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

Abstract

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.

Gut microbiota composition of Japanese macaques associates with extent of human encroachment

“…Likewise, they also found Spriochaetes and Proteobacteria at minor abundance. However, previous studies on Japanese macaques focused on captive samples mostly ( n = 2 from Hayakawa, Sawada et al, ; n = 97 from Ma et al, ) while limited samples were from wild, free‐ranging individuals ( n = 2 from Hayakawa, Nathan, et al, ).…”

Assessment of Inter-Laboratory Variation in the Characterization and Analysis of the Mucosal Microbiota in Crohn’s Disease and Ulcerative Colitis

“…Extraction methods have, however, been reported to contribute significantly to variability in taxonomic classification from metagenomic data (Wesolowska-Andersen et al, 2014). Across all such studies, including our multicentre study, the contribution from extraction method to total variability was substantially outweighed by the biological variability targeted by the respective studies (Jones et al, 2015;Sinha et al, 2015;Gohl et al, 2016;Hayakawa et al, 2018).…”

“…Multicentre studies assessing technical variability of 16S rRNA sequencing for microbiome analysis have reported its contribution to be significant, despite high intra-center reproducibility (Hiergeist et al, 2016). To address a lack of standard protocols, initiatives including International Human Microbiome Standards (IHMS) and the Microbiome Quality Control (MBQC) project have been developed to promote reproducibility in microbiome research and help inform study design to reduce inter-study technical variability (Santiago et al, 2014;Sinha et al, 2015;Hayakawa et al, 2018). Their findings indicate that the choice of DNA extraction protocol and amplicon primer sets substantially influence inter-laboratory variability (Jones et al, 2015;Sinha et al, 2015;Hayakawa et al, 2018).…”

“…To address a lack of standard protocols, initiatives including International Human Microbiome Standards (IHMS) and the Microbiome Quality Control (MBQC) project have been developed to promote reproducibility in microbiome research and help inform study design to reduce inter-study technical variability (Santiago et al, 2014;Sinha et al, 2015;Hayakawa et al, 2018). Their findings indicate that the choice of DNA extraction protocol and amplicon primer sets substantially influence inter-laboratory variability (Jones et al, 2015;Sinha et al, 2015;Hayakawa et al, 2018). Other studies have also shown that both amplicon-based microbiome surveys and shotgun metagenomics methodologies suffer from biases due to a wide range of factors, including primer bias and library preparation (Jones et al, 2015;Sinha et al, 2015;Gohl et al, 2016;Hayakawa et al, 2018).…”

“…Their findings indicate that the choice of DNA extraction protocol and amplicon primer sets substantially influence inter-laboratory variability (Jones et al, 2015;Sinha et al, 2015;Hayakawa et al, 2018). Other studies have also shown that both amplicon-based microbiome surveys and shotgun metagenomics methodologies suffer from biases due to a wide range of factors, including primer bias and library preparation (Jones et al, 2015;Sinha et al, 2015;Gohl et al, 2016;Hayakawa et al, 2018). As well, the choice of bioinformatic processing pipeline used to convert DNA sequences into count tables can impact the characterization of the microbial community (Golob et al, 2017).…”