Pseudomonas putida as saviour for troubled Synechococcus elongatus in a synthetic co-culture - interaction studies based on a multi-OMICs approach.

In their natural habitats, microbes rarely exist in isolation; instead, they thrive in consortia, where various interactions occur. In this study, a defined synthetic co-culture of the cyanobacterium S. elongatus cscB, which supplies sucrose to the heterotrophic P. putida cscRABY, is investigated to identify potential interactions. Initial experiments reveal a remarkable growth-promoting effect of the heterotrophic partner on the cyanobacterium, resulting in an up to 80% increase in the growth rate and enhanced photosynthetic capacity. Vice versa, the presence of the cyanobacterium has a neutral effect on P. putida cscRABY, highlighting the resilience of pseudomonads against stress and their potential as co-culture partners. Next, a suitable reference process reinforcing the growth-promoting effect is established in a parallel photobioreactor system, which sets the basis for the analysis of the co-culture at the transcriptome, proteome, and metabolome levels. In addition to several moderate changes, including alterations in the metabolism and stress response in both microbes, this comprehensive multi-OMICs approach strongly hints towards the exchange of further molecules beyond the unidirectional feeding with sucrose. Taken together, these findings provide valuable insights into the complex dynamics between both co-culture partners, indicating multi-level interactions, which can be employed for further streamlining of the co-cultivation system.

Metabolic impact of heterologous protein production in Pseudomonas putida: Insights into carbon and energy flux control.

For engineered microorganisms, the production of heterologous proteins that are often useless to host cells represents a burden on resources, which have to be shared with normal cellular processes. Within a certain metabolic leeway, this competitive process has no impact on growth. However, once this leeway, or free capacity, is fully utilized, the extra load becomes a metabolic burden that inhibits cellular processes and triggers a broad cellular response, reducing cell growth and often hindering the production of heterologous proteins. In this study, we sought to characterize the metabolic rearrangements occurring in the central metabolism of Pseudomonas putida at different levels of metabolic load. To this end, we constructed a P. putida KT2440 strain that expressed two genes encoding fluorescent proteins, one in the genome under constitutive expression to monitor the free capacity, and the other on an inducible plasmid to probe heterologous protein production. We found that metabolic fluxes are considerably reshuffled, especially at the level of periplasmic pathways, as soon as the metabolic load exceeds the free capacity. Heterologous protein production leads to the decoupling of anabolism and catabolism, resulting in large excess energy production relative to the requirements of protein biosynthesis. Finally, heterologous protein production was found to exert a stronger control on carbon fluxes than on energy fluxes, indicating that the flexible nature of P. putida's central metabolic network is solicited to sustain energy production.

Application of an Escherichia coli triple reporter strain for at-line monitoring of single-cell physiology during L-phenylalanine production.

Biotechnological production processes are sustainable approaches for the production of biobased components such as amino acids for food and feed industry. Scale-up from ideal lab-scale bioreactors to large-scale processes is often accompanied by loss in productivity. This may be related to population heterogeneities of cells originating from isogenic cultures that arise due to dynamic non-ideal conditions in the bioreactor. To better understand this phenomenon, deeper insights into single-cell physiologies in bioprocesses are mandatory before scale-up. Here, a triple reporter strain (3RP) was developed by chromosomally integrating the fluorescent proteins mEmerald, CyOFP1, and mTagBFP2 into the L-phenylalanine producing Escherichia coli strain FUS4 (pF81kan) to allow monitoring of growth, oxygen availability, and general stress response of the single cells. Functionality of the 3RP was confirmed in well-mixed lab-scale fed-batch processes with glycerol as carbon source in comparison to the strain without fluorescent proteins, leading to no difference in process performance. Fluorescence levels could successfully reflect the course of related process state variables, revealed population heterogeneities during the transition between different process phases and potentially subpopulations that exhibit superior process performance. Furthermore, indications were found for noise in gene expression as regulation strategy against environmental perturbation.

Streamlining of a synthetic co-culture towards an individually controllable one-pot process for polyhydroxyalkanoate production from light and CO2.

Rationally designed synthetic microbial consortia carry a vast potential for biotechnological applications. The application of such a consortium in a bioprocess, however, requires tight and individual controllability of the involved microbes. Here, we present the streamlining of a co-cultivation process consisting of Synechococcus elongatus cscB and Pseudomonas putida for the production of polyhydroxyalkanoates (PHA) from light and CO2. First, the process was improved by employing P. putida cscRABY, a strain with a higher metabolic activity towards sucrose. Next, the individual controllability of the co-culture partners was addressed by providing different nitrogen sources, each exclusively available for one strain. By this, the growth rate of the co-culture partners could be regulated individually, and defined conditions could be set. The molC/molN ratio, a key value for PHA accumulation, was estimated from the experimental data, and the necessary feeding rates to obtain a specific ratio could be predicted. This information was then implemented in the co-cultivation process, following the concept of a DBTL-cycle. In total, the streamlining of the process resulted in an increased maximal PHA titer of 393 mg/L and a PHA production rate of 42.1 mg/(L•day).

Targeting Transcriptional and Translational Hindrances in a Modular T7RNAP Expression System in Engineered Pseudomonas putida.

The T7 RNA polymerase is considered one of the most popular tools for heterologous gene expression in the gold standard biotechnological host Escherichia coli. However, the exploitation of this tool in other prospective hosts, such as the biotechnologically relevant bacterium Pseudomonas putida, is still very scarce. The majority of the existing T7-based systems in P. putida show low expression strengths and possess only weak controllability. A fundamental understanding of these systems is necessary in order to design robust and predictable biotechnological processes. To fill this gap, we established and characterized a modular T7 RNA polymerase-based system for heterologous protein production in P. putida, using the enhanced Green Fluorescent Protein (eGFP) as an easy-to-quantify reporter protein. We have effectively targeted the limitations associated with the initial genetic setup of the system, such as slow growth and low protein production rates. By replacing the T7 phage-inherent TΦ terminator downstream of the heterologous gene with the synthetic tZ terminator, growth and protein production rates improved drastically, and the T7 RNA polymerase system reached a productivity level comparable to that of an intrinsic RNA polymerase-based system. Furthermore, we were able to show that the system was saturated with T7 RNA polymerase by applying a T7 RNA polymerase ribosome binding site library to tune heterologous protein production. This saturation indicates an essential role for the ribosome binding sites of the T7 RNA polymerase since, in an oversaturated system, cellular resources are lost to the synthesis of unnecessary T7 RNA polymerase. Eventually, we combined the experimental data into a model that can predict the eGFP production rate with respect to the relative strength of the ribosome binding sites upstream of the T7 gene.

Metabolic engineering of Halomonas elongata: Ectoine secretion is increased by demand and supply driven approaches.

The application of naturally-derived biomolecules in everyday products, replacing conventional synthetic manufacturing, is an ever-increasing market. An example of this is the compatible solute ectoine, which is contained in a plethora of treatment formulations for medicinal products and cosmetics. As of today, ectoine is produced in a scale of tons each year by the natural producer Halomonas elongata. In this work, we explore two complementary approaches to obtain genetically improved producer strains for ectoine production. We explore the effect of increased precursor supply (oxaloacetate) on ectoine production, as well as an implementation of increased ectoine demand through the overexpression of a transporter. Both approaches were implemented on an already genetically modified ectoine-excreting strain H. elongata KB2.13 (ΔteaABC ΔdoeA) and both led to new strains with higher ectoine excretion. The supply driven approach led to a 45% increase in ectoine titers in two different strains. This increase was attributed to the removal of phosphoenolpyruvate carboxykinase (PEPCK), which allowed the conversion of 17.9% of the glucose substrate to ectoine. For the demand driven approach, we investigated the potential of the TeaBC transmembrane proteins from the ectoine-specific Tripartite ATP-Independent Periplasmic (TRAP) transporter as export channels to improve ectoine excretion. In the absence of the substrate-binding protein TeaA, an overexpression of both subunits TeaBC facilitated a three-fold increased excretion rate of ectoine. Individually, the large subunit TeaC showed an approximately five times higher extracellular ectoine concentration per dry weight compared to TeaBC shortly after its expression was induced. However, the detrimental effect on growth and ectoine titer at the end of the process hints toward a negative impact of TeaC overexpression on membrane integrity and possibly leads to cell lysis. By using either strategy, the ectoine synthesis and excretion in H. elongata could be boosted drastically. The inherent complementary nature of these approaches point at a coordinated implementation of both as a promising strategy for future projects in Metabolic Engineering. Moreover, a wide variation of intracelllular ectoine levels was observed between the strains, which points at a major disruption of mechanisms responsible for ectoine regulation in strain KB2.13.

Modeling Approaches to Microbial Metabolism.

Microbial systems are frequently used in biotechnology to convert substrates into valuable products. To make this efficient, knowledge on the specific metabolic characteristics of a system is required as well as a theoretical description that allows researchers to design the system for a profitable use in an industrial application. In this chapter, basics on mathematical modelling approaches are introduced and examples are provided.

Adaptation to Varying Salinity in Halomonas elongata: Much More Than Ectoine Accumulation.

The halophilic γ-proteobacterium Halomonas elongata DSM 2581 T thrives at salt concentrations well above 10 % NaCl (1.7 M NaCl). A well-known osmoregulatory mechanism is the accumulation of the compatible solute ectoine within the cell in response to osmotic stress. While ectoine accumulation is central to osmoregulation and promotes resistance to high salinity in halophilic bacteria, ectoine has this effect only to a much lesser extent in non-halophiles. We carried out transcriptome analysis of H. elongata grown on two different carbon sources (acetate or glucose), and low (0.17 M NaCl), medium (1 M), and high salinity (2 M) to identify additional mechanisms for adaptation to high saline environments. To avoid a methodological bias, the transcripts were evaluated by applying two methods, DESeq2 and Transcripts Per Million (TPM). The differentially transcribed genes in response to the available carbon sources and salt stress were then compared to the transcriptome profile of Chromohalobacter salexigens, a closely related moderate halophilic bacterium. Transcriptome profiling supports the notion that glucose is degraded via the cytoplasmic Entner-Doudoroff pathway, whereas the Embden-Meyerhoff-Parnas pathway is employed for gluconeogenesis. The machinery of oxidative phosphorylation in H. elongata and C. salexigens differs greatly from that of non-halophilic organisms, and electron flow can occur from quinone to oxygen along four alternative routes. Two of these pathways via cytochrome bo' and cytochrome bd quinol oxidases seem to be upregulated in salt stressed cells. Among the most highly regulated genes in H. elongata and C. salexigens are those encoding chemotaxis and motility proteins, with genes for chemotaxis and flagellar assembly severely downregulated at low salt concentrations. We also compared transcripts at low and high-salt stress (low growth rate) with transcripts at optimal salt concentration and found that the majority of regulated genes were down-regulated in stressed cells, including many genes involved in carbohydrate metabolism, while ribosome synthesis was up-regulated, which is in contrast to what is known from non-halophiles at slow growth. Finally, comparing the acidity of the cytoplasmic proteomes of non-halophiles, extreme halophiles and moderate halophiles suggests adaptation to an increased cytoplasmic ion concentration of H. elongata. Taken together, these results lead us to propose a model for salt tolerance in H. elongata where ion accumulation plays a greater role in salt tolerance than previously assumed.

Applications of Coarse-Grained Models in Metabolic Engineering.

Mathematical modeling is a promising tool for better understanding of cellular processes. In recent years, the development of coarse-grained models has gained attraction since these simple models are able to capture and describe a broad range of growth conditions. Coarse-grained models often comprise only two cellular components, a low molecular component as representative for central metabolism and energy generation and a macromolecular component, representing the entire proteome. A framework is presented that presents a strict mass conservative model for bacterial growth during a biotechnological production process. After providing interesting properties for the steady-state solution, applications are presented 1) for a production process of an amino acid and 2) production of a metabolite from central metabolism.

A counting-strategy together with a spatial structured model describes RNA polymerase and ribosome availability in Escherichia coli.

The allocation of resources during bacterial growth is strongly related to the availability of ribosomes and RNA polymerase molecules. Here, coarse-grained models offer a promising start due to their simple structure and the limited number of kinetic parameters. Based on published data sets for proteome and mRNA data in Escherichia coli, and together with mass balance equations describing gene expression, we are able to calculate the number of active molecules (that is, the number of ribosomes that are currently translating nascent and mature mRNA, as well as the number of RNA polymerase molecules on the DNA). This information is a prerequisite for meaningful coarse-grained models. In our approach, the cellular compartment is structured into a cytosolic region and a nucleoid region, and the processes of transcription and translation are assigned accordingly. The theoretical study reveals a quadratic relationship between the number of active ribosomes and the growth rate µ. While the overall available number of ribosomes follows the linear "bacterial growth law", the approach allows us to determine the growth limit for the chosen experimental environment (minimal medium, only one C source). The new approach is in good agreement with published experimental data, and, with a simple rule of thumb can be applied to other cellular systems.

In-Depth Computational Analysis of Natural and Artificial Carbon Fixation Pathways.

In the recent years, engineering new-to-nature CO2- and C1-fixing metabolic pathways made a leap forward. New, artificial pathways promise higher yields and activity than natural ones like the Calvin-Benson-Bassham (CBB) cycle. The question remains how to best predict their in vivo performance and what actually makes one pathway "better" than another. In this context, we explore aerobic carbon fixation pathways by a computational approach and compare them based on their specific activity and yield on methanol, formate, and CO2/H2 considering the kinetics and thermodynamics of the reactions. Besides pathways found in nature or implemented in the laboratory, this included two completely new cycles with favorable features: the reductive citramalyl-CoA cycle and the 2-hydroxyglutarate-reverse tricarboxylic acid cycle. A comprehensive kinetic data set was collected for all enzymes of all pathways, and missing kinetic data were sampled with the Parameter Balancing algorithm. Kinetic and thermodynamic data were fed to the Enzyme Cost Minimization algorithm to check for respective inconsistencies and calculate pathway-specific activities. The specific activities of the reductive glycine pathway, the CETCH cycle, and the new reductive citramalyl-CoA cycle were predicted to match the best natural cycles with superior product-substrate yield. However, the CBB cycle performed better in terms of activity compared to the alternative pathways than previously thought. We make an argument that stoichiometric yield is likely not the most important design criterion of the CBB cycle. Still, alternative carbon fixation pathways were paretooptimal for specific activity and product-substrate yield in simulations with C1 substrates and CO2/H2 and therefore hold great potential for future applications in Industrial Biotechnology and Synthetic Biology.

Corrigendum to "In-Depth Computational Analysis of Natural and Artificial Carbon Fixation Pathways".

[This corrects the article DOI: 10.34133/2021/9898316.].

Trehalose production by Cupriavidus necator from CO2 and hydrogen gas.

In this work, the hydrogen-oxidizing bacterium Cupriavidus necator H16 was engineered for trehalose production from gaseous substrates. First, it could be shown that C. necator is a natural producer of trehalose when stressed with sodium chloride. Bioinformatic investigations revealed a so far unknown mode of trehalose and glycogen metabolism in this organism. Next, it was found that expression of the sugar efflux transporter A (setA) from Escherichia coli lead to a trehalose leaky phenotype of C. necator. Finally, the strain was characterized under autotrophic conditions using a H2/CO2/O2-mixture and other substrates reaching titers of up to 0.47 g L-1 and yields of around 0.1 g g-1. Taken together, this process represents a new way to produce sugars with high areal efficiency. With further metabolic engineering, an application of this technology for the renewable production of trehalose and other sugars, as well as for the synthesis of 13C-labeled sugars seems promising.

Anaplerotic Pathways in Halomonas elongata: The Role of the Sodium Gradient.

Salt tolerance in the γ-proteobacterium Halomonas elongata is linked to its ability to produce the compatible solute ectoine. The metabolism of ectoine production is of great interest since it can shed light on the biochemical basis of halotolerance as well as pave the way for the improvement of the biotechnological production of such compatible solute. Ectoine belongs to the biosynthetic family of aspartate-derived amino-acids. Aspartate is formed from oxaloacetate, thereby connecting ectoine production to the anaplerotic reactions that refill carbon into the tricarboxylic acid cycle (TCA cycle). This places a high demand on these reactions and creates the need to regulate them not only in response to growth but also in response to extracellular salt concentration. In this work, we combine modeling and experiments to analyze how these different needs shape the anaplerotic reactions in H. elongata. First, the stoichiometric and thermodynamic factors that condition the flux distributions are analyzed, then the optimal patterns of operation for oxaloacetate production are calculated. Finally, the phenotype of two deletion mutants lacking potentially relevant anaplerotic enzymes: phosphoenolpyruvate carboxylase (Ppc) and oxaloacetate decarboxylase (Oad) are experimentally characterized. The results show that the anaplerotic reactions in H. elongata are indeed subject to evolutionary pressures that differ from those faced by other gram-negative bacteria. Ectoine producing halophiles must meet a higher metabolic demand for oxaloacetate and the reliance of many marine bacteria on the Entner-Doudoroff pathway compromises the anaplerotic efficiency of Ppc, which is usually one of the main enzymes fulfilling this role. The anaplerotic flux in H. elongata is contributed not only by Ppc but also by Oad, an enzyme that has not yet been shown to play this role in vivo. Ppc is necessary for H. elongata to grow normally at low salt concentrations but it is not required to achieve near maximal growth rates as long as there is a steep sodium gradient. On the other hand, the lack of Oad presents serious difficulties to grow at high salt concentrations. This points to a shared role of these two enzymes in guaranteeing the supply of oxaloacetate for biosynthetic reactions.

A Nitrate-Blind P. putida Strain Boosts PHA Production in a Synthetic Mixed Culture.

One of the major challenges for the present and future generations is to find suitable substitutes for the fossil resources we rely on today. In this context, cyanobacterial carbohydrates have been discussed as an emerging renewable feedstock in industrial biotechnology for the production of fuels and chemicals. Based on this, we recently presented a synthetic bacterial co-culture for the production of medium-chain-length polyhydroxyalkanoates (PHAs) from CO2. This co-cultivation system is composed of two partner strains: Synechococcus elongatus cscB which fixes CO2, converts it to sucrose and exports it into the culture supernatant, and a Pseudomonas putida strain that metabolizes this sugar and accumulates PHAs in the cytoplasm. However, these biopolymers are preferably accumulated under conditions of nitrogen limitation, a situation difficult to achieve in a co-culture as the other partner, at best, should not perceive any limitation. In this article, we will present an approach to overcome this dilemma by uncoupling the PHA production from the presence of nitrate in the medium. This is achieved by the construction of a P. putida strain that is no longer able to grow with nitrate as nitrogen source -is thus nitrate blind, and able to grow with sucrose as carbon source. The deletion of the nasT gene encoding the response regulator of the NasS/NasT two-component system resulted in such a strain that has lost the ability use nitrate, but growth with ammonium was not affected. Subsequently, the nasT deletion was implemented in P. putida cscRABY, an efficient sucrose consuming strain. This genetic engineering approach introduced an artificial unilateral nitrogen limitation in the co-cultivation process, and the amount of PHA produced from light and CO2 was 8.8 fold increased to 14.8% of its CDW compared to the nitrate consuming reference strain. This nitrate blind strain, P. putidaΔnasT attTn7:cscRABY, is not only a valuable partner in the co-cultivation but additionally enables the use of other nitrate containing substrates for medium-chain-length PHA production, like for example waste-water.

Understanding biochemical design principles with ensembles of canonical non-linear models.

Systems biology applies concepts from engineering in order to understand biological networks. If such an understanding was complete, biologists would be able to design ad hoc biochemical components tailored for different purposes, which is the goal of synthetic biology. Needless to say that we are far away from creating biological subsystems as intricate and precise as those found in nature, but mathematical models and high throughput techniques have brought us a long way in this direction. One of the difficulties that still needs to be overcome is finding the right values for model parameters and dealing with uncertainty, which is proving to be an extremely difficult task. In this work, we take advantage of ensemble modeling techniques, where a large number of models with different parameter values are formulated and then tested according to some performance criteria. By finding features shared by successful models, the role of different components and the synergies between them can be better understood. We will address some of the difficulties often faced by ensemble modeling approaches, such as the need to sample a space whose size grows exponentially with the number of parameters, and establishing useful selection criteria. Some methods will be shown to reduce the predictions from many models into a set of understandable "design principles" that can guide us to improve or manufacture a biochemical network. Our proposed framework formulates models within standard formalisms in order to integrate information from different sources and minimize the dimension of the parameter space. Additionally, the mathematical properties of the formalism enable a partition of the parameter space into independent subspaces. Each of these subspaces can be paired with a set of criteria that depend exclusively on it, thus allowing a separate sampling/screening in spaces of lower dimension. By applying tests in a strict order where computationally cheaper tests are applied first to each subspace and applying computationally expensive tests to the remaining subset thereafter, the use of resources is optimized and a larger number of models can be examined. This can be compared to a complex database query where the order of the requests can make a huge difference in the processing time. The method will be illustrated by analyzing a classical model of a metabolic pathway with end-product inhibition. Even for such a simple model, the method provides novel insight.

Engineering sucrose metabolism in Pseudomonas putida highlights the importance of porins.

Using agricultural wastes as a substrate for biotechnological processes is of great interest in industrial biotechnology. A prerequisite for using these wastes is the ability of the industrially relevant microorganisms to metabolize the sugars present therein. Therefore, many metabolic engineering approaches are directed towards widening the substrate spectrum of the workhorses of industrial biotechnology like Escherichia coli, yeast or Pseudomonas putida. For instance, neither xylose or arabinose from cellulosic residues, nor sucrose, the main sugar in waste molasses, can be metabolized by most E. coli and P. putida wild types. We evaluated a new, so far uncharacterized gene cluster for sucrose metabolism from Pseudomonas protegens Pf-5 and showed that it enables P. putida to grow on sucrose as the sole carbon and energy source. Even when integrated into the genome of P. putida, the resulting strain grew on sucrose at rates similar to the rate of the wild type on glucose - making it the fastest growing, plasmid-free P. putida strain known so far using sucrose as substrate. Next, we elucidated the role of the porin, an orthologue of the sucrose porin ScrY, in the gene cluster and found that in P. putida, a porin is needed for sucrose transport across the outer membrane. Consequently, native porins were not sufficient to allow unlimited growth on sucrose. Therefore, we concluded that the outer membrane can be a considerable barrier for substrate transport, depending on strain, genotype and culture conditions, all of which should be taken into account in metabolic engineering approaches. We additionally showed the potential of the engineered P. putida strains by growing them on molasses with efficiencies twice as high as obtained with the wild-type P. putida. This can be seen as a further step towards the production of low-value chemicals and biofuels with P. putida from alternative and more affordable substrates in the future.

An automated and parallelised DIY-dosing unit for individual and complex feeding profiles: Construction, validation and applications.

Since biotechnological research becomes more and more important for industrial applications, there is an increasing need for scalable and controllable laboratory procedures. A widely used approach in biotechnological research to improve the performance of a process is to vary the growth rates in order to find the right balance between growth and the production. This can be achieved by the application of a suitable feeding strategy. During this initial bioprocess development, it is beneficial to have at hand cheap and easy setups that work in parallel (e.g. in shaking flasks). Unfortunately, there is a gap between these easy setups and defined and controllable processes, which are necessary for up-scaling to an industrial relevant volume. One prerequisite to test and evaluate different process strategies apart from batch-mode is the availability of pump systems that allow for defined feeding profiles in shaking flasks. To our knowledge, there is no suitable dosing device on the market which fulfils the requirements of being cheap, precise, programmable, and parallelizable. Commercially available dosing units are either already integrated in bioreactors and therefore inflexible, or not programmable, or expensive, or a combination of those. Here, we present a LEGO-MINDSTORMS-based syringe pump, which has the potential of being widely used in daily laboratory routine due to its low price, programmability, and parallelisability. The acquisition costs do not exceed 350 € for up to four dosing units, that are independently controllable with one EV3 block. The system covers flow rates ranging from 0.7 µL min-1 up to 210 mL min-1 with a reliable flux. One dosing unit can convey at maximum a volume of 20 mL (using all 4 units even up to 80 mL in total) over the whole process time. The design of the dosing unit enables the user to perform experiments with up to four different growth rates in parallel (each measured in triplicates) per EV3-block used. We estimate, that the LEGO-MINDSTORMS-based dosing unit with 12 syringes in parallel is reducing the costs up to 50-fold compared to a trivial version of a commercial pump system (~1500 €) which fits the same requirements. Using the pump, we set the growth rates of a E. coli HMS174/DE3 culture to values between 0.1 and 0.4 h-1 with a standard deviation of at best 0.35% and an average discrepancy of 13.2%. Additionally, we determined the energy demand of a culture for the maintenance of the pTRA-51hd plasmid by quantifying the changes in biomass yield with different growth rates set. Around 25% of total substrate taken up is used for plasmid maintenance. To present possible applications and show the flexibility of the system, we applied a constant feed to perform microencapsulation of Pseudomonas putida and an individual dosing profile for the purification of a his-tagged eGFP via IMAC. This smart and versatile dosing unit, which is ready-to-use without any prior knowledge in electronics and control, is affordable for everyone and due to its flexibility and broad application range a valuable addition to the laboratory routine.

An ensemble of mathematical models showing diauxic growth behaviour.

BACKGROUND: Carbon catabolite repression (CCR) controls the order in which different carbon sources are metabolised. Although this system is one of the paradigms of regulation in bacteria, the underlying mechanisms remain controversial. CCR involves the coordination of different subsystems of the cell - responsible for the uptake of carbon sources, their breakdown for the production of energy and precursors, and the conversion of the latter to biomass. The complexity of this integrated system, with regulatory mechanisms cutting across metabolism, gene expression, and signalling, has motivated important modelling efforts over the past four decades, especially in the enterobacterium Escherichia coli. RESULTS: Starting from a simple core model with only four intracellular metabolites, we develop an ensemble of model variants, all showing diauxic growth behaviour during a batch process. The model variants fall into one of the four categories: flux balance models, kinetic models with growth dilution, kinetic models with regulation, and resource allocation models. The model variants differ from one another in only a single aspect, each breaking the symmetry between the two substrate assimilation pathways in a different manner, and can be quantitatively compared using a so-called diauxic growth index. For each of the model variants, we predict the behaviour in two new experimental conditions, namely a glucose pulse for a culture growing in minimal medium with lactose and a batch culture with different initial concentrations of the components of the transport systems. When qualitatively comparing these predictions with experimental data for these two conditions, a number of models can be excluded while other model variants are still not discriminable. The best-performing model variants are based on inducer inclusion and activation of enzymatic genes by a global transcription factor, but the other proposed factors may complement these well-known regulatory mechanisms. CONCLUSIONS: The model ensemble presented here offers a better understanding of the variety of mechanisms that have been proposed to play a role in CCR. In addition, it provides an educational resource for systems biology, as it gives an introduction to a broad range of modeling approaches in the context of a simple but biologically relevant example.

pTRA - A reporter system for monitoring the intracellular dynamics of gene expression.

The presence of standardised tools and methods to measure and represent accurately biological parts and functions is a prerequisite for successful metabolic engineering and crucial to understand and predict the behaviour of synthetic genetic circuits. Many synthetic gene networks are based on transcriptional circuits, thus information on transcriptional and translational activity is important for understanding and fine-tuning the synthetic function. To this end, we have developed a toolkit to analyse systematically the transcriptional and translational activity of a specific synthetic part in vivo. It is based on the plasmid pTRA and allows the assignment of specific transcriptional and translational outputs to the gene(s) of interest (GOI) and to compare different genetic setups. By this, the optimal combination of transcriptional strength and translational activity can be identified. The design is tested in a case study using the gene encoding the fluorescent mCherry protein as GOI. We show the intracellular dynamics of mRNA and protein formation and discuss the potential and shortcomings of the pTRA plasmid.