Adaptive laboratory evolution (ALE) is a powerful strategy for enhancing microbial traits by harnessing the principles of natural selection in controlled environments. It has enabled significant advances in microbial growth, stress tolerance, and product yield across a variety of organisms, while also providing insight into evolutionary mechanisms. However, the traditional ALE workflow is time- and resource-intensive, relying on prolonged cultivation to allow beneficial mutations to emerge and be maintained in the population. To improve this, a range of evolutionary engineering tools have been developed to accelerate ALE by increasing mutation rates and genetic diversity in evolving strains. In this review, we explore the core parameters that shape ALE, such as selection pressure, transfer method, and passage size, and provide a comprehensive overview of both established and emerging acceleration methods. These techniques are categorized based on portability (applicability across different microorganisms), genomic targetability (specificity of mutagenesis), and reliability (minimal off-target mutations and mutational reproducibility), with the resulting framework for selecting the most suitable approach summarized in Table 3 at the end of the review. We highlight the growing potential of accelerated ALE and outline future directions, including the integration of genome-wide and targeted mutagenesis, computational modeling, laboratory automation, and broader application beyond model organisms. This review aims to streamline the use of accelerated ALE, unlocking its true potential for advancing microbial strain engineering.
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