Recombinant protein expression in proteome-reduced cells under aerobic and oxygen-limited regimes.

Industrial cultures are hindered by the physiological complexity of the host and the limited mass transfer capacity of conventional bioreactors. In this study, a minimal cell approach was combined with genetic devices to overcome such issues. A flavin mononucleotide-based fluorescent protein (FbFP) was expressed in a proteome-reduced Escherichia coli (PR). When FbFP was expressed from a constitutive protein generator (CPG), the PR strain produced 47% and 35% more FbFP than its wild type (WT), in aerobic or oxygen-limited regimes, respectively. Metabolic and expression models predicted more efficient biomass formation at higher fluxes to FbFP, in agreement with these results. A microaerobic protein generator (MPG) and a microaerobic transcriptional cascade (MTC) were designed to induce FbFP expression upon oxygen depletion. The FbFP fluorescence using the MTC in the PR strain was 9% higher than that of the WT bearing the CPG under oxygen limitation. To further improve the PR strain, the pyruvate dehydrogenase complex regulator gene was deleted, and the Vitreoscilla hemoglobin was expressed. Compared to oxygen-limited cultures of the WT, the engineered strains increased the FbFP expression more than 50% using the MTC. Therefore, the designed expression systems can be a valuable alternative for industrial cultivations.

Enhancing Escherichia coli abiotic stress resistance through ornithine lipid formation.

Escherichia coli is a common host for biotechnology and synthetic biology applications. During growth and fermentation, the microbes are often exposed to stress conditions, such as variations in pH or solvent concentrations. Bacterial membranes play a key role in response to abiotic stresses. Ornithine lipids (OLs) are a group of membrane lipids whose presence and synthesis have been related to stress resistance in bacteria. We wondered if this stress resistance could be transferred to bacteria not encoding the capacity to form OLs in their genome, such as E. coli. In this study, we engineered different E. coli strains to produce unmodified OLs and hydroxylated OLs by expressing the synthetic operon olsFC. Our results showed that OL formation improved pH resistance and increased biomass under phosphate limitation. Transcriptome analysis revealed that OL-forming strains differentially expressed stress- and membrane-related genes. OL-producing strains also showed better growth in the presence of the ionophore carbonyl cyanide 3-chlorophenylhydrazone (CCCP), suggesting reduced proton leakiness in OL-producing strains. Furthermore, our engineered strains showed improved heterologous violacein production at phosphate limitation and also at low pH. Overall, this study demonstrates the potential of engineering the E. coli membrane composition for constructing robust hosts with an increased abiotic stress resistance for biotechnology and synthetic biology applications. KEY POINTS: • Ornithine lipid production in E. coli increases biomass yield under phosphate limitation. • Engineered strains show an enhanced production phenotype under low pH stress. • Transcriptome analysis and CCCP experiments revealed reduced proton leakage.

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.

Author Correction: A quantitative method for proteome reallocation using minimal regulatory interventions.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Effect of operational parameters on photocatalytic degradation of ethylparaben using rGO/TiO2 composite under UV radiation.

The objective of this study was to analyze the influence of different operational variables (catalyst loading, initial EtP concentration, medium pH, the presence of anions and radical scavengers) on the performance of ethylparaben (EtP) photodegradation catalyzed with an rGO/TiO2 composite. EtP was selected for study after analyzing the effect of paraben chain length on its catalytic photodegradation, finding that the photodegradation rate constant values of methyl-, ethyl-, and butyl-paraben are 0.050, 0.096, and 0.136 min-1, respectively. This indicates that the photodegradation rate constant of parabens is higher with longer alkyl chain, which augments its oxidation capacity. The percentage removal of EtP at 40 min increases from 66.3 to 98.6 % when the composite dose rises from 100 to 700 mg/L; however, an additional increase in the composite dose to 1000 mg/L does not substantively improve the photodegradation rate or percentage EtP removal (98.9 %). A rise in the initial EtP concentration from 15 to 100 mg/L reduces the percentage of degradation from 100 to 76.4 %. The percentage EtP degradation is lower with higher solution pH. The presence of HCO3- or Cl- anions in the medium reduces the degradation performance. Results obtained using positive hole and hydroxyl radical scavengers demonstrate that positive holes play an important role in EtP degradation. No degradation product evidences toxicity against the cultured human embryonic kidney cell line HEK-293.

Laboratory evolution reveals a two-dimensional rate-yield tradeoff in microbial metabolism.

Growth rate and yield are fundamental features of microbial growth. However, we lack a mechanistic and quantitative understanding of the rate-yield relationship. Studies pairing computational predictions with experiments have shown the importance of maintenance energy and proteome allocation in explaining rate-yield tradeoffs and overflow metabolism. Recently, adaptive evolution experiments of Escherichia coli reveal a phenotypic diversity beyond what has been explained using simple models of growth rate versus yield. Here, we identify a two-dimensional rate-yield tradeoff in adapted E. coli strains where the dimensions are (A) a tradeoff between growth rate and yield and (B) a tradeoff between substrate (glucose) uptake rate and growth yield. We employ a multi-scale modeling approach, combining a previously reported coarse-grained small-scale proteome allocation model with a fine-grained genome-scale model of metabolism and gene expression (ME-model), to develop a quantitative description of the full rate-yield relationship for E. coli K-12 MG1655. The multi-scale analysis resolves the complexity of ME-model which hindered its practical use in proteome complexity analysis, and provides a mechanistic explanation of the two-dimensional tradeoff. Further, the analysis identifies modifications to the P/O ratio and the flux allocation between glycolysis and pentose phosphate pathway (PPP) as potential mechanisms that enable the tradeoff between glucose uptake rate and growth yield. Thus, the rate-yield tradeoffs that govern microbial adaptation to new environments are more complex than previously reported, and they can be understood in mechanistic detail using a multi-scale modeling approach.

Metabolic reconstruction of Pseudomonas chlororaphis ATCC 9446 to understand its metabolic potential as a phenazine-1-carboxamide-producing strain.

Pseudomonas chlororaphis is a plant-associated bacterium with reported antagonistic activity against different organisms and plant growth-promoting properties. P. chlororaphis possesses exciting biotechnological features shared with another Pseudomonas with a nonpathogenic phenotype. Part of the antagonistic role of P. chlororaphis is due to its production of a wide variety of phenazines. To expand the knowledge of the metabolic traits of this organism, we constructed the first experimentally validated genome-scale model of P. chlororaphis ATCC 9446, containing 1267 genes and 2289 reactions, and analyzed strategies to maximize its potential for the production of phenazine-1-carboxamide (PCN). The resulting model also describes the capability of P. chlororaphis to carry out the denitrification process and its ability to consume sucrose (Scr), trehalose, mannose, and galactose as carbon sources. Additionally, metabolic network analysis suggested fatty acids as the best carbon source for PCN production. Moreover, the optimization of PCN production was performed with glucose and glycerol. The optimal PCN production phenotype requires an increased carbon flux in TCA and glutamine synthesis. Our simulations highlight the intrinsic H2O2 flux associated with PCN production, which may generate cellular stress in an overproducing strain. These results suggest that an improved antioxidative strategy could lead to optimal performance of phenazine-producing strains of P. chlororaphis. KEY POINTS : • This is the first publication of a metabolic model for a strain of P. chlororaphis. • Genome-scale model is worthy tool to increase the knowledge of a non model organism. • Fluxes simulations indicate a possible effect of H2O2 on phenazines production. • P. chlororaphis can be a suitable model for a wide variety of compounds.

Model-driven discovery of underground metabolic functions in Escherichia coli.

Enzyme promiscuity toward substrates has been discussed in evolutionary terms as providing the flexibility to adapt to novel environments. In the present work, we describe an approach toward exploring such enzyme promiscuity in the space of a metabolic network. This approach leverages genome-scale models, which have been widely used for predicting growth phenotypes in various environments or following a genetic perturbation; however, these predictions occasionally fail. Failed predictions of gene essentiality offer an opportunity for targeting biological discovery, suggesting the presence of unknown underground pathways stemming from enzymatic cross-reactivity. We demonstrate a workflow that couples constraint-based modeling and bioinformatic tools with KO strain analysis and adaptive laboratory evolution for the purpose of predicting promiscuity at the genome scale. Three cases of genes that are incorrectly predicted as essential in Escherichia coli--aspC, argD, and gltA--are examined, and isozyme functions are uncovered for each to a different extent. Seven isozyme functions based on genetic and transcriptional evidence are suggested between the genes aspC and tyrB, argD and astC, gabT and puuE, and gltA and prpC. This study demonstrates how a targeted model-driven approach to discovery can systematically fill knowledge gaps, characterize underground metabolism, and elucidate regulatory mechanisms of adaptation in response to gene KO perturbations.

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.

Use of adaptive laboratory evolution to discover key mutations enabling rapid growth of Escherichia coli K-12 MG1655 on glucose minimal medium.

Adaptive laboratory evolution (ALE) has emerged as an effective tool for scientific discovery and addressing biotechnological needs. Much of ALE's utility is derived from reproducibly obtained fitness increases. Identifying causal genetic changes and their combinatorial effects is challenging and time-consuming. Understanding how these genetic changes enable increased fitness can be difficult. A series of approaches that address these challenges was developed and demonstrated using Escherichia coli K-12 MG1655 on glucose minimal media at 37°C. By keeping E. coli in constant substrate excess and exponential growth, fitness increases up to 1.6-fold were obtained compared to the wild type. These increases are comparable to previously reported maximum growth rates in similar conditions but were obtained over a shorter time frame. Across the eight replicate ALE experiments performed, causal mutations were identified using three approaches: identifying mutations in the same gene/region across replicate experiments, sequencing strains before and after computationally determined fitness jumps, and allelic replacement coupled with targeted ALE of reconstructed strains. Three genetic regions were most often mutated: the global transcription gene rpoB, an 82-bp deletion between the metabolic pyrE gene and rph, and an IS element between the DNA structural gene hns and tdk. Model-derived classification of gene expression revealed a number of processes important for increased growth that were missed using a gene classification system alone. The methods described here represent a powerful combination of technologies to increase the speed and efficiency of ALE studies. The identified mutations can be examined as genetic parts for increasing growth rate in a desired strain and for understanding rapid growth phenotypes.

Melatonin controls experimental autoimmune encephalomyelitis by altering the T effector/regulatory balance.

Experimental autoimmune encephalomyelitis (EAE), the experimental model for multiple sclerosis (MS), is triggered by myelin-specific Th1 and Th17 cells. The immunomodulatory activities of melatonin have been shown to be beneficial under several conditions in which the immune system is exacerbated. Here, we sought to elucidate the basis of the melatonin protective effect on EAE by characterizing the T effector/regulatory responses, particularly those of the memory cell subsets. Melatonin was tested for its effect on Th1, Th17 and T regulatory (Treg) cells in the lymph nodes and CNS of immunodominant peptide of myelin oligodendrocyte glycoprotein (pMOG)-immunized and EAE mice, respectively. The capacity of melatonin to ameliorate EAE as well as modifying both T cell response and effector/regulatory balance was surveyed. T cell memory subsets and CD44, a key activation marker involved in the EAE pathogenesis, were also examined. Melatonin protected from EAE by decreasing peripheral and central Th1/Th17 responses and enhancing both the Treg frequency and IL-10 synthesis in the CNS. Melatonin reduced the T effector memory population and its pro-inflammatory response and regulated CD44 expression, which was decreased in T effector cells and increased in Tregs. The alterations in the T cell subpopulations were associated with a reduced mononuclear infiltration (CD4 and CD11b cells) of the melatonin-treated mice CNS. For the first time, we report that melatonin protects against EAE by controlling peripheral and central T effector/regulatory responses, effects that might be partially mediated by CD44. This immunomodulatory effect on EAE suggests that melatonin may represent an effective treatment option for MS.

Electrostatic Fermentation: Molecular Response Insights for Tailored Beer Production.

Electrostatic fermentation avoids the cellular redox imbalance of traditional fermentation, but knowledge gaps exist. This study explores the impact of electrostatic fermentation on the growth, volatile profile, and genetic response of Saccharomyces pastorianus Saflager S-23. The applied voltage (15 and 30 V) in the electrostatic fermentation system increased the growth and substrate utilization of S. pastorianus while decreasing ethanol production. The aromas typically associated with traditional fermentation, such as alcoholic, grape, apple, and sweet notes, were diminished, while aromas like roses, fruits, flowers, and bananas were augmented in electrostatic fermentation. RNA-seq analysis revealed upregulation of genes involved in cell wall structure, oxidoreductase activity, and iron ion binding, while genes associated with protein synthesis, growth control, homeostasis, and membrane function were downregulated under the influence of applied voltage. The electrostatic fermentation system modulates genetic responses and metabolic pathways in yeast, rendering it a promising method for tailored beer production. Demonstrating feasibility under industrial-scale and realistic conditions is crucial for advancing towards commercialization.

Metabolic and transcriptional response of Escherichia coli with a NADP(+)-dependent glyceraldehyde 3-phosphate dehydrogenase from Streptococcus mutans.

The NAD(+)-dependent glyceraldehyde-3-phosphate-dehydrogenase (NAD(+)-GAPDH) is a key enzyme to sustain the glycolytic function in Escherichia coli and to generate NADH. In the absence of NAD(+)-GAPDH activity, the glycolytic function can be restored through NADP(+)-dependent GAPDH heterologous expression. Here, some metabolic and transcriptional effects are described when the NAD(+)-GAPDH gene from E. coli (gapA) is replaced with the NADP(+)-GAPDH gene from Streptococcus mutans (gapN). Expression of gapN was controlled by the native gapA promoter (E. coliΔgapA::gapN) or by the constitutive trc promoter in a multicopy plasmid (E. coliΔgapA::gapN/pTrcgapN). The specific NADP(+)-GAPDH activity was 4.7 times higher in E. coliΔgapA::gapN/pTrcgapN than E. coliΔgapA::gapN. Growth, glucose consumption and acetic acid production rates increased in agreement with the NADP(+)-GAPDH activity level. Analysis of E. coliΔgapA::gapN/pTrcgapN showed that although gapN expression complemented NAD(+)-GAPDH activity, the resulting low NADH levels decreased the expression of the respiratory chain and oxidative phosphorylation genes (ndh, cydA, cyoB and atpA). In comparison with the wild type strain, E. coliΔgapA::gapN/pTrcgapN decreased the percentage of mole of oxygen consumed per mole of glucose metabolized by 40 % with a concomitant reduction of 54 % in the ATP/ADP ratio. The cellular response to avoid NADPH excess led to the overexpression of the transhydrogenase coded by udhA and the down-regulation of the pentose-phosphate and Krebs cycle genes, which reduced the CO2 production and increased the acetic acid synthesis. The E. coli strains obtained in this work can be useful for future metabolic engineering efforts aiming for the production of metabolites which biosynthesis depends on NADPH.

Expression of hypothalamic regulatory peptides in thyroid C cells of different mammals.

Besides intervening in calcium homeostasis by means of calcitonin, C cells are also implicated in the synthesis of an increasing number of regulatory peptides that could exert a paracrine regulation on the neighbouring follicular cells. Among the latest peptides reported in C cells, there are several characteristic hypothalamic peptides, such as TRH, CART, and ghrelin, which are mainly involved in the regulation of the metabolism at hypothalamic-pituitary-thyroid axis. The main aim of the present work has been to study the synthesis of the referred hypothalamic peptides by normal and neoplastic C cells of different mammals as well as in C-cell lines of both rat (CA-77, 6-23) and human (TT) origins in order to elucidate whether this is a fact in this kind of vertebrates. With that objective, we have applied the immunoperoxidase technique to analyze the presence of TRH, CART, ghrelin, and somatostatin in thyroid tissues of different species, and immunofluorescence to study those same peptides in C-cell cultures. Furthermore, we have investigated their expression at mRNA level by RT-PCR analysis. Our results demonstrate immunocolocalization of CART, ghrelin, somatostatin and TRH with calcitonin in normal C cells of different mammals, as well as in rat and human neoplastic C cells. We also confirm the expression of those peptides in rat and human C-cell lines by RT-PCR. Consequently, we can conclude that the synthesis of those peptides by C cells is a general event characteristic of the thyroid gland in mammals.

Tetracycline removal from water by adsorption/bioadsorption on activated carbons and sludge-derived adsorbents.

The objective of this study was to analyze the behavior of activated carbons with different chemical and textural natures in the adsorption of three tetracyclines (TCs) (tetracycline, oxytetracycline, and chlortetracycline). We also assessed the influence of the solution pH and ionic strength on the adsorption of these compounds and studied their removal by the combined use of microorganisms and activated carbon (bioadsorption). Sludge-derived materials were also used to remove TC from water. The capacity of these materials to adsorb TC was very high and was much greater than that of commercial activated carbon. This elevated adsorption capacity (512.1-672.0 mg/g) is explained by the high tendency of TC to form complex ions with some of the metal ions present in these materials. The medium pH and presence of electrolytes considerably affected TCs adsorption on commercial activated carbon. These results indicate that electrostatic adsorbent-adsorbate interactions play an important role in TC adsorption processes when conducted at pH values that produce TC deprotonation. The presence of bacteria during the TCs adsorption process decreases their adsorption/bioadsorption on the commercial activated carbon, weakening interactions between the adsorbate and the microfilm formed on the carbon surface. The adsorptive capacity was considerably lower in dynamic versus static regime, attributable to problems of TC diffusion into carbon pores and the shorter contact time between adsorbate and adsorbent.

Engineering resource allocation in artificially minimized cells: Is genome reduction the best strategy?

The elimination of the expression of cellular functions that are not needed in a certain well-defined artificial environment, such as those used in industrial production facilities, has been the goal of many cellular minimization projects. The generation of a minimal cell with reduced burden and less host-function interactions has been pursued as a tool to improve microbial production strains. In this work, we analysed two cellular complexity reduction strategies: genome and proteome reduction. With the aid of an absolute proteomics data set and a genome-scale model of metabolism and protein expression (ME-model), we quantitatively assessed the difference of reducing genome to the correspondence of reducing proteome. We compare the approaches in terms of energy consumption, defined in ATP equivalents. We aim to show what is the best strategy for improving resource allocation in minimized cells. Our results show that genome reduction by length is not proportional to reducing resource use. When we normalize calculated energy savings, we show that strains with the larger calculated proteome reduction show the largest resource use reduction. Furthermore, we propose that reducing highly expressed proteins should be the target as the translation of a gene uses most of the energy. The strategies proposed here should guide cell design when the aim of a project is to reduce the maximum amount or cellular resources.

Engineering and adaptive evolution of Escherichia coli for D-lactate fermentation reveals GatC as a xylose transporter.

Despite the abundance of xylose in nature, the production of chemicals from C5 sugars remains challenging in metabolic engineering. By deleting xylFGH genes and using adaptive evolution, an efficient E. coli strain capable of producing D-lactate from xylose was engineered. Quantitative proteomics and genome sequencing were used to understand the new phenotype and the metabolic limitations of xylose conversion to D-lactate. Proteomics identified major changes in enzyme concentration in the glycolytic and tricarboxylic acid pathways. Whole genome sequencing of the evolved strain identified a point mutation in the gatC gene, which resulted in a change from serine to leucine at position 184 of the GatC protein. The knockout of gatC in a number of strains and the insertion of the mutation in the non-evolved strain confirmed its activity as a xylose transporter and demonstrated that the mutation is responsible for the high xylose consumption phenotype in the evolved strain. The newly found xylose transporter is a candidate for future strain engineering for converting C5-C6 syrups into valuable chemicals.

Environmental impact of phthalic acid esters and their removal from water and sediments by different technologies--a review.

This article describes the most recent methods developed to remove phthalic acid esters (PAEs) from water, wastewater, sludge, and soil. In general, PAEs are considered to be endocrine disrupting chemicals (EDCs), whose effects may not appear until long after exposure. There are numerous methods for removing PAEs from the environment, including physical, chemical and biological treatments, advanced oxidation processes and combinations of these techniques. This review largely focuses on the treatment of PAEs in aqueous solutions but also reports on their treatment in soil and sludge, as well as their effects on human health and the environment.

Regulatory perturbations of ribosome allocation in bacteria reshape the growth proteome with a trade-off in adaptation capacity.

Bacteria regulate their cellular resource allocation to enable fast growth-adaptation to a variety of environmental niches. We studied the ribosomal allocation, growth, and expression profiles of two sets of fast-growing mutants of Escherichia coli K-12 MG1655. Mutants with only three of the seven copies of ribosomal RNA operons grew faster than the wild-type strain in minimal media and show similar phenotype to previously studied fast-growing rpoB mutants. Comparing these two different regulatory perturbations (rRNA promoters or rpoB mutations), we show how they reshape the proteome for growth with a concomitant fitness cost. The fast-growing mutants shared downregulation of hedging functions and upregulated growth functions. They showed longer diauxic shifts and reduced activity of gluconeogenic promoters during glucose-acetate shifts, suggesting reduced availability of the RNA polymerase for expressing hedging proteome. These results show that the regulation of ribosomal allocation underlies the growth/hedging phenotypes obtained from laboratory evolution experiments.

Life Cycle Assessment of Cement Production with Marble Waste Sludges.

The construction industry has a considerable environmental impact in societies, which must be controlled to achieve adequate sustainability levels. In particular, cement production contributes 5-8% of CO2 emissions worldwide, mainly from the utilization of clinker. This study applied Life Cycle Assessment (LCA) methodology to investigate the environmental impact of cement production and explore environmental improvements obtained by adding marble waste sludges in the manufacture of Portland cement. It was considered that 6-35% of the limestone required for its production could be supplied by marble waste sludge (mainly calcite), meeting the EN 197-1:2011 norm. Energy consumption and greenhouse gas (GHG) emission data were obtained from the Ecovent database using commercial LCA software. All life cycle impact assessment indicators were lower for the proposed "eco-cement" than for conventional cement, attributable to changes in the utilization of limestone and clinker. The most favorable results were achieved when marble waste sludge completely replaced limestone and was added to clinker at 35%. In comparison to conventional Portland cement production, this process reduced GHG emissions by 34%, the use of turbine waters by 60%, and the emission of particles into the atmosphere by 50%. Application of LCA methodology allowed evaluation of the environmental impact and improvements obtained with the production of a type of functional eco-cement. This approach is indispensable for evaluating the environmental benefits of using marble waste sludges in the production of cement.