#METABOLOMICS WORKBENCH Xinyu_Zhang_20200818_170706 DATATRACK_ID:2129 STUDY_ID:ST001450 ANALYSIS_ID:AN002423 PROJECT_ID:PR000996 VERSION 1 CREATED_ON August 21, 2020, 11:29 am #PROJECT PR:PROJECT_TITLE Five Easy Metrics of Data Quality for LC-MS based Global Metabolomics PR:PROJECT_TYPE MS global profiling PR:PROJECT_SUMMARY Data quality in global metabolomics is of great importance for biomarker PR:PROJECT_SUMMARY discovery and systems biology studies. However, comprehensive metrics and PR:PROJECT_SUMMARY methods to evaluate and compare the data quality of global metabolomics data PR:PROJECT_SUMMARY sets are lacking. In this work, we combine newly developed metrics, along with PR:PROJECT_SUMMARY well-known measures, to comprehensively and quantitatively characterize the data PR:PROJECT_SUMMARY quality across two similar LC-MS platforms, with the goal of providing an PR:PROJECT_SUMMARY efficient and improved ability to evaluate the data quality in global metabolite PR:PROJECT_SUMMARY profiling experiments. A pooled human serum sample was run 50 times on two PR:PROJECT_SUMMARY high-resolution LC-QTOF-MS platforms to provide profile and centroid MS data. PR:PROJECT_SUMMARY These data were processed using Progenesis Qi software and then analyzed using PR:PROJECT_SUMMARY five important data quality measures, including retention time drift, compound PR:PROJECT_SUMMARY coverage, missing values and MS reproducibility (2 measures). The coverage was PR:PROJECT_SUMMARY fit to a Gamma distribution versus compound abundance, which was normalized to PR:PROJECT_SUMMARY allow comparison of different platforms. To evaluate missing values, PR:PROJECT_SUMMARY characteristic curves were obtained by plotting the compound detection PR:PROJECT_SUMMARY percentage versus extraction frequency. To characterize reproducibility, the PR:PROJECT_SUMMARY accumulative coefficient of variation (CV) versus percentage of total compounds PR:PROJECT_SUMMARY detected and CV vs intra-class correlation coefficient (ICC) were investigated. PR:PROJECT_SUMMARY Key findings include significantly better performance using profile mode data PR:PROJECT_SUMMARY compared to centroid mode as well quantitatively better performance from the PR:PROJECT_SUMMARY newer, higher resolution instrument. A summary of the results given in tabulated PR:PROJECT_SUMMARY form gives a snapshot of the experimental results and provides a template to PR:PROJECT_SUMMARY evaluate the global metabolite profiling workflow. In total, these measures give PR:PROJECT_SUMMARY a good overall view of data quality in global profiling and allow comparisons of PR:PROJECT_SUMMARY data acquisition strategies and platforms as well as optimization of parameters. PR:INSTITUTE University of Washington PR:DEPARTMENT Anesthesiology and Pain PR:LABORATORY Daniel Raftery PR:LAST_NAME Zhang PR:FIRST_NAME Xinyu PR:ADDRESS 850 Republican Street, Seattle, WA, 98109, USA PR:EMAIL xinyu.z@live.com PR:PHONE 8505672757 #STUDY ST:STUDY_TITLE Five Easy Metrics of Data Quality for LC-MS based Global Metabolomics ST:STUDY_SUMMARY Data quality in global metabolomics is of great importance for biomarker ST:STUDY_SUMMARY discovery and systems biology studies. However, comprehensive metrics and ST:STUDY_SUMMARY methods to evaluate and compare the data quality of global metabolomics data ST:STUDY_SUMMARY sets are lacking. In this work, we combine newly developed metrics, along with ST:STUDY_SUMMARY well-known measures, to comprehensively and quantitatively characterize the data ST:STUDY_SUMMARY quality across two similar LC-MS platforms, with the goal of providing an ST:STUDY_SUMMARY efficient and improved ability to evaluate the data quality in global metabolite ST:STUDY_SUMMARY profiling experiments. A pooled human serum sample was run 50 times on two ST:STUDY_SUMMARY high-resolution LC-QTOF-MS platforms to provide profile and centroid MS data. ST:STUDY_SUMMARY These data were processed using Progenesis Qi software and then analyzed using ST:STUDY_SUMMARY five important data quality measures, including retention time drift, compound ST:STUDY_SUMMARY coverage, missing values and MS reproducibility (2 measures). The coverage was ST:STUDY_SUMMARY fit to a Gamma distribution versus compound abundance, which was normalized to ST:STUDY_SUMMARY allow comparison of different platforms. To evaluate missing values, ST:STUDY_SUMMARY characteristic curves were obtained by plotting the compound detection ST:STUDY_SUMMARY percentage versus extraction frequency. To characterize reproducibility, the ST:STUDY_SUMMARY accumulative coefficient of variation (CV) versus percentage of total compounds ST:STUDY_SUMMARY detected and CV vs intra-class correlation coefficient (ICC) were investigated. ST:STUDY_SUMMARY Key findings include significantly better performance using profile mode data ST:STUDY_SUMMARY compared to centroid mode as well quantitatively better performance from the ST:STUDY_SUMMARY newer, higher resolution instrument. A summary of the results given in tabulated ST:STUDY_SUMMARY form gives a snapshot of the experimental results and provides a template to ST:STUDY_SUMMARY evaluate the global metabolite profiling workflow. In total, these measures give ST:STUDY_SUMMARY a good overall view of data quality in global profiling and allow comparisons of ST:STUDY_SUMMARY data acquisition strategies and platforms as well as optimization of parameters. ST:INSTITUTE University of Washington ST:DEPARTMENT Anesthesiology and Pain ST:LABORATORY Daniel Raftery ST:LAST_NAME Zhang ST:FIRST_NAME Xinyu ST:ADDRESS 850 Republican Street, Seattle, Washington 98109, United States ST:EMAIL xinyu.z@live.com ST:PHONE 850-567-2757 #SUBJECT SU:SUBJECT_TYPE Human SU:SUBJECT_SPECIES Homo sapiens SU:TAXONOMY_ID 9606 #FACTORS #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 - 1 Data type:Agilent 6520 profile data RAW_FILE_NAME=1 SUBJECT_SAMPLE_FACTORS - 2 Data type:Agilent 6520 profile data RAW_FILE_NAME=2 SUBJECT_SAMPLE_FACTORS - 3 Data type:Agilent 6520 profile data RAW_FILE_NAME=3 SUBJECT_SAMPLE_FACTORS - 4 Data type:Agilent 6520 profile data RAW_FILE_NAME=4 SUBJECT_SAMPLE_FACTORS - 5 Data type:Agilent 6520 profile data RAW_FILE_NAME=5 SUBJECT_SAMPLE_FACTORS - 6 Data type:Agilent 6520 profile data RAW_FILE_NAME=6 SUBJECT_SAMPLE_FACTORS - 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174 Data type:Agilent 6545 centroid data RAW_FILE_NAME=174 SUBJECT_SAMPLE_FACTORS - 175 Data type:Agilent 6545 centroid data RAW_FILE_NAME=175 SUBJECT_SAMPLE_FACTORS - 176 Data type:Agilent 6545 centroid data RAW_FILE_NAME=176 SUBJECT_SAMPLE_FACTORS - 177 Data type:Agilent 6545 centroid data RAW_FILE_NAME=177 SUBJECT_SAMPLE_FACTORS - 178 Data type:Agilent 6545 centroid data RAW_FILE_NAME=178 SUBJECT_SAMPLE_FACTORS - 179 Data type:Agilent 6545 centroid data RAW_FILE_NAME=179 SUBJECT_SAMPLE_FACTORS - 180 Data type:Agilent 6545 centroid data RAW_FILE_NAME=180 SUBJECT_SAMPLE_FACTORS - 181 Data type:Agilent 6545 centroid data RAW_FILE_NAME=181 SUBJECT_SAMPLE_FACTORS - 182 Data type:Agilent 6545 centroid data RAW_FILE_NAME=182 SUBJECT_SAMPLE_FACTORS - 183 Data type:Agilent 6545 centroid data RAW_FILE_NAME=183 SUBJECT_SAMPLE_FACTORS - 184 Data type:Agilent 6545 centroid data RAW_FILE_NAME=184 SUBJECT_SAMPLE_FACTORS - 185 Data type:Agilent 6545 centroid data RAW_FILE_NAME=185 SUBJECT_SAMPLE_FACTORS - 186 Data type:Agilent 6545 centroid data RAW_FILE_NAME=186 SUBJECT_SAMPLE_FACTORS - 187 Data type:Agilent 6545 centroid data RAW_FILE_NAME=187 SUBJECT_SAMPLE_FACTORS - 188 Data type:Agilent 6545 centroid data RAW_FILE_NAME=188 SUBJECT_SAMPLE_FACTORS - 189 Data type:Agilent 6545 centroid data RAW_FILE_NAME=189 SUBJECT_SAMPLE_FACTORS - 190 Data type:Agilent 6545 centroid data RAW_FILE_NAME=190 SUBJECT_SAMPLE_FACTORS - 191 Data type:Agilent 6545 centroid data RAW_FILE_NAME=191 SUBJECT_SAMPLE_FACTORS - 192 Data type:Agilent 6545 centroid data RAW_FILE_NAME=192 SUBJECT_SAMPLE_FACTORS - 193 Data type:Agilent 6545 centroid data RAW_FILE_NAME=193 SUBJECT_SAMPLE_FACTORS - 194 Data type:Agilent 6545 centroid data RAW_FILE_NAME=194 SUBJECT_SAMPLE_FACTORS - 195 Data type:Agilent 6545 centroid data RAW_FILE_NAME=195 SUBJECT_SAMPLE_FACTORS - 196 Data type:Agilent 6545 centroid data RAW_FILE_NAME=196 SUBJECT_SAMPLE_FACTORS - 197 Data type:Agilent 6545 centroid data RAW_FILE_NAME=197 SUBJECT_SAMPLE_FACTORS - 198 Data type:Agilent 6545 centroid data RAW_FILE_NAME=198 SUBJECT_SAMPLE_FACTORS - 199 Data type:Agilent 6545 centroid data RAW_FILE_NAME=199 SUBJECT_SAMPLE_FACTORS - 200 Data type:Agilent 6545 centroid data RAW_FILE_NAME=200 #COLLECTION CO:COLLECTION_SUMMARY Human serum was frozen at -80 C. CO:SAMPLE_TYPE Blood (serum) #TREATMENT TR:TREATMENT_SUMMARY See sampleprep #SAMPLEPREP SP:SAMPLEPREP_SUMMARY 4 mL frozen commercial pooled human serum (Innovative Research, Novi, MI, USA) SP:SAMPLEPREP_SUMMARY was thawed at 4 °C, vortexed and aliquoted into 50 µL portions in 2 mL SP:SAMPLEPREP_SUMMARY Eppendorf vials. Every 50 µL portion was mixed with 250 µL cold methanol and SP:SAMPLEPREP_SUMMARY vortexed to precipitate proteins.38 After 20 min incubation at −20 °C, these SP:SAMPLEPREP_SUMMARY mixtures were centrifuged at 20,800 x g for 10 min at 4 °C. The supernatants SP:SAMPLEPREP_SUMMARY were transferred into clean 2.0 mL Eppendorf vials and then dried in an SP:SAMPLEPREP_SUMMARY Eppendorf Vacufuge (Brinkmann Instruments, Westbury, NY, USA). The residue in SP:SAMPLEPREP_SUMMARY each Eppendorf vial was reconstituted in 50 µL H2O:ACN (2:3 v/v), vortexed and SP:SAMPLEPREP_SUMMARY centrifuged at 20,800 x g for 10 min at 4 °C. The supernatant in all Eppendorf SP:SAMPLEPREP_SUMMARY vials was pooled into a 5 mL Eppendorf vial, vortexed and centrifuged at xx,xxx SP:SAMPLEPREP_SUMMARY x g (To Dan: I should have used 5000 rpm or a typical rpm in the big centrifuge SP:SAMPLEPREP_SUMMARY in the biosample prep lab) for 10 min at 4 °C to further remove any solid SP:SAMPLEPREP_SUMMARY residue. The resultant supernatant was aliquoted into 50 µL portions in 1.5 mL SP:SAMPLEPREP_SUMMARY Eppendorf vials and stored at −80 °C. Prior to repeated injections to LC-MS SP:SAMPLEPREP_SUMMARY in this work, 8 portions were diluted to 200 µL each with H2O:ACN (2:3 v/v), SP:SAMPLEPREP_SUMMARY pooled into a 2 mL LC vial and vortexed. #CHROMATOGRAPHY CH:CHROMATOGRAPHY_SUMMARY The mobile phase consisted of (A) H2O:ACN (95:5, v/v) with 5 mM ammonium acetate CH:CHROMATOGRAPHY_SUMMARY and 0.1% acetic acid, and (B) H2O:ACN (5:95, v/v), 5 mM ammonium acetate and CH:CHROMATOGRAPHY_SUMMARY 0.1% acetic acid. Gradient elution was performed as follows: 100% mobile phase B CH:CHROMATOGRAPHY_SUMMARY for 1.5 min, 100 to 78% B from 1.5-6.0 min, 78 to 50% B from 6.0-9.0 min, 50% B CH:CHROMATOGRAPHY_SUMMARY from 9.0-15.0 min, restoration to 100% B from 15.0-17.0 min, and continued 100% CH:CHROMATOGRAPHY_SUMMARY B from 17.0-30.0 to equilibrate the LC column. The flow rate was 0.3 mL/min, the CH:CHROMATOGRAPHY_SUMMARY injection volume was 5 µL, followed by an H2O:ACN (5:95, v/v) needle wash for CH:CHROMATOGRAPHY_SUMMARY 10 s, and the column temperature was 35 oC. CH:CHROMATOGRAPHY_TYPE HILIC CH:INSTRUMENT_NAME Agilent 1290 Infinity CH:COLUMN_NAME Waters XBridge BEH Amide column (15 cm x 2.1 mm, 2.5 µm) #ANALYSIS AN:ANALYSIS_TYPE MS AN:DATA_FORMAT .d (profile) #MS MS:INSTRUMENT_NAME Agilent 6545 QTOF MS:INSTRUMENT_TYPE QTOF MS:MS_TYPE ESI MS:ION_MODE POSITIVE MS:MS_COMMENTS (Agilent 6545) MS scan rate of 1.03 spectra/s across the range m/z 60-1000. The MS:MS_COMMENTS software, Progenesis Qi, was used to process raw data. In the results, every MS:MS_COMMENTS compound (feature) had at least two ions, like an ion and its isotope ion or MS:MS_COMMENTS adduct ion. Compounds with single ions were filtered out. If a compound had m/z MS:MS_COMMENTS information only, the m/z was directly used in the compound name. If a compound MS:MS_COMMENTS had neutral mass information, the neutral mass was converted to m/z. MS:MS_RESULTS_FILE ST001450_AN002423_Results.txt UNITS:Peak area Has m/z:Yes Has RT:Yes RT units:Minutes #END