Improving the standards for gut microbiome analysis of fecal samples: insights from the field biology of Japanese macaques on Yakushima Island

Takashi Hayakawa, Akiko Sawada, Akifumi S. Tanabe, Shinji Fukuda, Takushi Kishida, Yosuke Kurihara, Kei Matsushima, Jie Liu, Etienne-Francois Akomo-Okoue, Waleska Gravena, Makoto Kashima, Mariko Suzuki, Kohmei Kadowaki, Takafumi Suzumura, Eiji Inoue, Hideki Sugiura, Goro Hanya, Kiyokazu Agata

Fecal DNA-based 16S ribosomal RNA (rRNA) gene sequencing using next-generation sequencers allows us to understand the dynamic gut microbiome adaptation of animals to their specific habitats. Conventional techniques of fecal microbiome analysis have been developed within the broad contexts defined by human biology; hence, many of these techniques are not immediately applicable to wild nonhuman primates. In order to establish a standard experimental protocol for the analysis of the gut microbiomes of wild animals, we selected the Japanese macaques (Macaca fuscata yakui) on Yakushima Island. We tested different protocols for each stage of fecal sample processing: storage, DNA extraction, and choice of the sequencing region in the bacterial 16S rRNA gene. We also analyzed the gut microbiome of captive Japanese macaques as the control. The comparison of samples obtained from identical macaques but subjected to different protocols showed that the tested storage methods (RNAlater and lysis buffer) produced effectively the same composition of bacterial operational taxonomic units (OTUs) as the standard frozen storage method, although the relative abundance of each OTU was quantitatively affected. Taxonomic assignment of the detected bacterial groups was also significantly affected by the region being sequenced, indicating that sequencing regions and the corresponding polymerase chain reaction (PCR) primer pairs for the 16S rRNA gene should be carefully selected. This study improves the current standard methods for microbiome analysis in wild nonhuman primates. Japanese macaques were shown to be a suitable model for understanding microbiome adaptation to various environments.