Summary of Study ST001807

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 PR001141. The data can be accessed directly via it's Project DOI: 10.21228/M8711S 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.

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Study IDST001807
Study TitleUntargeted metabolomics of Daphnia magna exposed to a lithium cobalt oxide nanomaterial
Study TypeUntargeted MS
Study SummaryThe goal of this project was to determine lithium cobalt oxide (LCO)’s effects on pathways in the model organism Daphnia magna through untargeted metabolomics.
Institute
University of Wisconsin - Milwaukee
DepartmentSchool of Freshwater Sciences
LaboratoryRebecca Klaper
Last NameKlaper
First NameRebecca
Address600 E Greenfield Ave, Milwaukee, WI 53204
Emailrklaper@uwm.edu
Phone4143821713
Submit Date2021-05-18
Num Groups4
Total Subjects36
Study CommentsPooled samples of 20 Daphnia magna per replicate.
Raw Data AvailableYes
Raw Data File Type(s)mzXML
Analysis Type DetailLC-MS
Release Date2022-05-19
Release Version1
Rebecca Klaper Rebecca Klaper
https://dx.doi.org/10.21228/M8711S
ftp://www.metabolomicsworkbench.org/Studies/ application/zip

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Project:

Project ID:PR001141
Project DOI:doi: 10.21228/M8711S
Project Title:Energy starvation in Daphnia magna from exposure to a lithium cobalt oxide nanomaterial
Project Type:Untargeted MS
Project Summary:Our previous research demonstrated that energy metabolism is significantly impacted in sediment-dwelling invertebrate Chironomus riparius upon exposure to metal oxide nanomaterial lithium cobalt oxide (LCO), used as a cathode material in lithium-ion batteries, an impact that is not replicated by ion controls. To further explore metabolic impacts, we determined LCO’s effects on model organism Daphnia magna using untargeted metabolomics. Our results show a sublethal 1 mg/L 48 h LCO exposure causes significant impacts on D. magna metabolites, while ion control exposure equivalent to released Li and Co had no impact, showing the nano-specificity of LCO impacts. Specifically, metabolomic analysis indicated alteration of metabolites related to amino acid metabolism and starch, sucrose, and galactose metabolism as a result of LCO exposure.
Institute:University of Wisconsin - Milwaukee
Department:School of Freshwater Sciences
Laboratory:Rebecca Klaper
Last Name:Niemuth
First Name:Nicholas
Address:600 E Greenfield Ave, Milwaukee, WI, 53204, USA
Email:niemuthn@uwm.edu
Phone:4143821763
Funding Source:National Science Foundation CHE-2001611
Contributors:Nicholas J Niemuth, Becky J Curtis, Elizabeth D Laudadio, Jelena Sostare, Evan A Bennett, Nicklaus J Neureuther, Mark R Viant, Robert J Hamers, Rebecca D Klaper

Subject:

Subject ID:SU001884
Subject Type:Invertebrate
Subject Species:Daphnia magna
Taxonomy ID:35525
Age Or Age Range:neonates < 9 h old

Factors:

Subject type: Invertebrate; Subject species: Daphnia magna (Factor headings shown in green)

mb_sample_id local_sample_id characteristics
SA167724Dm_polneg_Ion_1_39Ion
SA167725Dm_polpos_Ion_1_44Ion
SA167726Dm_polneg_Ion_1_24Ion
SA167727Dm_polneg_Ion_1_44Ion
SA167728Dm_polneg_Ion_1_29Ion
SA167729Dm_polneg_Ion_1_49Ion
SA167730Dm_polpos_Ion_1_39Ion
SA167731Dm_polpos_Ion_1_34Ion
SA167732Dm_polpos_Ion_1_49Ion
SA167733Dm_polneg_Ion_1_19Ion
SA167734Dm_polneg_Ion_1_34Ion
SA167735Dm_polpos_Ion_1_9Ion
SA167736Dm_polneg_Ion_1_14Ion
SA167737Dm_polpos_Ion_1_14Ion
SA167738Dm_polpos_Ion_1_4Ion
SA167739Dm_polpos_Ion_1_19Ion
SA167740Dm_polneg_Ion_1_9Ion
SA167741Dm_polpos_Ion_1_29Ion
SA167742Dm_polneg_Ion_1_4Ion
SA167743Dm_polpos_Ion_1_24Ion
SA167744Dm_polpos_LCO_01_7LCO 0.1 mg/L
SA167745Dm_polpos_LCO_01_2LCO 0.1 mg/L
SA167746Dm_polpos_LCO_01_12LCO 0.1 mg/L
SA167747Dm_polpos_LCO_01_47LCO 0.1 mg/L
SA167748Dm_polpos_LCO_01_37LCO 0.1 mg/L
SA167749Dm_polpos_LCO_01_42LCO 0.1 mg/L
SA167750Dm_polpos_LCO_01_27LCO 0.1 mg/L
SA167751Dm_polpos_LCO_01_22LCO 0.1 mg/L
SA167752Dm_polpos_LCO_01_17LCO 0.1 mg/L
SA167753Dm_polneg_LCO_01_12LCO 0.1 mg/L
SA167754Dm_polneg_LCO_01_17LCO 0.1 mg/L
SA167755Dm_polpos_LCO_01_32LCO 0.1 mg/L
SA167756Dm_polneg_LCO_01_7LCO 0.1 mg/L
SA167757Dm_polneg_LCO_01_2LCO 0.1 mg/L
SA167758Dm_polneg_LCO_01_47LCO 0.1 mg/L
SA167759Dm_polneg_LCO_01_22LCO 0.1 mg/L
SA167760Dm_polneg_LCO_01_42LCO 0.1 mg/L
SA167761Dm_polneg_LCO_01_37LCO 0.1 mg/L
SA167762Dm_polneg_LCO_01_32LCO 0.1 mg/L
SA167763Dm_polneg_LCO_01_27LCO 0.1 mg/L
SA167764Dm_polpos_LCO_1_43LCO 1 mg/L
SA167765Dm_polneg_LCO_1_8LCO 1 mg/L
SA167766Dm_polpos_LCO_1_13LCO 1 mg/L
SA167767Dm_polpos_LCO_1_8LCO 1 mg/L
SA167768Dm_polneg_LCO_1_3LCO 1 mg/L
SA167769Dm_polpos_LCO_1_18LCO 1 mg/L
SA167770Dm_polpos_LCO_1_28LCO 1 mg/L
SA167771Dm_polpos_LCO_1_38LCO 1 mg/L
SA167772Dm_polpos_LCO_1_33LCO 1 mg/L
SA167773Dm_polpos_LCO_1_48LCO 1 mg/L
SA167774Dm_polneg_LCO_1_13LCO 1 mg/L
SA167775Dm_polneg_LCO_1_38LCO 1 mg/L
SA167776Dm_polneg_LCO_1_43LCO 1 mg/L
SA167777Dm_polneg_LCO_1_48LCO 1 mg/L
SA167778Dm_polneg_LCO_1_33LCO 1 mg/L
SA167779Dm_polneg_LCO_1_28LCO 1 mg/L
SA167780Dm_polneg_LCO_1_18LCO 1 mg/L
SA167781Dm_polneg_LCO_1_23LCO 1 mg/L
SA167782Dm_polpos_LCO_1_3LCO 1 mg/L
SA167783Dm_polneg_QC_6Quality control
SA167784Dm_polneg_QC_3Quality control
SA167785Dm_polneg_QC_2Quality control
SA167786Dm_polneg_QC_4Quality control
SA167787Dm_polneg_QC_5Quality control
SA167788Dm_polneg_QC_7Quality control
SA167789Dm_polneg_QC_1Quality control
SA167790Dm_polpos_QC_9Quality control
SA167791Dm_polpos_QC_13Quality control
SA167792Dm_polpos_QC_14Quality control
SA167793Dm_polpos_QC_12Quality control
SA167794Dm_polpos_QC_11Quality control
SA167795Dm_polpos_QC_10Quality control
SA167796Dm_polneg_QC_8Quality control
SA167797Dm_polneg_QC_9Quality control
SA167798Dm_polpos_QC_5Quality control
SA167799Dm_polpos_QC_6Quality control
SA167800Dm_polpos_QC_4Quality control
SA167801Dm_polpos_QC_3Quality control
SA167802Dm_polpos_QC_2Quality control
SA167803Dm_polpos_QC_7Quality control
SA167804Dm_polpos_QC_8Quality control
SA167805Dm_polneg_QC_11Quality control
SA167806Dm_polneg_QC_10Quality control
SA167807Dm_polneg_QC_12Quality control
SA167808Dm_polneg_QC_13Quality control
SA167809Dm_polneg_QC_14Quality control
SA167810Dm_polpos_QC_1Quality control
SA167811Dm_polpos_C_6untreated
SA167812Dm_polneg_C_31untreated
SA167813Dm_polneg_C_36untreated
SA167814Dm_polneg_C_41untreated
SA167815Dm_polneg_C_26untreated
SA167816Dm_polneg_C_21untreated
SA167817Dm_polneg_C_11untreated
SA167818Dm_polneg_C_16untreated
SA167819Dm_polneg_C_6untreated
SA167820Dm_polpos_C_11untreated
SA167821Dm_polpos_C_36untreated
SA167822Dm_polpos_C_41untreated
SA167823Dm_polpos_C_31untreated
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Collection:

Collection ID:CO001877
Collection Summary:Daphnid cultures D. magna were cultured at a density of 20 animals per liter MHRW, 16 h:8 h light:dark photoperiod, and a temperature of 20 °C. For metabolomics, cultures were fed daily on suspensions of unicellular green alga, Chlorella vulgaris (7.84 × 107 cells/mL) at 2 mL/L. Algae was supplemented daily by 50 µL/L of dried bakers yeast (1mg/mL stock, Sigma–Aldrich). Cultures were maintained using third or fourth brood neonates less than 24 h old. Ten replicates were prepared for each treatment: MHRW control, 1 mg/L LCO, and ion control (66 μg/L Li as LiCl and 15 μg/L Co as CoCl2; equivalent to ions released by 1 mg/L LCO over 48 h).1,2 Twenty neonates per replicate (< 9 h old) were transferred to 100 ml beakers 48 hours prior to exposure and fed proportionate amounts of food for 48 hours. At the end of the 48-hour feeding period, daphnids were transferred to 200 ml control or exposure beakers. Exposures were carried out for 48 h without food per standard OECD guidelines for D. magna. At the end of the exposure daphnids were collected and transferred (20 pooled animals per replicate) into labeled Precellys tubes using a fine sable brush and flash frozen in liquid nitrogen.At the end of the exposure daphnids were collected and transferred (20 pooled animals per replicate) into labeled Precellys tubes using a fine sable brush and flash frozen in liquid nitrogen. Samples were stored at -80 °C and shipped to the University of Birmingham, UK on dry ice.
Sample Type:Whole animals
Storage Conditions:-80℃
Collection Vials:Precellys tubes

Treatment:

Treatment ID:TR001897
Treatment Summary:Ten replicates were prepared for each treatment: MHRW control, 1 mg/L LCO, and ion control (66 μg/L Li as LiCl and 15 μg/L Co as CoCl2; equivalent to ions released by 1 mg/L LCO over 48 h).1,2 Twenty neonates per replicate (< 9 h old) were transferred to 100 ml beakers 48 hours prior to exposure and fed proportionate amounts of food for 48 hours. At the end of the 48-hour feeding period, daphnids were transferred to 200 ml control or exposure beakers. Exposures were carried out for 48 h without food per standard OECD guidelines for D. magna.
Treatment Compound:Lithium boalt oxide (LCO) nanosheets
Treatment Dosevolume:0.1 and 1 mg/L
Treatment Doseduration:48 h

Sample Preparation:

Sampleprep ID:SP001890
Sampleprep Summary:all solvents were chilled to 4 ºC. A mixture of 320 µL of HPLC grade MeOH and 128 µL of HPLC grade H2O were added to each sample tube and kept on ice. Tubes were then placed in a Precellys 24 homogeniser for 2 × 10s bursts at 6400 rpm. The homogenised mixture was then transferred into a clean 1.8 mL glass vial (Fisher TUL 520 006 J) using a Pasteur pipette. 320 µL (32 µL/mg) CHCl3 (HPLC grade) and 160 µL (16 µL/mg) dH2O (HPLC grade) were then added to each vial. These vials were vortexed on full power for 15 s each to thoroughly mix polar and non-polar solvents. Vials were then left on ice for on ice for 10 min to allow initial phase separation. Vials were then centrifuged at 4000 rpm at 4 ºC for 10 min to ensure complete phase separation. Centrifuged vials were allowed to come to room temperature by setting them on the lab bench for 5 min. Samples were then visibly biphasic, with protein debris separating the upper (polar) and lower (non-polar) layers. A 500 uL Hamilton syringe was then used to remove the polar phase (~ 2 × 150 µL aliquots) into 2 clean 1.5 mL Eppendorf tubes (one for positive, one for negative ion analysis). Polar samples were then dried using a Speed Vac concentrator and stored at -80 °C until analysis. Sample Preparation and Direct Infusion Mass Spectrometry Metabolomics For positive ion analysis, 30 µL of 4 ºC 80:20 methanol:water plus 0.25% formic acid was added to each of the frozen, dried extracts, and each sample vortexed for 30s. For negative ion analysis 30 µL of 4 ºC 80:20 methanol:water plus 20 mM ammonium acetate was added to each of the frozen, dried extracts, and each sample vortexed for 30 s. Samples were then centrifuged at 4000 g at 4 ºC for 10 mins. For both positive and negative ion analyses, samples were randomized and 5 µL of sample supernatant was pipetted into a pre-washed 96-well sample plate in quadruplicate. Three quality control (QC) samples (a mixture with equal volume from all samples) and a blank were also included on each plate. Loaded plates were covered with a foil seal using heat sealer and loaded into a TriVersa Nano-Mate® nanoelectro-spray ion source (Advion) with the cooler set at 10 ºC. Non-targeted analysis was carried out on polar fractions by direct infusion mass spectrometry (DIMS) using an LTQ Orbitrap Elite (Thermo Fisher Scientific). 21 overlapping selected ion monitoring (SIM) windows were collected covering m/z values from 50 to 620.
Processing Storage Conditions:4℃
Extract Storage:4℃

Combined analysis:

Analysis ID AN002929 AN002930
Analysis type MS MS
Chromatography type None (Direct infusion) None (Direct infusion)
Chromatography system LTQ Orbitrap Elite (Thermo Fisher Scientific) LTQ Orbitrap Elite (Thermo Fisher Scientific)
Column none none
MS Type ESI ESI
MS instrument type LTQ-FT LTQ-FT
MS instrument name Thermo Orbitrap Elite Hybrid Ion Trap-Orbitrap Thermo Orbitrap Elite Hybrid Ion Trap-Orbitrap
Ion Mode POSITIVE NEGATIVE
Units arbitrary units arbitrary units

Chromatography:

Chromatography ID:CH002171
Chromatography Summary:Non-targeted analysis was carried out on polar fractions by direct infusion mass spectrometry (DIMS) using an LTQ Orbitrap Elite (Thermo Fisher Scientific). 21 overlapping selected ion monitoring (SIM) windows were collected covering m/z values from 50 to 620.
Instrument Name:LTQ Orbitrap Elite (Thermo Fisher Scientific)
Column Name:none
Chromatography Type:None (Direct infusion)

MS:

MS ID:MS002720
Analysis ID:AN002929
Instrument Name:Thermo Orbitrap Elite Hybrid Ion Trap-Orbitrap
Instrument Type:LTQ-FT
MS Type:ESI
MS Comments:For both positive and negative ion analyses, samples were randomized and 5 µL of sample supernatant was pipetted into a pre-washed 96-well sample plate in quadruplicate. Three quality control (QC) samples (a mixture with equal volume from all samples) and a blank were also included on each plate. Loaded plates were covered with a foil seal using heat sealer and loaded into a TriVersa Nano-Mate® nanoelectro-spray ion source (Advion) with the cooler set at 10 ºC. Non-targeted analysis was carried out on polar fractions by direct infusion mass spectrometry (DIMS) using an LTQ Orbitrap Elite (Thermo Fisher Scientific). 21 overlapping selected ion monitoring (SIM) windows were collected covering m/z values from 50 to 620. Data are available in the NIH National Metabolomics Data Repository (NMDR). The Galaxy pipeline at the University of Birmingham was used to process raw data collected. SIM windows were assembled into single spectra for each sample (SIM-Stitching). Filtering A signal to noise ratio (SNR) of 10 was selected to filter out background noise from the data. A replicate filter was applied to retain only peaks found in at least 3 out of 4 technical replicates, and samples aligned across biological samples. A blank filter was applied to only retain peaks if they are a specified % larger than blank values. Finally a sample filter was applied to keep only those peaks found in greater than 80% of biological samples. Missing-value imputation, normalization, and quality assessment Probabilistic quotient normalization (PQN) was applied to normalize the DIMS metabolomics data to account for differences in dilution between samples. A K-nearest neighbor (KNN) algorithm was then applied to impute missing values. A generalized-log transformation was then applied to stabilize the technical variance of the DIMS measurements. To assess data quality, the median relative standard deviation (RSD) was measured across technical replicates and an RSD cutoff value of 10 was specified. Data analysis Univariate ANOVAs were carried out on metabolite data with a false discovery rate (FDR) correction to account for the large number of possible comparisons. Peaks were annotated using the Functional Analysis tool for MS peaks on the MetaboAnalyst 5.0 online web server.4 Peak list files were uploaded containing m/z values and FDR corrected p-values obtained by the processing above, and analyzed in the respective (positive or negative) ion mode with a 5.0 ppm mass tolerance. For enrichment analysis, the Mummichog algorithm was applied with a p-value cutoff of p < 0.1 and analyzed against the KEGG database for Homo sapiens and Drosophila melanogaster. References (1) Bozich, J.; Hang, M.; Hamers, R.; Klaper, R. Core Chemistry Influences the Toxicity of Multicomponent Metal Oxide Nanomaterials, Lithium Nickel Manganese Cobalt Oxide, and Lithium Cobalt Oxide to Daphnia Magna. Environ. Toxicol. Chem. 2017, 36 (9), 2493–2502. https://doi.org/10.1002/etc.3791. (2) Niemuth, N. J. N. J.; Curtis, B. J. B. J.; Hang, M. N. M. N.; Gallagher, M. J. M. J.; Fairbrother, D. H. H.; Hamers, R. J. R. J.; Klaper, R. D. R. D. Next-Generation Complex Metal Oxide Nanomaterials Negatively Impact Growth and Development in the Benthic Invertebrate Chironomus Riparius upon Settling. Environ. Sci. Technol. 2019, 53 (7), 3860–3870. https://doi.org/10.1021/acs.est.8b06804. (3) Davidson, R. L.; Weber, R. J. M.; Liu, H.; Sharma-Oates, A.; Viant, M. R. Galaxy-M: A Galaxy Workflow for Processing and Analyzing Direct Infusion and Liquid Chromatography Mass Spectrometry-Based Metabolomics Data. Gigascience 2016, 5 (1), 10. https://doi.org/10.1186/s13742-016-0115-8. (4) Xia, J.; Psychogios, N.; Young, N.; Wishart, D. S. MetaboAnalyst: A Web Server for Metabolomic Data Analysis and Interpretation. Nucleic Acids Res. 2009, 37 (Web Server), W652–W660. https://doi.org/10.1093/nar/gkp356.
Ion Mode:POSITIVE
  
MS ID:MS002721
Analysis ID:AN002930
Instrument Name:Thermo Orbitrap Elite Hybrid Ion Trap-Orbitrap
Instrument Type:LTQ-FT
MS Type:ESI
MS Comments:For both positive and negative ion analyses, samples were randomized and 5 µL of sample supernatant was pipetted into a pre-washed 96-well sample plate in quadruplicate. Three quality control (QC) samples (a mixture with equal volume from all samples) and a blank were also included on each plate. Loaded plates were covered with a foil seal using heat sealer and loaded into a TriVersa Nano-Mate® nanoelectro-spray ion source (Advion) with the cooler set at 10 ºC. Non-targeted analysis was carried out on polar fractions by direct infusion mass spectrometry (DIMS) using an LTQ Orbitrap Elite (Thermo Fisher Scientific). 21 overlapping selected ion monitoring (SIM) windows were collected covering m/z values from 50 to 620. Data are available in the NIH National Metabolomics Data Repository (NMDR). The Galaxy pipeline at the University of Birmingham was used to process raw data collected. SIM windows were assembled into single spectra for each sample (SIM-Stitching). Filtering A signal to noise ratio (SNR) of 10 was selected to filter out background noise from the data. A replicate filter was applied to retain only peaks found in at least 3 out of 4 technical replicates, and samples aligned across biological samples. A blank filter was applied to only retain peaks if they are a specified % larger than blank values. Finally a sample filter was applied to keep only those peaks found in greater than 80% of biological samples. Missing-value imputation, normalization, and quality assessment Probabilistic quotient normalization (PQN) was applied to normalize the DIMS metabolomics data to account for differences in dilution between samples. A K-nearest neighbor (KNN) algorithm was then applied to impute missing values. A generalized-log transformation was then applied to stabilize the technical variance of the DIMS measurements. To assess data quality, the median relative standard deviation (RSD) was measured across technical replicates and an RSD cutoff value of 10 was specified. Data analysis Univariate ANOVAs were carried out on metabolite data with a false discovery rate (FDR) correction to account for the large number of possible comparisons. Peaks were annotated using the Functional Analysis tool for MS peaks on the MetaboAnalyst 5.0 online web server.4 Peak list files were uploaded containing m/z values and FDR corrected p-values obtained by the processing above, and analyzed in the respective (positive or negative) ion mode with a 5.0 ppm mass tolerance. For enrichment analysis, the Mummichog algorithm was applied with a p-value cutoff of p < 0.1 and analyzed against the KEGG database for Homo sapiens and Drosophila melanogaster. References (1) Bozich, J.; Hang, M.; Hamers, R.; Klaper, R. Core Chemistry Influences the Toxicity of Multicomponent Metal Oxide Nanomaterials, Lithium Nickel Manganese Cobalt Oxide, and Lithium Cobalt Oxide to Daphnia Magna. Environ. Toxicol. Chem. 2017, 36 (9), 2493–2502. https://doi.org/10.1002/etc.3791. (2) Niemuth, N. J. N. J.; Curtis, B. J. B. J.; Hang, M. N. M. N.; Gallagher, M. J. M. J.; Fairbrother, D. H. H.; Hamers, R. J. R. J.; Klaper, R. D. R. D. Next-Generation Complex Metal Oxide Nanomaterials Negatively Impact Growth and Development in the Benthic Invertebrate Chironomus Riparius upon Settling. Environ. Sci. Technol. 2019, 53 (7), 3860–3870. https://doi.org/10.1021/acs.est.8b06804. (3) Davidson, R. L.; Weber, R. J. M.; Liu, H.; Sharma-Oates, A.; Viant, M. R. Galaxy-M: A Galaxy Workflow for Processing and Analyzing Direct Infusion and Liquid Chromatography Mass Spectrometry-Based Metabolomics Data. Gigascience 2016, 5 (1), 10. https://doi.org/10.1186/s13742-016-0115-8. (4) Xia, J.; Psychogios, N.; Young, N.; Wishart, D. S. MetaboAnalyst: A Web Server for Metabolomic Data Analysis and Interpretation. Nucleic Acids Res. 2009, 37 (Web Server), W652–W660. https://doi.org/10.1093/nar/gkp356.
Ion Mode:NEGATIVE
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