Obesity Increases Mitogen-Activated Protein Kinase Phosphatase-3 Levels in the Hypothalamus of Mice

Abstract

Mitogen-activated Protein Kinase Phosphatase 3 (MKP-3) has been involved in the negative regulation of insulin signaling. The absence of MKP-3 is also associated with reduced adiposity, increased energy expenditure and improved insulin sensitivity. The MKP-3 is known as the main Erk1/2 phosphatase and FoxO1 activator, which has repercussions on the gluconeogenesis pathway and hyperglycemia in obese mice. Recently, we showed that MKP-3 overexpression decreases FoxO1 phosphorylation in the hypothalamus of lean mice. However, the hypothalamic interaction between MKP-3 and FoxO1 during obesity was not investigated yet. Here, the MKP-3 expression and the effects on food intake and energy expenditure, were investigated in high-fat diet-induced obese mice. The results indicate that obesity in mice increased the MKP-3 protein content in the hypothalamus. This hypothalamic upregulation led to an increase of food intake, adiposity, and body weight. Furthermore, the obese mice with increased MKP-3 showed an insulin signaling impairment with reduction of insulin-induced FoxO1 and Erk1/2 phosphorylation in the hypothalamus. Moreover, a bioinformatics analysis of data demonstrated that hypothalamic MKP-3 mRNA levels were positively correlated with body weight and negatively correlated to oxygen consumption (VO2) in BXD mice. Taken together, our study reports that obesity is associated with increased protein levels of hypothalamic MKP-3, which is related to the reduction of FoxO1 and Erk1/2 phosphorylation in the hypothalamus as well as to an increase in body weight and a reduction in energy expenditure.

A platform for experimental precision medicine: The extended BXD mouse family

“…The BXD Family Is the Largest and the Most Deeply Phenotyped Mammalian Genetic Reference Panel Data sets for the BXD encompass multiple levels-from single molecules to complex behavioral repertoires and to traits measured with environmental perturbations, including exposure to alcohol and drugs of abuse (Dickson et al, 2019;Mulligan et al, 2018;Thé berge et al, 2019;Zhou et al, 2018), infectious agents (Boon et al, 2014;Chella Krishnan et al, 2016;Russo et al, 2015), dietary modifications (Fleet et al, 2016;Jha et al, 2018bJha et al, , 2018aJones and Jellen, 2017;Reyes Fernandez et al, 2016;Rodrigues et al, 2017), stress (Diessler et al, 2018;Jung et al, 2017), and even as a function of age (Sandoval-Sierra et al, 2020;Williams et al, 2020). This phenome is linked to over 500 publications, including state-of-the-art proteome, metabolome (Williams et al, 2018(Williams et al, , 2020, epigenome (Baker et al, 2019;Sandoval-Sierra et al, 2019), and metagenome (Perez-Munoz et al, 2019) data sets available on GeneNetwork.org.…”

Impact of Conventional and Atypical MAPKs on the Development of Metabolic Diseases

“…Fasting activates ERK1/2 in the ARC and the paraventricular nucleus in mice [86,87] and the activation is reversed by refeeding [87]. Obesity is associated with increased protein levels of hypothalamic MAPK phosphatase-3 (MKP-3), which is related to the reduction of ERK1/2 phosphorylation in the hypothalamus as well as to an increase in body weight and a reduction in energy expenditure [88]. In parallel, leptin acts on the hypothalamus through its receptor, increasing the phosphorylation (Thr202/Tyr204) of ERK1/2 [89,90].…”

Private and sub-family specific mutations of founder haplotypes in the BXD family reveal phenotypic consequences relevant to health and disease

“…The BXDs are well suited to studying gene-by-environmental interactions (GXE) and for experimental precision medicine 11 . For almost 50 years, they have been used to study the genetic and environmental factors that underlie a diverse collection of phenotypes, including environmental toxicant exposures, alcohol and drugs of abuse [64][65][66][67][68] , infectious agents [69][70][71][72][73] , diets [74][75][76][77][78][79] , and stressors 80,81 . Beyond this, there are also extensive -omics data available for many BXD family members, including over 100 transcriptome datasets (e.g, 82,83 ), as well as more recent miRNA 84,85 , proteome [86][87][88] , metabolome 83,88,89 , epigenome 16,90 , and metagenome 91,92 profiles.…”