Metabolomics-driven approach to solving a CoA imbalance for improved 1-butanol production in Escherichia coli.

High titer 1-butanol production in Escherichia coli has previously been achieved by overexpression of a modified clostridial 1-butanol production pathway and subsequent deletion of native fermentation pathways. This strategy couples growth with production as 1-butanol pathway offers the only available terminal electron acceptors required for growth in anaerobic conditions. With further inclusion of other well-established metabolic engineering principles, a titer of 15g/L has been obtained. In achieving this titer, many currently existing strategies have been exhausted, and 1-butanol toxicity level has been surpassed. Therefore, continued engineering of the host strain for increased production requires implementation of alternative strategies that seek to identify non-obvious targets for improvement. In this study, a metabolomics-driven approach was used to reveal a CoA imbalance resulting from a pta deletion that caused undesirable accumulation of pyruvate, butanoate, and other CoA-derived compounds. Using metabolomics, the reduction of butanoyl-CoA to butanal catalyzed by alcohol dehydrogenase AdhE2 was determined as a rate-limiting step. Fine-tuning of this activity and subsequent release of free CoA restored the CoA balance that resulted in a titer of 18.3g/L upon improvement of total free CoA levels using cysteine supplementation. By enhancing AdhE2 activity, carbon flux was directed towards 1-butanol production and undesirable accumulation of pyruvate and butanoate was diminished. This study represents the initial report describing the improvement of 1-butanol production in E. coli by resolving CoA imbalance, which was based on metabolome analysis and rational metabolic engineering strategies.

A reverse glyoxylate shunt to build a non-native route from C4 to C2 in Escherichia coli.

Most central metabolic pathways such as glycolysis, fatty acid synthesis, and the TCA cycle have complementary pathways that run in the reverse direction to allow flexible storage and utilization of resources. However, the glyoxylate shunt, which allows for the synthesis of four-carbon TCA cycle intermediates from acetyl-CoA, has not been found to be reversible to date. As a result, glucose can only be converted to acetyl-CoA via the decarboxylation of the three-carbon molecule pyruvate in heterotrophs. A reverse glyoxylate shunt (rGS) could be extended into a pathway that converts C4 carboxylates into two molecules of acetyl-CoA without loss of CO2. Here, as a proof of concept, we engineered in Escherichia coli such a pathway to convert malate and succinate to oxaloacetate and two molecules of acetyl-CoA. We introduced ATP-coupled heterologous enzymes at the thermodynamically unfavorable steps to drive the pathway in the desired direction. This synthetic pathway in essence reverses the glyoxylate shunt at the expense of ATP. When integrated with central metabolism, this pathway has the potential to increase the carbon yield of acetate and biofuels from many carbon sources in heterotrophic microorganisms, and could be the basis of novel carbon fixation cycles.

Toward nitrogen neutral biofuel production.

Environmental concerns and an increasing global energy demand have spurred scientific research and political action to deliver large-scale production of liquid biofuels. Current biofuel processes and developing approaches have focused on closing the carbon cycle by biological fixation of atmospheric carbon dioxide and conversion of biomass to fuels. To date, these processes have relied on fertilizer produced by the energy-intensive Haber-Bosch process, and have not addressed the global nitrogen cycle and its environmental implications. Recent developments to convert protein to fuel and ammonia may begin to address these problems. In this scheme, recycling ammonia to either plant or algal feedstocks reduces the demand for synthetic fertilizer supplementation. Further development of this technology will realize its advantages of high carbon fixation rates, inexpensive and simple feedstock processing, in addition to reduced fertilizer requirements.

Determination of the Escherichia coli S-nitrosoglutathione response network using integrated biochemical and systems analysis.

During infection or denitrification, bacteria encounter reactive nitrogen species. Although the molecular targets of and defensive response against nitric oxide (NO) in Escherichia coli are well studied, the response elements specific to S-nitrosothiols are less clear. Previously, we employed an integrated systems biology approach to unravel the E. coli NO-response network. Here we use a similar approach to confirm that S-nitrosoglutathione (GSNO) primarily impacts the metabolic and regulatory programs of E. coli in minimal medium by reaction with homocysteine and cysteine and subsequent disruption of the methionine biosynthesis pathway. Targeting of homocysteine and cysteine results in altered regulatory activity of MetJ, MetR, and CysB, activation of the stringent response and growth inhibition. Deletion of metJ or supplementation with methionine strongly attenuated the effect of GSNO on growth and gene expression. Furthermore, GSNO inhibited the ArcAB two-component system. Consistent with the underlying nitrosative and thiol-oxidative chemistry, growth inhibition and the majority of the regulatory perturbations were dependent upon GSNO internalization by the Dpp dipeptide transporter. Contrastingly, perturbation of NsrR appeared to be a result of the submicromolar levels of NO released from GSNO and did not require GSNO internalization.

Biological network mapping and source signal deduction.

MOTIVATION: Many biological networks, including transcriptional regulation, metabolism, and the absorbance spectra of metabolite mixtures, can be represented in a bipartite fashion. Key to understanding these bipartite networks are the network architecture and governing source signals. Such information is often implicitly imbedded in the data. Here we develop a technique, network component mapping (NCM), to deduce bipartite network connectivity and regulatory signals from data without any need for prior information. RESULTS: We demonstrate the utility of our approach by analyzing UV-vis spectra from mixtures of metabolites and gene expression data from Saccharomyces cerevisiae. From UV-vis spectra, hidden mixing networks and pure component spectra (sources) were deduced to a higher degree of resolution with our method than other current bipartite techniques. Analysis of S. cerevisiae gene expression from two separate environmental conditions (zinc and DTT treatment) yielded transcription networks consistent with ChIP-chip derived network connectivity. Due to the high degree of noise in gene expression data, the transcription network for many genes could not be inferred. However, with relatively clean expression data, our technique was able to deduce hidden transcription networks and instances of combinatorial regulation. These results suggest that NCM can deduce correct network connectivity from relatively accurate data. For noisy data, NCM yields the sparsest network capable of explaining the data. In addition, partial knowledge of the network topology can be incorporated into NCM as constraints. AVAILABILITY: Algorithm available on request from the authors. Soon to be posted on the web, http://www.seas.ucla.edu/~liaoj/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.