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Abstract Mevalonate is a key precursor in isoprenoid biosynthesis and a promising commodity chemical. Although mevalonate is a native metabolite in Saccharomyces cerevisiae, its production is challenged by the relatively low flux toward acetyl-CoA in this yeast. In this study we explore different approaches to increase acetyl-CoA supply in S. cerevisiae to boost mevalonate production. Stable integration of a feedback-insensitive acetyl-CoA synthetase (Se-acsL641P) from Salmonella enterica and the mevalonate pathway from Enterococcus faecalis results in the production of 1,390 ± 10 mg/l of mevalonate from glucose. While bifid shunt enzymes failed to improve titers in high-producing strains, inhibition of squalene synthase (ERG9) results in a significant enhancement. Finally, increasing coenzyme A (CoA) biosynthesis by overexpression of pantothenate kinase (CAB1) and pantothenate supplementation further increased production to 3,830 ± 120 mg/l. Using strains that combine these strategies in lab-scale bioreactors results in the production of 13.3 ± 0.5 g/l, which is ∼360-fold higher than previously reported mevalonate titers in yeast. This study demonstrates the feasibility of engineering S. cerevisiae for high-level mevalonate production. 

Abstract Branched-chain amino acid (BCAA) metabolism fulfills numerous physiological roles and can be harnessed to produce valuable chemicals. However, the lack of eukaryotic biosensors specific for BCAA-derived products has limited the ability to develop high-throughput screens for strain engineering and metabolic studies. Here, we harness the transcriptional regulator Leu3p fromSaccharomyces cerevisiaeto develop a genetically encoded biosensor for BCAA metabolism. In one configuration, we use the biosensor to monitor yeast production of isobutanol, an alcohol derived from valine degradation. Small modifications allow us to redeploy Leu3p in another biosensor configuration that monitors production of the leucine-derived alcohol, isopentanol. These biosensor configurations are effective at isolating high-producing strains and identifying enzymes with enhanced activity from screens for branched-chain higher alcohol (BCHA) biosynthesis in mitochondria as well as cytosol. Furthermore, this biosensor has the potential to assist in metabolic studies involving BCAA pathways, and offers a blueprint to develop biosensors for other products derived from BCAA metabolism. 

Abstract Osteoarthritis is the third most rapidly growing health condition associated with disability, after dementia and diabetes¹. By 2050, the total number of patients with osteoarthritis is estimated to reach 1 billion worldwide². As no disease-modifying treatments exist for osteoarthritis, a better understanding of disease aetiopathology is urgently needed. Here we perform a genome-wide association study meta-analyses across up to 489,975 cases and 1,472,094 controls, establishing 962 independent associations, 513 of which have not been previously reported. Using single-cell multiomics data, we identify signal enrichment in embryonic skeletal development pathways. We integrate orthogonal lines of evidence, including transcriptome, proteome and epigenome profiles of primary joint tissues, and implicate 700 effector genes. Within these, we find rare coding-variant burden associations with effect sizes that are consistently higher than common frequency variant associations. We highlight eight biological processes in which we find convergent involvement of multiple effector genes, including the circadian clock, glial-cell-related processes and pathways with an established role in osteoarthritis (TGFβ, FGF, WNT, BMP and retinoic acid signalling, and extracellular matrix organization). We find that 10% of the effector genes express a protein that is the target of approved drugs, offering repurposing opportunities, which can accelerate translation.