Summary of Study ST001977

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 PR001255. The data can be accessed directly via it's Project DOI: 10.21228/M8GT41 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	ST001977
Study Title	Anti-oxidative metabolism measurement in mammalian cells and tissues by quantitative LC/MS method (IV)
Study Summary	Anti-oxidation metabolism measurement in mammalian cells and tissues by quantitative LC/MS method of human patient/lymphoma patient CSF.
Institute	Boston Children's Hospital, Harvard Medical School
Last Name	Petrova
First Name	Boryana
Address	300 Longwood Ave
Email	boryana.petrova@childrens.harvard.edu
Phone	6173557433
Submit Date	2021-09-15
Raw Data File Type(s)	raw(Thermo)
Analysis Type Detail	LC-MS
Release Date	2022-08-29
Release Version	1

Select appropriate tab below to view additional metadata details:

Project:

Project ID:	PR001255
Project DOI:	doi: 10.21228/M8GT41
Project Title:	Gene-therapy enhances CSF’s anti-oxidative activity to mitigate chemotherapy side effects
Project Type:	Anti-oxidative Metabolism Measurement in CSF of MTX-treated mice under gene therapy by quantitative LC/MS method
Project Summary:	In order to test the protective activity of SOD3 levels on the redox state of the CSF of MTX-treated mice, targeted metabolomics on CSF was employed at different timepoints after treatment, on mice of both sexes, at various levels of impacted hSOD3 expression.
Institute:	Boston Childrens Hospital
Department:	Pathology
Laboratory:	Naama Kanarek
Last Name:	Petrova
First Name:	Boryana
Address:	300 Longwood Av, Boston, MA, 2115, USA
Email:	boryana.petrova@childrens.harvard.edu
Phone:	6173557433

Subject:

Subject ID:	SU002057
Subject Type:	Mammal
Subject Species:	Homo sapiens
Taxonomy ID:	9606
Gender:	Male and female

Factors:

Subject type: Mammal; Subject species: Homo sapiens (Factor headings shown in green)

mb_sample_id	local_sample_id	Factor
SA185384	pooled sample QC 1/10 dilution a	-
SA185385	pooled sample QC 1/10 dilution b	-
SA185386	pooled sample QC 1/5 dilution	-
SA185387	pooled sample QCb	-
SA185388	pooled sample QCd	-
SA185389	pooled sample QC 1/3 dilution	-
SA185390	pooled sample QC 1a	-
SA185391	pooled sample QC 1/10 dilution 1a	-
SA185392	pooled sample QC 1/10 dilution 1b	-
SA185393	pooled sample QC 1/3 dilution 1a	-
SA185394	pooled sample QC 1c	-
SA185395	pooled sample QC 1b	-
SA185396	blank 8	-
SA185397	pooled sample QCa	-
SA185398	blank 8-1	-
SA185399	blank 10	-
SA185400	blank 9	-
SA185401	human CSF 18	CSF2 10.03
SA185402	human CSF 15	CSF3 11.22
SA185403	human CSF 20	CSF4 11.27
SA185404	human CSF 16	CSF5 11.27
SA185382	human CSF 17	"lymphoma, patient 1"
SA185383	human CSF 19	"lymphoma, patient 2 2020.02.07"
SA185405	human CSF 14	N9
SA185406	human CSF 13	NJ3
SA185407	human CSF 7	patient12_1
SA185408	human CSF 8	patient12_2
SA185409	human CSF 9	patient12_3
SA185410	human CSF 10	patient13_1
SA185411	human CSF 11	patient13_2
SA185412	human CSF 12	patient13_3
SA185413	human CSF 1	patient2_1
SA185414	human CSF 2	patient2_2
SA185415	human CSF 3	patient2_3
SA185416	human CSF 4	patient4_1
SA185417	human CSF 5	patient4_2
SA185418	human CSF 6	patient4_3

Showing results 1 to 37 of 37

Showing results 1 to 37 of 37

Collection:

Collection ID:	CO002050
Collection Summary:	De-identified CSF samples from both central nervous system (CNS) lymphoma patients and non-chemotherapy exposed controls were obtained by Dr. Eric Wong (BIDMC) under BIDMC Institutional Review Board (IRB)-approved protocols and analyzed under BCH IRB-approved protocols. Samples were aliquoted and stored at −80°C until use. CSF from patient samples was collected independently and aliquoted in 3uL or 5uL amounts for analysis.
Sample Type:	CSF

Treatment:

Treatment ID:	TR002069
Treatment Summary:	No treatment + buffers from study design

Sample Preparation:

Sampleprep ID:	SP002063
Sampleprep Summary:	For characterization by mass spectrometry, CSF was acquired 4h, 24h, and 48h following a single 75 mg/kg MTX injection from 6-8 mice and flash frozen for further analysis. Per condition, 3 μl of CSF were extracted by brief sonication in 240 μl 100% methanol, supplemented with isotopically labeled internal standards (17 amino acids and reduced glutathione, Cambridge Isotope Laboratories, MSK-A2-1.2 and CNLM-6245-10) and 60 μl 20 mM Ellman’s reagent in water (Sigma-Aldrich, D8130). After centrifugation for 10min. at maximum speed on a benchtop centrifuge (Eppendorf) the cleared supernatant was dried using a nitrogen dryer and reconstituted in 30 µl water by brief sonication. Extracted metabolites were spun again and cleared supernatant was transferred in LC-MS microvials. A small amount of each sample was pooled and serially diluted 3 and 10-fold to be used as quality controls throughout the batch run. Two microliters (equivalent to 0.2 ul of CSF) of reconstituted sample were injected into a ZIC-pHILIC 150 × 2.1 mm (5 µm particle size) column (EMD Millipore) operated on a Dionex UltiMate 3000 UPLC system (Thermo Fisher Scientific). Chromatographic separation was achieved using the following conditions: buffer A was acetonitrile; buffer B was 20 mM ammonium carbonate, 0.1% ammonium hydroxide. Gradient conditions were: linear gradient from 20% to 80% B; 20–20.5 min: from 80% to 20% B; 20.5–28 min: hold at 20% B. The column oven and autosampler tray were held at 25 °C and 4 °C, respectively. The MS data acquisition was on a QExactive benchtop orbitrap mass spectrometer equipped with an Ion Max source and a HESI II probe and was performed in a range of m/z= 70–1000, with the resolution set at 70,000, the AGC target at 1x106, and the maximum injection time (Max IT) at 20 msec. For tSIM scans, the resolution was set at 70,000, the AGC target was 1x105, and the max IT was 100 msec. Relative quantitation of polar metabolites was performed with TraceFinder 4.1 (Thermo Fisher Scientific) using a 5 ppm mass tolerance and referencing an in-house library of chemical standards. Pooled samples and fractional dilutions were prepared as quality controls and only those metabolites were taken for further analysis, for which the correlation between the dilution factor and the peak area was >0.95 (high confidence metabolites). Normalization for biological material amounts was based on the total integrated peak area values of high-confidence metabolites within an experimental batch after normalizing to the averaged factor from all mean-centered chromatographic peak areas of isotopically labeled amino acids internal standards (Cambridge Isotope Laboratories). The data were Log transformed and Pareto scaled for MetaboAnalyst-based statistical or pathway analysis (41). We profiled 200 metabolites, 85 of which were detected in CSF and passed our quality control protocol. Single-cell transcriptomics Mouse embryonic ChP single cell RNA-seq dataset was acquired and analyzed in (35). Briefly, whole embryonic ChP tissue from each ventricle was micro-dissected, digested, and live cells were FACS sorted. Single cells (~7,000 cells) were processed through the 10X Genomics Single Cell 3’ platform. Variable genes were selected by using the method described in (42). Briefly, a logistic regression model was fit to the cellular detection fraction as a function of total numbers of unique molecular identifiers (UMIs) per cell. Outliers from this curve (i.e., genes expressed in fewer cells than expected given the number of UMIs) were genes that contained more variance than proportionally expected, and therefore were particularly suited for reducing the dimensionality of the dataset. We used a threshold of deviance of -0.15 and determined the variable genes independently for each of three experimental replicates. The genes that were at the intersection of these three replicate gene lists (i.e., global variable genes) were used for downstream analysis. The expression matrix was restricted to the subset of these global variable genes, and then centered and scaled before performing principle component analysis (PCA) using Seurat’s RunPCA() function. After PCA, the number of significant principle components was determined to be 5 using the elbow method. The data were then visualized as a 2D embedding of the significant principle components using t-SNE (43) via the RunTSNE() function in Seurat.

Sampleprep ID:

SP002063

Sampleprep Summary:

For characterization by mass spectrometry, CSF was acquired 4h, 24h, and 48h following a single 75 mg/kg MTX injection from 6-8 mice and flash frozen for further analysis. Per condition, 3 μl of CSF were extracted by brief sonication in 240 μl 100% methanol, supplemented with isotopically labeled internal standards (17 amino acids and reduced glutathione, Cambridge Isotope Laboratories, MSK-A2-1.2 and CNLM-6245-10) and 60 μl 20 mM Ellman’s reagent in water (Sigma-Aldrich, D8130). After centrifugation for 10min. at maximum speed on a benchtop centrifuge (Eppendorf) the cleared supernatant was dried using a nitrogen dryer and reconstituted in 30 µl water by brief sonication. Extracted metabolites were spun again and cleared supernatant was transferred in LC-MS microvials. A small amount of each sample was pooled and serially diluted 3 and 10-fold to be used as quality controls throughout the batch run. Two microliters (equivalent to 0.2 ul of CSF) of reconstituted sample were injected into a ZIC-pHILIC 150 × 2.1 mm (5 µm particle size) column (EMD Millipore) operated on a Dionex UltiMate 3000 UPLC system (Thermo Fisher Scientific). Chromatographic separation was achieved using the following conditions: buffer A was acetonitrile; buffer B was 20 mM ammonium carbonate, 0.1% ammonium hydroxide. Gradient conditions were: linear gradient from 20% to 80% B; 20–20.5 min: from 80% to 20% B; 20.5–28 min: hold at 20% B. The column oven and autosampler tray were held at 25 °C and 4 °C, respectively. The MS data acquisition was on a QExactive benchtop orbitrap mass spectrometer equipped with an Ion Max source and a HESI II probe and was performed in a range of m/z= 70–1000, with the resolution set at 70,000, the AGC target at 1x106, and the maximum injection time (Max IT) at 20 msec. For tSIM scans, the resolution was set at 70,000, the AGC target was 1x105, and the max IT was 100 msec. Relative quantitation of polar metabolites was performed with TraceFinder 4.1 (Thermo Fisher Scientific) using a 5 ppm mass tolerance and referencing an in-house library of chemical standards. Pooled samples and fractional dilutions were prepared as quality controls and only those metabolites were taken for further analysis, for which the correlation between the dilution factor and the peak area was >0.95 (high confidence metabolites). Normalization for biological material amounts was based on the total integrated peak area values of high-confidence metabolites within an experimental batch after normalizing to the averaged factor from all mean-centered chromatographic peak areas of isotopically labeled amino acids internal standards (Cambridge Isotope Laboratories). The data were Log transformed and Pareto scaled for MetaboAnalyst-based statistical or pathway analysis (41). We profiled 200 metabolites, 85 of which were detected in CSF and passed our quality control protocol. Single-cell transcriptomics Mouse embryonic ChP single cell RNA-seq dataset was acquired and analyzed in (35). Briefly, whole embryonic ChP tissue from each ventricle was micro-dissected, digested, and live cells were FACS sorted. Single cells (~7,000 cells) were processed through the 10X Genomics Single Cell 3’ platform. Variable genes were selected by using the method described in (42). Briefly, a logistic regression model was fit to the cellular detection fraction as a function of total numbers of unique molecular identifiers (UMIs) per cell. Outliers from this curve (i.e., genes expressed in fewer cells than expected given the number of UMIs) were genes that contained more variance than proportionally expected, and therefore were particularly suited for reducing the dimensionality of the dataset. We used a threshold of deviance of -0.15 and determined the variable genes independently for each of three experimental replicates. The genes that were at the intersection of these three replicate gene lists (i.e., global variable genes) were used for downstream analysis. The expression matrix was restricted to the subset of these global variable genes, and then centered and scaled before performing principle component analysis (PCA) using Seurat’s RunPCA() function. After PCA, the number of significant principle components was determined to be 5 using the elbow method. The data were then visualized as a 2D embedding of the significant principle components using t-SNE (43) via the RunTSNE() function in Seurat.

Combined analysis:

Analysis ID	AN003225
Analysis type	MS
Chromatography type	HILIC
Chromatography system	Thermo Q Exactive Orbitrap
Column	EMD Millipore ZIC-HILIC (100 x 2.1mm,3.5um)
MS Type	ESI
MS instrument type	Orbitrap
MS instrument name	Thermo Exactive Plus Orbitrap
Ion Mode	UNSPECIFIED
Units	ppm

Chromatography:

Chromatography ID:	CH002379
Instrument Name:	Thermo Q Exactive Orbitrap
Column Name:	EMD Millipore ZIC-HILIC (100 x 2.1mm,3.5um)
Chromatography Type:	HILIC

MS:

MS ID:	MS002999
Analysis ID:	AN003225
Instrument Name:	Thermo Exactive Plus Orbitrap
Instrument Type:	Orbitrap
MS Type:	ESI
MS Comments:	Xcalibur + Tracefinder
Ion Mode:	UNSPECIFIED