Plant metabolism underpins many traits of ecological and agronomic importance. Plants produce numerous compounds to cope with their environments but the biosynthetic pathways for most of these compounds have not yet been elucidated. To engineer and improve metabolic traits, we need comprehensive and accurate knowledge of the organization and regulation of plant metabolism at the genome scale. Here, we present a computational pipeline to identify metabolic enzymes, pathways, and gene clusters from a sequenced genome. Using this pipeline, we generated metabolic pathway databases for 22 species and identified metabolic gene clusters from 18 species. This unified resource can be used to conduct a wide array of comparative studies of plant metabolism. Using the resource, we discovered a widespread occurrence of metabolic gene clusters in plants: 11,969 clusters from 18 species. The prevalence of metabolic gene clusters offers an intriguing possibility of an untapped source for uncovering new metabolite biosynthesis pathways. For example, more than 1,700 clusters contain enzymes that could generate a specialized metabolite scaffold (signature enzymes) and enzymes that modify the scaffold (tailoring enzymes). In four species with sufficient gene expression data, we identified 43 highly coexpressed clusters that contain signature and tailoring enzymes, of which eight were characterized previously to be functional pathways. Finally, we identified patterns of genome organization that implicate local gene duplication and, to a lesser extent, single gene transposition as having played roles in the evolution of plant metabolic gene clusters.

All plants synthesize basic metabolites needed for survival (primary metabolism), but different taxa produce distinct metabolites that are specialized for specific environmental interactions (specialized metabolism). Because evolutionary pressures on primary and specialized metabolism differ, we investigated differences in the emergence and maintenance of these processes across 16 species encompassing major plant lineages from algae to angiosperms. We found that, relative to their primary metabolic counterparts, genes coding for specialized metabolic functions have proliferated to a much greater degree and by different mechanisms and display lineage-specific patterns of physical clustering within the genome and coexpression. These properties illustrate the differential evolution of specialized metabolism in plants, and collectively they provide unique signatures for the potential discovery of novel specialized metabolic processes.

The metabolite acetyl-coenzyme A (acetyl-CoA) is the required acetyl donor for lysine acetylation and thereby links metabolism, signaling, and epigenetics. Nutrient availability alters acetyl-CoA levels in cancer cells, correlating with changes in global histone acetylation and gene expression. However, the specific molecular mechanisms through which acetyl-CoA production impacts gene expression and its functional roles in promoting malignant phenotypes are poorly understood. Here, using histone H3 Lys27 acetylation (H3K27ac) ChIP-seq (chromatin immunoprecipitation [ChIP] coupled with next-generation sequencing) with normalization to an exogenous reference genome (ChIP-Rx), we found that changes in acetyl-CoA abundance trigger site-specific regulation of H3K27ac, correlating with gene expression as opposed to uniformly modulating this mark at all genes. Genes involved in integrin signaling and cell adhesion were identified as acetyl-CoA-responsive in glioblastoma cells, and we demonstrate that ATP citrate lyase (ACLY)-dependent acetyl-CoA production promotes cell migration and adhesion to the extracellular matrix. Mechanistically, the transcription factor NFAT1 (nuclear factor of activated T cells 1) was found to mediate acetyl-CoA-dependent gene regulation and cell adhesion. This occurs through modulation of Ca signals, triggering NFAT1 nuclear translocation when acetyl-CoA is abundant. The findings of this study thus establish that acetyl-CoA impacts H3K27ac at specific loci, correlating with gene expression, and that expression of cell adhesion genes are driven by acetyl-CoA in part through activation of Ca-NFAT signaling.

Purpose: Everolimus inhibits the mTOR, activating cytoprotective autophagy. Hydroxychloroquine inhibits autophagy. On the basis of preclinical data demonstrating synergistic cytotoxicity when mTOR inhibitors are combined with an autophagy inhibitor, we launched a clinical trial of combined everolimus and hydroxychloroquine, to determine its safety and activity in patients with clear-cell renal cell carcinoma (ccRCC). Patients and Methods: Three centers conducted a phase I/II trial of everolimus 10 mg daily and hydroxychloroquine in patients with advanced ccRCC. The objectives were to determine the MTD of hydroxychloroquine with daily everolimus, and to estimate the rate of 6-month progression-free survival (PFS) in patients with ccRCC receiving everolimus/hydroxychloroquine after 1-3 prior treatment regimens. Correlative studies to identify patient subpopulations that achieved the most benefit included population pharmacokinetics, measurement of autophagosomes by electron microscopy, and next-generation tumor sequencing. Results: No dose-limiting toxicity was observed in the phase I trial. The recommended phase II dose of hydroxychloroquine 600 mg twice daily with everolimus was identified. Disease control [stable disease þ partial response (PR)] occurred in 22 of 33 (67%) evaluable patients. PR was observed in 2 of 33 patients (6%). PFS ! 6 months was achieved in 15 of 33 (45%) of patients who achieved disease control. Conclusions: Combined hydroxychloroquine 600 mg twice daily with 10 mg daily everolimus was tolerable. The primary endpoint of >40% 6-month PFS rate was met. Hydroxychloroquine is a tolerable autophagy inhibitor in future RCC or other trials.