Evolutionarily Distinct Enzymes Uncovered Through Sequence Similarity Network Analysis of De Novo Transcriptomes from Underexplored Protist Axenic Cultures

Protists represent a vast yet underexplored reservoir of enzymatic diversity across the eukaryotic tree of life. In this study, we established axenic strains of diverse protists from four major eukaryotic supergroups using single-cell isolation and generated de novo transcriptomes for each strain, as reference genomes or transcriptomes are not available for these strains. As a test case for industrial enzyme discovery, we targeted nine enzyme classes used in pulp processing and evaluated whether protist-derived sequences occupy underrepresented sequence space relative to major public databases. Functional annotation combined with Sequence Similarity Network analysis revealed multiple clusters composed exclusively of protist-origin sequences, indicating candidate enzymes with high sequence-level novelty. These results suggest that protists may provide a practical resource for expanding the repertoire of industrially relevant enzymes and prioritizing targets for further characterization. However, additional in silico analyses and experimental validation will be required to determine whether these sequence-divergent candidates exhibit properties that meet industrial requirements.