Mito-TEMPO improves survival rates in npc1-knockout zebrafish by reducing oxidative stress and enhancing mitophagy via Sod2
Data files
Jun 08, 2026 version files 4.42 GB
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Proteomics_DATA.zip
4.42 GB
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README.md
18.34 KB
Jul 22, 2026 version files 4.42 GB
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Proteomics_DATA.zip
4.42 GB
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README.md
19.29 KB
Abstract
Niemann–Pick type C (NPC) disease is a lysosomal storage disorder primarily caused by mutations in the NPC1 gene. Most patients present with early-life symptoms including hepatosplenomegaly and digestive system impairment, followed by progressive neurodegeneration. However, effective therapeutic approaches to improve survival in NPC disease remain limited. In this study, using a npc1-knockout (NPC1-KO) zebrafish model established in our laboratory, our team suggests that npc1-deficiency appears to correlate with marked downregulation of superoxide dismutase 2 (Sod2) expression, concurrent with excessive oxidative stress (OS), mitochondrial dysfunction, and defective mitophagy. Treatment with Mito-TEMPO, a mitochondria-targeted antioxidant acting on SOD, increased survival rates and ameliorated cholesterol accumulation and liver function impairment in early-stage NPC1-KO zebrafish. The underlying mechanism may involve attenuation of OS and promotion of PINK1/Parkin-dependent mitophagic flux through SOD2 enhancement. Our findings support Mito-TEMPO as a potential therapeutic agent and SOD2 as a possible target for NPC disease.
Dataset DOI: 10.5061/dryad.j9kd51csp
Description of the data and file structure
This dataset contains all source data required to reproduce the analyses described in the manuscript titled Mito-TEMPO improves survival rates in npc1-knockout zebrafish by reducing oxidative stress and enhancing mitophagy via Sod2. The dataset is split into two components:
- Quantitative proteomic datasets comparing 1-month-old npc1-knockout and wild-type (WT) zebrafish, with three independent biological replicates per genotype (n = 3). Files hosted on Dryad.
- Raw experimental source data corresponding to main-text Figures 1–7 and Supplementary Figures 1–3, including unprocessed immunofluorescence photographs, full Western blot (WB) gel images, and raw flow cytometry output files. Note that partial cropping was performed on select raw images prior to assembling the final published figures. Files hosted on Zenodo.
Section 1: Quantitative proteomic data files and variables
File: Proteomics_DATA.zip
Description: This folder contains raw and processed quantitative proteomics data comparing 1-month-old npc1-knockout zebrafish and wild-type (WT) control zebrafish. Three independent biological replicates were included for each genotype group (n = 3 per group). Mass spectrometry raw files, normalized abundance matrices, differential expression analysis results, and sample grouping information are organized within subfolders.
Core terminology in Excel and PDF files
| Column Name | Full Definition & Unit/Note |
|---|---|
| ProteinID | Unique accession ID from UniProt zebrafish reference database, dimensionless identifier, no measurement unit |
| GeneSymbol | Official standard gene nomenclature of zebrafish |
| FC (Fold Change) | Expression fold change (KO/WT group), dimensionless ratio value for differential protein abundance |
| P-value | Two-tailed student’s t-test statistical significance value for differential expression screening |
| GO_term | Gene Ontology functional classification annotation text for corresponding protein |
| KEGG_pathway | Annotated metabolic/signaling pathway information from KEGG database |
| Abundance | Protein/peptide quantitative abundance value |
File List
| File Name | Content Description |
|---|---|
| 1. all_kmeans_cluster_annotation.xlsx | Full functional annotation table for all quantified proteins grouped by K-means expression clustering; contains cluster grouping number, gene name, UniProt ID and functional enrichment results of each protein |
| 2. Expressed_annotation.xlsx | Annotation catalogue for all reliably expressed proteins detected in proteome profiling; includes basic protein identity and GO/KEGG functional classification information |
| 3. NPC1_KO_vs_WT_annotation.xlsx | Core differential proteomics table comparing NPC1-knockout(KO) and wild-type(WT) zebrafish; fold change, statistical P-value and functional annotation of significantly altered proteins |
| 4. Peptides_Summary.xlsx | Consolidated quantification raw data of all identified peptides from DIA mass spectrometry experiment; raw abundance values of every detectable peptide across all six biological replicates |
| 5. Protein_Annot_Summary.xlsx | Master integrated summary file: aggregated protein-level quantitative data merged with corresponding gene and pathway annotation; the primary outcome dataset for downstream statistical analysis |
| 6. GO_term files/goAnnotation.xlsx | Full raw annotation linking each protein entry to matched GO terms and descriptive names across three GO domains (BP, CC, MF) |
| 6. GO_term files/goClassification.xls | Summary table for GO primary-level classification grouped by three core GO ontologies |
| 6. GO_term files/goLevel2Classification.xlsx | Secondary GO category classification and corresponding annotated protein count for plotting |
| 6. GO_term files/prot2go.xlsx | Simplified index table containing protein ID-GO ID pairing for downstream bioinformatic enrichment calculation |
| Six M251212XXaP1_*.zip | Raw instrument output files from DIA(Data-Independent Acquisition) liquid chromatography-mass spectrometry (LC-MS); each zip corresponds to one independent biological replicate sample of zebrafish tissue |
| info (1).md5 | Plain-text MD5 checksum file generated by open-source command-line md5sum tool; used to verify local file integrity after user downloads the full dataset |
| Group.abundance.PDF | Figure inside this PDF refers to log2-transformed protein intensity values used for plotting |
Excel file details
All XLSX quantitative tables are standardized pipeline-derived outputs processed by DIA-NN (v1.8.1) combined with MaxLFQ quantification algorithm, following uniform DIA proteomic bioinformatic workflow, no manual data filtering or numerical modification was applied to the raw exported values.
All original raw intensity data from DIA-NN remains unchanged in the Excel source files; only derived normalized values, FC and statistical outputs (P-value/FDR) were newly added columns in final XLSX spreadsheets.
DIA file details
Naming Convention for Raw DIA Zip Files (M25121225aP1_MWY-25-2074-a_DIA_Astral_2.raw)
- M25121225aP1: Sample ID
- MWY-25-2074-a: Project ID
- DIA: Scan mode
- Astral: Mass spectrometer model
Raw DIA mass spectrometry spectra were searched via library-free mode in DIA-NN v1.8.1 against database the uniprotkb_proteome_UP000000437_banmayu_2024_08_06.fasta reference database (46559 protein entries).
Key built-in workflow parameters:
- Deep learning-based spectral library prediction was enabled;
- MBR (Match Between Runs) function was activated to generate in-house spectral library for reanalysis of raw DIA data;
- Precursor ion and protein-level FDR were strictly filtered at 1% threshold as standard pipeline cutoff.
After raw quantitative intensity values were automatically exported from DIA-NN (MaxLFQ algorithm), in-house post-processing normalization and statistical testing were performed manually outside the original software pipeline, detailed as below:
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Intra-sample normalization
Raw protein intensity (Iij) from exported tables was converted into relative normalized quantification value (Rij) with the formula:
Rij=Iij/Median(Ii)
Where: i = individual sample; j = individual detected protein.
This median-centering normalization was conducted per sample to eliminate intra-sample quantitative bias.
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Differential expression statistical analysis
Normalized Rij values were used for downstream differential protein screening:
Two-group comparison: Fold change (FC) = mean normalized abundance ratio between two experimental groups; two-tailed unpaired Student’s t-test was applied to calculate P-value for each protein.
Three or more experimental groups: One-way ANOVA was used to generate P-values across all cohorts.
Multiple testing correction: Benjamini–Hochberg (BH) algorithm was implemented to compute FDR from raw P-values when needed.
Group name Sample ID Product Type Sample Quality Assessment Sample Volume (μL) WT-1 M25121223a Ultra-Fast Quantitative Proteomics Passed 500 WT-2 M25121224a Ultra-Fast Quantitative Proteomics Passed 500 WT-3 M25121225a Ultra-Fast Quantitative Proteomics Passed 500 NPC1 KO-1 M25121226a Ultra-Fast Quantitative Proteomics Passed 500 NPC1 KO-2 M25121227a Ultra-Fast Quantitative Proteomics Passed 500 NPC1 KO-3 M25121228a Ultra-Fast Quantitative Proteomics Passed 500
Section 2: Raw experimental source data corresponding to main-text figures
File: Main_figure_source_data_.zip（https://doi.org/10.5281/zenodo.20521222）
This is the original version of the Zenodo deposit; see below for information about new version.
File: Main_figure_source_data_(NEW VERSION) .zip（https://doi.org/10.5281/zenodo.21478034）
Description: This part is the raw data of Figures 1 – 7 in the main text, covering the most original images such as immunofluorescence, WB bands and flow cytometry. Some of these images were cropped before being used in the main figures. NEW VERSION: Corrected miswritten y-axis labels for JC-1 bar charts in Fig. 4 and Supplementary Fig. S2: all axis text has been updated to JC-1-M and JC-1-A as the standard naming convention. Only labeling text is modified without altering any experimental data.
Fig1.Establishment of NPC1-KO in zebrafish and proteomic results; Mito-TEMPO molecular docking results and zebrafish embryo toxicity test results. (A) Identification of the effect of the npc1 genotype on NPC1-KO zebrafish establishment(npc1 sequence). (B) Fluorescence microscopy of Npc1 in zebrafish. (C) Volcano plot showing clustering of differential proteins in WT and NPC1-KO zebrafish. (D) Heatmap showing clustering of differential proteins in WT and NPC1-KO zebrafish. Proteins related to mitochondria, lysosomes, autophagy, lipid metabolism, OS and apoptosis were chosen. (E) Embryonic development of WT zebrafish exposed to Mito-TEMPO and β-CD. (F) Statistical analysis of heartbeats was performed to evaluate the toxicity of Mito-TEMPO and β-CD.
Fig. 2. Mito-TEMPO therapeutic effect on NPC1-KO zebrafish. (A) Flow chart showing Mito-TEMPO administration in zebrafish. (B) Statistical analysis of zebrafish survival rate. (C) Oil Red O staining of zebrafish showing lipid droplet accumulation mainly in the abdominal cavity, liver, and intestine of NPC1-KO zebrafish. (D) Filipin Ⅲ staining of cholesterol in zebrafish, showing cholesterol accumulation primarily in the abdominal cavity and head of NPC1-KO zebrafish. (E) ROS staining in zebrafish, captured in the abdominal cavity near the liver. (F to K) Statistical results of AST, ALT, triglyceride, total cholesterol, ROS, and MDA levels measured using assay kits.
Fig. 3. Mito-TEMPO effects on Sod2 protein and mitophagy in NPC1-KO zebrafish. (A) Fluorescence microscopy of Sod2 expression in zebrafish. (B) Confocal microscopy of Park2 and Lc3b in zebrafish cells, focusing on the abdominal cavity near the liver. (C) Immunoblot analysis of Sod2, Lc3, and Park2 proteins in zebrafish (WB band). (D) Transmission electron microscopy of zebrafish cells near the intestine. (E to G) Quantitative immunoblot results for Sod2, Lc3, and Park2 proteins in zebrafish.
Fig. 4. Mito-TEMPO effects on cholesterol, ROS and mitochondrial membrane potential in model cells. (A) The flow chart of Mito-TEMPO administration on HepG2 cells. (B) The results of cytotoxicity test of Mito-TEMPO administration. 2.5% DMSO was used as the positive drug for toxicity. (C) The results of Filipin Ⅲ staining for cholesterol in HepG2 cells. (D) The results of ROS staining in HepG2 cells. (E) The results of JC-1 staining for mitochondrial membrane potential in HepG2 cells. Green panel indicates JC-1 monomer (JC-1-M), red panel indicates JC-1 aggregate (JC-1-M). (F) The statistical results of cholesterol and cholesterol ester by cholesterol kit in HepG2 cells. (G) The statistical results of ROS by ROS kit in HepG2 cells. (H) The statistical results of JC-1 MFI by JC-1 kit.
Fig. 5. Mito-TEMPO effects on apoptosis and SOD2 protein in HepG2 cells analyzed by flow cytometry. (A) Flow cytometry dot plots of HepG2 cell apoptosis detected by Annexin V/PI staining. (B) Statistical analysis of apoptosis in HepG2 cells (C) Flow cytometry histograms showing SOD2 expression in HepG2 cells. For each assay, a blank group was set without antibody but with FITC dye. (D) Statistical results for SOD2 expression in HepG2 cells.
Fig. 6. Mito-TEMPO effects on mitophagy flux in HepG2 cells. (A) Confocal fluorescence images of LC3B in HepG2 cells. (B) Confocal fluorescence images of HepG2 cells transfected with the pmCherry-GFP-LC3B tandem reporter. (C) Confocal fluorescence images of HepG2 cells transfected with the pmCherry-GFP-FIS1101–152 tandem reporter. (D) Schematic illustration of pmCherry-GFP-FIS1101–152 tandem reporter analysis principle. (E) Quantification of vesicles positive for both GFP and mCherry (autophagosomes) and for mCherry alone (autolysosomes). (F) Quantification of vesicles positive for mCherry puncta (mitolysosomes).
Fig. 7. Mito-TEMPO effects on mitophagy pathway proteins in HepG2 cells analyzed by flow cytometry. (A to F) Flow cytometry histograms showing LC3B, p62, TOMM20, COX-IV, PINK1 and PARK2 expression in HepG2 cells. For each assay, a blank group was set without antibody but with FITC dye. (G to L) Statistical results for LC3B, SQSTM1/p62, TOMM20, COX-Ⅳ, PINK1 and PARK2 expression in HepG2 cells.
File: Supplementary_Materials_data.zip （https://doi.org/10.5281/zenodo.20521222 )
This is the original version of the Zenodo deposit; see below for information about new version.
File: Supplementary_Materials_data_ (NEW VERSION).zip（https://doi.org/10.5281/zenodo.21478034 )
Description: This part is the raw data of Supplementary Figures 1 — 3 ，covering the most original images such as immunofluorescence and flow cytometry. NEW VERSION: Corrected miswritten y-axis labels for JC-1 bar charts in Fig. 4 and Supplementary Fig. S2: all axis text has been updated to JC-1-M and JC-1-A as the standard naming convention. Only labeling text is modified without altering any experimental data.
Fig. S1. Mito-TEMPO effects on MitoSOX in model cells. (A) The results of ROS staining in HepG2 cells. (B) The statistical results of MitoSOX by MitoSOX kit in HepG2 cells.
Fig. S2. Mito-TEMPO or SOD2-overexpression effects on cholesterol, ROS and mitochondrial membrane potential in model or SOD2-knockdown cells. (A) The plasmid maps of SOD2 OE and SOD2 shRNA construction. (B) Flow cytometry histogram showing SOD2 expression in HepG2 cells. For each assay, a blank group without antibody but with FITC dye. The control group was induced by empty plasmids with EndoFectin HepG2 reagent. (C) Statistical results for SOD2 expression in HepG2 cells. (D) The flow chart of Mito-TEMPO administration and SOD2 OE and SOD2 shRNA plasmids on HepG2 cells. (E) The results of Filipin Ⅲ staining for cholesterol in HepG2 cells. (F) The results of ROS staining in HepG2 cells. (G) The results of JC-1 staining for mitochondrial membrane potential in HepG2 cells. Green panel indicates JC-1 monomer (JC-1-M). (H) The statistical results of cholesterol and cholesterol ester by cholesterol kit in HepG2 cells. (I) The statistical results of ROS by ROS kit in HepG2 cells. (J) The statistical results of JC-1 MFI by JC-1 kit.
Fig. S3. Mito-TEMPO or SOD2-overexpression effects on mitophagy pathway proteins in model or SOD2-knockdown cells. (A to C) Flow cytometry histograms showing LC3B, PINK1 and PARK2 expression in HepG2 cells. For each assay, a blank group without antibody but with FITC dye was included as a control. (D to F) Statistical results for LC3B, PINK1 and PARK2 expression in HepG2 cells.
Code/software
No custom analytical code was generated for this study. Certain dataset files require the following software for access and visualization, with open-source alternatives listed for proprietary programs as requested:
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GraphPad Prism 10: Statistical analysis and quantitative graph plotting
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AutoDock 2.1.6: Molecular docking simulation
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Adobe Acrobat Reader: PDF file preview and document browsing
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Compatible open-source free software: LibreOffice Calc, OpenOffice Calc (cross-platform: Windows/macOS/Linux, fully open access, no proprietary license limitation). Commercial alternatives: Microsoft Excel / WPS Office.
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Compressed .zip raw DIA mass spectrometry archives
Option 1 (Open-source): Download Skyline (free open-source MS analysis software, CC0 compatible) from its official repository to visualize and process extracted raw DIA spectra files;
Option 2 (Convenient access without MS software): All processed peptide/protein quantitative results have been fully exported to above open-format XLSX tables. Users can directly obtain quantified values from Peptides_Summary.xlsx and Protein_Annot_Summary.xlsx without opening original proprietary raw MS files.
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info (1).md5 checksum file
info (1).md5 is plain text file, open with any text editor. To verify file integrity, users use built-in md5sum command via Git Bash(Windows)/Terminal(Mac & Linux). Third-party md5 software is not included in this dataset.