Summary of Study ST001415
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 PR000971. The data can be accessed directly via it's Project DOI: 10.21228/M85X14 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 | ST001415 |
| Study Title | Multi-omic profiling of primary mouse neutrophils reveals a pattern of sex and age-related functional regulation |
| Study Summary | Neutrophils are the most abundant white blood cells in humans and constitute one of the first lines of defense in the innate immune response. Neutrophils are extremely short-lived cells, which survive less than a day after reaching terminal differentiation. Thus, little is known about how organismal aging, rather than the daily cellular aging process, may impact neutrophil biology. In addition, accumulating evidence suggests that both immunity and organismal aging are extremely sex-dimorphic. Here, we describe a multi-omic resource of mouse primary bone marrow neutrophils from young and old female and male animals, at the transcriptomic, metabolomic and lipidomic levels. Importantly, we identify widespread age-related and sex-dimorphic regulation of ‘omics’ in neutrophils, specifically regulation of chromatin metabolism. We leverage machine-learning and identify candidate molecular drivers of age-related and sex-dimorphic transcriptional regulation of neutrophils. We leverage our resource to predict increased levels/release of neutrophil elastase in male mice. To date, this dataset represents the largest multi-omic resource for the study of neutrophils across biological sex and ages. This resource identifies molecular states linked to neutrophil characteristics linked to organismal age or sex, which could be leveraged to improve immune responses across individuals. |
| Institute | Stanford University |
| Last Name | Contrepois |
| First Name | Kevin |
| Address | 300 Pasteur Dr |
| kcontrep@stanford.edu | |
| Phone | 6506664538 |
| Submit Date | 2020-06-30 |
| Raw Data Available | Yes |
| Raw Data File Type(s) | raw(Thermo) |
| Analysis Type Detail | LC-MS |
| Release Date | 2021-06-30 |
| Release Version | 1 |
Select appropriate tab below to view additional metadata details:
Project:
| Project ID: | PR000971 |
| Project DOI: | doi: 10.21228/M85X14 |
| Project Title: | Untargeted metabolomics of primary mouse neutrophils |
| Project Summary: | Untargeted metabolomics of primary neutrophils from young and old, male and female mice |
| Institute: | Stanford University |
| Department: | Genetics |
| Last Name: | Contrepois |
| First Name: | Kevin |
| Address: | 300 Pasteur Dr, ALWAY bldg M302, STANFORD, California, 94305, USA |
| Email: | kcontrep@stanford.edu |
| Phone: | 6507239914 |
Subject:
| Subject ID: | SU001489 |
| Subject Type: | Mammal |
| Subject Species: | Mus musculus |
| Taxonomy ID: | 10090 |
| Genotype Strain: | C57BL/6J |
| Age Or Age Range: | 4 months & 20 months |
| Gender: | Male and female |
| Animal Animal Supplier: | Jackson Laboratories |
| Animal Housing: | SPF animal facility at USC |
Factors:
Subject type: Mammal; Subject species: Mus musculus (Factor headings shown in green)
| mb_sample_id | local_sample_id | Sex | Age |
|---|---|---|---|
| SA116246 | F_20m_4a | Female | Old |
| SA116247 | F_20m_4b | Female | Old |
| SA116248 | F_20m_3a | Female | Old |
| SA116249 | F_20m_3b | Female | Old |
| SA116250 | F_4m_2b | Female | Young |
| SA116251 | F_4m_1a | Female | Young |
| SA116252 | F_4m_1b | Female | Young |
| SA116253 | F_4m_2a | Female | Young |
| SA116254 | M_20m_4b | Male | Old |
| SA116255 | M_20m_3b | Male | Old |
| SA116256 | M_20m_3a | Male | Old |
| SA116257 | M_20m_4a | Male | Old |
| SA116258 | M_4m_1a | Male | Young |
| SA116259 | M_4m_2a | Male | Young |
| SA116260 | M_4m_2b | Male | Young |
| SA116261 | M_4m_1b | Male | Young |
| Showing results 1 to 16 of 16 |
Collection:
| Collection ID: | CO001484 |
| Collection Summary: | The hindlimb bones of each mouse were harvested and kept on ice in D-PBS (Corning) supplemented with 1% Penicillin/Streptomycin (Corning) until further processing. Muscle tissue was removed from the bones, and the bone marrow from cleaned bones was collected into clean tubes (Amend et al., 2016). Red blood cells from the marrow were removed using Red Blood Cell Lysis (Miltenyi Biotech #130-094-183), according to the manufacturer’s instructions, albeit with no vortexing step to avoid unscheduled neutrophil activation. Neutrophils were isolated from other bone marrow cells using magnetic-assisted cell sorting (Miltenyi Biotech kit #130-097-658). Viability and yield were assessed using trypan blue exclusion and an automated COUNTESS cell counter (Thermo-Fisher Scientific). Purified cells were pelleted at 300g and snap-frozen in liquid nitrogen until processing for RNA, lipid or metabolite isolation. |
| Sample Type: | Bone marrow |
Treatment:
| Treatment ID: | TR001504 |
| Treatment Summary: | There was no treatment. |
Sample Preparation:
| Sampleprep ID: | SP001497 |
| Sampleprep Summary: | Metabolites and lipids were extracted from neutrophil cell pellets and analyzed in a randomized order. Extraction was performed using a biphasic separation protocol with ice-cold methanol, methyl tert-butyl ether (MTBE) and water (Contrepois et al., 2018). Briefly, 300μL of methanol spiked-in with 54 deuterated internal standards provided with the Lipidyzer platform (SCIEX, cat #5040156, LPISTDKIT-101) was added to the cell pellet, samples were vigorously vortexed for 20 seconds and sonicated in a water bath 3 times for 30 seconds on ice. Lipids were solubilized by adding 1000μL of MTBE and incubated under agitation for 1h at 4°C. After addition of 250μL of ice-cold water, the samples were vortexed for 1 min and centrifuged at 14,000g for 5 min at 20°C. The upper phase containing the lipids was then collected and dried down under nitrogen. The dry lipid extracts were reconstituted with 300μL of 10 mM ammonium acetate in 9:1 methanol:toluene for analaysis. The lower phase containing metabolites was subjected to further protein precipitation by adding 4 times of ice-cold 1:1:1 isopropanol:acetonitrile:water spiked in with 17 labeled internal standards and incubating for 2 hours at -20°C. The supernatant was dried down to completion under nitrogen and re-suspended in 100μL of 1:1 MeOH:Water for analysis. |
Combined analysis:
| Analysis ID | AN002365 | AN002366 | AN002367 | AN002368 |
|---|---|---|---|---|
| Analysis type | MS | MS | MS | MS |
| Chromatography type | HILIC | HILIC | Reversed phase | Reversed phase |
| Chromatography system | Thermo Dionex Ultimate 3000 RS | Thermo Dionex Ultimate 3000 RS | Thermo Dionex Ultimate 3000 RS | Thermo Dionex Ultimate 3000 RS |
| Column | SeQuant ZIC-HILIC (100 x 2.1mm,3.5um) | SeQuant ZIC-HILIC (100 x 2.1mm,3.5um) | Agilent Zorbax SBaq (50 x 2.1mm,1.7um) | Agilent Zorbax SBaq (50 x 2.1mm,1.7um) |
| MS Type | ESI | ESI | ESI | ESI |
| MS instrument type | Orbitrap | Orbitrap | Orbitrap | Orbitrap |
| MS instrument name | Thermo Q Exactive Plus Orbitrap | Thermo Q Exactive Plus Orbitrap | Thermo Q Exactive Plus Orbitrap | Thermo Q Exactive Plus Orbitrap |
| Ion Mode | POSITIVE | NEGATIVE | POSITIVE | NEGATIVE |
| Units | MS count | MS count | MS count | MS count |
Chromatography:
| Chromatography ID: | CH001735 |
| Chromatography Summary: | HILIC experiments were performed using a ZIC-HILIC column 2.1x100 mm, 3.5μm, 200Å (Merck Millipore) and mobile phase solvents consisting of 10mM ammonium acetate in 50/50 acetonitrile/water (A) and 10 mM ammonium acetate in 95/5 acetonitrile/water (B).(Contrepois et al., 2015) |
| Instrument Name: | Thermo Dionex Ultimate 3000 RS |
| Column Name: | SeQuant ZIC-HILIC (100 x 2.1mm,3.5um) |
| Column Temperature: | 40 |
| Flow Rate: | 0.5 ml/min |
| Solvent A: | 95% acetonitrile/5% water; 10 mM ammonium acetate |
| Solvent B: | 95% acetonitrile/5% water; 10 mM ammonium acetate |
| Chromatography Type: | HILIC |
| Chromatography ID: | CH001736 |
| Chromatography Summary: | RPLC experiments were performed using a Zorbax SBaq column 2.1 x 50 mm, 1.7 μm, 100Å (Agilent Technologies) and mobile phase solvents consisting of 0.06% acetic acid in water (A) and 0.06% acetic acid in methanol (B). (Contrepois et al., 2015) |
| Instrument Name: | Thermo Dionex Ultimate 3000 RS |
| Column Name: | Agilent Zorbax SBaq (50 x 2.1mm,1.7um) |
| Column Temperature: | 60 |
| Flow Rate: | 0.6 ml/min |
| Solvent A: | 100% water; 0.06% acetic acid |
| Solvent B: | 100% methanol; 0.06% acetic acid |
| Chromatography Type: | Reversed phase |
MS:
| MS ID: | MS002207 |
| Analysis ID: | AN002365 |
| Instrument Name: | Thermo Q Exactive Plus Orbitrap |
| Instrument Type: | Orbitrap |
| MS Type: | ESI |
| MS Comments: | Data processing. Data from each mode were independently analyzed using Progenesis QI software v2.3 (Nonlinear Dynamics). Metabolic features from blanks and that didn’t show sufficient linearity upon dilution were discarded. Only metabolic features present in >33% of the samples in each group were kept for further analysis and missing values were imputed by drawing from a random distribution of small values in the corresponding sample (Tyanova et al., 2016). Metabolic feature annotation. Annotation confidence levels for each metabolite were provided following the Metabolomics Standards Initiative (MSI) confidence scheme. Peak annotation was first performed by matching experimental m/z, retention time and MS/MS spectra to an in-house library of analytical-grade standards (level 1). Remaining peaks were identified by matching experimental m/z and fragmentation spectra to publicly available databases including HMDB (http://www.hmdb.ca/), MoNA (http://mona.fiehnlab.ucdavis.edu/) and MassBank (http://www.massbank.jp/) using the R package ‘MetID’ (v0.2.0) (PMID: 30944337) (level 2). Briefly, metabolic feature tables from Progenesis QI were matched to fragmentation spectra with a m/z and a retention time window of ±15 ppm and ±30 s (HILIC) and ± 20 s (RPLC), respectively. When multiple MS/MS spectra match a single metabolic feature, all matched MS/MS spectra were used for the identification. Next, MS1 and MS2 pairs were searched against public databases and a similarity score was calculated using the forward dot–product algorithm which takes into account both fragments and intensities. Metabolites were reported if the similarity score was above 0.4. Level 3 corresponds to unknown metabolites. |
| Ion Mode: | POSITIVE |
| Capillary Temperature: | 375C |
| Capillary Voltage: | 3.4kV |
| Collision Energy: | 25 & 35 NCE |
| Collision Gas: | N2 |
| Dry Gas Temp: | 310C |
| MS ID: | MS002208 |
| Analysis ID: | AN002366 |
| Instrument Name: | Thermo Q Exactive Plus Orbitrap |
| Instrument Type: | Orbitrap |
| MS Type: | ESI |
| MS Comments: | Data processing. Data from each mode were independently analyzed using Progenesis QI software v2.3 (Nonlinear Dynamics). Metabolic features from blanks and that didn’t show sufficient linearity upon dilution were discarded. Only metabolic features present in >33% of the samples in each group were kept for further analysis and missing values were imputed by drawing from a random distribution of small values in the corresponding sample (Tyanova et al., 2016). Metabolic feature annotation. Annotation confidence levels for each metabolite were provided following the Metabolomics Standards Initiative (MSI) confidence scheme. Peak annotation was first performed by matching experimental m/z, retention time and MS/MS spectra to an in-house library of analytical-grade standards (level 1). Remaining peaks were identified by matching experimental m/z and fragmentation spectra to publicly available databases including HMDB (http://www.hmdb.ca/), MoNA (http://mona.fiehnlab.ucdavis.edu/) and MassBank (http://www.massbank.jp/) using the R package ‘MetID’ (v0.2.0) (PMID: 30944337) (level 2). Briefly, metabolic feature tables from Progenesis QI were matched to fragmentation spectra with a m/z and a retention time window of ±15 ppm and ±30 s (HILIC) and ± 20 s (RPLC), respectively. When multiple MS/MS spectra match a single metabolic feature, all matched MS/MS spectra were used for the identification. Next, MS1 and MS2 pairs were searched against public databases and a similarity score was calculated using the forward dot–product algorithm which takes into account both fragments and intensities. Metabolites were reported if the similarity score was above 0.4. Level 3 corresponds to unknown metabolites. |
| Ion Mode: | NEGATIVE |
| Capillary Temperature: | 375C |
| Capillary Voltage: | 3.4kV |
| Collision Energy: | 25 & 35 NCE |
| Collision Gas: | N2 |
| Dry Gas Temp: | 310C |
| MS ID: | MS002209 |
| Analysis ID: | AN002367 |
| Instrument Name: | Thermo Q Exactive Plus Orbitrap |
| Instrument Type: | Orbitrap |
| MS Type: | ESI |
| MS Comments: | Data processing. Data from each mode were independently analyzed using Progenesis QI software v2.3 (Nonlinear Dynamics). Metabolic features from blanks and that didn’t show sufficient linearity upon dilution were discarded. Only metabolic features present in >33% of the samples in each group were kept for further analysis and missing values were imputed by drawing from a random distribution of small values in the corresponding sample (Tyanova et al., 2016). Metabolic feature annotation. Annotation confidence levels for each metabolite were provided following the Metabolomics Standards Initiative (MSI) confidence scheme. Peak annotation was first performed by matching experimental m/z, retention time and MS/MS spectra to an in-house library of analytical-grade standards (level 1). Remaining peaks were identified by matching experimental m/z and fragmentation spectra to publicly available databases including HMDB (http://www.hmdb.ca/), MoNA (http://mona.fiehnlab.ucdavis.edu/) and MassBank (http://www.massbank.jp/) using the R package ‘MetID’ (v0.2.0) (PMID: 30944337) (level 2). Briefly, metabolic feature tables from Progenesis QI were matched to fragmentation spectra with a m/z and a retention time window of ±15 ppm and ±30 s (HILIC) and ± 20 s (RPLC), respectively. When multiple MS/MS spectra match a single metabolic feature, all matched MS/MS spectra were used for the identification. Next, MS1 and MS2 pairs were searched against public databases and a similarity score was calculated using the forward dot–product algorithm which takes into account both fragments and intensities. Metabolites were reported if the similarity score was above 0.4. Level 3 corresponds to unknown metabolites. |
| Ion Mode: | POSITIVE |
| Capillary Temperature: | 375C |
| Capillary Voltage: | 3.4kV |
| Collision Energy: | 25 & 50 NCE |
| Collision Gas: | N2 |
| Dry Gas Temp: | 310C |
| MS ID: | MS002210 |
| Analysis ID: | AN002368 |
| Instrument Name: | Thermo Q Exactive Plus Orbitrap |
| Instrument Type: | Orbitrap |
| MS Type: | ESI |
| MS Comments: | Data processing. Data from each mode were independently analyzed using Progenesis QI software v2.3 (Nonlinear Dynamics). Metabolic features from blanks and that didn’t show sufficient linearity upon dilution were discarded. Only metabolic features present in >33% of the samples in each group were kept for further analysis and missing values were imputed by drawing from a random distribution of small values in the corresponding sample (Tyanova et al., 2016). Metabolic feature annotation. Annotation confidence levels for each metabolite were provided following the Metabolomics Standards Initiative (MSI) confidence scheme. Peak annotation was first performed by matching experimental m/z, retention time and MS/MS spectra to an in-house library of analytical-grade standards (level 1). Remaining peaks were identified by matching experimental m/z and fragmentation spectra to publicly available databases including HMDB (http://www.hmdb.ca/), MoNA (http://mona.fiehnlab.ucdavis.edu/) and MassBank (http://www.massbank.jp/) using the R package ‘MetID’ (v0.2.0) (PMID: 30944337) (level 2). Briefly, metabolic feature tables from Progenesis QI were matched to fragmentation spectra with a m/z and a retention time window of ±15 ppm and ±30 s (HILIC) and ± 20 s (RPLC), respectively. When multiple MS/MS spectra match a single metabolic feature, all matched MS/MS spectra were used for the identification. Next, MS1 and MS2 pairs were searched against public databases and a similarity score was calculated using the forward dot–product algorithm which takes into account both fragments and intensities. Metabolites were reported if the similarity score was above 0.4. Level 3 corresponds to unknown metabolites. |
| Ion Mode: | NEGATIVE |
| Capillary Temperature: | 375C |
| Capillary Voltage: | 3.4kV |
| Collision Energy: | 25 & 50 NCE |
| Collision Gas: | N2 |
| Dry Gas Temp: | 310C |
