Enhancing Microbial Resilience: The Role of Adaptive Laboratory Evolution in Industrial Biotechnology

미생물 내성 강화: 산업 생명공학에서의 적응 실험실 진화의 역할

Abstract

Industrial biotechnology leverages microorganisms such as Saccharomyces cerevisiae and Escherichia coli for sustainable production of chemicals, fuels, and pharmaceuticals. However, despite their potential, microbial production faces challenges due to environmental stressors, which impede efficiency and economic feasibility. While traditional genetic engineering offers solutions, it often fails to create robust strains for industrial conditions. Adaptive laboratory evolution (ALE) has emerged as a potent strategy to enhance microbial resilience by mimicking natural selection under controlled conditions. ALE has successfully improved tolerance to stressors such as toxic compounds, extreme pH, and high temperatures in various microorganisms. In yeasts, ALE has enhanced acetic acid and furfural tolerance, which is crucial for bioethanol production. Similarly, in E. coli, ALE has increased resistance to acid stress and improved production of succinic acid and L-serine. In lactic acid bacteria, ALE has boosted lactic acid production and strain stability under thermal and freeze-thaw stresses, benefiting both industrial and probiotic applications. Corynebacterium glutamicum has also shown significant improvements in growth rates, stress tolerance, and production capabilities through ALE. These advancements underline ALE's role in optimizing microbial strains for diverse industrial processes, making it a powerful tool in microbial biotechnology. This review highlights the latest applications and methods of ALE, emphasizing its impact on industrial microorganisms and potential for future research in sustainable bioproduction.

산업 생명공학은 지속 가능한 화학물질, 연료, 의약품 생산을 위해 효모와 대장균과 같은 미생물을 활용합니다. 그러나 미생물 생산은 환경 스트레스로 인해 효율성과 경제성이 저해되는 문제에 직면하고 있다. 전통적인 유전공학은 많은 해결책을 제공하지만, 종종 산업적 조건에서 견딜 수 있는 강력한 균주를 만드는 데 어려움이 있다. 적응 실험실 진화는 자연 선택을 모방하여 제어된 환경에서 미생물 내성을 향상시킬 수 있는 좋은 전략으로 부상했다. 적응 실험실 진화는 다양한 미생물에서 유해 화합물, 극한의 pH, 고온 등의 스트레스에 대한 내성을 성공적으로 향상시켰다. 효모에서는 적응 실험실 진화가 에탄올 생산에 중요한 아세트산 및 퓨프랄 내성을 향상시켰다. 또한, 대장균에서는 적응 실험실 진화가 산 스트레스에 대한 저항성을 증가시키고 숙신산과 세린의 생산을 개선했다. 젖산균에서는 적응 실험실 진화가 젖산 생산, 열 및 냉동-해동 스트레스 하에서의 균주 안정성을 증대시켜, 산업적 및 프로바이오틱 응용 분야에 혜택을 주었다. 코리네박테리움 글루타미컴 또한 적응 실험실 진화를 통해 성장률, 스트레스 내성 및 생산 능력에서 상당한 개선을 보였다. 이러한 발전은 다양한 산업 공정을 최적화하는 데 있어 적응 실험실 진화의 역할을 강조하며, 미생물 생명공학에서 강력한 도구임을 입증한다. 본 논문은 적응 실험실 진화의 최신 응용 및 방법을 조명하며, 산업 미생물에 미치는 영향과 지속 가능한 생물 생산을 위한 미래 연구의 잠재력을 보여주었다.

Introduction

Industrial biotechnology has revolutionized the production of chemicals, fuels, pharmaceuticals, and other valuable products by utilizing microorganisms as biological factories [31]. By harnessing the metabolic capabilities of bacteria, yeast, and other microorganisms, this approach enables the efficient conversion of raw materials into desired products [31, 42]. For instance, yeasts like Saccharomyces cerevisiae are widely used in the production of bioethanol from biomass [35, 67], while Escherichia coli serves as a platform for producing high-value pharmaceuticals such as insulin and therapeutic proteins [1, 38]. These bioprocesses offer sustainable and environmentally friendly alternatives to traditional chemical manufacturing, often requiring less energy and producing fewer pollutants. However, the efficiency and viability of microbial production processes face significant challenges due to the inherent toxicity of substrates, the accumulation of inhibitory by-products, extreme pH levels, and other environmental stressors [37, 69]. These factors can severely impede microbial growth and productivity, thereby limiting the economic feasibility of bioprocesses.

To address the challenges of microbial production, Adaptive Laboratory Evolution (ALE) has emerged as a powerful strategy [14, 17]. ALE leverages natural selection principles to evolve microbial populations under controlled laboratory conditions by continuously exposing them to specific stressors relevant to industrial processes, such as toxic compounds, extreme pH levels, or high temperatures [48, 50, 65]. This method facilitates the selection of strains with improved resistance and robustness. ALE begins by subjecting a diverse microbial population to a defined selective pressure, allowing those that can tolerate the stress to survive and reproduce, passing on beneficial traits. This cycle, repeated over many generations with gradually increasing stressor intensity, helps identify mutations that confer tolerance to toxic substrates or extreme conditions. ALE is believed to enhance the stress resilience of microorganisms and optimizes metabolic pathways, leading to improved yield and productivity.

This method has produced strains that withstand high concentrations of fermentation inhibitors, like acetic acid and furfural, or operate efficiently at extreme pH levels. Over the last decade, ALE has been widely employed with various microorganisms to enhance resistance and production capabilities. For example, strains of Saccharomyces cerevisiae have evolved to tolerate inhibitors in lignocellulosic hydrolysates, enhancing their ability to assimilate methanol, resist xenobiotics, and withstand furfural [11, 16, 41, 66]. Reyes et al. demonstrated a three-fold increase in carotenoid production in S. cerevisiae through short-term evolution with periodic hydrogen peroxide shocks, from 6 mg/g to 18 mg/g dry cell weight [47]. Recent research by Sánchez-Adriá et al. also showed improved acetic acid tolerance in S. cerevisiae for sourdough fermentation, resulting in increased tolerance in several clones [48]. Numerous resistant strains of Escherichia coli have been developed through ALE to withstand various stressors, including UV light, temperature fluctuations, freezing, osmotic pressure, and exposure to ethanol, isobutanol, and butanol [9, 10]. A study conducted by Du et al. showed that after 800 generations, E. coli MG1655 exhibited an 18% increase in growth rate at pH 5.5, while still maintaining growth at pH 7 [10]. Additionally, Lactobacillus species have shown enhanced lactic acid productivity from xylose-rich media at low pH [8]. Meanwhile, Corynebacterium glutamicum has exhibited increased methanol tolerance and improved glutarate production [45, 61].

In this paper, we present the latest applications of ALE in the development of industrial microorganisms with enhanced resistance and evaluate their effectiveness. In more details, we focus on ALE applications in widely used industrial microorganisms, including E. coli, lactic acid bacteria, yeasts, and Corynebacterium glutamicum. We analyze the methods used in ALE experiments, i.e., experimental design, selective pressures, and analytical techniques, while highlighting key case studies that demonstrate the effectiveness of ALE in enhancing microbial resistance to toxic environments, extreme pH levels, and other industrial stressors. Given the growing demand for sustainable and economically viable bioprocesses, this review aims to illustrate how ALE serves as a promising strategy for optimizing industrial microorganisms. By comparing the benefits and challenges of ALE and traditional genetic engineering approaches, we aim to underscore ALE's unique advantages in evolving microorganisms for complex industrial applications. Ultimately, we expect to provide valuable insights into the strategies and outcomes of ALE, encouraging further research and applications in the field of industrial biotechnology.

Adaptive Laboratory Evolution Method

Generally, ALE mimics the principles of natural selection to evolve microbial populations under controlled laboratory conditions. ALE experiments have employed a wide range of stress conditions to evolve microbial strains with enhanced performance under industrial settings. These stressors include high concentrations of toxic compounds (e.g., acetic acid, furfural, ethanol), extreme temperature fluctuations, osmotic stress, oxidative stress, nutrient limitations, and extreme pH levels [15]. By subjecting microbial populations to these varied stress conditions, ALE enables the evolution of strains that are highly adaptable and resilient across different industrial processes. This versatility underscores the flexibility of ALE in tailoring microorganisms for diverse applications, from biofuel production to pharmaceutical manufacturing. The process begins with selecting target traits and establishing stress conditions. Microorganisms are then cultivated under these stresses, followed by serial passaging to ensure continuous exposure. Throughout the process, scientists monitor and analyze the populations, ultimately characterizing the evolved strains (Fig. 1). Common methods used in ALE include serial transfer, colony transfer, and continuous culture, as illustrated in Fig. 1.

Fig. 1. General adaptive laboratory evolution methods.

Serial transfer

In serial transfer experiments, a small aliquot of a growing culture is periodically transferred to fresh media containing the same stressors for an additional round of growth. This setup has the advantages of cheap equipment and the ease of massive parallel cultures. This method allows the population to continuously grow and adapt to the stress conditions over many generations. Although batch cultivation offers several advantages, it also has notable drawbacks. These include inconsistent population densities, fluctuating growth rates, nutrient supply issues, and varying environmental factors, such as pH and levels of dissolved oxygen [9]. In a study by Zhao et al., a modified strain of E. coli WL203 was evolved using serial transfer methods over three months in LB-xylose medium, resulting in the enhanced strain WL204 [70]. This evolution process significantly improved anaerobic growth and achieved a production of 62 g/l of L-lactic acid from xylose, with a maximum production rate of 1.631 g/l/hr. In another study conducted by Hong et al., three evolved S. cerevisiae strains (62A, 62B, and 62C) was developed after 62 days of serial transfers in galactose medium, resulting in a 24% increase in growth rates, 18‒36% higher galactose uptake, and 31‒170% increase in ethanol production [18].

Colony transfer

Colony transfer selects a single colony from an agar plate and transfers it to fresh plates over generations, allowing un-biased mutations to accumulate without selective pressures [6, 17]. This method is useful for aggregating organisms and controlled experiments, but is labor-intensive and offers less genetic control compared to engineering [17]. Charusanti et al. developed a competition-based ALE method to improve antibiotic discovery by co-culturing Streptomyces clavuligerus with methicillin-resistant Staphylococcus aureus, which led to a strain capable of producing holomycin, unlike the wild-type [6]. Another study by Maeda investigated Mycobacterium smegmatis evolution against 10 anti-TB drugs and identified mutations that confer resistance to meropenem and linezolid [29]. This work revealed 24 drug pairs with cross-resistance and 18 with collateral sensitivity, highlighting crucial insights for addressing drug-resistant tuberculosis.

Fig. 2. General adaptive laboratory evolution processes.

Continuous culture experiments

This method stabilizes microbial populations by continuously adding fresh media and removing waste, ensuring consistent selection pressure that promotes beneficial adaptations. It also allows for real-time monitoring and is scalable for industrial applications. However, maintaining multiple replicates can be costly, and cells may form biofilms in bioreactors, complicating the process. A study by Wright et al. aimed to enhance acetic acid tolerance in S. cerevisiae RWB218 for bioethanol production [64]. By adopting two strategies, sequential batch and continuous cultivation, strains with acetic acid tolerance of 5 g/l and 6 g/l were obtained after 400 generations, respectively.

Physiological and genetic traits analyses

To better understand the mechanisms underlying the improved traits in evolved strains, various physiological and genetic analyses are commonly employed post-evolution. Physiological analysis, such as growth rate measurements, substrate utilization profiling, and stress tolerance assays, helps quantify the phenotypic improvements in evolved strains. Meanwhile, genomic sequencing, transcriptomics, and proteomics are utilized to identify the specific mutations and regulatory changes that occur during ALE. By correlating these mutations with observed phenotypes, researchers gain insights into the genetic basis of improved stress resistance and productivity. These analyses provide valuable information on how ALE drives adaptive changes in microbial strains, enabling a more targeted approach in future strain engineering efforts.

Applications of Adaptive Laboratory Evolution to Microorganisms

Yeast

Yeasts are highly resilient organisms with tolerance to low pH environments and the ability to perform post-translational protein modifications. Supported by well-studied genetic mutant libraries and comprehensive omics data, they can adapt to various stress conditions. Recognized as safe, yeasts play a crucial role in industrial bioproduction. ALE leverages these strengths to enhance yeast strains for a wide range of biotechnological applications. For instance, Sánchez-Adrián et al. demonstrated effectiveness of ALE in enhancing acetic acid tolerance of S. cerevisiae for sourdough fermentation [48]. They alternated growth cycles of two yeast strains in synthetic complete medium with and without acetic acid, gradually increasing the concentration to 120 mM over 200 generations. Myriocin was added to one group to accelerate adaptation. Although this process improved acetic acid tolerance, it also gave rise to increased lactic acid sensitivity. Four clones were selected based on their CO₂ production potential in sourdough conditions: two exhibited instability and lactic sensitivity after several growth cycles, while the other two maintained acetic tolerance without compromising growth in lactic environments. The integrated study of ALE and whole genome analysis played an instrumental role in uncovering genetic determinants of chemical resistance [41]. Sequence analysis in S. cerevisiae identified numerous genes and amino acids contributing to chemical resistance, particularly highlighting the role of transcription factors. Notably, 25% of the resistance was linked to mutations in a specific domain of the Zn₂C₆ transcription factors YRR1 and YRM1. This study emphasizes the critical role of transcription factors in antifungal resistance and the challenges in developing effective antifungal treatments. Similarly, furfural, a byproduct of lignocellulose pretreatment, imposes inhibitory effects on S. cerevisiae in bioethanol production. Yao et al. addressed this by developing a strain named 12‒1 with enhanced furfural resistance through ALE [66]. This strain showed a 36 hr reduction in lag phase and a 6.7% increase in ethanol conversion rate under 4 g/l furfural. Further investigation using CRISPR/Cas9 to create the ADR1_1802 mutant, guided by whole genome resequencing, revealed a 20 hr reduction in lag time compared to the reference strain. The ADR1_1802 mutant also substantiate increased transcription of the genes GRE2 and ADH6 by 53.7% and 45.0%, respectively, linking the enhanced furfural tolerance to accelerated furfural degradation and an improved stress response. The flexibility of ALE has also spurred research into various nontraditional yeast species, e.g., improved CO₂ utilization with a growth rate increase from 0.008 to 0.018/hr in Pichia pastoris [12, 13], better ethanol (9% to 11.5%) and SO₂ tolerance in Torulaspora delbrueckii [5], inhibitors (acetic acid, furfural, and vanillin) or 10% ethanol tolerance in Kluyveromyces marxianus [16, 34], a fourfold increase in ethanol production and improved sugar utilization in Barnettozyma californica [39], enhanced H₂O₂ detoxification and growth in Candida glabrata [19], increased growth and lipid production in sugarcane bagasse hydrolysate in Rhodosporidium toruloides [3], gained resistance to posaconazole and other azoles in Candida albicans [23], and developed higher tolerance to ferulic acid in Yarrowia lipolytica [63]. Overall, ALE is a powerful tool for enhancing yeast strains, offering significant benefits across various industrial applications. By harnessing the natural adaptability of yeast, ALE enables the development of strains with improved stress tolerance, resistance, and production capabilities. This, in turn, supports advancements in bioproduction and antifungal treatment development. A summary of ALE applications in yeast can be found in Table 1.

Table 1. Applications of adaptive laboratory evolution to yeasts

Escherichia coli

E. coli has been extensively used in bioproduction of proteins, enzymes, and a plethora of metabolites, owing to its well-understood genetics and ease of manipulation. ALE exposes E. coli to controlled stressors over many generations to uncover key genetic mutations and metabolic changes that boost its resilience and productivity. This systematic approach helps researchers identify the precise molecular adaptations and evolutionary strategies that improve E. coli’s performance in industrial applications. A study by Du et al. demonstrated the improvement of E. coli under acid stress via ALE [10]. Cultures of E. coli MG1655 were grown at pH 5.5 in glucose minimal medium with reduced magnesium and buffered with 150 mM MES, while control cultures were maintained at pH 7. An automated system tracked OD and transferred cells at OD ≈ 0.3, with pH monitored to ensure proper buffering. The evolution process lasted 35 days, equivalent to 800 generations. The resulted strain represented an 18% increase in growth rate at pH 5.5 (from 0.77 to 0.91/hr) and a slightly higher growth rate at pH 7 (1.0/hr). In another study by Jiang et al., ALE was used to enhance E. coli MLB for succinic acid production [20]. Strain MLB, which initially struggled under anaerobic conditions, was evolved using a two-stage fermentation process with acetate as the sole carbon source. The yielded strain MLB46-05 exhibited improved growth and tolerance to high acetate concentrations and accumulated 111 g/l of succinic acid with a yield of 0.74 g/g glucose. Transcriptome analysis indicated that upregulation of the glyoxylate shunt and stress response factors is contributed to these improvements. To enhance L-serine tolerance in E. coli, Mundhada et al. introduced ALE on strains with deleted serine degradation pathways [36]. The original quadruple deletion strain Q1, which produced 0.42 g/g glucose of L-serine, struggled with high serine concentrations. Over 45 days, ALE was performed on five parallel populations, gradually increasing L-serine levels from 3 to 100 g/l. This evolution process outstandingly improved growth rates under high L-serine conditions. The most resilient strain, ALE-5, demonstrated up to 7.5 times higher growth rates than the wild-type MG1655 at 50 g/l serine and up to 34 times higher compared to a UV-mutagenized strain. These generated strains performed exceptionally well in both batch and fed-batch fermentations, underscoring ALE's effectiveness in boosting L-serine tolerance and production. Assimilation of methanol in E. coli was implemented via ALE. Sun et al. started with the strain E. coli X5, which showed better methanol assimilation but had lower cell density compared to the parental strain X1 [54]. To accelerate cell growth, they initially grew the strain X5 in Hi-Def Azure medium, gradually replacing it with M9 minimal medium. After 28 passages, they isolated a superior variant Ev17, which displayed a final cell density of 0.71 and a 90.9% increase in biomass from methanol, representing an 80% improvement over the strain X5. Ev17 also consumed 1.62 g/l of methanol, which is 60.4% more than X5. Furfural is a highly toxic compound that significantly hinders microbial growth in industrial biotechnology. Zheng et al. aimed to enhance furfural tolerance in E. coli using CREATE (CRISPR-enabled trackable genome engineering) technology to construct a global regulator library, accelerating ALE [71]. The initial strains were cultivated with 0.9 g/l furfural, gradually increasing to 3.2 g/l over 31 rounds of selection. This process notably enhanced furfural tolerance, with evolved strains tolerating up to 3.2 g/l furfural after 53 rounds of transfers, compared to the control strain. Evolved strains KQ51 and KQ52 exhibited remarkable growth, with KQ52 tolerating up to 4.7 g/l furfural, the highest reported for E. coli. These studies collectively highlight the ALE potency in enhancing tolerance of E. coli to various industrial stressors. Through ALE, noteworthy performances have been made in E. coli, including enhanced acid stress resistance, increased production of succinic acid and L-serine, optimized methanol assimilation, and improved tolerance to highly toxic compounds like furfural. These advancements underscore the potential of ALE as a powerful tool for refining E. coli for diverse biotechnological applications. A summary of ALE applied to E. coli is provided in Table 2.

Table 2. Applications of adaptive laboratory evolution to Eschericia coli

Lactic acid bacteria

Lactobacillus strains widely used for industrial lactic acid production require high titers, productivity, yield, and optical purity, and the ability to operate at elevated temperatures. Tian et al. addressed this challenge by utilizing ALE, which led to the creation of a strain capable of thriving at 45℃and producing 221 g/l of L-lactic acid [57]. Lactobacillus also serves as a starter or probiotic, making effective preservation crucial for maintaining its viability and metabolic activity. Freezing is a common preservation method, but ice crystal formation can damage cells and reduce their effectiveness. To tackle this issue, Kwon et al. employed ALE to create a freeze-thaw tolerant strain of L. rhamnosus GG [24]. After 150 cycles of freeze-thaw-growth, the evolved mutants displayed enhanced survival, faster growth, and shorter lag phases. Genome sequencing revealed genetic modifications that improved cellular fluidity and stress tolerance. Moreover, heat stress during dehydration poses a notable challenge for probiotics. Bommasamudram et al. used ALE to enhance heat tolerance in two Lactobacillus strains, Lacticaseibacillus casei N and L. helveticus NRRL B-4526 [2]. Subjecting these strains to 45℃ over 500 generations boosted a two-fold increase in biomass and improved probiotic qualities. L. casei N-45 showed superior tolerance to acidic conditions, bile, and digestive juices, alongside enhanced salt tolerance. Other studies have also highlighted ALE’s impact on Lactobacillus strains: doubled lactic acid production and increased xylose consumption in Lactiplantibacillus pentosus [8]; improved lactic acid production by 59% and antioxidant activity in Lacticaseibacillus paracasei [33]; better survival, lactate, acetate production, and bile tolerance in various L. casei strains [32, 58, 68]; and increased lactic acid production by 1.8-fold and enhanced H⁺-ATPase activity in L. delbrueckii [52]. These studies underscore ALE's power in developing robust Lactobacillus strains for industrial bioproduction. Recent advances in Lactobacillus based on ALE studies are presented in Table 3.

Table 3. Applications of adaptive laboratory evolution to lactic acid bacteria

Corynebacterium glutamicum

As a cornerstone of industrial biotechnology, C. glutamicum benefits greatly from ALE, which enhances its metabolic efficiency and strain robustness through targeted evolutionary adjustments. For instance, ALE has used to accelerate growth on glucose minimal media, resulting in a 26% higher growth rate after approximately 630 generations and a 42% higher growth rate after 1,500 generations, with pivotal mutations in genes such as pyk, fruK, corA, gntR1^E70K, and ramA^A52V[43, 62]. ALE also enhanced the thermal tolerance of C. glutamicum, with whole genome analysis (WGA) revealing that the missense mutations in glmU^E295K and otsA^R328H are associated with the increased thermal stress resistance [40]. Moreover, ALE improved tolerance to inhibitors found in corn stover hydrolysate and methanol, and enhanced cell growth on cellobiose and D-xylose as carbon sources through similar evolutionary processes [4, 26, 28, 46, 60]. Likewise, anthranilate tolerance was increased through ALE [22]. Sequential batch fermentations with escalating anthranilate concentrations yielded strains capable of withstanding up to 25.9 g/l of anthranilate. As a result, the evolved strains exhibited improved growth and biomass production under high anthranilate stress. Meanwhile, substrate utilization and small molecule production capabilities of C. glutamicum also have been significantly enhanced through ALE. For example, Schwentner et al. evolved the Δpyc Δppc C. glutamicum and obtained a mutant with an increased growth rate in glucose-based medium, which was found to be related to icd^G407S mutation, and subsequently applied it for L-valine production [51]. Accumulation of fatty acid was enabled through ALE, attributed to genetic alteration in fasR^S20D, fasA^upC63G, fasA^A2623V, and accD3^A433T[55, 56]. Biosensor-driven ALE allowed us to develop evolved strains with both approximately 25% increased L-valine production and a 3- to 4-fold decrease in L-alanine formation. WGA revealed that a loss-of-function in urease activity (ureD^E188*) resulted in a significant increase in L-valine titer, up to 100% [30]. Accelerated glutarate production in gdh-deleted C. glutamicum was achieved through ALE, generating faster glutarate-coupled growth rates from 0.10/hr to 0.17/hr and doubling of volumetric productivity to 0.18 g/l/hr [45]. The generated strain boosted production of 22.7 g/l of glutarate with a yield of 0.23 g/g in a 2-l bioreactor. Overall, ALE has significantly advanced the capabilities of C. glutamicum in industrial applications (Table 4) [53]. Through targeted evolutionary strategies, ALE has improved growth rates, stress tolerance, and production efficiency. These attainments underline the critical role of ALE in optimizing microbial strains for various industrial processes.

Table 4. Applications of adaptive laboratory evolution to Corynebacterium glutamicum

Discussion

The traditional approach of genetic engineering has been widely utilized to enhance microbial performance by introducing specific genetic modifications aimed at improving productivity, resistance to inhibitors, or substrate utilization. While this method has led to significant breakthroughs, it is often constrained by the requirement for prior knowledge of target genes or pathways, as well as the challenges of engineering microbes to survive in complex, multifactorial stress environments. In contrast, ALE provides a complementary approach that does not require pre-existing knowledge of specific genetic targets and allows for the discovery of novel mutations through natural selection. Unlike genetic engineering, which often focuses on modifying a limited number of genes, ALE enables the simultaneous optimization of multiple traits through the gradual accumulation of beneficial mutations. This holistic approach makes ALE particularly well-suited for addressing the complex and multifaceted stresses commonly encountered in industrial settings.

Although ALE presents a promising approach to overcoming microbial resistance, there are several limitations that must be addressed to fully realize its potential. The first major limitation is the time-intensive nature of the process. Depending on the stress factors and desired traits, ALE experiments may take a considerable amount of time to yield significant results [9]. Additionally, the randomness of mutations induced by ALE poses a challenge, as not all genetic changes may contribute to the desired phenotype [25]. Some mutations may even lead to undesirable traits, necessitating additional rounds of selection or further genetic modifications to fine-tune the outcomes [7]. The scalability of strains developed using ALE may also be limited. While ALE has been successfully applied in small-scale laboratory environments, scaling it up for industrial applications can be more complex [59]. Furthermore, ALE may not always yield the most efficient strains for every application. For instance, while a strain may evolve to tolerate high concentrations of a specific toxic subtance, it might simultaneously exhibit reduced growth rates or production efficiency, negating the benefits of increased resilience [44].

On the other hand, the combination of ALE with traditional genetic engineering, systems biology, and other methods could offer substantial synergies in strain development. Introducing mutations through genetic engineering to make organisms more responsive to ALE could accelerate the evolutionary process [27]. ALE can evolve strains with broad stress tolerances, which can then be further optimized through targeted genetic modifications for specific traits [9]. High-throughput omics technologies can also be integrated with ALE to map the mutations that occur during evolution, allowing for faster identification of beneficial genetic changes and a better understanding of how these mutations affect broader metabolic networks [49].

Conclusion

ALE is a powerful tool in microbial biotechnology, enabling targeted evolutionary improvements in microbial strains for various industrial applications. By applying natural selection in controlled environments, ALE enhances growth, stress tolerance, and production efficiency in organisms like yeast, E. coli, Lactobacillus, and C. glutamicum. In yeast, ALE has improved tolerance to acetic acid and furfural, boosting bioethanol production. In E. coli, ALE increased yields of key metabolites like succinic acid and L-serine by optimizing stress resistance. Lactobacillus strains have shown better heat and freeze-thaw tolerance, leading to enhanced lactic acid production. In C. glutamicum, ALE improved growth, stress tolerance, and production of compounds like L-valine and glutarate. Taken together, ALE is a powerful tool for advancing microbial strains across diverse applications. Its ability to drive specific and beneficial adaptations makes it indispensable for optimizing yeasts, E. coli, lactic acid bacteria, and C. glutamicum, thereby enhancing their roles in industrial biotechnology and bioproduction.