Assessment of Fecal Indicator Bacteria and Potential Pathogen Co-Occurrence at a Shellfish Growing Area

Abstract

Routine monitoring of shellfish growing waters for bacteria indicative of human sewage pollution reveals little about the bacterial communities that co-occur with these indicators. This study investigated the bacterial community, potential pathogens, and fecal indicator bacteria in 40 water samples from a shellfish growing area in the Chesapeake Bay, USA. Bacterial community composition was quantified with deep sequencing of 16S rRNA gene amplicons, and absolute gene abundances were estimated with an internal standard (Thermus thermophilus genomes). Fecal coliforms were quantified by culture, and Vibrio vulnificus and V. parahaemolyticus with quantitative PCR. Fecal coliforms and V. vulnificus were detected in most samples, and a diverse assemblage of potential human pathogens were detected in all samples. These taxa followed two general patterns of abundance. Fecal coliforms and 16S rRNA genes for Enterobacteriaceae, Aeromonas, Arcobacter, Staphylococcus, and Bacteroides increased in abundance after a 1.3-inch rain event in May, and, for some taxa, after smaller rain events later in the season, suggesting that these are allochthonous organisms washed in from land. Clostridiaceae and Mycobacterium 16S rRNA gene abundances increased with day of the year and were not positively related to rainfall, suggesting that these are autochthonous organisms. Other groups followed both patterns, such as Legionella. Fecal coliform abundance did not correlate with most other taxa, but were extremely high following the large rainstorm in May when they co-occurred with a broad range of potential pathogen groups. V. vulnificus were absent during the large rainstorm, and did not correlate with 16S rRNA abundances of Vibrio spp. or most other taxa. These results highlight the complex nature of bacterial communities and the limited utility of using specific bacterial groups as indicators of pathogen presence.

Keywords: estuary; human health; microbiome; pathogens; shellfish closures.

Figure 1

Relative abundances of 16S rRNA genes for the 12 most common taxonomic groups by sample. The phyla Proteobacteria were separated into Alpha-, Beta-, Gamma-, Delta-, and “other” classes; Bacteroidetes into Cytophagia, Sphingobacteriia, Flavobacteria, and “other” classes; and Actinobacteria into the class Actinobacteria and “other” classes.

Figure 2

Measurements of alpha diversity by sample date and sample depth (surface and bottom). Panel (A) shows Shannon diversity values and panel (B) shows Chao1 richness.

Figure 3

nMDS plot of beta diversity using Bray-Curtis similarity comparisons of log transformed 16S rRNA copy abundance. Surface nMDS plot based on 25 iterations with a final stress level of 0.01. Surface community composition (blue circles) showed higher variability in spring than in summer of fall.

Figure 4

Comparison of the number of T. thermophilus (Tt) 16S rRNA reads (blue bars) and the estimated total 16S rRNA gene densities (#/mL) (red squares) for the 40 samples in this study. Sample names include month and day followed by S (surface) or B (bottom) and replicate number. Jun13S and Jul09B2 had unusually low numbers of Tt reads, indicating an unusually high density of bacteria or some error in the addition of Tt genes to those samples.

Figure 5

Abundances of V. vulnificus cells (qPCR), pathogen-containing phylogenetic groups (16S amplicons), and fecal coliforms (culturing) on scales of (A) thousands per ml, (B) hundreds per ml, (C) thousands per ml, and (D) individuals per ml on each sampling date.

Figure 6

Correlation network of select pathogens (16S rRNA), fecal coliforms (culture), and V. vulnificus (qPCR) found in three or more samples. Connections represent significant (p < 0.05) Spearman rank correlations between pairs of taxa. Line thickness reflects the strength of this relationship (R²-value) and line color reflects whether the relationship was positive (solid, gray) or negative (dashed, red). All taxa included were correlated to at least one other taxa (Table S3). Line distance is not reflective of strength of correlation.