To understand how transplant handling might alter fecal microbial communities—which may affect therapeutic efficacy—we investigated three potential sources of degradation: oxygen exposure during homogenization, freeze-thaw cycles during transplant storage and transport, and lag time between defecation and transplant preparation. For each experiment, we prepared two separate stool samples from the same donor and divided each sample into subsamples for analysis under different transplant preparation methods, thus controlling for variance across fecal samples. After transplant preparation, we then further divided each subsample into three technical replicates. We used qPCR to estimate total 16S rRNA abundance. We then evaluated the replicates' resulting microbial composition using standard 16S rRNA sequencing [21,22] and PMA-seq, which selectively sequences DNA from bacteria with intact cell membranes—a proxy for living cells [23–25].

From our sequencing data, we generated two tables of operational taxonomic units (OTU), one with 1,362 OTUs clustered at 97% similarity (S1 Data) and another with 77 high-confidence OTUs—ones present in all sequencing samples—clustered at 100% similarity (S2 Data).

Oxygen exposure during fecal homogenization alters the composition of living fecal bacteria

To test the effects on fecal bacteria of oxygen exposure during stool sample homogenization, we prepared subsamples from two stool samples from a single donor using five different procedures, each with a different level of oxygen exposure (Materials and Methods; S1 Fig). To ensure that any patterns we observed from PMA-seq were not procedural artifacts, we also sequenced PMA-seq controls that replaced PMA with water for some transplant preparations (see Materials and Methods; S2 Fig).

We found that total 16S rRNA abundance decreased with increasing exposure to oxygen, indicating that oxygen exposure decreases the number of viable cells (S3 Fig). This degradation was reflected in both untreated replicates—which captured DNA from living cells, dead cells, and free-floating DNA not associated with a cell—and replicates treated with PMA—which captured only DNA within living cells (S3 Fig).

To understand which bacteria were affected, we analyzed 16S rRNA sequencing results. Standard 16S rRNA sequencing indicated a slight increase in beta diversity (Bray-Curtis dissimilarity) with increasing oxygen exposure, but these differences were much clearer in the PMA-seq data across all comparisons (Fig 1a, S4 Fig). Comparison with controls confirmed that the changes we observed were largely due to PMA's exclusion of unprotected DNA, not other steps in the PMA-seq process (S2 Fig). These results confirmed that PMA-seq more clearly reflects changes in bacterial composition due to differential oxygen exposure than does standard 16S sequencing.

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larger image TIFF original image Download: Fig 1. PMA-seq reveals changes in bacterial community composition with oxygen exposure. (a) Beta diversity (Bray-Curtis dissimilarity) between subsamples prepared with varying levels of oxygen exposure indicates that PMA-seq detects higher dissimilarity than standard 16S sequencing. (b) Beta diversity between standard 16S rRNA sequencing and PMA-seq results also reflects the degree of oxygen exposure. Data were generated from the same stool sample and same oxygen preparation, sequenced using either standard 16S rRNA sequencing or PMA-seq. (c–d) PMA-seq also detects changes in the abundance of individual OTUs to a greater extent than standard 16S sequencing. (c) OTUs from the genera Faecalibacterium and Megamonas largely decreased in relative abundance when exposed to oxygen, while those from Bacteroides increased. This signal was stronger in results from PMA-seq. Each point represents the mean change in relative abundance of a single OTU across three technical replicates. (d) Our analytical method identified individual OTUs that changed significantly in relative abundance between different oxygen preparations, many of which would have not been detected using standard 16S sequencing. Abbreviations of transplant preparation methods: ANC, anaerobic + cysteine; ANA, anaerobic; AEC, aerobic + cysteine; AER, aerobic; ARS, aerobic + sparging. https://doi.org/10.1371/journal.pone.0170922.g001

Given that PMA-seq reflects only living bacteria, and standard 16S rRNA sequencing ought to more closely reflect the entire bacterial community, we hypothesized that comparing sequencing results from each of these methods might provide a proxy for how much a bacterial community has been degraded. We found that beta diversity values between 16S rRNA sequencing and PMA-seq results from the same subsample increased with greater oxygen exposure (Fig 1b). This result suggests that comparing standard 16S rRNA sequencing and PMA-seq results could provide a proxy for the degradation of living bacteria within fecal material.

Our PMA-seq results also shed light on how specific bacterial taxa respond to short-term oxygen exposure, which could ultimately affect therapeutic efficacy. Oxygen appeared to have the greatest negative effect on the abundances of bacteria from the phylum Firmicutes (Fig 2). In particular, two of the four most abundant genera from one donor—Megamonas and Faecalibacterium (sp. prausnitzii)—uniformly decreased in abundance in both stool samples tested (Fig 1c, S4 Fig; comparison of anaerobic + cysteine and aerobic preparation, two-tailed Student's t-test, t = 6.293, P = 0.0033 and t = 7.494, P = 0.0017, respectively). Little is known about the role that Megamonas plays in the gut microbiota [26,27]. Faecalibacterium prausnitzii is believed to have anti-inflammatory properties in the gut and to help moderate or prevent illnesses like inflammatory bowel disease [28,29]. F. prausnitzii produces short-chain fatty acids, which help regulate host immune cells [30] and are the preferred energy source of colonic epithelial cells [31]. Thus, by decreasing the viability of F. prausnitzii cells during oxygen exposure, we may be compromising the therapeutic value of fecal transplant material.

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larger image TIFF original image Download: Fig 2. Responses to oxygen exposure cluster taxonomically. Phylogeny of high-confidence OTUs with their changes in abundance from ANC to AER transplant preparations. PMA-seq revealed clustered responses to oxygen exposure. Firmicutes, particularly those from Megamonas and Faecalibacterium, decreased in abundance with oxygen exposure, while those from Bacteroides increased. Branches with greater than 90% bootstrap support are annotated. https://doi.org/10.1371/journal.pone.0170922.g002

We also identified oxygen-resistant bacteria—such as Bacteroides, Parabacteroides, Barnesiellaceae, and Rikenellaceae—that increased in relative abundance (Figs 1c and 2, S4 Fig). We hypothesized that these increases were compositional effects—which arise because we are measuring proportions rather than counting directly—since we expected little to no growth during our brief sample handling and freezer storage. Indeed, many of these apparent increases were flattened by normalizing the data to total community size (S3 Fig). OTUs from the genus Bacteroides were most often identified as oxygen resistant in our data, which aligns with previous evidence that some Bacteroides species can survive or even grow during short periods of oxygen exposure [32].

To identify individual OTUs that significantly changed in abundance between different transplant preparations, we created an analysis pipeline based on texmex [33], which models microbial community analyses using a Poisson log-normal distribution (see Materials and Methods, Fig 1d, S5 Fig). Using this pipeline and our table of high-confidence OTUs, we found that OTUs that decreased significantly in abundance during oxygen exposure most often belonged to the genera Faecalibacterium, Megamonas, and Bifidobacterium, mirroring the overall taxonomic shifts (S1 Table). OTUs that increased often belonged to Bacteroides, including B. ovatus, B. uniformis, and B. caccae (S1 Table).

Although responses to oxygen exposure by individual OTUs largely reflected the patterns of larger taxonomic groups, PMA-seq detected some heterogeneity in these responses (S6 Fig). For example, the most abundant OTUs within the genus Oscillospira did not all exhibit the same dynamics in response to oxygen exposure (S6 Fig).