Metabolomic analysis of riboswitch containing E. coli recombinant expression system

Dynamic flux balance analysis of high cell density fed-batch culture of Escherichia coli BL21 (DE3) with mass spectrometry-based spent media analysis

Dynamic flux balance analysis (FBA) allows estimation of intracellular reaction rates using organism-specific genome-scale metabolic models (GSMM) and by assuming instantaneous pseudo-steady states for processes that are inherently dynamic. This technique is well-suited for industrial bioprocesses employing complex media characterized by a hierarchy of substrate uptake and product secretion. However, knowledge of exchange rates of many components of the media would be required to obtain meaningful results. Here, we performed spent media analysis using mass spectrometry coupled with liquid and gas chromatography for a fed-batch, high-cell density cultivation of Escherichia coli BL21(DE3) expressing a recombinant protein. Time course measurements thus obtained for 246 metabolites were converted to instantaneous exchange rates. These were then used as constraints for dynamic FBA using a previously reported GSMM, thus providing insights into how the flux map evolves through the process. Changes in tri-carboxylic acid cycle fluxes correlated with the increased demand for energy during recombinant protein production. The results show how amino acids act as hubs for the synthesis of other cellular metabolites. Our results provide a deeper understanding of an industrial bioprocess and will have implications in further optimizing the process.

Precision fermentation with mass spectrometry-based spent media analysis

Optimization and monitoring of bioprocesses requires the measurement of several process parameters and quality attributes. Mass spectrometry (MS)-based techniques such as those coupled to gas chromatography (GCMS) and liquid Chromatography (LCMS) enable the simultaneous measurement of hundreds of metabolites with high sensitivity. When applied to spent media, such metabolome analysis can help determine the sequence of substrate uptake and metabolite secretion, consequently facilitating better design of initial media and feeding strategy. Furthermore, the analysis of metabolite diversity and abundance from spent media will aid the determination of metabolic phases of the culture and the identification of metabolites as surrogate markers for product titer and quality. This review covers the recent advances in metabolomics analysis applied to the development and monitoring of bioprocesses. In this regard, we recommend a stepwise workflow and guidelines that a bioprocesses engineer can adopt to develop and optimize a fermentation process using spent media analysis. Finally, we show examples of how the use of MS can revolutionize the design and monitoring of bioprocesses.

Central carbon metabolite profiling reveals vector-associated differences in the recombinant protein production host Escherichia coli BL21

The Gram-negative bacterium Escherichia coli is the most widely used host for recombinant protein production, both as an industrial expression platform and as a model system at laboratory scale. The recombinant protein production industry generates proteins with direct applications as biopharmaceuticals and in technological processes central to a plethora of fields. Despite the increasing economic significance of recombinant protein production, and the importance of E. coli as an expression platform and model organism, only few studies have focused on the central carbon metabolic landscape of E. coli during high-level recombinant protein production. In the present work, we applied four targeted CapIC- and LC-MS/MS methods, covering over 60 metabolites, to perform an in-depth metabolite profiling of the effects of high-level recombinant protein production in strains derived from E. coli BL21, carrying XylS/Pm vectors with different characteristics. The mass-spectrometric central carbon metabolite profiling was complemented with the study of growth kinetics and protein production in batch bioreactors. Our work shows the robustness in E. coli central carbon metabolism when introducing increased plasmid copy number, as well as the greater importance of induction of recombinant protein production as a metabolic challenge, especially when strong promoters are used.

Overexpression of bacteriophage T4 and T7 endolysins differentially regulate the metabolic fingerprint of host Escherichia coli

Bioactive proteins are often overexpressed in different host systems for biotechnological/biomedical applications. Endolysins are natural bactericidal proteins that cleave the bacterial peptidoglycan membrane, and have the potential to be the next-generation enzybiotics. Therefore, the present study aims to elucidate the impact of two endolysins (T4L, T7L) overexpression on metabolic fingerprint of E. coli using NMR spectroscopy. The ¹H NMR-based metabolomics analysis revealed global metabolite profiles of E. coli in response to endolysins. The study has identified nearly 75 metabolites, including organic acids, amino acids, sugars and nucleic acids. RNA Polymerase (RNAP) has been considered as reference protein for marking the specific alterations in metabolic pathways. The data suggested downregulation of central carbon metabolic pathway in both endolysins overexpression, but to a different extent. Also, the endolysin overexpression have highlighted the enhanced metabolic load and stress generation in the host cells, thus leading to the activation of osmoregulatory pathways. The overall changes in metabolic fingerprint of E. coli highlights the enhanced perturbations during the overexpression of T4L as compared to T7L. These untargeted metabolic studies shed light on the regulation of molecular pathways during the heterologous overexpression of these lytic enzymes that are lethal to the host.

Metabolic Fingerprint Analysis of Cytochrome b5-producing E. coli N4830-1 Using FT-IR Spectroscopy

Optimization of recombinant protein expression in bacteria is an important task in order to increase protein yield while maintaining the structural fidelity of the product. In this study, we employ Fourier transform infrared (FT-IR) spectroscopy as a high throughput metabolic fingerprinting approach to optimize and monitor cytochrome b₅ (CYT b₅) production in Escherichia coli N4830-1, as the heterologous host. Cyt b₅ was introduced as a plasmid with between 0 and 6 copies under a strong promoter. The FT-IR spectroscopy results combined with multivariate chemometric analysis illustrated discriminations among culture conditions as well as revealing features that correlated to the different cytb₅ gene copy numbers. The second derivative of the FT-IR spectral data allowed for the quantitative detection of Cyt b₅ directly inside the intact cells without the need for extraction, and highlighted changes in protein secondary structure that was directly correlated to the cytb₅ gene copy number and protein content, and was in complete agreement with quantitative findings of standard traditional techniques such as SDS–PAGE and western blot analysis.

Improving the Robustness of Engineered Bacteria to Nutrient Stress Using Programmed Proteolysis

The use of short peptide tags in synthetic genetic circuits allows for the tuning of gene expression dynamics and release of amino acid resources through targeted protein degradation. Here, we use elements of the Escherichia coli and Mesoplasma florum transfer-mRNA (tmRNA) ribosome rescue systems to compare endogenous and foreign proteolysis systems in E. coli. We characterize the performance and burden of each and show that, while both greatly shorten the half-life of a tagged protein, the endogenous system is approximately 10 times more efficient. On the basis of these results we then demonstrate using mathematical modeling and experiments how proteolysis can improve cellular robustness through targeted degradation of a reporter protein in auxotrophic strains, providing a limited secondary source of essential amino acids that help partially restore growth when nutrients become scarce. These findings provide avenues for controlling the functional lifetime of engineered cells once deployed and increasing their tolerance to fluctuations in nutrient availability.

Evaluation of Sample Preparation Methods for Inter-Laboratory Metabolomics Investigation of Streptomyces lividans TK24

In the past two decades, metabolomics has proved to be a valuable tool with many potential applications in different areas of science. However, there are still some challenges that need to be addressed, particularly for multicenter studies. These challenges are mainly attributed to various sources of fluctuation and unwanted variations that can be introduced at pre-analytical, analytical, and/or post-analytical steps of any metabolomics experiment. Thus, this study aimed at using Streptomyces lividans TK24 as the model organism in a cross-laboratory experiment in Manchester and Leuven to evaluate the reproducibility of a standard sample preparation method, and determine the optimal sample format (cell extract or quenched biomass) required to preserve the metabolic profile of the cells during cross-lab sample transportation and storage. Principal component analysis (PCA) scores plot of the gas chromatography-mass spectrometry (GC-MS) data from both laboratories displayed clear growth-dependent clustering patterns which was in agreement with the Procrustes analysis findings. In addition, the data generated in Manchester displayed tight clustering of cell pellets (quenched biomass) and metabolite extracts, confirming the stability of both sample formats during the transportation and storage period.

Systematic Evaluation of Genetic and Environmental Factors Affecting Performance of Translational Riboswitches

Since their discovery, riboswitches have been attractive tools for the user-controlled regulation of gene expression in bacterial systems. Riboswitches facilitate small molecule mediated fine-tuning of protein expression, making these tools of great use to the synthetic biology community. However, the use of riboswitches is often restricted due to context dependent performance and limited dynamic range. Here, we report the drastic improvement of a previously developed orthogonal riboswitch achieved through in vivo functional selection and optimization of flanking coding and noncoding sequences. The behavior of the derived riboswitches was mapped under a wide array of growth and induction conditions, using a structured Design of Experiments approach. This approach successfully improved the maximal protein expression levels 8.2-fold relative to the original riboswitches, and the dynamic range was improved to afford riboswitch dependent control of 80-fold. The optimized orthogonal riboswitch was then integrated downstream of four endogenous stress promoters, responsive to phosphate starvation, hyperosmotic stress, redox stress, and carbon starvation. These responsive stress promoter-riboswitch devices were demonstrated to allow for tuning of protein expression up to ∼650-fold in response to both environmental and cellular stress responses and riboswitch dependent attenuation. We envisage that these riboswitch stress responsive devices will be useful tools for the construction of advanced genetic circuits, bioprocessing, and protein expression.

Tuning recombinant protein expression to match secretion capacity

Background

The secretion of recombinant disulfide-bond containing proteins into the periplasm of Gram-negative bacterial hosts, such as E. coli, has many advantages that can facilitate product isolation, quality and activity. However, the secretion machinery of E. coli has a limited capacity and can become overloaded, leading to cytoplasmic retention of product; which can negatively impact cell viability and biomass accumulation. Fine control over recombinant gene expression offers the potential to avoid this overload by matching expression levels to the host secretion capacity.

Results

Here we report the application of the RiboTite gene expression control system to achieve this by finely controlling cellular expression levels. The level of control afforded by this system allows cell viability to be maintained, permitting production of high-quality, active product with enhanced volumetric titres.

Conclusions

The methods and systems reported expand the tools available for the production of disulfide-bond containing proteins, including antibody fragments, in bacterial hosts.

Electronic supplementary material

The online version of this article (10.1186/s12934-018-1047-z) contains supplementary material, which is available to authorized users.

Rapid, accurate, and comparative differentiation of clinically and industrially relevant microorganisms via multiple vibrational spectroscopic fingerprinting

Despite the fact that various microorganisms (e.g., bacteria, fungi, viruses, etc.) have been linked with infectious diseases, their crucial role towards sustaining life on Earth is undeniable. The huge biodiversity, combined with the wide range of biochemical capabilities of these organisms, have always been the driving force behind their large number of current, and, as of yet, undiscovered future applications. The presence of such diversity could be said to expedite the need for the development of rapid, accurate and sensitive techniques which allow for the detection, differentiation, identification and classification of such organisms. In this study, we employed Fourier transform infrared (FT-IR), Raman, and surface enhanced Raman scattering (SERS) spectroscopies, as molecular whole-organism fingerprinting techniques, combined with multivariate statistical analysis approaches for the classification of a range of industrial, environmental or clinically relevant bacteria (P. aeruginosa, P. putida, E. coli, E. faecium, S. lividans, B. subtilis, B. cereus) and yeast (S. cerevisiae). Principal components-discriminant function analysis (PC-DFA) scores plots of the spectral data collected from all three techniques allowed for the clear differentiation of all the samples down to sub-species level. The partial least squares-discriminant analysis (PLS-DA) models generated using the SERS spectral data displayed lower accuracy (74.9%) when compared to those obtained from conventional Raman (97.8%) and FT-IR (96.2%) analyses. In addition, whilst background fluorescence was detected in Raman spectra for S. cerevisiae, this fluorescence was quenched when applying SERS to the same species, and conversely SERS appeared to introduce strong fluorescence when analysing P. putida. It is also worth noting that FT-IR analysis provided spectral data of high quality and reproducibility for the whole sample set, suggesting its applicability to a wider range of samples, and perhaps the most suitable for the analysis of mixed cultures in future studies. Furthermore, our results suggest that while each of these spectroscopic approaches may favour different organisms (sample types), when combined, they would provide complementary and more in-depth knowledge (structural and/or metabolic state) of biological systems. To the best of our knowledge, this is the first time that such a comparative and combined spectroscopic study (using FT-IR, Raman and SERS) has been carried out on microbial samples.

Translation Stress Positively Regulates MscL-Dependent Excretion of Cytoplasmic Proteins

The apparent mislocalization or excretion of cytoplasmic proteins is a commonly observed phenomenon in both bacteria and eukaryotes. However, reports on the mechanistic basis and the cellular function of this so-called “nonclassical protein secretion” are limited. Here we report that protein overexpression in recombinant cells and antibiotic-induced translation stress in wild-type Escherichia coli cells both lead to excretion of cytoplasmic protein (ECP). Condition-specific metabolomic and proteomic analyses, combined with genetic knockouts, indicate a role for both the large mechanosensitive channel (MscL) and the alternative ribosome rescue factor A (ArfA) in ECP. Collectively, the findings indicate that MscL-dependent protein excretion is positively regulated in response to both osmotic stress and arfA-mediated translational stress.

Protein translocation is an essential feature of cellular organisms. Bacteria, like all single-cell organisms, interact with their environment by translocation of proteins across their cell membranes via dedicated secretion pathways. Proteins destined for secretion are directed toward the secretion pathways by the presence of specific signal peptides. This study demonstrates that under conditions of both osmotic stress and translation stress, E. coli cells undergo an excretion phenomenon whereby signal peptide-less proteins are translocated across both the inner and outer cell membranes into the extracellular environment. Confirming the presence of alternative translocation/excretion pathways and understanding their function and regulation are thus important for fundamental microbiology and biotechnology.

Systematic optimization of L-tryptophan riboswitches for efficient monitoring of the metabolite in Escherichia coli

Riboswitches form a class of genetically encoded sensor-regulators and are considered as promising tools for monitoring various metabolites. Functional parameters of a riboswitch, like dynamic or operational range, should be optimized before the riboswitch is implemented in a specific application for monitoring the target molecule efficiently. However, optimization of a riboswitch was not straightforward and required detailed studies owing to its complex sequence-function relationship. Here, we present three approaches for tuning and optimization of functional parameters of a riboswitch using an artificial L-tryptophan riboswitch as an example. First, the constitutive expression level was adjusted to control the dynamic range of an L-tryptophan riboswitch. The dynamic range increased as the constitutive expression level increased. Then, the function of a riboswitch-encoded protein was utilized to connect the regulatory response of the riboswitch to another outcome for amplifying the dynamic range. Riboswitch-mediated control of the host cell growth enabled the amplification of the riboswitch response. Finally, L-tryptophan aptamers with different dissociation constants were employed to alter the operational range of the riboswitch. The dose-response curve was shifted towards higher L-tryptophan concentrations when an aptamer with higher dissociation constant was employed. All strategies were effective in modifying the distinct functional parameters of the L-tryptophan riboswitch, and they could be easily applied to optimization of other riboswitches owing to their simplicity.

Partial Least Squares with Structured Output for Modelling the Metabolomics Data Obtained from Complex Experimental Designs: A Study into the Y-Block Coding

Partial least squares (PLS) is one of the most commonly used supervised modelling approaches for analysing multivariate metabolomics data. PLS is typically employed as either a regression model (PLS-R) or a classification model (PLS-DA). However, in metabolomics studies it is common to investigate multiple, potentially interacting, factors simultaneously following a specific experimental design. Such data often cannot be considered as a “pure” regression or a classification problem. Nevertheless, these data have often still been treated as a regression or classification problem and this could lead to ambiguous results. In this study, we investigated the feasibility of designing a hybrid target matrix Y that better reflects the experimental design than simple regression or binary class membership coding commonly used in PLS modelling. The new design of Y coding was based on the same principle used by structural modelling in machine learning techniques. Two real metabolomics datasets were used as examples to illustrate how the new Y coding can improve the interpretability of the PLS model compared to classic regression/classification coding.

SYNBIOCHEM Synthetic Biology Research Centre, Manchester - A UK foundry for fine and speciality chemicals production

The UK Synthetic Biology Research Centre, SYNBIOCHEM, hosted by the Manchester Institute of Biotechnology at the University of Manchester is delivering innovative technology platforms to facilitate the predictable engineering of microbial bio-factories for fine and speciality chemicals production. We provide an overview of our foundry activities that are being applied to grand challenge projects to deliver innovation in bio-based chemicals production for industrial biotechnology.