Marine & Environmental Sciences Faculty Articles
ORCID
0000-0002-1637-4125
Document Type
Article
Publication Title
PeerJ
ISSN
2167-8359
Publication Date
5-8-2018
Keywords
Microbiome, 16S, Port Everglades Inlet, Bacterioplankton, MiSeq
Abstract
Background
Similar to natural rivers, manmade inlets connect inland runoff to the ocean. Port Everglades Inlet (PEI) is a busy cargo and cruise ship port in South Florida, which can act as a source of pollution to surrounding beaches and offshore coral reefs. Understanding the composition and fluctuations of bacterioplankton communities (“microbiomes”) in major port inlets is important due to potential impacts on surrounding environments. We hypothesize seasonal microbial fluctuations, which were profiled by high throughput 16S rRNA amplicon sequencing and analysis.
Methods & Results
Surface water samples were collected every week for one year. A total of four samples per month, two from each sampling location, were used for statistical analysis creating a high sampling frequency and finer sampling scale than previous inlet microbiome studies. We observed significant differences in community alpha diversity between months and seasons. Analysis of composition of microbiomes (ANCOM) tests were run in QIIME 2 at genus level taxonomic classification to determine which genera were differentially abundant between seasons and months. Beta diversity results yielded significant differences in PEI community composition in regard to month, season, water temperature, and salinity. Analysis of potentially pathogenic genera showed presence of Staphylococcus and Streptococcus. However, statistical analysis indicated that these organisms were not present in significantly high abundances throughout the year or between seasons.
Discussion
Significant differences in alpha diversity were observed when comparing microbial communities with respect to time. This observation stems from the high community evenness and low community richness in August. This indicates that only a few organisms dominated the community during this month. August had lower than average rainfall levels for a wet season, which may have contributed to less runoff, and fewer bacterial groups introduced into the port surface waters. Bacterioplankton beta diversity differed significantly by month, season, water temperature, and salinity. The 2013–2014 dry season (October–April), was warmer and wetter than historical averages. This may have driven significant differences in beta diversity. Increased nitrogen and phosphorous concentrations were observed in these dry season months, possibly creating favorable bacterial growth conditions. Potentially pathogenic genera were present in the PEI. However their relatively low, non-significant abundance levels highlight their relatively low risk for public health concerns. This study represents the first to sample a large port at this sampling scale and sequencing depth. These data can help establish the inlet microbial community baseline and supplement the vital monitoring of local marine and recreational environments, all the more poignant in context of local reef disease outbreaks and worldwide coral reef collapse in wake of a harsh 2014–16 El Niño event.
DOI
10.7717/peerj.4671
Volume
6
Issue
e4671
NSUWorks Citation
Lauren M. O'Connell, Song Gao, Donald S. McCorquodale Jr., Jay M. Fleisher, and Jose Lopez. 2018. Fine grained compositional analysis of Port Everglades Inlet microbiome using high throughput DNA sequencing .PeerJ , (e4671) . https://nsuworks.nova.edu/occ_facarticles/920.
Included in
Environmental Indicators and Impact Assessment Commons, Genomics Commons, Marine Biology Commons, Microbiology Commons
Comments
Copyright
© 2018 O’Connell et al.
Licence
This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.