H+-Translocating Membrane-Bound Pyrophosphatase from Rhodospirillum rubrum Fuels Escherichia coli Cells via an Alternative Pathway for Energy Generation.

Inorganic pyrophosphatases (PPases) catalyze an essential reaction, namely, the hydrolysis of PPi, which is formed in large quantities as a side product of numerous cellular reactions. In the majority of living species, PPi hydrolysis is carried out by soluble cytoplasmic PPase (S-PPases) with the released energy dissipated in the form of heat. In Rhodospirillum rubrum, part of this energy can be conserved by proton-pumping pyrophosphatase (H+-PPaseRru) in the form of a proton electrochemical gradient for further ATP synthesis. Here, the codon-harmonized gene hppaRru encoding H+-PPaseRru was expressed in the Escherichia coli chromosome. We demonstrate, for the first time, that H+-PPaseRru complements the essential native S-PPase in E. coli cells. 13C-MFA confirmed that replacing native PPase to H+-PPaseRru leads to the re-distribution of carbon fluxes; a statistically significant 36% decrease in tricarboxylic acid (TCA) cycle fluxes was found compared with wild-type E. coli MG1655. Such a flux re-distribution can indicate the presence of an additional method for energy generation (e.g., ATP), which can be useful for the microbiological production of a number of compounds, the biosynthesis of which requires the consumption of ATP.

Universal Actuator for Efficient Silencing of Escherichia coli Genes Based on Convergent Transcription Resistant to Rho-Dependent Termination.

Dynamic control is a distinguished strategy in modern metabolic engineering, in which inducible convergent transcription is an attractive approach for conditional gene silencing. Instead of a simple strong "reverse" (r-) promoter, a three-component actuator has been developed for constitutive genes silencing. These actuators, consisting of r-promoters with different strengths, the ribosomal transcription antitermination-inducing sequence rrnG-AT, and the RNase III processing site, were inserted into the 3'-UTR of three E. coli metabolic genes. Second and third actuator components were important to improve the effectiveness and robustness of the approach. The maximal silencing folds achieved for gltA, pgi, and ppc were approximately 7, 11, and >100, respectively. Data were analyzed using a simple model that considered RNA polymerase (RNAP) head-on collisions as the unique reason for gene silencing and continued transcription after collision with only one of two molecules. It was previously established that forward (f-) RNAP with a trailing ribosome was approximately 13-times more likely to continue transcription after head-on collision than untrailed r-RNAP which is sensitive to Rho-dependent transcription termination (RhoTT). According to the current results, this bias in complex stabilities decreased to no more than (3.0-5.7)-fold if r-RNAP became resistant to RhoTT. Therefore, the developed constitutive actuator could be considered as an improved tool for controlled gene expression mainly due to the transfer of r-transcription into a state that is resistant to potential termination and used as the basis for the design of tightly regulated actuators for the achievement of conditional silencing.

OpenFLUX2: (13)C-MFA modeling software package adjusted for the comprehensive analysis of single and parallel labeling experiments.

BACKGROUND: Steady-state (13)C-based metabolic flux analysis ((13)C-MFA) is the most powerful method available for the quantification of intracellular fluxes. These analyses include concertedly linked experimental and computational stages: (i) assuming the metabolic model and optimizing the experimental design; (ii) feeding the investigated organism using a chosen (13)C-labeled substrate (tracer); (iii) measuring the extracellular effluxes and detecting the (13)C-patterns of intracellular metabolites; and (iv) computing flux parameters that minimize the differences between observed and simulated measurements, followed by evaluating flux statistics. In its early stages, (13)C-MFA was performed on the basis of data obtained in a single labeling experiment (SLE) followed by exploiting the developed high-performance computational software. Recently, the advantages of parallel labeling experiments (PLEs), where several LEs are conducted under the conditions differing only by the tracer(s) choice, were demonstrated, particularly with regard to improving flux precision due to the synergy of complementary information. The availability of an open-source software adjusted for PLE-based (13)C-MFA is an important factor for PLE implementation. RESULTS: The open-source software OpenFLUX, initially developed for the analysis of SLEs, was extended for the computation of PLE data. Using the OpenFLUX2, in silico simulation confirmed that flux precision is improved when (13)C-MFA is implemented by fitting PLE data to the common model compared with SLE-based analysis. Efficient flux resolution could be achieved in the PLE-mediated analysis when the choice of tracer was based on an experimental design computed to minimize the flux variances from different parts of the metabolic network. The analysis provided by OpenFLUX2 mainly includes (i) the optimization of the experimental design, (ii) the computation of the flux parameters from LEs data, (iii) goodness-of-fit testing of the model's adequacy, (iv) drawing conclusions concerning the identifiability of fluxes and construction of a contribution matrix reflecting the relative contribution of the measurement variances to the flux variances, and (v) precise determination of flux confidence intervals using a fine-tunable and convergence-controlled Monte Carlo-based method. CONCLUSIONS: The developed open-source OpenFLUX2 provides a friendly software environment that facilitates beginners and existing OpenFLUX users to implement LEs for steady-state (13)C-MFA including experimental design, quantitative evaluation of flux parameters and statistics.