Summary of Study ST003515

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 PR002160. The data can be accessed directly via it's Project DOI: 10.21228/M8DR6G 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 IDST003515
Study TitleUntargeted Metabolomics of 3xTg-AD Neurotoxic Astrocytes
Study SummaryAlzheimer's disease (AD) is the most common form of dementia, affecting approximately 47M people worldwide. Histological features and genetic risk factors, among other evidence, supported the amyloid hypothesis of the disease. This neuronocentric paradigm is currently undergoing a shift, considering evidence of the role of other cell types, such as microglia and astrocytes, in disease progression. Previously, we described a particular astrocyte subtype obtained from the 3xTg-AD murine model that displays neurotoxic properties in vitro. We continue here our exploratory analysis through the lens of metabolomics to identify potentially altered metabolites and biological pathways. Cell extracts from neurotoxic and control astrocytes were compared using HRMS-based metabolomics. Around 12% of metabolic features demonstrated significant differences between neurotoxic and control astrocytes, including alterations in the key metabolite glutamate. Consistent with our previous transcriptomic study, the present results illustrate many homeostatic and regulatory functions of metabolites, suggesting that neurotoxic 3xTg-AD astrocytes exhibit alterations in the Krebs cycle as well as the prostaglandin pathway. This is the first metabolomic study performed in 3xTg-AD neurotoxic astrocytes. These results provide insight into metabolic alterations potentially associated with neurotoxicity and pathology progression in the 3xTg-AD mouse model and strengthen the therapeutic potential of astrocytes in AD.
Institute
Instituto de Investigaciones Biológicas Clemente Estable (IIBCE)
Last NameCarvalho
First NameDiego
AddressIsidoro de María 1614, Montevideo, Montevideo, 11800, Uruguay
Emaildicarez@fq.edu.uy
Phone(+598) 2924 1879
Submit Date2024-10-01
Raw Data AvailableYes
Raw Data File Type(s)cdf, raw(Thermo)
Analysis Type DetailLC-MS
Release Date2024-10-11
Release Version1
Diego Carvalho Diego Carvalho
https://dx.doi.org/10.21228/M8DR6G
ftp://www.metabolomicsworkbench.org/Studies/ application/zip

Select appropriate tab below to view additional metadata details:

Project:

Project ID:PR002160
Project DOI:doi: 10.21228/M8DR6G
Project Title:Untargeted Metabolomics of 3xTg-AD Neurotoxic Astrocytes
Project Summary:Alzheimer's disease (AD) is the most common form of dementia, affecting approximately 47M people worldwide. Histological features and genetic risk factors, among other evidence, supported the amyloid hypothesis of the disease. This neuronocentric paradigm is currently undergoing a shift, considering evidence of the role of other cell types, such as microglia and astrocytes, in disease progression. Previously, we described a particular astrocyte subtype obtained from the 3xTg-AD murine model that displays neurotoxic properties in vitro. We continue here our exploratory analysis through the lens of metabolomics to identify potentially altered metabolites and biological pathways. Cell extracts from neurotoxic and control astrocytes were compared using HRMS-based metabolomics. Around 12% of metabolic features demonstrated significant differences between neurotoxic and control astrocytes, including alterations in the key metabolite glutamate. Consistent with our previous transcriptomic study, the present results illustrate many homeostatic and regulatory functions of metabolites, suggesting that neurotoxic 3xTg-AD astrocytes exhibit alterations in the Krebs cycle as well as the prostaglandin pathway. This is the first metabolomic study performed in 3xTg-AD neurotoxic astrocytes. These results provide insight into metabolic alterations potentially associated with neurotoxicity and pathology progression in the 3xTg-AD mouse model and strengthen the therapeutic potential of astrocytes in AD.
Institute:Instituto de Investigaciones Biológicas Clemente Estable (IIBCE)
Department:Neuroquímica
Last Name:Carvalho
First Name:Diego
Address:Isidoro de María 1614, Montevideo, Montevideo, 11800, Uruguay
Email:dicarez@fq.edu.uy
Phone:(+598) 2924 1879

Subject:

Subject ID:SU003644
Subject Type:Cultured cells
Subject Species:Mus musculus
Taxonomy ID:10090
Gender:Female
Species Group:Mammals

Factors:

Subject type: Cultured cells; Subject species: Mus musculus (Factor headings shown in green)

mb_sample_id local_sample_id Sample source Genotype Condition
SA3861705B_3Cultured_astrocytes 3xTg-AD Neonatal
SA3861712A_5Cultured_astrocytes 3xTg-AD Neonatal
SA3861722B_1Cultured_astrocytes 3xTg-AD Neonatal
SA3861732B_3Cultured_astrocytes 3xTg-AD Neonatal
SA3861742B_5Cultured_astrocytes 3xTg-AD Neonatal
SA3861752C_1Cultured_astrocytes 3xTg-AD Neonatal
SA3861762C_3Cultured_astrocytes 3xTg-AD Neonatal
SA3861772C_5Cultured_astrocytes 3xTg-AD Neonatal
SA3861785A_1Cultured_astrocytes 3xTg-AD Neonatal
SA3861795A_3Cultured_astrocytes 3xTg-AD Neonatal
SA3861805A_5Cultured_astrocytes 3xTg-AD Neonatal
SA3861815B_1Cultured_astrocytes 3xTg-AD Neonatal
SA3861825B_5Cultured_astrocytes 3xTg-AD Neonatal
SA3861832B_4Cultured_astrocytes 3xTg-AD Neonatal
SA3861845C_1Cultured_astrocytes 3xTg-AD Neonatal
SA3861855C_3Cultured_astrocytes 3xTg-AD Neonatal
SA3861865C_5Cultured_astrocytes 3xTg-AD Neonatal
SA3861879A_1Cultured_astrocytes 3xTg-AD Neonatal
SA3861889A_3Cultured_astrocytes 3xTg-AD Neonatal
SA3861899A_5Cultured_astrocytes 3xTg-AD Neonatal
SA3861909B_1Cultured_astrocytes 3xTg-AD Neonatal
SA3861919B_3Cultured_astrocytes 3xTg-AD Neonatal
SA3861929B_5Cultured_astrocytes 3xTg-AD Neonatal
SA3861939C_1Cultured_astrocytes 3xTg-AD Neonatal
SA3861949C_3Cultured_astrocytes 3xTg-AD Neonatal
SA3861959C_5Cultured_astrocytes 3xTg-AD Neonatal
SA3861962A_3Cultured_astrocytes 3xTg-AD Neonatal
SA3861972B_2Cultured_astrocytes 3xTg-AD Neonatal
SA3861982A_1Cultured_astrocytes 3xTg-AD Neonatal
SA3861999C_6Cultured_astrocytes 3xTg-AD Neonatal
SA3862005C_2Cultured_astrocytes 3xTg-AD Neonatal
SA3862015A_6Cultured_astrocytes 3xTg-AD Neonatal
SA3862025A_4Cultured_astrocytes 3xTg-AD Neonatal
SA3862035A_2Cultured_astrocytes 3xTg-AD Neonatal
SA3862045B_6Cultured_astrocytes 3xTg-AD Neonatal
SA3862055B_4Cultured_astrocytes 3xTg-AD Neonatal
SA3862065B_2Cultured_astrocytes 3xTg-AD Neonatal
SA3862072A_6Cultured_astrocytes 3xTg-AD Neonatal
SA3862082A_4Cultured_astrocytes 3xTg-AD Neonatal
SA3862092A_2Cultured_astrocytes 3xTg-AD Neonatal
SA3862109C_2Cultured_astrocytes 3xTg-AD Neonatal
SA3862115C_6Cultured_astrocytes 3xTg-AD Neonatal
SA3862129B_6Cultured_astrocytes 3xTg-AD Neonatal
SA3862139B_4Cultured_astrocytes 3xTg-AD Neonatal
SA3862149B_2Cultured_astrocytes 3xTg-AD Neonatal
SA3862152C_6Cultured_astrocytes 3xTg-AD Neonatal
SA3862162C_4Cultured_astrocytes 3xTg-AD Neonatal
SA3862172C_2Cultured_astrocytes 3xTg-AD Neonatal
SA3862189A_6Cultured_astrocytes 3xTg-AD Neonatal
SA3862199A_4Cultured_astrocytes 3xTg-AD Neonatal
SA3862209A_2Cultured_astrocytes 3xTg-AD Neonatal
SA3862212B_6Cultured_astrocytes 3xTg-AD Neonatal
SA3862225C_4Cultured_astrocytes 3xTg-AD Neonatal
SA3862239C_4Cultured_astrocytes 3xTg-AD Neonatal
SA3862247C_6Cultured_astrocytes 3xTg-AD Old
SA3862253A_6Cultured_astrocytes 3xTg-AD Old
SA3862267B_4Cultured_astrocytes 3xTg-AD Old
SA3862277B_6Cultured_astrocytes 3xTg-AD Old
SA3862287A_2Cultured_astrocytes 3xTg-AD Old
SA3862297A_4Cultured_astrocytes 3xTg-AD Old
SA3862307A_6Cultured_astrocytes 3xTg-AD Old
SA3862313B_2Cultured_astrocytes 3xTg-AD Old
SA3862323B_4Cultured_astrocytes 3xTg-AD Old
SA3862333B_6Cultured_astrocytes 3xTg-AD Old
SA3862343A_2Cultured_astrocytes 3xTg-AD Old
SA3862353A_4Cultured_astrocytes 3xTg-AD Old
SA3862367B_2Cultured_astrocytes 3xTg-AD Old
SA3862373A_5Cultured_astrocytes 3xTg-AD Old
SA3862383C_2Cultured_astrocytes 3xTg-AD Old
SA3862393C_4Cultured_astrocytes 3xTg-AD Old
SA3862403C_6Cultured_astrocytes 3xTg-AD Old
SA3862414A_2Cultured_astrocytes 3xTg-AD Old
SA3862424A_4Cultured_astrocytes 3xTg-AD Old
SA3862434A_6Cultured_astrocytes 3xTg-AD Old
SA3862444B_2Cultured_astrocytes 3xTg-AD Old
SA3862454B_4Cultured_astrocytes 3xTg-AD Old
SA3862464B_6Cultured_astrocytes 3xTg-AD Old
SA3862474C_2Cultured_astrocytes 3xTg-AD Old
SA3862483A_1Cultured_astrocytes 3xTg-AD Old
SA3862493B_1Cultured_astrocytes 3xTg-AD Old
SA3862504C_6Cultured_astrocytes 3xTg-AD Old
SA3862514C_3Cultured_astrocytes 3xTg-AD Old
SA3862527C_5Cultured_astrocytes 3xTg-AD Old
SA3862537C_3Cultured_astrocytes 3xTg-AD Old
SA3862547C_1Cultured_astrocytes 3xTg-AD Old
SA3862557B_5Cultured_astrocytes 3xTg-AD Old
SA3862567B_3Cultured_astrocytes 3xTg-AD Old
SA3862577B_1Cultured_astrocytes 3xTg-AD Old
SA3862587A_5Cultured_astrocytes 3xTg-AD Old
SA3862597A_3Cultured_astrocytes 3xTg-AD Old
SA3862607A_1Cultured_astrocytes 3xTg-AD Old
SA3862614C_5Cultured_astrocytes 3xTg-AD Old
SA3862624C_1Cultured_astrocytes 3xTg-AD Old
SA3862633B_3Cultured_astrocytes 3xTg-AD Old
SA3862644B_5Cultured_astrocytes 3xTg-AD Old
SA3862654B_3Cultured_astrocytes 3xTg-AD Old
SA3862664B_1Cultured_astrocytes 3xTg-AD Old
SA3862674A_5Cultured_astrocytes 3xTg-AD Old
SA3862684A_3Cultured_astrocytes 3xTg-AD Old
SA3862694A_1Cultured_astrocytes 3xTg-AD Old
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Collection:

Collection ID:CO003637
Collection Summary:Neurotoxic astrocyte cultures were prepared from the cerebral cortex and hippocampus of 9- to 10-month-old 3xTg-AD female mice according to previously described methods [2]. Female animals were used since sex differences in the development of the pathology have been described in this AD murine model, with a greater expression of transgenes in females [3,4]. Astrocytes isolated from 9- to 10-month-old non-Tg mice were not used as controls in our studies due to the low yield achieved [2]. Instead, astrocytic cultures derived from neonatal non-Tg mice as well as astrocytes from neonatal 3xTg-AD mice were used as controls. These non-toxic controls allowed us to assess whether astrocytes from this mice model of AD exhibit alterations when isolated before the disease onset. Nontoxic control astrocyte cultures were derived from the cerebral cortex and hippocampus of neonatal (postnatal day 0–2) 3xTg-AD and non-Tg (C57BL/6J) mice following the methods described by Cassina et al. with minor modifications [2,5]. All cell cultures were amplified and maintained at 37°C in a humidified incubator with 5% CO2. References [2] P. Diaz-Amarilla, F. Arredondo, R. Dapueto, V. Boix, D. Carvalho, M.D. Santi, E. Vasilskis, R. Mesquita-Ribeiro, F. Dajas-Bailador, J.A. Abin-Carriquiry, H. Engler, E. Savio, Isolation and characterization of neurotoxic astrocytes derived from old triple transgenic Alzheimer’s disease mice, Neurochem. Int. 159 (2022). https://doi.org/10.1016/j.neuint.2022.105403. [3] J.C. Carroll, E.R. Rosario, S. Kreimer, A. Villamagna, E. Gentzschein, F.Z. Stanczyk, C.J. Pike, Sex differences in β-amyloid accumulation in 3xTg-AD mice: Role of neonatal sex steroid hormone exposure, Brain Res. 1366 (2010) 233–245. https://doi.org/10.1016/J.BRAINRES.2010.10.009. [4] L.K. Clinton, L.M. Billings, K.N. Green, A. Caccamo, J. Ngo, S. Oddo, J.L. McGaugh, F.M. LaFerla, Age-dependent sexual dimorphism in cognition and stress response in the 3xTg-AD mice, Neurobiol. Dis. 28 (2007) 76–82. https://doi.org/10.1016/J.NBD.2007.06.013. [5] P. Cassina, H. Peluffo, M. Pehar, L. Martinez-Palma, A. Ressia, J.S. Beckman, A.G. Estévez, L. Barbeito, Peroxynitrite triggers a phenotypic transformation in spinal cord astrocytes that induces motor neuron apoptosis, J. Neurosci. Res. 67 (2002) 21–29. https://doi.org/10.1002/jnr.10107.
Sample Type:Astrocytes

Treatment:

Treatment ID:TR003653
Treatment Summary:No treatment

Sample Preparation:

Sampleprep ID:SP003651
Sampleprep Summary:Extraction of metabolites from cultured cells was performed based on previous work by Go et al. (2015), Liu et al. (2019), as well as Sapcariu et al. (2014) [6-8]. One sample consisted of metabolites extracted and pooled from 3 wells of a 6-well plate, pooling a total of 9 samples per condition. Briefly, confluent cells were washed with 0.9% (m/v) NaCl at room temperature, followed by the addition of 300 µL of an ice-cold HPLC-grade acetonitrile-water solution mixture (1:2) per well. This allowed us to scrape cells, precipitate proteins, and extract metabolites. The extracts were kept at 4 °C for 30 min. and centrifuged at 16,100 g for 10 min to remove the protein and any remaining insoluble fraction. Supernatants were transferred to screw-cap vials and dried in a fast vacuum centrifuge (overnight, 35°C).

Combined analysis:

Analysis ID AN005771 AN005772
Analysis type MS MS
Chromatography type Reversed phase HILIC
Chromatography system Thermo Dionex Ultimate 3000 Thermo Dionex Ultimate 3000
Column Higgins Analytical C18 (50 x 2.1mm,2.6um) Thermo Accucore HILIC (50 x 2.1mm,2.6um)
MS Type ESI ESI
MS instrument type Orbitrap Orbitrap
MS instrument name Thermo Q Exactive Orbitrap Thermo Q Exactive Orbitrap
Ion Mode NEGATIVE POSITIVE
Units m/z m/z

Chromatography:

Chromatography ID:CH004379
Chromatography Summary:Solvent A: Water; Solvent B: Acetonitrile; Solvent C: 10 mM ammonium acetate in water
Instrument Name:Thermo Dionex Ultimate 3000
Column Name:Higgins Analytical C18 (50 x 2.1mm,2.6um)
Column Temperature:60
Flow Gradient:Mobile phase conditions for the C18 column were 60% A, 35% B, 5% C for 0.5 min, with a linear gradient to 0% A, 95% B, 5% C starting at 1.5 min, and held for 3.5 min, resulting in a 5 min run. The reverse phase column was flushed with 0% A, 95% B, 5% C for 2.5 min, followed by an equilibration solution of 60% A, 35% B, 5% C for the remaining 2.5 min.
Flow Rate:Flow rate was maintained at 0.4 mL/min for 1.5 min and was then increased to 0.5 mL/min at 2 min and held constant for 3 min
Solvent A:100% water
Solvent B:100% acetonitrile
Chromatography Type:Reversed phase
Solvent C:100% water; 10 mM ammonium acetate
  
Chromatography ID:CH004380
Chromatography Summary:Solvent A: Water; Solvent B: Acetonitrile; Solvent C: 2% formic acid (v/v) in water
Instrument Name:Thermo Dionex Ultimate 3000
Column Name:Thermo Accucore HILIC (50 x 2.1mm,2.6um)
Column Temperature:60
Flow Gradient:Mobile phase conditions consisted of 22.5% A, 75% B, 2.5% C which was held for 1.5 min, with a linear gradient to 77.5% A, 20% B, 2.5% C at 4 min, and held for 1 min
Flow Rate:Flow rate of the HILIC column was maintained at 0.35 mL/min until 1.5 min, increased to 0.4 mL/min at 4 min and held for 1 min, resulting in a total analytical run time of 5 min
Solvent A:100% water
Solvent B:100% acetonitrile
Chromatography Type:HILIC
Solvent C:98% water/2% formic acid

MS:

MS ID:MS005491
Analysis ID:AN005771
Instrument Name:Thermo Q Exactive Orbitrap
Instrument Type:Orbitrap
MS Type:ESI
MS Comments:MS acquisition Comments: Collected mass spectral data were analyzed for features using Xcaliber (ThermoFisher; Waltham MA). Ultra-high resolution mass spectrometry operating at 60,000 and 120,000 resolution has previously been shown to provide effective metabolite quantification in biological extracts [11] and the use of complementary chromatography and ionization phases have been shown to improve the detection of endogenous and exogenous chemicals. Data processing Comments: Raw mass spectral data files were converted to computable document format (CDF) using Xcalibur file conversion software (Thermo Fisher Scientific, San Diego, CA) for further processing. Software/procedures used for feature assignments: Data were processed for peak extraction, noise filtering, m/z and retention time alignment, and quantification of ion intensities using apLCMS [29] with enhanced data extraction using xMSanalyzer [30]. xMSanalyzer improves feature detection through systematic data re-extraction, statistical filtering and fusion [30]. Metabolite feature peak intensity values ​​were summarized by the median in triplicate (technical replicates) and subjected to quality assessment. The samples were filtered considering an overall Pearson correlation of technical replicates of (r) > 0.70 and a cut-off coefficient of variation of 75%. Considering the number of missing values, one sample outlier was further removed from the C18 and HILIC cell extraction feature tables. Attached is the xMSAnalyzer table of the detected peak intensities. As stated above, the values ​​represent the median of three technical replicates evaluated per original sample. For example, samples labeled 2A_2, 2A_4 and 2A_6 in the design table are summarized under label 2A in the features table. For further details on the procedure, please refer to the xMSAnalyzer publication. Uppal, K., Soltow, Q.A., Strobel, F.H. et al. xMSanalyzer: automated pipeline for improved feature detection and downstream analysis of large-scale, non-targeted metabolomics data. BMC Bioinformatics 14, 15 (2013). https://doi.org/10.1186/1471-2105-14-15
Ion Mode:NEGATIVE
  
MS ID:MS005492
Analysis ID:AN005772
Instrument Name:Thermo Q Exactive Orbitrap
Instrument Type:Orbitrap
MS Type:ESI
MS Comments:MS acquisition Comments: Collected mass spectral data were analyzed for features using Xcaliber (ThermoFisher; Waltham MA). Ultra-high resolution mass spectrometry operating at 60,000 and 120,000 resolution has previously been shown to provide effective metabolite quantification in biological extracts [11] and the use of complementary chromatography and ionization phases have been shown to improve the detection of endogenous and exogenous chemicals. Data processing Comments: Raw mass spectral data files were converted to computable document format (CDF) using Xcalibur file conversion software (Thermo Fisher Scientific, San Diego, CA) for further processing. Software/procedures used for feature assignments: Data were processed for peak extraction, noise filtering, m/z and retention time alignment, and quantification of ion intensities using apLCMS [29] with enhanced data extraction using xMSanalyzer [30]. xMSanalyzer improves feature detection through systematic data re-extraction, statistical filtering and fusion [30]. Metabolite feature peak intensity values ​​were summarized by the median in triplicate (technical replicates) and subjected to quality assessment. The samples were filtered considering an overall Pearson correlation of technical replicates of (r) > 0.70 and a cut-off coefficient of variation of 75%. Considering the number of missing values, one sample outlier was further removed from the C18 and HILIC cell extraction feature tables. Attached is the xMSAnalyzer table of the detected peak intensities. As stated above, the values ​​represent the median of three technical replicates evaluated per original sample. For example, samples labeled 2A_1, 2A_3 and 2A_5 in the design table are summarized under label 2A in the features table. For further details on the procedure, please refer to the xMSAnalyzer publication. Uppal, K., Soltow, Q.A., Strobel, F.H. et al. xMSanalyzer: automated pipeline for improved feature detection and downstream analysis of large-scale, non-targeted metabolomics data. BMC Bioinformatics 14, 15 (2013). https://doi.org/10.1186/1471-2105-14-15
Ion Mode:POSITIVE
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