Welcome to OPABAT!

Obesity is a polygenic disorder with variable penetrance in the general population. Brown adipose tissue (BAT) is a major regulator of energy expenditure and metabolic physiology due to a specialized proteome that orchestrates futile metabolic cycles, which could be leveraged to treat obesity. However, nearly all mechanistic studies of BAT protein function occur in a single inbred mouse strain, which has limited understanding of generalizable mechanisms of BAT regulation over metabolism. Here we perform deep quantitative multiplexed proteomics of BAT across a cohort of 163 genetically defined Diversity Outbred (DO) mice, a model that parallels the genetic and phenotypic variation found in the human population. Leveraging the high variation afforded by this model, we define the functional architecture of the outbred BAT proteome, comprising 10,479 proteins. In doing so, we assign novel co-operative functions to 2,578 proteins with 780 established protein networks. We demonstrate that this analytic framework enables systematic discovery of regulators of BAT function, exemplified by uncovering SFXN5 and LETMD1 as modulators of UCP1-dependent thermogenesis. We also identify 638 proteins that underlie protection from, or sensitivity to, at least one parameter of metabolic disease. From this basis, we identify the Na+/K+-ATPase α2 subunit as an inhibitor of BAT energy expenditure, that increases adiposity through antagonism of calcium influx-dependent activation of thermogenic effectors. We provide this Outbred Proteomic Architecture of BAT (OPABAT) as a resource to understanding conserved mechanisms of BAT regulation over metabolic physiology.

Citation

If this website is useful to you, please consider citing Xiao et al., Cell, 2022!

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Expression

Select a protein to see its expression level in OPABAT, and color mice by phenotypic data.

Correlations

Select any two proteins to see the correlation between their expression levels in OPABAT.

Networks

Select a protein to explore its significant immediate correlators in OPABAT network.

Complexes

Select a protein or a CORUM core complex to explore new accesory proteins to established protein complexes identified in OPABAT network.

Phenotypes

Explore the positive and negative protein correlators of each physiological parameter.

Strain Selection

Explore strains that are best candidates to model phenotypes.

Human Data

Explore correlations between human phenotypes and BAT transcript abundance of all OPABAT metabolic physiology correlators.

Please click here for full protein and phenotype QTL mapping results.

Acknowledgement

This project is a collaboration across the Chouchani, Gygi, Churchill, Spiegelman, McAllister, van Bruggen, Chondronikola, Rosen, Cohen, Tsai, Tseng, and Banks labs at Dana-Farber Cancer Institute, The Rockefeller University, Beth Israel Deaconess Medical Center, The Jackson Laborotory, UC Davis, Joselin Diabetes Center, and Harvard Medical School, along with Calico Life Sciences LLC.

The OPABAT web application is developed by Haopeng Xiao and Jiaming Li from the Chouchani and Gygi labs. The website is maintained by Nathan Bulloch. Source codes are deposited on GitHub (https://github.com/Angrycodeboy/OPABAT). The full visualization of QTL mapping is developed by Matthew Vincent from the Churchill lab.

This project is funded by Calico Life Sciences LLC and National Institute of Health.

Please contact Haopeng Xiao (haopeng_xiao@dfci.harvard.edu) for bug report.