Primary cilia sense glutamine availability and respond via asparagine synthetase.

Depriving cells of nutrients triggers an energetic crisis, which is resolved by metabolic rewiring and organelle reorganization. Primary cilia are microtubule-based organelles at the cell surface, capable of integrating multiple metabolic and signalling cues, but their precise sensory function is not fully understood. Here we show that primary cilia respond to nutrient availability and adjust their length via glutamine-mediated anaplerosis facilitated by asparagine synthetase (ASNS). Nutrient deprivation causes cilia elongation, mediated by reduced mitochondrial function, ATP availability and AMPK activation independently of mTORC1. Of note, glutamine removal and replenishment is necessary and sufficient to induce ciliary elongation or retraction, respectively, under nutrient stress conditions both in vivo and in vitro by restoring mitochondrial anaplerosis via ASNS-dependent glutamate generation. Ift88-mutant cells lacking cilia show reduced glutamine-dependent mitochondrial anaplerosis during metabolic stress, due to reduced expression and activity of ASNS at the base of cilia. Our data indicate a role for cilia in responding to, and possibly sensing, cellular glutamine levels via ASNS during metabolic stress.

Metabolic Reprogramming and Reconstruction: Integration of Experimental and Computational Studies to Set the Path Forward in ADPKD.

Metabolic reprogramming is a key feature of Autosomal Dominant Polycystic Kidney Disease (ADPKD) characterized by changes in cellular pathways occurring in response to the pathological cell conditions. In ADPKD, a broad range of dysregulated pathways have been found. The studies supporting alterations in cell metabolism have shown that the metabolic preference for abnormal cystic growth is to utilize aerobic glycolysis, increasing glutamine uptake and reducing oxidative phosphorylation, consequently resulting in ADPKD cells shifting their energy to alternative energetic pathways. The mechanism behind the role of the polycystin proteins and how it leads to disease remains unclear, despite the identification of numerous signaling pathways. The integration of computational data analysis that accompanies experimental findings was pivotal in the identification of metabolic reprogramming in ADPKD. Here, we summarize the important results and argue that their exploitation may give further insights into the regulative mechanisms driving metabolic reprogramming in ADPKD. The aim of this review is to provide a comprehensive overview on metabolic focused studies and potential targets for treatment, and to propose that computational approaches could be instrumental in advancing this field of research.

Dissection of metabolic reprogramming in polycystic kidney disease reveals coordinated rewiring of bioenergetic pathways.

Autosomal Dominant Polycystic Kidney Disease (ADPKD) is a genetic disorder caused by loss-of-function mutations in PKD1 or PKD2. Increased glycolysis is a prominent feature of the disease, but how it impacts on other metabolic pathways is unknown. Here, we present an analysis of mouse Pkd1 mutant cells and kidneys to investigate the metabolic reprogramming of this pathology. We show that loss of Pkd1 leads to profound metabolic changes that affect glycolysis, mitochondrial metabolism, and fatty acid synthesis (FAS). We find that Pkd1-mutant cells preferentially use glutamine to fuel the TCA cycle and to sustain FAS. Interfering with either glutamine uptake or FAS retards cell growth and survival. We also find that glutamine is diverted to asparagine via asparagine synthetase (ASNS). Transcriptional profiling of PKD1-mutant human kidneys confirmed these alterations. We find that silencing of Asns is lethal in Pkd1-mutant cells when combined with glucose deprivation, suggesting therapeutic approaches for ADPKD.

mTORC1 Upregulation Leads to Accumulation of the Oncometabolite Fumarate in a Mouse Model of Renal Cell Carcinoma.

Renal cell carcinomas (RCCs) are common cancers diagnosed in more than 350,000 people each year worldwide. Several pathways are de-regulated in RCCs, including mTORC1. However, how mTOR drives tumorigenesis in this context is unknown. The lack of faithful animal models has limited progress in understanding and targeting RCCs. Here, we generated a mouse model harboring the kidney-specific inactivation of Tsc1. These animals develop cysts that evolve into papillae, cystadenomas, and papillary carcinomas. Global profiling confirmed several metabolic derangements previously attributed to mTORC1. Notably, Tsc1 inactivation results in the accumulation of fumarate and in mTOR-dependent downregulation of the TCA cycle enzyme fumarate hydratase (FH). The re-expression of FH in cellular systems lacking Tsc1 partially rescued renal epithelial transformation. Importantly, the mTORC1-FH axis is likely conserved in human RCC specimens. We reveal a role of mTORC1 in renal tumorigenesis, which depends on the oncometabolite fumarate.

In Silico Modeling of Liver Metabolism in a Human Disease Reveals a Key Enzyme for Histidine and Histamine Homeostasis.

Primary hyperoxaluria type I (PH1) is an autosomal-recessive inborn error of liver metabolism caused by alanine:glyoxylate aminotransferase (AGT) deficiency. In silico modeling of liver metabolism in PH1 recapitulated accumulation of known biomarkers as well as alteration of histidine and histamine levels, which we confirmed in vitro, in vivo, and in PH1 patients. AGT-deficient mice showed decreased vascular permeability, a readout of in vivo histamine activity. Histamine reduction is most likely caused by increased catabolism of the histamine precursor histidine, triggered by rerouting of alanine flux from AGT to the glutamic-pyruvate transaminase (GPT, also known as the alanine-transaminase ALT). Alanine administration reduces histamine levels in wild-type mice, while overexpression of GPT in PH1 mice increases plasma histidine, normalizes histamine levels, restores vascular permeability, and decreases urinary oxalate levels. Our work demonstrates that genome-scale metabolic models are clinically relevant and can link genotype to phenotype in metabolic disorders.

A genome-scale modeling approach to study inborn errors of liver metabolism: toward an in silico patient.

Inborn errors of metabolism (IEM) are genetic diseases caused by mutations in enzymes or transporters affecting specific metabolic reactions that cause a block in the physiological metabolic fluxes. Therapeutic treatment can be achieved either by decreasing the metabolic flux upstream of the block or by increasing the flux downstream of the block. The identification of upstream and downstream fluxes however is not trivial, since metabolic reactions are intertwined in a complex network. To overcome this problem, we propose an innovative computational workflow to model the alteration of metabolism caused by IEM and predict the metabolites and reactions that are affected by the mutation. Our workflow exploits a recent genome-scale metabolic network model of hepatocyte metabolism to identify metabolites accumulating in hepatocytes due to single gene mutations in IEM via an innovative "differential flux analysis." We simulated 38 IEMs in the liver, and in about half of the cases, our workflow correctly identified the metabolites known to accumulate in the blood and urine of IEM patients.