The interrelationship between promoter strength, gene expression, and growth rate

Optimization of electroporation method and promoter evaluation for type-1 methanotroph, Methylotuvimicrobium alcaliphilum

Methanotrophic bacteria are promising hosts for methane bioconversion to biochemicals or bioproducts. However, due to limitations associated with long genetic manipulation timelines and, lack of choice in genetic tools required for strain engineering, methanotrophs are currently not employed for bioconversion technologies. In this study, a rapid and reproducible electroporation protocol is developed for type 1 methanotroph, Methylotuvimicrobium alcaliphilum using common laboratory solutions, analyzing optimal electroshock voltages and post-shock cell recovery time. Successful reproducibility of the developed method was achieved when different replicative plasmids were assessed on lab adapted vs. wild-type M. alcaliphilum strains (DASS vs. DSM19304). Overall, a ∼ 3-fold decrease in time is reported with use of electroporation protocol developed here, compared to conjugation, which is the traditionally employed approach. Additionally, an inducible (3-methyl benzoate) and a constitutive (sucrose phosphate synthase) promoter is characterized for their strength in driving gene expression.

The energetic costs of cellular complexity in evolution

The evolutionary history of cells has been marked by drastic increases in complexity. Some hypothesize that such cellular complexification requires a massive energy flux as the origin of new features is hypothetically more energetically costly than their evolutionary maintenance. However, it remains unclear how increases in cellular complexity demand more energy. I propose that the early evolution of new genes with weak functions imposes higher energetic costs by overexpression before their functions are evolutionarily refined. In the long term, the accumulation of new genes deviates resources away from growth and reproduction. Accrued cellular complexity further requires additional infrastructure for its maintenance. Altogether, this suggests that larger and more complex cells are defined by increased survival but lower reproductive capacity.

Fighting the battle against evolution: designing genetically modified organisms for evolutionary stability

Synthetic biology has made significant progress in many areas, but a major challenge that has received limited attention is the evolutionary stability of synthetic constructs made of heterologous genes. The expression of these constructs in microorganisms, that is, production of proteins that are not necessary for the organism, is a metabolic burden, leading to a decrease in relative fitness and make the synthetic constructs unstable over time. This is a significant concern for the synthetic biology community, particularly when it comes to bringing this technology out of the laboratory. In this review, we discuss the issue of evolutionary stability in synthetic biology and review the available tools to address this challenge.

Feedforward growth rate control mitigates gene activation burden

Heterologous gene activation causes non-physiological burden on cellular resources that cells are unable to adjust to. Here, we introduce a feedforward controller that actuates growth rate upon activation of a gene of interest (GOI) to compensate for such a burden. The controller achieves this by activating a modified SpoT enzyme (SpoTH) with sole hydrolysis activity, which lowers ppGpp level and thus increases growth rate. An inducible RelA+ expression cassette further allows to precisely set the basal level of ppGpp, and thus nominal growth rate, in any bacterial strain. Without the controller, activation of the GOI decreased growth rate by more than 50%. With the controller, we could activate the GOI to the same level without growth rate defect. A cell strain armed with the controller in co-culture enabled persistent population-level activation of a GOI, which could not be achieved by a strain devoid of the controller. The feedforward controller is a tunable, modular, and portable tool that allows dynamic gene activation without growth rate defects for bacterial synthetic biology applications.

Advancing Yarrowia lipolytica as a superior biomanufacturing platform by tuning gene expression using promoter engineering

Yarrowia lipolytica is recognized as an excellent non-conventional yeast in the field of biomanufacturing, where it is used as a host to produce oleochemicals, terpenes, organic acids, polyols and recombinant proteins. Consequently, metabolic engineering of this yeast is becoming increasingly popular to advance it as a superior biomanufacturing platform, of which promoters are the most basic elements for tuning gene expression. Endogenous promoters of Yarrowia lipolytica were reviewed, which are the basis for promoter engineering. The engineering strategies, such as hybrid promoter engineering, intron enhancement promoter engineering, and transcription factor-based inducible promoter engineering are described. Additionally, the applications of Yarrowia lipolytica promoter engineering to rationally reconstruct biosynthetic gene clusters and improve the genome-editing efficiency of the CRISPR-Cas systems were reviewed. Finally, research needs and future directions for promoter engineering are also discussed in this review.

Toward improved terpenoids biosynthesis: strategies to enhance the capabilities of cell factories

Terpenoids form the most diversified class of natural products, which have gained application in the pharmaceutical, food, transportation, and fine and bulk chemical industries. Extraction from naturally occurring sources does not meet industrial demands, whereas chemical synthesis is often associated with poor enantio-selectivity, harsh working conditions, and environmental pollutions. Microbial cell factories come as a suitable replacement. However, designing efficient microbial platforms for isoprenoid synthesis is often a challenging task. This has to do with the cytotoxic effects of pathway intermediates and some end products, instability of expressed pathways, as well as high enzyme promiscuity. Also, the low enzymatic activity of some terpene synthases and prenyltransferases, and the lack of an efficient throughput system to screen improved high-performing strains are bottlenecks in strain development. Metabolic engineering and synthetic biology seek to overcome these issues through the provision of effective synthetic tools. This review sought to provide an in-depth description of novel strategies for improving cell factory performance. We focused on improving transcriptional and translational efficiencies through static and dynamic regulatory elements, enzyme engineering and high-throughput screening strategies, cellular function enhancement through chromosomal integration, metabolite tolerance, and modularization of pathways.

Predicting Composition of Genetic Circuits with Resource Competition: Demand and Sensitivity

The design of genetic circuits typically relies on characterization of constituent modules in isolation to predict the behavior of modules' composition. However, it has been shown that the behavior of a genetic module changes when other modules are in the cell due to competition for shared resources. In order to engineer multimodule circuits that behave as intended, it is thus necessary to predict changes in the behavior of a genetic module when other modules load cellular resources. Here, we introduce two characteristics of circuit modules: the demand for cellular resources and the sensitivity to resource loading. When both are known for every genetic module in a circuit library, they can be used to predict any module's behavior upon addition of any other module to the cell. We develop an experimental approach to measure both characteristics for any circuit module using a resource sensor module. Using the measured resource demand and sensitivity for each module in a library, the outputs of the modules can be accurately predicted when they are inserted in the cell in arbitrary combinations. These resource competition characteristics may be used to inform the design of genetic circuits that perform as predicted despite resource competition.

RBS and Promoter Strengths Determine the Cell-Growth-Dependent Protein Mass Fractions and Their Optimal Synthesis Rates

Models of gene expression considering host–circuit interactions are relevant for understanding both the strategies and associated trade-offs that cell endogenous genes have evolved and for the efficient design of heterologous protein expression systems and synthetic genetic circuits. Here, we consider a small-size model of gene expression dynamics in bacterial cells accounting for host–circuit interactions due to limited cellular resources. We define the cellular resources recruitment strength as a key functional coefficient that explains the distribution of resources among the host and the genes of interest and the relationship between the usage of resources and cell growth. This functional coefficient explicitly takes into account lab-accessible gene expression characteristics, such as promoter and ribosome binding site (RBS) strengths, capturing their interplay with the growth-dependent flux of available free cell resources. Despite its simplicity, the model captures the differential role of promoter and RBS strengths in the distribution of protein mass fractions as a function of growth rate and the optimal protein synthesis rate with remarkable fit to the experimental data from the literature for Escherichia coli. This allows us to explain why endogenous genes have evolved different strategies in the expression space and also makes the model suitable for model-based design of exogenous synthetic gene expression systems with desired characteristics.

Development of an Autoinducible Plasmid for Recombinant Protein Production

BACKGROUND

The production of recombinant proteins in E. coli involves such factors as host strains, expression vectors, culture media, and induction methods. The typical procedure to produce heterologous proteins consists of the following: (1) insertion of the target gene into a suitable vector to construct an overexpression plasmid, (2) transformation of a strain specialized for protein production with the constructed plasmid DNA, (3) growth of the host in a suitable medium and induction of the protein production at a right moment, and (4) further growth to get the maximum yield. There are hurdles involved in each of these steps, and researchers have developed many materials or methods, which often require special recipes or procedures.

OBJECTIVE

To eliminate the special requirements for the recombinant protein production by using readily available materials. Also to save time and effort in the routine protein production work.

METHOD

We started with a vector capable of producing a target protein fused to the C-terminus of the maltose binding protein (MBP). The mCherry (red fluorescent protein) gene was fused to MBP. It acted as a reporter in the initial screening procedure. The original lethal gene (barnase) was replaced with sacB. We chose 3 stationary phase promoters, and made hybrids of them by mixing halves from each one. The T5 promoter was replaced with these stationary phase promoters or their hybrids. The best plasmid was selected by the color intensity of the cell pellet. MBP and GST genes were inserted in place of sacB, and their production yields were compared with the original plasmid in the conventional way of expression.

RESULTS

We constructed an expression plasmid with an autoinducible promoter working in a host that was not specially designed for protein production and in a TB medium which did not contain any secret ingredient, nor was difficult to prepare unlike Studier's defined medium. This plasmid also contains a color indicator which turns red when protein production is successful. We tested our system with the maltose binding protein (MBP) and the glutathione S-transferase (GST), and showed that both proteins were produced to a level comparable to what the commercial medium and/or the specialized strain yielded.

CONCLUSION

We developed a plasmid equipped with an autoinducible promoter, a hybrid of the two promoters which were activated at the stationary phase. This plasmid does not need a special E. coli strain nor a sophisticated nor an expensive medium. It produces an intense red (or pink) color, which can be used as an indicator of a successful production of the target protein and as a predictive measure of the amount of the produced target protein. We speculate that this plasmid will have its greatest advantage when growing cells at low temperatures which would inevitably take a long time.  .

Engineered Attenuated Salmonella typhimurium Expressing Neoantigen Has Anticancer Effects

Neoantigen vaccines are an immunotherapy strategy for treating cancer. The vaccine degrades quickly, so the strategy must include protection and precise targeting for immune cell stimulation. In this study, we engineered attenuated Salmonella typhimurium, which is highly infiltrative to tumors, to act as a carrier for Neoantigen peptide vaccine. Our system used a constitutive promoter vector, so that a single injection of Salmonella expressing Neoantigen could be used without requiring additional induction injections. In vivo experiments on bacteria-treated mice showed that Neoantigen expressed by the engineered carrier infiltrated tumors and resulted in suppressed tumor growth, higher survival rates and longer survival times, a relative increase of CD4 and CD8 T cells, and cytokine release. These results indicate that engineered Salmonella can be used as a carrier for Neoantigen immunotherapy.

Promoter Architecture Differences among Alphaproteobacteria and Other Bacterial Taxa

Much of our knowledge of bacterial transcription initiation has been derived from studying the promoters of Escherichia coli and Bacillus subtilis. Given the expansive diversity across the bacterial phylogeny, it is unclear how much of this knowledge can be applied to other organisms. Here, we report on bioinformatic analyses of promoter sequences of the primary σ factor (σ70) by leveraging publicly available transcription start site (TSS) sequencing data sets for nine bacterial species spanning five phyla. This analysis identifies previously unreported differences in the -35 and -10 elements of σ70-dependent promoters in several groups of bacteria. We found that Actinobacteria and Betaproteobacteria σ70-dependent promoters lack the TTG triad in their -35 element, which is predicted to be conserved across the bacterial phyla. In addition, the majority of the Alphaproteobacteria σ70-dependent promoters analyzed lacked the thymine at position -7 that is highly conserved in other phyla. Bioinformatic examination of the Alphaproteobacteria σ70-dependent promoters identifies a significant overrepresentation of essential genes and ones encoding proteins with common cellular functions downstream of promoters containing an A, C, or G at position -7. We propose that transcription of many σ70-dependent promoters in Alphaproteobacteria depends on the transcription factor CarD, which is an essential protein in several members of this phylum. Our analysis expands the knowledge of promoter architecture across the bacterial phylogeny and provides new information that can be used to engineer bacteria for use in medical, environmental, agricultural, and biotechnological processes. IMPORTANCE Transcription of DNA to RNA by RNA polymerase is essential for cells to grow, develop, and respond to stress. Understanding the process and control of transcription is important for health, disease, the environment, and biotechnology. Decades of research on a few bacteria have identified promoter DNA sequences that are recognized by the σ subunit of RNA polymerase. We used bioinformatic analyses to reveal previously unreported differences in promoter DNA sequences across the bacterial phylogeny. We found that many Actinobacteria and Betaproteobacteria promoters lack a sequence in their -35 DNA recognition element that was previously assumed to be conserved and that Alphaproteobacteria lack a thymine residue at position -7, also previously assumed to be conserved. Our work reports important new information about bacterial transcription, illustrates the benefits of studying bacteria across the phylogenetic tree, and proposes new lines of future investigation.

The Marburg Collection: A Golden Gate DNA Assembly Framework for Synthetic Biology Applications in Vibrio natriegens

Vibrio natriegens is known as the world's fastest growing organism with a doubling time of less than 10 min. This incredible growth speed empowers V. natriegens as a chassis for synthetic and molecular biology, potentially replacing E. coli in many applications. While first genetic parts have been built and tested for V. natriegens, a comprehensive toolkit containing well-characterized and standardized parts did not exist. To close this gap, we created the Marburg Collection-a highly flexible Golden Gate cloning toolbox optimized for the emerging chassis organism V. natriegens, containing 191 genetic parts. The Marburg Collection overcomes the paradigm of plasmid construction-integrating inserts into a backbone-by enabling the de novo assembly of plasmids from basic genetic parts. This allows users to select the plasmid replication origin and resistance part independently, which is highly advantageous when limited knowledge about the behavior of those parts in the target organism is available. Additional design highlights of the Marburg Collection are novel connector parts, which facilitate modular circuit assembly and, optionally, the inversion of individual transcription units to reduce transcriptional crosstalk in multigene constructs. To quantitatively characterize the genetic parts contained in the Marburg Collection in V. natriegens, we developed a reliable microplate reader measurement workflow for reporter experiments and overcame organism-specific challenges. We think the Marburg Collection with its thoroughly characterized parts will provide a valuable resource for the growing V. natriegens community.

A plant CitPITP1 protein-coding exon sequence serves as a promoter in bacteria

Genetic manipulation of plant genes in prokaryotes has been widely used in molecular biology, but the function of a DNA sequence is far from being fully known. Here, we discovered that a plant protein-coding gene containing the CRAL_TRIO domain serves as a promoter in bacteria. We firstly characterized CitPITP1 from Citrus, which contains the CRAL_TRIO domain, and identified a 64-bp sequence (key64) that is critical for prokaryotic promoter activity. In vitro experiments indicated that the bacterial RNA polymerase subunit RpoD specifically binds to key64. We then expanded our research to fungi, plant and animal species to identify key64-like sequences. Five such prokaryotic promoters were isolated from Amborella, Rice, Arabidopsis and Citrus. Two conserved motifs were identified, and mutation analysis indicated that the nucleotides at positions 7, 29 and 30 are crucial for key64-like transcription activity. We detected full-length recombinant CitPITP1 from E. coli, and visualized a CitPITP1-GFP fusion protein in plant cells, supporting the idea that CitPITP1 encodes a protein. However, although exon 4 of CitPITP1 contained key64, it did not demonstrate promoter activity in plants. Our study describes a new basal promoter, provides evidence for neofunction of gene elements across different kingdoms, and provides new knowledge for the modular design of promoters.

Gene Expression Space Shapes the Bioprocess Trade-Offs among Titer, Yield and Productivity

Optimal gene expression is central for the development of both bacterial expression systems for heterologous protein production, and microbial cell factories for industrial metabolite production. Our goal is to fulfill industry-level overproduction demands optimally, as measured by the following key performance metrics: titer, productivity rate, and yield (TRY). Here we use a multiscale model incorporating the dynamics of (i) the cell population in the bioreactor, (ii) the substrate uptake and (iii) the interaction between the cell host and expression of the protein of interest. Our model predicts cell growth rate and cell mass distribution between enzymes of interest and host enzymes as a function of substrate uptake and the following main lab-accessible gene expression-related characteristics: promoter strength, gene copy number and ribosome binding site strength. We evaluated the differential roles of gene transcription and translation in shaping TRY trade-offs for a wide range of expression levels and the sensitivity of the TRY space to variations in substrate availability. Our results show that, at low expression levels, gene transcription mainly defined TRY, and gene translation had a limited effect; whereas, at high expression levels, TRY depended on the product of both, in agreement with experiments in the literature.

Rational engineering strategies for achieving high-yield, high-quality and high-stability of natural product production in actinomycetes

Actinomycetes are recognized as excellent producers of microbial natural products, which have a wide range of applications, especially in medicine, agriculture and stockbreeding. The three main indexes of industrialization (titer, purity and stability) must be taken into overall consideration in the manufacturing process of natural products. Over the past decades, synthetic biology techniques have expedited the development of industrially competitive strains with excellent performances. Here, we summarize various rational engineering strategies for upgrading the performance of industrial actinomycetes, which include enhancing the yield of natural products, eliminating the by-products and improving the genetic stability of engineered strains. Furthermore, the current challenges and future perspectives for optimizing the industrial strains more systematically through combinatorial engineering strategies are also discussed.

Robotic integration enables autonomous operation of laboratory scale stirred tank bioreactors with model-driven process analysis

Given its geometric similarity to large-scale production plants and the excellent possibilities for precise process control and monitoring, the classic stirred tank bioreactor (STR) still represents the gold standard for bioprocess development at a laboratory scale. However, compared to microbioreactor technologies, bioreactors often suffer from a low degree of process automation and deriving key performance indicators (KPIs) such as specific rates or yields often requires manual sampling and sample processing. A widely used parallelized STR setup was automated by connecting it to a liquid handling system and controlling it with a custom-made process control system. This allowed for the setup of a flexible modular platform enabling autonomous operation of the bioreactors without any operator present. Multiple unit operations like automated inoculation, sampling, sample processing and analysis, and decision making, for example for automated induction of protein production were implemented to achieve such functionality. The data gained during application studies was used for fitting of bioprocess models to derive relevant KPIs being in good agreement with literature. By combining the capabilities of STRs with the flexibility of liquid handling systems, this platform technology can be applied to a multitude of different bioprocess development pipelines at laboratory scale.

The Effect of Promoter and RBS Combination on the Growth and Glycogen Productivity of Sodium-Dependent Bicarbonate Transporter (SbtA) Overexpressing Synechococcus sp. PCC 7002 Cells

Sodium dependent bicarbonate transporter, SbtA is a high-affinity, inducible bicarbonate transporter in cyanobacterial cells. Our previous work has shown that overexpression of this transporter can significantly increase growth and glycogen accumulation in Synechococcus sp. PCC 7002 cells. In this work, we have tested the effect of two different RBS sequences (RBS1: GGAGGA and RBS2: AGGAGA) and three different promoters (P_cpcB, P_cpcB560, and P_rbcL2) on the growth and glycogen production in SbtA-overexpressing Synechococcus sp. PCC 7002 cells. Our results show that P_cpcB or P_cpcB560 were more effective than P_rbcL2 in increasing the growth and glycogen content. The choice of RBS sequence had relatively minor effect, though RBS2 was more effective than RBS1. The transformant E, with P_cpcB560 and RBS2, showed the highest growth. The biomass after 5 days of growth on air or 1% CO₂ was increased by about 90% in the strain E compared to PCC 7002 cells. All transformants overexpressing SbtA had higher glycogen content. However, growing the cells with bubbling of 1% CO₂ did not increase cellular glycogen content any further. The strain E had about 80% higher glycogen content compared to WT PCC 7002 cells. Therefore, the glycogen productivity of the strain E grown with air-bubbling was about 2.5-fold that of the WT PCC 7002 cells grown similarly. Additionally, some of the transformants had higher chlorophyll content while all the transformants had higher carotenoid content compared to the PCC 7002 cells, suggesting interaction between carbon transport and pigment levels. Thus, this work shows that the choice of photosynthetic promoters and RBSs sequences can impact growth and glycogen accumulation in SbtA-overexpressing cells.

Proteome Regulation Patterns Determine Escherichia coli Wild-Type and Mutant Phenotypes

It is generally recognized that proteins constitute the key cellular component in shaping microbial phenotypes. Due to limited cellular resources and space, optimal allocation of proteins is crucial for microbes to facilitate maximum proliferation rates while allowing a flexible response to environmental changes. To account for the growth condition-dependent proteome in the constraint-based metabolic modeling of Escherichia coli, we consolidated a coarse-grained protein allocation approach with the explicit consideration of enzymatic constraints on reaction fluxes. Besides representing physiologically relevant wild-type phenotypes and flux distributions, the resulting protein allocation model (PAM) advances the predictability of the metabolic responses to genetic perturbations. A main driver of mutant phenotypes was ascribed to inherited regulation patterns in protein distribution among metabolic enzymes. Moreover, the PAM correctly reflected metabolic responses to an augmented protein burden imposed by the heterologous expression of green fluorescent protein. In summary, we were able to model the effects of important and frequently applied metabolic engineering approaches on microbial metabolism. Therefore, we want to promote the integration of protein allocation constraints into classical constraint-based models to foster their predictive capabilities and application for strain analysis and engineering purposes.

IMPORTANCE Predictive metabolic models are important, e.g., for generating biological knowledge and designing microbes with superior performance for target compound production. Yet today’s whole-cell models either show insufficient predictive capabilities or are computationally too expensive to be applied to metabolic engineering purposes. By linking the inherent genotype-phenotype relationship to a complete representation of the proteome, the PAM advances the accuracy of simulated phenotypes and intracellular flux distributions of E. coli. Being equally computationally lightweight as classical stoichiometric models and allowing for the application of established in silico tools, the PAM and related simulation approaches will foster the use of a model-driven metabolic research. Applications range from the investigation of mechanisms of microbial evolution to the determination of optimal strain design strategies in metabolic engineering, thus supporting basic scientists and engineers alike.

Monitoring and control of E. coli cell integrity

Soluble expression of recombinant proteins in E. coli is often done by translocation of the product across the inner membrane (IM) into the periplasm, where it is retained by the outer membrane (OM). While the integrity of the IM is strongly coupled to viability and impurity release, a decrease in OM integrity (corresponding to increased "leakiness") leads to accumulation of product in the extracellular space, strongly impacting the downstream process. Whether leakiness is desired or not, differential monitoring and control of IM and OM integrity are necessary for an efficient E. coli bioprocess in compliance with the guidelines of Quality by Design and Process Analytical Technology. In this review, we give an overview of relevant monitoring tools, summarize the research on factors affecting E. coli membrane integrity and provide a brief discussion on how the available monitoring technology can be implemented in real-time control of E. coli cultivations.

Microbial Production of Retinyl Palmitate and Its Application as a Cosmeceutical

Chemically synthesized retinyl palmitate has been widely used in the cosmetic and biotechnology industry. In this study, we aimed to demonstrate the microbial production of retinyl palmitate and the benefits of microbial retinyl palmitate in skin physiology. A heterologous retinyl palmitate biosynthesis pathway was reconstructed in metabolically engineered Escherichia coli using synthetic expression modules from Pantoea agglomerans, Salinibacter ruber, and Homo sapiens. High production of retinyl palmitate (69.96 ± 2.64 mg/L) was obtained using a fed-batch fermentation process. Moreover, application of purified microbial retinyl palmitate to human foreskin HS68 fibroblasts led to increased cellular retinoic acid-binding protein 2 (CRABP2) mRNA level [1.7-fold (p = 0.001) at 100 μg/mL], acceleration of cell proliferation, and enhancement of procollagen synthesis [111% (p < 0.05) at 100 μg/mL], strongly indicating an anti-ageing-related effect of this substance. These results would pave the way for large-scale production of retinyl palmitate in microbial systems and represent the first evidence for the application of microbial retinyl palmitate as a cosmeceutical.

Inhibition of E. coli Host RNA Polymerase Allows Efficient Extracellular Recombinant Protein Production by Enhancing Outer Membrane Leakiness

With the growing interest in continuous cultivation of Escherichia coli, secretion of product to the medium is not only a benefit, but a necessity in future bioprocessing. In this study, it is shown that induced decoupling of growth and heterologous gene expression in the E. coli X-press strain (derived from BL21(DE3)) facilitates extracellular recombinant protein production. The effect of the process parameters temperature and specific glucose consumption rate (q_S ) on growth, productivity, lysis and leakiness, is investigated, to find the parameter space allowing extracellular protein production. Two model proteins are used, Protein A (SpA) and a heavy-chain single-domain antibody (VHH), and performance is compared to the industrial standard strain BL21(DE3). It is shown that inducible growth repression in the X-press strain greatly mitigates the effect of metabolic burden under different process conditions. Furthermore, temperature and q_S are used to control productivity and leakiness. In the X-press strain, extracellular SpA and VHH titer reach up to 349 and 19.6 mg g^-1 , respectively, comprising up to 90% of the total soluble product, while keeping cell lysis at a minimum. The findings demonstrate that the X-press strain constitutes a valuable host for extracellular production of recombinant protein with E. coli.

A quantitative method for proteome reallocation using minimal regulatory interventions

Engineering resource allocation in biological systems is an ongoing challenge. Organisms allocate resources for ensuring survival, reducing the productivity of synthetic biology functions. Here we present a new approach for engineering the resource allocation of Escherichia coli by rationally modifying its transcriptional regulatory network. Our method (ReProMin) identifies the minimal set of genetic interventions that maximizes the savings in cell resources. To this end, we categorized transcription factors according to the essentiality of its targets and we used proteomic data to rank them. We designed the combinatorial removal of transcription factors that maximize the release of resources. Our resulting strain containing only three mutations, theoretically releasing 0.5% of its proteome, had higher proteome budget, increased production of an engineered metabolic pathway and showed that the regulatory interventions are highly specific. This approach shows that combining proteomic and regulatory data is an effective way of optimizing strains using conventional molecular methods.

Turning the Screw: Engineering Extreme pH Resistance in Escherichia coli through Combinatorial Synthetic Operons

Adoption of microorganisms as platforms for sustainable biobased production requires host cells to be able to withstand harsh conditions, usually very distant from those in which these organisms are naturally adapted to thrive. However, novel survival mechanisms unearthed by the study of microbiomes from extreme habitats may be exploited to enhance microbial robustness under the strict conditions needed for different industrial appplications. In this work, synthetic biology approaches were used to engineer enhanced acidic resistance in Escherichia coli through the characterization of a collection of unique operons composed of combinatorial assemblies of three novel genes from an extreme environment and three synthetic ribosome binding sites. The results here presented illustrate the efficacy of combining different metagenomic genes for resistance in synthetic operons, as expression of these gene clusters increased hundred-fold the survival percentage of cells exposed to an acidic shock in minimal media at pH 1.9 under aerobic conditions.

Flux, toxicity, and expression costs generate complex genetic interactions in a metabolic pathway

Our ability to predict the impact of mutations on traits relevant for disease and evolution remains severely limited by the dependence of their effects on the genetic background and environment. Even when molecular interactions between genes are known, it is unclear how these translate to organism-level interactions between alleles. We therefore characterized the interplay of genetic and environmental dependencies in determining fitness by quantifying ~4000 fitness interactions between expression variants of two metabolic genes, starting from various environmentally modulated expression levels. We detect a remarkable variety of interactions dependent on initial expression levels and demonstrate that they can be quantitatively explained by a mechanistic model accounting for catabolic flux, metabolite toxicity, and expression costs. Complex fitness interactions between mutations can therefore be predicted simply from their simultaneous impact on a few connected molecular phenotypes.

Implication of in vivo circulating fibrocytes ablation in experimental pulmonary hypertension murine model

BACKGROUND AND PURPOSE

Recruitment and involvement of bone-/blood-derived circulating fibrocytes (CF) in the promotion of fibrotic tissue remodelling processes have been shown. However, their direct contribution to pathological changes is not clear. The present study investigates the causal role of CF in the pathogenesis of pulmonary hypertension (PH).

EXPERIMENTAL APPROACH

For selective ablation of CF, we applied the suicidal gene strategy with herpes simplex virus thymidine kinase (HSV-TK) and ganciclovir. The transgenic mice were generated, having HSV-TK-GFP transgene under the collagen 1 promoter. To selectively target CF, HSV-TK-GFP⁺ bone marrow transplanted into irradiated wild type mice. These chimera mice were subjected to hypoxia for PH induction and ganciclovir for CF ablation.

KEY RESULTS

In vivo CF ablation reduced right ventricular hypertrophy and vascular remodelling with reduced total collagen content. We quantified the CF recruited in the perivascular area and arterial wall of small pulmonary arteries. There was significant recruitment of CF in the lung in response to hypoxia. The characterization of CF showed the expression of CD45 and collagen1 (GFP) along with α-smooth muscle actin (αSMA).

CONCLUSION AND IMPLICATIONS

Our data demonstrated that CF ablation has a potential impact on right ventricular hypertrophy and vascular remodelling in the setting of experimental pulmonary hypertension induced by hypoxia. The beneficial effects may be related to the direct contribution of fibrocytes or its paracrine effect on other resident cell types. Thus, clinical manipulation of CF may represent a novel therapeutic approach to ameliorate the disease state in pulmonary hypertension.

Impact of In Vivo Protein Folding Probability on Local Fitness Landscapes

It is incompletely understood how biophysical properties like protein stability impact molecular evolution and epistasis. Epistasis is defined as specific when a mutation exclusively influences the phenotypic effect of another mutation, often at physically interacting residues. In contrast, nonspecific epistasis results when a mutation is influenced by a large number of nonlocal mutations. As most mutations are pleiotropic, the in vivo folding probability-governed by basal protein stability-is thought to determine activity-enhancing mutational tolerance, implying that nonspecific epistasis is dominant. However, evidence exists for both specific and nonspecific epistasis as the prevalent factor, with limited comprehensive data sets to support either claim. Here, we use deep mutational scanning to probe how in vivo enzyme folding probability impacts local fitness landscapes. We computationally designed two different variants of the amidase AmiE with statistically indistinguishable catalytic efficiencies but lower probabilities of folding in vivo compared with wild-type. Local fitness landscapes show slight alterations among variants, with essentially the same global distribution of fitness effects. However, specific epistasis was predominant for the subset of mutations exhibiting positive sign epistasis. These mutations mapped to spatially distinct locations on AmiE near the initial mutation or proximal to the active site. Intriguingly, the majority of specific epistatic mutations were codon dependent, with different synonymous codons resulting in fitness sign reversals. Together, these results offer a nuanced view of how protein folding probability impacts local fitness landscapes and suggest that transcriptional-translational effects are as important as stability in determining evolutionary outcomes.

Construction of Genetic Logic Gates Based on the T7 RNA Polymerase Expression System in Rhodococcus opacus PD630

Rhodococcus opacus PD630 (R. opacus) is a nonmodel, Gram-positive bacterium that holds promise as a biological catalyst for the conversion of lignocellulosic biomass to value-added products. In particular, it demonstrates both a high tolerance for and an ability to consume inhibitory lignin-derived aromatics, generates large quantities of lipids, exhibits a relatively rapid growth rate, and has a growing genetic toolbox for engineering. However, the availability of genetic parts for tunable, high-activity gene expression is still limited in R. opacus. Furthermore, genetic logic circuits for sophisticated gene regulation have never been demonstrated in Rhodococcus spp. To address these shortcomings, two inducible T7 RNA polymerase-based expression systems were implemented for the first time in R. opacus and applied to the construction of AND and NAND genetic logic gates. Additionally, three isopropyl β-d-1-thiogalactopyranoside (IPTG)-inducible promoters were created by inserting LacI binding sites into newly characterized constitutive promoters. Furthermore, four novel aromatic sensors for 4-hydroxybenzoic acid, vanillic acid, sodium benzoate, and guaiacol were developed, expanding the gene expression toolbox. Finally, the T7 RNA polymerase platform was combined with a synthetic IPTG-inducible promoter to create an IMPLY logic gate. Overall, this work represents the first demonstration of a heterologous RNA polymerase system and synthetic genetic logic in R. opacus, enabling complex and tunable gene regulation in this promising nonmodel host for bioproduction.

FeedER: a feedback-regulated enzyme-based slow-release system for fed-batch cultivation in microtiter plates

With the advent of modern genetic engineering methods, microcultivation systems have become increasingly important tools for accelerated strain phenotyping and bioprocess engineering. While these systems offer sophisticated capabilities to screen batch processes, they lack the ability to realize fed-batch processes, which are used more frequently in industrial bioprocessing. In this study, a novel approach to realize a feedback-regulated enzyme-based slow-release system (FeedER), allowing exponential fed-batch for microscale cultivations, was realized by extending our existing Mini Pilot Plant technology with a customized process control system. By continuously comparing the experimental growth rates with predefined set points, the automated dosage of Amyloglucosidase enzyme for the cleavage of dextrin polymers into d-glucose monomers is triggered. As a prerequisite for stable fed-batch operation, a constant pH is maintained by automated addition of ammonium hydroxide. We show the successful application of FeedER to study fed-batch growth of different industrial model organisms including Corynebacterium glutamicum, Pichia pastoris, and Escherichia coli. Moreover, the comparative analysis of a C. glutamicum GFP producer strain, cultivated under microscale batch and fed-batch conditions, revealed two times higher product yields under slow growing fed-batch operation. In summary, FeedER enables to run 48 parallel fed-batch experiments in an automated and miniaturized manner, and thereby accelerates industrial bioprocess development at the screening stage.

Salmonella Single-Cell Metabolism and Stress Responses in Complex Host Tissues

Systemic Salmonella enterica infections are a major cause of mortality worldwide and are becoming increasingly untreatable. Recent single-cell data from a mouse model of typhoid fever show that the host immune system actually eradicates many Salmonella cells, while other Salmonella organisms thrive at the same time in the same tissue, causing lethal disease progression. The surviving Salmonella cells have highly heterogeneous metabolism, growth rates, and exposure to various stresses. Emerging evidence suggests that similarly heterogeneous host-pathogen encounters might be a key feature of many infectious diseases. This heterogeneity offers fascinating opportunities for research and application. If we understand the mechanisms that determine the disparate local outcomes, we might be able to develop entirely novel strategies for infection control by broadening successful host antimicrobial attacks and closing permissive niches in which pathogens can thrive. This review describes suitable technologies, a current working model of heterogeneous host-Salmonella interactions, the impact of diverse Salmonella subsets on antimicrobial chemotherapy, and major open questions and challenges.

An Automated Data-Driven Pipeline for Improving Heterologous Enzyme Expression

Enzymes are the ultimate entities responsible for chemical transformations in natural and engineered biosynthetic pathways. However, many natural enzymes suffer from suboptimal functional expression due to poor intrinsic protein stability. Further, stability enhancing mutations often come at the cost of impaired function. Here we demonstrate an automated protein engineering strategy for stabilizing enzymes while retaining catalytic function using deep mutational scanning coupled to multiple-filter based screening and combinatorial mutagenesis. We validated this strategy by improving the functional expression of a Type III polyketide synthase from the Atropa belladonna biosynthetic pathway for tropane alkaloids. The best variant had a total of 8 mutations with over 25-fold improved activity over wild-type in E. coli cell lysates, an improved melting temperature of 11.5 ± 0.6 °C, and only minimal reduction in catalytic efficiency. We show that the multiple-filter approach maintains acceptable sensitivity with homology modeling structures up to 4 Å RMS. Our results highlight an automated protein engineering tool for improving the stability and solubility of difficult to express enzymes, which has impact for biotechnological applications.

Synthetic biology and metabolic engineering of actinomycetes for natural product discovery

Actinomycetes are one of the most valuable sources of natural products with industrial and medicinal importance. After more than half a century of exploitation, it has become increasingly challenging to find novel natural products with useful properties as the same known compounds are often repeatedly re-discovered when using traditional approaches. Modern genome mining approaches have led to the discovery of new biosynthetic gene clusters, thus indicating that actinomycetes still harbor a huge unexploited potential to produce novel natural products. In recent years, innovative synthetic biology and metabolic engineering tools have greatly accelerated the discovery of new natural products and the engineering of actinomycetes. In the first part of this review, we outline the successful application of metabolic engineering to optimize natural product production, focusing on the use of multi-omics data, genome-scale metabolic models, rational approaches to balance precursor pools, and the engineering of regulatory genes and regulatory elements. In the second part, we summarize the recent advances of synthetic biology for actinomycetal metabolic engineering including cluster assembly, cloning and expression, CRISPR/Cas9 technologies, and chassis strain development for natural product overproduction and discovery. Finally, we describe new advances in reprogramming biosynthetic pathways through polyketide synthase and non-ribosomal peptide synthetase engineering. These new developments are expected to revitalize discovery and development of new natural products with medicinal and other industrial applications.

Circuit-Host Coupling Induces Multifaceted Behavioral Modulations of a Gene Switch

Quantitative modeling of gene circuits is fundamentally important to synthetic biology, as it offers the potential to transform circuit engineering from trial-and-error construction to rational design and, hence, facilitates the advance of the field. Currently, typical models regard gene circuits as isolated entities and focus only on the biochemical processes within the circuits. However, such a standard paradigm is getting challenged by increasing experimental evidence suggesting that circuits and their host are intimately connected, and their interactions can potentially impact circuit behaviors. Here we systematically examined the roles of circuit-host coupling in shaping circuit dynamics by using a self-activating gene switch as a model circuit. Through a combination of deterministic modeling, stochastic simulation, and Fokker-Planck equation formalism, we found that circuit-host coupling alters switch behaviors across multiple scales. At the single-cell level, it slows the switch dynamics in the high protein production regime and enlarges the difference between stable steady-state values. At the population level, it favors cells with low protein production through differential growth amplification. Together, the two-level coupling effects induce both quantitative and qualitative modulations of the switch, with the primary component of the effects determined by the circuit's architectural parameters. This study illustrates the complexity and importance of circuit-host coupling in modulating circuit behaviors, demonstrating the need for a new paradigm-integrated modeling of the circuit-host system-for quantitative understanding of engineered gene networks.

Prediction of recombinant protein production by Escherichia coli derived online from indicators of metabolic burden

BACKGROUND

The oxygen transfer rate (OTR) and the biomass concentration are two important parameters describing a microbial fermentation. It has been shown before that from the course of these parameters over time information on metabolic burden during heterologous protein production can be obtained. While online monitoring in large fermenters is ubiquitously established, it is still not a common practice in small-scale cultures. Nevertheless, several techniques like the Respiration Activity MOnitoring System (RAMOS) device for online monitoring of the OTR in shake flasks and the BioLector device for measuring scattered light (ScL) representing biomass in microtiter plates have been developed.

RESULTS

A new microtiter plate-based method is presented that reveals how online derived ScL signals can be transformed into signals that are proportional to the courses of OTR over time for Escherichia coli. The transformed signal is obtained by simply taking the first derivative of ScL (dScL/dt). The proportionality of both parameters is successfully validated for the strains E. coli BL21(DE3) and Tuner(DE3) expressing cellulases and the fluorescent protein FbFP, respectively. Relative amounts of produced heterologous proteins are predicted exclusively based on the course of the transformed ScL signal. A variety of induction conditions with varying inducer concentration and induction time were investigated with this method.

CONCLUSION

The presented method based on ScL measurement allows for high-throughput online determination of signals proportional to OTR courses. They enable the interpretation of physiological states and offer the possibility to predict the recombinant protein production in E. coli. © 2018 American Institute of Chemical Engineers Biotechnol. Prog., 34:1543-1552, 2018.

Engineering a palette of eukaryotic chromoproteins for bacterial synthetic biology

Background

Coral reefs are colored by eukaryotic chromoproteins (CPs) that are homologous to green fluorescent protein. CPs differ from fluorescent proteins (FPs) by intensely absorbing visible light to give strong colors in ambient light. This endows CPs with certain advantages over FPs, such as instrument-free detection uncomplicated by ultra-violet light damage or background fluorescence, efficient Förster resonance energy transfer (FRET) quenching, and photoacoustic imaging. Thus, CPs have found utility as genetic markers and in teaching, and are attractive for potential cell biosensor applications in the field. Most near-term applications of CPs require expression in a different domain of life: bacteria. However, it is unclear which of the eukaryotic CP genes might be suitable and how best to assay them.

Results

Here, taking advantage of codon optimization programs in 12 cases, we engineered 14 CP sequences (meffRed, eforRed, asPink, spisPink, scOrange, fwYellow, amilGFP, amajLime, cjBlue, meffBlue, aeBlue, amilCP, tsPurple and gfasPurple) into a palette of Escherichia coli BioBrick plasmids. BioBricks comply with synthetic biology’s most widely used, simplified, cloning standard. Differences in color intensities, maturation times and fitness costs of expression were compared under the same conditions, and visible readout of gene expression was quantitated. A surprisingly large variation in cellular fitness costs was found, resulting in loss of color in some overnight liquid cultures of certain high-copy-plasmid-borne CPs, and cautioning the use of multiple CPs as markers in competition assays. We solved these two problems by integrating pairs of these genes into the chromosome and by engineering versions of the same CP with very different colors.

Conclusion

Availability of 14 engineered CP genes compared in E. coli, together with chromosomal mutants suitable for competition assays, should simplify and expand CP study and applications. There was no single plasmid-borne CP that combined all of the most desirable features of intense color, fast maturation and low fitness cost, so this study should help direct future engineering efforts.

Electronic supplementary material

The online version of this article (10.1186/s13036-018-0100-0) contains supplementary material, which is available to authorized users.

Optimizing recombinant protein expression via automated induction profiling in microtiter plates at different temperatures

Background

Escherichia coli (E. coli) is the most abundant expression host for recombinant proteins. The production efficiency is dependent on a multitude of parameters. Therefore, high-throughput applications have become an increasingly frequent technique to investigate the main factors. Within this study, the effects of temperature, induction time and inducer concentration on the metabolic state and the product formation were extensively examined. Induction profiling of E. coli Tuner(DE3) pRhotHi-2-EcFbFP was performed in 48-well Flowerplates and standard 96-well plates using a robotic platform. In parallel shake flask cultivations, the respiration activity of the microorganisms was analyzed. Therefore, two online-monitoring systems were applied: the BioLector for microtiter plates and the RAMOS-device for shake flasks. The impact of different induction conditions on biomass and product formation as well as on the oxygen transfer rate was surveyed.

Results

Different optimal induction conditions were obtained for temperatures of 28, 30, 34, and 37 °C. The best inducer concentrations were determined to be between 0.05 and 0.1 mM IPTG for all investigated temperatures. This is 10–20 times lower than conventional guidelines suggest. The induction time was less relevant when the correct inducer concentration was chosen. Furthermore, there was a stronger impact on growth and respiration activity at higher temperatures. This indicated a higher metabolic burden. Therefore, lower IPTG concentrations were advantageous at elevated temperatures. Very similar results were obtained in standard 96-well plates.

Conclusion

Two online-monitoring systems were successfully used to investigate the optimal induction conditions for the E. coli Tuner(DE3) pRhotHi-2-EcFbFP strain (lacY deletion mutant) at four different temperatures. The experimental effort was reduced to a minimum by integrating a liquid handling robot. To reach the maximum product formation, a detailed induction analysis was necessary. Whenever the cultivation temperature was changed, the induction conditions have to be adapted. Due to the experimental options provided by the BioLector technology, it was found that the higher the cultivation temperature, the lower the inducer concentration that has to be applied.

Electronic supplementary material

The online version of this article (10.1186/s12934-017-0832-4) contains supplementary material, which is available to authorized users.

Single-mutation fitness landscapes for an enzyme on multiple substrates reveal specificity is globally encoded

Our lack of total understanding of the intricacies of how enzymes behave has constrained our ability to robustly engineer substrate specificity. Furthermore, the mechanisms of natural evolution leading to improved or novel substrate specificities are not wholly defined. Here we generate near-comprehensive single-mutation fitness landscapes comprising >96.3% of all possible single nonsynonymous mutations for hydrolysis activity of an amidase expressed in E. coli with three different substrates. For all three selections, we find that the distribution of beneficial mutations can be described as exponential, supporting a current hypothesis for adaptive molecular evolution. Beneficial mutations in one selection have essentially no correlation with fitness for other selections and are dispersed throughout the protein sequence and structure. Our results further demonstrate the dependence of local fitness landscapes on substrate identity and provide an example of globally distributed sequence-specificity determinants for an enzyme.

Systematically understanding the sequence determinants to substrate specificity for enzymes has implications in areas from evolutionary biology to biocatalysis. Here, Whitehead and colleagues generate and analyse near-comprehensive single-mutation fitness landscapes for an amidase with three different substrates.

Tunable recombinant protein expression in E. coli: promoter systems and genetic constraints

Tuning of transcription is a promising strategy to overcome challenges associated with a non-suitable expression rate like outgrowth of segregants, inclusion body formation, metabolic burden and inefficient translocation. By adjusting the expression rate-even on line-to purposeful levels higher product titres and more cost-efficient production processes can be achieved by enabling culture long-term stability and constant product quality. Some tunable systems are registered for patents or already commercially available. Within this contribution, we discuss the induction mechanisms of various Escherichia coli inherent promoter systems with respect to their tunability and review studies using these systems for expression tuning. According to the current level of knowledge, some promoter systems were successfully used for expression tuning, and in some cases, analytical evidence on single-cell level is still pending. However, only a few studies using tunable strains apply a suitable process control strategy. So far, expression tuning has only gathered little attention, but we anticipate that expression tuning harbours great potential for enabling and optimizing the production of a broad spectrum of products in E. coli.

Gene Architectures that Minimize Cost of Gene Expression

Gene expression burdens cells by consuming resources and energy. While numerous studies have investigated regulation of expression level, little is known about gene design elements that govern expression costs. Here, we ask how cells minimize production costs while maintaining a given protein expression level and whether there are gene architectures that optimize this process. We measured fitness of ∼14,000 E. coli strains, each expressing a reporter gene with a unique 5' architecture. By comparing cost-effective and ineffective architectures, we found that cost per protein molecule could be minimized by lowering transcription levels, regulating translation speeds, and utilizing amino acids that are cheap to synthesize and that are less hydrophobic. We then examined natural E. coli genes and found that highly expressed genes have evolved more forcefully to minimize costs associated with their expression. Our study thus elucidates gene design elements that improve the economy of protein expression in natural and heterologous systems.

Determination of binding affinity upon mutation for type I dockerin-cohesin complexes from Clostridium thermocellum and Clostridium cellulolyticum using deep sequencing

The comprehensive sequence determinants of binding affinity for type I cohesin toward dockerin from Clostridium thermocellum and Clostridium cellulolyticum was evaluated using deep mutational scanning coupled to yeast surface display. We measured the relative binding affinity to dockerin for 2970 and 2778 single point mutants of C. thermocellum and C. cellulolyticum, respectively, representing over 96% of all possible single point mutants. The interface ΔΔG for each variant was reconstructed from sequencing counts and compared with the three independent experimental methods. This reconstruction results in a narrow dynamic range of -0.8-0.5 kcal/mol. The computational software packages FoldX and Rosetta were used to predict mutations that disrupt binding by more than 0.4 kcal/mol. The area under the curve of receiver operator curves was 0.82 for FoldX and 0.77 for Rosetta, showing reasonable agreements between predictions and experimental results. Destabilizing mutations to core and rim positions were predicted with higher accuracy than support positions. This benchmark dataset may be useful for developing new computational prediction tools for the prediction of the mutational effect on binding affinities for protein-protein interactions. Experimental considerations to improve precision and range of the reconstruction method are discussed. Proteins 2016; 84:1914-1928. © 2016 Wiley Periodicals, Inc.

Plasmid-based one-pot saturation mutagenesis

Deep mutational scanning is a foundational tool for addressing the functional consequences of large numbers of mutants, but a more efficient and accessible method for construction of user-defined mutagenesis libraries is needed. Here we present nicking mutagenesis, a robust, single-day, one-pot saturation mutagenesis method performed on routinely prepped plasmid dsDNA. The method can be used to produce comprehensive or single- or multi-site saturation mutagenesis libraries.

Promoter Screening from Bacillus subtilis in Various Conditions Hunting for Synthetic Biology and Industrial Applications

The use of Bacillus subtilis in synthetic biology and metabolic engineering is highly desirable to take advantage of the unique metabolic pathways present in this organism. To do this, an evaluation of B. subtilis’ intrinsic biological parts is required to determine the best strategies to accurately regulate metabolic circuits and expression of target proteins. The strengths of promoter candidates were evaluated by measuring relative fluorescence units of a green fluorescent protein reporter, integrated into B. subtilis’ chromosome. A total of 84 predicted promoter sequences located upstream of different classes of proteins including heat shock proteins, cell-envelope proteins, and proteins resistant against toxic metals (based on similarity) and other kinds of genes were tested. The expression levels measured ranged from 0.0023 to 4.53-fold of the activity of the well-characterized strong promoter P43. No significant shifts were observed when strains, carrying different promoter candidates, were cultured at high temperature or in media with ethanol, but some strains showed increased activity when cultured under high osmotic pressure. Randomly selected promoter candidates were tested and found to activate transcription of thermostable β-galactosidase (bgaB) at a similar level, implying the ability of these sequences to function as promoter elements in multiple genetic contexts. In addition, selected promoters elevated the final production of both cytoplasmic bgaB and secreted protein α-amylase to about fourfold and twofold, respectively. The generated data allows a deeper understanding of B. subtilis’ metabolism and will facilitate future work to develop this organism for synthetic biology.

Quantification and Classification of E. coli Proteome Utilization and Unused Protein Costs across Environments

The costs and benefits of protein expression are balanced through evolution. Expression of un-utilized protein (that have no benefits in the current environment) incurs a quantifiable fitness costs on cellular growth rates; however, the magnitude and variability of un-utilized protein expression in natural settings is unknown, largely due to the challenge in determining environment-specific proteome utilization. We address this challenge using absolute and global proteomics data combined with a recently developed genome-scale model of Escherichia coli that computes the environment-specific cost and utility of the proteome on a per gene basis. We show that nearly half of the proteome mass is unused in certain environments and accounting for the cost of this unused protein expression explains >95% of the variance in growth rates of Escherichia coli across 16 distinct environments. Furthermore, reduction in unused protein expression is shown to be a common mechanism to increase cellular growth rates in adaptive evolution experiments. Classification of the unused protein reveals that the unused protein encodes several nutrient- and stress- preparedness functions, which may convey fitness benefits in varying environments. Thus, unused protein expression is the source of large and pervasive fitness costs that may provide the benefit of hedging against environmental change.

An overarching endeavor in systems biology is to characterize and understand the allocation of an organism’s proteome. Common approaches to characterize proteome allocation are based on annotations of protein functions or transcriptional regulatory targets. Here, we develop a novel approach based on model-predicted proteome utilization. This approach reveals that in many environments, a large fraction of the proteome is unused. Unused protein expression is known to incur costs on organismal fitness. We show that changes in the allocation of the proteome to used versus unused fractions can account for the variability in growth rates observed across environments and is a common mechanism to increase growth rates in laboratory evolution experiments. We compare our approach to classify the proteome based on model-predicted utilization to more traditional approaches to reveal biological functions and transcriptional regulators underlying the expression of unused protein. Expression of these functions may reflect ecological trade-offs between growth, nutrient-readiness, and stress resistance.

Tunable recombinant protein expression in E. coli: enabler for continuous processing?

Tuning of transcription is a powerful process technological tool for efficient recombinant protein production in Escherichia coli. Many challenges such as product toxicity, formation of inclusion bodies, cell death, and metabolic burden are associated with non-suitable (too high or too low) levels of recombinant protein expression. Tunable expression systems allow adjusting the recombinant protein expression using process technological means. This enables to exploit the cell's metabolic capacities to a maximum. Within this article, we review genetic and process technological aspects of tunable expression systems in E. coli, providing a roadmap for the industrial exploitation of the reviewed technologies. We attempt to differentiate the term "expression tuning" from its inflationary use by providing a concise definition and highlight interesting fields of application for this versatile new technology. Dependent on the type of inducer (metabolizable or non-metabolizable), different process strategies are required in order to achieve tuning. To fully profit from the benefits of tunable systems, an independent control of growth rate and expression rate is indispensable. Being able to tackle problems such as long-term culture stability and constant product quality expression tuning is a promising enabler for continuous processing in biopharmaceutical production.

Light-induced gene expression with photocaged IPTG for induction profiling in a high-throughput screening system

BACKGROUND

Inducible expression systems are frequently used for the production of heterologous proteins. Achieving maximum product concentrations requires induction profiling, namely the optimization of induction time and inducer concentration. However, the respective experiments can be very laborious and time-consuming. In this work, a new approach for induction profiling is presented where induction in a microtiter plate based cultivation system (BioLector) is achieved by light using photocaged isopropyl β-D-1-thiogalactopyranoside (cIPTG).

RESULTS

A flavin mononucleotide-based fluorescent reporter protein (FbFP) was expressed using a T7-RNA-polymerase dependent E. coli expression system which required IPTG as inducer. High power UV-A irradiation was directed into a microtiter plate by light-emitting diodes placed above each well of a 48-well plate. Upon UV irradiation, IPTG is released (uncaged) and induces product formation. IPTG uncaging, formation of the fluorescent reporter protein and biomass growth were monitored simultaneously in up to four 48-well microtiter plates in parallel with an in-house constructed BioLector screening system. The amount of released IPTG can be gradually and individually controlled for each well by duration of UV-A exposure, irradiance and concentration of photocaged IPTG added at the start of the cultivation. A comparison of experiments with either optical or conventional IPTG induction shows that product formation and growth are equivalent. Detailed induction profiles revealed that for the strain and conditions used maximum product formation is reached for very early induction times and with just 6-8 s of UV-A irradiation or 60-80 µM IPTG.

CONCLUSIONS

Optical induction and online monitoring were successfully combined in a high-throughput screening system and the effect of optical induction with photocaged IPTG was shown to be equivalent to conventional induction with IPTG. In contrast to conventional induction, optical induction is less costly to parallelize, easy to automate, non-invasive and without risk of contamination. Therefore, light-induced gene expression with photocaged IPTG is a highly advantageous method for the efficient optimization of heterologous protein production and has the potential to replace conventional induction with IPTG.

High-throughput evaluation of synthetic metabolic pathways

A central challenge in the field of metabolic engineering is the efficient identification of a metabolic pathway genotype that maximizes specific productivity over a robust range of process conditions. Here we review current methods for optimizing specific productivity of metabolic pathways in living cells. New tools for library generation, computational analysis of pathway sequence-flux space, and high-throughput screening and selection techniques are discussed.

Memory and Combinatorial Logic Based on DNA Inversions: Dynamics and Evolutionary Stability

Genetic memory can be implemented using enzymes that catalyze DNA inversions, where each orientation corresponds to a "bit". Here, we use two DNA invertases (FimE and HbiF) that reorient DNA irreversibly between two states with opposite directionality. First, we construct memory that is set by FimE and reset by HbiF. Next, we build a NOT gate where the input promoter drives FimE and in the absence of signal the reverse state is maintained by the constitutive expression of HbiF. The gate requires ∼3 h to turn on and off. The evolutionary stabilities of these circuits are measured by passaging cells while cycling function. The memory switch is stable over 400 h (17 days, 14 state changes); however, the gate breaks after 54 h (>2 days) due to continuous invertase expression. Genome sequencing reveals that the circuit remains intact, but the host strain evolves to reduce invertase expression. This work highlights the need to evaluate the evolutionary robustness and failure modes of circuit designs, especially as more complex multigate circuits are implemented.