Deciphering neuronal deficit and protein profile changes in human brain organoids from patients with creatine transporter deficiency
- Université Paris-Saclay, CEA, INRAE, Département Médicaments et Technologies pour la Santé, France
- Department of Pharmacy Practice and Pharmacotherapeutics, College of Pharmacy, University of Sharjah, United Arab Emirates
- Sharjah Institute for Medical Research, University of Sharjah, United Arab Emirates
- CERES BRAIN Therapeutics, France
- Institute of Enzymology, Research Centre for Natural Sciences, ELKH, and Doctoral School of Molecular Medicine, Semmelweis University, Hungary
- Department of Pediatrics, University of Cincinnati College of Medicine and Division of Neurology, Cincinnati Children’s Research Foundation, United States
- SupBiotech/Service d'Etude des Prions et des Infections Atypiques (SEPIA), Institut François Jacob, CEA, Université Paris Saclay, France
- Université Paris-Saclay, CEA, INRAE, Département Médicaments et Technologies pour la Santé (DMTS), SPI, France
- Clinical Sciences Department, College of Medicine, University of Sharjah, United Arab Emirates
- Division of Surgery and Interventional Science, University College London, United Kingdom
- ASPIRE Precision Medicine Research Institute Abu Dhabi, University of Sharjah, United Arab Emirates
Figures
Figure 1 with 3 supplements
Generation and characterization of human creatine transporter deficiency (CTD) brain organoids.
(A) Intracellular concentration of creatine in CTD iPSCs after 1 hr incubation with creatine-supplemented media. Healthy control is BJ. n=3–4, one-way ANOVA, Tukey’s multiple comparison test. (B–D) …
Figure 1—figure supplement 1
Generation of creatine transporter deficiency (CTD) iPSCs.
(A) Real-time PCR (RT-qPCR) of pluripotency markers SOX2, NANOG, and OCT4 in fibroblasts (PK and CTD1, 2, and 3) and iPSCs (BJ and CTD1-4, 2–3, and 3–7). n=1–3. (B) Representative analysis of SSEA4 …
Figure 1—figure supplement 2
Generation of creatine transporter deficiency (CTD)-rescue iPSCs.
(A) The p10-CAG-SLC6A8-IRES2-eGFP vector used for transfection. (B) FACS analysis of transfected cells according to pluripotency marker SSEA4 (RL1-H) and green fluorescent protein (GFP) (BL1-H). (C) …
Figure 1—figure supplement 3
Assessment of brain organoids variability.
Diameter of healthy BJ brain organoids obtained from three different productions.
Figure 2 with 1 supplement
Creatine transporter deficiency (CTD) brain organoid organization and neurogenesis deficit.
(A) Representative images of 2 month old brain organoid tissue sections immunostained for PAX6 (radial glial cell and forebrain marker), MAP2 (neuronal marker), PSD95 (post-synaptic marker), TBR1 …
Figure 2—figure supplement 1
Neurogenesis deficit in a creatine transporter deficiency (CTD) mouse model.
Relative mRNA expression of SOX2 (radial glial cell markers) in whole brains of postnatal day 0 Slc6a8-/y mice. n=8 Slc6a8+/y, 7 Slc6a8-/y mice. Data was analyzed using a two-tailed t-test on 2-(ΔΔCt…
Figure 3 with 1 supplement
Unsupervised hierarchical clustering, reproducibility plots, principal component analysis (PCA), volcano plots, and Venn diagram showing overlap of the proteins.
(A–R) The degree and quality of the separation of the data between the various groups being compared Healthy (BJ) vs creatine transporter deficiency (CTD)-derived brain organoids (CTD1_4); Healthy …
Figure 3—figure supplement 1
Flowchart diagram depicting the entire bioinformatics analysis workflow.
The raw data generated by MS/MS was normalized and filtered. The proteins significantly altered in the three creatine transporter deficiency (CTD)-derived cerebral organoids in comparison with …
Figure 4
Representation of heatmaps and graphs obtained by the absolute gene set enrichment analysis (GSEA) for significant pathways with enrichment scores.
(A–C) Enrichment score and graphical representation for the GSEA for healthy vs creatine transporter deficiency (CTD)-derived brain organoids obtained across the gene sets c2_cp; c3_tft; c4_cgn; …
Figure 5
Heatmap, STRING interaction, and GO molecular functional analysis.
(A) Heatmap showing expression levels of the 142 proteins in the top 90 percentile. (B) Heatmap showing expression levels of 32 most altered and abundant proteins were found to be significantly …
Figure 6
Relationship between GSK3β and neurogenesis deficit.
(A–B) Representative western blot of GSK3β and pSer9-GSK3β in creatine transporter deficiency (CTD) vs healthy brain organoids (A) and graph showing analysis of P-GSK3β/GSK3β ratio (B). n=8, one-way …
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Figure 6—source data 1
Original files of the full raw unedited blots (colorimetric and chemiluminescence images) for Figure 6A–B.
- https://cdn.elifesciences.org/articles/88459/elife-88459-fig6-data1-v1.zip
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Figure 6—source data 2
Original files of the full raw unedited blots (colorimetric and chemiluminescence images) for Figure 6C–D.
- https://cdn.elifesciences.org/articles/88459/elife-88459-fig6-data2-v1.zip
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Figure 6—source data 3
Original files of the full raw unedited blots (colorimetric and chemiluminescence images) for Figure 6E–H.
- https://cdn.elifesciences.org/articles/88459/elife-88459-fig6-data3-v1.zip
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Figure 6—source data 4
Original files of the full raw unedited blots (colorimetric and chemiluminescence images) for Figure 6I–L.
- https://cdn.elifesciences.org/articles/88459/elife-88459-fig6-data4-v1.zip
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Figure 6—source data 5
Figures with the uncropped blots with the relevant bands labeled for Figure 6.
- https://cdn.elifesciences.org/articles/88459/elife-88459-fig6-data5-v1.zip
Figure 7
Schematic presentation of the main findings of the study.
The decrease in the cerebral creatine pool could favor the accumulation of the dephosphorylated form of GSK3β, making it more active. This kinase has many targets in the cell, including …
Additional files
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Supplementary file 1
Raw proteomic Data showing the list of proteins and their spectral counts generated by High-resolution tandem mass spectrometry on the 16 biological samples generated a very large dataset comprising a total of 943,656 MS/MS spectra and the monitoring of the abundance of 4219 proteins.
- https://cdn.elifesciences.org/articles/88459/elife-88459-supp1-v1.xlsx
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Supplementary file 2
Normalized and filtered proteomic data.
The raw proteomic data consisting of 4219 proteins were normalized using Variance Stabilizing Normalization (VSN) and filtered using an unsupervised variation filter.
- https://cdn.elifesciences.org/articles/88459/elife-88459-supp2-v1.xlsx
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Supplementary file 3
Normalized and filtered proteomic data were sorted according to p-value (p<0.05 and logfc).
The differential expression analysis of the proteins between healthy and CTD-derived brain organoids was carried out using a modification of the R package for Reproducibility-Optimized Test Statistic (ROTS). The data was sorted according to p-value (<0.05) based on FDR ≤0.25. The blue color indicated proteins downregulated in CTD compared to BJ organoids. The red color indicates proteins upregulated in healthy (BJ) vs CTD-derived brain organoids.
- https://cdn.elifesciences.org/articles/88459/elife-88459-supp3-v1.xlsx
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Supplementary file 4
Frequency of proteins identified by GSEA.
Absolute GSEA was carried out searching through more than 10,000 different cellular pathways obtained across well-annotated gene sets (c2_cp; c3_tft; c4_cgn; c5_bp; c5_mf; c7). The pathways identified through the GSEA were sorted according to the nominal p-value (<0.05). The list of enriched genes was then identified for each significant pathway and their recurrence in other pathways among all studied gene sets. The genes with the highest frequency across the multiple significant pathways (top 90 percentile cut-off; a total of 142 proteins) were selected for subsequent analysis.
- https://cdn.elifesciences.org/articles/88459/elife-88459-supp4-v1.xlsx
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Supplementary file 5
List of 142 proteins sorted according to the fold change.
The 142 identified by the GSEA and frequency analysis (top 90 percentile cut-off) as differentially expressed proteins occurring frequently across all enriched pathways were sorted according to fold change; the most abundant proteins with fold change (–3<fold change >+3) (48 proteins, highlighted in yellow) and a sc higher than 10 (32 proteins, highlighted in dark yellow) were selected for further analysis. The 32 proteins selected are the following: RUFY3; MAP1B; GSK3B; PAK1; STMN1; FYN; GNAI1; MYO5A; PAK2; DCTN1; LMNA; SRC; GNAQ; CDK5; PLCG1; MECP2; ACTN3; HMGB2; SYT1; CALM1; ANXA2; L1CAM; ANK2; ACTN2; TNNT2; MYH6; ANXA1; PTK7; TPM1; SFRP1; POSTN; CASQ2.
- https://cdn.elifesciences.org/articles/88459/elife-88459-supp5-v1.xlsx
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Supplementary file 6
Frequency of 32 proteins identified by Enrichr analysis.
An ENRICHR analysis was performed on the 32 proteins to identify the proteins in potential relation with the cognitive functions. The pathways with p-value less than 0.05 from the following libraries: (BioCarta, Elsevier_Pathway_Collection, GO_Biological_Process, GO_Molecular_Function, KEGG_Human, MSigDB_Hallmark, WikiPathways_Human). The diseases with p value less than 0.05 from the following libraries: (ClinVar, DisGeNET, Jensen_DISEASES, OMIM_Disease).
- https://cdn.elifesciences.org/articles/88459/elife-88459-supp6-v1.docx
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Supplementary file 7
32 proteins functions and relations to creatine transporter deficiency (CTD) symptoms.
- https://cdn.elifesciences.org/articles/88459/elife-88459-supp7-v1.xlsx
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Supplementary file 8
Primer sequences used for real-time PCR (RT-PCR) analysis.
- https://cdn.elifesciences.org/articles/88459/elife-88459-supp8-v1.xlsx
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MDAR checklist
- https://cdn.elifesciences.org/articles/88459/elife-88459-mdarchecklist1-v1.pdf
