Summary of Study ST002504
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 PR001618. The data can be accessed directly via it's Project DOI: 10.21228/M8JT6D 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 | ST002504 |
| Study Title | Lipid droplets and peroxisomes are co-regulated to drive lifespan extension in response to mono-unsaturated fatty acids |
| Study Summary | Dietary mono-unsaturated fatty acids (MUFAs) are linked to human longevity and extend lifespan in several species. But the mechanisms by which MUFAs extend lifespan remain unclear. Here we show that an organelle network involving lipid droplets and peroxisomes is critical for lifespan extension by MUFAs in C. elegans. MUFA accumulation increases lipid droplet number in fat storage tissues, and this is necessary for MUFA-induced longevity. Lipid droplet number in young or middle-aged individuals can predict remaining lifespan, consistent with a beneficial effect of lipid droplets on lifespan. Lipidomics datasets reveal that MUFA accumulation also modifies the ratio of membrane lipids and ether lipids, a signature predictive of decreased lipid oxidation. We validate that MUFAs decrease lipid oxidation in middle-aged individuals, and that this is important for MUFA-induced longevity. Intriguingly, the increase in lipid droplet number in response to MUFAs is accompanied by a concomitant increase in peroxisome number. Using a targeted screen, we identify genes involved in the co-regulation or uncoupling of this lipid droplet-peroxisome network. We find that induction of both organelles is optimal for lifespan extension. Our study uncovers an organelle network involved in lipid homeostasis and lifespan regulation and identifies a mechanism of action for MUFAs to extend lifespan, opening new avenues for lipid-based interventions to delay aging. For the manuscript only the conditions “control” and “ash-2 RNAi” are plotted |
| Institute | Stanford University |
| Last Name | Papsdorf |
| First Name | Katharina |
| Address | 290 Jane Stanford way, 94301 Palo Alto, CA, USA |
| papsdorf@stanford.edu | |
| Phone | +1 650 546 5366 |
| Submit Date | 2023-02-03 |
| Raw Data Available | Yes |
| Raw Data File Type(s) | raw(Thermo) |
| Analysis Type Detail | LC-MS |
| Release Date | 2023-03-20 |
| Release Version | 1 |
Select appropriate tab below to view additional metadata details:
Project:
| Project ID: | PR001618 |
| Project DOI: | doi: 10.21228/M8JT6D |
| Project Title: | Untargeted lipidomics of C. elegans upon depletion of ash-2 and prx-5. |
| Project Summary: | Untargeted lipidomics in middle-aged C. elegans upon enrichment of monounsaturated fatty acids by ash-2 RNAi and peroxisome depletion by prx-5 RNAi. |
| Institute: | Stanford University |
| Last Name: | Papsdorf |
| First Name: | Katharina |
| Address: | 290 Jane Stanford way, 94301 Palo Alto, CA, USA |
| Email: | papsdorf@stanford.edu |
| Phone: | +1 650 546 5366 |
Subject:
| Subject ID: | SU002603 |
| Subject Type: | Invertebrate |
| Subject Species: | Caenorhabditis elegans |
| Taxonomy ID: | 6239 |
| Age Or Age Range: | middle-aged (adult day 5) |
Factors:
Subject type: Invertebrate; Subject species: Caenorhabditis elegans (Factor headings shown in green)
| mb_sample_id | local_sample_id | Genotype | Treatment |
|---|---|---|---|
| SA251719 | QC_MSMS | - | - |
| SA251720 | blank | - | - |
| SA251733 | P-A7 | Wild-type | ash-2/prx-5 RNAi |
| SA251734 | P-A15 | Wild-type | ash-2/prx-5 RNAi |
| SA251735 | P-A3 | Wild-type | ash-2/prx-5 RNAi |
| SA251736 | P-A23 | Wild-type | ash-2/prx-5 RNAi |
| SA251737 | P-A19 | Wild-type | ash-2/prx-5 RNAi |
| SA251738 | P-A11 | Wild-type | ash-2/prx-5 RNAi |
| SA251727 | ASH18 | Wild-type | ash-2 RNAi |
| SA251728 | ASH14 | Wild-type | ash-2 RNAi |
| SA251729 | ASH10 | Wild-type | ash-2 RNAi |
| SA251730 | ASH22 | Wild-type | ash-2 RNAi |
| SA251731 | ASH2 | Wild-type | ash-2 RNAi |
| SA251732 | ASH6 | Wild-type | ash-2 RNAi |
| SA251721 | EV21 | Wild-type | Control |
| SA251722 | EV5 | Wild-type | Control |
| SA251723 | EV17 | Wild-type | Control |
| SA251724 | EV9 | Wild-type | Control |
| SA251725 | EV13 | Wild-type | Control |
| SA251726 | EV1 | Wild-type | Control |
| SA251739 | PRX8 | Wild-type | prx-5 RNAi |
| SA251740 | PRX24 | Wild-type | prx-5 RNAi |
| SA251741 | PRX12 | Wild-type | prx-5 RNAi |
| SA251742 | PRX16 | Wild-type | prx-5 RNAi |
| SA251743 | PRX20 | Wild-type | prx-5 RNAi |
| SA251744 | PRX4 | Wild-type | prx-5 RNAi |
| Showing results 1 to 26 of 26 |
Collection:
| Collection ID: | CO002596 |
| Collection Summary: | At middle-age (adult day 5), worms were transferred to empty RNAi plates without any bacteria for 15 minutes, to clear residual bacteria in the gut. Worms were then collected in 200 µl M9 in protein-low bind Eppendorf tubes (cat # 13-698-794). Worms were lysed using a pre-chilled stainless-steel homogenizer (Wheaton, cat # 357572) and were homogenized with 15 plunger strokes and protein concentration of the lysate was determined using the Pierce BCA Protein Assay Kit (Thermo- Scientific). The lysate (from approximately 500 worms) was frozen on dry ice and stored at -80°C |
| Sample Type: | Whole worm lysate |
Treatment:
| Treatment ID: | TR002615 |
| Treatment Summary: | Hermaphrodites were treated with control (empty vector) RNAi, prx-5, ash-2 or prx-5/ash-2 RNAi until middle-age (adult day 6). Each condition consists of six biological replicates. To retrieve a large number of age-synchronized worms, approximately 500 eggs were laid by age-synchronized adult day 1 wild type parents per replicate plate. After 2 hours of egg laying, the parents were removed, and the plates were checked that no parents remained. Once the worms reached the young adult stage, they were washed each day to separate the adult worms from larvae/eggs. For this, worms were collected in M9 buffer (22 mM KH2PO4, 34 mM K2HPO4, 86 mM NaCl, 1mM MgSO4) and allowed to settle to the bottom of the tube. The supernatant was removed and fresh M9 was added. This washing procedure was repeated 6 times and the adult worms were transferred to fresh 6-cm RNAi plates seeded with 500 µl RNAi-expressing HT115 bacteria. |
Sample Preparation:
| Sampleprep ID: | SP002609 |
| Sampleprep Summary: | Lipids from the whole worm lysates were extracted using a biphasic separation with methyl tert-butyl ether (MTBE), methanol and water as described previously (PMID 30532037, PMID 32612231). All reagents used are for lipidomics were LC/MS grade. Briefly, 298 μl of ice-cold methanol and 2 μl of internal standard (equiSPLASH, Avanti Polar Lipids, cat# 330731) were added to 50 μl of worm lysate. The mixture was vortexed for 20 seconds and 1000 μl of ice-cold MTBE was added. The mixture was incubated under agitation for 30 minutes at 4°C. After addition of 250 μl of water, the samples were vortexed for 1 minute and centrifuged at 14,000 g for 10 minutes at room temperature. The upper phase containing the lipids was collected and dried down under nitrogen. The dry extracts were reconstituted with 300 μl of 9:1 methanol:toluene (Fisher Scientific) with 10 mM of ammonium acetate (Sigma Aldrich) and centrifuged at 14,000 g for 5 minutes before analysis. Water extracted using the same protocol was used as a blank control. Samples were randomized in all cases during lipid extraction. |
Combined analysis:
| Analysis ID | AN004120 | AN004121 |
|---|---|---|
| Analysis type | MS | MS |
| Chromatography type | Reversed phase | Reversed phase |
| Chromatography system | Thermo Dionex Ultimate 3000 RS | Thermo Dionex Ultimate 3000 RS |
| Column | Thermo Accucore C30 (150 x 2.1mm,2.6um) | Thermo Accucore C30 (150 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 | POSITIVE | NEGATIVE |
| Units | peak area | peak area |
Chromatography:
| Chromatography ID: | CH003052 |
| Chromatography Summary: | Lipid extracts were analyzed in a randomized order using an Ultimate 3000 RSLC system coupled with a Q Exactive mass spectrometer (Thermo Fisher Scientific) as previously described (PMID: 32612231). To identify complex lipids, isolated lipids were analyzed with untargeted lipidomics using liquid chromatography coupled to a Q Exactive mass spectrometer (Thermo Fisher Scientific) (LC/MS). Lipids were separated using an Accucore C30 column 2.1 x 150 mm, 2.6 μm (Thermo Scientific, cat# 27826-152130) and mobile phase solvents consisted in 1 mM ammonium formate and 0.1% formic acid in 60/40 acetonitrile/water (A) and 1 mM ammonium formate and 0.1% formic acid in 90/10 isopropanol/acetonitrile (B). The gradient profile used was 30% B for 3 minutes, 30–43% B over 5 minutes, 43–50% B over 1 minute, 55–90% B over 9 minutes, 90-99% B over 9 minutes and 99% B for 5 minutes. Lipids were eluted from the column at 0.2 ml/min, the oven temperature was set at 30°C, and the injection volume was 15 μl. Autosampler temperature was set at 15°C to prevent lipid aggregation. |
| Instrument Name: | Thermo Dionex Ultimate 3000 RS |
| Column Name: | Thermo Accucore C30 (150 x 2.1mm,2.6um) |
| Column Temperature: | 30 |
| Flow Gradient: | The gradient profile used was 30% B for 3 minutes, 30–43% B over 5 minutes, 43–50% B over 1 minute, 55–90% B over 9 minutes, 90-99% B over 9 minutes and 99% B for 5 minutes. |
| Flow Rate: | 0.2 ml/min |
| Sample Injection: | 5ul |
| Solvent A: | 60% acetonitrile/40% water; 1mM ammonium formate; 0.1% formic acid |
| Solvent B: | 90% isopropanol/10% acetonitrile; 1mM ammonium formate; 0.1% formic acid |
| Chromatography Type: | Reversed phase |
MS:
| MS ID: | MS003867 |
| Analysis ID: | AN004120 |
| Instrument Name: | Thermo Q Exactive Orbitrap |
| Instrument Type: | Orbitrap |
| MS Type: | ESI |
| MS Comments: | LC-MS peak extraction, alignment, quantification and annotation was performed using LipidSearch software version 4.2.21 (Thermo Fisher Scientific). Lipids were identified by matching the precursor ion mass to a database and the experimental MS/MS spectra to a spectral library containing theoretical fragmentation spectra. To reduce the risk of misidentification, MS/MS spectra from lipids of interest were validated as follows: 1) both positive and negative mode MS/MS spectra match the expected fragments, 2) the main lipid adduct forms detected in positive and negative modes agree with the lipid class identified, 3) the retention time is compatible with the lipid class identified and 4) the peak shape is acceptable. The fragmentation pattern of each lipid class was experimentally validated using lipid internal standards. Single-point internal standard calibrations were used to estimate absolute concentrations using one internal standard for each lipid class. In cases with no exact lipid standard available lipids with molecular similarity were used. Further data processing was done using an in-house analysis pipeline written in R (Version 3.6.3, available in Github at https://github.com/brunetlab). Briefly, processing for samples and spike-in standards were done in the same way. All ions for one lipid were aggregated and lipids with a signal <0 discarded from further analysis. Lipid species were quantified using the corresponding internal standard (equiSPLASH, Avanti Polar Lipids, cat# 330731) for each lipid class. Lipids with signals lower than 3x blank signal were discarded. Lipids with more than 50% of missing values were discarded, and for the remaining missing values, imputation was performed. For this, a value was randomly assigned based on the bottom 5% for the corresponding lipid. Lipids were filtered for a coefficient of variance <0.5. Each sample was divided by its corresponding protein concentration to correct for sample input variations (protein concentrations can be found at https://github.com/brunetlab/Papsdorf_etal_2023). To calculate normalized abundance, each lipid within a sample was divided by the sample median followed by multiplication with the global median. This resulted in a total of 499 filtered and normalized lipids belonging to 16 lipid classes. For a list of identified lipid ions using LipidSearch see https://github.com/brunetlab/Papsdorf_etal_2023. |
| Ion Mode: | POSITIVE |
| MS ID: | MS003868 |
| Analysis ID: | AN004121 |
| Instrument Name: | Thermo Q Exactive Orbitrap |
| Instrument Type: | Orbitrap |
| MS Type: | ESI |
| MS Comments: | LC-MS peak extraction, alignment, quantification and annotation was performed using LipidSearch software version 4.2.21 (Thermo Fisher Scientific). Lipids were identified by matching the precursor ion mass to a database and the experimental MS/MS spectra to a spectral library containing theoretical fragmentation spectra. To reduce the risk of misidentification, MS/MS spectra from lipids of interest were validated as follows: 1) both positive and negative mode MS/MS spectra match the expected fragments, 2) the main lipid adduct forms detected in positive and negative modes agree with the lipid class identified, 3) the retention time is compatible with the lipid class identified and 4) the peak shape is acceptable. The fragmentation pattern of each lipid class was experimentally validated using lipid internal standards. Single-point internal standard calibrations were used to estimate absolute concentrations using one internal standard for each lipid class. In cases with no exact lipid standard available lipids with molecular similarity were used. Further data processing was done using an in-house analysis pipeline written in R (Version 3.6.3, available in Github at https://github.com/brunetlab). Briefly, processing for samples and spike-in standards were done in the same way. All ions for one lipid were aggregated and lipids with a signal <0 discarded from further analysis. Lipid species were quantified using the corresponding internal standard (equiSPLASH, Avanti Polar Lipids, cat# 330731) for each lipid class. Lipids with signals lower than 3x blank signal were discarded. Lipids with more than 50% of missing values were discarded, and for the remaining missing values, imputation was performed. For this, a value was randomly assigned based on the bottom 5% for the corresponding lipid. Lipids were filtered for a coefficient of variance <0.5. Each sample was divided by its corresponding protein concentration to correct for sample input variations (protein concentrations can be found at https://github.com/brunetlab/Papsdorf_etal_2023). To calculate normalized abundance, each lipid within a sample was divided by the sample median followed by multiplication with the global median. This resulted in a total of 499 filtered and normalized lipids belonging to 16 lipid classes.For a list of identified lipid ions using LipidSearch see https://github.com/brunetlab/Papsdorf_etal_2023. |
| Ion Mode: | NEGATIVE |
