Niess,A., Failmezger,J., Kuschel,M., Siemann-Herzberg,M. and Takors,R. Experimentally Validated Model Enables Debottlenecking of in Vitro Protein Synthesis and Identifies a Control Shift under in Vivo Conditions. ACS SYNTHETIC BIOLOGY, 6, 1913–1921.
Abstract
Cell-free (in vitro) protein synthesis (CFPS) systems provide a
versatile tool that can be used to investigate different aspects of the
transcription-translation machinery by reducing cells to the basic
functions of protein formation. Recent improvements in reaction
stability and lysate preparation offer the potential to expand the scope
of in vitro biosynthesis from a research tool to a multifunctional and
versatile platform for protein production and synthetic biology. To
date, even the best-performing CFPS systems are drastically slower than
in vivo references. Major limitations are imposed by ribosomal
activities that progress in an order of magnitude slower on the mRNA
template. Owing to the complex nature of the ribosomal machinery,
conventional ``trial and error'' experiments only provide little
insight into how the desired performance could be improved. By applying
a DNA-sequence-oriented mechanistic model, we analyzed the major
differences between cell-free in vitro and in vivo protein synthesis. We
successfully identified major limiting elements of in vitro translation,
namely the supply of ternary complexes consisting of EFTu and tRNA.
Additionally, we showed that diluted in vitro systems suffer from
reduced ribosome numbers. On the basis of our model, we propose a new
experimental design predicting 90\% increased translation rates, which
were well achieved in experiments. Furthermore, we identified a shifting
control in the translation rate, which is characterized by availability
of the ternary complex under in vitro conditions and the initiation of
translation in a living cell. Accordingly, the model can successfully be
applied to sensitivity analyses and experimental design.BibTeX
Niess,A., Loeffler,M., Simen,J.D. and Takors,R. Repetitive Short-Term Stimuli Imposed in Poor Mixing Zones Induce Long-Term Adaptation of E-Coli Cultures in Large-Scale Bioreactors: Experimental Evidence and Mathematical Model. FRONTIERS IN MICROBIOLOGY, 8.
Abstract
Rapidly changing concentrations of substrates frequently occur during
large-scale microbial cultivations. These changing conditions, caused by
large mixing times, result in a heterogeneous population distribution.
Here, we present a powerful and efficient modeling approach to predict
the influence of varying substrate levels on the transcriptional and
translational response of the cell. This approach consists of two parts,
a single-cell model to describe transcription and translation for an
exemplary operon (trp operon) and a second part to characterize cell
distribution during the experimental setup. Combination of both models
enables prediction of transcriptional patterns for the whole population.
In summary, the resulting model is not only able to anticipate the
experimentally observed short-term and long-term transcriptional
response, it further allows envision of altered protein levels. Our
model shows that locally induced stress responses propagate throughout
the bioreactor, resulting in temporal, and spatial population
heterogeneity. Stress induced transcriptional response leads to a new
population steady-state shortly after imposing fluctuating substrate
conditions. In contrast, the protein levels take more than 10 h to
achieve steady-state conditions.BibTeX
Simen,J.D., Loeffler,M., Jaeger,G., Schaeferhoff,K., Freund,A., Matthes,J., Mueller,J., Takors,R. and RecogNice-Team Transcriptional Response of Escherichia Coli to Ammonia and Glucose Fluctuations. MICROBIAL BIOTECHNOLOGY, 10, 858–872.
Abstract
In large-scale production processes, metabolic control is typically
achieved by limited supply of essential nutrients such as glucose or
ammonia. With increasing bioreactor dimensions, microbial producers such
as Escherichia coli are exposed to changing substrate availabilities due
to limited mixing. In turn, cells sense and respond to these dynamic
conditions leading to frequent activation of their regulatory
programmes. Previously, we characterized short- and long-term strategies
of cells to adapt to glucose fluctuations. Here, we focused on
fluctuating ammonia supply while studying a continuously running
two-compartment bioreactor system comprising a stirred tank reactor
(STR) and a plug-flow reactor (PFR). The alarmone ppGpp rapidly
accumulated in PFR, initiating considerable transcriptional responses
after 70s. About 400 genes were repeatedly switched on/off when E.coli
returned to the STR. E.coli revealed highly diverging long-term
transcriptional responses in ammonia compared to glucose fluctuations.
In contrast, the induction of stringent regulation was a common feature
of both short-term responses. Cellular ATP demands for coping with
fluctuating ammonia supply were found to increase maintenance by 15\%.
The identification of genes contributing to the increased ATP demand
together with the elucidation of regulatory mechanisms may help to
create robust cells and processes for large-scale application.BibTeX
Teleki,A., Rahnert,M., Bungart,O., Gann,B., Ochrombel,I. and Takors,R. Robust Identification of Metabolic Control for Microbial L-Methionine Production Following an Easy-to-Use Puristic Approach. METABOLIC ENGINEERING, 41, 159–172.
Abstract
The identification of promising metabolic engineering targets is a key
issue in metabolic control analysis (MCA). Conventional approaches make
intensive use of model-based studies, such as exploiting post-pulse
metabolic dynamics after proper perturbation of the microbial system.
Here, we present an easy-to-use, purely data-driven approach, defining
pool efflux capacities (PEC) for identifying reactions that exert the
highest flux control in linear pathways. Comparisons with linlog-based
MCA and data-driven substrate elasticities (DDSE) showed that similar
key control steps were identified using PEC. Using the example of
L-methionine production with recombinant Escherichia coli, PEC
consistently and robustly identified main flux controls using
perturbation data after a non-labeled C-12-L-serine stimulus.
Furthermore, the application of full-labeled C-13-L-serine stimuli
yielded additional insights into stimulus propagation to L-methionine.
PEC analysis performed on the C-13 data set revealed the same targets as
the C-12 data set. Notably, the typical drawback of metabolome analysis,
namely, the omnipresent leakage of metabolites, was excluded using the
C-13 PEC approach.BibTeX
Lange,J., Mueller,F., Bernecker,K., Dahmen,N., Takors,R. and Blombach,B. Valorization of Pyrolysis Water: A Biorefinery Side Stream, for 1,2-Propanediol Production with Engineered Corynebacterium Glutamicum. BIOTECHNOLOGY FOR BIOFUELS, 10.
Abstract
Background: A future bioeconomy relies on the efficient use of renewable
resources for energy and material product supply. In this context,
biorefineries have been developed and play a key role in converting
lignocellulosic residues. Although a holistic use of the biomass feed is
desired, side streams evoke in current biorefinery approaches. To ensure
profitability, efficiency, and sustainability of the overall conversion
process, a meaningful valorization of these materials is needed. Here, a
so far unexploited side stream derived from fast pyrolysis of wheat
straw-pyrolysis water-was used for production of 1,2-propanediol in
microbial fermentation with engineered Corynebacterium glutamicum.
Results: A protocol for pretreatment of pyrolysis water was established
and enabled growth on its major constituents, acetate and acetol, with
rates up to 0.36 +/- 0.04 h(-1). To convert acetol to 1,2-propanediol,
the plasmid pJULgldA expressing the glycerol dehydrogenase from
Escherichia coli was introduced into C. glutamicum. 1,2-propanediol was
formed in a growth-coupled biotransformation and production was further
increased by construction of C. glutamicum.pqo.aceE.ldhA.mdh pJULgldA.
In a two-phase aerobic/microaerobic fed-batch process with pyrolysis
water as substrate, this strain produced 18.3 +/- 1.2 mM 1,2-propanediol
with a yield of 0.96 +/- 0.05 mol 1,2-propanediol per mol acetol and
showed an overall volumetric productivity of 1.4 +/- 0.1 mmol
1,2-propanediol -L-1 h(-1).
Conclusions: This study implements microbial fermentation into a
biorefinery based on pyrolytic liquefaction of lignocellulosic biomass
and accesses a novel value chain by valorizing the side stream pyrolysis
water for 1,2-PDO production with engineered C. glutamicum. The
established bioprocess operated at maximal product yield and
accomplished the so far highest overall volumetric productivity for
microbial 1,2-PDO production with an engineered producer strain.
Besides, the results highlight the potential of microbial conversion of
this biorefinery side stream to other valuable products.BibTeX
Failmezger,J., Rauter,M., Nitschel,R., Kraml,M. and Siemann-Herzberg,M. Cell-Free Protein Synthesis from Non-Growing, Stressed Escherichia Coli. SCIENTIFIC REPORTS, 7.
Abstract
Cell-free protein synthesis is a versatile protein production system.
Performance of the protein synthesis depends on highly active
cytoplasmic extracts. Extracts from E. coli are believed to work best;
they are routinely obtained from exponential growing cells, aiming to
capture the most active translation system. Here, we report an active
cell-free protein synthesis system derived from cells harvested at
non-growth, stressed conditions. We found a downshift of ribosomes and
proteins. However, a characterization revealed that the stoichiometry of
ribosomes and key translation factors was conserved, pointing to a fully
intact translation system. This was emphasized by synthesis rates, which
were comparable to those of systems obtained from fast-growing cells.
Our approach is less laborious than traditional extract preparation
methods and multiplies the yield of extract per cultivation. This
simplified growth protocol has the potential to attract new entrants to
cell-free protein synthesis and to broaden the pool of applications. In
this respect, a translation system originating from heat stressed,
non-growing E. coli enabled an extension of endogenous transcription
units. This was demonstrated by the sigma factor depending activation of
parallel transcription. Our cell-free expression platform adds to the
existing versatility of cell-free translation systems and presents a
tool for cell-free biology.BibTeX
Loeffler,M., Simen,J.D., Mueller,J., Jaeger,G., Laghrami,S., Schaeferhoff,K., Freund,A., Takors,R. and RecogNice-Team Switching between Nitrogen and Glucose Limitation: Unraveling Transcriptional Dynamics in Escherichia Coli. JOURNAL OF BIOTECHNOLOGY, 258, 2–12.
Abstract
Transcriptional control under nitrogen and carbon-limitation conditions
have been well analyzed for Escherichia colt. However, the
transcriptional dynamics that underlie the shift in regulatory programs
from nitrogen to carbon limitation is not well studied. In the present
study, cells were cultivated at steady state under nitrogen
(ammonia)-limited conditions then shifted to carbon (glucose) limitation
to monitor changes in transcriptional dynamics. Nitrogen limitation was
found to be dominated by sigma 54 (RpoN) and sigma 38 (RpoS), whereas
the ``housekeeping'' sigma factor 70 (RpoD) and sigma 38 regulate
cellular status under glucose limitation. During the transition,
nitrogen-mediated control was rapidly redeemed and mRNAs that encode
active uptake systems, such as ptsG and manXYZ, were quickly amplified.
Next, genes encoding facilitators such as lamB were overexpressed,
followed by high affinity uptake systems such as mglABC and non-specific
porins such as ompF. These regulatory programs are complex and require
well-equilibrated and superior control. At the metabolome level,
2-oxoglutarate is the likely component that links carbon- and
nitrogen-mediated regulation by interacting with major regulatory
elements. In the case of dual glucose and ammonia limitation, sigma 24
(RpoE) appears to play a key role in orchestrating these complex
regulatory networks.BibTeX
Eigenstetter,G. and Takors,R. Dynamic Modeling Reveals a Three-Step Response of Saccharomyces Cerevisiae to High CO2 Levels Accompanied by Increasing ATP Demands. FEMS YEAST RESEARCH, 17.
Abstract
Saccharomyces cerevisiae is often applied in large-scale bioreactors
where gradients of dissolved CO2 exist. Under high CO2 pressure, the
dissolved gas enters the microbe, causing multifold intracellular
responses such as decrease of pH, increase of HCO3- and changes of ion
balance. Effects of varying CO2 concentrations are multifold, hard to
scale and hardly investigated. Hence, the multi-level response to CO2
shifts was summarized in a predicting ODE model with mass action
kinetics, balancing electrochemical charges in steady-state growth
conditions. Compared to experimental observations, the simulated
dynamics of ion concentrations were found to be consistent. During CO2
shifts, the model predicts the initial depolarization of the membrane
potential, the temporal pH drop and the activation of countermeasures
such as Pma1-mediated H+ export and Trk1,2-mediated K+ import. In
conclusion, extracellular cation concentrations and the cellular pH
regulation are critical factors that determine physiology and cellular
energy management. Consequently, pressure-induced CO2 gradients cause
peaks of ATP demand which may occur in cells circulating in large-scale
industrial bioreactors.BibTeX
Failmezger,J., Ludwig,J., Niess,A. and Siemann-Herzberg,M. Quantifying Ribosome Dynamics in Escherichia Coli Using Fluorescence. FEMS MICROBIOLOGY LETTERS, 364.
Abstract
Ribosomes are a crucial component of the physiological state of a cell.
Therefore, we aimed to monitor ribosome dynamics using a fast and easy
fluorescence readout. Using fluorescent-labeled ribosomal proteins, the
dynamics of ribosomes during batch cultivation and during nutritional
shift conditions was investigated. The fluorescence readout was compared
to the cellular rRNA content determined by capillary gel electrophoresis
with laser-induced fluorescence detection during exponentially
accelerating and decelerating growth. We found a linear correlation
between the observed fluorescence and the extracted rRNA content
throughout cultivation, demonstrating the applicability of this method.
Moreover, the results show that ribosome dynamics, as a result of
slowing growth, are accompanied by the passive effect of dilution of
preexisting ribosomes, de novo ribosome synthesis and ribosome
degradation. In light of the challenging task of deciphering ribosome
regulatory mechanisms, our approach of using fluorescence to follow
ribosome dynamics will allow more comprehensive studies of biological
systems.BibTeX
Michalowski,A., Siemann-Herzberg,M. and Takors,R. Escherichia Coli HGT: Engineered for High Glucose Throughput Even under Slowly Growing or Resting Conditions. METABOLIC ENGINEERING, 40, 93–103.
Abstract
Aerobic production-scale processes are constrained by the technical
limitations of maximum oxygen transfer and heat removal. Consequently,
microbial activity is often controlled via limited nutrient feeding to
maintain it within technical operability. Here, we present an
alternative approach based on a newly engineered Escherichia coli
strain. This E. coli HGT (high glucose throughput) strain was engineered
by modulating the stringent response regulation program and decreasing
the activity of pyruvate dehydrogenase. The strain offers about
three-fold higher rates of cell-specific glucose uptake under
nitrogen-limitation (0.6 g(Glc) gCDW(-1) h(-1)) compared to that of wild
type, with a maximum glucose uptake rate of about 1.8 gGlc gCDW(-1)
h(-1) already at a 0.3 h(-1) specific growth rate. The surplus of
imported glucose is almost completely available via pyruvate and is used
to fuel pyruvate and lactate formation. Thus, E. coli HGT represents a
novel chassis as a host for pyruvate-derived products.BibTeX
Lange,J., Takors,R. and Blombach,B. Zero-Growth Bioprocesses: A Challenge for Microbial Production Strains and Bioprocess Engineering. ENGINEERING IN LIFE SCIENCES, 17, 27–35.
Abstract
Microbial fermentation of renewable feedstocks is an established
technology in industrial biotechnology. Besides strict aerobic or
anaerobic modes of operation, novel innovative and industrially
applicable fermentation processes were developed connecting the
advantages of aerobic and anaerobic conditions in a combined production
approach. As a consequence, rapid aerobic biomass formation to high cell
densities and subsequent anaerobic high-yield and zero-growth production
is realized. Following this strategy, bioprocesses operating with
substantial overall yield and productivity can be obtained. Here, we
summarize the current knowledge and achievements in such microbial
zero-growth production processes and pinpoint to challenges due to the
complex adaptation of the cellular metabolism during the cell's passage
from aerobiosis to anaerobiosis.BibTeX
Wolf,S., Barbosa,S., Bücher,J. and Takors,R. (2017) Automatic Network Generation Describes Differential Gene Data in User Friendly and Expeditiously Analyzable Network Views. 2, 1–14.
Abstract
Cancer is a group of diseases that involves abnormal cell growth, resulting from genetic perturbations in signaling mechanisms. High resolution RNAseq and microarray assays enable the evaluation of the transcriptional activity of high number of signaling molecules. Furthermore, many signaling pathways are described in publically available databases. Today’s challenge lies in the connection of signaling pathways and signaling data to produce predictive models which have the power to validate and identify targets in disease treatment. Curating networks manually can be exhaustive handiwork. We designed an ensemble approach of gene set enrichment on seven pathway databases. It generates a basic gene set mapping of the complex input data on comprehensive pathways. Using two publically available protein-protein interaction databases, the novel algorithm automatically reconstructs a comprehensive biological system representation from these mappings. The reconstruction was based on a newly shortest path algorithm. Using a microarray data set from hepatocellular cancer cells as input, a network with well-known cancer signaling mechanisms was derived. Furthermore, nodes accounting for hormone signaling were found as being modified in liver cancer that can be used as future research targets. Two recent publically available networks were adequately inferred when testing the method to reconstruct manually curated signaling networks. Finally, our method shows that integration of raw data and publically available knowledge expeditiously generates convenient and analyzable network views.BibTeX
Pfreundt,U., Spungin,D., Hou,S., Voß,B., Berman-Frank,I. and Hess,W.R. (2017) Genome of a Giant Bacteriophage from a Decaying Trichodesmium Bloom. Marine Genomics, 33, 21–25.
Abstract
De-novo assembly of a metagenomic dataset obtained from a decaying cyanobacterial Trichodesmium bloom from the New Caledonian lagoon resulted in a complete giant phage genome of 257,908bp, obtained independently with multiple assembly tools. Noteworthy, gammaproteobacteria were an abundant fraction in the sequenced samples. Mapping of the raw reads with 99% accuracy to the giant phage genome resulted in an average coverage of 262X. The closest sequenced relatives, albeit still distant, are the Pseudomonas phages PaBG from Lake Baikal and Lu11 isolated from a soil sample from the Philippines. The phage reported here might belong to the same family within the Myoviridae as PaBG and Lu11 and would thus be its first marine member, indicating a more widespread occurrence of this group. We named this phage NCTB (New Caledonia Trichodesmium Bloom) after its origin.BibTeX
Hellmers,F., Takors,R. and Thum,O. (2017) Robust Enzyme Immobilizates for Industrial Isomalt Production. Molecular Catalysis, 445, 293–298.
BibTeX
Kuschel,M., Siebler,F. and Takors,R. (2017) Lagrangian Trajectories to Predict the Formation of Population Heterogeneity in Large-Scale Bioreactors. Bioengineering, 4, 27.
Abstract
Successful scale-up of bioprocesses requires that laboratory-scale performance is equally achieved during large-scale production to meet economic constraints. In industry, heuristic approaches are often applied, making use of physical scale-up criteria that do not consider cellular needs or properties. As a consequence, large-scale productivities, conversion yields, or product purities are often deteriorated, which may prevent economic success. The occurrence of population heterogeneity in large-scale production may be the reason for underperformance. In this study, an in silico method to predict the formation of population heterogeneity by combining computational fluid dynamics (CFD) with a cell cycle model of Pseudomonas putida KT2440 was developed. The glucose gradient and flow field of a 54,000 L stirred tank reactor were generated with the Euler approach, and bacterial movement was simulated as Lagrange particles. The latter were statistically evaluated using a cell cycle model. Accordingly, 72% of all cells were found to switch between standard and multifork replication, and 10% were likely to undergo massive, transcriptional adaptations to respond to extracellular starving conditions. At the same time, 56% of all cells replicated very fast, with µ ≥ 0.3 h−1 performing multifork replication. The population showed very strong heterogeneity, as indicated by the observation that 52.9% showed higher than average adenosine triphosphate (ATP) maintenance demands (12.2%, up to 1.5 fold). These results underline the potential of CFD linked to structured cell cycle models for predicting large-scale heterogeneity in silico and ab initio.BibTeX