Stabilized and unstabilized sampling methods result in differential fecal 16S rRNA microbial sequencing results

Abstract

Over the past decade, studies have been conducted to increase the understanding of associations between the fecal microbiome and human health. In conjunction, researchers have investigated the effects of study design, methods, molecular processing, and sequencing techniques. However, a lack of standardization of fecal sample collection methodology has introduced heterogeneity in sequencing results. Sources of variability include sample collection methods, storage temperatures, and transport times. Here we present 16S rRNA gene amplicon sequencing results from two sample collection methods (unstabilized sterile swab and stabilized OmniGene Gut Kits) collected from the same fecal specimens. The paired samples were collected either at the research facility or the participants' home and ground shipped to the research facility at ambient temperature. Therefore, samples were exposed to variable temperatures and transport times. We found that fecal sample collection methods resulted in taxonomic and diversity differences that showed distinct patterns between swab and OmniGene samples. Swab samples were disproportionally affected by increased transport time, but differences in taxa and diversity were driven more by sample collection method, as compared to transport time. Based on previous studies, many of the taxa that were associated with sample collection methods and transport times have clinical relevance. Collectively, this research highlights: 1) the need for further standardization of methods for fecal microbiome studies; 2) limitations of direct comparisons between different fecal sample collection methods; and 3) the importance of careful consideration of sample collection methods for future studies and meta-analyses.

Fig 1. PCoA plots illustrating differences in microbial community structure between the sample collection methods.

A) Weighted UniFrac distance metric. B) Unweighted UniFrac distance metric. p-values from PERMANOVA.

Fig 2. Log fold change at the phylum (A), class (B), and genus (C) level.

Log fold change values were relative to the relative abundance of taxa for swabs, therefore positive values indicate higher abundance in swabs and negative values indicate higher abundance in OmniGene. Statistically significant (ANCOMBC2; Bonferroni corrected, p < 0.05) differential abundance is indicated by a colored bar and gray bars indicate no statistical significance. A table with statistics can be found in the supplemental material (S1 Table).

Fig 3. Spearman correlation of alpha diversity metrics by sample collection method.

A) Shannon diversity. B) Observed features. Rho (R) and p-values from Spearman correlation.

Fig 4. Associations between relative abundances of specific taxa with transport time by sample collection method at the A) phylum- and B) class-level.

Scatter plots with line of best fit over transport time colored by sample collection method. Rho (R) and p-values from Spearman correlation.

Fig 5. Beta diversity PCoA plot of the subset of non-shipped paired swab and OmniGene samples.

A) Weighted UniFrac distance metric. B) Unweighted UniFrac distance metric.

Fig 6. Log fold change of phylum (A), class (B), and genus (C) level in the subset of non-shipped paired swab and OmniGene samples.

Log fold change values were relative to the relative abundance of swabs, therefore positive values indicate higher relative abundance in swabs and negative values indicate higher relative abundance in OmniGene. Statistically significant (ANCOMBC2; Bonferroni corrected, p < 0.05) differential abundance is indicated by a colored bar and gray bars indicate no statistical significance. A table with statistics can be found in the supplemental material (S2 Table).