Assessing the potential of mutational strategies to elicit new phenotypes in industrial strains

High-throughput bioamphiphile production by ethyl methane sulphonate induced mutant of hydrocarbonoclastic Enterobacter xiangfangensis STP-3: In depth structural elucidation and application to petroleum refinery oil sludge bioremediation

The environmental release of noxious petroleum hydrocarbons (PHCs) from the petroleum refining industries is an intractable global challenge. Indigenous PHCs degrading microbes produce insufficient yield of amphiphilic biomolecules with trivial efficiency makes the bioremediation process ineffective. In this concern, the present study is focused on the production of high yield multi-functional amphiphilic biomolecule through the genetic modification of Enterobacter xiangfangensis STP-3 strain using Ethyl methane sulphonate (EMS) induced mutagenesis. Mutant M9_{E.xiangfangensis} showed 2.32-fold increased yield of bioamphiphile than wild-type strain. Novel bioamphiphile produced by M9_{E.xiangfangensis} exhibited improved surface and emulsification activities which ensure the maximum degradation of petroleum oil sludge (POS) by 86% than wild-type (72%). SARA, FT-IR, and GC-MS analyses confirmed the expedited degradation of POS and ICP-MS analysis indicated the enhanced removal of heavy metals in connection with the ample production of functionally improved bioamphiphile. FT-IR NMR, MALDI-TOF, GC-MS and LC-MS/MS analyses portrayed the lipoprotein nature of bioamphiphile comprising pentameric fatty acid moiety conjugated with the catalytic esterase moiety. Further, homology modelling and molecular docking revealed the stronger interaction of hydrophobic amino acids, leucine and isoleucine with the PHCs in the case of wild-type esterase moiety, whereas in the mutant, aromatic amino acids were majorly interacted with the long chain and branched chain alkanes, thereby exhibited better efficiency. This is the first report on the adoption of EMS induced mutagenesis strategy to ameliorate the amphiphilic biomolecules for their sustainable applications in diverse biotechnological, environmental and industrial arenas.

Improving acid resistance of Escherichia coli base on the CfaS-mediated membrane engineering strategy derived from extreme acidophile

Industrial microorganisms used for the production of organic acids often face challenges such as inhibited cell growth and reduced production efficiency due to the accumulation of acidic metabolites. One promising way for improving the acid resistance of microbial cells is to reconstruct their membranes. Herein, the overexpression of cfa2 from extreme acidophile endowed E. coli with high-performance on resistance to the acid stress. The engineered strain M1-93-Accfa2, constructed by CRISPR/Cas9-mediated chromosome integration, also exhibited a significantly higher resistance to severe acid stress. The analysis of fatty acid profiles indicated that the proportion of Cy-19:0 in the cell membrane of M1-93-Accfa2 increased by 5.26 times compared with the control, while the proportion of C18:1w9c decreased by 5.81 times. Correspondingly, the permeability and fluidity of the membrane decreased significantly. HPLC analysis demonstrated that the contents of intracellular glutamic acid, arginine, methionine and aspartic acid of M1-93-Accfa2 were 2.59, 2.04, 22.07 and 2.65 times that of the control after environmental acidification, respectively. Meanwhile, transmission electron microscopy observation indicated that M1-93-Accfa2 could maintain a plumper cell morphology after acid stimulation. M1-93-Accfa2 also exhibited higher-performance on the resistance to organic acids, especially succinic acid stress. These results together demonstrated the great potential of M1-93-Accfa2 constructed here in the production of organic acids.

Engineering prokaryotic regulator IrrE to enhance stress tolerance in budding yeast

BACKGROUND

Stress tolerance is one of the important desired microbial traits for industrial bioprocesses, and global regulatory protein engineering is an efficient approach to improve strain tolerance. In our study, IrrE, a global regulatory protein from the prokaryotic organism Deinococcus radiodurans, was engineered to confer yeast improved tolerance to the inhibitors in lignocellulose hydrolysates or high temperatures.

RESULTS

Three IrrE mutations were developed through directed evolution, and the expression of these mutants could improve the yeast fermentation rate by threefold or more in the presence of multiple inhibitors. Subsequently, the tolerance to multiple inhibitors of single-site mutants based on the mutations from the variants were then evaluated, and 11 mutants, including L65P, I103T, E119V, L160F, P162S, M169V, V204A, R244G, Base 824 Deletion, V299A, and A300V were identified to be critical for the improved representative inhibitors, i.e., furfural, acetic acid and phenol (FAP) tolerance. Further studies indicated that IrrE caused genome-wide transcriptional perturbation in yeast, and the mutant I24 led to the rapid growth of Saccharomyces cerevisiae by primarily regulating the transcription level of transcription activators/factors, protecting the intracellular environment and enhancing the antioxidant capacity under inhibitor environments, which reflected IrrE plasticity. Meanwhile, we observed that the expression of the wild-type or mutant IrrE could also protect Saccharomyces cerevisiae from the damage caused by thermal stress. The recombinant yeast strains were able to grow with glucose at 42 ℃.

CONCLUSIONS

IrrE from Deinococcus radiodurans can be engineered as a tolerance-enhancer for Saccharomyces cerevisiae. Systematic research on the regulatory model and mechanism of a prokaryotic global regulatory factor IrrE to increase yeast tolerance provided valuable insights for the improvements in microbial tolerance to complex industrial stress conditions.

Sigma Factor Modulation for Cyanobacterial Metabolic Engineering

Sigma (σ) factors are key regulatory proteins that control the transcription initiation in prokaryotes. In response to environmental or developmental cues, σ factors initiate the transcription of necessary genes responsible for maintaining a life-sustaining metabolic balance. Due to the significant role of σ factors in bacterial metabolism, their rational engineering for commercial metabolite production in photoautotrophic, cyanobacterial cells is a desirable venture. As cyanobacterial genomes typically encode multiple σ factors, effective execution of metabolic engineering efforts largely relies on uncovering the complicated gene regulatory network and further characterization of the members of σ factor regulatory circuits. This review outlines the prospects of σ factor in metabolic engineering of cyanobacteria, summarizes the challenges in the path towards an efficient strain construction and highlights the genomic context of putative regulators of cyanobacterial σ factors.

Metabolic pathway engineering: Perspectives and applications

BACKGROUND

Metabolic engineering aims at contriving microbes as biocatalysts for enhanced and cost-effective production of countless secondary metabolites. These secondary metabolites can be treated as the resources of industrial chemicals, pharmaceuticals and fuels. Plants are also crucial targets for metabolic engineers to produce necessary secondary metabolites. Metabolic engineering of both microorganism and plants also contributes towards drug discovery. In order to implement advanced metabolic engineering techniques efficiently, metabolic engineers should have detailed knowledge about cell physiology and metabolism. Principle behind methodologies: Genome-scale mathematical models of integrated metabolic, signal transduction, gene regulatory and protein-protein interaction networks along with experimental validation can provide such knowledge in this context. Incorporation of omics data into these models is crucial in the case of drug discovery. Inverse metabolic engineering and metabolic control analysis (MCA) can help in developing such models. Artificial intelligence methodology can also be applied for efficient and accurate metabolic engineering.

CONCLUSION

In this review, we discuss, at the beginning, the perspectives of metabolic engineering and its application on microorganism and plant leading to drug discovery. At the end, we elaborate why inverse metabolic engineering and MCA are closely related to modern metabolic engineering. In addition, some crucial steps ensuring efficient and optimal metabolic engineering strategies have been discussed. Moreover, we explore the use of genomics data for the activation of silent metabolic clusters and how it can be integrated with metabolic engineering. Finally, we exhibit a few applications of artificial intelligence to metabolic engineering.

CgCmk1 Activates CgRds2 To Resist Low-pH Stress in Candida glabrata

In Candida glabrata, the transcription factor CgRds2 has been previously characterized as a regulator of glycerophospholipid metabolism, playing a crucial role in the response to osmotic stress. Here, we report that CgRds2 is also involved in the response to pH 2.0 stress. At pH 2.0, the deletion of CgRDS2 led to reduced cell growth and survival, by 33% and 57%, respectively, compared with those of the wild-type strain. These adverse phenotypes resulted from the downregulation of genes related to energy metabolism in the Cgrds2Δ strain at pH 2.0, which led to a 34% reduction of the intracellular ATP content and a 24% decrease in membrane permeability. In contrast, the overexpression of CgRDS2 rescued the growth defect of the Cgrds2Δ strain and increased cell survival at pH 2.0 by 17% compared with that of the wild-type strain, and this effect was accompanied by significant increases in ATP content and membrane permeability, by 42% and 19%, respectively. Furthermore, we found that the calcium/calmodulin-dependent protein kinase (CaMK) CgCmk1 physically interacts with the PAS domain of CgRds2, and CgCmk1 is required for CgRds2 activation and translocation from the cytoplasm to the nucleus under pH 2.0 stress. Moreover, CgCmk1 is critical for CgRds2 function in resistance to pH 2.0 stress, because cells of the Cgrds2-pas strain with a disrupted CgCmk1-CgRds2 interaction exhibited impaired energy metabolism and membrane permeability at pH 2.0. Therefore, our results indicate that CgCmk1 positively regulates CgRds2 and suggest that they promote resistance to low-pH stress by enhancing energy metabolism and membrane permeability in C. glabrata IMPORTANCE An acidic environment is the main problem in the production of organic acids in C. glabrata The present study reports that the calcium/calmodulin-dependent protein kinase CgCmk1 positively regulates CgRds2 to increase intracellular ATP content, membrane permeability, and resistance to low-pH stress. Hence, the transcription factor CgRds2 may be a potential target for improving the acid stress tolerance of C. glabrata during the fermentation of organic acids. The present study also establishes a new link between the calcium signaling pathway and energy metabolism.

Engineering global transcription to tune lipophilic properties in Yarrowia lipolytica

BACKGROUND

Evolution of complex phenotypes in cells requires simultaneously tuning expression of large amounts of genes, which can be achieved by reprograming global transcription. Lipophilicity is an important complex trait in oleaginous yeast Yarrowia lipolytica. It is necessary to explore the changes of which genes' expression levels will tune cellular lipophilic properties via the strategy of global transcription engineering.

RESULTS

We achieved a strategy of global transcription engineering in Y. lipolytica by modifying the sequences of a key transcriptional factor (TF), SPT15-like (Yl-SPT15). The combinatorial mutagenesis of this gene was achieved by DNA assembly of up to five expression cassettes of its error-prone PCR libraries. A heterologous beta-carotene biosynthetic pathway was constructed to research the effects of combined Yl-SPT15 mutants on carotene and lipid production. As a result, we obtained both an "enhanced" strain with 4.7-fold carotene production and a "weakened" strain with 0.13-fold carotene production relative to the initial strain, nearly 40-fold changing range. Genotype verification, comparative transcriptome analysis, and detection of the amounts of total and free fatty acids were made for the selected strains, indicating effective tuning of cells' lipophilic properties. We exploited the key pathways including RNA polymerase, ketone body metabolism, fatty acid synthesis, and degradation that drastically determined cells' variable lipophilicity.

CONCLUSIONS

We have examined the effects of combinatorial mutagenesis of Yl-SPT15 on cells' capacity of producing beta-carotene and lipids. The lipophilic properties in Y. lipolytica could be effectively tuned by simultaneously regulating genome-wide multi-gene expression levels. The exploited gene targets and pathways could guide design and reconstruction of yeast cells for tunable and optimal production of other lipophilic products.

Systematic and synthetic approaches to rewire regulatory networks

Microbial gene regulatory networks are composed of cis- and trans-components that in concert act to control essential and adaptive cellular functions. Regulatory components and interactions evolve to adopt new configurations through mutations and network rewiring events, resulting in novel phenotypes that may benefit the cell. Advances in high-throughput DNA synthesis and sequencing have enabled the development of new tools and approaches to better characterize and perturb various elements of regulatory networks. Here, we highlight key recent approaches to systematically dissect the sequence space of cis-regulatory elements and trans-regulators as well as their inter-connections. These efforts yield fundamental insights into the architecture, robustness, and dynamics of gene regulation and provide models and design principles for building synthetic regulatory networks for a variety of practical applications.

Mutator genomes decay, despite sustained fitness gains, in a long-term experiment with bacteria

Understanding the extreme variation among bacterial genomes remains an unsolved challenge in evolutionary biology, despite long-standing debate about the relative importance of natural selection, mutation, and random drift. A potentially important confounding factor is the variation in mutation rates between lineages and over evolutionary history, which has been documented in several species. Mutation accumulation experiments have shown that hypermutability can erode genomes over short timescales. These results, however, were obtained under conditions of extremely weak selection, casting doubt on their general relevance. Here, we circumvent this limitation by analyzing genomes from mutator populations that arose during a long-term experiment with Escherichia coli, in which populations have been adaptively evolving for >50,000 generations. We develop an analytical framework to quantify the relative contributions of mutation and selection in shaping genomic characteristics, and we validate it using genomes evolved under regimes of high mutation rates with weak selection (mutation accumulation experiments) and low mutation rates with strong selection (natural isolates). Our results show that, despite sustained adaptive evolution in the long-term experiment, the signature of selection is much weaker than that of mutational biases in mutator genomes. This finding suggests that relatively brief periods of hypermutability can play an outsized role in shaping extant bacterial genomes. Overall, these results highlight the importance of genomic draft, in which strong linkage limits the ability of selection to purge deleterious mutations. These insights are also relevant to other biological systems evolving under strong linkage and high mutation rates, including viruses and cancer cells.

Biosensor-assisted transcriptional regulator engineering for Methylobacterium extorquens AM1 to improve mevalonate synthesis by increasing the acetyl-CoA supply

Acetyl-CoA is not only an important intermediate metabolite for cells but also a significant precursor for production of industrially interesting metabolites. Methylobacterium extorquens AM1, a model strain of methylotrophic cell factories using methanol as carbon source, is of interest because it produces abundant coenzyme A compounds capable of directing to synthesis of different useful compounds from methanol. However, acetyl-CoA is not always efficiently accumulated in M. extorquens AM1, as it is located in the center of three cyclic central metabolic pathways. Here we successfully demonstrated a strategy for sensor-assisted transcriptional regulator engineering (SATRE) to control metabolic flux re-distribution to increase acetyl-CoA flux from methanol for mevalonate production in M. extorquens AM1 with introduction of mevalonate synthesis pathway. A mevalonate biosensor was constructed and we succeeded in isolating a mutated strain (Q49) with a 60% increase in mevalonate concentration (an acetyl-CoA-derived product) following sensor-based high-throughput screening of a QscR transcriptional regulator library. The mutated QscR-49 regulator (Q8*,T61S,N72Y,E160V) lost an N-terminal α-helix and underwent a change in the secondary structure of the RD-I domain at the C terminus, two regions that are related to its interaction with DNA. ¹³C labeling analysis revealed that acetyl-CoA flux was improved by 7% and transcriptional analysis revealed that QscR had global effects and that two key points, NADPH generation and fumC overexpression, might contribute to the carbon flux re-distribution. A fed-batch fermentation in a 5-L bioreactor for QscR-49 mutant yielded a mevalonate concentration of 2.67g/L, which was equivalent to an overall yield of 0.055mol acetyl-CoA/mol methanol, the highest yield among engineered strains of M. extorquens AM1. This work was the first attempt to regulate M. extorquens AM1 on transcriptional level and provided molecular insights into the mechanism of carbon flux regulation.

Crz1p Regulates pH Homeostasis in Candida glabrata by Altering Membrane Lipid Composition

The asexual facultative aerobic haploid yeast Candida glabrata is widely used in the industrial production of various organic acids. To elucidate the physiological function of the C. glabrata transcription factor Crz1p (CgCrz1p) and its role in tolerance to acid stress, we deleted or overexpressed the corresponding gene, CgCRZ1 Deletion of CgCRZ1 resulted in a 60% decrease in the dry weight of cells (DCW) and a 50% drop in cell viability compared with those of the wild type at pH 2.0. Expression of lipid metabolism-associated genes was also significantly downregulated. Consequently, the proportion of C_18:1 fatty acids, the ratio of unsaturated to saturated fatty acids, and the ergosterol content decreased by 30%, 46%, and 30%, respectively. Additionally, membrane integrity, fluidity, and H⁺-ATPase activity were reduced by 45%, 9%, and 50%, respectively. In contrast, overexpression of CgCrz1p increased C_18:1 and ergosterol contents by 16% and 40%, respectively. Overexpression also enhanced membrane integrity, fluidity, and H⁺-ATPase activity by 31%, 6%, and 20%, respectively. Moreover, in the absence of pH buffering, the DCW and pyruvate titers increased by 48% and 60%, respectively, compared to that of the wild type. Together, these results suggest that CgCrz1p regulates tolerance to acidic conditions by altering membrane lipid composition in C. glabrataIMPORTANCE This study provides insight into the metabolism of Candida glabrata under acidic conditions, such as those encountered during the industrial production of organic acids. We found that overexpression of the transcription factor CgCrz1p improved viability, biomass, and pyruvate yields at a low pH. Analysis of plasma membrane lipid composition indicated that CgCrz1p might play an important role in its integrity and fluidity and that it enhanced the pumping of protons in acidic environments. We propose that altering the structure of the cell membrane may provide a successful strategy for increasing C. glabrata productivity at a low pH.

Using global transcription machinery engineering (gTME) to improve ethanol tolerance of Zymomonas mobilis

BACKGROUND

With the increasing global crude oil crisis and resulting environmental concerns, the production of biofuels from renewable resources has become increasingly important. One of the major challenges faced during the process of biofuel production is the low tolerance of the microbial host towards increasing biofuel concentrations.

RESULTS

Here, we demonstrate that the ethanol tolerance of Zymomonas mobilis can be greatly enhanced through the random mutagenesis of global transcription factor RpoD protein, (σ(70)). Using an enrichment screening, four mutants with elevated ethanol tolerance were isolated from error-prone PCR libraries. All mutants showed significant growth improvement in the presence of ethanol stress when compared to the control strain. After an ethanol (9 %) stress exposure lasting 22 h, the rate of glucose consumption was approximately 1.77, 1.78 and 1.39 g L(-1) h(-1) in the best ethanol-tolerant strain ZM4-mrpoD4, its rebuilt mutant strain ZM4-imrpoD and the control strain, respectively. Our results indicated that both ZM4-mrpoD4 and ZM4-imrpoD consumed glucose at a faster rate after the initial 9 % (v/v) ethanol stress, as nearly 0.64 % of the initial glucose remained after 54 h incubation versus approximately 5.43 % for the control strain. At 9 % ethanol stress, the net ethanol productions by ZM4-mrpoD4 and ZM4-imrpoD during the 30-54 h were 13.0-14.1 g/l versus only 6.6-7.7 g/l for the control strain. The pyruvate decarboxylase activity of ZM4-mrpoD4 was 62.23 and 68.42 U/g at 24 and 48 h, respectively, which were 2.6 and 1.6 times higher than the control strain. After 24 and 48 h of 9 % ethanol stress, the alcohol dehydrogenase activities of ZM4-mrpoD4 were also augmented, showing an approximate 1.4 and 1.3 times increase, respectively, when compared to the control strain. Subsequent quantitative real-time PCR analysis under these stress conditions revealed that the relative expression of pdc in cultured (6 and 24 h) ZM4-mrpoD4 increased by 9.0- and 12.7-fold when compared to control strain.

CONCLUSIONS

Collectively, these results demonstrate that the RpoD mutation can enhance ethanol tolerance in Z. mobilis. Our results also suggested that RpoD may play an important role in resisting high ethanol concentration in Z. mobilis and manipulating RpoD via global transcription machinery engineering (gTME) can provide an alternative and useful approach for strain improvement for complex phenotypes.

DNA microarray of global transcription factor mutant reveals membrane-related proteins involved in n-butanol tolerance in Escherichia coli

BACKGROUND

Escherichia coli has been explored as a platform host strain for biofuels production such as butanol. However, the severe toxicity of butanol is considered to be one major limitation for butanol production from E. coli. The goal of this study is therefore to construct butanol-tolerant E. coli strains and clarify the tolerance mechanisms.

RESULTS

A recombinant E. coli strain harboring σ(70) mutation capable of tolerating 2 % (v/v) butanol was isolated by the global transcription machinery engineering (gTME) approach. DNA microarrays were employed to assess the transcriptome profile of butanol-tolerant strain B8. Compared with the wild-type strain, 329 differentially expressed genes (197 up-regulated and 132 down-regulated) (p < 0.05; FC ≥ 2) were identified. These genes are involved in carbohydrate metabolism, energy metabolism, two-component signal transduction system, oxidative stress response, lipid and cell envelope biogenesis and efflux pump.

CONCLUSIONS

Several membrane-related proteins were proved to be involved in butanol tolerance of E. coli. Two down-regulated genes, yibT and yghW, were identified to be capable of affecting butanol tolerance by regulating membrane fatty acid composition. Another down-regulated gene ybjC encodes a predicted inner membrane protein. In addition, a number of up-regulated genes, such as gcl and glcF, contribute to supplement metabolic intermediates for glyoxylate and TCA cycles to enhance energy supply. Our results could serve as a practical strategy for the construction of platform E. coli strains as biofuel producer.

Origins of Cell-to-Cell Bioprocessing Diversity and Implications of the Extracellular Environment Revealed at the Single-Cell Level

Bioprocess limitations imposed by microbial cell-to-cell phenotypic diversity remain poorly understood. To address this, we investigated the origins of such culture diversity during lipid production and assessed the impact of the fermentation microenvironment. We measured the single-cell lipid production dynamics in a time-invariant microfluidic environment and discovered that production is not monotonic, but rather sporadic with time. To characterize this, we introduce bioprocessing noise and identify its epigenetic origins. We linked such intracellular production fluctuations with cell-to-cell productivity diversity in culture. This unmasked the phenotypic diversity amplification by the culture microenvironment, a critical parameter in strain engineering as well as metabolic disease treatment.

Significantly improved solvent tolerance of Escherichia coli by global transcription machinery engineering

BACKGROUND

Escherichia coli has emerged as a promising platform microorganism to produce biofuels and fine chemicals of industrial interests. Certain obstacles however remain to be overcome, among which organic-solvent tolerance is a crucial one.

RESULTS

We used global transcription machinery engineering (gTME) to improve the organic-solvent tolerance (OST) of E. coli JM109. A mutant library of σ(70) encoded by rpoD was screened under cyclohexane pressure. E. coli JM109 strain harboring σ(70) mutant C9 was identified with capability of tolerating 69 % cyclohexane. The rpoD mutant contains three amino-acid substitutes and a stop-codon mutation, resulting a truncated sequence containing regions σ(1.1) and σ(1.2). Total protein difference produced by E. coli JM109 strain harboring C9 was examined with 2D-PAGE, and 204 high-abundant proteins showed over twofold variation under different solvent stress.

CONCLUSIONS

Our results show that several genes (gapA, sdhB, pepB and dppA) play critical roles in enhanced solvent tolerance of E. coli, mainly involving in maintaining higher intracellular energy level under solvent stress. Global transcription machinery engineering is therefore a feasible and efficient approach for engineering strain with enhanced OST-phenotype.

Improving furfural tolerance of Zymomonas mobilis by rewiring a sigma factor RpoD protein

Furfural from lignocellulosic hydrolysates is the key inhibitor for bio-ethanol fermentation. In this study, we report a strategy of improving the furfural tolerance in Zymomonas mobilis on the transcriptional level by engineering its global transcription sigma factor (σ(70), RpoD) protein. Three furfural tolerance RpoD mutants (ZM4-MF1, ZM4-MF2, and ZM4-MF3) were identified from error-prone PCR libraries. The best furfural-tolerance strain ZM4-MF2 reached to the maximal cell density (OD600) about 2.0 after approximately 30 h, while control strain ZM4-rpoD reached its highest cell density of about 1.3 under the same conditions. ZM4-MF2 also consumed glucose faster and yield higher ethanol; expression levels and key Entner-Doudoroff (ED) pathway enzymatic activities were also compared to control strain under furfural stress condition. Our results suggest that global transcription machinery engineering could potentially be used to improve stress tolerance and ethanol production in Z. mobilis.

Rapid prototyping of microbial cell factories via genome-scale engineering

Advances in reading, writing and editing genetic materials have greatly expanded our ability to reprogram biological systems at the resolution of a single nucleotide and on the scale of a whole genome. Such capacity has greatly accelerated the cycles of design, build and test to engineer microbes for efficient synthesis of fuels, chemicals and drugs. In this review, we summarize the emerging technologies that have been applied, or are potentially useful for genome-scale engineering in microbial systems. We will focus on the development of high-throughput methodologies, which may accelerate the prototyping of microbial cell factories.

Bacterial sigma factors as targets for engineered or synthetic transcriptional control

Sigma (σ) factors are the predominant constituents of transcription regulation in bacteria. σ Factors recruit the core RNA polymerase to recognize promoters with specific DNA sequences. Recently, engineering of transcriptional regulators has become a significant tool for strain engineering. The present review summarizes the recent advances in σ factor based engineering or synthetic design. The manipulation of σ factors presents insights into the bacterial stress tolerance and metabolite productivity. We envision more synthetic design based on σ factors that can be used to tune the regulatory network of bacteria.

Rational selection and engineering of exogenous principal sigma factor (σ(HrdB)) to increase teicoplanin production in an industrial strain of Actinoplanes teichomyceticus

Background

Transcriptional engineering has presented a strong ability of phenotypic improvement in microorganisms. However, it could not be directly applied to Actinoplanes teichomyceticus L-27 because of the paucity of endogenous transcription factors in the strain. In this study, exogenous transcription factors were rationally selected and transcriptional engineering was carried out to increase the productivity of teicoplanin in L-27.

Results

It was illuminated that the σ^HrdB molecules shared strong similarity of amino acid sequences among some genera of actinomycetes. Combining this advantage with the ability of transcriptional engineering, exogenous sigma factor σ^HrdB molecules were rationally selected and engineered to improve L-27. hrdB genes from Actinoplanes missouriensis 431, Micromonospora aurantiaca ATCC 27029 and Salinispora arenicola CNS-205 were selected based on molecular evolutionary analysis. Random mutagenesis, DNA shuffling and point mutation were subsequently performed to generate diversified mutants. A recombinant was identified through screening program, yielding 5.3 mg/ml of teicoplanin, over 2-fold compared to that of L-27. More significantly, the engineered strain presented a good performance in 500-l pilot scale fermentation, which meant its valuable potential application in industry.

Conclusions

Through rational selection and engineering of exogenous transcriptional factor, we have extended the application of transcriptional engineering. To our knowledge, it is the first time to focus on the related issue. In addition, possessing the advantage of efficient metabolic perturbation in transcription level, this strategy could be useful in analyzing metabolic and physiological mechanisms of strains, especially those with the only information on taxonomy.

Strategies for the multiplex mapping of genes to traits

Rewiring and optimization of metabolic networks to enable the production of commercially valuable chemicals is a central goal of metabolic engineering. This prospect is challenged by the complexity of metabolic networks, lack of complete knowledge of gene function(s), and the vast combinatorial genotype space that is available for exploration and optimization. Various approaches have thus been developed to aid in the efficient identification of genes that contribute to a variety of different phenotypes, allowing more rapid design and engineering of traits desired for industrial applications. This review will highlight recent technologies that have enhanced capabilities to map genotype-phenotype relationships on a genome wide scale and emphasize how such approaches enable more efficient design and engineering of complex phenotypes.

Expanding the metabolic engineering toolbox with directed evolution

Cellular systems can be engineered into factories that produce high-value chemicals from renewable feedstock. Such an approach requires an expanded toolbox for metabolic engineering. Recently, protein engineering and directed evolution strategies have started to play a growing and critical role within metabolic engineering. This review focuses on the various ways in which directed evolution can be applied in conjunction with metabolic engineering to improve product yields. Specifically, we discuss the application of directed evolution on both catalytic and non-catalytic traits of enzymes, on regulatory elements, and on whole genomes in a metabolic engineering context. We demonstrate how the goals of metabolic pathway engineering can be achieved in part through evolving cellular parts as opposed to traditional approaches that rely on gene overexpression and deletion. Finally, we discuss the current limitations in screening technology that hinder the full implementation of a metabolic pathway-directed evolution approach.

Protein engineering for metabolic engineering: current and next-generation tools

Protein engineering in the context of metabolic engineering is increasingly important to the field of industrial biotechnology. As the demand for biologically produced food, fuels, chemicals, food additives, and pharmaceuticals continues to grow, the ability to design and modify proteins to accomplish new functions will be required to meet the high productivity demands for the metabolism of engineered organisms. We review advances in selecting, modeling, and engineering proteins to improve or alter their activity. Some of the methods have only recently been developed for general use and are just beginning to find greater application in the metabolic engineering community. We also discuss methods of generating random and targeted diversity in proteins to generate mutant libraries for analysis. Recent uses of these techniques to alter cofactor use; produce non-natural amino acids, alcohols, and carboxylic acids; and alter organism phenotypes are presented and discussed as examples of the successful engineering of proteins for metabolic engineering purposes.

Combinatorial approaches for inverse metabolic engineering applications

Traditional metabolic engineering analyzes biosynthetic and physiological pathways, identifies bottlenecks, and makes targeted genetic modifications with the ultimate goal of increasing the production of high-value products in living cells. Such efforts have led to the development of a variety of organisms with industrially relevant properties. However, there are a number of cellular phenotypes important for research and the industry for which the rational selection of cellular targets for modification is not easy or possible. In these cases, strain engineering can be alternatively carried out using “inverse metabolic engineering”, an approach that first generates genetic diversity by subjecting a population of cells to a particular mutagenic process, and then utilizes genetic screens or selections to identify the clones exhibiting the desired phenotype. Given the availability of an appropriate screen for a particular property, the success of inverse metabolic engineering efforts usually depends on the level and quality of genetic diversity which can be generated. Here, we review classic and recently developed combinatorial approaches for creating such genetic diversity and discuss the use of these methodologies in inverse metabolic engineering applications.

Targeted metabolic engineering guided by computational analysis of single-nucleotide polymorphisms (SNPs)

The non-synonymous SNPs, the so-called non-silent SNPs, which are single-nucleotide variations in the coding regions that give "birth" to amino acid mutations, are often involved in the modulation of protein function. Understanding the effect of individual amino acid mutations on a protein/enzyme function or stability is useful for altering its properties for a wide variety of engineering studies. Since measuring the effects of amino acid mutations experimentally is a laborious process, a variety of computational methods have been discussed here that aid to extract direct genotype to phenotype information.

"Direct cloning in Lactobacillus plantarum: electroporation with non-methylated plasmid DNA enhances transformation efficiency and makes shuttle vectors obsolete"

Background

Lactic acid bacteria (LAB) play an important role in agricultural as well as industrial biotechnology. Development of improved LAB strains using e.g. library approaches is often limited by low transformation efficiencies wherefore one reason could be differences in the DNA methylation patterns between the Escherichia coli intermediate host for plasmid amplification and the final LAB host. In the present study, we examined the influence of DNA methylation on transformation efficiency in LAB and developed a direct cloning approach for Lactobacillus plantarum CD033. Therefore, we propagated plasmid pCD256 in E. coli strains with different dam/dcm-methylation properties. The obtained plasmid DNA was purified and transformed into three different L. plantarum strains and a selection of other LAB species.

Results

Best transformation efficiencies were obtained using the strain L. plantarum CD033 and non-methylated plasmid DNA. Thereby we achieved transformation efficiencies of ~ 10⁹ colony forming units/μg DNA in L. plantarum CD033 which is in the range of transformation efficiencies reached with E. coli. Based on these results, we directly transformed recombinant expression vectors received from PCR/ligation reactions into L. plantarum CD033, omitting plasmid amplification in E. coli. Also this approach was successful and yielded a sufficient number of recombinant clones.

Conclusions

Transformation efficiency of L. plantarum CD033 was drastically increased when non-methylated plasmid DNA was used, providing the possibility to generate expression libraries in this organism. A direct cloning approach, whereby ligated PCR-products where successfully transformed directly into L. plantarum CD033, obviates the construction of shuttle vectors containing E. coli-specific sequences, as e.g. a ColEI origin of replication, and makes amplification of these vectors in E. coli obsolete. Thus, plasmid constructs become much smaller and occasional structural instability or mutagenesis during E. coli propagation is excluded. The results of our study provide new genetic tools for L. plantarum which will allow fast, forward and systems based genetic engineering of this species.

Synthetic biology: an emerging engineering discipline

Over the past decade, synthetic biology has emerged as an engineering discipline for biological systems. Compared with other substrates, biology poses a unique set of engineering challenges resulting from an incomplete understanding of natural biological systems and tools for manipulating them. To address these challenges, synthetic biology is advancing from developing proof-of-concept designs to focusing on core platforms for rational and high-throughput biological engineering. These platforms span the entire biological design cycle, including DNA construction, parts libraries, computational design tools, and interfaces for manipulating and probing synthetic circuits. The development of these enabling technologies requires an engineering mindset to be applied to biology, with an emphasis on generalizable techniques in addition to application-specific designs. This review aims to discuss the progress and challenges in synthetic biology and to illustrate areas where synthetic biology may impact biomedical engineering and human health.

Oxytetracycline biosynthesis improvement in Streptomyces rimosus following duplication of minimal PKS genes

Oxytetracycline (OTC) is a widely used antibiotic, which is commercially produced by Streptomyces rimosus. The type II minimal polyketide synthases (minimal PKS) genes of the oxytetracycline biosynthesis cluster in S. rimosus, consisting of oxyA, oxyB and oxyC, are involved in catalyzing 19-C chain building by the condensation of eight malonyl-CoA groups to form the starting polyketide. This study aimed to investigate the effects of overexpression of the minimal PKS gene in a model S. rimosus strain (M4018) and in an industrial overproducer (SR16) by introduction of a second copy of the gene into the chromosome. Increased levels of oxyA, oxyB and oxyC gene transcription were monitored using reverse transcription quantitative real-time PCR. Overexpression of the minimal PKS gene elicited retardation of cell growth and a significant improvement in OTC production in corresponding mutants (approximately 51.2% and 32.9% in M4018 and SR16 mutants respectively). These data indicate that the minimal PKS plays an important role in carbon flux redirection from cell growth pathways to OTC biosynthesis pathways.

Using transcription machinery engineering to elicit complex cellular phenotypes

Cellular hosts are widely used for the production of chemical compounds, including pharmaceutics, fuels, and specialty chemicals. However, common metabolic engineering techniques are limited in their capacity to elicit multigenic, complex phenotypes. These phenotypes can include non-pathway-based traits, such as tolerance and productivity. Global transcription machinery engineering (gTME) is a generic methodology for eliciting these complex cellular phenotypes. In gTME, dominant mutant alleles of a transcription-related protein are screened for their ability to reprogram cellular metabolism and regulation, resulting in a unique and desired phenotype. gTME has been successfully applied to both prokaryotic and eukaryotic systems, resulting in improved environmental tolerances, metabolite production, and substrate utilization. The underlying principle involves creating mutant libraries of transcription factors, screening for a desired phenotype, and iterating the process in a directed evolution fashion. The successes of this approach and details for its implementation and application are described here.

Strain engineering for improved expression of recombinant proteins in bacteria

Protein expression in Escherichia coli represents the most facile approach for the preparation of non-glycosylated proteins for analytical and preparative purposes. So far, the optimization of recombinant expression has largely remained a matter of trial and error and has relied upon varying parameters, such as expression vector, media composition, growth temperature and chaperone co-expression. Recently several new approaches for the genome-scale engineering of E. coli to enhance recombinant protein expression have been developed. These methodologies now enable the generation of optimized E. coli expression strains in a manner analogous to metabolic engineering for the synthesis of low-molecular-weight compounds. In this review, we provide an overview of strain engineering approaches useful for enhancing the expression of hard-to-produce proteins, including heterologous membrane proteins.

From Pathways to Genomes and Beyond: The Metabolic Engineering Toolbox and Its Place in Biofuels Production

Concerns about the availability of petroleum-derived fuels and chemicals have led to the exploration of metabolically engineered organisms as novel hosts for biofuels and chemicals production. However, the complexity inherent in metabolic and regulatory networks makes this undertaking a complex task. To address these limitations, metabolic engineering has adapted a wide-variety of tools for altering phenotypes. In this review, we will highlight traditional and recent metabolic engineering tools for optimizing cells including pathway-based, global, and genomics enabled approaches. Specifically, we describe these tools as well as provide demonstrations of their effectiveness in optimizing biofuels production. However, each of these tools provides stepping stones towards the grand goal of biofuels production. Thus, developing methods for largescale cellular optimization and integrative approaches are invaluable for further cell optimization. This review highlights the challenges that still must be met to accomplish this goal.

Global strain engineering by mutant transcription factors

Cellular hosts are widely used for the production of chemical compounds including pharmaceutics, fuels, and specialty chemicals. Strain engineering focuses on manipulating and improving these hosts for new and enhanced functionalities including increased titers and better bioreactor performance. These tasks have traditionally been accomplished using a combination of random mutation, screening and selection, and metabolic engineering. However, common metabolic engineering techniques are limited in their capacity to elicit multigenic, complex phenotypes. These phenotypes can also include nonpathway-based traits such as tolerance and productivity. Global transcription machinery engineering (gTME) is a generic methodology for engineering strains with these complex cellular phenotypes. In gTME, dominant mutant alleles of a transcription-related protein are screened for their ability to reprogram cellular metabolism and regulation, resulting in a unique and desired phenotype. gTME has been successfully applied to both prokaryotic and eukaryotic systems, resulting in improved environmental tolerances, metabolite production, and substrate utilization. The underlying principle involves creating mutant libraries of transcription factors, screening for a desired phenotype, and iterating the process in a directed evolution fashion. The successes of this approach and details for its implementation and application are described here.

Method for designing and optimizing random-search libraries for strain improvement

Random searches have been the hallmark of directed evolution and have been extensively employed in the improvement of complex or poorly understood phenotypes such as tolerance to toxic compounds in the context of cellular engineering. While genome-wide mutagenesis followed by selection or screening has been a traditional means of phenotype improvement, the list of experimental methods for cellular engineering based on random searches is rapidly expanding. Adding to the confusion is the element of chance, which lengthens the process and most notably adds to the cost of phenotypic improvement programs. Here we present a method to systematize the effort of finding superior mutants by successively improving random libraries. The method, based on the quantification of phenotypic diversity, is then used to isolate more-robust strains.

Assessing the potential of an induced-mutation strategy for avermectin overproducers

Mutant libraries of avermectin-producing Streptomyces avermitilis strains were constructed by different mutagenesis strategies. A metric was applied to assess the mutation spectrum by calculating the distribution of average phenotypic distance of each population. The results showed for the first time that a microgravity environment could introduce larger phenotype distribution and diversity than UV and N-methyl-N-nitro-N-nitrosoguanidine (NTG) could.

Enhancing stress resistance and production phenotypes through transcriptome engineering

As Saccharomyces cerevisiae is engineered further as a microbial factory for industrially relevant but potentially cytotoxic molecules such as ethanol, issues of cell viability arise that threaten to place a biological limit on output capacity and/or the use of less refined production conditions. Evidence suggests that one naturally evolved mode of survival in deleterious environments involves the complex, multigenic interplay between disparate stress response and homeostasis mechanisms. Rational engineering of such resistance would require a systems-level understanding of cellular behavior that is, in general, not yet available. To circumvent this limitation, we have developed a phenotype discovery approach termed global transcription machinery engineering (gTME) that allows for the generation and selection of nonphysiological traits. We alter gene expression on a genome-wide scale by selecting for dominant mutations in a randomly mutagenized general transcription factor. The gene encoding the mutated transcription factor resides on a plasmid in a strain carrying the unaltered chromosomal allele. Thus, although the dominant mutations may destroy the essential function of the plasmid-borne variant, alteration of the transcriptome with minimal perturbation to normal cellular processes is possible via the presence of the native genomic allele. Achieving a phenotype of interest involves the construction and diversity evaluation of yeast libraries harboring random sequence variants of a chosen transcription factor and the subsequent selection and validation of mutant strains. We describe the rationale and procedures associated with each step in the context of generating strains possessing enhanced ethanol tolerance.