Negligible effect of host DNA on metagenomic analysis enables microbial ecology investigation in historical samples
Microbiome composition and function are strongly influenced by environmental factors, with major shifts driven by intensified anthropogenic pressures over the past centuries. This timeframe extends beyond the scope of traditional experimental or longitudinal studies commonly used to investigate microbiome dynamics. The historical samples might provide important insights into the mechanistic consequences of anthropogenic pressures and the potential shift in microbial diversity and composition. Despite their vast potential, historical samples available in museums and herbaria worldwide remain underutilized for exploring host-microbiome interactions across broad temporal and spatial scales due to incompatibilities with standard analytical pipelines and limited understanding of optimal classification parameters. While host DNA removal has conventionally been considered essential for taxonomic assignment of metagenomic reads, and might be of particular importance when processing degraded DNA, this step is impractical for specimens with no reference genome available for host species. Here, we show that host DNA content has negligible impact on microbial data analysis with empirical and simulation datasets. Since DNA molecules from historical samples are highly fragmented and uneven in length, we further analysed the impact of k-mer value on the classification of metagenomic reads from historical samples. To improve recall rate, we proposed a simple two-step approach in which reads are classified with two annotation databases constructed with a long and a short k-mer values. Through simulation and published datasets, we demonstrated that this approach outperforms single-step workflows in effectively recovering microbial signals from reads in a wide range of length. Together, this study provides a solid foundation for incorporating natural history collections into host-associated microbiome research, offering valuable insights into the long-term effects of anthropogenic change on microbial communities.