Identifying Amino Acid Overproducers Using Rare-Codon-Rich Markers.

To satisfy the ever-growing market for amino acids, high-performance production strains are needed. The amino acid overproducers are conventionally identified by harnessing the competitions between amino acids and their analogs. However, this analog-based method is of low accuracy, and proper analogs for specific amino acids are limited. Here, we present an alternative strategy that enables an accurate, sensitive, and high-throughput screening of amino acid overproducers using rare-codon-rich markers. This strategy is inspired by the phenomenon of codon usage bias in protein translation, for which codons are categorized into common or rare ones based on their frequencies of occurrence in the coding DNA. The translation of rare codons depends on their corresponding rare transfer RNAs (tRNAs), which cannot be fully charged by the cognate amino acids under starvation. Theoretically, the rare tRNAs can be charged if there is a surplus of the amino acids after charging the synonymous common isoacceptors. Therefore, retarded translations caused by rare codons could be restored by feeding or intracellular overproductions of the corresponding amino acids. Under this assumption, a selection or screening system for identifying amino acid overproducers is established by replacing the common codons of the targeted amino acids with their synonymous rare alternatives in the antibiotic resistance genes or the genes encoding fluorescent or chromogenic proteins. We show that the protein expressions can be greatly hindered by the incorporation of rare codons and that the levels of proteins correlate positively with the amino acid concentrations. Using this system, overproducers of multiple amino acids can be readily screened out from mutation libraries. This rare-codon-based strategy only requires a single modified gene, and the host is less likely to escape the selection than in other methods. It offers an alternative approach for obtaining amino acid overproducers.