Species sorting and seasonal dynamics primarily shape bacterial communities in the Upper Mississippi River

Staley, Christopher; Gould, Trevor; Wang, Ping; Phillips, Jane; Cotner, James B.; Sadowsky, Michael J.

doi:10.1016/j.scitotenv.2014.10.012

Cited by 136 publications

(112 citation statements)

References 54 publications

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“…In contrast, Brisbane River water samples were dominated by Rhodospirillales, Burkholderiales, Actinomycetales, and Flavobacteriales. The presence of these taxonomic orders in surface waters has been reported previously (66)(67)(68).…”

Section: Discussionsupporting

confidence: 59%

Toolbox Approaches Using Molecular Markers and 16S rRNA Gene Amplicon Data Sets for Identification of Fecal Pollution in Surface Water

Ahmed

Staley

Sadowsky

et al. 2015

Appl Environ Microbiol

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dIn this study, host-associated molecular markers and bacterial 16S rRNA gene community analysis using high-throughput sequencing were used to identify the sources of fecal pollution in environmental waters in Brisbane, Australia. A total of 92 fecal and composite wastewater samples were collected from different host groups (cat, cattle, dog, horse, human, and kangaroo), and 18 water samples were collected from six sites (BR1 to BR6) along the Brisbane River in Queensland, Australia. Bacterial communities in the fecal, wastewater, and river water samples were sequenced. Water samples were also tested for the presence of bird-associated (GFD), cattle-associated (CowM3), horse-associated, and human-associated (HF183) molecular markers, to provide multiple lines of evidence regarding the possible presence of fecal pollution associated with specific hosts. Among the 18 water samples tested, 83%, 33%, 17%, and 17% were real-time PCR positive for the GFD, HF183, CowM3, and horse markers, respectively. Among the potential sources of fecal pollution in water samples from the river, DNA sequencing tended to show relatively small contributions from wastewater treatment plants (up to 13% of sequence reads). Contributions from other animal sources were rarely detected and were very small (<3% of sequence reads). Source contributions determined via sequence analysis versus detection of molecular markers showed variable agreement. A lack of relationships among fecal indicator bacteria, host-associated molecular markers, and 16S rRNA gene community analysis data was also observed. Nonetheless, we show that bacterial community and host-associated molecular marker analyses can be combined to identify potential sources of fecal pollution in an urban river. This study is a proof of concept, and based on the results, we recommend using bacterial community analysis (where possible) along with PCR detection or quantification of host-associated molecular markers to provide information on the sources of fecal pollution in waterways. Fecal indicator bacteria (FIB), such as Escherichia coli and Enterococcus spp., have long been used as indirect measures of public health risks associated with environmental waters (1, 2). However, the use of FIB to identify the health risks associated with enteric viruses and protozoa has been questioned because of their poor cooccurrence or correlation (3-5). Some strains of FIB have been reported to have the ability to adapt in the environment and to persist in sediment and vegetation (6, 7). The major limitation of FIB is that they cannot be assigned to a specific original source due to their cosmopolitan nature (being frequently found in different warm-blooded and some cold-blooded animals) (8, 9). When environmental waters are polluted with FIB from multiple sources, it becomes extremely difficult to implement a robust management plan without identifying the potential sources of this pollution.Over the past 2 decades, library-dependent and library-independent microbial source tracking (MST) methods ha...

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Section: Discussionsupporting

confidence: 59%

Toolbox Approaches Using Molecular Markers and 16S rRNA Gene Amplicon Data Sets for Identification of Fecal Pollution in Surface Water

Ahmed

Staley

Sadowsky

et al. 2015

Appl Environ Microbiol

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“…Within the Proteobacteria, the Betaproteobacteria underwent most drastic fluctuation during and after the storm event, while the Gammaproteobacteria decreased steadily over the sampling period. Previous studies have noted similar trends with respect to fluctuation of the Proteobacteria during rainfall events (59,62). The Proteobacteria are important in nutrient cycling within freshwater ecosystems, and specific subclasses (e.g., Betaproteobacteria) consist of bacterioplankton, which has been shown to readily fluctuate with varied nutrient concentrations (63).…”

Section: Discussionmentioning

confidence: 62%

“…Use of the 16S rRNA gene as a genetic marker allows for holistic bacterial community assessment by using multiple indicators to assess microbiological water quality over large spatial and temporal scales (34,39,54). Tracking bacterial community composition might prove to be an informative tool for long-term temporal studies, as other factors, including seasonal changes and climate change, cause shifts in bacterial community dynamics and associated risks (19,32,62,80). Further studies should examine beyond the 16S rRNA gene and probe functional genetic markers, such as genes involved in host-microbial interactions, which might prove to be more temporally stable indicators for assessing microbial risks.…”

Section: Discussionmentioning

confidence: 99%

Restructuring of the Aquatic Bacterial Community by Hydric Dynamics Associated with Superstorm Sandy

Ulrich

Rosenberger

Brislawn

et al. 2016

Appl Environ Microbiol

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Bacterial community composition and longitudinal fluctuations were monitored in a riverine system during and after Superstorm Sandy to better characterize inter-and intracommunity responses associated with the disturbance associated with a 100-year storm event. High-throughput sequencing of the 16S rRNA gene was used to assess microbial community structure within water samples from Muddy Creek Run, a second-order stream in Huntingdon, PA, at 12 different time points during the storm event (29 October to 3 November 2012) and under seasonally matched baseline conditions. High-throughput sequencing of the 16S rRNA gene was used to track changes in bacterial community structure and divergence during and after Superstorm Sandy. Bacterial community dynamics were correlated to measured physicochemical parameters and fecal indicator bacteria (FIB) concentrations. Bioinformatics analyses of 2.1 million 16S rRNA gene sequences revealed a significant increase in bacterial diversity in samples taken during peak discharge of the storm. Beta-diversity analyses revealed longitudinal shifts in the bacterial community structure. Successional changes were observed, in which Betaproteobacteria and Gammaproteobacteria decreased in 16S rRNA gene relative abundance, while the relative abundance of members of the Firmicutes increased. Furthermore, 16S rRNA gene sequences matching pathogenic bacteria, including strains of Legionella, Campylobacter, Arcobacter, and Helicobacter, as well as bacteria of fecal origin (e.g., Bacteroides), exhibited an increase in abundance after peak discharge of the storm. This study revealed a significant restructuring of in-stream bacterial community structure associated with hydric dynamics of a storm event. IMPORTANCEIn order to better understand the microbial risks associated with freshwater environments during a storm event, a more comprehensive understanding of the variations in aquatic bacterial diversity is warranted. This study investigated the bacterial communities during and after Superstorm Sandy to provide fine time point resolution of dynamic changes in bacterial composition. This study adds to the current literature by revealing the variation in bacterial community structure during the course of a storm. This study employed high-throughput DNA sequencing, which generated a deep analysis of inter-and intracommunity responses during a significant storm event. This study has highlighted the utility of applying high-throughput sequencing for water quality monitoring purposes, as this approach enabled a more comprehensive investigation of the bacterial community structure. Altogether, these data suggest a drastic restructuring of the stream bacterial community during a storm event and highlight the potential of high-throughput sequencing approaches for assessing the microbiological quality of our environment. M ore than 12,000 water bodies in the United States are considered to be impaired by fecal indicator bacteria (FIB), due to both point and nonpoint sources of pollution, according t...

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“…This hypothesis was predicated on a prior finding that each of these rivers has a distinct microbiome [14]; the repeatability of this finding and its implications were tested independently in this study. By following microbiome diversity with river flow from directly above, to close below, to far between, and within tributary inputs we were able to evaluate the likelihood of these two proposed mechanisms, sudden tributary inoculation vs. gradual environmental selection [11, 15, 16], on the pattern of downriver variation in compositional diversity of the Mississippi River microbiome.…”

Section: Introductionmentioning

confidence: 99%

Patterns of variation in diversity of the Mississippi river microbiome over 1,300 kilometers

et al. 2017

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We examined the downriver patterns of variation in taxonomic diversity of the Mississippi River bacterioplankton microbiome along 1,300 river kilometers, or approximately one third the total length of the river. The study section included portions of the Upper, Middle, and Lower Mississippi River, confluences with five tributaries draining distinct sub-basins, river cities, and extended stretches without major inputs to the Mississippi. The composition and proportional abundance of dominant bacterial phyla was distinct for free-living and particle-associated cells, and constant along the entire reach, except for a substantial but transient disturbance near the city of Memphis, Tennessee. At a finer scale of taxonomic resolution (operational taxonomic units, OTUs), however, there were notable patterns in downriver variation in bacterial community alpha diversity (richness within a site) and beta diversity (variation in composition among sites). There was a strong and steady increase downriver in alpha diversity of OTUs on suspended particles, suggesting an increase in particle niche heterogeneity, and/or particle colonization. Relatively large shifts in beta diversity of free-living and particle-associated communities occurred following major tributary confluences and transiently at Memphis, while in long stretches between these points diversity typically varied more gradually. We conclude that the Mississippi River possesses a bacterioplankton microbiome distinct in diversity from other large river microbiomes in the Mississippi River Basin, that at major river confluences or urban point sources its OTU diversity may shift abruptly and substantially, presumably by immigration of distinct external microbiomes, but that where environmental conditions are more stable along the downriver gradient, microbiome diversity tends to vary gradually, presumably by a process of successional change in community composition.

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Species sorting and seasonal dynamics primarily shape bacterial communities in the Upper Mississippi River

Cited by 136 publications

References 54 publications

Toolbox Approaches Using Molecular Markers and 16S rRNA Gene Amplicon Data Sets for Identification of Fecal Pollution in Surface Water

Toolbox Approaches Using Molecular Markers and 16S rRNA Gene Amplicon Data Sets for Identification of Fecal Pollution in Surface Water

Restructuring of the Aquatic Bacterial Community by Hydric Dynamics Associated with Superstorm Sandy

Patterns of variation in diversity of the Mississippi river microbiome over 1,300 kilometers

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