SummaryThree distinct RNA polymerases (Pols) transcribe different classes of genes in the eukaryotic nucleus1. Pol III is the essential, evolutionarily conserved enzyme that generates short, non-coding RNAs, including transfer RNAs (tRNAs) and 5S ribosomal RNA (rRNA)2. Historical focus on transcription of protein-coding genes has left the roles of Pol III in organismal physiology relatively unexplored. The prominent regulator of Pol III activity, Target of Rapamycin kinase Complex 1 (TORC1), is an important longevity determinant3, raising the question of Pol III’s involvement in ageing. Here we show that Pol III limits lifespan downstream of TORC1. We find that a reduction in Pol III extends chronological lifespan in yeast and organismal lifespan in worms and flies. Inhibiting Pol III activity in the adult worm or fly gut is sufficient to extend lifespan, and in flies, longevity can be achieved by Pol III inhibition specifically in the intestinal stem cells (ISCs). The longevity phenotype is associated with amelioration of age-related gut pathology and functional decline, dampened protein synthesis and increased tolerance of proteostatic stress. Importantly, Pol III acts downstream of TORC1 for lifespan and limiting Pol III activity in the adult gut achieves the full longevity benefit of systemic TORC1 inhibition. Hence, Pol III is a pivotal output of this key nutrient signalling network for longevity; Pol III’s growth-promoting, anabolic activity mediates the acceleration of ageing by TORC1. The evolutionary conservation of Pol III affirms its potential as a therapeutic target.

In the past decades, numerous instances of phenotypic diversity were observed in clonal microbial populations, particularly, on the gene expression level. Much less is, however, known about phenotypic differences that occur on the level of metabolism. This is likely explained by the fact that experimental tools probing metabolism of single cells are still at an early stage of development. Here, we review recent exciting discoveries that point out different causes for metabolic heterogeneity within clonal microbial populations. These causes range from ecological factors and cell-inherent dynamics in constant environments to molecular noise in gene expression that propagates into metabolism. Furthermore, we provide an overview of current methods to quantify the levels of metabolites and biomass components in single cells.

A comprehensive description of the phenotypic changes during cellular aging is key towards unraveling its causal forces. Previously, we mapped age-related changes in the proteome and transcriptome (Janssens et al., 2015). Here, employing the same experimental procedure and model-based inference, we generate a comprehensive account of metabolic changes during the replicative life of Saccharomyces cerevisiae. With age, we found decreasing metabolite levels, decreasing growth and substrate uptake rates accompanied by a switch from aerobic fermentation to respiration, with glycerol and acetate production. The identified metabolic fluxes revealed an increase in redox cofactor turnover, likely to combat increased production of reactive oxygen species. The metabolic changes are possibly a result of the age-associated decrease in surface area per cell volume. With metabolism being an important factor of the cellular phenotype, this work complements our recent mapping of the transcriptomic and proteomic changes towards a holistic description of the cellular phenotype during aging.

Metabolic heterogeneity between individual cells of a population harbors significant challenges for fundamental and applied research. Identifying metabolic heterogeneity and investigating its emergence require tools to zoom into metabolism of individual cells. While methods exist to measure metabolite levels in single cells, we lack capability to measure metabolic flux, i.e., the ultimate functional output of metabolic activity, on the single‐cell level. Here, combining promoter engineering, computational protein design, biochemical methods, proteomics, and metabolomics, we developed a biosensor to measure glycolytic flux in single yeast cells. Therefore, drawing on the robust cell‐intrinsic correlation between glycolytic flux and levels of fructose‐1,6‐bisphosphate (FBP), we transplanted the B. subtilis FBP‐binding transcription factor CggR into yeast. With the developed biosensor, we robustly identified cell subpopulations with different FBP levels in mixed cultures, when subjected to flow cytometry and microscopy. Employing microfluidics, we were also able to assess the temporal FBP/glycolytic flux dynamics during the cell cycle. We anticipate that our biosensor will become a valuable tool to identify and study metabolic heterogeneity in cell populations.

RNA-based sensors for intracellular metabolites are a promising solution to the emerging issue of metabolic heterogeneity. However, their development, i.e., the conversion of an aptamer into an in vivo-functional intracellular metabolite sensor, still harbors challenges. Here, we accomplished this for the glycolytic fluxsignaling metabolite, fructose-1,6-bisphosphate (FBP). Starting from in vitro selection of an aptamer, we constructed device libraries with a hammerhead ribozyme as actuator. Using high-throughput screening in yeast with fluorescence-activated cell sorting (FACS), next-generation sequencing, and genetic-environmental perturbations to modulate the intracellular FBP levels, we identified a sensor that generates ratiometric fluorescent readout. An abrogated response in sensor mutants and occurrence of two sensor conformationsrevealed by RNA structural probing-indicated in vivo riboswitching activity. Microscopy showed that the sensor can differentiate cells with different glycolytic fluxes within yeast populations, opening research avenues into metabolic heterogeneity. We demonstrate the possibility to generate RNA-based sensors for intracellular metabolites for which no natural metabolite-binding RNA element exits.