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.
| Study ID | ST001807 |
| Study Title | Untargeted metabolomics of Daphnia magna exposed to a lithium cobalt oxide nanomaterial |
| Study Type | Untargeted MS |
| Study Summary | The 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 |
| Department | School of Freshwater Sciences |
| Laboratory | Rebecca Klaper |
| Last Name | Klaper |
| First Name | Rebecca |
| Address | 600 E Greenfield Ave, Milwaukee, WI 53204 |
| rklaper@uwm.edu | |
| Phone | 4143821713 |
| Submit Date | 2021-05-18 |
| Num Groups | 4 |
| Total Subjects | 36 |
| Study Comments | Pooled samples of 20 Daphnia magna per replicate. |
| Raw Data Available | Yes |
| Raw Data File Type(s) | mzXML |
| Analysis Type Detail | MS(Dir. Inf.) |
| Release Date | 2022-05-19 |
| Release Version | 1 |
Select appropriate tab below to view additional metadata details:
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 |
|---|---|---|
| SA167724 | Dm_polneg_Ion_1_39 | Ion |
| SA167725 | Dm_polpos_Ion_1_44 | Ion |
| SA167726 | Dm_polneg_Ion_1_24 | Ion |
| SA167727 | Dm_polneg_Ion_1_44 | Ion |
| SA167728 | Dm_polneg_Ion_1_29 | Ion |
| SA167729 | Dm_polneg_Ion_1_49 | Ion |
| SA167730 | Dm_polpos_Ion_1_39 | Ion |
| SA167731 | Dm_polpos_Ion_1_34 | Ion |
| SA167732 | Dm_polpos_Ion_1_49 | Ion |
| SA167733 | Dm_polneg_Ion_1_19 | Ion |
| SA167734 | Dm_polneg_Ion_1_34 | Ion |
| SA167735 | Dm_polpos_Ion_1_9 | Ion |
| SA167736 | Dm_polneg_Ion_1_14 | Ion |
| SA167737 | Dm_polpos_Ion_1_14 | Ion |
| SA167738 | Dm_polpos_Ion_1_4 | Ion |
| SA167739 | Dm_polpos_Ion_1_19 | Ion |
| SA167740 | Dm_polneg_Ion_1_9 | Ion |
| SA167741 | Dm_polpos_Ion_1_29 | Ion |
| SA167742 | Dm_polneg_Ion_1_4 | Ion |
| SA167743 | Dm_polpos_Ion_1_24 | Ion |
| SA167744 | Dm_polpos_LCO_01_7 | LCO 0.1 mg/L |
| SA167745 | Dm_polpos_LCO_01_2 | LCO 0.1 mg/L |
| SA167746 | Dm_polpos_LCO_01_12 | LCO 0.1 mg/L |
| SA167747 | Dm_polpos_LCO_01_47 | LCO 0.1 mg/L |
| SA167748 | Dm_polpos_LCO_01_37 | LCO 0.1 mg/L |
| SA167749 | Dm_polpos_LCO_01_42 | LCO 0.1 mg/L |
| SA167750 | Dm_polpos_LCO_01_27 | LCO 0.1 mg/L |
| SA167751 | Dm_polpos_LCO_01_22 | LCO 0.1 mg/L |
| SA167752 | Dm_polpos_LCO_01_17 | LCO 0.1 mg/L |
| SA167753 | Dm_polneg_LCO_01_12 | LCO 0.1 mg/L |
| SA167754 | Dm_polneg_LCO_01_17 | LCO 0.1 mg/L |
| SA167755 | Dm_polpos_LCO_01_32 | LCO 0.1 mg/L |
| SA167756 | Dm_polneg_LCO_01_7 | LCO 0.1 mg/L |
| SA167757 | Dm_polneg_LCO_01_2 | LCO 0.1 mg/L |
| SA167758 | Dm_polneg_LCO_01_47 | LCO 0.1 mg/L |
| SA167759 | Dm_polneg_LCO_01_22 | LCO 0.1 mg/L |
| SA167760 | Dm_polneg_LCO_01_42 | LCO 0.1 mg/L |
| SA167761 | Dm_polneg_LCO_01_37 | LCO 0.1 mg/L |
| SA167762 | Dm_polneg_LCO_01_32 | LCO 0.1 mg/L |
| SA167763 | Dm_polneg_LCO_01_27 | LCO 0.1 mg/L |
| SA167764 | Dm_polpos_LCO_1_43 | LCO 1 mg/L |
| SA167765 | Dm_polneg_LCO_1_8 | LCO 1 mg/L |
| SA167766 | Dm_polpos_LCO_1_13 | LCO 1 mg/L |
| SA167767 | Dm_polpos_LCO_1_8 | LCO 1 mg/L |
| SA167768 | Dm_polneg_LCO_1_3 | LCO 1 mg/L |
| SA167769 | Dm_polpos_LCO_1_18 | LCO 1 mg/L |
| SA167770 | Dm_polpos_LCO_1_28 | LCO 1 mg/L |
| SA167771 | Dm_polpos_LCO_1_38 | LCO 1 mg/L |
| SA167772 | Dm_polpos_LCO_1_33 | LCO 1 mg/L |
| SA167773 | Dm_polpos_LCO_1_48 | LCO 1 mg/L |
| SA167774 | Dm_polneg_LCO_1_13 | LCO 1 mg/L |
| SA167775 | Dm_polneg_LCO_1_38 | LCO 1 mg/L |
| SA167776 | Dm_polneg_LCO_1_43 | LCO 1 mg/L |
| SA167777 | Dm_polneg_LCO_1_48 | LCO 1 mg/L |
| SA167778 | Dm_polneg_LCO_1_33 | LCO 1 mg/L |
| SA167779 | Dm_polneg_LCO_1_28 | LCO 1 mg/L |
| SA167780 | Dm_polneg_LCO_1_18 | LCO 1 mg/L |
| SA167781 | Dm_polneg_LCO_1_23 | LCO 1 mg/L |
| SA167782 | Dm_polpos_LCO_1_3 | LCO 1 mg/L |
| SA167783 | Dm_polneg_QC_6 | Quality control |
| SA167784 | Dm_polneg_QC_3 | Quality control |
| SA167785 | Dm_polneg_QC_2 | Quality control |
| SA167786 | Dm_polneg_QC_4 | Quality control |
| SA167787 | Dm_polneg_QC_5 | Quality control |
| SA167788 | Dm_polneg_QC_7 | Quality control |
| SA167789 | Dm_polneg_QC_1 | Quality control |
| SA167790 | Dm_polpos_QC_9 | Quality control |
| SA167791 | Dm_polpos_QC_13 | Quality control |
| SA167792 | Dm_polpos_QC_14 | Quality control |
| SA167793 | Dm_polpos_QC_12 | Quality control |
| SA167794 | Dm_polpos_QC_11 | Quality control |
| SA167795 | Dm_polpos_QC_10 | Quality control |
| SA167796 | Dm_polneg_QC_8 | Quality control |
| SA167797 | Dm_polneg_QC_9 | Quality control |
| SA167798 | Dm_polpos_QC_5 | Quality control |
| SA167799 | Dm_polpos_QC_6 | Quality control |
| SA167800 | Dm_polpos_QC_4 | Quality control |
| SA167801 | Dm_polpos_QC_3 | Quality control |
| SA167802 | Dm_polpos_QC_2 | Quality control |
| SA167803 | Dm_polpos_QC_7 | Quality control |
| SA167804 | Dm_polpos_QC_8 | Quality control |
| SA167805 | Dm_polneg_QC_11 | Quality control |
| SA167806 | Dm_polneg_QC_10 | Quality control |
| SA167807 | Dm_polneg_QC_12 | Quality control |
| SA167808 | Dm_polneg_QC_13 | Quality control |
| SA167809 | Dm_polneg_QC_14 | Quality control |
| SA167810 | Dm_polpos_QC_1 | Quality control |
| SA167811 | Dm_polpos_C_6 | untreated |
| SA167812 | Dm_polneg_C_31 | untreated |
| SA167813 | Dm_polneg_C_36 | untreated |
| SA167814 | Dm_polneg_C_41 | untreated |
| SA167815 | Dm_polneg_C_26 | untreated |
| SA167816 | Dm_polneg_C_21 | untreated |
| SA167817 | Dm_polneg_C_11 | untreated |
| SA167818 | Dm_polneg_C_16 | untreated |
| SA167819 | Dm_polneg_C_6 | untreated |
| SA167820 | Dm_polpos_C_11 | untreated |
| SA167821 | Dm_polpos_C_36 | untreated |
| SA167822 | Dm_polpos_C_41 | untreated |
| SA167823 | Dm_polpos_C_31 | untreated |
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 |
