta-glucosidase activity is increased in GNPTAB-KO cells. n = 3 biological replicates, error = SEM, significance was assessed by Dunnett’s test, where *p<0.05, **p<0.01, ***p<0.001 and ****p<0.0001. (C) Representative confocal images of Filipin (cyan) and LysoTracker Red (red) double staining showing increased amount of cholesterol and enlarged Lysotracker-positive puncta in GNPTAB mutant cells. The graphs report the fluorescence intensity of LysoTracker- and Filipin-positive puncta normalized on cell number and Pearson’s coefficient measuring colocalization between Filipin and LysoTracker fluorescence signals. n = 3, error = SEM, significance was assessed by Dunnett’s test, where *p<0.05, **p<0.01 and ***p<0.001. (D) Western blots probed for LAMP2, p62 and LC3 show increased protein levels in GNPTAB mutants compared to control cells. n = 3 biological replicates, error = SEM, significance was assessed by Dunnett’s test, where ***p<0.001.

Impaired lysosomal targeting is the primary expected consequence of GNPT loss of function due to defective mannose-6-phosphate (M6P) biosynthesis on soluble lysosomal enzymes. To biochemically validate the GNPTAB mutants, the intracellular activity of multiple acid glycosidases was evaluated in protein extracts generated from the GNPTAB-KO D3 and E4 clones and DAOY parental control cells. Consistent with impaired M6P-dependent sorting of lysosomal hydrolases, the activity of multiple enzymes was significantly reduced in GNPTAB mutant cells (Figure 1B). Compared to control cells the residual activity of β-galactosidase was 4.3% in clone D3 and 3.3% in clone E4; the residual activity of β-hexosaminidase was 14.7% in clone D3 and 13.4% in clone E4, and β-glucuronidase was 16.5% in clone D3 and 23.4% in clone E4. Consistent with its M6P-independent sorting, β-glucosidase activity was actually increased in both GNPTAB mutants (216.9% enzymatic activity in clone D3 and 186.6% enzymatic activity in clone E4) (Figure 1B) ^40,41. Increased activity of ß-glucosidase likely reflects hyperproliferation of lysosomes in the GNPTAB-knockout clones.

As a consequence of defective transport and lack of lysosomal glycosidases, MLII cells often accumulate undegraded material inside dysfunctional lysosomes. Confocal analysis of LysoTracker Red-stained cells identified more LysoTracker-positive puncta present in clones D3 and E4 compared to control cells (Figure 1C). Filipin-III, which binds free cholesterol, was also increased in the mutant clones compared to controls (Figure 1C). Pearson’s coefficient analyses show increased overlap between Lysotracker Red and Filipin-III signals in mutant cells (Figure 1C), suggesting at least some of the cholesterol accumulation occurs inside lysosomes. Notably, not all of the Filipin-III staining overlapped with LysoTracker Red positive puncta, suggesting free cholesterol may also be increased in some non-lysosomal compartments in mutant clones.

Consistent with the detected increase of Lysotracker-positive puncta, Lysosomal Associated Membrane Protein 2 (LAMP2) protein levels were increased in both clones (Figure 1D). Considering the fundamental role of lysosomes in autophagy, we also analyzed p62 and microtubule-associated protein 1A/1B-light chain 3 (LC3) abundance in GNPTAB-KO clones and control cells. Although p62 was not significantly increased in either clone, the LC3-II/LC3-I ratio was skewed toward more LC3-II present in mutants compared to controls (Figure 1D). Although not statistically significant, these results suggest autophagic flux may be impaired in GNPTAB mutant cells.

Transcriptome profiling of GNPTAB-null DAOY cells.

RNA sequencing was performed on four independent biological replicates of knockout clones and the parental DAOY cells. Differential gene expression analysis was performed pairwise, comparing each clone to control, and both clones together compared to control. While both GNPTAB deficient clones displayed unique changes, several genes were similarly affected in each compared to control (Figure 2A–B). The breadth of transcript changes between clone E3 and D4 and the control cells is represented by the volcano plot, along with the top 15 up and downregulated genes (FDR p-value < 0.01, magnitude of log₂(Fold change) > 0.6 (Figure 2C). Using the lists of all genes that were up- or down-regulated (FDR p-value < 0.01) between both clones compared to control, overrepresentation analysis was performed using PANTHER pathways (Figure 2D). The pathway with the highest enrichment in upregulated genes was “Cholesterol biosynthesis”, followed by several pathways related to carbohydrate and sugar nucleotide metabolism. The pathway with the highest enrichment of downregulated genes was “Arginine biosynthesis”, followed by “Pyruvate metabolism.” As the most statistically significant results, it is possible that these reflect key metabolic adaptations to loss of GNPTAB expression. These changes could indicate a shift of membrane lipid composition/synthesis and changes in sugar-nucleotide biosynthesis, both consistent with dysfunction of the lysosome and/or glycosylation machinery. In particular, the upregulation of nucleotide-sugar biosynthesis may reflect a response to the normal monosaccharide salvage pathways being compromised by lysosomal dysfunction in these cells. Concordant with observations of increased lysosomal proteins in knockout clones and increased lysosomal content, transcripts of many lysosome components and hydrolases were increased in one or both clones compared to control (Figure 3A–D). Additionally, the pyruvate metabolism and integrin signaling pathways were enriched showing both up- and down-regulated genes. Transcript abundance of multiple genes involved in neuronal function and neurodegeneration were also altered, including several enzymes involved in the processing of amyloid precursor protein (APP) (Figure 2E). This includes one of the top 10 upregulated genes across both clones, membrane metalloendopeptidase (MME) (Figure 1A). Transcript abundance of several genes in “Enkephalin release” pathway, which modulates nociception, was reduced (Figure 2F). The downregulated genes represented in this pathway belong to a group of G proteins involved in mediating enkephalin release. Of note, MME is also known to deactivate enkephalins and other peptide hormones, suggesting a possible interaction between the pathways ⁴². Other genes corresponding to proteins enriched in the cell surface proteome were also shown to be upregulated in the transcriptome data including IGF2R, LDLR, and p62 (SQSTM1) (Figure 3).

Figure 2 -. Transcriptome profiling of GNPTAB-null DAOY cells.

RNAseq analysis of KO clones shows consistent changes in metabolism and genes associated with protein processing and nociception. (A) Venn diagram indicating significantly upregulated genes shared by both GNPTAB KO clones compared to parental cell line, and a table of top 10 significant genes with largest average fold increase across both clones. (B) Venn diagram indicating significantly downregulated genes shared by both GNPTAB KO clones, and a table of the top 10 significant genes with largest average fold decrease across both clones. (C) Volcano plot depicting differential expression analysis comparing both KO clones to parental control. Dots represent individual genes. Genes with FDR < 0.01 and with a of log₂ fold-change either greater than 0.6 or less than −0.6 are colored red and blue, respectively. Dashed gray lines represent those cutoff values on axes. Top 15 up- and down-regulated genes are labeled. (D) Pathway overrepresentation analysis of all up- or down-regulated genes across both clones. Length of bars indicate fold-enrichment of genes in the pathway, size of circle at the end represents relative −log(p-value) of statistical overrepresentation test, and color represents whether the pathway was enriched from upregulated (red) or downregulated (blue) genes. (E-F) Normalized read count expression values of genes of interest, including APP/Alzheimer’s related genes and enkephalin release pathway genes, respectively. APP, amyloid precursor protein; BACE2, ß-secretase; MME, neprilysin; MMP14, matrix metalloproteinase 14 or MT1-MMP; GNAO1, G protein subunit alpha o1, GNG12, G protein subunit gamma 12; GNAS, G protein alpha-stimulating. Significance was assessed by Dunnett’s test, where *p<0.05, **p<0.01, ***p<0.001 and ****p<0.0001.

Figure 3 – Relative expression fold changes in lysosomal genes in GNPTAB-null DAOY cells.

(A) Relative expression fold change values of lysosome related genes. (B) Relative expression fold change values of genes found to be significantly altered from SEEL experiments. (C) Relative expression fold change values for GNPTAB. (D) Relative expression fold change values for GNPTG.

Cell surface abundance of several glycoproteins is altered in GNPTAB-null DAOY cells.

Our prior work demonstrated altered cell surface abundance of numerous glycoproteins in GNPTAB-null HeLa cells ⁴³. These data supported the possibility that lysosomal storage and disrupted autophagy impairs recycling and/or trafficking within the endocytic system. To similarly explore how cell surface residence of glycoproteins is impacted in the neuronal GNPTAB-null DAOY cells, we used selective exo-enzymatic labeling (SEEL) with CMP-sialic acid-biotin and the sialyltransferase ST6Gal1 on control cells and each GNPTAB deficient clone (D3 and E4) (Figure 4A). Existing sialic acids were removed from the cell surface using a bacterial neuraminidase prior to labeling in order to increase labeling efficiency. Anti-biotin western blot of labeled whole cell lysates suggest each cell line was labeled with equal efficiency (Figure 4B). SEEL-labeled proteins were isolated from cell lysates using streptavidin beads and proteomic analysis performed. These analyses suggest abundance of numerous membrane proteins is altered in GNPTAB deficient cells (Figure 5). Most striking was the substantial increase in SQSTM1/p62 (~4-fold). Detection of this cytoplasmic autophagy-related protein by SEEL was unexpected since it is not a bona fide N-glycosylated protein or present on the cell surface. It is possible, however, that p62 is not directly SEEL modified but instead binds to another SEEL labeled surface protein. Regardless, the finding that p62 is increased in the mutant cells correlates with the elevation noted by western blot (Figure 1D).

Figure 4 -. Cell surface abundance of several glycoproteins is altered in GNPTAB-null DAOY cells.

(A) Overview of the SEEL methodology using ST6Gal1 and CMP-sialic acid biotin. (B) Representative western blot using an anti-biotin HRP antibody to demonstrate the labeling efficiency in WT and GNPTAB-KO DAOY cell clones. (C) Relative abundance of cell surface glycoproteins in GNPTAB-KO vs. WT DAOY cells plotted using a log2 scale. (D) Representative western blot using an anti-APP antibody; the corresponding ß-actin western blot serves as a loading control. (E) Quantification of the total and upper reactive bands on the western blot. n = 3 biological replicates, error = SEM, significance was assessed by Dunnett’s test, where **p<0.01 and *p<0.05.

Figure 5 -. Volcano plot showing the changes in membrane protein abundance in WT cells as compared to both KO mutants.

Proteins were filtered to retain those quantified in all in wild type replicate samples. Proteins with increased abundance in knock out cells are on the right.

Of the SEEL-labeled membrane proteins, we identified the known N-glycoproteins and quantitated their relative abundance in GNPTAB deficient cells compared to control cells (Figure 4C). Of note was the increased cell surface abundance of IGF2R and LDLR, both trafficking receptors implicated in M6P-dependent and -independent uptake of lysosomal hydrolases. Numerous other cell surface glycoproteins involved in neuronal differentiation (SEMA3C, NFASC), metabolite transport (ABCD3, ABCC4), and protein processing (TSPAN14, ECE1) also showed altered cell surface abundance. These data suggest recycling, trafficking or stability of key glycoproteins may be more broadly disrupted when GNPTAB expression is reduced. Consistent with increased transcript abundance of amyloid precursor protein (APP), we also noted a 4-fold elevation in the amount of APP detected by SEEL in each GNPTAB null cell line. Western blot analysis performed in whole cell lysates (Figure 4D) further confirm APP abundance (relative to ß-actin) is increased in GNPT deficient neural cells (Figure 4E). The APP protein molecular weight ranges from 100-140kDa, with two primary bands detected in the DAOY cells at ~110kDa and ~140kDa. The 140kDA form was increased ~3 -fold in the D3 KO cells and 2.2-fold E4 KO cells.

Discussion

Here we present a multidimensional analysis of a neuronal cell model for ML II, which identified new potential pathogenic contributors to neural pathology. Collectively the data reveal a compelling link to several known neurodegeneration and drug metabolism pathways. In light of its amenability to CRISPR-Cas9 genome editing and its epithelial morphology, we used the medulloblastoma cell line DAOY to generate this cell model. Biochemical characterization of two knockout cell clones demonstrated key hallmarks of ML II, including missorting of acid hydrolases, increased lysosomal content and storage, and impaired autophagy. The new insights gained from the transcriptome and proteomic analysis are discussed below, with a focus on the emerging connection between lysosomal dysfunction and neurodegeneration.

In line with our prior studies on the GNPTAB-null HeLa cells ⁴³, the SEEL-based proteomics revealed altered abundance of numerous cell surface glycoproteins. Altered cell surface abundance of these glycoproteins may arise to due impaired recycling, a potential consequence of cholesterol accumulation and altered lipid metabolism that is suggested by transcriptome analyses in the KO cells. The stability of cell surface proteins could also be impacted by the presence of secreted proteases, such as the cysteine cathepsins, which were previously shown to retain activity in the extracellular space ^44–46. Our prior work in GNPTAB-knockout HeLa cells showed a decrease in cell surface abundance of the amyloid uptake receptor LRP1 impairs clearance of Aß40 peptide ⁴³. Here we found altered cell surface abundance of additional glycoproteins also relevant to neurodegeneration, including increased abundance of APP itself. Increased APOB, PPIA and PPIB were also observed in the GNPTAB-KO DAOY clones. Notably, APOB has been suggested to be an early marker for tau pathology in Alzheimer’s disease ⁴⁷, whereas PPIA is typically observed in neurofibrillary tangles and neurons containing granulovacuolar degeneration ⁴⁸. Elevation of PPIA, PPIB, TNFSF4 and MICB all highlight an intriguing enrichment in proteins involved inflammation, immune cell function, and stress responses within the ER.

Our investigation identified increased abundance of the key autophagy regulator, p62/SQSTM1, that was evident at the level of the transcriptome (Figure 2) and cell surface proteome (Figure 5). Increased p62 abundance corresponds with impaired autophagy, which is expected in MLII due to the profound lysosomal dysfunction. This protein has also been shown to be relevant in the onset of morphine tolerance. Studies in rodent models and cultured cells have shown that modulating p62 abundance impacts tolerance to this commonly used pain medication ^49–51. Chronic morphine administration can increase p62 levels and several studies show that reducing p62 abundance can alleviate morphine tolerance ⁴⁹. High dose pain medications are often required for ML patients dealing with severe joint and bone pain typically associated with this condition. In light of our findings, we hypothesize that impaired autophagy and increased p62 levels may influence ML patient response to these medications, rendering them less effective for pain management. The observed differences in transcript and protein abundance of multiple components within drug metabolism pathways, in particular glucuronate metabolism, further support this possibility. This pathway is important for the clearance of drugs in the liver through their conjugation with glucuronic acid ^52,53. SEEL labeling also uncovered altered cell surface abundance of several ABC transporters. It is unclear whether these changes arise secondarily due to effects on lipid metabolism or what impact such alterations would have on drug metabolism. The issue of how lysosomal dysfunction impacts drug uptake, sensitivity, resistance and metabolism is an important understudied area of research that warrants greater attention and awareness.

From a broader perspective, this study adds to the growing connection between lysosomal dysfunction and neurodegeneration. Whether variants in GNPTAB prove to be genuine modifiers of neurodegenerative conditions like Alzheimer’s or Parkinson’s disease is yet to be proven, but our evidence clearly suggests the involvement of pathways related to these conditions. The broad deficiency in lysosomal glycosidases observed in ML disease, including many already linked to neurodegenerative disorders, would predict that GNPTAB loss-of-function would contribute to onset and/or progression in Alzheimer’s disease. Cathepsin proteases have been implicated in Alzheimer’s and other neurodegenerative conditions as disease modifiers, but their impact is less clear ^27,54–56. While we did detect increased APP abundance in GNPTAB KO cells, no obvious effects on APP processing were noted. Therefore, the contribution of cathepsin secretion, a known hallmark of ML, on intracellular or extracellular APP processing remains to be elucidated.

Conclusions

This study uncovers transcriptomic and proteomic alterations in GNPTAB KO cells within biochemical pathways not previously associated with ML, including neurodegeneration, drug metabolism, and nucleotide-sugar/amino acid metabolism. We view these observations as important clues into emerging aspects of this condition, such as anecdotal reports of altered responses to pain medication in patients with advanced ML disease and the growing link between lysosomal disorders and adult neurodegenerative diseases. We expect others may identify other pathways of interest upon reviewing these results and hope the collective insights made will point the way towards much-needed therapies and improvements in quality of life.