#METABOLOMICS WORKBENCH xs41379_20210916_114337 DATATRACK_ID:2845 STUDY_ID:ST001981 ANALYSIS_ID:AN003231 PROJECT_ID:PR001257 VERSION 1 CREATED_ON September 16, 2021, 12:08 pm #PROJECT PR:PROJECT_TITLE Non-destructive characterization of Mesenchymal stem cells PR:PROJECT_SUMMARY Background: Mesenchymal stem cells (MSCs) have shown promising results in PR:PROJECT_SUMMARY clinical trials for their anti-inflammatory function. However, MSC therapy PR:PROJECT_SUMMARY isn’t licensed by FDA, in part because of the heterogeneity of MSCs. The lack PR:PROJECT_SUMMARY of predictive markers also makes it difficult to both manufacture and translate PR:PROJECT_SUMMARY MSCs into clinic. Indoleamine 2,3-Dioxygenase (IDO) assay and T cell suppression PR:PROJECT_SUMMARY assays correlate with MSCs function. We previously showed that cellular PR:PROJECT_SUMMARY metabolites can be used to predict IDO assay and T cell suppression results. PR:PROJECT_SUMMARY Although these methods are promising, they are all destructive and PR:PROJECT_SUMMARY time-consuming and therefore cannot easily translate to a cell manufacturing PR:PROJECT_SUMMARY setting. A non-destructive, in-process method to evaluate cell quality would be PR:PROJECT_SUMMARY extremely valuable. Methods: Culture media from the growth of three different PR:PROJECT_SUMMARY MSC cell lines (two bone marrow, one iPSC) were sampled daily for NMR PR:PROJECT_SUMMARY metabolomics analysis. T cell proliferation and IDO assays were used as PR:PROJECT_SUMMARY surrogates of anti-inflammatory function. Linear regression was used to assess PR:PROJECT_SUMMARY the media metabolic changes over time, and partial least squares regression PR:PROJECT_SUMMARY (PLSR) was then used to obtain predictive media markers (PMMs) based on variable PR:PROJECT_SUMMARY importance in projection (VIP) scores. In addition, pathway analysis was PR:PROJECT_SUMMARY performed to show the relations between media metabolites (MMs) and cell PR:PROJECT_SUMMARY metabolites (CMs). Results: Depending on the time of sampling, PLSR of culture PR:PROJECT_SUMMARY media regressed against a composite score resulted in R2 values between 0.73 and PR:PROJECT_SUMMARY 0.86. Several amnio acids and organic acids were useful PMMs at different time PR:PROJECT_SUMMARY periods. Correlation and pathway analyses related the consumption of valine and PR:PROJECT_SUMMARY aspartate to the release of glycine and alanine during culture. Discussion: The PR:PROJECT_SUMMARY work described here used PLSR models to identify PMMs that can predict MSC PR:PROJECT_SUMMARY function. This method is relatively simple, non-destructive and can could in the PR:PROJECT_SUMMARY future be used in a manufacturing setting to help predict MSC function. PR:INSTITUTE University of Georgia PR:LAST_NAME Shen PR:FIRST_NAME Xunan PR:ADDRESS 315 riverbend road PR:EMAIL xs41379@uga.edu PR:PHONE 7858407009 #STUDY ST:STUDY_TITLE Non-destructive characterization of Mesenchymal stem cells ST:STUDY_SUMMARY Culture media from the growth of three different MSC cell lines (two bone ST:STUDY_SUMMARY marrow, one iPSC) were sampled daily for NMR metabolomics analysis. T cell ST:STUDY_SUMMARY proliferation and IDO assays were used as surrogates of anti-inflammatory ST:STUDY_SUMMARY function. Linear regression was used to assess the media metabolic changes over ST:STUDY_SUMMARY time, and partial least squares regression (PLSR) was then used to obtain ST:STUDY_SUMMARY predictive media markers (PMMs) based on variable importance in projection (VIP) ST:STUDY_SUMMARY scores. In addition, pathway analysis was performed to show the relations ST:STUDY_SUMMARY between media metabolites (MMs) and cell metabolites (CMs). ST:INSTITUTE University of Georgia ST:LAST_NAME Shen ST:FIRST_NAME Xunan ST:ADDRESS 315 riverbend road ST:EMAIL xs41379@uga.edu ST:PHONE 7858407009 #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 - iMSCp1 experimental factor:p1 SUBJECT_SAMPLE_FACTORS - iMSCp2 experimental factor:p2 SUBJECT_SAMPLE_FACTORS - iMSCp3 experimental factor:p3 SUBJECT_SAMPLE_FACTORS - BM71P1 experimental factor:P1 SUBJECT_SAMPLE_FACTORS - BM71P2 experimental factor:P2 SUBJECT_SAMPLE_FACTORS - BM71P3 experimental factor:P3 SUBJECT_SAMPLE_FACTORS - BM182P1 experimental factor:P1 SUBJECT_SAMPLE_FACTORS - BM182P2 experimental factor:P2 SUBJECT_SAMPLE_FACTORS - BM182P3 experimental factor:P3 #COLLECTION CO:COLLECTION_SUMMARY Each cell line has 10 replicates. Two bone marrow-derived MSC lines (RoosterBio, CO:COLLECTION_SUMMARY Frederick MD) lot #0071 (F, 18-30) and #0182 (F, 26) (which the manufacturer has CO:COLLECTION_SUMMARY both research and clinical-grade lots available), and one induced pluripotent CO:COLLECTION_SUMMARY stem cell derived MSC cell-line (Cellular Dynamics International, Madison WI) CO:COLLECTION_SUMMARY (Lot #0003, also prequalified) were used and referred here as BM71, BM182, and CO:COLLECTION_SUMMARY iMSC, respectively. iMSC were cultured for 25 days, BM71 were cultured for 21 CO:COLLECTION_SUMMARY days and BM182 were cultured for 23 days. 100 µl media was sampled daily from CO:COLLECTION_SUMMARY each sample and stored at -80◦C for further analysis. CO:SAMPLE_TYPE Bone marrow #TREATMENT TR:TREATMENT_SUMMARY Each cell line has 10 replicates. Two bone marrow-derived MSC lines (RoosterBio, TR:TREATMENT_SUMMARY Frederick MD) lot #0071 (F, 18-30) and #0182 (F, 26) (which the manufacturer has TR:TREATMENT_SUMMARY both research and clinical-grade lots available), and one induced pluripotent TR:TREATMENT_SUMMARY stem cell derived MSC cell-line (Cellular Dynamics International, Madison WI) TR:TREATMENT_SUMMARY (Lot #0003, also prequalified) were used and referred here as BM71, BM182, and TR:TREATMENT_SUMMARY iMSC, respectively. iMSC were cultured for 25 days, BM71 were cultured for 21 TR:TREATMENT_SUMMARY days and BM182 were cultured for 23 days. 100 µl media was sampled daily from TR:TREATMENT_SUMMARY each sample and stored at -80◦C for further analysis. #SAMPLEPREP SP:SAMPLEPREP_SUMMARY One hundred µl culture media was thawed on ice and then centrifuged at 14,000 x SP:SAMPLEPREP_SUMMARY g for 15 min at 4◦C. For each sample, 54 µl of media supernatant was SP:SAMPLEPREP_SUMMARY transferred to a new Eppendorf tube. 30 µl of remaining media in each sample SP:SAMPLEPREP_SUMMARY from the same cell line was pooled together to generate six 54 µl internal SP:SAMPLEPREP_SUMMARY quality control (QC) samples. 6 µl of 10/3 mM DSS-D6 (Cambridge Isotope SP:SAMPLEPREP_SUMMARY Laboratory) in D2O (Cambridge Isotope Laboratory) was then added into each SP:SAMPLEPREP_SUMMARY sample. In addition, six buffer blanks (6 µl of 10/3 mM DSS-D6 in 54 µl D2O) SP:SAMPLEPREP_SUMMARY samples were added in each cell line for quality assurance purpose. We had 10 SP:SAMPLEPREP_SUMMARY replicates for each cell line and time point. A total of 262 samples including SP:SAMPLEPREP_SUMMARY 250 experimental samples, 6 pooled samples and 6 buffer blanks were generated SP:SAMPLEPREP_SUMMARY for the iMSC group. A total of 222 samples including 210 experimental samples, 6 SP:SAMPLEPREP_SUMMARY pooled samples and 6 buffer blanks were generated for BM71. A total of 242 SP:SAMPLEPREP_SUMMARY samples including 230 experimental samples, 6 pooled samples and 6 buffer blanks SP:SAMPLEPREP_SUMMARY were generated for BM182. All samples were randomized to reduce technical SP:SAMPLEPREP_SUMMARY variance. #ANALYSIS AN:ANALYSIS_TYPE NMR #NMR NM:INSTRUMENT_NAME bruker800 NM:INSTRUMENT_TYPE FT-NMR NM:NMR_EXPERIMENT_TYPE 1D-1H NM:SPECTROMETER_FREQUENCY 800 #NMR_METABOLITE_DATA NMR_METABOLITE_DATA:UNITS change rate NMR_METABOLITE_DATA_START Samples iMSCp1 iMSCp2 iMSCp3 BM71P1 BM71P2 BM71P3 BM182P1 BM182P2 BM182P3 Factors experimental factor:p1 experimental factor:p2 experimental factor:p3 experimental factor:P1 experimental factor:P2 experimental factor:P3 experimental factor:P1 experimental factor:P2 experimental factor:P3 leucine 2500000000 4000000000 -13500000000 15000000000 10000000000 25000000000 2000000000 1000000000 -500000000 isoleucine -8500000000 3000000000 -13500000000 6500000000 3000000000 8000000000 -4000000000 3500000000 -500000000 valine 7000000000 8000000000 -4000000000 13500000000 14500000000 25000000000 16500000000 10000000000 6500000000 ethanol 49000000000 73500000000 73000000000 66000000000 2.43E+11 2.06E+11 1.19E+11 71500000000 86000000000 threonine -2500000000 2500000000 -5500000000 40000000000 14000000000 30000000000 2500000000 -15000000000 4000000000 alanine 16500000000 14000000000 2000000000 26000000000 31500000000 30500000000 20000000000 12500000000 13000000000 uk1 -9500000000 2.02E-06 -19000000000 10000000000 -2.70E-06 -15000000000 10000000000 5500000000 12500000000 acetic_acid -3500000000 24000000000 -5500000000 16000000000 -25000000000 -32500000000 16500000000 3500000000 16000000000 uk2 80000000000 45000000000 65000000000 1.10E+11 1.55E+11 1.70E+11 80000000000 70000000000 45000000000 glutamine -1.30E+11 -55000000000 -1.55E+11 -85000000000 -1.85E+11 -1.40E+11 -1.15E+11 -90000000000 -75000000000 pyruvate -2000000000 4500000000 -500000000 7500000000 -4000000000 -13500000000 -6000000000 -4000000000 5000000000 succinate 55500000000 30000000000 45000000000 60000000000 95500000000 92000000000 54000000000 48000000000 37000000000 a_ketoglutaric_acid -65000000000 -9000000000 -1.20E+11 -75000000000 -65000000000 -45000000000 -1.35E+11 -75000000000 -60000000000 uk3 1160000000 -6585000000 2245000000 500000000 -6000000000 -13000000000 8650000000 -3550000000 5500000000 glucose -1.08E-05 5000000000 -40000000000 15000000000 35000000000 35000000000 -5000000000 -15000000000 -10000000000 glycine -65000000000 -13000000000 -55000000000 14000000000 -1.81E+11 -1.99E+11 -1.06E+11 -1.14E+11 6000000000 fructose 7500000000 12000000000 500000000 14500000000 37000000000 50500000000 20000000000 26500000000 4500000000 uk4 -25500000000 9000000000 -20000000000 8500000000 -72500000000 -69000000000 -42000000000 -33000000000 -5500000000 lactate 17500000000 28000000000 -4500000000 65000000000 35000000000 30000000000 38500000000 35500000000 35500000000 uk5 45000000000 29000000000 39000000000 55500000000 66000000000 66000000000 39500000000 46000000000 32000000000 tyrosine 1500000000 -500000000 -6500000000 5000000000 -7000000000 -5000000000 4000000000 7500000000 5000000000 uk6 -12500000000 -3500000000 -10500000000 -500000000 -18500000000 -32000000000 -10500000000 3500000000 -2500000000 phenylalanine -2000000000 3000000000 -6500000000 6500000000 -1000000000 3500000000 -2000000000 6500000000 2000000000 arginine -6500000000 -7500000000 -18500000000 -4500000000 4000000000 12000000000 -4000000000 -7500000000 -12000000000 uk7 -5595000000 -4500000000 -6150000000 -2500000000 -4500000000 -4500000000 -5950000000 -4850000000 -3500000000 uk8 -2500000000 1.69E-07 -5500000000 4500000000 2500000000 3500000000 -1.69E-07 -500000000 1000000000 uk9 -47000000000 3500000000 -34500000000 -7000000000 -12000000000 -3000000000 -57000000000 -16500000000 -9000000000 uk10 31000000000 23500000000 28000000000 45500000000 51000000000 48000000000 29500000000 34500000000 27000000000 uk11 -8300000000 -160000000 -5760000000 980000000 -13860000000 -17370000000 -11655000000 -4905000000 -6350000000 uk12 1000000000 -3500000000 -2500000000 -500000000 -5000000000 -7500000000 -6.74E-07 500000000 2000000000 uk13 7000000000 10000000000 4000000000 9000000000 30500000000 40500000000 13000000000 11000000000 -3500000000 asparate -10500000000 -8000000000 -13000000000 -8500000000 -23000000000 -31000000000 -10000000000 -10500000000 500000000 uk14 -20500000000 -9000000000 -18500000000 -2000000000 -32000000000 -39500000000 -21000000000 -18500000000 -500000000 creatine -7000000000 -1500000000 -10000000000 6000000000 -10500000000 -10500000000 -5000000000 -8500000000 -2000000000 uk15 7000000000 3000000000 1.69E-07 22000000000 11500000000 8000000000 7000000000 -1000000000 8000000000 betaine -770000000 1250000000 -355000000 1500000000 -5000000000 -2500000000 -7050000000 400000000 1850000000 proline -1000000000 -4000000000 -5000000000 3000000000 -4000000000 -9000000000 -1000000000 -8500000000 4000000000 myo_inositol 10500000000 -1500000000 -6500000000 14500000000 8000000000 8500000000 3500000000 -1000000000 2500000000 uk16 -760000000 450000000 -1880000000 -235000000 -2590000000 625000000 -2075000000 3285000000 -820000000 uk17 -1050000000 450000000 -3165000000 195000000 -1555000000 1440000000 -910000000 5420000000 5000000 uk18 -495000000 590000000 -945000000 695000000 -650000000 310000000 -225000000 1755000000 875000000 uk19 -305000000 900000000 -530000000 1015000000 -530000000 375000000 -580000000 1375000000 -345000000 uk20 -11500000000 2500000000 -7000000000 -500000000 -12500000000 2000000000 -17500000000 -8000000000 -6500000000 uk21 -960000000 615000000 -2700000000 3000000000 -3000000000 1500000000 -900000000 3850000000 750000000 uk22 -320000000 1070000000 -420000000 2140000000 440000000 1305000000 40000000 2015000000 1345000000 uk23 -2265000000 -1290000000 -2760000000 -1885000000 -2605000000 -1375000000 -1705000000 -250000000 -990000000 uk24 1205000000 5420000000 1645000000 9500000000 8000000000 6000000000 4200000000 6750000000 4900000000 uk25 -3880000000 -1710000000 -4465000000 -2755000000 -4780000000 -3635000000 -3915000000 -910000000 -875000000 uk26 -2895000000 200000000 -4530000000 -500000000 -3300000000 -1000000000 -1900000000 2750000000 -400000000 uk27+formate -770000000 1165000000 -2385000000 1945000000 -835000000 1950000000 -15000000 3695000000 1250000000 NMR_METABOLITE_DATA_END #METABOLITES METABOLITES_START metabolite_name KEGG leucine isoleucine valine ethanol threonine alanine uk1 acetic_acid uk2 glutamine pyruvate succinate a_ketoglutaric_acid uk3 glucose glycine fructose uk4 lactate uk5 tyrosine uk6 phenylalanine arginine uk7 uk8 uk9 uk10 uk11 uk12 uk13 asparate uk14 creatine uk15 betaine proline myo_inositol uk16 uk17 uk18 uk19 uk20 uk21 uk22 uk23 uk24 uk25 uk26 uk27+formate METABOLITES_END #END