Genomics enabled approaches in strain engineering

Recent progress in adaptive laboratory evolution of industrial microorganisms

Adaptive laboratory evolution (ALE) is a technique for the selection of strains with better phenotypes by long-term culture under a specific selection pressure or growth environment. Because ALE does not require detailed knowledge of a variety of complex and interactive metabolic networks, and only needs to simulate natural environmental conditions in the laboratory to design a selection pressure, it has the advantages of broad adaptability, strong practicability, and more convenient transformation of strains. In addition, ALE provides a powerful method for studying the evolutionary forces that change the phenotype, performance, and stability of strains, resulting in more productive industrial strains with beneficial mutations. In recent years, ALE has been widely used in the activation of specific microbial metabolic pathways and phenotypic optimization, the efficient utilization of specific substrates, the optimization of tolerance to toxic substance, and the biosynthesis of target products, which is more conducive to the production of industrial strains with excellent phenotypic characteristics. In this paper, typical examples of ALE applications in the development of industrial strains and the research progress of this technology are reviewed, followed by a discussion of its development prospects.

Tolerance against butanol stress by disrupting succinylglutamate desuccinylase inEscherichia coli

The four-carbon alcohol, butanol, is emerging as a promising biofuel and efforts have been undertaken to improve several microbial hosts for its production.

Engineered global regulator H-NS improves the acid tolerance of E. coli

Background

Acid stress is often encountered during industrial fermentation as a result of the accumulation of acidic metabolites. Acid stress increases the intracellular acidity and can cause DNA damage and denaturation of essential enzymes, thus leading to a decrease of growth and fermentation yields. Although acid stress can be relieved by addition of a base to the medium, fermentations with acid-tolerant strains are generally considered much more efficient and cost-effective.

Results

In this study, the global regulator H-NS was found to have significant influence on the acid tolerance of E. coli. The final OD₆₀₀ of strains overexpressing H-NS increased by 24% compared to control, when cultured for 24 h at pH 4.5 using HCl as an acid agent. To further improve the acid tolerance, a library of H-NS was constructed by error-prone PCR and subjected to selection. Five mutants that conferred a significant growth advantage compared to the control strain were obtained. The final OD₆₀₀ of strains harboring the five H-NS mutants was enhanced by 26–53%, and their survival rate was increased by 10- to 100-fold at pH 2.5. Further investigation showed that the improved acid tolerance of H-NS mutants coincides with the activation of multiple acid resistance mechanisms, in particular the glutamate- and glutamine-dependent acid resistance system (AR2). The improved acid tolerance of H-NS mutants was also demonstrated in media acidified by acetic acid and succinic acid, which are common acidic fermentation by-products or products.

Conclusions

The results obtained in this work demonstrate that the engineering of H-NS can enhance the acid tolerance of E. coli. More in general, this study shows the potential of the engineering of global regulators acting as repressors, such as H-NS, as a promising method to obtain phenotypes of interest. This approach could expand the spectrum of application of global transcription machinery engineering.

Electronic supplementary material

The online version of this article (10.1186/s12934-018-0966-z) contains supplementary material, which is available to authorized users.

High precision genome sequencing of engineered Gluconobacter oxydans 621H by combining long nanopore and short accurate Illumina reads

State of the art and novel high-throughput DNA sequencing technologies enable fascinating opportunities and applications in the life sciences including microbial genomics. Short high-quality read data already enable not only microbial genome sequencing, yet can be inadequately to solve problems in genome assemblies and for the analysis of structural variants, especially in engineered microbial cell factories. Single-molecule real-time sequencing technologies generating long reads promise to solve such assembly problems. In our study, we wanted to increase the average read length of long nanopore reads with R9 chemistry and conducted a hybrid approach for the analysis of structural variants to check the genome stability of a recombinant Gluconobacter oxydans 621H strain (IK003.1) engineered for improved growth. Therefore we combined accurate Illumina sequencing technology and low-cost single-molecule nanopore sequencing using the MinION^® device from Oxford Nanopore. In our hybrid approach with a modified library protocol we could increase the average size of nanopore 2D reads to about 18.9kb. Combining the long MinION nanopore reads with the high quality short Illumina reads enabled the assembly of the engineered chromosome into a single contig and comprehensive detection and clarification of 7 structural variants including all three known genetically engineered modifications. We found the genome of IK003.1 was stable over 70 generations of strain handling including 28h of process time in a bioreactor. The long read data revealed a novel 1420 bp transposon-flanked and ORF-containing sequence which was hitherto unknown in the G. oxydans 621H reference. Further analysis and genome sequencing showed that this region is already present in G. oxydans 621H wild-type strains. Our data of G. oxydans 621H wild-type DNA from different resources also revealed in 73 annotated coding sequences about 91 uniform nucleotide differences including InDels. Together, our results contribute to an improved high quality genome reference for G. oxydans 621H which is available via ENA accession PRJEB18739.

White biotechnology: State of the art strategies for the development of biocatalysts for biorefining

White biotechnology is a term that is now often used to describe the implementation of biotechnology in the industrial sphere. Biocatalysts (enzymes and microorganisms) are the key tools of white biotechnology, which is considered to be one of the key technological drivers for the growing bioeconomy. Biocatalysts are already present in sectors such as the chemical and agro-food industries, and are used to manufacture products as diverse as antibiotics, paper pulp, bread or advanced polymers. This review proposes an original and global overview of highly complementary fields of biotechnology at both enzyme and microorganism level. A certain number of state of the art approaches that are now being used to improve the industrial fitness of biocatalysts particularly focused on the biorefinery sector are presented. The first part deals with the technologies that underpin the development of industrial biocatalysts, notably the discovery of new enzymes and enzyme improvement using directed evolution techniques. The second part describes the toolbox available by the cell engineer to shape the metabolism of microorganisms. And finally the last part focuses on the 'omic' technologies that are vital for understanding and guide microbial engineering toward more efficient microbial biocatalysts. Altogether, these techniques and strategies will undoubtedly help to achieve the challenging task of developing consolidated bioprocessing (i.e. CBP) readily available for industrial purpose.

Improving a recombinant Zymomonas mobilis strain 8b through continuous adaptation on dilute acid pretreated corn stover hydrolysate

BACKGROUND

Complete conversion of the major sugars of biomass including both the C5 and C6 sugars is critical for biofuel production processes. Several inhibitory compounds like acetate, hydroxymethylfurfural (HMF), and furfural are produced from the biomass pretreatment process leading to 'hydrolysate toxicity,' a major problem for microorganisms to achieve complete sugar utilization. Therefore, development of more robust microorganisms to utilize the sugars released from biomass under toxic environment is critical. In this study, we use continuous culture methodologies to evolve and adapt the ethanologenic bacterium Zymomonas mobilis to improve its ethanol productivity using corn stover hydrolysate.

RESULTS

A turbidostat was used to adapt the Z. mobilis strain 8b in the pretreated corn stover liquor. The adaptation was initiated using pure sugar (glucose and xylose) followed by feeding neutralized liquor at different dilution rates. Once the turbidostat reached 60% liquor content, the cells began washing out and the adaptation was stopped. Several 'sub-strains' were isolated, and one of them, SS3 (sub-strain 3), had 59% higher xylose utilization than the parent strain 8b when evaluated on 55% neutralized PCS (pretreated corn stover) liquor. Using saccharified PCS slurry generated by enzymatic hydrolysis from 25% solids loading, SS3 generated an ethanol yield of 75.5% compared to 64% for parent strain 8b. Furthermore, the total xylose utilization was 57.7% for SS3 versus 27.4% for strain 8b. To determine the underlying genotypes in these new sub-strains, we conducted genomic resequencing and identified numerous single-nucleotide mutations (SNPs) that had arisen in SS3. We further performed quantitative reverse transcription PCR (qRT-PCR) on genes potentially affected by these SNPs and identified significant down-regulation of two genes, ZMO0153 and ZMO0776, in SS3 suggesting potential genetic mechanisms behind SS3's improved performance.

CONCLUSION

We have adapted/evolved Z. mobilis strain 8b for enhanced tolerance to the toxic compounds present in corn stover hydrolysates. The adapted strain SS3 has higher xylose utilization rate and produce more ethanol than the parent strain. We have identified transcriptional changes which may be responsible for these phenotypes, providing foundations for future research directions in improving Z. mobilis as biocatalysts for the production of ethanol or other fuel precursors.

Evolutionary engineering of yeast

Evolutionary engineering is an inverse metabolic engineering strategy which is based on increasing genetic diversity and screening large populations for desired phenotypes. This strategy is highly advantageous in certain situations over rational metabolic engineering approaches, since there is little or no requirement of detailed genetic background information for the trait of interest. Here, we describe the experimental methodology for selecting stress-resistant yeast strains via evolutionary engineering approach by either serial batch or chemostat cultivations.

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.

Analyzing the genomic variation of microbial cell factories in the era of "New Biotechnology"

The application of genome-scale technologies, both experimental and in silico, to industrial biotechnology has allowed improving the conversion of biomass-derived feedstocks to chemicals, materials and fuels through microbial fermentation. In particular, due to rapidly decreasing costs and its suitability for identifying the genetic determinants of a phenotypic trait of interest, whole genome sequencing is expected to be one of the major driving forces in industrial biotechnology in the coming years. We present some of the recent studies that have successfully applied high-throughput sequencing technologies for finding the underlying molecular mechanisms for (a) improved carbon source utilization, (b) increased product formation, and (c) stress tolerance. We also discuss the strengths and weaknesses of different strategies for mapping industrially relevant genotype-to-phenotype links including exploiting natural diversity in natural isolates or crosses between isolates, classical mutagenesis and evolutionary engineering.

Recovery of phenotypes obtained by adaptive evolution through inverse metabolic engineering

In a previous study, system level analysis of adaptively evolved yeast mutants showing improved galactose utilization revealed relevant mutations. The governing mutations were suggested to be in the Ras/PKA signaling pathway and ergosterol metabolism. Here, site-directed mutants having one of the mutations RAS2(Lys77), RAS2(Tyr112), and ERG5(Pro370) were constructed and evaluated. The mutants were also combined with overexpression of PGM2, earlier proved as a beneficial target for galactose utilization. The constructed strains were analyzed for their gross phenotype, transcriptome and targeted metabolites, and the results were compared to those obtained from reference strains and the evolved strains. The RAS2(Lys77) mutation resulted in the highest specific galactose uptake rate among all of the strains with an increased maximum specific growth rate on galactose. The RAS2(Tyr112) mutation also improved the specific galactose uptake rate and also resulted in many transcriptional changes, including ergosterol metabolism. The ERG5(Pro370) mutation only showed a small improvement, but when it was combined with PGM2 overexpression, the phenotype was almost the same as that of the evolved mutants. Combination of the RAS2 mutations with PGM2 overexpression also led to a complete recovery of the adaptive phenotype in galactose utilization. Recovery of the gross phenotype by the reconstructed mutants was achieved with much fewer changes in the genome and transcriptome than for the evolved mutants. Our study demonstrates how the identification of specific mutations by systems biology can direct new metabolic engineering strategies for improving galactose utilization by yeast.

Genome shuffling of Streptomyces gilvosporeus for improving natamycin production

Improvement of natamycin production by Streptomyces gilvosporeus ATCC 13326 was performed by recursive protoplast fusion in a genome-shuffling format. After four rounds of genome shuffling, the best producer, GS 4-21, with genetic stability was obtained and its production of natamycin reached 4.69 ± 0.05 g/L in shaking flask after 96 h cultivation, which was increased by 97.1% and 379% in comparison with the highest parental strain pop-72A(r)07 and the initial strain ATCC 13326, respectively. Compared with the initial strain ATCC 13326, the recombinant GS 4-21 presented higher polymorphism. Fifty-four proteins showed differential expression levels between the recombinant GS 4-21 and initial strain ATCC 13326. Of these proteins, 34 proteins were upregulated and 20 proteins were downregulated. Of the upregulated proteins, one protein, glucokinase regulatory protein, was involved in natamycin biosynthesis. This comprehensive analysis would provide useful information for understanding the natamycin metabolic pathway in S. gilvosporeus.

Genomics in mammalian cell culture bioprocessing

Explicitly identifying the genome of a host organism including sequencing, mapping, and annotating its genetic code has become a priority in the field of biotechnology with aims at improving the efficiency and understanding of cell culture bioprocessing. Recombinant protein therapeutics, primarily produced in mammalian cells, constitute a $108 billion global market. The most common mammalian cell line used in biologic production processes is the Chinese hamster ovary (CHO) cell line, and although great improvements have been made in titer production over the past 25 years, the underlying molecular and physiological factors are not well understood. Confident understanding of CHO bioprocessing elements (e.g. cell line selection, protein production, and reproducibility of process performance and product specifications) would significantly improve with a well understood genome. This review describes mammalian cell culture use in bioprocessing, the importance of obtaining CHO cell line genetic sequences, and the current status of sequencing efforts. Furthermore, transcriptomic techniques and gene expression tools are presented, and case studies exploring genomic techniques and applications aimed to improve mammalian bioprocess performance are reviewed. Finally, future implications of genomic advances are surmised.

Isolation of improved free fatty acid overproducing strains of Escherichia coli via Nile red based high-throughput screening

Biological production of hydrocarbons is an attractive strategy to produce drop-in replacement transportation fuels. Several methods for converting microbially-produced fatty acids into reduced compounds compatible with petrodiesel have been reported. For these processes to become economically viable, microorganisms must be engineered to approach the theoretical yield of fatty acid products from renewable feedstocks such as glucose. Strains with increased titers can be obtained through both rational and random approaches. While powerful, random approaches require a genetic selection or facile screen that is amenable to high throughput platforms. Here, we present the use of a high throughput screen for fatty acids based on the hydrophobic dye Nile red. The method was applied to screening a transposon library of a free fatty acid overproducing strain of Escherichia coli in search of high producing mutants. Ten gene targets were identified via primary and secondary screening. A strain comprising a clean knockout of one of the identified genes led to a 20% increase in titer over the baseline strain. A selection strategy that combines these findings and can act in an iterative fashion has been developed and can be used for future strain optimization in hydrocarbon producing strains.

Engineering microbes for tolerance to next-generation biofuels

A major challenge when using microorganisms to produce bulk chemicals such as biofuels is that the production targets are often toxic to cells. Many biofuels are known to reduce cell viability through damage to the cell membrane and interference with essential physiological processes. Therefore, cells must trade off biofuel production and survival, reducing potential yields. Recently, there have been several efforts towards engineering strains for biofuel tolerance. Promising methods include engineering biofuel export systems, heat shock proteins, membrane modifications, more general stress responses, and approaches that integrate multiple tolerance strategies. In addition, in situ recovery methods and media supplements can help to ease the burden of end-product toxicity and may be used in combination with genetic approaches. Recent advances in systems and synthetic biology provide a framework for tolerance engineering. This review highlights recent targeted approaches towards improving microbial tolerance to next-generation biofuels with a particular emphasis on strategies that will improve production.

Evolution combined with genomic study elucidates genetic bases of isobutanol tolerance in Escherichia coli

Background

Isobutanol is a promising next-generation biofuel with demonstrated high yield microbial production, but the toxicity of this molecule reduces fermentation volumetric productivity and final titer. Organic solvent tolerance is a complex, multigenic phenotype that has been recalcitrant to rational engineering approaches. We apply experimental evolution followed by genome resequencing and a gene expression study to elucidate genetic bases of adaptation to exogenous isobutanol stress.

Results

The adaptations acquired in our evolved lineages exhibit antagonistic pleiotropy between minimal and rich medium, and appear to be specific to the effects of longer chain alcohols. By examining genotypic adaptation in multiple independent lineages, we find evidence of parallel evolution in marC, hfq, mdh, acrAB, gatYZABCD, and rph genes. Many isobutanol tolerant lineages show reduced RpoS activity, perhaps related to mutations in hfq or acrAB. Consistent with the complex, multigenic nature of solvent tolerance, we observe adaptations in a diversity of cellular processes. Many adaptations appear to involve epistasis between different mutations, implying a rugged fitness landscape for isobutanol tolerance. We observe a trend of evolution targeting post-transcriptional regulation and high centrality nodes of biochemical networks. Collectively, the genotypic adaptations we observe suggest mechanisms of adaptation to isobutanol stress based on remodeling the cell envelope and surprisingly, stress response attenuation.

Conclusions

We have discovered a set of genotypic adaptations that confer increased tolerance to exogenous isobutanol stress. Our results are immediately useful to further efforts to engineer more isobutanol tolerant host strains of E. coli for isobutanol production. We suggest that rpoS and post-transcriptional regulators, such as hfq, RNA helicases, and sRNAs may be interesting mutagenesis targets for future global phenotype engineering.

Whole genome sequencing of Saccharomyces cerevisiae: from genotype to phenotype for improved metabolic engineering applications

BACKGROUND

The need for rapid and efficient microbial cell factory design and construction are possible through the enabling technology, metabolic engineering, which is now being facilitated by systems biology approaches. Metabolic engineering is often complimented by directed evolution, where selective pressure is applied to a partially genetically engineered strain to confer a desirable phenotype. The exact genetic modification or resulting genotype that leads to the improved phenotype is often not identified or understood to enable further metabolic engineering.

RESULTS

In this work we performed whole genome high-throughput sequencing and annotation can be used to identify single nucleotide polymorphisms (SNPs) between Saccharomyces cerevisiae strains S288c and CEN.PK113-7D. The yeast strain S288c was the first eukaryote sequenced, serving as the reference genome for the Saccharomyces Genome Database, while CEN.PK113-7D is a preferred laboratory strain for industrial biotechnology research. A total of 13,787 high-quality SNPs were detected between both strains (reference strain: S288c). Considering only metabolic genes (782 of 5,596 annotated genes), a total of 219 metabolism specific SNPs are distributed across 158 metabolic genes, with 85 of the SNPs being nonsynonymous (e.g., encoding amino acid modifications). Amongst metabolic SNPs detected, there was pathway enrichment in the galactose uptake pathway (GAL1, GAL10) and ergosterol biosynthetic pathway (ERG8, ERG9). Physiological characterization confirmed a strong deficiency in galactose uptake and metabolism in S288c compared to CEN.PK113-7D, and similarly, ergosterol content in CEN.PK113-7D was significantly higher in both glucose and galactose supplemented cultivations compared to S288c. Furthermore, DNA microarray profiling of S288c and CEN.PK113-7D in both glucose and galactose batch cultures did not provide a clear hypothesis for major phenotypes observed, suggesting that genotype to phenotype correlations are manifested post-transcriptionally or post-translationally either through protein concentration and/or function.

CONCLUSIONS

With an intensifying need for microbial cell factories that produce a wide array of target compounds, whole genome high-throughput sequencing and annotation for SNP detection can aid in better reducing and defining the metabolic landscape. This work demonstrates direct correlations between genotype and phenotype that provides clear and high-probability of success metabolic engineering targets. The genome sequence, annotation, and a SNP viewer of CEN.PK113-7D are deposited at http://www.sysbio.se/cenpk.

Elucidating acetate tolerance in E. coli using a genome-wide approach

Engineering organisms for improved performance using lignocellulose feedstocks is an important step towards a sustainable fuel and chemical industry. Cellulosic feedstocks contain carbon and energy in the form of cellulosic and hemicellulosic sugars that are not metabolized by most industrial microorganisms. Pretreatment processes that hydrolyze these polysaccharides often also result in the accumulation of growth inhibitory compounds, such as acetate and furfural among others. Here, we have applied a recently reported strategy for engineering tolerance towards the goal of increasing Escherichia coli growth in the presence of elevated acetate concentrations (Lynch et al., 2007). We performed growth selections upon an E. coli genome library developed using a moderate selection pressure to identify genomic regions implicated in acetate toxicity and tolerance. These studies identified a range of high-fitness genes that are normally involved in membrane and extracellular processes, are key regulated steps in pathways, and are involved in pathways that yield specific amino acids and nucleotides. Supplementation of the products and metabolically related metabolites of these pathways significantly increased growth rate (a 130% increase in specific growth) at inhibitory acetate concentrations. Our results suggest that acetate tolerance will not involve engineering of a single pathway; rather we observe a range of potential mechanisms for overcoming acetate based inhibition.

Toward engineering synthetic microbial metabolism

The generation of well-characterized parts and the formulation of biological design principles in synthetic biology are laying the foundation for more complex and advanced microbial metabolic engineering. Improvements in de novo DNA synthesis and codon-optimization alone are already contributing to the manufacturing of pathway enzymes with improved or novel function. Further development of analytical and computer-aided design tools should accelerate the forward engineering of precisely regulated synthetic pathways by providing a standard framework for the predictable design of biological systems from well-characterized parts. In this review we discuss the current state of synthetic biology within a four-stage framework (design, modeling, synthesis, analysis) and highlight areas requiring further advancement to facilitate true engineering of synthetic microbial metabolism.