#METABOLOMICS WORKBENCH douglas_walker_20200622_081712_mwtab.txt DATATRACK_ID:2060 STUDY_ID:ST001407 ANALYSIS_ID:AN002351 PROJECT_ID:000000
VERSION             	1
CREATED_ON             	June 22, 2020, 12:08 pm
#PROJECT
PR:PROJECT_TITLE                 	Environmental chemical burden in metabolic tissues and systemic biological
PR:PROJECT_TITLE                 	pathways in adolescent bariatric surgery patients: A pilot untargeted
PR:PROJECT_TITLE                 	metabolomic approach
PR:PROJECT_TYPE                  	Pilot Study
PR:PROJECT_SUMMARY               	Background: Advances in untargeted metabolomic technologies have great potential
PR:PROJECT_SUMMARY               	for insight into adverse metabolic effects underlying exposure to environmental
PR:PROJECT_SUMMARY               	chemicals. However, important challenges need to be addressed, including how
PR:PROJECT_SUMMARY               	biological response corresponds to the environmental chemical burden in
PR:PROJECT_SUMMARY               	different target tissues. Aim: We performed a pilot study using state-of-the-art
PR:PROJECT_SUMMARY               	ultra-high-resolution mass spectrometry (UHRMS) to characterize the burden of
PR:PROJECT_SUMMARY               	lipophilic persistent organic pollutants (POPs) in metabolic tissues and
PR:PROJECT_SUMMARY               	associated alterations in the plasma metabolome. Methods: We studied 11
PR:PROJECT_SUMMARY               	adolescents with severe obesity at the time of bariatric surgery. We measured 18
PR:PROJECT_SUMMARY               	POPs that can act as endocrine and metabolic disruptors (i.e. 2 dioxins, 11
PR:PROJECT_SUMMARY               	organochlorine compounds [OCs] and 5 polybrominated diphenyl ethers [PBDEs]) in
PR:PROJECT_SUMMARY               	visceral and subcutaneous abdominal adipose tissue (vAT and sAT), and liver
PR:PROJECT_SUMMARY               	samples using gas chromatography with UHRMS. Biological pathways were evaluated
PR:PROJECT_SUMMARY               	by measuring the plasma metabolome using high-resolution metabolomics. Network
PR:PROJECT_SUMMARY               	and pathway enrichment analysis assessed correlations between the
PR:PROJECT_SUMMARY               	tissue-specific burden of three frequently detected POPs (i.e.
PR:PROJECT_SUMMARY               	p,p’-dichlorodiphenyldichloroethene [DDE], hexachlorobenzene [HCB] and
PR:PROJECT_SUMMARY               	PBDE-47) and plasma metabolic pathways. Results: Concentrations of 4 OCs and 3
PR:PROJECT_SUMMARY               	PBDEs were quantifiable in at least one metabolic tissue for >80% of
PR:PROJECT_SUMMARY               	participants. All POPs had the highest median concentrations in adipose tissue,
PR:PROJECT_SUMMARY               	especially sAT, except for PBDE-154, which had comparable average concentrations
PR:PROJECT_SUMMARY               	across all tissues. Pathway analysis showed high correlations between
PR:PROJECT_SUMMARY               	tissue-specific POPs and metabolic alterations in pathways of amino acid
PR:PROJECT_SUMMARY               	metabolism, lipid and fatty acid metabolism, and carbohydrate metabolism.
PR:PROJECT_SUMMARY               	Conclusions: Most of the measured POPs appear to accumulate preferentially in
PR:PROJECT_SUMMARY               	adipose tissue compared to liver. Findings of plasma metabolic pathways
PR:PROJECT_SUMMARY               	potentially associated with tissue-specific POPs concentrations merit further
PR:PROJECT_SUMMARY               	investigation in larger populations. Keywords: persistent organic pollutants,
PR:PROJECT_SUMMARY               	adipose tissue, liver, bariatric surgery, exposome, high-resolution metabolomics
PR:INSTITUTE                     	Icahn School of Medicine at Mount Sinai
PR:DEPARTMENT                    	Environmental Medicine and Public Health
PR:LABORATORY                    	High Resolution Exposomics Research Group
PR:LAST_NAME                     	Walker
PR:FIRST_NAME                    	Douglas
PR:ADDRESS                       	One Gustave L. Levy Place, Box 1057, New York, NY 10029
PR:EMAIL                         	douglas.walker@mssm.edu
PR:PHONE                         	212-241-9891
PR:FUNDING_SOURCE                	NIEHS: R21ES028903, R21ES029328, R21ES029681, R01ES029944, R01ES030364,
PR:FUNDING_SOURCE                	U2CES026561, U2CES030163, P30ES023515, P30 ES019776, P30ES007048, P01ES022845,
PR:FUNDING_SOURCE                	R01ES024946; EPA: RD-83544101
PR:PROJECT_COMMENTS              	This upload is 2 of 2 and includes untargeted plasma metabolomics results. Part
PR:PROJECT_COMMENTS              	1 included targeted levels of organic pollutants
PR:PUBLICATIONS                  	Valvi D, Walker DI, Inge T, Bartell SM, Jenkins T, Helmrath M, Ziegler TR, La
PR:PUBLICATIONS                  	Merrill MA, Eckel SP, Conti D, Liang Y, Jones DP, McConnell R, Chatzi L. (2020).
PR:PUBLICATIONS                  	Environmental chemical burden in metabolic tissues and systemic biological
PR:PUBLICATIONS                  	pathways in adolescent bariatric surgery patients: A pilot untargeted
PR:PUBLICATIONS                  	metabolomic approach. Environment International. In Press.
PR:CONTRIBUTORS                  	Valvi D, Walker DI, Inge T, Bartell SM, Jenkins T, Helmrath M, Ziegler TR, La
PR:CONTRIBUTORS                  	Merrill MA, Eckel SP, Conti D, Liang Y, Jones DP, McConnell R, Chatzi L
#STUDY
ST:STUDY_TITLE                   	Environmental chemical burden in metabolic tissues and systemic biological
ST:STUDY_TITLE                   	pathways in adolescent bariatric surgery patients: A pilot untargeted
ST:STUDY_TITLE                   	metabolomic approach
ST:STUDY_TYPE                    	Subcutaneous adipose tissue (AT); Visceral AT; Liver Tissue; Plasma
ST:STUDY_SUMMARY                 	Background: Advances in untargeted metabolomic technologies have great potential
ST:STUDY_SUMMARY                 	for insight into adverse metabolic effects underlying exposure to environmental
ST:STUDY_SUMMARY                 	chemicals. However, important challenges need to be addressed, including how
ST:STUDY_SUMMARY                 	biological response corresponds to the environmental chemical burden in
ST:STUDY_SUMMARY                 	different target tissues. Aim: We performed a pilot study using state-of-the-art
ST:STUDY_SUMMARY                 	ultra-high-resolution mass spectrometry (UHRMS) to characterize the burden of
ST:STUDY_SUMMARY                 	lipophilic persistent organic pollutants (POPs) in metabolic tissues and
ST:STUDY_SUMMARY                 	associated alterations in the plasma metabolome. Methods: We studied 11
ST:STUDY_SUMMARY                 	adolescents with severe obesity at the time of bariatric surgery. We measured 18
ST:STUDY_SUMMARY                 	POPs that can act as endocrine and metabolic disruptors (i.e. 2 dioxins, 11
ST:STUDY_SUMMARY                 	organochlorine compounds [OCs] and 5 polybrominated diphenyl ethers [PBDEs]) in
ST:STUDY_SUMMARY                 	visceral and subcutaneous abdominal adipose tissue (vAT and sAT), and liver
ST:STUDY_SUMMARY                 	samples using gas chromatography with UHRMS. Biological pathways were evaluated
ST:STUDY_SUMMARY                 	by measuring the plasma metabolome using high-resolution metabolomics. Network
ST:STUDY_SUMMARY                 	and pathway enrichment analysis assessed correlations between the
ST:STUDY_SUMMARY                 	tissue-specific burden of three frequently detected POPs (i.e.
ST:STUDY_SUMMARY                 	p,p’-dichlorodiphenyldichloroethene [DDE], hexachlorobenzene [HCB] and
ST:STUDY_SUMMARY                 	PBDE-47) and plasma metabolic pathways. Results: Concentrations of 4 OCs and 3
ST:STUDY_SUMMARY                 	PBDEs were quantifiable in at least one metabolic tissue for >80% of
ST:STUDY_SUMMARY                 	participants. All POPs had the highest median concentrations in adipose tissue,
ST:STUDY_SUMMARY                 	especially sAT, except for PBDE-154, which had comparable average concentrations
ST:STUDY_SUMMARY                 	across all tissues. Pathway analysis showed high correlations between
ST:STUDY_SUMMARY                 	tissue-specific POPs and metabolic alterations in pathways of amino acid
ST:STUDY_SUMMARY                 	metabolism, lipid and fatty acid metabolism, and carbohydrate metabolism.
ST:STUDY_SUMMARY                 	Conclusions: Most of the measured POPs appear to accumulate preferentially in
ST:STUDY_SUMMARY                 	adipose tissue compared to liver. Findings of plasma metabolic pathways
ST:STUDY_SUMMARY                 	potentially associated with tissue-specific POPs concentrations merit further
ST:STUDY_SUMMARY                 	investigation in larger populations.
ST:INSTITUTE                     	Icahn School of Medicine at Mount Sinai
ST:DEPARTMENT                    	Environmental Medicine and Public Health
ST:LABORATORY                    	High Resolution Exposomics Research Group
ST:LAST_NAME                     	Walker
ST:FIRST_NAME                    	Doug
ST:ADDRESS                       	One Gustave L. Levy Place, Box 1057, New York, NY 10029
ST:EMAIL                         	douglas.walker@mssm.edu
ST:PHONE                         	212-241-9891
ST:NUM_GROUPS                    	1
ST:TOTAL_SUBJECTS                	11
ST:NUM_MALES                     	1
ST:NUM_FEMALES                   	10
ST:STUDY_COMMENTS                	Upload #1: Visceral and subcutaneous abdominal adipose tissue, liver tissue.
ST:STUDY_COMMENTS                	Plasma metabolomics are in upload #2
ST:PUBLICATIONS                  	Valvi D, Walker DI, Inge T, Bartell SM, Jenkins T, Helmrath M, Ziegler TR, La
ST:PUBLICATIONS                  	Merrill MA, Eckel SP, Conti D, Liang Y, Jones DP, McConnell R, Chatzi L. (2020).
ST:PUBLICATIONS                  	Environmental chemical burden in metabolic tissues and systemic biological
ST:PUBLICATIONS                  	pathways in adolescent bariatric surgery patients: A pilot untargeted
ST:PUBLICATIONS                  	metabolomic approach. Environment International. In Press.
#SUBJECT
SU:SUBJECT_TYPE                  	Human
SU:SUBJECT_SPECIES               	Homo sapiens
SU:TAXONOMY_ID                   	9606
SU:AGE_OR_AGE_RANGE              	11-20 years
SU:GENDER                        	Male and female
#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           	QC	NIST_1958_1	Description:NIST 1958	Batch=1; RAW_FILE_NAME=VT_170706_001; RAW_FILE_NAME=VT_170706_003; RAW_FILE_NAME=VT_170706_005; RAW_FILE_NAME=VT_170706_002; RAW_FILE_NAME=VT_170706_004; RAW_FILE_NAME=VT_170706_006
SUBJECT_SAMPLE_FACTORS           	QC	q3June2014_1a	Description:Q-Standard plasma pool	Batch=1; RAW_FILE_NAME=VT_170706_007; RAW_FILE_NAME=VT_170706_009; RAW_FILE_NAME=VT_170706_011; RAW_FILE_NAME=VT_170706_008; RAW_FILE_NAME=VT_170706_010; RAW_FILE_NAME=VT_170706_012
SUBJECT_SAMPLE_FACTORS           	QC	q3June2014_1b	Description:Q-Standard plasma pool	Batch=1; RAW_FILE_NAME=VT_170706_013; RAW_FILE_NAME=VT_170706_015; RAW_FILE_NAME=VT_170706_017; RAW_FILE_NAME=VT_170706_014; RAW_FILE_NAME=VT_170706_016; RAW_FILE_NAME=VT_170706_013
SUBJECT_SAMPLE_FACTORS           	QC	chearplasma_1a	Description:CHEAR plasma pool	Batch=1; RAW_FILE_NAME=VT_170706_019; RAW_FILE_NAME=VT_170706_021; RAW_FILE_NAME=VT_170706_023; RAW_FILE_NAME=VT_170706_020; RAW_FILE_NAME=VT_170706_022; RAW_FILE_NAME=VT_170706_014
SUBJECT_SAMPLE_FACTORS           	QC	chearplasma_1b	Description:CHEAR plasma pool	Batch=1; RAW_FILE_NAME=VT_170706_025; RAW_FILE_NAME=VT_170706_027; RAW_FILE_NAME=VT_170706_029; RAW_FILE_NAME=VT_170706_026; RAW_FILE_NAME=VT_170706_028; RAW_FILE_NAME=VT_170706_015
SUBJECT_SAMPLE_FACTORS           	Study_Sample	POTR_02_Plasma	Description:POTR_02	Batch=1; RAW_FILE_NAME=VT_170706_037; RAW_FILE_NAME=VT_170706_039; RAW_FILE_NAME=VT_170706_041; RAW_FILE_NAME=VT_170706_038; RAW_FILE_NAME=VT_170706_040; RAW_FILE_NAME=VT_170706_017
SUBJECT_SAMPLE_FACTORS           	Study_Sample	POTR_03_Plasma	Description:POTR_03	Batch=1; RAW_FILE_NAME=VT_170706_043; RAW_FILE_NAME=VT_170706_045; RAW_FILE_NAME=VT_170706_047; RAW_FILE_NAME=VT_170706_044; RAW_FILE_NAME=VT_170706_046; RAW_FILE_NAME=VT_170706_018
SUBJECT_SAMPLE_FACTORS           	Study_Sample	POTR_04_Plasma	Description:POTR_04	Batch=1; RAW_FILE_NAME=VT_170706_049; RAW_FILE_NAME=VT_170706_051; RAW_FILE_NAME=VT_170706_053; RAW_FILE_NAME=VT_170706_050; RAW_FILE_NAME=VT_170706_052; RAW_FILE_NAME=VT_170706_019
SUBJECT_SAMPLE_FACTORS           	Study_Sample	POTR_05_Plasma	Description:POTR_05	Batch=1; RAW_FILE_NAME=VT_170706_055; RAW_FILE_NAME=VT_170706_057; RAW_FILE_NAME=VT_170706_059; RAW_FILE_NAME=VT_170706_056; RAW_FILE_NAME=VT_170706_058; RAW_FILE_NAME=VT_170706_020
SUBJECT_SAMPLE_FACTORS           	Study_Sample	POTR_06_Plasma	Description:POTR_06	Batch=1; RAW_FILE_NAME=VT_170706_061; RAW_FILE_NAME=VT_170706_063; RAW_FILE_NAME=VT_170706_065; RAW_FILE_NAME=VT_170706_062; RAW_FILE_NAME=VT_170706_064; RAW_FILE_NAME=VT_170706_021
SUBJECT_SAMPLE_FACTORS           	Study_Sample	POTR_07_Plasma	Description:POTR_07	Batch=1; RAW_FILE_NAME=VT_170706_067; RAW_FILE_NAME=VT_170706_069; RAW_FILE_NAME=VT_170706_071; RAW_FILE_NAME=VT_170706_068; RAW_FILE_NAME=VT_170706_070; RAW_FILE_NAME=VT_170706_022
SUBJECT_SAMPLE_FACTORS           	Study_Sample	POTR_08_Plasma	Description:POTR_08	Batch=1; RAW_FILE_NAME=VT_170706_073; RAW_FILE_NAME=VT_170706_075; RAW_FILE_NAME=VT_170706_077; RAW_FILE_NAME=VT_170706_074; RAW_FILE_NAME=VT_170706_076; RAW_FILE_NAME=VT_170706_023
SUBJECT_SAMPLE_FACTORS           	Study_Sample	POTR_09_Plasma	Description:POTR_09	Batch=1; RAW_FILE_NAME=VT_170706_079; RAW_FILE_NAME=VT_170706_081; RAW_FILE_NAME=VT_170706_083; RAW_FILE_NAME=VT_170706_080; RAW_FILE_NAME=VT_170706_082; RAW_FILE_NAME=VT_170706_024
SUBJECT_SAMPLE_FACTORS           	Study_Sample	POTR_10_Plasma	Description:POTR_10	Batch=1; RAW_FILE_NAME=VT_170706_085; RAW_FILE_NAME=VT_170706_087; RAW_FILE_NAME=VT_170706_089; RAW_FILE_NAME=VT_170706_086; RAW_FILE_NAME=VT_170706_088; RAW_FILE_NAME=VT_170706_025
SUBJECT_SAMPLE_FACTORS           	Study_Sample	POTR_11_Plasma	Description:POTR_11	Batch=1; RAW_FILE_NAME=VT_170706_091; RAW_FILE_NAME=VT_170706_093; RAW_FILE_NAME=VT_170706_095; RAW_FILE_NAME=VT_170706_092; RAW_FILE_NAME=VT_170706_094; RAW_FILE_NAME=VT_170706_026
SUBJECT_SAMPLE_FACTORS           	Study_Sample	POTR_12_Plasma	Description:POTR_12	Batch=1; RAW_FILE_NAME=VT_170706_097; RAW_FILE_NAME=VT_170706_099; RAW_FILE_NAME=VT_170706_101; RAW_FILE_NAME=VT_170706_098; RAW_FILE_NAME=VT_170706_100; RAW_FILE_NAME=VT_170706_027
SUBJECT_SAMPLE_FACTORS           	QC	q3June2014_1c	Description:Q-Standard plasma pool	Batch=1; RAW_FILE_NAME=VT_170706_103; RAW_FILE_NAME=VT_170706_105; RAW_FILE_NAME=VT_170706_107; RAW_FILE_NAME=VT_170706_104; RAW_FILE_NAME=VT_170706_106; RAW_FILE_NAME=VT_170706_028
SUBJECT_SAMPLE_FACTORS           	QC	q3June2014_1d	Description:Q-Standard plasma pool	Batch=1; RAW_FILE_NAME=VT_170706_109; RAW_FILE_NAME=VT_170706_111; RAW_FILE_NAME=VT_170706_113; RAW_FILE_NAME=VT_170706_110; RAW_FILE_NAME=VT_170706_112; RAW_FILE_NAME=VT_170706_029
SUBJECT_SAMPLE_FACTORS           	QC	chearplasma_1c	Description:CHEAR plasma pool	Batch=1; RAW_FILE_NAME=VT_170706_115; RAW_FILE_NAME=VT_170706_117; RAW_FILE_NAME=VT_170706_119; RAW_FILE_NAME=VT_170706_116; RAW_FILE_NAME=VT_170706_118; RAW_FILE_NAME=VT_170706_030
SUBJECT_SAMPLE_FACTORS           	QC	chearplasma_1d	Description:CHEAR plasma pool	Batch=1; RAW_FILE_NAME=VT_170706_121; RAW_FILE_NAME=VT_170706_123; RAW_FILE_NAME=VT_170706_125; RAW_FILE_NAME=VT_170706_122; RAW_FILE_NAME=VT_170706_124; RAW_FILE_NAME=VT_170706_031
SUBJECT_SAMPLE_FACTORS           	QC	NIST_1958_2	Description:NIST 1958	Batch=1; RAW_FILE_NAME=VT_170706_127; RAW_FILE_NAME=VT_170706_129; RAW_FILE_NAME=VT_170706_131; RAW_FILE_NAME=VT_170706_128; RAW_FILE_NAME=VT_170706_130; RAW_FILE_NAME=VT_170706_032
#COLLECTION
CO:COLLECTION_SUMMARY            	Eleven adolescents 12–20 years of age undergoing bariatric surgery at
CO:COLLECTION_SUMMARY            	Cincinnati Children’s Hospital between 2006 and 2012 were offered enrollment
CO:COLLECTION_SUMMARY            	in a prospective biospecimen repository protocol (Pediatric Obesity Tissue
CO:COLLECTION_SUMMARY            	Repository [POTR]). Sample recruitment and other POTR features have been
CO:COLLECTION_SUMMARY            	reported previously (Davidson et al. 2017). Intraoperatively, visceral adipose
CO:COLLECTION_SUMMARY            	tissue (vAT) samples from the omentum, abdominal subcutaneous AT (sAT), and
CO:COLLECTION_SUMMARY            	liver samples were obtained by the surgeon and processed immediately in an area
CO:COLLECTION_SUMMARY            	adjacent to the operating room. All samples were snap-frozen in liquid nitrogen,
CO:COLLECTION_SUMMARY            	then stored at −80°C. Plasma was collected pre-operatively after overnight
CO:COLLECTION_SUMMARY            	fasting and stored at -80°C. Written informed consent was obtained from
CO:COLLECTION_SUMMARY            	participants equal to or above 18 years old or from the parent or guardian if
CO:COLLECTION_SUMMARY            	participants were less than 18 years old. The study was approved by the
CO:COLLECTION_SUMMARY            	Institutional Review Board at Cincinnati Children’s Hospital.
CO:SAMPLE_TYPE                   	Blood (plasma)
CO:STORAGE_CONDITIONS            	-80℃
#TREATMENT
TR:TREATMENT_SUMMARY             	The objective of the observational study was to evaluate the relationship
TR:TREATMENT_SUMMARY             	between adipose and liver tissue POPs and the plasma metabolome. All
TR:TREATMENT_SUMMARY             	participants underwent bariatric surgery at the time of tissue collection. No
TR:TREATMENT_SUMMARY             	other treatment or intervention was evaluated.
#SAMPLEPREP
SP:SAMPLEPREP_SUMMARY            	Samples are prepared for metabolomics analysis using established methods
SP:SAMPLEPREP_SUMMARY            	(Johnson et al. (2010). Analyst; Go et al. (2015). Tox Sci). Prior to analysis,
SP:SAMPLEPREP_SUMMARY            	plasma aliquots were removed from storage at -80°C and thawed on ice. Each
SP:SAMPLEPREP_SUMMARY            	cryotube is then vortexed briefly to ensure homogeneity, and 50 μL transferred
SP:SAMPLEPREP_SUMMARY            	to a clean microfuge tube. Immediately after, the plasma is treated with 100 μL
SP:SAMPLEPREP_SUMMARY            	of ice-cold LC-MS grade acetonitrile (Sigma Aldrich) containing 2.5 μL of
SP:SAMPLEPREP_SUMMARY            	internal standard solution with eight stable isotopic chemicals selected to
SP:SAMPLEPREP_SUMMARY            	cover a range of chemical properties. Following addition of acetonitrile, plasma
SP:SAMPLEPREP_SUMMARY            	is then equilibrated for 30 min on ice, upon which precipitated proteins are
SP:SAMPLEPREP_SUMMARY            	removed by centrifuge (16.1 ×g at 4°C for 10 min). The resulting supernatant
SP:SAMPLEPREP_SUMMARY            	(100 μL) is removed, added to a low volume autosampler vial and maintained at
SP:SAMPLEPREP_SUMMARY            	4°C until analysis (<22 h).
SP:SAMPLEPREP_PROTOCOL_ID        	EmoryUniversity_HRM_SP_082016_01.pdf
SP:SAMPLEPREP_PROTOCOL_FILENAME  	EmoryUniversity_HRM_SP_082016_01.pdf
SP:PROCESSING_STORAGE_CONDITIONS 	Room temperature
#CHROMATOGRAPHY
CH:CHROMATOGRAPHY_SUMMARY        	The C18 column is operated parallel to the HILIC column for simultaneous
CH:CHROMATOGRAPHY_SUMMARY        	analytical separation and column flushing through the use of a dual head HPLC
CH:CHROMATOGRAPHY_SUMMARY        	pump equipped with 10-port and 6- port switching valves. During operation of the
CH:CHROMATOGRAPHY_SUMMARY        	C18 method, the MS is operated in negative ion mode and 10 μL of sample is
CH:CHROMATOGRAPHY_SUMMARY        	injected onto the C18 column while the HILIC column is flushing with wash
CH:CHROMATOGRAPHY_SUMMARY        	solution. Flow rate is maintained at 0.4 mL/min until 1.5 min, increased to 0.5
CH:CHROMATOGRAPHY_SUMMARY        	mL/min at 2 min and held for 3 min. Solvent A is 100% LC-MS grade water, solvent
CH:CHROMATOGRAPHY_SUMMARY        	B is 100% LC-MS grade acetonitrile and solvent C is 10mM ammonium acetate in
CH:CHROMATOGRAPHY_SUMMARY        	LC-MS grade water. Initial mobile phase conditions are 60% A, 35% B, 5% C hold
CH:CHROMATOGRAPHY_SUMMARY        	for 0.5 min, with linear gradient to 0% A, 95% B, 5% C at 1.5 min, hold for 3.5
CH:CHROMATOGRAPHY_SUMMARY        	min, resulting in a total analytical run time of 5 min. During the flushing
CH:CHROMATOGRAPHY_SUMMARY        	phase (HILIC analytical separation), the C18 column is equilibrated with a wash
CH:CHROMATOGRAPHY_SUMMARY        	solution of 0% A, 95% B, 5% C until 2.5 min, followed by an equilibration
CH:CHROMATOGRAPHY_SUMMARY        	solution of 60% A, 35% B, 5% C for 2.5 min.
CH:CHROMATOGRAPHY_TYPE           	Reversed phase
CH:INSTRUMENT_NAME               	Thermo Dionex Ultimate 3000
CH:COLUMN_NAME                   	Higgins endcapped C18 stainless steel (2.1mm x 50mm x 3µm)
CH:FLOW_GRADIENT                 	Flow rate is maintained at 0.4 mL/min until 1.5 min, increased to 0.5 mL/min at
CH:FLOW_GRADIENT                 	2 min and held for 3 min
CH:FLOW_RATE                     	0.4- 0.5mL/min
CH:COLUMN_TEMPERATURE            	60C
CH:INTERNAL_STANDARD             	[13C6]-D-glucose, [15N,13C5]- L-methionine, [13C5]-L-glutamic acid,
CH:INTERNAL_STANDARD             	[15N]-L-tyrosine, [3,3-13C2]-cystine, [trimethyl- 13C3]-caffeine, [U-13C5,
CH:INTERNAL_STANDARD             	U-15N2]-L-glutamine
CH:SAMPLE_INJECTION              	10 uL
CH:ANALYTICAL_TIME               	5 min
#ANALYSIS
AN:ANALYSIS_TYPE                 	MS
AN:LABORATORY_NAME               	Clinical Biomarkers Laboratory
AN:OPERATOR_NAME                 	Vilinh Tran
AN:ACQUISITION_DATE              	July 2017
AN:DATA_FORMAT                   	.RAW
#MS
MS:INSTRUMENT_NAME               	Thermo Q Exactive HF hybrid Orbitrap
MS:INSTRUMENT_TYPE               	Orbitrap
MS:MS_TYPE                       	ESI
MS:ION_MODE                      	NEGATIVE
MS:MS_COMMENTS                   	The high-resolution mass spectrometer was operated at 120,000 resolution and
MS:MS_COMMENTS                   	mass-to-charge ratio (m/z) range 85-1275. Probe temperature, capillary
MS:MS_COMMENTS                   	temperature, sweep gas and S-Lens RF levels were maintained at 200°C, 300°C, 1
MS:MS_COMMENTS                   	arbitrary units (AU), and 45, respectively. Additional source settings were
MS:MS_COMMENTS                   	optimized for sensitivity using a standard mixture, tune settings for sheath
MS:MS_COMMENTS                   	gas, auxiliary gas, sweep gas and spray voltage setting were 45 AU, 25 AU and
MS:MS_COMMENTS                   	3.5 kV, respectively. Maximum C-trap injection times were set at 100
MS:MS_COMMENTS                   	milliseconds and automatic gain control target 1 × 106. During untargeted data
MS:MS_COMMENTS                   	acquisition, no exclusion or inclusion masses were selected, and data was
MS:MS_COMMENTS                   	acquired in MS1 mode only. Raw data files were then extracted using apLCMS (Yu
MS:MS_COMMENTS                   	et al. 2009) at five different peak detection settings that have been separately
MS:MS_COMMENTS                   	optimized for detection of a wide range of peak intensities and abundances.
MS:MS_COMMENTS                   	Peaks detected during each injection were aligned using a mass tolerance of 5
MS:MS_COMMENTS                   	ppm (parts-per-million) and retention grouping was accomplished using
MS:MS_COMMENTS                   	non-parametric density estimation grouping, with a maximum retention time
MS:MS_COMMENTS                   	deviation of 30 seconds. The resulting feature tables were merged using
MS:MS_COMMENTS                   	xMSanalyzer, which identifies overlapping or unique features detected across the
MS:MS_COMMENTS                   	different peak detection parameters, and retains the peak with the lowest
MS:MS_COMMENTS                   	replicate CV and non-detects for inclusion in the final feature table (Uppal et
MS:MS_COMMENTS                   	al. 2013). All R-scripts for data extraction with apLCMS and data merging with
MS:MS_COMMENTS                   	xMSanalyzer are provided in the supplementary material. Uniquely detected ions
MS:MS_COMMENTS                   	consisted of m/z, retention time and ion abundance, referred to as m/z features.
MS:MS_COMMENTS                   	Prior to data analysis, triplicate m/z features averaged and filtered to remove
MS:MS_COMMENTS                   	those with triplicate coefficient of variation (CV) ≥ 100% and non-detected
MS:MS_COMMENTS                   	values greater than 10%.
MS:CAPILLARY_TEMPERATURE         	300C
MS:ION_SOURCE_TEMPERATURE        	200C
MS:ION_SPRAY_VOLTAGE             	3.5kV
MS:IONIZATION                    	NEgative
MS:MASS_ACCURACY                 	5ppm
MS:SOURCE_TEMPERATURE            	200C
MS:MS_RESULTS_FILE               	ST001407_AN002351_Results.txt	UNITS:Peak intensity	Has m/z:Yes	Has RT:Yes	RT units:Seconds
#END