In many tissues (epithelia, muscle, neurons), electrical or neurohormonal signals activate metabolism at times of heightened demand to ensure efficient use of resources. These cues are typically lost in cancers, but resource-efficiency remains important, particularly when oncogenic mutations instruct a programme of rapid growth that could lead to self-limiting depletion of tumour resources. Sustainable use of resources may be implemented through rationing, whereby cohorts of cancer cells take turns to engage in energy-intensive activities (e.g. biomass growth, division). We believe this explains the emergence of metabolic heterogeneity. However, time-dependent phenomena evade discovery pipelines based on steady-state measurements of gene expression, protein abundance, or metabolite levels. We developed a method for sorting cells by a surrogate of fermentative flux, as opposed to steady-state metabolite concentrations which do not predict rates. Applying this to rapidly-growing pancreatic ductal adenocarcinoma (PDAC) cells, we described a signalling cascade that alternates metabolic state between basal and activated1. Operating as a delayed negative feedback circuit (akin to pacemakers, e.g. circadian), the cascade is triggered by interleukin 6 (IL6) receptors activating STAT3, which stimulates fermentation and respiration alongside transcription of its negative regulator SOCS3. Such a system can produce metabolic rhythms independently of cell-cycling. Since it is not hardwired, a population of such metabolic oscillators maintains dynamic heterogeneity, without drifting. We propose that our mechanism rations resources for energy-efficient PDAC expansion, and that its inactivation would eventually deplete resources, i.e. have therapeutic value. This project will: Screen a panel of PDAC lines for energy-efficiency of growth using real-time measurements of fermentative/respiratory fluxes and biomass, and relate this to metabolic phenotype and its heterogeneity. We will use single-cell assays and sorting methods developed by our group. Ranking by energy-efficiency will enable correlative discovery. Verify the delayed negative feedback mechanism. Metabolic sub-populations will be tested for IL6-STAT3-SOCS3 markers and oscillator kinetics will be tracked using a fluorescent reporter of STAT3 transcriptional activity after sequential sorting. Oscillator properties will be manipulated, e.g. changes to PEST motif that affect SOCS3 degradation. Identify genetic regulators that enable resource-smart growth using a CRISPR/Cas9 screen under limited resources (closed system), relative to unlimited resources (superfused system). The effect of inactivating candidate-genes on 'resource-smart' growth will be validated using competition assays with wild-type cells. Test vulnerabilities in the rhythm-generator as a therapeutic strategy by growing mouse xenografts comprising efficiency-compromised and wild-type cells.