bioRxiv Science⌕ Search

Biology subjects

Stöckli, J.

Publications and source records attributed to Stöckli, J..

6 recordsLinked to original sources

Renal nutrient loss promotes metabolic health at the expense of increased vulnerability to acute kidney injury

Obesity is a major risk factor for interrelated cardiorenal metabolic diseases including type 2 diabetes, heart failure and chronic kidney disease (1-4). Although obesity develops when energy intake chronically exceeds energy expenditure, individuals vary markedly in the amount of adiposity and metabolic dysfunction that develop in response to comparable caloric excess. Controlled overfeeding studies demonstrate several-fold variation in weight gain between individuals (5), while susceptibility to metabolic dysfunction also differs substantially between populations (6), suggesting considerable variation in how excess nutrients are partitioned. Energy balance is conventionally considered in terms of intake and expenditure, yet energy-containing nutrients can also be eliminated from the body. The kidney is uniquely positioned to regulate this third component of energy balance by determining whether filtered metabolites are reabsorbed or excreted. The metabolic benefits of SGLT2 inhibition demonstrate that reducing renal nutrient reabsorption can favourably alter systemic metabolic function (7,8), but whether naturally occurring variation in renal nutrient conservation contributes to metabolic disease susceptibility remains unknown. Here, screening eleven genetically divergent mouse strains identified BXD34 mice as strikingly resistant to diet-induced obesity, ectopic lipid accumulation and insulin resistance despite increased caloric intake. Mechanistically, this protection was associated with widespread urinary nutrient loss accompanied by coordinated suppression of renal solute transport, but came at the cost of profound susceptibility to acute kidney injury. Together, these findings identify renal nutrient conservation as an underappreciated determinant of whole-body metabolism and reveal a renometabolic trade-off in which protection from obesity is achieved at the expense of renal resilience.

physiology↗

Systems genetics identifies ETS1 as a stress-dependent regulator of adipocyte insulin action and heme-iron homeostasis

White adipose tissue plays a central role in systemic energy homeostasis by buffering nutrient excess through insulin-stimulated glucose uptake and triglyceride storage. Despite its importance, the genetic and molecular mechanisms governing adipose tissue insulin action remain poorly defined because tissue-specific insulin responsiveness has been difficult to quantify at the scale required for genetic discovery. Here, we developed the first scalable platform for high-throughput genetic mapping of tissue-specific insulin action in adipose tissue, enabling systems genetic analysis across 559 genetically diverse Diversity Outbred Australia (DOz) mice. Genetic analysis accounting for adiposity identified 39 loci associated with adipose tissue insulin action, demonstrating that adipose insulin responsiveness is a genetically encoded trait that captures a dimension of metabolic health beyond adiposity. Among these, a strong diet-dependent locus on chromosome 9 encompassed the transcription factor Ets1. Functional studies demonstrated that Ets1 silencing selectively restored insulin-stimulated glucose uptake in insulin-resistant adipocytes. Proteomic profiling revealed that ETS1 orchestrates a stress-responsive program involving heme metabolism, iron handling and redox homeostasis. Consistent with this, ETS1 knockdown reduced cellular heme and labile iron levels and attenuated oxidative stress under insulin-resistant conditions. Collectively, these findings demonstrate the power of systems genetics to identify previously unrecognised regulators of adipose insulin action and establish the heme-iron axis as a critical determinant of adipocyte insulin responsiveness.

systems biology↗

Synteny: a high throughput web tool to streamline causal gene prioritisation and provide insight into protein function

Accounting for human genetic evidence can improve the outcomes and impact of basic research studies. However, current approaches are incompatible with the high volume of disease-associated genes that require mechanistic interrogation. Synteny responds to an urgent need in systems biology, scaling human genetic analysis to match the throughput of modern omics technologies. This approach prioritises candidates with the strongest human disease relevance and unearths functionally important proteins (https://bigproteomics.shinyapps.io/Synteny/).

systems biology↗

Very long-chain ceramides in muscle associate with insulin resistance independent of obesity

Lipids, in particular ceramides and diacylglycerols (DAGs), are implicated in insulin resistance, however their precise roles remain unclear. We leverage natural genetic variation to examine muscle lipids and systemic insulin resistance (IR) in 399 Diversity Outbred Australia mice. Adipose mass was associated with 55% of muscle lipids and IR, with DAGs as the only enriched lipid class. To disentangle adiposity and muscle lipid contributions, we used two approaches: (1) linear modelling of muscle lipids corrected for adipose mass on systemic IR, and (2) stratifying mice into insulin sensitivity quartiles within adiposity bins. Both revealed that very long-chain ceramides, but not DAGs, were linked to IR. Transcriptomic and proteomics further associated these ceramides with cellular and mitochondrial stress. DAGs correlated with leptin expression in muscle, suggesting they originate from muscle-residing adipocytes. We propose that many muscle lipids, including DAGs, associate with IR due to adipose accumulation rather than directly influencing muscle insulin sensitivity. By addressing the relationship between adiposity and metabolic state, we identified very long-chain muscle ceramides as highly associated with IR independently of adiposity.

systems biology↗

Genetic variance in the murine defensin locus modulates glucose homeostasis

Insulin resistance is a heritable risk factor for many chronic diseases; however, the genetic drivers remain elusive. In seeking these, we performed genetic mapping of insulin sensitivity in 670 chow-fed Diversity Outbred in Australia (DOz) mice and identified a genome-wide significant locus (QTL) on chromosome 8 encompassing 17 defensin genes. By taking a systems genetics approach, we ultimately identified alpha-defensin 26 (Defa26) as the causal gene in this region. To validate these findings, we synthesized Defa26 and performed diet supplementation experiments in two mouse strains with distinct endogenous Defa26 expression levels. In the strain with relatively lower endogenous expression (C57BL/6J) supplementation improved insulin sensitivity and reduced gut permeability, while in the strain with higher endogenous expression (A/J) it caused hypoinsulinemia, glucose intolerance and muscle wasting. Based on gut microbiome and plasma bile acid profiling this appeared to be the result of disrupted microbial bile acid metabolism. These data illustrate the danger of single strain over-reliance and provide the first evidence of a link between host-genetics and insulin sensitivity which is mediated by the microbiome.

systems biology↗

Leveraging genetic diversity to identify small molecules that reverse mouse skeletal muscle insulin resistance

Systems genetics has begun to tackle the complexity of insulin resistance by capitalising on computational advances to study high-diversity populations. "Diversity Outbred in Australia (DOz)" is a population of genetically unique mice with profound metabolic heterogeneity. We leveraged this variance to explore skeletal muscles contribution to whole-body insulin action through metabolic phenotyping and skeletal muscle proteomics of 215 DOz mice. Linear modelling identified 553 proteins that associated with whole-body insulin sensitivity (Matsuda Index) including regulators of endocytosis and muscle proteostasis. To enrich for causality, we refined this network by focussing on negatively associated, genetically regulated proteins, resulting in a 76-protein fingerprint of insulin resistance. We sought to perturb this network and restore insulin action with small molecules by integrating the Broad Institute Connectivity Map platform and in vitro assays of insulin action using the Prestwick chemical library. These complimentary approaches identified the antibiotic thiostrepton as an insulin resistance reversal agent. Subsequent validation in ex vivo insulin resistant mouse muscle, and palmitate induced insulin resistant myotubes demonstrated potent insulin action restoration, potentially via up-regulation of glycolysis. This work demonstrates the value of a drug-centric framework to validate systems level analysis by identifying potential therapeutics for insulin resistance.

systems biology↗