Long vs. short read sequencing for microbial ecology of sedimentary environments: a case study from Lake Arnon, Switzerland

Abstract

Microbial communities in the subsurface biosphere remain poorly characterized because many taxa lack cultured representatives and genomic references, limiting the accuracy of taxonomy inferred from short-read 16S ribosomal RNA gene sequencing. We tested the hypothesis that long-read 16S sequencing improves taxonomic resolution and detection of rare lineages compared with short-read approaches in low-biomass, diversity-rich sediments. Microbial communities from a sediment core of Lake Arnon (Switzerland) were analyzed using both long-and short-read sequencing, and community composition, diversity metrics, and taxonomic resolution were compared. Sequencing technology influenced observed community structure, but sediment depth also exerted a strong effect. Taxonomic profiles were broadly consistent across methods for most bacterial groups, whereas archaeal diversity was underrepresented in long-read datasets due to primer mismatches. When detected, long reads provided higher taxonomic resolution, frequently to species level, improving ecological interpretation and inference of metabolic potential. Finer-scale analyses, including species contributions to beta diversity and co-occurrence networks, showed greater specificity with long reads. These results demonstrate that long-read sequencing can substantially enhance subsurface microbial characterization, provided that primer design is optimized, and highlight its potential to improve assessments of microbial identity, structure, and function in low-biomass environments.