Genome-scale metabolic models (GEMs) are valuable tools to study metabolism and provide a scaffold for the integrative analysis of omics data. Researchers have developed increasingly comprehensive human GEMs, but the disconnect among different model sources and versions impedes further progress. We therefore integrated and extensively curated the most recent human metabolic models to construct a consensus GEM, Human1. We demonstrated the versatility of Human1 through the generation and analysis of cell- and tissue-specific models using transcriptomic, proteomic, and kinetic data. We also present an accompanying web portal, Metabolic Atlas (https://www.metabolicatlas.org/), which facilitates further exploration and visualization of Human1 content. Human1 was created using a version-controlled, open-source model development framework to enable community-driven curation and refinement. This framework allows Human1 to be an evolving shared resource for future studies of human health and disease.

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AUTHOR CONTRIBUTIONS G.F., A.A. and A.L. performed experiments and helped analyze all data with supervision from R.K.J. and M.G.V.H. D.P.K., D.B. and D.F. contributed in identifying metabolic signatures of brain metastasis; K.LA. and A.W. contributed to in vitro work and GCMS analysis. A.D. and C.B.C. performed LCMS lipidomics and helped with analysis; L.B., B.P. and V.A.D performed IMS imaging and analysis; X.J. and T.R.G. contributed to extracellular fluid isolation and provided input on data interpretation. J.M.P., N.I.L. and E.B. collected clinical samples and contributed to analysis of patient tumor sections; J.C. and D.G.D. performed ultrasound imaging of liver tumors; C.R.C. and S.M.D. contributed to in vivo glucose tracing studies. Z.A. performed flow cytometry analysis. R.F. and J.N. helped with analysis of lipidomics data. I.C., C.N. and D.E.H. analyzed human expression databases. K.N. performed analysis of Affymetrix array. M.D. and S.R. contributed to CRISPR Cas9 methodology and animal implantations.

BackgroundTranscriptional reprogramming is a fundamental process of living cells in order to adapt to environmental and endogenous cues. In order to allow flexible and timely control over gene expression without the interference of native gene expression machinery, a large number of studies have focused on developing synthetic biology tools for orthogonal control of transcription. Most recently, the nuclease-deficient Cas9 (dCas9) has emerged as a flexible tool for controlling activation and repression of target genes, by the simple RNA-guided positioning of dCas9 in the vicinity of the target gene transcription start site.ResultsIn this study we compared two different systems of dCas9-mediated transcriptional reprogramming, and applied them to genes controlling two biosynthetic pathways for biobased production of isoprenoids and triacylglycerols (TAGs) in baker’s yeast Saccharomyces cerevisiae. By testing 101 guide-RNA (gRNA) structures on a total of 14 different yeast promoters, we identified the best-performing combinations based on reporter assays. Though a larger number of gRNA-promoter combinations do not perturb gene expression, some gRNAs support expression perturbations up to ~threefold. The best-performing gRNAs were used for single and multiplex reprogramming strategies for redirecting flux related to isoprenoid production and optimization of TAG profiles. From these studies, we identified both constitutive and inducible multiplex reprogramming strategies enabling significant changes in isoprenoid production and increases in TAG.ConclusionTaken together, we show similar performance for a constitutive and an inducible dCas9 approach, and identify multiplex gRNA designs that can significantly perturb isoprenoid production and TAG profiles in yeast without editing the genomic context of the target genes. We also identify a large number of gRNA positions in 14 native yeast target pomoters that do not affect expression, suggesting the need for further optimization of gRNA design tools and dCas9 engineering.Electronic supplementary materialThe online version of this article (doi:10.1186/s12934-017-0664-2) contains supplementary material, which is available to authorized users.