ArcMark: a marker-based database for archaeal detection in shotgun metagenomic food samples

Archaea constitute a relatively underexplored domain of microorganisms, despite their widespread distribution across diverse environments, including marine ecosystems, soils, and host-associated niches. Although their presence has been reported in various food matrices, comprehensive insights into their occurrence and diversity within these contexts remain limited. Shotgun metagenomic sequencing offers the opportunity to characterize entire microbial communities, underscoring the need for robust databases and bioinformatic pipelines specifically designed for the detection and quantification of archaea. In this study, we developed a targeted approach based on marker sequences derived from 50S ribosomal proteins, obtained from 635 archaeal genomes representing 444 taxa. The ArcMark database and pipeline showed high sensitivity and precision in detecting archaeal sequences across simulated mock communities. ArcMark was subsequently applied to 639 shotgun metagenomic datasets from several sources, including animal and environmental samples available in GenBank, with a subset of 360 Illumina samples derived from plant- and animal-based foods. Our analysis revealed that 8% of the examined food samples contained archaeal reads. Alpha-diversity analysis showed higher Chao1 and Fisher indices in fermented fish compared with cheese, milk, and olive samples. Notably, halophilic taxa were predominantly detected in salt-rich fermented foods. Genera such as Haloarcula, Halobacterium, Halococcus, Halorussus, Halolamina, Halapricum, and Halobellus were identified in olives and fermented fish, highlighting the ecological relevance of halophilic archaea in these environments. Although both fermented fish and olives harboured halophilic taxa, their overall community composition differed significantly (PERMANOVA, p-value < 0.05). Overall, this work establishes a curated archaeal marker database and a dedicated bioinformatic pipeline for archaeal detection in shotgun metagenomic datasets, providing a foundation for future studies on their distribution and functional roles in food systems.