#METABOLOMICS WORKBENCH Karin_20241006_114144 DATATRACK_ID:5264 STUDY_ID:ST003544 ANALYSIS_ID:AN005821 PROJECT_ID:PR002180 VERSION 1 CREATED_ON October 9, 2024, 2:10 am #PROJECT PR:PROJECT_TITLE Metabolomics of Ndufs4 KO human induced pluripotent stem cells (iPSCs) PR:PROJECT_TYPE Multi-platform metabolomics analysis PR:PROJECT_SUMMARY Mitochondrial diseases, often linked to complex I (CI) defects, lack curative PR:PROJECT_SUMMARY treatments. High-throughput drug screening using human-relevant platforms is PR:PROJECT_SUMMARY crucial for identifying new therapeutics. Induced pluripotent stem cell (iPSC) PR:PROJECT_SUMMARY and CRISPR technologies offer a powerful tool for this purpose. While typically PR:PROJECT_SUMMARY differentiated into disease-relevant cell types, recent studies support the use PR:PROJECT_SUMMARY of undifferentiated iPSCs for drug discovery. The aim of this project was to PR:PROJECT_SUMMARY develop and characterize NDUFS4 KO iPSCs in their pluripotent state. The PR:PROJECT_SUMMARY metabolic profile of Ndufs4 KO human induced pluripotent stem cells (iPSCs) were PR:PROJECT_SUMMARY compared to that of isogenic controls using multi-platform metabolomics, PR:PROJECT_SUMMARY consisting of targeted LC-MS/MS, targeted GC-MS/MS, and untargeted GC-TOFMS PR:PROJECT_SUMMARY analyses. Metabolic profiling revealed a distinct phenotype in NDUFS4 KO iPSCs, PR:PROJECT_SUMMARY predominantly associated with an elevated NADH/NAD+ ratio, consistent with PR:PROJECT_SUMMARY alterations observed in other models of mitochondrial dysfunction. These PR:PROJECT_SUMMARY findings underscore the potential of iPSCs for early-stage, high-throughput PR:PROJECT_SUMMARY therapeutic screening in mitochondrial diseases. PR:INSTITUTE North-West University PR:LAST_NAME Louw PR:FIRST_NAME Roan PR:ADDRESS Hofman Street, Potchefstroom, North-West, 2520, South Africa PR:EMAIL Roan.Louw@nwu.ac.za PR:PHONE +27182994074 #STUDY ST:STUDY_TITLE Metabolomics of Ndufs4 KO human induced pluripotent stem cells (iPSCs) ST:STUDY_SUMMARY Mitochondrial diseases, often linked to complex I (CI) defects, lack curative ST:STUDY_SUMMARY treatments. High-throughput drug screening using human-relevant platforms is ST:STUDY_SUMMARY crucial for identifying new therapeutics. Induced pluripotent stem cell (iPSC) ST:STUDY_SUMMARY and CRISPR technologies offer a powerful tool for this purpose. While typically ST:STUDY_SUMMARY differentiated into disease-relevant cell types, recent studies support the use ST:STUDY_SUMMARY of undifferentiated iPSCs for drug discovery. Here, we developed and ST:STUDY_SUMMARY characterized NDUFS4 KO iPSCs in their pluripotent state. Metabolomic profiling ST:STUDY_SUMMARY revealed a distinct phenotype in NDUFS4 KO iPSCs, predominantly associated with ST:STUDY_SUMMARY an elevated NADH/NAD+ ratio, consistent with alterations observed in other ST:STUDY_SUMMARY models of mitochondrial dysfunction. These findings underscore the potential of ST:STUDY_SUMMARY iPSCs for early-stage, high-throughput therapeutic screening in mitochondrial ST:STUDY_SUMMARY diseases. ST:INSTITUTE North-West University ST:LAST_NAME Louw ST:FIRST_NAME Roan ST:ADDRESS Hoffman street ST:EMAIL Roan.Louw@nwu.ac.za ST:PHONE +27182994074 #SUBJECT SU:SUBJECT_TYPE Cultured cells SU:SUBJECT_SPECIES Homo sapiens SU:TAXONOMY_ID 9606 #SUBJECT_SAMPLE_FACTORS: SUBJECT(optional)[tab]SAMPLE[tab]FACTORS(NAME:VALUE pairs separated by |)[tab]Raw file names and additional sample data SUBJECT_SAMPLE_FACTORS - WT7_1 Genotype:WT | Sample source:Stem cells RAW_FILE_NAME(LC file name)=WT7_1.d; RAW_FILE_NAME(GCTOF file name)=W7_1.cdf; RAW_FILE_NAME(GC-QQQ file name)=W71_Method1.d; RAW_FILE_NAME(GC-QQQ file name)=W71_Method2.d; RAW_FILE_NAME(GC-QQQ file name)=W71_Method3.d SUBJECT_SAMPLE_FACTORS - WT7_2 Genotype:WT | Sample source:Stem cells RAW_FILE_NAME(LC file name)=WT7_2.d; RAW_FILE_NAME(GCTOF file name)=W7_2.cdf; RAW_FILE_NAME(GC-QQQ file name)=W72_Method1.d; RAW_FILE_NAME(GC-QQQ file name)=W72_Method2.d; RAW_FILE_NAME(GC-QQQ file name)=W72_Method3.d SUBJECT_SAMPLE_FACTORS - WT7_3 Genotype:WT | Sample source:Stem cells RAW_FILE_NAME(LC file name)=WT7_3.d; RAW_FILE_NAME(GCTOF file name)=W7_3.cdf; RAW_FILE_NAME(GC-QQQ file name)=W73_Method1.d; RAW_FILE_NAME(GC-QQQ file name)=W73_Method2.d; RAW_FILE_NAME(GC-QQQ file name)=W73_Method3.d SUBJECT_SAMPLE_FACTORS - WT7_4 Genotype:WT | Sample source:Stem cells RAW_FILE_NAME(LC file name)=WT7_4.d; RAW_FILE_NAME(GCTOF file name)=W7_4.cdf; RAW_FILE_NAME(GC-QQQ file name)=W74_Method1.d; RAW_FILE_NAME(GC-QQQ file name)=W74_Method2.d; RAW_FILE_NAME(GC-QQQ file name)=W74_Method3.d SUBJECT_SAMPLE_FACTORS - WT7_5 Genotype:WT | Sample source:Stem cells RAW_FILE_NAME(LC file name)=WT7_5.d; RAW_FILE_NAME(GCTOF file name)=W7_5.cdf; RAW_FILE_NAME(GC-QQQ file name)=W75_Method1.d; RAW_FILE_NAME(GC-QQQ file name)=W75_Method2.d; RAW_FILE_NAME(GC-QQQ file name)=W75_Method3.d SUBJECT_SAMPLE_FACTORS - KO5_1 Genotype:KO | Sample source:Stem cells RAW_FILE_NAME(LC file name)=KO5_1.d; RAW_FILE_NAME(GCTOF file name)=KO5_1.cdf; RAW_FILE_NAME(GC-QQQ file name)=K51_Method1.d; RAW_FILE_NAME(GC-QQQ file name)=K51_Method2.d; RAW_FILE_NAME(GC-QQQ file name)=K51_Method3.d SUBJECT_SAMPLE_FACTORS - KO5_2 Genotype:KO | Sample source:Stem cells RAW_FILE_NAME(LC file name)=KO5_2.d; RAW_FILE_NAME(GCTOF file name)=KO5_2.cdf; RAW_FILE_NAME(GC-QQQ file name)=K52_Method1.d; RAW_FILE_NAME(GC-QQQ file name)=K52_Method2.d; RAW_FILE_NAME(GC-QQQ file name)=K52_Method3.d SUBJECT_SAMPLE_FACTORS - KO5_3 Genotype:KO | Sample source:Stem cells RAW_FILE_NAME(LC file name)=KO5_3.d; RAW_FILE_NAME(GCTOF file name)=KO5_3.cdf; RAW_FILE_NAME(GC-QQQ file name)=K53_Method1.d; RAW_FILE_NAME(GC-QQQ file name)=K53_Method2.d; RAW_FILE_NAME(GC-QQQ file name)=K53_Method3.d SUBJECT_SAMPLE_FACTORS - KO5_4 Genotype:KO | Sample source:Stem cells RAW_FILE_NAME(LC file name)=KO5_4.d; RAW_FILE_NAME(GCTOF file name)=KO5_4.cdf; RAW_FILE_NAME(GC-QQQ file name)=K54_Method1.d; RAW_FILE_NAME(GC-QQQ file name)=K54_Method2.d; RAW_FILE_NAME(GC-QQQ file name)=K54_Method3.d SUBJECT_SAMPLE_FACTORS - KO5_5 Genotype:KO | Sample source:Stem cells RAW_FILE_NAME(LC file name)=KO5_5.d; RAW_FILE_NAME(GCTOF file name)=KO5_5.cdf; RAW_FILE_NAME(GC-QQQ file name)=K55_Method1.d; RAW_FILE_NAME(GC-QQQ file name)=K55_Method2.d; RAW_FILE_NAME(GC-QQQ file name)=K55_Method3.d #COLLECTION CO:COLLECTION_SUMMARY Five replicate samples per genotype (i.e. distinct cultures in parallel) were CO:COLLECTION_SUMMARY prepared for each metabolic analysis. Each cell pellet, harvested from a T25 CO:COLLECTION_SUMMARY culture flasks, was washed three times with chilled PBS before being quenched in CO:COLLECTION_SUMMARY cold HPLC-grade methanol, with subsequent addition of an internal standard CO:COLLECTION_SUMMARY mixture in cold HPLC-grade water. Thereafter, samples were homogenized using a CO:COLLECTION_SUMMARY vibration mill (30 Hz, 1 min) and incubated on ice (10 min) after the addition CO:COLLECTION_SUMMARY of cold HPLC-grade chloroform. Solvents were added in a ratio of 3:1:1, CO:COLLECTION_SUMMARY methanol/water/chloroform, as required for a modified monophasic Bligh-Dyer CO:COLLECTION_SUMMARY extraction. After centrifugation at 12 000 ×g (10 min, 4°C) supernatants were CO:COLLECTION_SUMMARY aliquoted into 2 mL glass vials. CO:SAMPLE_TYPE Cultured cells #TREATMENT TR:TREATMENT_SUMMARY N/A #SAMPLEPREP SP:SAMPLEPREP_SUMMARY Samples were derivatized by butylation on the day of analysis. To butylate the SP:SAMPLEPREP_SUMMARY dried extracts, 300 μL of freshly prepared 1-butanol:acetyl chloride (4:1, SP:SAMPLEPREP_SUMMARY v/v) was added and samples were incubated at 50 °C for 60 min. Thereafter, SP:SAMPLEPREP_SUMMARY the samples were evaporated to dryness under a gentle stream of nitrogen at 37 SP:SAMPLEPREP_SUMMARY °C. The samples were then reconstituted in 100 μL of water:acetonitrile SP:SAMPLEPREP_SUMMARY (50:50, v/v), containing 0.1% formic acid and vortex mixed. Finally, the total SP:SAMPLEPREP_SUMMARY volume was transferred to 250 μL tapered glass inserts placed in 2 mL vials SP:SAMPLEPREP_SUMMARY and loaded onto the autosampler for analysis.  #CHROMATOGRAPHY CH:CHROMATOGRAPHY_TYPE GC CH:INSTRUMENT_NAME Agilent 7890B CH:COLUMN_NAME Restek Rxi-1MS (30m x 0.32mm x 0.25μm) CH:SOLVENT_A N/A CH:SOLVENT_B N/A CH:FLOW_GRADIENT N/A CH:FLOW_RATE 1 mL/min CH:COLUMN_TEMPERATURE 70 °C for 1 min; followed by a ramp at 12 °C/min until reaching 135 °C, held CH:COLUMN_TEMPERATURE for 1.5 min; a ramp at 2 °C/min until reaching 145 °C, held for 1.5 min; and a CH:COLUMN_TEMPERATURE ramp of 23 °C/min until reaching a final temperature of 300 °C, held for 1 min #ANALYSIS AN:ANALYSIS_TYPE MS #MS MS:INSTRUMENT_NAME Agilent 7010B MS:INSTRUMENT_TYPE Triple quadrupole MS:MS_TYPE EI MS:ION_MODE POSITIVE MS:MS_COMMENTS Redox-related organic acids were analysed by multiple reaction monitoring of the MS:MS_COMMENTS transition from precursor to product ions at associated optimized collision MS:MS_COMMENTS energies, and fragmentor voltages using Agilent Masshunter. To increase MS:MS_COMMENTS analytical sensitivity, dMRMs were divided into three methods (identical MS:MS_COMMENTS chromatography), thus requiring three separate sample injections to analyse all MS:MS_COMMENTS compounds.To achieve the highest confidence level in metabolite identities, two MS:MS_COMMENTS unique transitions were monitored per metabolite, thus, allowing spectral and MS:MS_COMMENTS retention time matching #MS_METABOLITE_DATA MS_METABOLITE_DATA:UNITS Normalised peak areas MS_METABOLITE_DATA_START Samples WT7_1 WT7_2 WT7_3 WT7_4 WT7_5 KO5_1 KO5_2 KO5_3 KO5_4 KO5_5 Factors Genotype:WT | Sample source:Stem cells Genotype:WT | Sample source:Stem cells Genotype:WT | Sample source:Stem cells Genotype:WT | Sample source:Stem cells Genotype:WT | Sample source:Stem cells Genotype:KO | Sample source:Stem cells Genotype:KO | Sample source:Stem cells Genotype:KO | Sample source:Stem cells Genotype:KO | Sample source:Stem cells Genotype:KO | Sample source:Stem cells 2-Keto-3-methylbutyrate 0.435 0.466 0.368 0.424 0.388 0.343 0.468 0.378 0.39 0.377 2-Keto-3-methylvalerate 0.093 0.108 0.102 0.114 0.108 0.082 0.115 0.103 0.148 0.136 2-Ketoglutarate 0.088 0.071 0.086 0.09 0.086 0.068 0.066 0.069 0.073 0.079 2-Hydroxy-3-methylvalerate 10.433 11.03 11.585 11.231 12.232 14.735 16.109 16.441 17.212 17.714 2-Hydroxy-4-methylvalerate 0.676 0.609 0.799 0.636 0.819 0.525 0.496 0.593 0.578 0.604 2-Hydroxyglutarate 0.008 0.008 0.008 0.006 0.005 0.005 0.004 0.004 0.005 0.005 3-Ketodecanoate 0.156 0.15 0.205 0.192 0.182 0.309 0.164 0.239 0.19 0.189 3-Hydroxybutyrate 0.081 0.085 0.069 0.075 0.078 0.08 0.104 0.098 0.107 0.093 3-Hydroxyisovalerate 0.121 0.115 0.131 0.108 0.13 0.088 0.094 0.124 0.113 0.132 3-Hydroxypalmitate 0.195 0.161 0.194 0.163 0.192 0.178 0.16 0.156 0.159 0.167 Acetoacetate 0.222 0.241 0.198 0.219 0.158 0.258 0.303 0.241 0.24 0.254 Citrate 0.273 0.27 0.294 0.276 0.299 0.268 0.254 0.252 0.258 0.262 Lactate 0.862 0.856 0.87 0.89 0.922 0.904 0.891 0.898 0.888 0.889 Aspartate 0.048 0.056 0.044 0.035 0.025 0.035 0.047 0.043 0.049 0.052 Malate 0.068 0.065 0.065 0.056 0.042 0.044 0.045 0.045 0.047 0.043 Pyruvate 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 MS_METABOLITE_DATA_END #METABOLITES METABOLITES_START metabolite_name PubChem ID 2-Hydroxy-3-methylvalerate 10796774 2-Hydroxy-4-methylvalerate 92779 2-Hydroxyglutarate 43 2-Keto-3-methylbutyrate 49 2-Keto-3-methylvalerate 439286 2-Ketoglutarate 51 3-Hydroxybutyrate 441 3-Hydroxyisovalerate 69362 3-Hydroxypalmitate 10989404 Acetoacetate 6971017 Aspartate 5960 Citrate 311 Lactate 107689 Malate 222656 Pyruvate 1060 3-Ketodecanoate 5282982 METABOLITES_END #END