Mass spectrometry-based workflow for accurate quantification of Escherichia coli enzymes: how proteomics can play a key role in metabolic engineering

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 PP_i, which is formed in large quantities as a side product of numerous cellular reactions. In the majority of living species, PP_i 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⁺-PPase^Rru) in the form of a proton electrochemical gradient for further ATP synthesis. Here, the codon-harmonized gene hppa^Rru encoding H⁺-PPase^Rru was expressed in the Escherichia coli chromosome. We demonstrate, for the first time, that H⁺-PPase^Rru complements the essential native S-PPase in E. coli cells. ¹³C-MFA confirmed that replacing native PPase to H⁺-PPase^Rru 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.

Metabolic Engineering: Methodologies and Applications

Metabolic engineering aims to improve the production of economically valuable molecules through the genetic manipulation of microbial metabolism. While the discipline is a little over 30 years old, advancements in metabolic engineering have given way to industrial-level molecule production benefitting multiple industries such as chemical, agriculture, food, pharmaceutical, and energy industries. This review describes the design, build, test, and learn steps necessary for leading a successful metabolic engineering campaign. Moreover, we highlight major applications of metabolic engineering, including synthesizing chemicals and fuels, broadening substrate utilization, and improving host robustness with a focus on specific case studies. Finally, we conclude with a discussion on perspectives and future challenges related to metabolic engineering.

An innovative standard for LC-MS-based HCP profiling and accurate quantity assessment: Application to batch consistency in viral vaccine samples

Biotherapeutics, molecules produced from biological systems, require rigorous purification steps to remove impurities including host cell proteins (HCPs). Regulatory guidelines require manufacturers to monitor process-related impurities along the purification workflow. Mass spectrometry (MS) has recently been considered as a complementary method to the well-established ELISA for HCPs quantification, since it has the advantage of unambiguously identifying individual HCP. In this study, we developed an innovative standard dedicated to MS-based HCP profiling analysis in order to monitor the consistency of viral vaccine intermediate purification samples. This standard, termed the HCP-PROFILER standard, is composed of a water-soluble bead (READYBEADS technology) which, after being added into the sample, releases unlabeled peptides in controlled amounts. The standard meets three desired criteria: (1) it is composed of multiple peptides, at different concentration levels, allowing construction of a calibration curve covering the dynamic range of HCPs present in the target sample, ensuring quantification accuracy; (2) it demonstrates high batch-to-batch reproducibility, ensuring quantification robustness and consistency over time; and (3) it is easy to use and avoids user-induced analytical biases. In this study, we present the use of the HCP-PROFILER standard for vaccine batches comparison and downstream process performance studies.

Redox rebalance against genetic perturbations and modulation of central carbon metabolism by the oxidative stress regulation

The micro-aerophilic organisms and aerobes as well as yeast and higher organisms have evolved to gain energy through respiration (via oxidative phosphorylation), thereby enabling them to grow much faster than anaerobes. However, during respiration, reactive oxygen species (ROSs) are inherently (inevitably) generated, and threaten the cell's survival. Therefore, living organisms (or cells) must furnish the potent defense systems to keep such ROSs at harmless level, where the cofactor balance plays crucial roles. Namely, NADH is the source of energy generation (catabolism) in the respiratory chain reactions, through which ROSs are generated, while NADPH plays important roles not only for the cell synthesis (anabolism) but also for detoxifying ROSs. Therefore, the cell must rebalance the redox ratio by modulating the fluxes of the central carbon metabolism (CCM) by regulating the multi-level regulation machinery upon genetic perturbations and the change in the growth conditions. Here, we discuss about how aerobes accomplish such cofactor homeostasis against redox perturbations. In particular, we consider how single-gene mutants (including pgi, pfk, zwf, gnd and pyk mutants) modulate their metabolisms in relation to cofactor rebalance (and also by adaptive laboratory evolution). We also discuss about how the overproduction of NADPH (by the pathway gene mutation) can be utilized for the efficient production of useful value-added chemicals such as medicinal compounds, polyhydroxyalkanoates, and amino acids, all of which require NADPH in their synthetic pathways. We then discuss about the metabolic responses against oxidative stress, where αketoacids play important roles not only for the coordination between catabolism and anabolism, but also for detoxifying ROSs by non-enzymatic reactions, as well as for reducing the production of ROSs by repressing the activities of the TCA cycle and respiration (via carbon catabolite repression). Thus, we discuss about the mechanisms (basic strategies) that modulate the metabolism from respiration to respiro-fermentative metabolism causing overflow, based on the role of Pyk activity, affecting the NADPH production at the oxidative pentose phosphate (PP) pathway, and the roles of αketoacids for the change in the source of energy generation from the oxidative phosphorylation to the substrate level phosphorylation.

WellInverter: a web application for the analysis of fluorescent reporter gene data

Background

Fluorescent reporter genes have become widely used for monitoring gene expression in living cells. When a microbial strain carrying a reporter gene is grown in a microplate reader, the fluorescence and the absorbance (optical density) of the culture can be automatically measured every few minutes in a highly parallelized way. The extraction of useful information from the resulting large amounts of data is not easy to achieve, because the fluorescence and absorbance measurements are only indirectly related to promoter activities and protein concentrations, requiring mathematical models of the expression of reporter genes for their interpretation. Although the principles of the analysis of reporter gene data are well-established today, there is a lack of general-purpose bioinformatics tools based on generic measurement models and sound inference procedures. This has motivated the development of WellInverter, a web application based on well-known methods for regularized linear inversion.

Results

We present a new version of WellInverter that considerably improves the performance and usability of the original application. In particular, we have put in place a parallel computing architecture with a load balancer to distribute analysis queries over several back-end servers, we have completely redesigned the graphical user interface to better support the different analysis steps, and we have developed a plug-in system for the parsing of data files produced by microplate readers from different manufacturers. We illustrate the functioning of WellInverter by analyzing data of the expression of a fluorescent reporter gene controlled by a phage promoter in growing Escherichia coli populations. We show that the expression pattern in different growth media, supporting different growth rates, corresponds to the pattern expected for a constitutive gene.

Conclusions

The new version of WellInverter is a robust, easy-to-use and scalable web application, which has been deployed on two publicly accessible web servers and which can also be installed locally. A demo version of the application with two sample datasets is available on-line.

Electronic supplementary material

The online version of this article (10.1186/s12859-019-2920-4) contains supplementary material, which is available to authorized users.

Regulation of glycolytic flux and overflow metabolism depending on the source of energy generation for energy demand

Overflow metabolism is a common phenomenon observed at higher glycolytic flux in many bacteria, yeast (known as Crabtree effect), and mammalian cells including cancer cells (known as Warburg effect). This phenomenon has recently been characterized as the trade-offs between protein costs and enzyme efficiencies based on coarse-graining approaches. Moreover, it has been recognized that the glycolytic flux increases as the source of energy generation changes from energetically efficient respiration to inefficient respiro-fermentative or fermentative metabolism causing overflow metabolism. It is highly desired to clarify the metabolic regulation mechanisms behind such phenomena. Metabolic fluxes are located on top of the hierarchical regulation systems, and represent the outcome of the integrated response of all levels of cellular regulation systems. In the present article, we discuss about the different levels of regulation systems for the modulation of fluxes depending on the growth rate, growth condition such as oxygen limitation that alters the metabolism towards fermentation, and genetic perturbation affecting the source of energy generation from respiration to respiro-fermentative metabolism in relation to overflow metabolism. The intracellular metabolite of the upper glycolysis such as fructose 1,6-bisphosphate (FBP) plays an important role not only for flux sensing, but also for the regulation of the respiratory activity either directly or indirectly (via transcription factors) at higher growth rate. The glycolytic flux regulation is backed up (enhanced) by unphosphorylated EIIA and HPr of the phosphotransferase system (PTS) components, together with the sugar-phosphate stress regulation, where the transcriptional regulation is further modulated by post-transcriptional regulation via the degradation of mRNA (stability of mRNA) in Escherichia coli. Moreover, the channeling may also play some role in modulating the glycolytic cascade reactions.

In Vivo Quantitative Monitoring of Subunit Stoichiometry for Metabolic Complexes

Metabolic pathways often employ assemblies of individual enzymes to facilitate substrate channeling to improve thermodynamic efficiency and confer pathway directionality. It is often assumed that subunits to multienzyme complexes are coregulated and accumulate at fixed levels in vivo, reflecting complex stoichiometry. Such assumptions can be experimentally tested using modern tandem mass spectrometry, and herein we describe such an approach applied toward an important metabolic complex. The committed step of de novo fatty acid synthesis in the plastids of most plants is catalyzed by the multienzyme, heteromeric acetyl-CoA carboxylase (hetACCase). This complex is composed of four catalytic subunits and a recently discovered regulatory subunit resembling the biotin carboxyl carrier protein but lacking the biotinylation motif necessary for activity. To better understand this novel form of regulation, a targeted tandem mass-spectrometry-based assay was developed to absolutely quantify all subunits to the Arabidopsis thaliana hetACCase. After validation against pure, recombinant protein, this multiplexed assay was used to quantify hetACCase subunits in siliques in various stages of development. Quantitation provided a developmental profile of hetACCase and BADC protein expression that supports a recently proposed regulatory mechanism for hetACCase and demonstrates a promising application of targeted mass spectrometry for in vivo analysis of protein complexes.

Application of targeted mass spectrometry in bottom-up proteomics for systems biology research

The enormous diversity of proteoforms produces tremendous complexity within cellular proteomes, facilitates intricate networks of molecular interactions, and constitutes a formidable analytical challenge for biomedical researchers. Currently, quantitative whole-proteome profiling often relies on non-targeted liquid chromatography-mass spectrometry (LC-MS), which samples proteoforms broadly, but can suffer from lower accuracy, sensitivity, and reproducibility compared with targeted LC-MS. Recent advances in bottom-up proteomics using targeted LC-MS have enabled previously unachievable identification and quantification of target proteins and posttranslational modifications within complex samples. Consequently, targeted LC-MS is rapidly advancing biomedical research, especially systems biology research in diverse areas that include proteogenomics, interactomics, kinomics, and biological pathway modeling. With the recent development of targeted LC-MS assays for nearly the entire human proteome, targeted LC-MS is positioned to enable quantitative proteomic profiling of unprecedented quality and accessibility to support fundamental and clinical research. Here we review recent applications of bottom-up proteomics using targeted LC-MS for systems biology research. SIGNIFICANCE: Advances in targeted proteomics are rapidly advancing systems biology research. Recent applications include systems-level investigations focused on posttranslational modifications (such as phosphoproteomics), protein conformation, protein-protein interaction, kinomics, proteogenomics, and metabolic and signaling pathways. Notably, absolute quantification of metabolic and signaling pathway proteins has enabled accurate pathway modeling and engineering. Integration of targeted proteomics with other technologies, such as RNA-seq, has facilitated diverse research such as the identification of hundreds of "missing" human proteins (genes and transcripts that appear to encode proteins but direct experimental evidence was lacking).

Enzyme I facilitates reverse flux from pyruvate to phosphoenolpyruvate in Escherichia coli

The bacterial phosphoenolpyruvate-carbohydrate phosphotransferase system (PTS) consists of cascading phosphotransferases that couple the simultaneous import and phosphorylation of a variety of sugars to the glycolytic conversion of phosphoenolpyruvate (PEP) to pyruvate. As the primary route of glucose uptake in E. coli, the PTS plays a key role in regulating central carbon metabolism and carbon catabolite repression, and is a frequent target of metabolic engineering interventions. Here we show that Enzyme I, the terminal phosphotransferase responsible for the conversion of PEP to pyruvate, is responsible for a significant in vivo flux in the reverse direction (pyruvate to PEP) during both gluconeogenic and glycolytic growth. We use 13C alanine tracers to quantify this back-flux in single and double knockouts of genes relating to PEP synthetase and PTS components. Our findings are relevant to metabolic engineering design and add to our understanding of gene-reaction connectivity in E. coli.

Metabolic profiling of recombinant Escherichia coli cultivations based on high-throughput FT-MIR spectroscopic analysis

Escherichia coli is one of the most used host microorganism for the production of recombinant products, such as heterologous proteins and plasmids. However, genetic, physiological and environmental factors influence the plasmid replication and cloned gene expression in a highly complex way. To control and optimize the recombinant expression system performance, it is very important to understand this complexity. Therefore, the development of rapid, highly sensitive and economic analytical methodologies, which enable the simultaneous characterization of the heterologous product synthesis and physiologic cell behavior under a variety of culture conditions, is highly desirable. For that, the metabolic profile of recombinant E. coli cultures producing the pVAX-lacZ plasmid model was analyzed by rapid, economic and high-throughput Fourier Transform Mid-Infrared (FT-MIR) spectroscopy. The main goal of the present work is to show as the simultaneous multivariate data analysis by principal component analysis (PCA) and direct spectral analysis could represent a very interesting tool to monitor E. coli culture processes and acquire relevant information according to current quality regulatory guidelines. While PCA allowed capturing the energetic metabolic state of the cell, e.g. by identifying different C-sources consumption phases, direct FT-MIR spectral analysis allowed obtaining valuable biochemical and metabolic information along the cell culture, e.g. lipids, RNA, protein synthesis and turnover metabolism. The information achieved by spectral multivariate data and direct spectral analyses complement each other and may contribute to understand the complex interrelationships between the recombinant cell metabolism and the bioprocess environment towards more economic and robust processes design according to Quality by Design framework. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 33:285-298, 2017.

Inference of quantitative models of bacterial promoters from time-series reporter gene data

The inference of regulatory interactions and quantitative models of gene regulation from time-series transcriptomics data has been extensively studied and applied to a range of problems in drug discovery, cancer research, and biotechnology. The application of existing methods is commonly based on implicit assumptions on the biological processes under study. First, the measurements of mRNA abundance obtained in transcriptomics experiments are taken to be representative of protein concentrations. Second, the observed changes in gene expression are assumed to be solely due to transcription factors and other specific regulators, while changes in the activity of the gene expression machinery and other global physiological effects are neglected. While convenient in practice, these assumptions are often not valid and bias the reverse engineering process. Here we systematically investigate, using a combination of models and experiments, the importance of this bias and possible corrections. We measure in real time and in vivo the activity of genes involved in the FliA-FlgM module of the E. coli motility network. From these data, we estimate protein concentrations and global physiological effects by means of kinetic models of gene expression. Our results indicate that correcting for the bias of commonly-made assumptions improves the quality of the models inferred from the data. Moreover, we show by simulation that these improvements are expected to be even stronger for systems in which protein concentrations have longer half-lives and the activity of the gene expression machinery varies more strongly across conditions than in the FliA-FlgM module. The approach proposed in this study is broadly applicable when using time-series transcriptome data to learn about the structure and dynamics of regulatory networks. In the case of the FliA-FlgM module, our results demonstrate the importance of global physiological effects and the active regulation of FliA and FlgM half-lives for the dynamics of FliA-dependent promoters.

A wide variety of methods for the reverse engineering of regulatory networks and the identification of quantitative regulation functions are available. We investigate some common assumptions that are made in the application of these methods to time-series transcriptomics data, in the context of a central module in the motility network of E. coli. We show that these assumptions, which hypothesize that mRNA concentrations are good proxies for protein concentrations and that the gene expression machinery is equally active across different physiological conditions, are often not valid and may lead to biased inference results. We also show how models of gene expression can be used in combination with suitable experimental controls to correct for this bias and improve the inference process. The contribution of our work is thus not the addition of another method to the rich store of available reverse engineering algorithms, but lies in the critical examination of the information provided by the experimental data and new ways to exploit this information in the algorithms. The proposed approach is relevant for a wide range of applications using time-series transcriptomics data. For the motility system under study, it has underlined the importance of global physiological effects, the active degradation of the transcription factor FliA as well as the secretion of the anti-sigma factor FlgM for the network dynamics.