RiboScan: An Aquaculture-Focused Bioinformatics Tool for Codon Optimization and Translational Risk Assessment

The efficient expression of recombinant proteins in aquaculture fish poses a significant challenge, partly due to the lack of dedicated bioinformatics tools for species-specific codon usage analysis and optimization. RiboScan (v1.0.0), a portable, single-file command-line tool executed in Python, was designed in this study, for mRNA codon diagnostics and optimization. RiboScan supports ten species, including five major aquaculture fish. High-risk windows that are computationally predicted to impair translational efficiency are identified based on two complementary metrics, namely, the Relative Adaptiveness Index (RAI) and estimated NN-based stability score, which are calculated using a sliding-window approach. An optimization module is used to replace the suboptimal codons in high-risk regions with host-specific synonymous codons, which are selected based on their high RAI values, leaving the encoded protein sequence unaltered. The efficacy of RiboScan was evaluated using coding sequences (CDSs) from three representative aquaculture fish genes, namely, Salmo salar growth hormone (gh; GenBank accession: M21573), Oreochromis niloticus interleukin-1 beta (il1b; GenBank accession: OR432591), and Ctenopharyngodon idella beta-actin (actb; GenBank accession: M25013). The tool identified 25–30 high-risk windows per CDS pre-optimization, whereas no high-risk windows were detected in any of the CDSs post-optimization. The mean RAI for Sal. salar gh, Or. niloticus il1b, and Ct. idella actb increased from 0.189 to 0.339, 0.126 to 0.270, and 0.140 to 0.231, respectively. RiboScan’s main analytical workflow requires no third-party dependencies, as it uses only the Python standard library. In addition, the tool yields publication-ready figures and structured comma-separated values (CSV) output files. RiboScan can be used to perform species-specific codon optimization for major aquaculture fish, and provides a practical computational framework for designing recombinant proteins, vaccines, and other engineered genetic constructs, thus contributing to aquaculture biotechnology research.