Summary of Study ST001683
This data is available at the NIH Common Fund's National Metabolomics Data Repository (NMDR) website, the Metabolomics Workbench, https://www.metabolomicsworkbench.org, where it has been assigned Project ID PR001074. The data can be accessed directly via it's Project DOI: 10.21228/M8W11P This work is supported by NIH grant, U2C- DK119886.
See: https://www.metabolomicsworkbench.org/about/howtocite.php
This study contains a large results data set and is not available in the mwTab file. It is only available for download via FTP as data file(s) here.
Study ID | ST001683 |
Study Title | A gut microbe-focused metabolomics pipeline enables mechanistic interrogation of microbiome metabolism. |
Study Summary | Gut microbes modulate host phenotypes and are associated with numerous health effects in humans, ranging from cancer immunotherapy response to metabolic disease and obesity. However, difficulty in accurate and high-throughput functional analysis of human gut microbes has hindered defining mechanistic connections between individual microbial strains and host phenotypes. One key way the gut microbiome influences host physiology is through the production of small molecules hindered by limited tools calibrated to detect products of anaerobic biochemistry in the gut. Here we construct a microbiome-focused, integrated mass-spectrometry pipeline to accelerate the identification of microbiota-dependent metabolites (MDMs) in diverse sample types. We report the metabolic profiles of 178 gut microbe strains using our library of 833 metabolites. Leveraging this metabolomics resource we establish deviations in the relationships between phylogeny and metabolism, use machine learning to discover novel metabolism in Bacteroides, and employ comparative genomics-based discovery of candidate biochemical pathways. MDMs can be detected in diverse body fluids in gnotobiotic and conventional mice and traced back to corresponding metabolomic profiles of cultured bacteria. Collectively, our microbiome-focused metabolomics pipeline and interactive metabolomics profile explorer are a powerful tool for characterizing microbe and microbe-host interactions. |
Institute | Stanford University |
Department | Microbiology & Immunology |
Laboratory | Justin Sonnenburg |
Last Name | Han |
First Name | Shuo |
Address | 299 Campus Drive, Stanford, CA, 94305-5124, USA |
shuohan@stanford.edu | |
Phone | - |
Submit Date | 2021-02-06 |
Publications | not published, status to be updated |
Raw Data Available | Yes |
Raw Data File Type(s) | mzML |
Analysis Type Detail | LC-MS |
Release Date | 2021-05-17 |
Release Version | 1 |
Select appropriate tab below to view additional metadata details:
Project:
Project ID: | PR001074 |
Project DOI: | doi: 10.21228/M8W11P |
Project Title: | A gut microbe-focused metabolomics pipeline enables mechanistic interrogation of microbiome metabolism |
Project Summary: | Gut microbes modulate host phenotypes and are associated with numerous health effects in humans, ranging from cancer immunotherapy response to metabolic disease and obesity. However, difficulty in accurate and high-throughput functional analysis of human gut microbes has hindered defining mechanistic connections between individual microbial strains and host phenotypes. One key way the gut microbiome influences host physiology is through the production of small molecules1–3, yet progress in elucidating this chemical interplay has been hindered by limited tools calibrated to detect products of anaerobic biochemistry in the gut. Here we construct a microbiome-focused, integrated mass-spectrometry pipeline to accelerate the identification of microbiota-dependent metabolites (MDMs) in diverse sample types. We report the metabolic profiles of 178 gut microbe strains using our library of 833 metabolites. Leveraging this metabolomics resource we establish deviations in the relationships between phylogeny and metabolism, use machine learning to discover novel metabolism in Bacteroides, and employ comparative genomics-based discovery of candidate biochemical pathways. MDMs can be detected in diverse body fluids in gnotobiotic and conventional mice and traced back to corresponding metabolomic profiles of cultured bacteria. Collectively, our microbiome-focused metabolomics pipeline and interactive metabolomics profile explorer are a powerful tool for characterizing microbe and microbe-host interactions. |
Institute: | Stanford University |
Department: | Microbiology and Immunology |
Laboratory: | Justin Sonnenburg |
Last Name: | Van Treuren |
First Name: | Will |
Address: | Sherman Fairchild Building, 299 Campus Drive, Stanford CA, 94305 |
Email: | wdwvt@stanford.edu |
Phone: | 7209370980 |
Contributors: | Shuo Han1,*, Will Van Treuren1,2,*, Curt R. Fischer3, 4, Bryan D. Merrill1,2, Leah Guthrie1, Brian C. DeFelice4, Lalla A. Fall3,5, Dylan Dodd1,5,^, Michael A. Fischbach4,6,^, and Justin L. Sonnenburg1,4,7,^. |
Subject:
Subject ID: | SU001760 |
Subject Type: | Mammal |
Subject Species: | Mus musculus |
Taxonomy ID: | 10090 |
Genotype Strain: | Swiss Webster |
Age Or Age Range: | 10-14 weeks |
Gender: | Male |
Species Group: | Mammals |
Factors:
Subject type: Mammal; Subject species: Mus musculus (Factor headings shown in green)
mb_sample_id | local_sample_id | Experiment | Sample_type | Colonization |
---|---|---|---|---|
SA155124 | s0194 | community | caecal | Bt_Ca_Er_Pd_Et |
SA155125 | s0177 | community | caecal | Bt_Ca_Er_Pd_Et |
SA155126 | s0195 | community | caecal | Bt_Ca_Er_Pd_Et |
SA155127 | s0187 | community | caecal | Bt_Ca_Er_Pd_Et |
SA155128 | s0185 | community | caecal | Bt_Ca_Er_Pd_Et |
SA155129 | s0176 | community | caecal | Bt_Ca_Er_Pd_Et |
SA155130 | s0178 | community | caecal | Bt_Ca_Er_Pd_Et |
SA155131 | s0196 | community | caecal | Bt_Ca_Er_Pd_Et |
SA155132 | s0186 | community | caecal | Bt_Ca_Er_Pd_Et |
SA155133 | s0201 | community | caecal | Cs_Bt_Ca_Er_Pd_Et |
SA155134 | s0219 | community | caecal | Cs_Bt_Ca_Er_Pd_Et |
SA155135 | s0220 | community | caecal | Cs_Bt_Ca_Er_Pd_Et |
SA155136 | s0218 | community | caecal | Cs_Bt_Ca_Er_Pd_Et |
SA155137 | s0213 | community | caecal | Cs_Bt_Ca_Er_Pd_Et |
SA155138 | s0202 | community | caecal | Cs_Bt_Ca_Er_Pd_Et |
SA155139 | s0212 | community | caecal | Cs_Bt_Ca_Er_Pd_Et |
SA155140 | s0200 | community | caecal | Cs_Bt_Ca_Er_Pd_Et |
SA155141 | s0214 | community | caecal | Cs_Bt_Ca_Er_Pd_Et |
SA155142 | s0162 | community | caecal | germ-free |
SA155143 | s0161 | community | caecal | germ-free |
SA155144 | s0172 | community | caecal | germ-free |
SA155145 | s0163 | community | caecal | germ-free |
SA155146 | s0167 | community | caecal | germ-free |
SA155147 | s0171 | community | caecal | germ-free |
SA155148 | s0170 | community | caecal | germ-free |
SA155149 | s0169 | community | caecal | germ-free |
SA155150 | s0168 | community | caecal | germ-free |
SA155151 | s0054 | community | feces | Bt_Ca_Er_Pd_Et |
SA155152 | s0070 | community | feces | Bt_Ca_Er_Pd_Et |
SA155153 | s0092 | community | feces | Cs_Bt_Ca_Er_Pd_Et |
SA155154 | s0100 | community | feces | Cs_Bt_Ca_Er_Pd_Et |
SA155155 | s0082 | community | feces | Cs_Bt_Ca_Er_Pd_Et |
SA155156 | s0022 | community | feces | germ-free |
SA155157 | s0029 | community | feces | germ-free |
SA155158 | s0034 | community | feces | germ-free |
SA155159 | s0363 | community | serum | Bt_Ca_Er_Pd_Et |
SA155160 | s0368 | community | serum | Bt_Ca_Er_Pd_Et |
SA155161 | s0362 | community | serum | Bt_Ca_Er_Pd_Et |
SA155162 | s0359 | community | serum | Bt_Ca_Er_Pd_Et |
SA155163 | s0355 | community | serum | Bt_Ca_Er_Pd_Et |
SA155164 | s0374 | community | serum | Bt_Ca_Er_Pd_Et |
SA155165 | s0367 | community | serum | Bt_Ca_Er_Pd_Et |
SA155166 | s0366 | community | serum | Bt_Ca_Er_Pd_Et |
SA155167 | s0360 | community | serum | Cs_Bt_Ca_Er_Pd_Et |
SA155168 | s0357 | community | serum | Cs_Bt_Ca_Er_Pd_Et |
SA155169 | s0361 | community | serum | Cs_Bt_Ca_Er_Pd_Et |
SA155170 | s0356 | community | serum | Cs_Bt_Ca_Er_Pd_Et |
SA155171 | s0373 | community | serum | Cs_Bt_Ca_Er_Pd_Et |
SA155172 | s0369 | community | serum | Cs_Bt_Ca_Er_Pd_Et |
SA155173 | s0372 | community | serum | Cs_Bt_Ca_Er_Pd_Et |
SA155174 | s0365 | community | serum | germ-free |
SA155175 | s0364 | community | serum | germ-free |
SA155176 | s0358 | community | serum | germ-free |
SA155177 | s0371 | community | serum | germ-free |
SA155178 | s0370 | community | serum | germ-free |
SA155179 | s0286 | community | urine | Bt_Ca_Er_Pd_Et |
SA155180 | s0281 | community | urine | Bt_Ca_Er_Pd_Et |
SA155181 | s0290 | community | urine | Bt_Ca_Er_Pd_Et |
SA155182 | s0295 | community | urine | Bt_Ca_Er_Pd_Et |
SA155183 | s0309 | community | urine | Bt_Ca_Er_Pd_Et |
SA155184 | s0304 | community | urine | Bt_Ca_Er_Pd_Et |
SA155185 | s0314 | community | urine | Bt_Ca_Er_Pd_Et |
SA155186 | s0245 | community | urine | Cs_Bt_Ca_Er_Pd_Et |
SA155187 | s0250 | community | urine | Cs_Bt_Ca_Er_Pd_Et |
SA155188 | s0254 | community | urine | Cs_Bt_Ca_Er_Pd_Et |
SA155189 | s0259 | community | urine | Cs_Bt_Ca_Er_Pd_Et |
SA155190 | s0277 | community | urine | Cs_Bt_Ca_Er_Pd_Et |
SA155191 | s0272 | community | urine | Cs_Bt_Ca_Er_Pd_Et |
SA155192 | s0227 | community | urine | germ-free |
SA155193 | s0231 | community | urine | germ-free |
SA155194 | s0236 | community | urine | germ-free |
SA155195 | s1073 | conventional | caecal | conventional |
SA155196 | s1072 | conventional | caecal | conventional |
SA155197 | s1074 | conventional | caecal | conventional |
SA155198 | s1065 | conventional | caecal | germ-free |
SA155199 | s1067 | conventional | caecal | germ-free |
SA155200 | s1066 | conventional | caecal | germ-free |
SA155201 | s1064 | conventional | caecal | germ-free |
SA155202 | s1077 | conventional | feces | conventional |
SA155203 | s1076 | conventional | feces | conventional |
SA155204 | s1075 | conventional | feces | conventional |
SA155205 | s1069 | conventional | feces | germ-free |
SA155206 | s1068 | conventional | feces | germ-free |
SA155207 | s1070 | conventional | feces | germ-free |
SA155208 | s1071 | conventional | feces | germ-free |
SA155209 | s1061 | conventional | serum | conventional |
SA155210 | s1062 | conventional | serum | conventional |
SA155211 | s1063 | conventional | serum | conventional |
SA155212 | s1060 | conventional | serum | germ-free |
SA155213 | s1058 | conventional | serum | germ-free |
SA155214 | s1057 | conventional | serum | germ-free |
SA155215 | s1059 | conventional | serum | germ-free |
SA155216 | s1055 | conventional | urine | conventional |
SA155217 | s1054 | conventional | urine | conventional |
SA155218 | s1056 | conventional | urine | conventional |
SA155219 | s1050 | conventional | urine | germ-free |
SA155220 | s1051 | conventional | urine | germ-free |
SA155221 | s1052 | conventional | urine | germ-free |
SA155222 | s1053 | conventional | urine | germ-free |
SA155223 | s1100 | mono-colonization_2 | caecal | As |
Collection:
Collection ID: | CO001753 |
Collection Summary: | For all experiments, mice were euthanized by CO2 asphyxiation nine days (mono-colonization with Citrobacter portucalensis BEI HM-34 or Anaerostipes sp. BEI HM-220) or four weeks (all other experiments) following colonization, and four sample types (serum, urine, feces, and cecal contents) were harvested from each mouse. Prior to euthanization, urine and feces were collected. Whole blood was collected by cardiac puncture and serum was obtained using microcontainer serum separator tubes from Becton Dickinson following manufacturer’s instructions. The intact cecum was harvested and snap-frozen in liquid nitrogen. A single cecal sample was harvested for mono-association and conventional experiments, and three samples at three different sections of the cecum were harvested for the defined-community experiment. All mouse experiments were conducted under a protocol approved by the Stanford University Institutional Animal Care and Use Committee. |
Sample Type: | Feces;Urine;Serum;Cecal contents |
Treatment:
Treatment ID: | TR001773 |
Treatment Summary: | Mouse experiments were performed on gnotobiotic Swiss Webster germ-free mice (males, 10-14 weeks of age, n = 3-8 per group for all experiments) maintained in aseptic isolators, and originally obtained from Taconic Bioscience. For mono-association experiments, mice were colonized with Bacteroides thetaiotaomicron VPI 5482, Clostridium sporogenes ATCC 15579, Citrobacter portucalensis BEI HM-34, or Anaerostipes sp. BEI HM-220904a, by oral gavage (200 uL, ~1 x 107 CFU) and were maintained on a standard chow (LabDiet 5K67). For the defined-community experiment, mice with a six-member community were colonized with a 200 uL mixture consisting of equal volumes from saturated cultures of Bacteroides thetaiotaomicron VPI 5482 (8.7 x 109 CFU), Clostridium sporogenes ATCC 15579 (1.4 x 108 CFU), Edwardsiella tarda ATCC 23685 (3.6 x 1010 CFU), Collinsella aerofaciens ATCC 25986 (1.4 x 109), Eubacterium rectale ATCC 33656 (6.9 x 106 CFU), and Parabacteroides distasonis ATCC 8503 (1.5 x 109 CFU). Mice with a five-member community were colonized with all cultures mixed at the same volumes as described above except for Clostridium sporogenes ATCC 15579, which was not included. Successful colonization and stable community members were determined by 16S amplicon sequencing of the V4 (515f, 806r) region of microbial populations present in the feces and cecal contents from individual mice. |
Sample Preparation:
Sampleprep ID: | SP001766 |
Sampleprep Summary: | All samples were stored at -80oC until use, and were thawed on ice immediately before extraction. 200 µL of serum and bacterial supernatant samples were used for extraction directly without dilution. Urine samples were diluted 1:20 in LC-MS grade water (Fisher) to reach a final volume of 200 µL prior to extraction. Protein precipitation for bacterial, serum, and urine samples was conducted by adding 1 mL of extraction buffer (see composition below) in 100% methanol (LC-MS grade, Fisher) to 200 µL of each sample in a 2 mL 96-well microplate (Fisher), sealed with a silicone mat (Agilent), and vortexed to mix. For feces and cecal contents, ~ 20 mg of feces or cecal contents were added to ~ 20 mg of acid-washed glass beads (150-212 µm, Sigma) in a 2 mL autoclaved screw top vial. In the same vial, 600 µL of water (LC-MS grade, Fisher) and 600 µL of recovery buffer in 100% methanol (see composition below) were added. Fecal and cecal slurries were homogenized at 4oC using a Mini Beadbeater operating at 3,500 oscillations per minute for 5 minutes. For all sample types, samples were subsequently incubated at room temperature for 5 minutes, followed by centrifugation at 5,000 x g for 10 minutes. Two 440 µL aliquots of the same supernatant were transferred to two separate 2 mL plates and dried under air in a Biotage TurboVap. One of these dried plates was sealed and archived at -80oC. The dried extracts were reconstituted in 200 µL reconstitution buffer (see composition below) in 50% methanol in water (v/v, LC-MS grade, Fisher) by vortexing at max speed for 5 seconds. Reconstituted sample extracts were centrifuged at 2,000 x g for 1 minute, and filtered through a 96-well Durapore PVDF 0.22-µm filter plate (Millipore) into in a 1 mL 96-well plate (Agilent) by centrifugation at 2,000 x g for 10 minutes. Plates were then sealed with 96-well cap mats (Agilent) and stored at -80oC until LC-MS analysis. QC samples were generated by pooling 4 µL from each well of the experiment into a single designated well on the same plate for LC-MS analysis. The extraction buffer consisted of 4-Chloro-phenylalanine (6.8 µM, Carbosynth), Tridecanoic acid (6.8 µM, Sigma), and 2-Flurophenylglycine (3.4 µM, SCBT) in 100% methanol. The reconstitution buffer included the internal standards: Phenylalanine-2,3,4,5,6-d5 (12.5 µM, CIL), Glucose-1,2,3,4,5,6,6-d7 (25 µM, CIL), Methionine-methyl-d3 (12.5 µM, CIL), 4-Hydroxyphenyl-d4-alanine (3.125 µM, CDN), Tryptophan-2,4,5,6,7-d5 (12.5 µM, CDN), Leucine-5,5,5-d3 (12.5 µM, CDN), N-Benzoyl-d5-glycine (6.25 µM, CDN), 4-Bromo-phenylalanine (12.5 µM, Sigma), Progesterone-d9 (3.125 µM, CIL), Di-N-octyl phthalate-3,4,5,6-d4 (12.5 µM, CDN), d19-Decanoic acid (12.5 µM, CDN), d15-Octanoic acid (25 µM, CDN), Indole-2,4,5,6,7-d5-3-acetic acid (12.5 µM, CDN), Carnitine-trimethyl-d9 (3.125 µM, CDN), and d27-Tetradecanoic acid (12.5 µM, CDN), in 50% methanol in water. The final concentration for each internal standard in these buffers was determined by choosing a concentration falling within its linear dynamic range as measured by each analytical method. |
Combined analysis:
Analysis ID | AN002747 | AN002748 | AN002749 |
---|---|---|---|
Analysis type | MS | MS | MS |
Chromatography type | Reversed phase | Reversed phase | HILIC |
Chromatography system | Agilent qTOF 6545 | Agilent qTOF 6545 | Agilent qTOF 6545 |
Column | Waters Acquity BEH (100 x 2.1mm,1.7um) | Waters Acquity BEH (100 x 2.1mm,1.7um) | Waters Acquity BEH Amide (150 x 2.1mm,1.7um) |
MS Type | ESI | ESI | ESI |
MS instrument type | QTOF | QTOF | QTOF |
MS instrument name | Agilent qTOF 6545 | Agilent qTOF 6545 | Agilent qTOF 6545 |
Ion Mode | POSITIVE | NEGATIVE | POSITIVE |
Units | Raw ion count (peak area) | Raw ion count (peak area) | Raw ion count (peak area) |
Chromatography:
Chromatography ID: | CH002029 |
Chromatography Summary: | Published C18 reveres phase methods were implemented with minor modifications. The C18 positive method (ESI+) used mobile phase solvents (LC-MS grade) consisting of 0.1% formic acid (Fisher) in water (A) and 0.1% formic acid in methanol (B). The gradient profile was from 0.5% B to 70% B in 4 minutes, from 70% B to 98% B in 0.5 minutes, and holding at 98% B for 0.9 minute before returning to 0.5% B in 0.2 minutes. The flow rate was 350 µL per minute. The sample injection volume was 5 µL. LC separations were made at 40oC on separate columns fitted with a Vanguard pre-column of the same composition: Waters Acquity BEH 1.7 µm particle size, 2.1 mm id x 100 mm length (C18). Data were collected at a mass range of 70-1000 m/z at an acquisition rate of 2 spectra per second. Specific ion source parameters included Fragmentor (140V), Gas Temp (250oC), Sheath Gas Temp (200oC), and VCap (4000V). |
Instrument Name: | Agilent qTOF 6545 |
Column Name: | Waters Acquity BEH (100 x 2.1mm,1.7um) |
Column Temperature: | 40 |
Flow Gradient: | 0.5% B to 70% B in 4 minutes, from 70% B to 98% B in 0.5 minutes, and holding at 98% B for 0.9 minute before returning to 0.5% B in 0.2 minutes. |
Flow Rate: | 350 µL/min |
Solvent A: | 100% water; 0.1% formic acid |
Solvent B: | 100% methanol; 0.1% formic acid |
Chromatography Type: | Reversed phase |
Chromatography ID: | CH002030 |
Chromatography Summary: | Published C18 reverse phase methods were implemented with minor modifications. The C18 negative method (ESI-) used mobile phase solvents (LC-MS grade) consisting of 6.5 mM ammonium bicarbonate (Sigma) in water at pH 8 (A) and 6.5 mM ammonium bicarbonate in 95:5 v/v methanol:water (B). The gradient profile was from 0.5% B to 70% B in 4 minutes, from 70% B to 98% B in 0.5 minutes, and holding at 98% B for 0.9 minute before returning to 0.5% B in 0.2 minutes. The flow rate was 350 µL per minute. The sample injection volume was 5 µL. LC separations were made at 40oC on separate columns fitted with a Vanguard pre-column of the same composition: Waters Acquity BEH 1.7 µm particle size, 2.1 mm id x 100 mm length. Data were collected at a mass range of 70-1000 m/z at an acquisition rate of 2 spectra per second. Specific ion source parameters included Fragmentor (140V), Gas Temp (250oC), Sheath Gas Temp (200oC), and VCap (4000V). |
Instrument Name: | Agilent qTOF 6545 |
Column Name: | Waters Acquity BEH (100 x 2.1mm,1.7um) |
Column Temperature: | 40 |
Flow Gradient: | 0.5% B to 70% B in 4 minutes, from 70% B to 98% B in 0.5 minutes, and holding at 98% B for 0.9 minute before returning to 0.5% B in 0.2 minutes. |
Flow Rate: | 350 µL/min |
Solvent A: | 100% water; 0.1% formic acid |
Solvent B: | 100% methanol; 0.1% formic acid |
Chromatography Type: | Reversed phase |
Chromatography ID: | CH002031 |
Chromatography Summary: | Published HILIC method was implemented with minor modifications. The HILIC (Hydrophilic Interaction Liquid Chromatography) positive method (ESI+) used mobile phase solvents (LC-MS grade) consisting of 0.125% formic acid and 10 mM ammonium formate (Sigma) in water at pH 3 (A) and 0.125% formic acid in 10 mM ammonium formate in 95:5 v/v acetonitrile:water (B). The gradient profile was held at 100% B for 2 minutes, from 100% B to 70% B in 5 minutes, holding at 70% B for 0.7 minute, from 70% B to 40% B for 1.3 minutes, holding at 40% B for 0.5 minutes, from 40% B to 30% B for 0.75 minutes, before returning to 100% B for 2.5 minutes and holding at 100% B for 4 minutes. The flow rate was 400 µL per minute. The sample injection volume was 3 µL. LC separations were made at 40oC on separate columns fitted with a Vanguard pre-column of the same composition dedicated to each analytical method: Waters Acquity BEH Amide 1.7 µm particle size, 2.1 mm id x 150 mm length. Data were collected at a mass range of 70-1000 m/z at an acquisition rate of 2 spectra per second. Specific ion source parameters included Fragmentor (140V), Gas Temp (250oC), Sheath Gas Temp (200oC), and VCap (4000V). |
Instrument Name: | Agilent qTOF 6545 |
Column Name: | Waters Acquity BEH Amide (150 x 2.1mm,1.7um) |
Column Temperature: | 40 |
Flow Gradient: | The gradient profile was held at 100% B for 2 minutes, from 100% B to 70% B in 5 minutes, holding at 70% B for 0.7 minute, from 70% B to 40% B for 1.3 minutes, holding at 40% B for 0.5 minutes, from 40% B to 30% B for 0.75 minutes, before returning to 100% B for 2.5 minutes and holding at 100% B for 4 minutes. |
Flow Rate: | 400 µL/min |
Solvent A: | 100% water; 0.125% formic acid; 10 mM ammonium formate, pH 3 |
Solvent B: | 95% acetonitrile/5% water; 0.125% formic acid; 10 mM ammonium formate |
Chromatography Type: | HILIC |
MS:
MS ID: | MS002544 |
Analysis ID: | AN002747 |
Instrument Name: | Agilent qTOF 6545 |
Instrument Type: | QTOF |
MS Type: | ESI |
MS Comments: | The MS-DIAL software (v. 3.83) was used for analyzing all in vitro and in vivo data on a per-experimental run and per-analytical method basis. QC samples from each experimental run were used for peak alignment. Chemical assignment of molecular features in samples was performed by comparison of recorded RT and m/z information to our reference library constructed from authentic standards. Tolerance windows were set to 0.1 minute RT and 0.01 Da m/z for the C18 methods and 0.2 minute RT and 0.01 Da m/z for the HILIC method. The minimal peak count (height) filter was set to 3000 for all experiments except for select experiments in which the MS exhibited reduced sensitivity. For experiments where detection of internal standards goes beyond the 0.1 (C18 methods) or 0.2 (HILIC method) window, RT correction of the mz-RT reference library was conducted prior to feature annotation in MS-DIAL. The MS-DIAL analysis generated a list of m/z, RT, and ion counts (area under the curve) for high-confidence annotations (matched to the reference library) as well as unknown molecular features. Based on the list of annotations for each experiment, each set of aligned peaks was manually checked using the MS-DIAL graphical user interface. Select metabolite features were removed from this list when: 1) two adjacent but distinct peaks were concurrently assigned to a single molecular feature, 2) odd curvature/shape of the peak led to integration of several “peaks” from separate sections of the same peak, or 3) features were only detected in blank controls. Annotated peaks that passed this inspection were reported in the final output file. After MS-DIAL analysis, data were analyzed with a set of custom bioinformatics pipelines. In short, these pipelines implemented a set of filtration and normalization procedures with the goal of reducing technical variability and controlling for batch effects. |
Ion Mode: | POSITIVE |
MS ID: | MS002545 |
Analysis ID: | AN002748 |
Instrument Name: | Agilent qTOF 6545 |
Instrument Type: | QTOF |
MS Type: | ESI |
MS Comments: | The MS-DIAL software (v. 3.83) was used for analyzing all in vitro and in vivo data on a per-experimental run and per-analytical method basis. QC samples from each experimental run were used for peak alignment. Chemical assignment of molecular features in samples was performed by comparison of recorded RT and m/z information to our reference library constructed from authentic standards. Tolerance windows were set to 0.1 minute RT and 0.01 Da m/z for the C18 methods and 0.2 minute RT and 0.01 Da m/z for the HILIC method. The minimal peak count (height) filter was set to 3000 for all experiments except for select experiments in which the MS exhibited reduced sensitivity. For experiments where detection of internal standards goes beyond the 0.1 (C18 methods) or 0.2 (HILIC method) window, RT correction of the mz-RT reference library was conducted prior to feature annotation in MS-DIAL. The MS-DIAL analysis generated a list of m/z, RT, and ion counts (area under the curve) for high-confidence annotations (matched to the reference library) as well as unknown molecular features. Based on the list of annotations for each experiment, each set of aligned peaks was manually checked using the MS-DIAL graphical user interface. Select metabolite features were removed from this list when: 1) two adjacent but distinct peaks were concurrently assigned to a single molecular feature, 2) odd curvature/shape of the peak led to integration of several “peaks” from separate sections of the same peak, or 3) features were only detected in blank controls. Annotated peaks that passed this inspection were reported in the final output file. After MS-DIAL analysis, data were analyzed with a set of custom bioinformatics pipelines. In short, these pipelines implemented a set of filtration and normalization procedures with the goal of reducing technical variability and controlling for batch effects. |
Ion Mode: | NEGATIVE |
MS ID: | MS002546 |
Analysis ID: | AN002749 |
Instrument Name: | Agilent qTOF 6545 |
Instrument Type: | QTOF |
MS Type: | ESI |
MS Comments: | The MS-DIAL software (v. 3.83) was used for analyzing all in vitro and in vivo data on a per-experimental run and per-analytical method basis. QC samples from each experimental run were used for peak alignment. Chemical assignment of molecular features in samples was performed by comparison of recorded RT and m/z information to our reference library constructed from authentic standards. Tolerance windows were set to 0.1 minute RT and 0.01 Da m/z for the C18 methods and 0.2 minute RT and 0.01 Da m/z for the HILIC method. The minimal peak count (height) filter was set to 3000 for all experiments except for select experiments in which the MS exhibited reduced sensitivity. For experiments where detection of internal standards goes beyond the 0.1 (C18 methods) or 0.2 (HILIC method) window, RT correction of the mz-RT reference library was conducted prior to feature annotation in MS-DIAL. The MS-DIAL analysis generated a list of m/z, RT, and ion counts (area under the curve) for high-confidence annotations (matched to the reference library) as well as unknown molecular features. Based on the list of annotations for each experiment, each set of aligned peaks was manually checked using the MS-DIAL graphical user interface. Select metabolite features were removed from this list when: 1) two adjacent but distinct peaks were concurrently assigned to a single molecular feature, 2) odd curvature/shape of the peak led to integration of several “peaks” from separate sections of the same peak, or 3) features were only detected in blank controls. Annotated peaks that passed this inspection were reported in the final output file. After MS-DIAL analysis, data were analyzed with a set of custom bioinformatics pipelines. In short, these pipelines implemented a set of filtration and normalization procedures with the goal of reducing technical variability and controlling for batch effects. |
Ion Mode: | POSITIVE |