Natural diversity-guided catalytic-core chimerism engineers a rapid and inhibitor-tolerant reverse transcriptase

Reverse transcriptases (RTs) are essential components of RNA-based molecular technologies, yet their practical performance is often constrained by trade-offs between catalytic speed, thermal stability, and tolerance to inhibitory substances. Conventional optimization via mutagenesis or directed evolution often improves individual traits but struggles to integrate multiple traits within a single enzyme. Here, we applied catalytic-core recombination, guided by natural sequence diversity and diagnostic performance criteria, to recover reverse transcriptase phenotypes that would be difficult to obtain by single-trait optimization alone.

Starting from 1,028 sequences, 24 representative RT variants were used to generate a library of chimeras by swapping a critical 405-residue polymerase domain into a validated M-MuLV scaffold. We identified chRT V18 as the lead candidate, demonstrating consistent activity across a broad temperature range (40-70 °C). In addition, chRT V18 enabled efficient and linear cDNA synthesis in as little as 1 min at elevated temperatures, while maintaining strong resistance to clinically relevant inhibitors. Beyond RT-qPCR, chRT V18 supported high-temperature RT-LAMP at 69 °C, a regime typically incompatible with conventional RTs, enabling improved specificity and rapid amplification. When formulated into one-step RT-qPCR master mixes, chRT V18 achieved low limits of detection and full concordance with IVD-approved assays, while reducing reverse transcription time by 90%, enabling shorter time-to-result.

Natural diversity-guided catalytic-core chimerism enabled the development of a rapid, inhibitor-tolerant reverse transcriptase with an unusual combination of broad temperature compatibility, minute-scale reverse transcription, and resilience to clinically relevant inhibitors. Beyond the properties of chRT V18 itself, the results support modular recombination of evolutionarily optimized domains as a practical engineering strategy for integrating multiple performance traits in complex enzymes.