#METABOLOMICS WORKBENCH shovall_20200517_020906 DATATRACK_ID:2012 STUDY_ID:ST001380 ANALYSIS_ID:AN002300 PROJECT_ID:PR000944 VERSION 1 CREATED_ON May 18, 2020, 8:30 am #PROJECT PR:PROJECT_TITLE Fast and sensitive flow-injection mass spectrometry metabolomics by analyzing PR:PROJECT_TITLE sample specific ion distributions PR:PROJECT_SUMMARY Mass spectrometry based metabolomics is a widely used approach in biotechnology PR:PROJECT_SUMMARY and biomedical research. However, current methods coupling mass spectrometry PR:PROJECT_SUMMARY with chromatography are time-consuming and not suitable for high-throughput PR:PROJECT_SUMMARY analysis of thousands of samples. An alternative approach is flow-injection mass PR:PROJECT_SUMMARY spectrometry (FI-MS) in which samples are directly injected to the ionization PR:PROJECT_SUMMARY source. Here, we show that the sensitivity of Orbitrap FI-MS metabolomics PR:PROJECT_SUMMARY methods is limited by ion competition effect in the detection system. We PR:PROJECT_SUMMARY describe an approach for overcoming this effect by analyzing the distribution of PR:PROJECT_SUMMARY ion m/z values and computationally determining a series of optimal scan ranges. PR:PROJECT_SUMMARY This enables reproducible detection of ~9,000 and ~10,000 m/z features in PR:PROJECT_SUMMARY metabolomics and lipidomics analysis of serum samples, respectively, with a PR:PROJECT_SUMMARY sample scan time of ~15 seconds and duty time of ~30 seconds; a ~50% increase PR:PROJECT_SUMMARY versus current spectral-stitching FI-MS. This approach facilitates PR:PROJECT_SUMMARY high-throughput metabolomics for a variety of applications, including biomarker PR:PROJECT_SUMMARY discovery and functional genomics screens. PR:INSTITUTE Technion – Israel Institute of Technology PR:LABORATORY Prof. Tomer Shlomi Lab PR:LAST_NAME Lagziel PR:FIRST_NAME Shoval PR:ADDRESS Technion PR:EMAIL shovallagziel@gmail.com PR:PHONE +972-77-8871497 #STUDY ST:STUDY_TITLE Fast and sensitive flow-injection mass spectrometry metabolomics by analyzing ST:STUDY_TITLE sample specific ion distributions ST:STUDY_SUMMARY Mass spectrometry based metabolomics is a widely used approach in biotechnology ST:STUDY_SUMMARY and biomedical research. However, current methods coupling mass spectrometry ST:STUDY_SUMMARY with chromatography are time-consuming and not suitable for high-throughput ST:STUDY_SUMMARY analysis of thousands of samples. An alternative approach is flow-injection mass ST:STUDY_SUMMARY spectrometry (FI-MS) in which samples are directly injected to the ionization ST:STUDY_SUMMARY source. Here, we show that the sensitivity of Orbitrap FI-MS metabolomics ST:STUDY_SUMMARY methods is limited by ion competition effect in the detection system. We ST:STUDY_SUMMARY describe an approach for overcoming this effect by analyzing the distribution of ST:STUDY_SUMMARY ion m/z values and computationally determining a series of optimal scan ranges. ST:STUDY_SUMMARY This enables reproducible detection of ~9,000 and ~10,000 m/z features in ST:STUDY_SUMMARY metabolomics and lipidomics analysis of serum samples, respectively, with a ST:STUDY_SUMMARY sample scan time of ~15 seconds and duty time of ~30 seconds; a ~50% increase ST:STUDY_SUMMARY versus current spectral-stitching FI-MS. This approach facilitates ST:STUDY_SUMMARY high-throughput metabolomics for a variety of applications, including biomarker ST:STUDY_SUMMARY discovery and functional genomics screens. ST:INSTITUTE Technion – Israel Institute of Technology ST:LAST_NAME Lagziel ST:FIRST_NAME Shoval ST:ADDRESS Technion ST:EMAIL shovallagziel@gmail.com ST:PHONE +972-77-8871497 #SUBJECT SU:SUBJECT_TYPE Other 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 - Sample_1 Treatment:Serum RAW_FILE_NAME=Sample_1.raw SUBJECT_SAMPLE_FACTORS - Sample_2 Treatment:Serum RAW_FILE_NAME=Sample_2.raw SUBJECT_SAMPLE_FACTORS - Sample_3 Treatment:Serum RAW_FILE_NAME=Sample_3.raw SUBJECT_SAMPLE_FACTORS - Sample_4 Treatment:Serum RAW_FILE_NAME=Sample_4.raw SUBJECT_SAMPLE_FACTORS - Sample_5 Treatment:Serum RAW_FILE_NAME=Sample_5.raw SUBJECT_SAMPLE_FACTORS - Sample_6 Treatment:Serum RAW_FILE_NAME=Sample_6.raw SUBJECT_SAMPLE_FACTORS - Blank_1 Treatment:Blank RAW_FILE_NAME=Blank_1.raw SUBJECT_SAMPLE_FACTORS - Blank_2 Treatment:Blank RAW_FILE_NAME=Blank_2.raw SUBJECT_SAMPLE_FACTORS - Blank_3 Treatment:Blank RAW_FILE_NAME=Blank_3.raw SUBJECT_SAMPLE_FACTORS - Blank_4 Treatment:Blank RAW_FILE_NAME=Blank_4.raw SUBJECT_SAMPLE_FACTORS - Blank_5 Treatment:Blank RAW_FILE_NAME=Blank_5.raw SUBJECT_SAMPLE_FACTORS - Blank_6 Treatment:Blank RAW_FILE_NAME=Blank_6.raw #COLLECTION CO:COLLECTION_SUMMARY FI-MS method optimization was performed with commercially available serum, Human CO:COLLECTION_SUMMARY AB Serum (Biological Industries USA, Inc., USA). Matrix effect experiments and CO:COLLECTION_SUMMARY biological applications were performed with 98 serum samples of healthy CO:COLLECTION_SUMMARY individuals obtained from Rambam Hospital, Haifa, Israel (IRB 0481-18-RMB). CO:SAMPLE_TYPE Blood (serum) #TREATMENT TR:TREATMENT_SUMMARY To extract metabolites and lipids from serum samples, we mixed 20 µL of serum TR:TREATMENT_SUMMARY with an extraction solution for metabolomics analysis and 10 µL for lipidomics TR:TREATMENT_SUMMARY in 96-deep well plates. For lipidomics analysis, we utilized 100 µL of TR:TREATMENT_SUMMARY 2-propanol/methanol (6:1, v/v); and for metabolomics analysis, 100 µL of TR:TREATMENT_SUMMARY methanol/acetonitrile/water (5:3:1, v/v/v). After 10 min of vortexing, 800 rpm, TR:TREATMENT_SUMMARY precipitated proteins were separated by centrifugation for 20 min at 4 °C and TR:TREATMENT_SUMMARY 4000 rcf; supernatants were stored at -80 °C prior the analysis. #SAMPLEPREP SP:SAMPLEPREP_SUMMARY To extract metabolites and lipids from serum samples, we mixed 20 µL of serum SP:SAMPLEPREP_SUMMARY with an extraction solution for metabolomics analysis and 10 µL for lipidomics SP:SAMPLEPREP_SUMMARY in 96-deep well plates. For lipidomics analysis, we utilized 100 µL of SP:SAMPLEPREP_SUMMARY 2-propanol/methanol (6:1, v/v); and for metabolomics analysis, 100 µL of SP:SAMPLEPREP_SUMMARY methanol/acetonitrile/water (5:3:1, v/v/v). After 10 min of vortexing, 800 rpm, SP:SAMPLEPREP_SUMMARY precipitated proteins were separated by centrifugation for 20 min at 4 °C and SP:SAMPLEPREP_SUMMARY 4000 rcf; supernatants were stored at -80 °C prior the analysis. #CHROMATOGRAPHY CH:CHROMATOGRAPHY_TYPE None (Direct infusion) CH:INSTRUMENT_NAME none CH:COLUMN_NAME none #ANALYSIS AN:ANALYSIS_TYPE MS #MS MS:INSTRUMENT_NAME Thermo Q Exactive Orbitrap MS:INSTRUMENT_TYPE Orbitrap MS:MS_TYPE ESI MS:ION_MODE UNSPECIFIED MS:MS_COMMENTS To determine the number of reproducibly detected m/z features by a specific MS:MS_COMMENTS FI-MS method configuration, we performed 6 repeated injections of the biological MS:MS_COMMENTS sample from the same vial followed by the injection of 6 blank samples (i.e. MS:MS_COMMENTS sample preparation protocol applied to a water sample) and identified MS:MS_COMMENTS reproducibly detected features based on low RSD (<30%) and high SNR (>4) MS:MS_RESULTS_FILE ST001380_AN002300_Results.txt UNITS:intensity Has m/z:Yes Has RT:No RT units:No RT data #END