A pollution gradient contributes to the taxonomic, functional, and resistome diversity of microbial communities in marine sediments

Abstract

Background: Coastal marine environments are one of the most productive ecosystems on Earth. However, anthropogenic impacts exert significant pressure on coastal marine biodiversity, contributing to functional shifts in microbial communities and human health risk factors. However, relatively little is known about the impact of eutrophication-human-derived nutrient pollution-on the marine microbial biosphere.

Results: Here, we tested the hypothesis that benthic microbial diversity and function varies along a pollution gradient, with a focus on human pathogens and antibiotic resistance genes. Comprehensive metagenomic analysis including taxonomic investigation, functional detection, and ARG annotation revealed that zinc, lead, total volatile solids, and ammonia nitrogen were correlated with microbial diversity and function. We propose several microbes, including Planctomycetes and sulfate-reducing microbes as candidates to reflect pollution concentration. Annotation of antibiotic resistance genes showed that the highest abundance of efflux pumps was found at the most polluted site, corroborating the relationship between pollution and human health risk factors. This result suggests that sediments at polluted sites harbor microbes with a higher capacity to reduce intracellular levels of antibiotics, heavy metals, or other environmental contaminants.

Conclusions: Our findings suggest a correlation between pollution and the marine sediment microbiome and provide insight into the role of high-turnover microbial communities as well as potential pathogenic organisms as real-time indicators of water quality, with implications for human health and demonstrate the inner functional shifts contributed by the microcommunities.

Keywords: Antibiotic resistance genes; Marine sediments; Metagenomics; Pollution concentration.

Fig. 1

Sampling information. A map of Tolo Channel (including Tolo Harbour) and Mirs Bay shows the four sampling sites marked in circles of different colors: Centre Island, Che Lei Pai, Port Island, and Tung Ping Chau. Samples were collected from the sediments at 6–10-cm depth. The table shows the information of each sample including sampling site, region, longitude, and latitude

Fig. 2

Comparative analysis of the prokaryotic communities among the sampling sites. a, b, c Relative abundance of the most abundant microbes across sites at the phylum, family, and species levels, respectively. d, e, f Relative abundance of the most abundant microbes which have significantly different abundances among sites. Microbes with asterisk retain strong differentiation after FDR correction (adjust q value < 0.1)

Fig. 3

Community dissimilarities among sampling sites with pollutant vectors. a, b, c Principal component analyses for the microbes among sites at phylum, family, and species levels, respectively. Vector matrices of the significant pollution parameters are shown by individual black lines with an arrow. The significant microbes are shown in gray

Fig. 4

KEGG Orthology annotation and taxonomic drivers of functional shifts between sites. a Heat map of the top 50 abundant KEGG pathway annotations. b Taxon-level shift contribution profiles for significantly different KO pathways between Centre Island (case group) and Tung Ping Chau (control group) based on the top 25 abundant families. Taxonomic contributors to functional pathways differences between Centre Island (case group) and Tung Ping Chau (control group) based on the top 25 abundant families. The white and red diamonds refer to the taxa-based and functional-based shift scores, respectively

Fig. 5

Comparisons of abundances of potential pathogens and antibiotic resistant genes (ARGs) among samples. a Heat map based on relative abundances of potential pathogenic genera in different samples. b Comparisons of pathogenic alpha diversity among sampling sites. c Comparisons of significantly different pathogenic genera between Centre Island and Tung Ping Chau. d Total relative abundance of each ARG mechanism among the sampling sites. e Total ARG profile of the samples. f Comparisons of total ARG abundances from each site