Summary of Study ST002268
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 PR001450. The data can be accessed directly via it's Project DOI: 10.21228/M89703 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 | ST002268 |
| Study Title | Autophagy-related protein PIK3C3 maintains healthy brown and white adipose tissues to prevent metabolic diseases |
| Study Type | Lipidomics |
| Study Summary | Adequate mass and function of adipose tissues (ATs) play an essential role in preventing metabolic perturbations. Pathological reduction of ATs in lipodystrophy leads to an array of metabolic diseases. Understanding the underlying mechanisms may benefit the development of effective therapies. Several cellular processes, including autophagy, function collectively to maintain AT homeostasis. Here, we investigated the impact of adipocyte-specific deletion of the autophagy-related lipid kinase PIK3C3 on AT homeostasis and systemic metabolism in mice. We report that PIK3C3 functions in all ATs and that its absence disturbs adipocyte autophagy and hinders adipocyte differentiation, survival, and function with differential effects on brown and white ATs. These abnormalities caused loss of white ATs, whitening followed by loss of brown ATs, and impaired browning of white ATs. Consequently, mice exhibited compromised thermogenic capacity and developed dyslipidemia, hepatic steatosis, insulin resistance and type 2 diabetes. While these effects of PIK3C3 contrast previous findings with the autophagy-related protein ATG7 in adipocytes, mice with a combined deficiency in both factors revealed a dominant role of the PIK3C3-deficient phenotype. We also found that dietary lipid excess exacerbates AT pathologies caused by PIK3C3 deficiency. Surprisingly, glucose tolerance was spared in adipocyte-specific PIK3C3-deficient mice, a phenotype that was more evident during dietary lipid excess. These findings reveal a crucial yet complex role for PIK3C3 in ATs and suggest the potential of targeting this factor for therapeutic intervention in metabolic diseases. |
| Institute | Vanderbilt University |
| Department | Chemistry |
| Laboratory | Center for Innovative Technology |
| Last Name | Leaptrot |
| First Name | Katrina |
| Address | 1234 Stevenson Center Ln |
| katrina.l.leaptrot@vanderbilt.edu | |
| Phone | 6158758422 |
| Submit Date | 2022-08-26 |
| Num Groups | 4 |
| Total Subjects | 16 |
| Raw Data Available | Yes |
| Raw Data File Type(s) | d |
| Analysis Type Detail | LC-MS |
| Release Date | 2023-02-26 |
| Release Version | 1 |
Select appropriate tab below to view additional metadata details:
Combined analysis:
| Analysis ID | AN003705 |
|---|---|
| Analysis type | MS |
| Chromatography type | Reversed phase |
| Chromatography system | Agilent 1290 |
| Column | Thermo Hypersil Gold (100 x 2.mm,1.9um) |
| MS Type | ESI |
| MS instrument type | QTOF |
| MS instrument name | Agilent 6560 Ion Mobility |
| Ion Mode | POSITIVE |
| Units | retention time underscore m/z |
MS:
| MS ID: | MS003454 |
| Analysis ID: | AN003705 |
| Instrument Name: | Agilent 6560 Ion Mobility |
| Instrument Type: | QTOF |
| MS Type: | ESI |
| MS Comments: | Data analysis was performed using Progenesis QI software (version 3.0, Nonlinear Dynamics, Newcastle, UK). Retention time alignment, peak picking, and peak deconvolution used default parameters. Spectra were normalized to all compounds, and data were filtered for coefficients of variance < 25% in QC technical replicate injections. A prioritized compound list was generated via a one-factor ANOVA, with four experimental groups for comparison including wild type and Vps34 knockout for both brown and visceral adipose tissue. Lipids were considered to be differentially altered if the p-value < 0.05 and the fold change was greater than Ι2Ι. Significantly changed compounds were selected for annotation. Lipidomic annotations were performed using a previously described classification system with compounds being assigned a confidence level of 1 to 5 (1 being the highest confidence) with improved confidence requiring more supporting evidence such as accurate mass, MS/MS fragmentation, and retention time matching to standards. Lipid annotated were performed with reference to in-house and online databases (MS-DIAL, LipidMatch, and Lipid Annotator). Differentially abundant lipids (DALs) were uploaded into the LIPEA algorithm for pathway enrichment analysis. Corrected p-values were calculated using Benjamini correction and a p-value <0.05 was used to determine significantly affected pathways. |
| Ion Mode: | POSITIVE |
