Advanced strategies and tools to facilitate and streamline microbial adaptive laboratory evolution

Metabolic engineering strategies for L-Homoserine production in Escherichia coli

L-Homoserine, serves as a non-essential precursor for the essential amino acids derived from L-aspartate in both animals and humans. It finds widespread applications across the food, cosmetics, pharmaceutical, and animal feed industries. Microbial fermentation, primarily utilizing Escherichia coli, is the dominant approach for L-Homoserine production. However, despite recent advancements in fermentative processes employing E. coli strains, low production efficiency remains a significant barrier to its commercial viability. This review explores the biosynthesis, secretion, and regulatory mechanisms of L-Homoserine in E. coli while assessing various metabolic engineering strategies aimed at improving production efficiency.

Engineering microbial cell factories by multiplexed spatiotemporal control of cellular metabolism: Advances, challenges, and future perspectives

Generally, the metabolism in microbial organism is an intricate, spatiotemporal process that emerges from gene regulatory networks, which affects the efficiency of product biosynthesis. With the coming age of synthetic biology, spatiotemporal control systems have been explored as versatile strategies to promote product biosynthesis at both spatial and temporal levels. Meanwhile, the designer synthetic compartments provide new and promising approaches to engineerable spatiotemporal control systems to construct high-performance microbial cell factories. In this article, we comprehensively summarize recent developments in spatiotemporal control systems for tailoring advanced cell factories, and illustrate how to apply spatiotemporal control systems in different microbial species with desired applications. Future challenges of spatiotemporal control systems and perspectives are also discussed.

Optimisation strategies for directed evolution without sequencing

Directed evolution can enable engineering of biological systems with minimal knowledge of their underlying sequence-to-function relationships. A typical directed evolution process consists of iterative rounds of mutagenesis and selection that are designed to steer changes in a biological system (e.g. a protein) towards some functional goal. Much work has been done, particularly leveraging advancements in machine learning, to optimise the process of directed evolution. Many of these methods, however, require DNA sequencing and synthesis, making them resource-intensive and incompatible with developments in targeted in vivo mutagenesis. Operating within the experimental constraints of established sorting-based directed evolution techniques (e.g. Fluorescence-Activated Cell Sorting, FACS), we explore approaches for optimisation of directed evolution that could in future be implemented without sequencing information. We then expand our methods to the context of emerging experimental techniques in directed evolution, which allow for single-cell selection based on fitness objectives defined from any combination of measurable traits. Finally, we explore these alternative strategies on the GB1 and TrpB empirical landscapes, demonstrating that they could lead to up to 19-fold and 7-fold increases respectively in the probability of attaining the global fitness peak.

Fundamentals and Exceptions of the LysR-type Transcriptional Regulators

LysR-type transcriptional regulators (LTTRs) are emerging as a promising group of macromolecules for the field of biosensors. As the largest family of bacterial transcription factors, the LTTRs represent a vast and mostly untapped repertoire of sensor proteins. To fully harness these regulators for transcription factor-based biosensor development, it is crucial to understand their underlying mechanisms and functionalities. In the first part, this Review discusses the established model and features of LTTRs. As dual-function regulators, these inducible transcription factors exude precise control over their regulatory targets. In the second part of this Review, an overview is given of the exceptions to the "classic" LTTR model. While a general regulatory mechanism has helped elucidate the intricate regulation performed by LTTRs, it is essential to recognize the variations within the family. By combining this knowledge, characterization of new regulators can be done more efficiently and accurately, accelerating the expansion of transcriptional sensors for biosensor development. Unlocking the pool of LTTRs would significantly expand the currently limited range of detectable molecules and regulatory functions available for the implementation of novel synthetic genetic circuitry.

Identifying resistance molecules in TiO2 nanoparticle-tolerant strains to facilitate the development of strategies for combating TiO2 nanoparticle pollution

The severity of environmental pollution caused by TiO2 nanoparticles (nTiO2) is increasing, highlighting the urgent need for the development of strategies to combat nTiO2 pollution. Insights into resistance molecules from nTiO2-tolerant strains may facilitate such development. In this study, we utilized multi-omics, genetic manipulation, physiological and biochemical experiments to identify relevant resistance molecules in two strains (Physarum polycephalum Z259 and T83) tolerated to mixed-phase nTiO2 (MPnTiO2). We discovered that a competing endogenous RNA (ceRNA) network, comprising one long non-coding RNA (lncRNA), four microRNAs, and nine mRNAs, influenced metabolic rearrangement and was associated with significant resistance in these strains. Additionally, we found that the lncRNA in the ceRNAs network and certain small-weight metabolites associated with the ceRNA exhibited notable mitigation effects not only against MPnTiO2 but also against other types of nTiO2 with broad species applicability (they significantly improved the resistance of several non-nTiO2-tolerant cells/organisms in the laboratory and reduced cell damage of non-nTiO2-tolerant cells/organisms in highly suspected nTiO2-polluted areas of the real world). In summary, this study deepens our understanding of nTiO2-tolerant strains, provides valuable insights into resistance molecules in these strains, and facilitates the development of strategies to combat nTiO2 pollution.

Technological modes and processes to enhance the Rhodosporidium toruloides based lipid accumulation

Rhodosporidium toruloides has emerged as an excellent option for microbial lipid production due to its ability to accumulate up to 70 % of lipids per cell dry weight, consume multiple substrates such as glucose and xylose, and tolerate toxic compounds. Despite the potential of Rhodosporidium toruloides for high lipid yields, achieving these remains is a significant hurdle. A comprehensive review is essential to thoroughly evaluate the advancements in processes and technologies to enhance lipid production in R. toruloides. The review covers various strategies for enhancing lipid production like co-culture, adaptive evolution, carbon flux analysis, as well as different modes of fermentation. This review will help researchers to better understand the recent developments in technologies for sustainable and scalable lipid production from R. toruloides and simultaneously emphasize the need for developing an efficient and sustainable bioprocess.

Relieving metabolic burden to improve robustness and bioproduction by industrial microorganisms

Metabolic burden is defined by the influence of genetic manipulation and environmental perturbations on the distribution of cellular resources. The rewiring of microbial metabolism for bio-based chemical production often leads to a metabolic burden, followed by adverse physiological effects, such as impaired cell growth and low product yields. Alleviating the burden imposed by undesirable metabolic changes has become an increasingly attractive approach for constructing robust microbial cell factories. In this review, we provide a brief overview of metabolic burden engineering, focusing specifically on recent developments and strategies for diminishing the burden while improving robustness and yield. A variety of examples are presented to showcase the promise of metabolic burden engineering in facilitating the design and construction of robust microbial cell factories. Finally, challenges and limitations encountered in metabolic burden engineering are discussed.

Biosensor-Assisted Engineering for Diverse Microbial Cellular Physiologies

Recent advancements in biosensor technology have revolutionized the field of microbial engineering, enabling efficient and precise optimization of strains for the production of valuable chemicals. This review comprehensively explores the innovative integration of biosensors to enhance microbial cell factories, with a particular emphasis on the crucial role of high-throughput biosensor-assisted screening. Biosensor-assisted approaches have enabled the identification of novel transporters, the elucidation of underlying transport mechanisms, and the fine-tuning of metabolic pathways for enhanced production. Furthermore, this review illustrates the utilization of biosensors for manipulating cellular behaviors, including interactions with environmental factors, and the reduction of nongenetic cell-to-cell variations. This review highlights the indispensable role of biosensors in advancing the field of microbial engineering through the modulation and exploitation of diverse cellular physiological processes.

Development of transcriptional factor-based whole-cell biosensors to monitor and degrade antibiotics using mutant cells obtained via adaptive laboratory evolution

With the widespread use of antibiotics and increasing environmental concerns regarding antibiotic abuse, the detection and degradation of antibiotic residues in various samples has become a pressing issue. Transcriptional factor (TF)-based whole-cell biosensors are low-cost, easy-to-use, and flexible tools for detecting chemicals and controlling bioprocesses. However, because of cytotoxicity caused by antibiotics, the application of such biosensors is limited in the presence of antibiotics. In this study, we used antibiotic-tolerant mutants obtained via adaptive laboratory evolution (ALE) to develop TF-based whole-cell biosensors for antibiotic monitoring and degradation. The biosensors had high performance and stability in detecting relatively high concentrations of tetracycline (Tc) and nisin. The ALE mutant-based Tc biosensor exhibited a 10-fold larger linear detection range than the wild-type strain-based biosensor. Then, the Tc biosensor was employed to detect residual amounts of Tc in mouse stool, serum, and urine samples and facilitate Tc biodegradation in mouse stool, demonstrating its high utility. Considering that ALE has been demonstrated to enhance cell tolerance to various toxic chemicals, our strategy might facilitate the development of whole-cell biosensors for most antibiotics and other toxic ligands.

Transcription factor-based biosensor: A molecular-guided approach for advanced biofuel synthesis

As a sustainable and renewable alternative to petroleum fuels, advanced biofuels shoulder the responsibility of energy saving, emission reduction and environmental protection. Traditional engineering of cell factories for production of advanced biofuels lacks efficient high-throughput screening tools and regulating systems, impeding the improvement of cellular productivity and yield. Transcription factor-based biosensors have been widely applied to monitor and regulate microbial cell factory products due to the advantages of fast detection and in-situ screening. This review updates the design and application of transcription factor-based biosensors tailored for advanced biofuels and related intermediates. The construction and genetic parts selection principle of biosensors are discussed. Strategies to enhance the performance of biosensor, including regulating promoter strength and RBS strength, optimizing plasmid copy number, implementing genetic amplifier, and modulating the structure of transcription factor, have also been summarized. We further review the application of biosensors in high-throughput screening of new metabolic engineering targets, evolution engineering, confirmation of protein function, and dynamic regulation of metabolic flux for higher production of advanced biofuels. At last, we discuss the current limitations and future trends of transcription factor-based biosensors.

Automated in vivo enzyme engineering accelerates biocatalyst optimization

Achieving cost-competitive bio-based processes requires development of stable and selective biocatalysts. Their realization through in vitro enzyme characterization and engineering is mostly low throughput and labor-intensive. Therefore, strategies for increasing throughput while diminishing manual labor are gaining momentum, such as in vivo screening and evolution campaigns. Computational tools like machine learning further support enzyme engineering efforts by widening the explorable design space. Here, we propose an integrated solution to enzyme engineering challenges whereby ML-guided, automated workflows (including library generation, implementation of hypermutation systems, adapted laboratory evolution, and in vivo growth-coupled selection) could be realized to accelerate pipelines towards superior biocatalysts.

A model-driven approach to upcycling recalcitrant feedstocks in Pseudomonas putida by decoupling PHA production from nutrient limitation

Bacterial polyhydroxyalkanoates (PHAs) have emerged as promising eco-friendly alternatives to petroleum-based plastics since they are synthesized from renewable resources and offer exceptional properties. However, their production is limited to the stationary growth phase under nutrient-limited conditions, requiring customized strategies and costly two-phase bioprocesses. In this study, we tackle these challenges by employing a model-driven approach to reroute carbon flux and remove regulatory constraints using synthetic biology. We construct a collection of Pseudomonas putida-overproducing strains at the expense of plastics and lignin-related compounds using growth-coupling approaches. PHA production was successfully achieved during growth phase, resulting in the production of up to 46% PHA/cell dry weight while maintaining a balanced carbon-to-nitrogen ratio. Our strains are additionally validated under an upcycling scenario using enzymatically hydrolyzed polyethylene terephthalate as a feedstock. These findings have the potential to revolutionize PHA production and address the global plastic crisis by overcoming the complexities of traditional PHA production bioprocesses.

Transcriptomic profiling of an evolved Yarrowia lipolytica strain: tackling hexanoic acid fermentation to increase lipid production from short-chain fatty acids

BACKGROUND

Short-chain fatty acids (SCFAs) are cost-effective carbon sources for an affordable production of lipids. Hexanoic acid, the acid with the longest carbon chain in the SCFAs pool, is produced in anaerobic fermentation of organic residues and its use is very challenging, even inhibiting oleaginous yeasts growth.

RESULTS

In this investigation, an adaptive laboratory evolution (ALE) was performed to improve Yarrowia lipolytica ACA DC 50109 tolerance to high hexanoic acid concentrations. Following ALE, the transcriptomic analysis revealed several genetic adaptations that improved the assimilation of this carbon source in the evolved strain compared to the wild type (WT). Indeed, the evolved strain presented a high expression of the up-regulated gene YALI0 E16016g, which codes for FAT1 and is related to lipid droplets formation and responsible for mobilizing long-chain acids within the cell. Strikingly, acetic acid and other carbohydrate transporters were over-expressed in the WT strain.

CONCLUSIONS

A more tolerant yeast strain able to attain higher lipid content under the presence of high concentrations of hexanoic acid has been obtained. Results provided novel information regarding the assimilation of hexanoic acid in yeasts.

Pathway Evolution Through a Bottlenecking-Debottlenecking Strategy and Machine Learning-Aided Flux Balancing

The evolution of pathway enzymes enhances the biosynthesis of high-value chemicals, crucial for pharmaceutical, and agrochemical applications. However, unpredictable evolutionary landscapes of pathway genes often hinder successful evolution. Here, the presence of complex epistasis is identifued within the representative naringenin biosynthetic pathway enzymes, hampering straightforward directed evolution. Subsequently, a biofoundry-assisted strategy is developed for pathway bottlenecking and debottlenecking, enabling the parallel evolution of all pathway enzymes along a predictable evolutionary trajectory in six weeks. This study then utilizes a machine learning model, ProEnsemble, to further balance the pathway by optimizing the transcription of individual genes. The broad applicability of this strategy is demonstrated by constructing an Escherichia coli chassis with evolved and balanced pathway genes, resulting in 3.65 g L-1 naringenin. The optimized naringenin chassis also demonstrates enhanced production of other flavonoids. This approach can be readily adapted for any given number of enzymes in the specific metabolic pathway, paving the way for automated chassis construction in contemporary biofoundries.

Oxidative stress resistance prompts pyrroloquinoline quinone biosynthesis in Hyphomicrobium denitrificans H4-45

Pyrroloquinoline quinone (PQQ) is a natural antioxidant with diverse applications in food and pharmaceutical industries. A lot of effort has been devoted toward the discovery of PQQ high-producing microbial species and characterization of biosynthesis, but it is still challenging to achieve a high PQQ yield. In this study, a combined strategy of random mutagenesis and adaptive laboratory evolution (ALE) with fermentation optimization was applied to improve PQQ production in Hyphomicrobium denitrificans H4-45. A mutant strain AE-9 was obtained after nearly 400 generations of UV-LiCl mutagenesis, followed by an ALE process, which was conducted with a consecutive increase of oxidative stress generated by kanamycin, sodium sulfide, and potassium tellurite. In the flask culture condition, the PQQ production in mutant strain AE-9 had an 80.4% increase, and the cell density increased by 14.9% when compared with that of the initial strain H4-45. Moreover, batch and fed-batch fermentation processes were optimized to further improve PQQ production by pH control strategy, methanol and H2O2 feed flow, and segmented fermentation process. Finally, the highest PQQ production and productivity of the mutant strain AE-9 reached 307 mg/L and 4.26 mg/L/h in a 3.7-L bioreactor, respectively. Whole genome sequencing analysis showed that genetic mutations in the ftfL gene and thiC gene might contribute to improving PQQ production by enhancing methanol consumption and cell growth in the AE-9 strain. Our study provided a systematic strategy to obtain a PQQ high-producing mutant strain and achieve high production of PQQ in fermentation. These practical methods could be applicable to improve the production of other antioxidant compounds with uncleared regulation mechanisms. KEY POINTS: • Improvement of PQQ production by UV-LiCl mutagenesis combined with adaptive laboratory evolution (ALE) and fermentation optimization. • A consecutive increase of oxidative stress could be used as the antagonistic factor for ALE to enhance PQQ production. • Mutations in the ftfL gene and thiC gene indicated that PQQ production might be increased by enhancing methanol consumption and cell growth.

Biological functions at high pressure: transcriptome response of Shewanella oneidensis MR-1 to hydrostatic pressure relevant to Titan and other icy ocean worlds

High hydrostatic pressure (HHP) is a key driver of life's evolution and diversification on Earth. Icy moons such as Titan, Europa, and Enceladus harbor potentially habitable high-pressure environments within their subsurface oceans. Titan, in particular, is modeled to have subsurface ocean pressures ≥ 150 MPa, which are above the highest pressures known to support life on Earth in natural ecosystems. Piezophiles are organisms that grow optimally at pressures higher than atmospheric (0.1 MPa) pressure and have specialized adaptations to the physical constraints of high-pressure environments - up to ~110 MPa at Challenger Deep, the highest pressure deep-sea habitat explored. While non-piezophilic microorganisms have been shown to survive short exposures at Titan relevant pressures, the mechanisms of their survival under such conditions remain largely unelucidated. To better understand these mechanisms, we have conducted a study of gene expression for Shewanella oneidensis MR-1 using a high-pressure experimental culturing system. MR-1 was subjected to short-term (15 min) and long-term (2 h) HHP of 158 MPa, a value consistent with pressures expected near the top of Titan's subsurface ocean. We show that MR-1 is metabolically active in situ at HHP and is capable of viable growth following 2 h exposure to 158 MPa, with minimal pressure training beforehand. We further find that MR-1 regulates 264 genes in response to short-term HHP, the majority of which are upregulated. Adaptations include upregulation of the genes argA, argB, argC, and argF involved in arginine biosynthesis and regulation of genes involved in membrane reconfiguration. MR-1 also utilizes stress response adaptations common to other environmental extremes such as genes encoding for the cold-shock protein CspG and antioxidant defense related genes. This study suggests Titan's ocean pressures may not limit life, as microorganisms could employ adaptations akin to those demonstrated by terrestrial organisms.

Breeding of high-tolerance yeast by adaptive evolution and high-gravity brewing of mutant

BACKGROUND

Ethanol and osmotic stresses are the major limiting factors for brewing strong beer with high-gravity wort. Breeding of yeast strains with high osmotic and ethanol tolerance and studying very-high-gravity (VHG) brewing technology is of great significance for brewing strong beer.

RESULTS

This study used an optimized microbial microdroplet culture (MMC) system for adaptive laboratory evolution (ALE) of Saccharomyces cerevisiae YN81 to improve its tolerance to osmotic and ethanol stress. Meanwhile, we investigated the VHG and VHG with added ethanol (VHGAE) brewing processes for the evolved mutants in brewing strong beer. The results showed that three evolved mutants were obtained; among them, the growth performance of YN81mc-8.3 under 300, 340, 380, 420 and 460 g L-1 sucrose stresses was greater than that of the other strains. The ethanol tolerance of YN81mc-8.3 was 12%, which was 20% higher than that of YN81. During strong-beer brewing in a 100 L cylindrical cone-bottom tank, the sugar utilization and ethanol yield of YN81mc-8.3 outperformed those of YN81 in both the VHG and VHGAE brewing processes. Measurement of the diacetyl concentration showed that YN81mc-8.3 had a stronger diacetyl reduction ability; in particular, the real degree of fermentation of beers brewed by YN81mc-8.3 in VHG and VHGAE brewing processes was 75.35% and 66.71%, respectively - higher than those of the two samples brewed by YN81. Meanwhile, the visual, olfactive and gustative properties of the strong beer produced by YN81mc-8.3 were better than those of the other beers.

CONCLUSION

In this study, the mutant YN81mc-8.3 and the VHGAE brewing process were optimal and represented a better alternative strong-beer brewing process. © 2023 Society of Chemical Industry.

Microfluidics for adaptation of microorganisms to stress: design and application

Microfluidic systems have fundamentally transformed the realm of adaptive laboratory evolution (ALE) for microorganisms by offering unparalleled control over environmental conditions, thereby optimizing mutant generation and desired trait selection. This review summarizes the substantial influence of microfluidic technologies and their design paradigms on microbial adaptation, with a primary focus on leveraging spatial stressor concentration gradients to enhance microbial growth in challenging environments. Specifically, microfluidic platforms tailored for scaled-down ALE processes not only enable highly autonomous and precise setups but also incorporate novel functionalities. These capabilities encompass fostering the growth of biofilms alongside planktonic cells, refining selection gradient profiles, and simulating adaptation dynamics akin to natural habitats. The integration of these aspects enables shaping phenotypes under pressure, presenting an unprecedented avenue for developing robust, stress-resistant strains, a feat not easily attainable using conventional ALE setups. The versatility of these microfluidic systems is not limited to fundamental research but also offers promising applications in various areas of stress resistance. As microfluidic technologies continue to evolve and merge with cutting-edge methodologies, they possess the potential not only to redefine the landscape of microbial adaptation studies but also to expedite advancements in various biotechnological areas. KEY POINTS: • Microfluidics enable precise microbial adaptation in controlled gradients. • Microfluidic ALE offers insights into stress resistance and distinguishes between resistance and persistence. • Integration of adaptation-influencing factors in microfluidic setups facilitates efficient generation of stress-resistant strains.

Adaptive laboratory evolution to obtain furfural tolerant Saccharomyces cerevisiae for bioethanol production and the underlying mechanism

Introduction

Furfural, a main inhibitor produced during pretreatment of lignocellulose, has shown inhibitory effects on S. cerevisiae.

Method

In the present study, new strains named 12-1 with enhanced resistance to furfural were obtained through adaptive laboratory evolution, which exhibited a shortened lag phase by 36 h, and an increased ethanol conversion rate by 6.67% under 4 g/L furfural.

Results and Discussion

To further explore the mechanism of enhanced furfural tolerance, ADR1_1802 mutant was constructed by CRISPR/Cas9 technology, based on whole genome re-sequencing data. The results indicated that the time when ADR1_1802 begin to grow was shortened by 20 h compared with reference strain (S. cerevisiae CEN.PK113-5D) when furfural was 4 g/L. Additionally, the transcription levels of GRE2 and ADH6 in ADR1_ 1802 mutant were increased by 53.69 and 44.95%, respectively, according to real-time fluorescence quantitative PCR analysis. These findings suggest that the enhanced furfural tolerance of mutant is due to accelerated furfural degradation. Importance: Renewable carbon worldwide is vital to achieve "zero carbon" target. Bioethanol obtained from biomass is one of them. To make bioethanol price competitive to fossil fuel, higher ethanol yield is necessary, therefore, monosaccharide produced during biomass pretreatment should be effectively converted to ethanol by Saccharomyces cerevisiae. However, inhibitors formed by glucose or xylose oxidation could make ethanol yield lower. Thus, inhibitor tolerant Saccharomyces cerevisiae is important to this process. As one of the main component of pretreatment hydrolysate, furfural shows obvious impact on growth and ethanol production of Saccharomyces cerevisiae. To get furfural tolerant Saccharomyces cerevisiae and find the underlying mechanism, adaptive laboratory evolution and CRISPR/Cas9 technology were applied in the present study.

Heterotypic stress-induced adaptive evolution enhances freeze-drying tolerance and storage stability of Leuconostoc mesenteroides WiKim33

Lactic acid bacteria (LAB) are currently being investigated for their potential use as probiotics and starter cultures. Researchers have developed powdering processes for the commercialization of LAB. Previous studies have focused on identifying innovative cryoprotective agents and freeze-drying (FD) techniques to enhance the stability of LAB. In this study, adaptive laboratory evolution (ALE) was employed to develop a strain with high FD tolerance and enhanced storage stability. Leuconostoc mesenteroids WiKim33 was subjected to heterotypic shock (heat and osmosis shock) to induce the desired phenotype and genotype. An FD-tolerant enhanced Leu. mesenteroides WiKim33 strain (ALE50) was obtained, which harbored a modified fatty acid composition and cell envelope characteristics. Specifically, ALE50 showed a lower unsaturated fatty acid (UFA)/saturated fatty acid (SFA) ratio and a higher cyclic fatty acid (CFA) composition. Moreover, the exopolysaccharide (EPS) thickness increased significantly by 331% compared to that of the wild type (WT). FD tolerance, which was evaluated using viability testing after FD, was enhanced by 33.4%. Overall, we demonstrated the feasibility of ALE to achieve desirable characteristics and provided insights into the mechanisms underlying increased FD tolerance.

Robotic workflows for automated long-term adaptive laboratory evolution: improving ethanol utilization by Corynebacterium glutamicum

BACKGROUND

Adaptive laboratory evolution (ALE) is known as a powerful tool for untargeted engineering of microbial strains and genomics research. It is particularly well suited for the adaptation of microorganisms to new environmental conditions, such as alternative substrate sources. Since the probability of generating beneficial mutations increases with the frequency of DNA replication, ALE experiments are ideally free of constraints on the required duration of cell proliferation.

RESULTS

Here, we present an extended robotic workflow for performing long-term evolution experiments based on fully automated repetitive batch cultures (rbALE) in a well-controlled microbioreactor environment. Using a microtiter plate recycling approach, the number of batches and thus cell generations is technically unlimited. By applying the validated workflow in three parallel rbALE runs, ethanol utilization by Corynebacterium glutamicum ATCC 13032 (WT) was significantly improved. The evolved mutant strain WT_EtOH-Evo showed a specific ethanol uptake rate of 8.45 ± 0.12 mmolEtOH gCDW-1 h-1 and a growth rate of 0.15 ± 0.01 h-1 in lab-scale bioreactors. Genome sequencing of this strain revealed a striking single nucleotide variation (SNV) upstream of the ald gene (NCgl2698, cg3096) encoding acetaldehyde dehydrogenase (ALDH). The mutated basepair was previously predicted to be part of the binding site for the global transcriptional regulator GlxR, and re-engineering demonstrated that the identified SNV is key for enhanced ethanol assimilation. Decreased binding of GlxR leads to increased synthesis of the rate-limiting enzyme ALDH, which was confirmed by proteomics measurements.

CONCLUSIONS

The established rbALE technology is generally applicable to any microbial strain and selection pressure that fits the small-scale cultivation format. In addition, our specific results will enable improved production processes with C. glutamicum from ethanol, which is of particular interest for acetyl-CoA-derived products.

Case Studies in the Assessment of Microbial Fitness: Seemingly Subtle Changes Can Have Major Effects on Phenotypic Outcomes

Following the completion of an adaptive evolution experiment, fitness evaluations are routinely conducted to assess the magnitude of adaptation. In doing so, proper consideration should be given when determining the appropriate methods as trade-offs may exist between accuracy and throughput. Here, we present three instances in which small changes in the framework or execution of fitness evaluations significantly impacted the outcomes. The first case illustrates that discrepancies in fitness conclusions can arise depending on the approach to evaluating fitness, the culture vessel used, and the sampling method. The second case reveals that variations in environmental conditions can occur associated with culture vessel material. Specifically, these subtle changes can greatly affect microbial physiology leading to changes in the culture pH and distorting fitness measurements. Finally, the last case reports that heterogeneity in CFU formation time can result in inaccurate fitness conclusions. Based on each case, considerations and recommendations are presented for future adaptive evolution experiments.

Microbial tolerance engineering for boosting lactic acid production from lignocellulose

Lignocellulosic biomass is an attractive non-food feedstock for lactic acid production via microbial conversion due to its abundance and low-price, which can alleviate the conflict with food supplies. However, a variety of inhibitors derived from the biomass pretreatment processes repress microbial growth, decrease feedstock conversion efficiency and increase lactic acid production costs. Microbial tolerance engineering strategies accelerate the conversion of carbohydrates by improving microbial tolerance to toxic inhibitors using pretreated lignocellulose hydrolysate as a feedstock. This review presents the recent significant progress in microbial tolerance engineering to develop robust microbial cell factories with inhibitor tolerance and their application for cellulosic lactic acid production. Moreover, microbial tolerance engineering crosslinking other efficient breeding tools and novel approaches are also deeply discussed, aiming to providing a practical guide for economically viable production of cellulosic lactic acid.

Recent advances in microbial production of medium chain fatty acid from renewable carbon resources: a comprehensive review

Microbial production of medium chain length fatty acids (MCFAs) from renewable resources is becoming increasingly important in establishing a sustainable and clean chemical industry. This review comprehensively summarizes current advances in microbial MCFA production from renewable resources. Detailed information is provided on two major MCFA production pathways using various renewable resources and other auxiliary pathways supporting MCFA production to help understand the fundamentals of bio-based MCFA production. In addition, conventional and well-studied MCFA producers are classified into two categories, natural and synthetic producers, and their characteristics on MCFA production are outlined. Moreover, various engineering strategies employed to achieve the highest MCFAs production up to date are showcased together with key enzymes suggested for MCFA overproduction. Finally, future challenges and perspectives are discussed towards more efficient production of bio-based MCFA production.

Application of Adaptive Laboratory Evolution in Lipid and Terpenoid Production in Yeast and Microalgae

Due to the complexity of metabolic and regulatory networks in microorganisms, it is difficult to obtain robust phenotypes through artificial rational design and genetic perturbation. Adaptive laboratory evolution (ALE) engineering plays an important role in the construction of stable microbial cell factories by simulating the natural evolution process and rapidly obtaining strains with stable traits through screening. This review summarizes the application of ALE technology in microbial breeding, describes the commonly used methods for ALE, and highlights the important applications of ALE technology in the production of lipids and terpenoids in yeast and microalgae. Overall, ALE technology provides a powerful tool for the construction of microbial cell factories, and it has been widely used in improving the level of target product synthesis, expanding the range of substrate utilization, and enhancing the tolerance of chassis cells. In addition, in order to improve the production of target compounds, ALE also employs environmental or nutritional stress strategies corresponding to the characteristics of different terpenoids, lipids, and strains.

Discovery of novel amino acid production traits by evolution of synthetic co-cultures

BACKGROUND

Amino acid production features of Corynebacterium glutamicum were extensively studied in the last two decades. Many metabolic pathways, regulatory and transport principles are known, but purely rational approaches often provide only limited progress in production optimization. We recently generated stable synthetic co-cultures, termed Communities of Niche-optimized Strains (CoNoS), that rely on cross-feeding of amino acids for growth. This setup has the potential to evolve strains with improved production by selection of faster growing communities.

RESULTS

Here we performed adaptive laboratory evolution (ALE) with a CoNoS to identify mutations that are relevant for amino acid production both in mono- and co-cultures. During ALE with the CoNoS composed of strains auxotrophic for either L-leucine or L-arginine, we obtained a 23% growth rate increase. Via whole-genome sequencing and reverse engineering, we identified several mutations involved in amino acid transport that are beneficial for CoNoS growth. The L-leucine auxotrophic strain carried an expression-promoting mutation in the promoter region of brnQ (cg2537), encoding a branched-chain amino acid transporter in combination with mutations in the genes for the Na+/H+-antiporter Mrp1 (cg0326-cg0321). This suggested an unexpected link of Mrp1 to L-leucine transport. The L-arginine auxotrophic partner evolved expression-promoting mutations near the transcriptional start site of the yet uncharacterized operon argTUV (cg1504-02). By mutation studies and ITC, we characterized ArgTUV as the only L-arginine uptake system of C. glutamicum with an affinity of KD = 30 nM. Finally, deletion of argTUV in an L-arginine producer strain resulted in a faster and 24% higher L-arginine production in comparison to the parental strain.

CONCLUSION

Our work demonstrates the power of the CoNoS-approach for evolution-guided identification of non-obvious production traits, which can also advance amino acid production in monocultures. Further rounds of evolution with import-optimized strains can potentially reveal beneficial mutations also in metabolic pathway enzymes. The approach can easily be extended to all kinds of metabolite cross-feeding pairings of different organisms or different strains of the same organism, thereby enabling the identification of relevant transport systems and other favorable mutations.

Adaptive laboratory evolution boost Yarrowia lipolytica tolerance to vanillic acid

Microbial tolerance to lignocellulose-derived inhibitors, such as aromatic acids, is critical for the economical production of biofuels and biochemicals. Here, adaptive laboratory evolution was applied to improve the tolerance of Yarrowia lipolytica to a representative aromatic acid inhibitor vanillic acid. The transcriptome profiling of evolved strain suggested that the tolerance could be related to the up-regulation of RNA processing and multidrug transporting pathways. Further analysis by reverse engineering confirmed that the amplification of YALI0_F13475g coding for transcriptional coactivator and YALI0_E25201g coding for multidrug transporter conferred tolerance not only to vanillic acid but also towards ferulic acid, p-coumaric acid, p-hydroxybenzoic acid and syringic acid. These findings suggested that regulation of RNA processing and multidrug transporting pathways may be important for enhanced aromatic acid tolerance in Y. lipolytica. This study provides valuable genetic information for robust strain construction for lignocellulosic biorefinery.

Laboratory evolution reveals general and specific tolerance mechanisms for commodity chemicals

Although strain tolerance to high product concentrations is a barrier to the economically viable biomanufacturing of industrial chemicals, chemical tolerance mechanisms are often unknown. To reveal tolerance mechanisms, an automated platform was utilized to evolve Escherichia coli to grow optimally in the presence of 11 industrial chemicals (1,2-propanediol, 2,3-butanediol, glutarate, adipate, putrescine, hexamethylenediamine, butanol, isobutyrate, coumarate, octanoate, hexanoate), reaching tolerance at concentrations 60%-400% higher than initial toxic levels. Sequencing genomes of 223 isolates from 89 populations, reverse engineering, and cross-compound tolerance profiling were employed to uncover tolerance mechanisms. We show that: 1) cells are tolerized via frequent mutation of membrane transporters or cell wall-associated proteins (e.g., ProV, KgtP, SapB, NagA, NagC, MreB), transcription and translation machineries (e.g., RpoA, RpoB, RpoC, RpsA, RpsG, NusA, Rho), stress signaling proteins (e.g., RelA, SspA, SpoT, YobF), and for certain chemicals, regulators and enzymes in metabolism (e.g., MetJ, NadR, GudD, PurT); 2) osmotic stress plays a significant role in tolerance when chemical concentrations exceed a general threshold and mutated genes frequently overlap with those enabling chemical tolerance in membrane transporters and cell wall-associated proteins; 3) tolerization to a specific chemical generally improves tolerance to structurally similar compounds whereas a tradeoff can occur on dissimilar chemicals, and 4) using pre-tolerized starting isolates can hugely enhance the subsequent production of chemicals when a production pathway is inserted in many, but not all, evolved tolerized host strains, underpinning the need for evolving multiple parallel populations. Taken as a whole, this study provides a comprehensive genotype-phenotype map based on identified mutations and growth phenotypes for 223 chemical tolerant isolates.

Recent advances in screening amino acid overproducers

Microbial fermentation has contributed to 80% of global amino acid production. The key to microbial fermentation is to obtain fermentation strains with high performance to produce target amino acids with a high yield. These strains are primarily derived from screening enormous mutant libraries. Therefore, a high-throughput, rapid, accurate, and universal screening strategy for amino acid overproducers has become a guarantee for obtaining optional amino acid overproducers. In recent years, the rapid development of various novel screening strategies has been witnessed. However, proper analysis and discussion of these innovative technologies are lacking. Here we systematically reviewed recent advances in screening strategies: the auxotrophic-based strategy, the biosensor-based strategy, and the latest translation-based screening strategy. The design principle, application scope, working efficiency, screening accuracy, and universality of these strategies were discussed in detail. The potential for screening nonstandard amino acid overproducers was also analyzed. Guidance for the improvement of future screening strategies is provided in this review, which could expedite the reconstruction of amino acid overproducers and help promote the fermentation industry to reduce cost, increase yield, and improve quality.

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.

Contributions of Adaptive Laboratory Evolution towards the Enhancement of the Biotechnological Potential of Non-Conventional Yeast Species

Changes in biological properties over several generations, induced by controlling short-term evolutionary processes in the laboratory through selective pressure, and whole-genome re-sequencing, help determine the genetic basis of microorganism's adaptive laboratory evolution (ALE). Due to the versatility of this technique and the imminent urgency for alternatives to petroleum-based strategies, ALE has been actively conducted for several yeasts, primarily using the conventional species Saccharomyces cerevisiae, but also non-conventional yeasts. As a hot topic at the moment since genetically modified organisms are a debatable subject and a global consensus on their employment has not yet been attained, a panoply of new studies employing ALE approaches have emerged and many different applications have been exploited in this context. In the present review, we gathered, for the first time, relevant studies showing the ALE of non-conventional yeast species towards their biotechnological improvement, cataloging them according to the aim of the study, and comparing them considering the species used, the outcome of the experiment, and the employed methodology. This review sheds light on the applicability of ALE as a powerful tool to enhance species features and improve their performance in biotechnology, with emphasis on the non-conventional yeast species, as an alternative or in combination with genome editing approaches.

Microbial cell factories based on filamentous bacteria, yeasts, and fungi

BACKGROUND

Advanced DNA synthesis, biosensor assembly, and genetic circuit development in synthetic biology and metabolic engineering have reinforced the application of filamentous bacteria, yeasts, and fungi as promising chassis cells for chemical production, but their industrial application remains a major challenge that needs to be solved.

RESULTS

As important chassis strains, filamentous microorganisms can synthesize important enzymes, chemicals, and niche pharmaceutical products through microbial fermentation. With the aid of metabolic engineering and synthetic biology, filamentous bacteria, yeasts, and fungi can be developed into efficient microbial cell factories through genome engineering, pathway engineering, tolerance engineering, and microbial engineering. Mutant screening and metabolic engineering can be used in filamentous bacteria, filamentous yeasts (Candida glabrata, Candida utilis), and filamentous fungi (Aspergillus sp., Rhizopus sp.) to greatly increase their capacity for chemical production. This review highlights the potential of using biotechnology to further develop filamentous bacteria, yeasts, and fungi as alternative chassis strains.

CONCLUSIONS

In this review, we recapitulate the recent progress in the application of filamentous bacteria, yeasts, and fungi as microbial cell factories. Furthermore, emphasis on metabolic engineering strategies involved in cellular tolerance, metabolic engineering, and screening are discussed. Finally, we offer an outlook on advanced techniques for the engineering of filamentous bacteria, yeasts, and fungi.

Efficient biosynthesis of (R)-mandelic acid from styrene oxide by an adaptive evolutionary Gluconobacter oxydans STA

BACKGROUND

(R)-mandelic acid (R-MA) is a highly valuable hydroxyl acid in the pharmaceutical industry. However, biosynthesis of optically pure R-MA remains significant challenges, including the lack of suitable catalysts and high toxicity to host strains. Adaptive laboratory evolution (ALE) was a promising and powerful strategy to obtain specially evolved strains.

RESULTS

Herein, we report a new cell factory of the Gluconobacter oxydans to biocatalytic styrene oxide into R-MA by utilizing the G. oxydans endogenous efficiently incomplete oxidization and the epoxide hydrolase (SpEH) heterologous expressed in G. oxydans. With a new screened strong endogenous promoter P12780, the production of R-MA was improved to 10.26 g/L compared to 7.36 g/L of using Plac. As R-MA showed great inhibition for the reaction and toxicity to cell growth, adaptive laboratory evolution (ALE) strategy was introduced to improve the cellular R-MA tolerance. The adapted strain that can tolerate 6 g/L R-MA was isolated (named G. oxydans STA), while the wild-type strain cannot grow under this stress. The conversion rate was increased from 0.366 g/L/h of wild type to 0.703 g/L/h by the recombinant STA, and the final R-MA titer reached 14.06 g/L. Whole-genome sequencing revealed multiple gene-mutations in STA, in combination with transcriptome analysis under R-MA stress condition, we identified five critical genes that were associated with R-MA tolerance, among which AcrA overexpression could further improve R-MA titer to 15.70 g/L, the highest titer reported from bulk styrene oxide substrate.

CONCLUSIONS

The microbial engineering with systematic combination of static regulation, ALE, and transcriptome analysis strategy provides valuable solutions for high-efficient chemical biosynthesis, and our evolved G. oxydans would be better to serve as a chassis cell for hydroxyl acid production.

Towards enhancement of fungal hydrolytic enzyme cocktail using waste algal biomass of Oscillatoria obscura and enzyme stability investigation under the influence of iron oxide nanoparticles

Development of low-cost and economic cellulase production is among the key challenges due to its broad industrial applications. One of the main topics of research pertaining to sustainable biomass waste based biorefinaries is the development of economic cellulase production strategies. The main cause of the increase in cellulase production costs is the use of commercial substrates; as a result, the cost of any cellulase-based bioprocess can be decreased by employing a productive, low-cost substrate. The goal of the current study is to develop low-cost cellulase using the carbohydrate-rich, renewable, and widely accessible cyanobacteria algae Oscillatoria obscura as the production substrate. Maximum cellulase was produced utilising the fungus Rhizopus oryzae at substrate concentration of 7.0 g among various tested concentrations of algal biomass. Maximum production rates of 22 IU/gds FP, 105 IU/gds BGL, and 116 IU/gds EG in 72 h were possible under optimal conditions and substrate concentration. Further investigations on the crude enzyme's stability in the presence of iron oxide nanoparticles (IONPs) revealed that it was thermally stable at 60 °C for up to 8 h. Additionally, the crude enzyme demonstrated pH stability by maintaining its complete activity at pH 6.0 for 8 h in the presence of the optimal dose of 15 mg IONPs. The outcomes of this research may be used to investigate the possibility of producing such enzymes in large quantities at low cost for industrial use.

C1-based biomanufacturing: Advances, challenges and perspectives

One-carbon (C1) compounds have emerged as a key research focus due to the growth of metabolic engineering and synthetic biology as affordable and sustainable nonfood sugar feedstocks for energy-efficient and environmentally friendly biomanufacturing. This paper summarizes and discusses current developments in C1 compounds for biomanufacturing. First, two primary groups of microbes that use C1 compounds (native and synthetic) are introduced, and the traits, categorization, and functions of C1 microbes are summarized. Second, engineering strategies for C1 utilization are compiled and reviewed, including reconstruction of C1-utilization pathway, enzyme engineering, cofactor engineering, genome-scale modeling, and adaptive laboratory evolution. Third, a review of C1 compounds' uses in the synthesis of biofuels and high-value compounds is presented. Finally, potential obstacles to C1-based biomanufacturing are highlighted along with future research initiatives.

Genetically encoded biosensors for microbial synthetic biology: From conceptual frameworks to practical applications

Genetically encoded biosensors are the vital components of synthetic biology and metabolic engineering, as they are regarded as powerful devices for the dynamic control of genotype metabolism and evolution/screening of desirable phenotypes. This review summarized the recent advances in the construction and applications of different genetically encoded biosensors, including fluorescent protein-based biosensors, nucleic acid-based biosensors, allosteric transcription factor-based biosensors and two-component system-based biosensors. First, the construction frameworks of these biosensors were outlined. Then, the recent progress of biosensor applications in creating versatile microbial cell factories for the bioproduction of high-value chemicals was summarized. Finally, the challenges and prospects for constructing robust and sophisticated biosensors were discussed. This review provided theoretical guidance for constructing genetically encoded biosensors to create desirable microbial cell factories for sustainable bioproduction.

Synthetic biology tools for engineering Corynebacterium glutamicum

Corynebacterium glutamicum is a promising organism for the industrial production of amino acids, fuels, and various value-added chemicals. From the whole genome sequence release, C. glutamicum has been valuable in the field of industrial microbiology and biotechnology. Continuous discovery of genetic manipulations and regulation mechanisms has developed C. glutamicum as a synthetic biology platform chassis. This review summarized diverse genomic manipulation technologies and gene expression tools for static, dynamic, and multiplex control at transcription and translation levels. Moreover, we discussed the current challenges and applicable tools to C. glutamicum for future advancements.

Minireview: Engineering evolution to reconfigure phenotypic traits in microbes for biotechnological applications

Adaptive laboratory evolution (ALE) has long been used as the tool of choice for microbial engineering applications, ranging from the production of commodity chemicals to the innovation of complex phenotypes. With the advent of systems and synthetic biology, the ALE experimental design has become increasingly sophisticated. For instance, implementation of in silico metabolic model reconstruction and advanced synthetic biology tools have facilitated the effective coupling of desired traits to adaptive phenotypes. Furthermore, various multi-omic tools now enable in-depth analysis of cellular states, providing a comprehensive understanding of the biology of even the most genomically perturbed systems. Emerging machine learning approaches would assist in streamlining the interpretation of massive and multiplexed datasets and promoting our understanding of complexity in biology. This review covers some of the representative case studies among the 700 independent ALE studies reported to date, outlining key ideas, principles, and important mechanisms underlying ALE designs in bioproduction and synthetic cell engineering, with evidence from literatures to aid comprehension.

Design and engineering of genetically encoded protein biosensors for small molecules

Genetically encoded protein biosensors controlled by small organic molecules are valuable tools for many biotechnology applications, including control of cellular decisions in living cells. Here, we review recent advances in protein biosensor design and engineering for binding to novel ligands. We categorize sensor architecture as either integrated or portable, where portable biosensors uncouple molecular recognition from signal transduction. Proposed advances to improve portable biosensor development include standardizing a limited set of protein scaffolds, and automating ligand-compatibility screening and ligand-protein-interface design.

Enhancing menaquinone-7 biosynthesis by adaptive evolution of Bacillus natto through chemical modulator

Menaquinone-7 (MK-7) is a kind of vitamin K2 playing an important role in the treatment and prevention of cardiovascular disease, osteoporosis and arterial calcification. The purpose of this study is to establish an adaptive evolution strategy based on a chemical modulator to improve MK-7 biosynthesis in Bacillus natto. The inhibitor of 5-enolpyruvylshikimate-3-phosphate synthase (EPSP synthase), glyphosate, was chosen as the chemical modulator to perform the experiments. The final strain ALE-25-40, which was obtained after 40 cycles in 25 mmol/L glyphosate, showed a maximal MK-7 titer of 62 mg/L and MK-7 productivity of 0.42 mg/(L h), representing 2.5 and 3 times the original strain, respectively. Moreover, ALE-25-40 generated fewer spores and showed a higher NADH and redox potential. Furthermore, the mechanism related to the improved performance of ALE-25-40 was investigated by comparative transcriptomics analysis. Genes related to the sporation formation were down-regulated. In addition, several genes related to NADH formation were also up-regulated. This strategy proposed here may provide a new and alternative directive for the industrial production of vitamin K2.

Improving tolerance and 1,3-propanediol production of Clostridium butyricum using physical mutagenesis, adaptive evolution and genome shuffling

Bioconversion efficiency of glycerol to 1,3-propanediol (1,3-PD) by Clostridium butyricum is bottlenecked by its low tolerance to various stressors, especially glycerol as the substrate, 1,3-PD as the end product, and butyric acid as a by-product, which eventually decreases 1,3-PD yield. This study aimed at improving the tolerance and 1,3-PD production capability of C. butyricum using random mutagenesis and evolutionary techniques. Mutagenesis of wild strain by atmospheric room temperature plasma (ARTP) provided the first population with maximum tolerance to 160 g/L glycerol, while microbial microdroplet culture system (MMC)-mediated adaptive laboratory evolution (ALE) generated the second population with tolerance to 100 g/L 1,3-PD. Subsequently, genome shuffling of both populations yielded a final strain, GJH-418, which generated 60.12 g/L1,3-PD with a productivity of 1.72 g/L/h. The transcript analysis of the mutant and wild strains revealed the possible involvement of 8 genes in high tolerance and high 1,3-PD production through either up- or down-regulation.

Synthetic methylotrophic yeasts for the sustainable fuel and chemical production

Global energy-related emissions, in particular carbon dioxide, are rapidly increasing. Without immediate and strong reductions across all sectors, limiting global warming to 1.5 °C and thus mitigating climate change is beyond reach. In addition to the expansion of renewable energies and the increase in energy efficiency, the so-called Carbon Capture and Utilization technologies represent an innovative approach for closing the carbon cycle and establishing a circular economy. One option is to combine CO₂ capture with microbial C₁ fermentation. C₁-molecules, such as methanol or formate are considered as attractive alternative feedstock for biotechnological processes due to their sustainable production using only CO₂, water and renewable energy. Native methylotrophic microorganisms can utilize these feedstock for the production of value-added compounds. Currently, constraints exist regarding the understanding of methylotrophic metabolism and the available genetic engineering tools are limited. For this reason, the development of synthetic methylotrophic cell factories based on the integration of natural or artificial methanol assimilation pathways in biotechnologically relevant microorganisms is receiving special attention. Yeasts like Saccharomyces cerevisiae and Yarrowia lipolytica are capable of producing important products from sugar-based feedstock and the switch to produce these in the future from methanol is important in order to realize a CO₂-based economy that is independent from land use. Here, we review historical biotechnological applications, the metabolism and the characteristics of methylotrophic yeasts. Various studies demonstrated the production of a broad set of promising products from fine chemicals to bulk chemicals by applying methylotrophic yeasts. Regarding synthetic methylotrophy, the deep understanding of the methylotrophic metabolism serves as the basis for microbial strain engineering and paves the way towards a CO₂-based circular bioeconomy. We highlight design aspects of synthetic methylotrophy and discuss the resulting chances and challenges using non-conventional yeasts as host organisms. We conclude that the road towards synthetic methylotrophic yeasts can only be achieved through a combination of methods (e.g., metabolic engineering and adaptive laboratory evolution). Furthermore, we presume that the installation of metabolic regeneration cycles such as supporting carbon re-entry towards the pentose phosphate pathway from C₁-metabolism is a pivotal target for synthetic methylotrophy.

Sustainable production of astaxanthin in microorganisms: the past, present, and future

Astaxanthin (3,3'-dihydroxy-4,4'-diketo-β-carotene) is a type of C40 carotenoid with remarkable antioxidant characteristics, showing significant application prospects in many fields. Traditionally, the astaxanthin is mainly obtained from chemical synthesis and natural acquisition, with both approaches having many limitations and not capable of meeting the growing market demand. In order to cope with these challenges, novel techniques, e.g., the innovative cell engineering strategies, have been developed to increase the astaxanthin production. In this review, we first elaborated the biosynthetic pathway of astaxanthin, with the key enzymes and their functions discussed in the metabolic process. Then, we summarized the conventional, non-genetic strategies to promote the production of astaxanthin, including the methods of exogenous additives, mutagenesis, and adaptive evolution. Lastly, we reviewed comprehensively the latest studies on the synthesis of astaxanthin in various recombinant microorganisms based on the concept of microbial cell factory. Furthermore, we have proposed several novel technologies for improving the astaxanthin accumulation in several model species of microorganisms.

Application of Microalgal Stress Responses in Industrial Microalgal Production Systems

Adaptive laboratory evolution (ALE) has been widely utilized as a tool for developing new biological and phenotypic functions to explore strain improvement for microalgal production. Specifically, ALE has been utilized to evolve strains to better adapt to defined conditions. It has become a new solution to improve the performance of strains in microalgae biotechnology. This review mainly summarizes the key results from recent microalgal ALE studies in industrial production. ALE designed for improving cell growth rate, product yield, environmental tolerance and wastewater treatment is discussed to exploit microalgae in various applications. Further development of ALE is proposed, to provide theoretical support for producing the high value-added products from microalgal production.

Cellulase production and efficient saccharification of biomass by a new mutant Trichoderma afroharzianum MEA-12

BACKGROUND

Cellulase plays a key role in converting cellulosic biomass into fermentable sugar to produce chemicals and fuels, which is generally produced by filamentous fungi. However, most of the filamentous fungi obtained by natural breeding have low secretory capacity in cellulase production, which are far from meeting the requirements of industrial production. Random mutagenesis combined with adaptive laboratory evolution (ALE) strategy is an effective method to increase the production of fungal enzymes.

RESULTS

This study obtained a mutant of Trichoderma afroharzianum by exposures to N-methyl-N'-nitro-N-nitrosoguanidine (MNNG), Ethyl Methanesulfonate (EMS), Atmospheric and Room Temperature Plasma (ARTP) and ALE with high sugar stress. The T. afroharzianum mutant MEA-12 produced 0.60, 5.47, 0.31 and 2.17 IU/mL FPase, CMCase, pNPCase and pNPGase, respectively. These levels were 4.33, 6.37, 4.92 and 4.15 times higher than those of the parental strain, respectively. Also, it was found that T. afroharzianum had the same carbon catabolite repression (CCR) effect as other Trichoderma in liquid submerged fermentation. In contrast, the mutant MEA-12 can tolerate the inhibition of glucose (up to 20 mM) without affecting enzyme production under inducing conditions. Interestingly, crude enzyme from MEA-12 showed high enzymatic hydrolysis efficiency against three different biomasses (cornstalk, bamboo and reed), when combined with cellulase from T. reesei Rut-C30. In addition, the factors that improved cellulase production by MEA-12 were clarified.

CONCLUSIONS

Overall, compound mutagenesis combined with ALE effectively increased the production of fungal cellulase. A super-producing mutant MEA-12 was obtained, and its cellulase could hydrolyze common biomasses efficiently, in combination with enzymes derived from model strain T. reesei, which provides a new choice for processing of bioresources in the future.

Engineering robust microorganisms for organic acid production

Organic acids are an important class of compounds that can be produced by microbial conversion of renewable feedstocks and have huge demands and broad applications in food, chemical, and pharmaceutical industries. An economically viable fermentation process for production of organic acids requires robust microbial cell factories with excellent tolerance to low pH conditions, high concentrations of organic acids, and lignocellulosic inhibitors. In this review, we summarize various strategies to engineer robust microorganisms for organic acid production and highlight their applications in a few recent examples.