Acetyl coenzyme A (AcCoA) is the central biosynthetic precursor for fatty acid synthesis and protein acetylation. In the conventional view of mammalian cell metabolism, AcCoA is primarily generated from glucose-derived pyruvate through the citrate shuttle and adenosine triphosphate citrate lyase (ACL) in the cytosol1-3. However, proliferating cells that exhibit aerobic glycolysis and those exposed to hypoxia convert glucose to lactate at near stoichiometric levels, directing glucose carbon away from the tricarboxylic acid cycle (TCA) and fatty acid synthesis4. Although glutamine is consumed at levels exceeding that required for nitrogen biosynthesis5, the regulation and utilization of glutamine metabolism in hypoxic cells is not well understood. Here we show that human cells employ reductive metabolism of alpha-ketoglutarate (αKG) to synthesize AcCoA for lipid synthesis. This isocitrate dehydrogenase 1 (IDH1) dependent pathway is active in most cell lines under normal culture conditions, but cells grown under hypoxia rely almost exclusively on the reductive carboxylation of glutamine-derived αKG for de novo lipogenesis. Furthermore, renal cell lines deficient in the von Hippel-Lindau (VHL) tumor suppressor protein preferentially utilize reductive glutamine metabolism for lipid biosynthesis even at normal oxygen levels. These results identify a critical role for oxygen in regulating carbon utilization in order to produce AcCoA and support lipid synthesis in mammalian cells.

Taxol (paclitaxel) is a potent anticancer drug first isolated from the Taxus brevifolia Pacific yew tree. Currently, cost-efficient production of Taxol and its analogs remains limited. Here, we report a multivariate-modular approach to metabolic-pathway engineering that succeeded in increasing titers of taxadiene-the first committed Taxol intermediate-approximately 1 gram per liter (~15,000-fold) in an engineered Escherichia coli strain. Our approach partitioned the taxadiene metabolic pathway into two modules: a native upstream methylerythritol-phosphate (MEP) pathway forming isopentenyl pyrophosphate and a heterologous downstream terpenoid-forming pathway. Systematic multivariate search identified conditions that optimally balance the two pathway modules so as to maximize the taxadiene production with minimal accumulation of indole, which is an inhibitory compound found here. We also engineered the next step in Taxol biosynthesis, a P450-mediated 5α-oxidation of taxadiene to taxadien-5α-ol. More broadly, the modular pathway engineering approach helped to unlock the potential of the MEP pathway for the engineered production of terpenoid natural products.Taxol (paclitaxel) and its structural analogs are among the most potent and commercially successful anticancer drugs (1). Taxol was first isolated from the bark of the Pacific yew tree (2), and early-stage production methods required sacrificing two to four fully grown trees to secure sufficient dosage for one patient (3). Taxol's structural complexity limited its chemical synthesis to elaborate routes that required 35 to 51 steps, with a highest yield of 0.4% (4-6). A semisynthetic route was later devised in which the biosynthetic intermediate baccatin III, isolated from plant sources, was chemically converted to Taxol (7). Although this approach and subsequent plant cell culture-based production efforts have decreased the need for harvesting the yew tree, production still depends on plant-based processes (8), with

An elastomeric stamp, containing defined features on the micrometer scale, was used to imprint gold surfaces with specific patterns of self-assembled monolayers of alkanethiols and, thereby, to create islands of defined shape and size that support extracellular matrix protein adsorption and cell attachment. Through this technique, it was possible to place cells in predetermined locations and arrays, separated by defined distances, and to dictate their shape. Limiting the degree of cell extension provided control over cell growth and protein secretion. This method is experimentally simple and highly adaptable. It should be useful for applications in biotechnology that require analysis of individual cells cultured at high density or repeated access to cells placed in specified locations.

Most tumors display increased glucose metabolism compared to that of normal tissues. The preferential conversion of glucose to lactate in cancer cells (the Warburg Effect) has been emphasized1; however, the extent to which metabolic fluxes originating from glucose are utilized for alternative processes is poorly understood2,3. Here we used a combination of mass spectrometry and NMR with stable isotope labeling to investigate the alternate pathways derived from glucose metabolism in cancer cells. We found that in some cancer cells, a relatively large amount of glycolytic carbon is diverted into serine and glycine biosynthesis through phosphoglycerate dehydrogenase (PHGDH). A bioinformatics analysis of 3131 human cancers revealed that the gene PHGDH at 1p12 is recurrently amplified in a genomic region of focal copy number gain most commonly found in melanoma in which amplification was associated with increased protein expression. Decreased PHGDH expression by RNA interference impaired growth and flux into serine metabolism in PHGDH-amplified cell lines. Increased expression was also associated with breast cancer subtypes and ectopic expression of PHGDH in mammary epithelial cells (MCF-10a) disrupted acinar morphogenesis, induced loss of polarity, and preserved the viability of the extracellular matrix-deprived cells, each being phenotypic alterations that may predispose cells to transformation. Our findings demonstrate that altered metabolic flux from glucose into a specific alternate pathway can be selected during tumor development and may contribute to the pathogenesis of human cancer.

Cancer cells engage in a metabolic program to enhance biosynthesis and support cell proliferation. The regulatory properties of pyruvate kinase M2 (PKM2) influence altered glucose metabolism in cancer. PKM2 interaction with phosphotyrosine-containing proteins inhibits enzyme activity and increases availability of glycolytic metabolites to support cell proliferation. This suggests that high pyruvate kinase activity may suppress tumor growth. We show that expression of PKM1, the pyruvate kinase isoform with high constitutive activity, or exposure to published small molecule PKM2 activators inhibit growth of xenograft tumors. Structural studies reveal that small molecule activators bind PKM2 at the subunit interaction interface, a site distinct from that of the endogenous activator fructose-1,6-bisphosphate (FBP). However, unlike FBP, binding of activators to PKM2 promotes a constitutively active enzyme state that is resistant to inhibition by tyrosine-phosphorylated proteins. These data support the notion that small molecule activation of PKM2 can interfere with anabolic metabolism.

Gene function is typically evaluated by sampling the continuum of gene expression at only a few discrete points corresponding to gene knockout or overexpression. We argue that this characterization is incomplete and present a library of engineered promoters of varying strengths obtained through mutagenesis of a constitutive promoter. A multifaceted characterization of the library, especially at the single-cell level to ensure homogeneity, permitted quantitative assessment correlating the effect of gene expression levels to improved growth and product formation phenotypes in Escherichia coli . Integration of these promoters into the chromosome can allow for a quantitative accurate assessment of genetic control. To this end, we used the characterized library of promoters to assess the impact of phosphoenolpyruvate carboxylase levels on growth yield and deoxy-xylulose-P synthase levels on lycopene production. The multifaceted characterization of promoter strength enabled identification of optimal expression levels for ppc and dxs , which maximized the desired phenotype. Additionally, in a strain preengineered to produce lycopene, the response to deoxy-xylulose-P synthase levels was linear at all levels tested, indicative of a rate-limiting step, unlike the parental strain, which exhibited an optimum expression level, illustrating that optimal gene expression levels are variable and dependent on the genetic background of the strain. This promoter library concept is illustrated as being generalizable to eukaryotic organisms ( Saccharomyces cerevisiae ) and thus constitutes an integral platform for functional genomics, synthetic biology, and metabolic engineering endeavors.

Activation of cellular stress response pathways to maintain metabolic homeostasis is emerging as a critical growth and survival mechanism in many cancers1. The pathogenesis of pancreatic ductal adenocarcinoma (PDA) requires high levels of autophagy2–4, a conserved self-degradative process5. However, the regulatory circuits that activate autophagy and reprogram PDA cell metabolism are unknown. We now show that autophagy induction in PDA occurs as part of a broader transcriptional program that coordinates activation of lysosome biogenesis and function, and nutrient scavenging, mediated by the MiT/TFE family transcription factors. In PDA cells, the MiT/TFE proteins6 – MITF, TFE3 and TFEB – are decoupled from regulatory mechanisms that control their cytoplasmic retention. Increased nuclear import in turn drives the expression of a coherent network of genes that induce high levels of lysosomal catabolic function essential for PDA growth. Unbiased global metabolite profiling reveals that MiT/TFE-dependent autophagy-lysosomal activation is specifically required to maintain intracellular amino acid (AA) pools. These results identify the MiT/TFE transcription factors as master regulators of metabolic reprogramming in pancreatic cancer and demonstrate activation of clearance pathways converging on the lysosome as a novel hallmark of aggressive malignancy.

Metabolic Flux Analysis (MFA) has emerged as a tool of great significance for metabolic engineering and mammalian physiology. An important limitation of MFA, as carried out via stable isotope labeling and GC/MS and NMR measurements, is the large number of isotopomer or cumomer equations that need to be solved, especially when multiple isotopic tracers are used for the labeling of the system. This restriction reduces the ability of MFA to fully utilize the power of multiple isotopic tracers in elucidating the physiology of realistic situations comprising complex bioreaction networks.Here, we present a novel framework for the modeling of isotopic labeling systems that significantly reduces the number of system variables without any loss of information. The elementary metabolite unit (EMU) framework is based on a highly efficient decomposition method that identifies the minimum amount of information needed to simulate isotopic labeling within a reaction network using the knowledge of atomic transitions occurring in the network reactions. The functional units generated by the decomposition algorithm, called elementary metabolite units, form the new basis for generating system equations that describe the relationship between fluxes and stable isotope measurements. Isotopomer abundances simulated using the EMU framework are identical to those obtained using the isotopomer and cumomer methods, however, require significantly less computation time. For a typical 13 C-labeling system the total number of equations that needs to be solved is reduced by one order-of-magnitude (100s EMUs vs. 1000s isotopomers). As such, the EMU framework is most efficient for the analysis of labeling by multiple isotopic tracers. For example, analysis of the gluconeogenesis pathway with 2 H, 13 C, and 18 O tracers requires only 354 EMUs, compared to more than 2 million isotopomers.