Next Article in Journal
Occurrence and Distribution of Neonicotinoid Pesticides in Chinese Waterways: A Review
Previous Article in Journal
Projected Climate Change Effects on Global Vegetation Growth: A Machine Learning Approach
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Oyster Reefs Are Reservoirs for Potential Pathogens in a Highly Disturbed Subtropical Estuary

1
Smithsonian Marine Station, Fort Pierce, FL 34949, USA
2
Department of Biology, University of Central Florida, Orlando, FL 32816, USA
3
Florida Fish and Wildlife Conservation Commission Fish and Wildlife Research Institute, St. Petersburg, FL 33701, USA
4
Florida Department of Environmental Protection-Indian River Lagoon Aquatic Preserves, Fort Pierce, FL 34981, USA
5
Martin County Board of County Commissioners, Stuart, FL 34996, USA
6
Marine Discovery Center, New Smyrna Beach, FL 32169, USA
7
Indian River Lagoon National Estuary Program, Sebastian, FL 32958, USA
*
Author to whom correspondence should be addressed.
Environments 2023, 10(12), 205; https://doi.org/10.3390/environments10120205
Submission received: 15 September 2023 / Revised: 11 November 2023 / Accepted: 22 November 2023 / Published: 27 November 2023

Abstract

:
Estuaries worldwide are grappling with deteriorating water quality and benthic conditions that coincide with the rising detection of pathogenic and potentially pathogenic microbes (PPM). Both indigenous PPM and those that enter estuaries through urban and agricultural runoff are funneled through suspension-feeding organisms and deposited onto the benthos, where they can be moved through food webs. This study explored PPM communities in the Indian River Lagoon system, a biodiverse but urbanized estuary in east central Florida (USA). PPM were surveyed in estuary water, at stormwater outfalls, and in biodeposits of a key suspension feeder, the eastern oyster Crassostrea virginica. A total of 52 microbial exact sequence variants, with per-sample relative abundances up to 61.4%, were identified as PPM. The biodeposits contained relatively more abundant and diverse PPM than the water samples. PPM community composition also differed between seasons and between biodeposits and water. The community differences were driven primarily by Vibrio and Pseudoalteromonas spp. This investigation provides evidence that, through biodeposition, oyster reefs in the IRL estuary are a reservoir for PPM, and it documents some taxa of concern that should be conclusively identified and investigated for their pathogenicity and potential to pervade food webs and fisheries.

1. Introduction

Estuarine water quality and benthic conditions are deteriorating worldwide because of urbanization and climate change [1,2]. Of particular concern are increases in the detection of pathogens in estuary waters and sediments that threaten human and ecosystem health [3,4,5,6,7]. These increases are likely due, in part, to improved detection methods. But they also appear to be fueled by a combination of factors like wastewater seepage and stormwater runoff, which introduce new pathogens, along with eutrophication and warming, which stimulate the growth of both indigenous and introduced taxa [8,9]. However, the precise mechanisms by which virulent microbes enter, persist, and proliferate in estuarine systems are complex and still poorly understood [10,11].
The Indian River Lagoon (IRL) is a barrier island estuary system that spans approximately one-third (251 km) of Florida’s east coast (USA). With a database of >9000 species of animals, plants, and protists at the time of writing this paper [12], the IRL watershed is a biodiversity hotspot, and it was designated as one of the 28 estuaries of national significance by the U.S. Environmental Protection Agency [13]. Over the past several decades, however, increasing eutrophication from population growth and climate change has reduced IRL water quality and led to harmful algal blooms, hypoxic events, habitat degradation, and biodiversity losses [14,15,16,17,18]. These disturbances likely induced changes to the estuary’s microbiome, including the emergence and growth of pathogenic taxa. Studies on IRL microbial communities are limited, but they have detected pathogenic and potentially pathogenic microbes (PPM) that vary spatially and temporally [19,20,21,22]. This underscores the need for further investigations of PPM in estuaries, focusing on potential hot spots formed by pollution point sources (e.g., stormwater outfalls) and microbial aggregators like suspension-feeding organisms.
The eastern oyster, Crassostrea virginica, is an important suspension feeder in the IRL and other estuaries [23,24,25], wherein it filters a wide variety of organic and inorganic particles [26,27,28], including bacteria [25,29], from large volumes of water. Some particles are rejected prior to digestion in the form of pseudofeces, while others are ingested and either assimilated into biomass or excreted as feces [30,31,32]. Any or all of these particle fractions may contain bacteria that are pathogenic to a wide variety of species inhabiting coastal systems, including humans [2,5,8], animals [33,34,35], vascular plants [36,37], and macroalgae [38,39,40]. Pathogens that are ingested and remain in oyster guts and tissues present a direct health risk to oyster consumers. Human infections from consuming pathogen-contaminated oysters are well documented [19,41,42,43], and this is concerning since oysters are farmed for food on leased plots in the IRL [44] and can be recreationally harvested in certain areas [45]. But infections from contaminated oysters may occur in other predators such as fishes [46] and large crustaceans [47] as well. Oysters can also transport suspended pathogens to the benthos in their biodeposits [48,49], likely turning oyster reefs into PPM reservoirs as excreted biodeposits accumulate in reef crevices and sediments. From there, PPM may infect benthic organisms through direct contact, or be carried into trophic webs and distributed by myriad deposit feeders and their predators [50]. However, fully understanding this pathway is difficult because the composition and abundance of PPM in IRL oyster biodeposits is unknown.
This paper presents an examination of microbial communities in the IRL, with a particular focus on PPM from the water column, stormwater outfalls, and oyster biodeposits. The study’s objectives were to identify potential PPM hotspots, document some taxa of concern that should be further identified and investigated, and assess the potential for oyster reefs to serve as PPM reservoirs.

2. Materials and Methods

2.1. Study Sites

Samples were collected from 21 sites throughout the IRL system (Figure 1, Table 1), including 9 oyster reef (OR), 6 lagoon water (LW), and 6 stormwater outfall (SO) sites. LW samples were collected ≥1 km from any stormwater outfall, and SO samples were collected within 1 m of an outfall mouth. The sites complement those used in a parallel study on IRL microplastics [51].

2.2. Sample Collection and Processing

Samples were collected on 18–21 January and 19–22 July 2021 to capture temperature extremes in wet and dry seasons (January—typically cool, dry; July—typically warm, wet; see Table 1). At all 21 sites, water samples (500 mL, n = 3) were collected just below the surface to avoid capturing floating debris and pollen and were immediately stored on ice in sterile bags awaiting laboratory processing. At each OR site, adult oysters (n = 3) of comparable size (mean length = 77 ± 2 mm) were collected. After scrubbing the shells with site water to remove sediment and biofouling, each oyster was transferred to a dry, sterile bag and stored on ice prior to laboratory processing. Surface water temperature (digital thermometer) and salinity (refractometer) were measured at each site.
In the laboratory, each water sample was thoroughly mixed and vacuum-filtered through a sterile nitrocellulose filter (47 mm diameter, 0.22 µm pore size). Clogged filters were moved to individual sterile Petri dishes and replaced as needed until the entire sample volume was filtered (1–10 filters/sample). Using stereomicroscopy, each filter was quickly analyzed for the presence of microplastics for a parallel investigation. The filters were kept cool during analysis by placing an ice pack between the Petri dish and the microscope stage, and they were then preserved in 95% molecular-grade ethanol and stored at −20 °C. Microbes were separated from the filters via the following process, adapted from Sneed et al. [52]: Filters from each sample were pooled, shredded into ca. 0.5 cm strips, submerged in 95% molecular-grade ethanol, and vortexed at 3200 rpm for 1 min. Filter strips were carefully discarded, the sample was centrifuged at 5000 rpm for 20 min, the supernatant was discarded, and the pellet was stored at −80 °C awaiting DNA extraction. While traces of material remained on the filters, this protocol removed most of the sample biomass.
The outer shells of the live oysters were scrubbed again in the laboratory with filtered deionized water to remove as much biofouling as possible. Each oyster was placed in a separate, randomly assigned sterile tank filled with 500 mL of water from the region in which it was collected (water from MLC for northern sites MLA-MLC; water from VER for central sites SEB-WIL; water from IND for southern sites DRI-RIV). Tanks were covered and oysters were allowed to defecate for 12 h. Using sterile glass pipettes, oyster feces (OF) and oyster pseudofeces (OP)—collectively ‘biodeposits’ hereafter—were retrieved in separate samples (each <15 mL total volume) based on visual inspection [53], filtered (1–3 filters/sample), and processed according to the same methods used for the water samples. All oysters appeared healthy and active at the end of the defecation period, with no apparent difference in depuration across the replicates.

2.3. DNA Extraction and Sequencing

DNA was extracted from all water and biodeposit samples using the Qiagen DNeasy PowerSoil HTP 96 Kit according to the manufacturer’s protocol. Extracts were sent to Jonah Ventures (Boulder, CO, USA) for PCR amplification, library preparation, and sequencing following an adapted Earth Microbiome Project protocol (https://earthmicrobiome.org, accessed on 21 November 2023). In short, the V4 hypervariable region of the 16S rRNA gene (ca. 254 bp) was amplified from each DNA sample using the updated primer pair 515F (GTGYCAGCMGCCGCGGTAA) and 806R (GGACTACNVGGGTWTCTAAT) [54,55]. This region is too short to conclusively identify bacteria to the species level, but it is very effective for profiling community composition and classifying taxa at higher levels [56]. Reactions were visually inspected for amplicon size and PCR efficiency using 5 µL of PCR product per sample in 2% agarose gels. Amplicons were cleaned with Exo1/SAP for 30 min at 37 °C, followed by inactivation for 5 min at 95 °C, and were then stored at −20 °C. Samples underwent a second round of PCR for indexing. The final PCR products were cleaned again, normalized using the SequalPrep™ Normalization Kit (Applied Biosystems, Waltham, MA, USA) and pooled by combining 5 µL of each normalized sample. Library pools were then sequenced (10,000 reads/sample target depth) on the iSeq 100 platform (Illumina Inc., San Diego, CA, USA) with an iSeq i1 Reagent cartridge (Illumina Inc., San Diego, CA, USA).

2.4. Bioinformatics and Statistical Analyses

Taxonomic assignments were conducted by Jonah Ventures (Boulder, CO, USA) using the following protocol: Raw sequence data were demultiplexed using Pheniqs v2.1.0 [57], enforcing the strict matching of sample barcode indices. Cutadapt v3.4 [58] was used to remove gene primers from the forward and reverse reads and to discard any read pairs where one or both primers were not found at the expected 5′ location, with an error rate < 0.15. Read pairs were merged using VSEARCH v2.15.2 [59], removing resulting sequences < 244 bp, >264 bp, or with a maximum expected error rate > 0.5 bp. Reads in each sample were then clustered using the UNOISE3 [60] denoising algorithm (α = 5), and unique raw sequences observed < 8 times were discarded. Counts of the resulting exact sequence variants (ESVs) were compiled, and chimeras were removed using the UCHIME3 [61] algorithm. For each ESV, a consensus taxonomy was assigned using a custom best-hits algorithm and the SILVA v138.1 [62] reference database. Finally, the consensus taxonomy and ESV count matrices were produced and delivered for downstream analyses.
Analyses were performed using the phyloseq [63], WRS2 [64], and VEGAN [65] packages in RStudio [66] v2022.02.3, and with the PRIMER v7 (PRIMER-e, Auckland, New Zealand) and XLSTAT 2023 v25.1.1408 (Lumivero, Denver, CO, USA) software packages. Samples were grouped by treatment across sites for statistical comparisons (for each season: n = 18 for LW and SO; n = 27 for OW, OF, and OP). A total of 7 samples (3% of total) were removed after examining ESV richness across the dataset and between biological replicates, retaining 227 samples for analysis. Removed samples had (1) no or extremely low ESV richness (<25% of the number of ESVs from the other replicates) and (2) no reads for ESVs that were relatively abundant in the other replicates, indicating possible PCR inhibition from clay, polysaccharides, or humic substances in the samples [67]. For the remaining samples, non-target sequences (i.e., eukaryotes, chloroplasts, and mitochondria) were removed, and read counts were transformed to relative proportions per sample [68].
The overall compositions of microbial communities were viewed across seasons and treatments at the order level [69]. Potentially pathogenic microbes (PPM) were identified as ESVs with a 100% match [70] to one or more known or suspected pathogens for humans, animals, vascular plants, and/or macroalgae based on a literature review [9,33,34,35,36,37,38,39,40,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148] (Table S1). PPM proportions were square root transformed to reduce the influence of dominant taxa [149], and differences in community composition were identified using a two-way crossed analysis of similarities (ANOSIM) [150] and visualized via non-metric multidimensional scaling (nMDS) plots based on Bray–Curtis similarities [151]. Groups were considered different via ANOSIM only when R ≥ 0.2 and p < 0.05 [152]. A two-way similarity percentage analysis (SIMPER) was then used to determine the key taxa characterizing each group [152], which were defined as those contributing ≥ 10% to the overall similarity between replicate samples. Relationships between PPM composition and environmental variables were identified using distance-based linear models (DistLM, Best, adjusted R2). Raw and transformed relative abundance and richness data failed normality (Shapiro–Wilk test) and homogeneity (Levene’s test), which are assumptions of the parametric two-way ANOVAs that were intended to detect differences in both metrics among treatments and seasons. Therefore, non-parametric two-way mixed ANOVAs (bwtrim function) and subsequent post hoc tests (mcp2atm function) were used [64,153]. Mann–Whitney U tests were used to detect seasonal differences in temperature and salinity after those data also failed normality and homogeneity tests [154].

3. Results

The results tables for all statistical tests are reported in the Supplementary Materials (Tables S1–S5). Water temperatures were higher (p < 0.0001) in July (29.4 ± 0.2 °C) compared to January (17.4 ± 0.7 °C). No significant difference in seasonal salinity was detected, but salinity varied widely across sites, from 0 to 37 ppt (Table 1). A total of 1830 microbial ESVs (1812 Bacteria and 18 Archaea) were found across the 227 samples. The average ESV richness was 144 ± 3 per sample, ranging from 12 (OF, site MLC, July) to 265 (SO, site SVP, July). Water and biodeposit microbial communities differed overall during both seasons (Figure 2). In January, the dominant orders were the SAR11 clade in water and Vibrionales and Camplyobacterales in biodeposits. In July, Thiotrichales and Alteromonadales were common in water, and biodeposits were dominated by Geobacterales, PeM15, and Actinomarinales.
A deeper investigation of the microbial communities revealed 52 ESVs across 5 phyla and 20 families that were identified as PPM (Table S6), with per-sample relative abundances detected at up to 61.4%. In both January and July, the relative abundance and taxonomic richness of PPM were higher in OF and OP compared to all other treatments (p < 0.0001; Figure 3). PPM community composition differed (Figure 4) between seasons (R = 0.734, p = 0.001) and among treatments (R = 0.443, p = 0.001). Pairwise comparisons following the two-way crossed ANOSIM revealed that the treatments were split into two groups based on PPM composition—oyster biodeposits (OF and OP) and water (LW, OW, and SO) (R ≥ 0.494, p = 0.001)—with no significant differences found within these two groups. There was little overlap in the PPM detected from the biodeposits and from the water used for the depuration tanks (MLC, VER, and IND), and relative abundances were generally higher in the biodeposits when PPM overlap did occur (Figure 5). While water temperature and salinity were both significant contributors to PPM community composition (p = 0.001), temperature explained 19.8% of the variation compared to only 4.1% for salinity.
A few PPM ESVs were notably unique among sites or treatments, such as ESV_016069 (Bacteroidaceae, Bacteroides sp.) and ESV_072564 (Arcobacteraceae, Arcobacter sp.), which were only detected in samples from stormwater site POW (Figure 5, Table S6). However, the largescale differences in PPM composition between seasons and among treatments were primarily driven by prevalent and abundant taxa from the families Pseudoalteromonadaceae and Vibrionaceae, with five ESVs contributing most to those differences: ESV_008978, ESV_010267, ESV_010681, ESV_033709, and ESV_069904 (Figure 5). ESV_069904 (Vibrionaceae, Vibrio sp.) was the most abundant microbe in the January biodeposits, being found at all sites and reaching a relative abundance of 31.2% (OF, site DRI). Although it was also present in the water column in January, it was found primarily in OW samples, where it never exceeded a relative abundance of 0.6%. The January biodeposits were also characterized by ESV_033709 and ESV_010267 (both Pseudoalteromonadaceae, Pseudoalteromonas sp.). In July, ESV_069904 was not detected in any samples, except OP from site MLC. Instead, the July PPM composition was largely characterized by ESV_008978 (Pseudoalteromonadaceae, Pseudoalteromonas sp.) and ESV_010681 (Vibrionaceae, Vibrio sp.). Both ESVs were found in biodeposits from nearly all oyster reef sites in both seasons but were more plentiful in July, with relative abundances up to 19.8% (OF, site MLB). In water samples, they were found almost exclusively in July, with only ESV_010681 being detected in January (OW, sites MLC and RIV). In addition to these five major contributors, several other ESVs primarily found in biodeposits also exhibited seasonal patterns (Figure 5). ESV_069856 (Flavobacteriaceae, Tenacibaculum sp.), ESV_073069, and ESV_073075 (both Alteromonadaceae, Shewanella sp.) were more prevalent in January, while ESV_010878 (Vibrionaceae, Vibrio sp.) and ESV_073954 (Oceanospirillaceae, Oceanospirillum sp.) were found more in July. Examples of the potential pathogenicity of each of the 52 ESVs from the literature review are listed in Table S1. Taxa matching the ESVs have been documented as known or suspected pathogens in humans, a variety of animals from cattle to corals to crustaceans, vascular plants, and macroalgae.

4. Discussion

Microbial communities from water and biodeposits exhibited broad-scale differences in their composition during both seasons. Water samples contained high relative abundances of SAR11 in January and Thiotrichales and Alteromonadales in July. SAR11 dominates surface bacterioplankton communities [155,156]. Thiotrichales and Alteromonadales have been documented as two of the most abundant orders forming biofilms on suspended plastic particles [157]. Therefore, their abundance in water samples in this study was unsurprising. SAR11 is not a pathogen of concern, but both Thiotrichales and Altermonadales contain several known and suspected pathogens [158,159]. The orders that dominated biodeposit samples also varied in their potential to contain pathogens. For example, Vibrionales and Campylobacterales, which were abundant in January, have been frequently associated with human and animal diseases [69,144,160,161,162]. Conversely, Geobacterales, which was abundant in the July biodeposit samples, is potentially quite beneficial. It is key in biogeochemical cycling and is being investigated for its use in bioelectrochemistry and bioenergy applications [163]. This order-level analysis illustrates that microbial communities are complex assemblages containing both beneficial and harmful taxa, and it emphasizes the need for a more detailed investigation to detect PPM.
Per volume, the oyster biodeposits contained more diverse and abundant PPM that produced a different community composition than what was detected in the water column (Figure 2, Figure 3, Figure 4 and Figure 5). These results reinforce similar findings from other studies that have compared pathogen densities between oysters and water [164,165] and highlight the ability for oysters to concentrate PPM by filtering large water volumes. Crassostrea virginica is one of the most prolific suspension feeders in estuaries within its range. In a laboratory bacterial depletion study using water collected from the IRL, Galimany et al. [25] found that a single adult oyster can clear approximately 3 L of water and remove 1.5 × 105 suspended bacterial cells per hour. Bacterial removal can increase further when multiple cells are clumped together or are aggregated with larger particles (e.g., sediment, detritus, plankton, microplastics) that oysters filter more efficiently [27,166,167]. These aggregates can especially facilitate the uptake of the many surface- and sediment-associated PPM, like Vibrio spp. [26,168,169] and Pseudoalteromonas spp. [101,170,171], which were abundant in the present study. In fact, three common pathogenic vibrios—V. parahaemolyticus, V. vulnificus, and V. cholerae—have been detected in IRL sediments at concentrations three orders of magnitude higher than in the water column [19]. In addition to filtering these bacteria-laden sediments, the oysters may have also refiltered old biodeposits that are commonly resuspended [172,173,174], resulting in new, more concentrated biodeposit pathogen loads.
Strong seasonality was also detected for the microbial communities in this study, with the July samples containing a different community composition compared to those from January (Figure 2, Figure 4 and Figure 5). These results are not surprising, as it has been well established that many microbes grow better in warm waters [175,176,177,178,179,180,181]. Indeed, the relationship between pathogen emergence and sea surface temperature extends beyond individual systems to be recognized globally as a concerning consequence of climate change [182,183,184,185,186]. Conversely, work on congeners of taxa that were more prevalent in January, such as Tenacibaculum sp. and Shewanella sp. (Figure 5), suggests that their wide temperature tolerances may give them a competitive advantage in winter [187,188,189]. Although PPM richness and relative abundance did not differ between January and July, changes in their community composition highlight the need for further investigations of microbial seasonality. This is especially important as estuaries continue to warm, with water in the IRL reaching summer highs > 33 °C (IRLON: Indian River Lagoon Observatory Network of Environmental Sensors, Florida Atlantic University Harbor Branch, irlon.org) at the time of writing this paper. However, temperature accounted for just 20% of the total variation in PPM community composition herein, emphasizing that other factors were also important.
Salinity has been identified as an additional driver of pathogen composition in estuaries, especially among Vibrio spp. [19,190]. However, studies have demonstrated that this relationship is not linear when salinities vary widely [191,192]. In this investigation, salinity accounted for only 4% of PPM community variation. This may have been partly due to the wide salinity range among sites and seasons and the below average watershed precipitation during the 2021 wet season [193]. Lower precipitation surely also resulted in less PPM entering the IRL through stormwater outfalls than expected. Future investigations exploring the effects of salinity on estuarine PPM should sample before and after rain events and across multiple wet and dry seasons to account for annual variation.
Turbidity and chlorophyll are frequent drivers of pathogen composition in estuaries [164,165,191,194], and they were likely influential in this study as well. Although not measured during sample collection, both metrics differed in the IRL between the sampling seasons. A monitoring station located near the SEB oyster reef site (IRL-SB, maintained by Florida Atlantic University, hourly data) recorded higher chlorophyll and turbidity values in July than in January (p < 0.0001, Mann–Whitney U). Similar seasonal differences likely occurred at the other sites, especially those located away from inlets where tidal flushing is minimal. Pathogen composition can be altered by the suspended particles that are abundant during high-chlorophyll and/or high-turbidity events. For example, Johnson et al. [191] investigated the environmental factors associated with the abundances and distributions of pathogenic Vibrio parahaemolyticus and V. vulnificus in the northern Gulf of Mexico. The authors found that turbidity was a significant predictor of V. parahaemolyticus but not V. vulnificus. Moreover, the former species was more abundant in sediments than the latter, suggesting that the resuspension of the sediment grains to which it was attached was a driving factor behind its abundance in the water column during high-turbidity events. Similarly, positive relationships between chlorophyll a and pathogen concentrations could be caused by bacteria attached to the zooplankton that are feeding on developing phytoplankton blooms [195]. Such findings further support the potential for suspended particles to engineer differences in water column and biodeposit PPM communities by shifting the ratio of attached versus free-living bacteria, with attached bacteria being filtered more easily by oysters and other suspension feeders.
Although the biodeposit PPM loads detected in this study are concerning from the perspective of fisheries, the strong similarity between OP and OF PPM communities demonstrates that these microbes were present in both the ingested and rejected fractions and were not selectively taken up. The biodeposit PPM communities (Figure 5, Table S6) also appeared quite different overall from those commonly reported in C. virginica gut and muscle tissue [196,197,198], which may be more difficult for the oysters to excrete [199]. Hence, it is likely that recommended depuration methods [200,201] could be used to help purge harvested oysters of the microbes detected in this study, thereby reducing the human health risks associated with oyster consumption in the IRL.
Likely of greater concern is the potential for oyster reefs to function as hot spots for PPM by condensing pathogens onto the benthos [202], where they can both infect reef inhabitants and be moved through the ecosystem via trophic transfer. Oyster reefs are homes to diverse assemblages of polychaetes, crustaceans, molluscs, and other animals [203,204,205,206] that can be infected by contacting or consuming the pathogens potentially found in the biodeposit samples investigated in this study [114,120,135]. Infected animals often die, but they can also spread pathogens to higher-level predators such as wading birds [207] and several commercially and recreationally important fishery species, including juvenile groupers, snappers and flounders, and adult drum and sheepshead [179,208]. Many of these benthic-feeding fish tend to have higher pathogen concentrations than those feeding on pelagic prey [179], possibly causing diseases in the fish [121] and in the humans consuming them [209]. These connections establish a trophic pathway for pathogenic microbes that likely began, in part, with suspension feeding by oysters and will likely continue to intensify in increasingly populated coastal systems contending with eutrophication and climate change.

5. Conclusions

This study provides evidence that oyster reefs in the IRL estuary are a reservoir for PPM and documents some possible taxa of concern that should be positively identified and investigated further for their pathogenicity and potential to pervade food webs and fisheries. PPM were more diverse and abundant in oyster biodeposits than in the water column and were different in summer compared to winter. The seasonal differences were most likely due to a suite of drivers that included water temperature and, presumably, the turbidity and chlorophyll levels across the sites. The results also suggest that these environmental drivers helped to engineer PPM community structure in the treatments by regulating microbial growth and facilitating the uptake of certain taxa by oysters. The metabarcoding used in this study is not sufficient to conclusively identify pathogens from the many innocuous and beneficial taxa that exist. However, it is shown here as an effective tool to explore spatial and temporal differences in PPM communities and to highlight PPM hotspots that can be further investigated using other technologies designed for pathogen detection and virulence assessment. PPM monitoring in estuaries is becoming increasingly important as climate change and urbanization elevate water temperatures and concentrations of suspended particles that can serve as pathogen vectors.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/environments10120205/s1, Table S1. Differences in temperature and salinity between seasons; Table S2. Differences in PPM relative abundance and richness between groups; Table S3. Differences in PPM community composition between groups; Table S4. Effects of temperature and salinity on PPM community composition; Table S5. Key PPM taxa defining each group; Table S6: Taxonomic hierarchy of the 52 ESVs with 100% identity match to one or more potentially pathogenic microbes (PPM).

Author Contributions

Conceptualization, L.J.W., L.H.S., J.W. and E.D.; Methodology, L.H.S., L.J.W. and C.A.C.; Software, L.H.S.; Validation, L.H.S.; Formal Analysis, L.H.S.; Investigation, L.H.S., S.J.B., C.A.C., E.D., T.S.-T., J.W., P.E.S. and L.J.W.; Resources, L.J.W., L.H.S., J.W. and E.D.; Data Curation, L.H.S., T.S.-T., E.D. and P.E.S.; Writing—Original Draft Preparation, L.H.S.; Writing—Review and Editing, L.J.W., J.W., T.S.-T., E.D., S.J.B., C.A.C. and P.E.S.; Visualization, L.H.S.; Supervision, L.J.W., L.H.S., J.W. and E.D.; Project Administration, L.J.W. and L.H.S.; Funding Acquisition, L.J.W., L.H.S., J.W. and E.D. All authors have read and agreed to the published version of the manuscript.

Funding

This research article was funded by the Indian River Lagoon National Estuary Program, grant number IRL 2020-16.

Data Availability Statement

The data presented in this study are openly available in FigShare at: [https://doi.org/10.25573/data.24631914.v1], reference number [210]; [https://doi.org/10.25573/data.24631956.v1], reference number [211]; [https://doi.org/10.25573/data.24631962.v1], reference number [212]; [https://doi.org/10.25573/data.24632091.v1], reference number [213]; [https://doi.org/10.25573/data.24632094.v1], reference number [214]; and [https://doi.org/10.25573/data.24632157.v1], reference number [215].

Acknowledgments

We thank the Marine Discovery Center, the University of Central Florida, and the Florida Department of Environmental Protection IRL Aquatic Preserves Program for orchestrating and conducting sample collection. We would like to express our appreciation for the Smithsonian Marine Station and the National Museum of Natural History’s Laboratories for Analytical Biology for providing consumables and equipment for DNA extraction. We thank Smithsonian scientists Jennifer Sneed for project support and Alyssa Demko for reviewing a draft of the manuscript. Finally, we appreciate the work of all the volunteers who helped with sample processing and data collection.

Conflicts of Interest

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

References

  1. Freeman, L.A.; Corbett, D.R.; Fitzgerald, A.M.; Lemley, D.A.; Quigg, A.; Steppe, C.N. Impacts of urbanization and development on estuarine ecosystems and water quality. Estuar. Coast. 2019, 42, 1821–1838. [Google Scholar] [CrossRef]
  2. Landrigan, P.J.; Stegeman, J.J.; Fleming, L.E.; Allemand, D.; Anderson, D.M.; Backer, L.C.; Brucker-Davis, F.; Chevalier, N.; Corra, L.; Czerucka, D.; et al. Human health and ocean pollution. Ann. Glob. Health 2020, 86, 151. [Google Scholar] [CrossRef] [PubMed]
  3. Jacobs, J.; Rhodes, M.; Sturgis, B.; Wood, B. Influence of environmental gradients on the abundance and distribution of Mycobacterium spp. in a coastal lagoon estuary. Appl. Environ. Microbiol. 2009, 75, 7378–7384. [Google Scholar] [CrossRef] [PubMed]
  4. Janda, J.M.; Abbott, S.L. The genus Aeromonas: Taxonomy, pathogenicity, and infection. Clin. Microbiol. Rev. 2010, 23, 35–73. [Google Scholar] [CrossRef]
  5. Ghaderpour, A.; Mohd Nasori, K.N.; Chew, L.L.; Chong, V.C.; Thong, K.L.; Chai, L.C. Detection of multiple potentially pathogenic bacteria in matang mangrove estuaries, Malaysia. Mar. Pollut. Bull. 2014, 83, 324–330. [Google Scholar] [CrossRef] [PubMed]
  6. Ochsenkühn, M.A.; Fei, C.; Bayaara, O.; Romeo, E.; Amosa, P.; Idaghdour, Y.; Goldstein, G.; Bromage, T.G.; Amin, S.A. Microbial contamination survey of environmental fresh and saltwater resources of Upolu Island, Samoa. Environments 2021, 8, 112. [Google Scholar] [CrossRef]
  7. Hooban, B.; Fitzhenry, K.; O’Connor, L.; Miliotis, G.; Joyce, A.; Chueiri, A.; Farrell, M.L.; DeLappe, N.; Tuohy, A.; Cormican, M.; et al. A longitudinal survey of antibiotic-resistant Enterobacterales in the Irish environment, 2019–2020. Sci. Total Environ. 2022, 828, 154488. [Google Scholar] [CrossRef]
  8. Grimes, D.J. Ecology of estuarine bacteria capable of causing human disease: A review. Estuaries 1991, 14, 345–360. [Google Scholar] [CrossRef]
  9. Thompson, J.R.; Marcelino, L.A.; Polz, M.F. Diversity, sources, and detection of human bacterial pathogens in the marine environment. In Oceans and Health: Pathogens in the Marine Environment; Springer: New York, NY, USA, 2005; pp. 29–68. [Google Scholar] [CrossRef]
  10. Rose, J.B.; Epstein, P.R.; Lipp, E.K.; Sherman, B.H.; Bernard, S.M.; Patz, J.A. Climate variability and change in the United States: Potential impacts on water- and foodborne diseases caused by microbiologic agents. Environ. Health Perspect. 2001, 109, 211–221. [Google Scholar] [CrossRef]
  11. Hassard, F.; Gwyther, C.L.; Farkas, K.; Andrews, A.; Jones, V.; Cox, B.; Brett, H.; Jones, D.L.; McDonald, J.E.; Malham, S.K. Abundance and distribution of enteric bacteria and viruses in coastal and estuarine sediments-a review. Front. Microbiol. 2016, 7, 1692. [Google Scholar] [CrossRef]
  12. Indian River Lagoon Species Inventory. Available online: https://irlspecies.org (accessed on 22 August 2023).
  13. United States Environmental Protection Agency. Local Estuary Programs. Available online: https://www.epa.gov/nep/local-estuary-programs (accessed on 22 August 2023).
  14. Phlips, E.J.; Badylak, S.; Christman, M.C.; Lasi, M.A. Climatic trends and temporal patterns of phytoplankton composition, abundance, and succession in the Indian River Lagoon, Florida, USA. Estuar. Coast. 2010, 33, 498–512. [Google Scholar] [CrossRef]
  15. Lapointe, B.E.; Herren, L.W.; Brewton, R.A.; Alderman, P.K. Nutrient over-enrichment and light limitation of seagrass communities in the Indian River Lagoon, an urbanized subtropical estuary. Sci. Total Environ. 2020, 699, 134068. [Google Scholar] [CrossRef] [PubMed]
  16. Lopez, C.B.; Tilney, C.L.; Muhlbach, E.; Bouchard, J.N.; Villac, M.C.; Henschen, K.L.; Markley, L.R.; Abbe, S.K.; Shankar, S.; Shea, C.P.; et al. High-resolution spatiotemporal dynamics of harmful algae in the Indian River Lagoon (Florida)—A case study of Aureoumbra lagunensis, Pyrodinium bahamense, and Pseudo-Nitzschia. Front. Mar. Sci. 2021, 8, 769877. [Google Scholar] [CrossRef] [PubMed]
  17. Parkinson, R.W.; Seidel, V.; Henderson, C.; De Freese, D. Adaptation actions to reduce impairment of Indian River Lagoon water quality caused by climate change, Florida, USA. Coast. Manag. 2021, 49, 215–232. [Google Scholar] [CrossRef]
  18. Sweat, L.H.; Stephens, M.; Reed, S.A. Insights from 15 Years of benthic infaunal monitoring in a coastal lagoon system. Fla. Sci. 2021, 84, 147–161. [Google Scholar]
  19. Barbarite, G.M. The Occurrence of Vibrio vulnificus, V. parahaemolyticus and V. cholerae in the Indian River Lagoon, Florida, with Implications for Human Health. Ph.D. Thesis, Florida Atlantic University, Boca Raton, FL, USA, 2016. Available online: https://www.proquest.com/dissertations-theses/occurrence-i-vibrio-vulnificus-v-parahaemolyticus/docview/1847569447/se-2?accountid=46638 (accessed on 21 November 2023).
  20. Bradshaw, D.J.; Dickens, N.J.; Trefry, J.H.; McCarthy, P.J. Defining the sediment prokaryotic communities of the Indian River Lagoon, FL, USA, an Estuary of National Significance. PLoS ONE 2020, 15, e0236305. [Google Scholar] [CrossRef] [PubMed]
  21. Grant, T.A.; Jayakumar, J.M.; López-Pérez, M.; Almagro-Moreno, S. Vibrio floridensis sp. nov., a novel species closely related to the human pathogen Vibrio vulnificus isolated from a cyanobacterial bloom. Int. J. Syst. Evol. Microbiol. 2023, 73, 005675. [Google Scholar] [CrossRef]
  22. López-Pérez, M.; Jayakumar, J.M.; Grant, T.A.; Zaragoza-Solas, A.; Cabello-Yeves, P.J.; Almagro-Moreno, S. Ecological diversification reveals routes of pathogen emergence in endemic Vibrio vulnificus populations. Proc. Natl. Acad. Sci. USA 2021, 118, e2103470118. [Google Scholar] [CrossRef]
  23. Kirby, M.X.; Miller, H.M. Response of a benthic suspension feeder (Crassostrea virginica Gmelin) to three centuries of anthropogenic eutrophication in Chesapeake Bay. Estuar. Coast. Shelf Sci. 2005, 62, 679–689. [Google Scholar] [CrossRef]
  24. Grizzle, R.E.; Greene, J.K.; Coen, L.D. Seston removal by natural and constructed intertidal eastern oyster (Crassostrea virginica) reefs: A comparison with previous laboratory studies, and the value of in situ methods. Estuar. Coast. 2008, 31, 1208–1220. [Google Scholar] [CrossRef]
  25. Galimany, E.; Freeman, C.J.; Lunt, J.; Domingos, A.; Sacks, P.; Walters, L. Feeding competition between the native oyster Crassostrea virginica and the invasive mussel Mytella charruana. Mar. Ecol. Prog. Ser. 2017, 564, 57–66. [Google Scholar] [CrossRef]
  26. Froelich, B.; Ayrapetyan, M.; Oliver, J.D. Integration of Vibrio vulnificus into marine aggregates and its subsequent uptake by Crassostrea virginica oysters. Appl. Environ. Microbiol. 2013, 79, 1454–1458. [Google Scholar] [CrossRef]
  27. Fabra, M.; Williams, L.; Watts, J.E.M.; Hale, M.S.; Couceiro, F.; Preston, J. The plastic trojan horse: Biofilms increase microplastic uptake in marine filter feeders impacting microbial transfer and organism health. Sci. Total Environ. 2021, 797, 149217. [Google Scholar] [CrossRef] [PubMed]
  28. Galimany, E.; Lunt, J.; Freeman, C.J. Bivalve feeding on the brown tide Aureoumbra lagunensis in a shallow coastal environment. Front. Mar. Sci. 2021, 8, 714816. [Google Scholar] [CrossRef]
  29. Langdon, C.; Newell, R. Utilization of detritus and bacteria as food sources by two bivalve suspension-feeders, the oyster Crassostrea virginica and the mussel Geukensia demissa. Mar. Ecol. Prog. Ser. 1989, 58, 299–310. [Google Scholar] [CrossRef]
  30. Newell, R.I.; Jordan, S.J. Preferential ingestion of organic material by the American oyster Crassostrea virginica. Mar. Ecol. Prog. Ser. 1983, 13, 47–53. [Google Scholar] [CrossRef]
  31. Ward, J.E.; Newell, R.I.E.; Thompson, R.J.; MacDonald, B.A. In vivo studies of suspension-feeding processes in the eastern oyster, Crassostrea virginica (Gmelin). Biol. Bull. 1994, 186, 221–240. [Google Scholar] [CrossRef] [PubMed]
  32. Carmichael, R.H.; Walton, W.; Clark, H. Bivalve-enhanced nitrogen removal from coastal estuaries. Can. J. Fish. Aquat. Sci. 2012, 69, 1131–1149. [Google Scholar] [CrossRef]
  33. Ishimaru, K.; Akagawa-Matsushita, M.; Muroga, K. Vibrio ichthyoenteri sp. nov., a pathogen of Japanese flounder (Paralichthys olivaceus) larvae. Int. J. Syst. Bacteriol. 1996, 46, 155–159. [Google Scholar] [CrossRef]
  34. Austin, B.; Austin, D.; Sutherland, R.; Thompson, F.; Swings, J. Pathogenicity of vibrios to rainbow trout (Oncorhynchus mykiss, Walbaum) and Artemia nauplii. Environ. Microbiol. 2005, 7, 1488–1495. [Google Scholar] [CrossRef]
  35. Austin, B.; Zhang, X.H. Vibrio harveyi: A significant pathogen of marine vertebrates and invertebrates. Lett. Appl. Microbiol. 2006, 43, 119–124. [Google Scholar] [CrossRef] [PubMed]
  36. Gardan, L.; Dauga, C.; Prior, P.; Gillis, M.; Saddler, G.S. Acidovorax anthurii sp. nov., a new phytopathogenic bacterium which causes bacterial leaf-spot of Anthurium. Int. J. Syst. Evol. Microbiol. 2000, 50, 235–246. [Google Scholar] [CrossRef] [PubMed]
  37. Liang, Z.; Lin, X.; Liao, Y.; Tang, T. Characteristics and diversity of endophytic bacteria in Panax notoginseng under high temperature analysed using full-length 16S RRNA sequencing. Arch. Microbiol. 2022, 204, 435. [Google Scholar] [CrossRef] [PubMed]
  38. Sawabe, T.; Tanaka, R.; Iqbal, M.M.; Tajima, K.; Ezura, Y.; Ivanova, E.P.; Christen, R. Assignment of Alteromonas elyakovii KMM 162(T) and five strains isolated from spot-wounded fronds of Laminaria japonica to Pseudoalteromonas elyakovii comb. nov. and the extended description of the species. Int. J. Syst. Evol. Microbiol. 2000, 50, 265–271. [Google Scholar] [CrossRef]
  39. Yang, H.; Yan, Y.; Li, J.; Tang, L.; Mao, Y.; Mo, Z. Development of a PCR method for detection of Pseudoalteromonas marina associated with green spot disease in Pyropia yezoensis. J. Oceanol. Limnol. 2020, 38, 168–176. [Google Scholar] [CrossRef]
  40. Zhang, X.; Chen, Y.; Saha, M.; Zhuang, Y.; Chang, L.; Xiao, L.; Wang, G. Pseudoalteromonas piscicida X-8 causes bleaching disease in farmed Saccharina japonica. Aquaculture 2022, 546, 737354. [Google Scholar] [CrossRef]
  41. Richards, G.P.; Watson, M.A.; Crane, E.J.; Burt, I.G.; Bushek, D. Shewanella and Photobacterium spp. in oysters and seawater from the Delaware Bay. Appl. Environ. Microbiol. 2008, 74, 3323–3327. [Google Scholar] [CrossRef]
  42. Weis, K.E.; Hammond, R.M.; Hutchinson, R.; Blackmore, C.G.M. Vibrio illness in Florida, 1998-2007. Epidemiol. Infect. 2011, 139, 591–598. [Google Scholar] [CrossRef]
  43. Wright, A.C.; Danyluk, M.D.; Otwell, W.S. Pathogens in raw foods: What the salad bar can learn from the raw bar. Curr. Opin. Biotechnol. 2009, 20, 172–177. [Google Scholar] [CrossRef]
  44. Indian River Oyster Company. Available online: https://irocoysters.com (accessed on 9 November 2023).
  45. Oysters and Clams: Recreational Regulations. Florida Fish and Wildlife Conservation Commission. Available online: https://myfwc.com/fishing/saltwater/recreational/shellfish (accessed on 13 August 2023).
  46. George, G.J.; Brown, K.M.; Peterson, G.W.; Thompson, B.A. Removal of black drum on Louisiana reefs to increase survival of eastern oysters Crassostrea virginica. N. Am. J. Fish. Manag. 2008, 28, 1802–1811. [Google Scholar] [CrossRef]
  47. Eggleston, D.B. Foraging behavior of the blue crab, Callinectes sapidus, on juvenile oysters, Crassostrea virginica: Effects of prey density and size. Bull. Mar. Sci. 1990, 46, 62–82. [Google Scholar]
  48. Cook, D.W.; Ellender, R.D. Relaying to decrease the concentration of oyster-associated pathogens. J. Food Prot. 1986, 49, 196–202. [Google Scholar] [CrossRef]
  49. Kramer, A.M.; Ward, J.E.; Dobbs, F.C.; Pierce, M.L.; Drake, J.M. The contribution of marine aggregate-associated bacteria to the accumulation of pathogenic bacteria in oysters: An agent-based model. Ecol. Evol. 2016, 6, 7397–7408. [Google Scholar] [CrossRef]
  50. Abeels, H.A.; Loh, A.N.; Volety, A.K. Trophic transfer and habitat use of oyster Crassostrea virginica reefs in southwest Florida, identified by stable isotope analysis. Mar. Ecol. Prog. Ser. 2012, 462, 125–142. [Google Scholar] [CrossRef]
  51. Busch, S.J.; Craig, C.A.; Wayles, J.; Sailor-Tynes, T.; Dark, E.; Sweat, L.H.; Fox, D.W.; Zhai, L.; Walters, L.J. Contribution of stormwater outfalls to microplastic pollution in a subtropical estuary using data collected with the assistance of citizen scientists. Environments 2023, 10, 181. [Google Scholar] [CrossRef]
  52. Sneed, J.M.; Ritson-Williams, R.; Paul, V.J. Crustose coralline algal species host distinct bacterial assemblages on their surfaces. ISME J. 2015, 9, 2527–2536. [Google Scholar] [CrossRef] [PubMed]
  53. Craig, C.A.; Fox, D.W.; Zhai, L.; Walters, L.J. In-situ microplastic egestion efficiency of the eastern oyster Crassostrea virginica. Mar. Pollut. Bull. 2022, 178, 113653. [Google Scholar] [CrossRef]
  54. Apprill, A.; Mcnally, S.; Parsons, R.; Weber, L. Minor revision to V4 region SSU RRNA 806R gene primer greatly increases detection of SAR11 bacterioplankton. Aquat. Microb. Ecol. 2015, 75, 129–137. [Google Scholar] [CrossRef]
  55. Parada, A.E.; Needham, D.M.; Fuhrman, J.A. Every Base matters: Assessing small subunit RRNA primers for marine microbiomes with mock communities, time series and global field samples. Environ. Microbiol. 2015, 18, 1403–1414. [Google Scholar] [CrossRef] [PubMed]
  56. Rajeev, M.; Sushmitha, T.J.; Toleti, S.R.; Pandian, S.K. Sediment-associated bacterial community and predictive functionalities are influenced by choice of 16S ribosomal RNA hypervariable region(s): An amplicon-based diversity study. Genomics 2020, 112, 4968–4979. [Google Scholar] [CrossRef] [PubMed]
  57. Galanti, L.; Shasha, D.; Gunsalus, K.C. Pheniqs 2.0: Accurate, high-performance bayesian decoding and confidence estimation for combinatorial barcode indexing. BMC Bioinform. 2021, 22, 359. [Google Scholar] [CrossRef] [PubMed]
  58. Martin, M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet J. 2011, 17, 10–12. [Google Scholar] [CrossRef]
  59. Rognes, T.; Flouri, T.; Nichols, B.; Quince, C.; Mahé, F. VSEARCH: A versatile open source tool for metagenomics. PeerJ 2016, 4, e2584. [Google Scholar] [CrossRef] [PubMed]
  60. Edgar, R.C. UNOISE2: Improved error-correction for Illumina 16S and ITS amplicon sequencing. bioRxiv 2016, 081257. [Google Scholar] [CrossRef]
  61. Edgar, R.C. UCHIME2: Improved chimera prediction for amplicon sequencing. bioRxiv 2016, 074252. [Google Scholar] [CrossRef]
  62. Quast, C.; Pruesse, E.; Yilmaz, P.; Gerken, J.; Schweer, T.; Yarza, P.; Peplies, J.; Glöckner, F.O. The SILVA ribosomal RNA gene database project: Improved data processing and web-based tools. Nucleic Acids Res. 2013, 41, 590–596. [Google Scholar] [CrossRef]
  63. McMurdie, P.J.; Holmes, S. Phyloseq: An R package for reproducible interactive analysis and graphics of microbiome census data. PLoS ONE 2013, 8, e61217. [Google Scholar] [CrossRef]
  64. Mair, P.; Wilcox, R. Robust Statistical Methods Using WRS2. 2018. Available online: https://cran.r-project.org/web/packages/WRS2/vignettes/WRS2.pdf (accessed on 21 November 2023).
  65. Dixon, P. VEGAN, a package of R functions for community ecology. J. Veg. Sci. 2003, 14, 927–930. [Google Scholar] [CrossRef]
  66. Allaire, J. RStudio: Integrated development environment for R. In Proceedings of the the R User Conference, useR! 2011, University of Warwick. Coventry, UK, 16–18 August 2011. [Google Scholar]
  67. Schrader, C.; Schielke, A.; Ellerbroek, L.; Johne, R. PCR inhibitors—Occurrence, properties and removal. J. Appl. Microbiol. 2012, 113, 1014–1026. [Google Scholar] [CrossRef]
  68. McKnight, D.T.; Huerlimann, R.; Bower, D.S.; Schwarzkopf, L.; Alford, R.A.; Zenger, K.R. Methods for normalizing microbiome data: An ecological perspective. Methods Ecol. Evol. 2019, 10, 389–400. [Google Scholar] [CrossRef]
  69. Oetama, V.S.P.; Hennersdorf, P.; Abdul-Aziz, M.A.; Mrotzek, G.; Haryanti, H.; Saluz, H.P. Microbiome analysis and detection of pathogenic bacteria of Penaeus monodon from Jakarta Bay and Bali. Mar. Pollut. Bull. 2016, 110, 718–725. [Google Scholar] [CrossRef] [PubMed]
  70. Edgar, R.C. Updating the 97% identity threshold for 16S ribosomal RNA OTUs. Bioinformatics 2018, 34, 2371–2375. [Google Scholar] [CrossRef] [PubMed]
  71. Mastroianni, A. Mycobacterium flavescens vertebral osteomyelitis in an immunocompetent host. Infez. Med. 2003, 11, 97–101. [Google Scholar] [PubMed]
  72. Zhao, X.L.; Qi, Z.; Huang, H.; Tu, J.; Song, X.J.; Qi, K.Z.; Shao, Y. Diversity and distribution of potential pathogens and antibiotic resistance genes in anthropogenic disturbances aquatic environment and their relationship with microbial indicators. Res. Sq. 2021, preprint. 1–28. [Google Scholar] [CrossRef]
  73. Espiritu, H.M.; Mamuad, L.L.; Kim, S.H.; Jin, S.J.; Lee, S.S.; Kwon, S.W.; Cho, Y. Il Microbiome shift, diversity, and overabundance of opportunistic pathogens in bovine digital dermatitis revealed by 16S rRNA amplicon sequencing. Animals 2020, 10, 1798. [Google Scholar] [CrossRef]
  74. Good, C.; Davidson, J.; Wiens, G.D.; Welch, T.J.; Summerfelt, S. Flavobacterium branchiophilum and F. succinicans associated with bacterial gill disease in rainbow trout Oncorhynchus mykiss (Walbaum) in water recirculation aquaculture systems. J. Fish Dis. 2015, 38, 409–413. [Google Scholar] [CrossRef] [PubMed]
  75. Chen, S.; Blom, J.; Loch, T.P.; Faisal, M.; Walker, E.D. The emerging fish pathogen Flavobacterium spartansii isolated from Chinook salmon: Comparative genome analysis and molecular manipulation. Front. Microbiol. 2017, 8, 2339. [Google Scholar] [CrossRef]
  76. Dong, H.T.; Nguyen, V.V.; Mata, W.; Kayansamruaj, P.; Senapin, S.; Nilubol, D.; Rodkhum, C. Diversity of non-Flavobacterium columnare bacteria associated with columnaris-like diseased fish. Thai J. Vet. Med. 2016, 46, 251–259. [Google Scholar] [CrossRef]
  77. Fernández-Álvarez, C.; Santos, Y. Identification and typing of fish pathogenic species of the genus Tenacibaculum. Appl. Microbiol. Biotechnol. 2018, 102, 9973–9989. [Google Scholar] [CrossRef]
  78. Tesdorpf, J.E.; Geers, A.U.; Strube, M.L.; Gram, L.; Bentzon-Tilia, M. Roseobacter group probiotics exhibit differential killing of fish pathogenic Tenacibaculum species. Appl. Environ. Microbiol. 2022, 88, e02418-21. [Google Scholar] [CrossRef]
  79. Ferreira, S.; Queiroz, J.A.; Oleastro, M.; Domingues, F.C. Insights in the pathogenesis and resistance of Arcobacter: A review. Crit. Rev. Microbiol. 2016, 42, 364–383. [Google Scholar] [CrossRef]
  80. Pitt, T.L.; Malnick, H.; Shah, J.; Chattaway, M.A.; Keys, C.J.; Cooke, F.J.; Shah, H.N. Characterisation of Exiguobacterium aurantiacum isolates from blood cultures of six patients. Clin. Microbiol. Infect. 2007, 13, 946–948. [Google Scholar] [CrossRef]
  81. Hu, N.; Zou, W.; Cai, Q.; Liu, Y.; Chen, K.; Li, M.; Tan, Y.; Zhu, Q.; Zeng, L. The first report of cerebral nocardiosis caused by Nocardia terpenica together with Exiguobacterium profundum bacteremia. Jundishapur J. Microbiol. 2018, 11, e69604. [Google Scholar] [CrossRef]
  82. Patnool, R.B.; Vithya, T.; Wadhwani, A.; Balasubramaniam, V.; Ponnusankar, S. Streptococcal infections: Race to multidrug resistance—A review. J. Appl. Pharm. Sci. 2022, 12, 1–10. [Google Scholar] [CrossRef]
  83. Plassart, C.; Mauvais, F.; Heurté, J.; Sautereau, J.; Legeay, C.; Bouvet, P. First case of intra-abdominal infection with Clostridium disporicum. Anaerobe 2013, 19, 77–78. [Google Scholar] [CrossRef] [PubMed]
  84. Yoon, E.; Kim, T.Y.; Heo, W.Y.; Kang, O.; Yu, H.J.; Lee, J.H.; Ko, J.H.; Lee, N.Y.; Huh, H.J. The first case of Clostridium saudiense bacteremia in a patient with hepatocellular carcinoma. Ann. Lab. Med. 2022, 42, 491–493. [Google Scholar] [CrossRef]
  85. Fanci, R.; Corti, G.; Bartoloni, A.; Tortoli, E.; Mariottini, A.; Pecile, P. Unusual Methylobacterium fujisawaense infection in a patient with acute leukaemia undergoing hematopoietic stem cell transplantation: First Case Report. Case Rep. Med. 2010, 2010, 313514. [Google Scholar] [CrossRef]
  86. Sanders, J.W.; Martin, J.W.; Hooke, M.; Hooke, J. Methylobacterium mesophilicum infection: Case report and literature review of an unusual opportunistic pathogen. Clin. Infect. Dis. 2000, 30, 936–938. [Google Scholar] [CrossRef]
  87. Li, L.; Tarrand, J.J.; Han, X.Y. Microbiological and clinical features of four cases of catheter-related infection by Methylobacterium radiotolerans. J. Clin. Microbiol. 2015, 53, 1375–1379. [Google Scholar] [CrossRef]
  88. Basso, M.; Venditti, C.; Raponi, G.; Navazio, A.S.; Alessandri, F.; Giombini, E.; Nisii, C.; Di Caro, A.; Venditti, M. A Case of persistent bacteraemia by Ralstonia mannitolilytica and Ralstonia pickettii in an Intensive care unit. Infect. Drug Resist. 2019, 12, 2391–2395. [Google Scholar] [CrossRef]
  89. Ryan, M.P.; Pembroke, J.T.; Adley, C.C. Ralstonia pickettii: A persistent gram-negative nosocomial infectious organism. J. Hosp. Infect. 2006, 62, 278–284. [Google Scholar] [CrossRef] [PubMed]
  90. Yuwono, C.; Wehrhahn, M.C.; Liu, F.; Riordan, S.M.; Zhang, L. The isolation of Aeromonas species and other common enteric bacterial pathogens from patients with gastroenteritis in an Australian population. Microorganisms 2021, 9, 1440. [Google Scholar] [CrossRef] [PubMed]
  91. De Luca, F.; Giraud-Morin, C.; Rossolini, G.M.; Docquier, J.D.; Fosse, T. Genetic and biochemical characterization of TRU-1, the endogenous Class C β-lactamase from Aeromonas enteropelogenes. Antimicrob. Agents Chemother. 2010, 54, 1547–1554. [Google Scholar] [CrossRef] [PubMed]
  92. Esteve, C.; Amaro, C.; Toranzo, A.E. O-Serogrouping and surface components of Aeromonas hydrophila and Aeromonas jandaei pathogenic for eels. FEMS Microbiol. Lett. 1994, 117, 85–90. [Google Scholar] [CrossRef] [PubMed]
  93. Choudhury, J.D.; Pramanik, A.; Webster, N.S.; Llewellyn, L.E.; Gachhui, R.; Mukherjee, J. The pathogen of the Great Barrier Reef sponge Rhopaloeides odorabile is a new strain of Pseudoalteromonas agarivorans containing abundant and diverse virulence-related genes. Mar. Biotechnol. 2015, 17, 463–478. [Google Scholar] [CrossRef]
  94. Li, J.; Weinberger, F.; Saha, M.; Majzoub, M.E.; Egan, S. Cross-host protection of marine bacteria against macroalgal disease. Microb. Ecol. 2022, 84, 1288–1293. [Google Scholar] [CrossRef] [PubMed]
  95. Beurmann, S.; Ushijima, B.; Videau, P.; Svoboda, C.M.; Smith, A.M.; Rivers, O.S.; Aeby, G.S.; Callahan, S.M. Pseudoalteromonas piratica strain OCN003 is a coral pathogen that causes a switch from chronic to acute Montipora white syndrome in Montipora capitata. PLoS ONE 2017, 12, e0188319. [Google Scholar] [CrossRef]
  96. Jiang, F.; Huang, H.; Yang, N.; Feng, H.; Li, Y.; Han, B. Isolation, identification, and biological control in vitro of tail rot pathogen strain from Hippocampus kuda. PLoS ONE 2020, 15, e0232162. [Google Scholar] [CrossRef]
  97. Costa-Ramos, C.; Rowley, A.F. Effect of extracellular products of Pseudoalteromonas atlantica on the edible crab Cancer pagurus. Appl. Environ. Microbiol. 2004, 70, 729–735. [Google Scholar] [CrossRef]
  98. Li, M.; Wu, W.; You, W.; Huang, S.; Huang, M.; Luo, X.; Lu, Y.; Ke, C.; Xie, Q. A novel screening method for the detection of Pseudoalteromonas shioyasakiensis, an emerging opportunistic pathogen that caused the mass mortality of juvenile Pacific abalone (Haliotis discus Hannai) during a record-breaking heat wave. Aquaculture 2021, 545, 737191. [Google Scholar] [CrossRef]
  99. Liu, H.; Zheng, F.; Sun, X.; Hong, X.; Dong, S.; Wang, B.; Tang, X.; Wang, Y. Identification of the pathogens associated with skin ulceration and peristome tumescence in cultured sea cucumbers Apostichopus japonicus (Selenka). J. Invertebr. Pathol. 2010, 105, 236–242. [Google Scholar] [CrossRef]
  100. Pujalte, M.J.; Sitjà-Bobadilla, A.; Macián, M.C.; Álvarez-Pellitero, P.; Garay, E. Occurrence and virulence of Pseudoalteromonas spp. in cultured gilthead sea bream (Sparus aurata L.) and european sea bass (Dicentrarchus labrax L.). Molecular and phenotypic characterisation of P. undina strain U58. Aquaculture 2007, 271, 47–53. [Google Scholar] [CrossRef]
  101. Thomas, T.; Evans, F.F.; Schleheck, D.; Mai-Prochnow, A.; Burke, C.; Penesyan, A.; Dalisay, D.S.; Stelzer-Braid, S.; Saunders, N.; Johnson, J.; et al. Analysis of the Pseudoalteromonas tunicata genome reveals properties of a surface-associated life style in the marine environment. PLoS ONE 2008, 3, e3252. [Google Scholar] [CrossRef]
  102. Sawabe, T.; Makino, H.; Tatsumi, M.; Nakano, K.; Tajima, K.; Iqbal, M.M.; Yumoto, I.; Ezura, Y.; Christen, R. Pseudoalteromonas bacteriolytica sp. nov., a marine bacterium that is the causative agent of red spot disease of Laminaria japonica. Int. J. Syst. Bacteriol. 1998, 48, 769–774. [Google Scholar] [CrossRef] [PubMed]
  103. Liu, X.; Chen, Y.; Zhong, M.; Chen, W.; Lin, Q.; Du, H. Isolation and pathogenicity identification of bacterial pathogens in bleached disease and their physiological effects on the red macroalga Gracilaria lemaneiformis. Aquat. Bot. 2019, 153, 1–7. [Google Scholar] [CrossRef]
  104. Saulnier, D.; de Decker, S.; Haffner, P.; Cobret, L.; Robert, M.; Garcia, C. A large-scale epidemiological study to identify bacteria pathogenic to Pacific oyster Crassostrea gigas and correlation between virulence and metalloprotease-like activity. Microb. Ecol. 2010, 59, 787–798. [Google Scholar] [CrossRef]
  105. Wang, Y.; Feng, N.; Li, Q.; Ding, J.; Zhan, Y.; Chang, Y. Isolation and characterization of bacteria associated with a syndrome disease of sea urchin Strongylocentrotus intermedius in North China. Aquac. Res. 2013, 44, 691–700. [Google Scholar] [CrossRef]
  106. Li, H.; Qiao, G.; Li, Q.; Zhou, W.; Won, K.M.; Xu, D.H.; Park, S.I. Biological characteristics and pathogenicity of a highly pathogenic Shewanella marisflavi infecting sea cucumber, Apostichopus japonicus. J. Fish Dis. 2010, 33, 865–877. [Google Scholar] [CrossRef]
  107. Prabha, H.; Nataraj, K.; Rajesh, B.; Pratap Chandran, R. Isolation and molecular characterization of microbial population from the fish “Tilapia” collected from Vembanad Lake, Kerala, India. J. Mater. Environ. Sci. 2021, 12, 573–583. [Google Scholar]
  108. Hernández-Pérez, A.; Söderhäll, K.; Sirikharin, R.; Jiravanichpaisal, P.; Söderhäll, I. Vibrio Areninigrae as a Pathogenic Bacterium in a Crustacean. J. Invertebr. Pathol. 2021, 178, 107517. [Google Scholar] [CrossRef]
  109. Künili, İ.E.; Ertürk Gürkan, S.; Aksu, A.; Turgay, E.; Çakir, F.; Gürkan, M.; Altinağaç, U. Mass Mortality in Endangered Fan Mussels Pinna Nobilis (Linnaeus 1758) Caused by Co-Infection of Haplosporidium Pinnae and Multiple Vibrio Infection in Çanakkale Strait, Turkey. Biomarkers 2021, 26, 450–461. [Google Scholar] [CrossRef] [PubMed]
  110. Moreira, A.P.B.; Duytschaever, G.; Chimetto Tonon, L.A.; Fróes, A.M.; de Oliveira, L.S.; Amado-Filho, G.M.; Francini-Filho, R.B.; De Vos, P.; Swings, J.; Thompson, C.C.; et al. Photobacterium Sanctipauli Sp. Nov. Isolated from Bleached Madracis Decactis (Scleractinia) in the St Peter & St Paul Archipelago, Mid-Atlantic Ridge, Brazil. PeerJ 2014, 2014, e427. [Google Scholar] [CrossRef]
  111. Jacobs Slifka, K.M.; Newton, A.E.; Mahon, B.E. Vibrio Alginolyticus Infections in the USA, 1988-2012. Epidemiol. Infect. 2017, 145, 1491–1499. [Google Scholar] [CrossRef] [PubMed]
  112. Hasan, N.A.; Grim, C.J.; Lipp, E.K.; Rivera, I.N.G.; Chun, J.; Haley, B.J.; Taviani, E.; Choi, S.Y.; Hoq, M.; Munk, A.C.; et al. Deep-Sea Hydrothermal Vent Bacteria Related to Human Pathogenic Vibrio Species. Proc. Natl. Acad. Sci. USA 2015, 112, E2813–E2819. [Google Scholar] [CrossRef]
  113. Li, G.; Xie, G.; Wang, H.; Wan, X.; Li, X.; Shi, C.; Wang, Z.; Gong, M.; Li, T.; Wang, P.; et al. Characterization of a Novel Shrimp Pathogen, Vibrio Brasiliensis, Isolated from Pacific White Shrimp, Penaeus Vannamei. J. Fish Dis. 2021, 44, 1543–1552. [Google Scholar] [CrossRef]
  114. Wang, L.; Chen, Y.; Huang, H.; Huang, Z.; Chen, H.; Shao, Z. Isolation and Identification of Vibrio Campbellii as a Bacterial Pathogen for Luminous Vibriosis of Litopenaeus Vannamei. Aquac. Res. 2015, 46, 395–404. [Google Scholar] [CrossRef]
  115. Kimes, N.E.; Grim, C.J.; Johnson, W.R.; Hasan, N.A.; Tall, B.D.; Kothary, M.H.; Kiss, H.; Munk, A.C.; Tapia, R.; Green, L.; et al. Temperature Regulation of Virulence Factors in the Pathogen Vibrio Coralliilyticus. ISME J. 2012, 6, 835–846. [Google Scholar] [CrossRef]
  116. Prado, S.; Romalde, J.L.; Montes, J.; Barja, J.L. Pathogenic Bacteria Isolated from Disease Outbreaks in Shellfish Hatcheries. First Description of Vibrio Neptunius as an Oyster Pathogen. Dis. Aquat. Organ. 2005, 67, 209–215. [Google Scholar] [CrossRef]
  117. Goulden, E.F.; Hall, M.R.; Bourne, D.G.; Pereg, L.L.; Høj, L. Pathogenicity and Infection Cycle of Vibrio Owensii in Larviculture of the Ornate Spiny Lobster (Panulirus Ornatus). Appl. Environ. Microbiol. 2012, 78, 2841–2849. [Google Scholar] [CrossRef]
  118. Drake, S.L.; Depaola, A.; Jaykus, L.A. An Overview of Vibrio Vulnificus and Vibrio Parahaemolyticus. Compr. Rev. Food Sci. Food Saf. 2007, 6, 120–144. [Google Scholar] [CrossRef]
  119. Gai, C.; Liu, J.; Zheng, X.; Xu, L.; Ye, H. Identification of Vibrio Ponticus as a Bacterial Pathogen of Coral Trout Plectropomus Leopardus. Front. Cell. Infect. Microbiol. 2022, 12, 1925. [Google Scholar] [CrossRef]
  120. Zhang, X.J.; Yan, B.L.; Bai, X.S.; Bi, K.R.; Gao, H.; Qin, G.M. Isolation and Characterization of Vibrio Parahaemolyticus and Vibrio Rotiferianus Associated with Mass Mortality of Chinese Shrimp (Fenneropenaeus Chinensis). J. Shellfish Res. 2014, 33, 61–68. [Google Scholar] [CrossRef]
  121. Zhang, L.; Zhong, M.; Li, X.; Lu, W.; Li, J. River Bacterial Community Structure and Co-Occurrence Patterns under the Influence of Different Domestic Sewage Types. J. Environ. Manag. 2020, 266, 110590. [Google Scholar] [CrossRef] [PubMed]
  122. Flores-Miranda, M.; Luna-González, A.; Campa Córdova, Á.I.; Fierro-Coronado, J.A.; Partida-Arangure, B.O.; Pintado, J.; González-Ocampo, H.A. Isolation and characterization of infectious Vibrio sinaloensis strains from the Pacific shrimp Litopenaeus vannamei (Decapoda: Penaeidae). Rev. Biol. Trop. 2012, 60, 567–576. [Google Scholar] [CrossRef]
  123. Hada, H.S.; West, P.A.; Lee, J.V. Vibrio tubiashii sp. nov., a pathogen of bivalve mollusks. Int. J. Syst. Bacteriol. 1984, 34, 1–4. [Google Scholar] [CrossRef]
  124. Prayitno, S.B.; Latchford, J.W. Experimental infections of crustaceans with luminous bacteria related to Photobacterium and Vibrio. Effect of salinity and pH on infectiosity. Aquaculture 1995, 132, 105–112. [Google Scholar] [CrossRef]
  125. Yardimci, R.; Turgay, E.; Steinum, S.K. Diagnosis of Photobacterium sanguinicancri in smout-hound shark (Mustelus mustelus, Linnaeus 1758). Acta Aquat. Turc. 2019, 16, 338–343. [Google Scholar] [CrossRef]
  126. Fichi, G.; Cardeti, G.; Perrucci, S.; Vanni, A.; Cersini, A.; Lenzi, C.; De Wolf, T.; Fronte, B.; Guarducci, M.; Susini, F. Skin lesion-associated pathogens from Octopus vulgaris: First detection of Photobacterium swingsii, Lactococcus garvieae and betanodavirus. Dis. Aquat. Organ. 2015, 115, 147–156. [Google Scholar] [CrossRef]
  127. Ramamurthy, T.; Chowdhury, G.; Pazhani, G.P.; Shinoda, S. Vibrio fluvialis: An emerging human pathogen. Front. Microbiol. 2014, 5, 91. [Google Scholar] [CrossRef]
  128. Lux, T.M.; Lee, R.; Love, J. Genome-wide phylogenetic analysis of the pathogenic potential of Vibrio furnissii. Front. Microbiol. 2014, 5, 435. [Google Scholar] [CrossRef]
  129. Rivas, A.J.; Lemos, M.L.; Osorio, C.R. Photobacterium damselae subsp. damselae, a bacterium pathogenic for marine animals and humans. Front. Microbiol. 2013, 4, 283. [Google Scholar] [CrossRef]
  130. López, J.R.; Lorenzo, L.; Alcantara, R.; Navas, J.I. Characterization of Aliivibrio fischeri strains associated with disease outbreak in brill Scophthalmus rhombus. Dis. Aquat. Organ. 2017, 124, 215–222. [Google Scholar] [CrossRef]
  131. Hjerde, E.; Lorentzen, M.; Holden, M.T.G.; Seeger, K.; Paulsen, S.; Bason, N.; Churcher, C.; Harris, D.; Norbertczak, H.; Quail, M.A.; et al. The genome sequence of the fish pathogen Aliivibrio salmonicida strain LFI1238 shows extensive evidence of gene decay. BMC Genom. 2008, 9, 616. [Google Scholar] [CrossRef]
  132. Hjerde, E.; Karlsen, C.; Sørum, H.; Parkhill, J.; Willassen, N.P.; Thomson, N.R. Co-cultivation and transcriptome sequencing of two co-existing fish pathogens Moritella viscosa and Aliivibrio wodanis. BMC Genom. 2015, 16, 447. [Google Scholar] [CrossRef]
  133. Labreuche, Y.; Soudant, P.; Gonçalves, M.; Lambert, C.; Nicolas, J.L. Effects of extracellular products from the pathogenic Vibrio aestuarianus strain 01/32 on lethality and cellular immune responses of the oyster Crassostrea gigas. Dev. Comp. Immunol. 2006, 30, 367–379. [Google Scholar] [CrossRef] [PubMed]
  134. Beaz-Hidalgo, R.; Diéguez, A.L.; Cleenwerck, I.; Balboa, S.; Doce, A.; de Vos, P.; Romalde, J.L. Vibrio celticus sp. nov., a new Vibrio species belonging to the Splendidus clade with pathogenic potential for clams. Syst. Appl. Microbiol. 2010, 33, 311–315. [Google Scholar] [CrossRef] [PubMed]
  135. Urtubia, R.; Miranda, C.D.; Rodríguez, S.; Dubert, J.; Barja, J.L.; Rojas, R. First report, characterization and pathogenicity of Vibrio chagasii isolated from diseased reared larvae of Chilean scallop, Argopecten purpuratus (Lamarck, 1819). Pathogens 2023, 12, 183. [Google Scholar] [CrossRef]
  136. Bruto, M.; James, A.; Petton, B.; Labreuche, Y.; Chenivesse, S.; Alunno-Bruscia, M.; Polz, M.F.; Le Roux, F. Vibrio crassostreae, a benign oyster colonizer turned into a pathogen after plasmid acquisition. ISME J. 2017, 11, 1043–1052. [Google Scholar] [CrossRef] [PubMed]
  137. Li, Y.F.; Chen, Y.W.; Xu, J.K.; Ding, W.Y.; Shao, A.Q.; Zhu, Y.T.; Wang, C.; Liang, X.; Yang, J.L. Temperature elevation and Vibrio cyclitrophicus infection reduce the diversity of haemolymph microbiome of the mussel Mytilus coruscus. Sci. Rep. 2019, 9, 16391. [Google Scholar] [CrossRef] [PubMed]
  138. Huang, B.; Zhang, X.; Wang, C.; Bai, C.; Li, C.; Li, C.; Xin, L. Isolation and characterization of Vibrio kanaloae as a major pathogen associated with mass mortalities of ark clam, Scapharca broughtonii, in cold season. Microorganisms 2021, 9, 2161. [Google Scholar] [CrossRef] [PubMed]
  139. Duperthuy, M.; Schmitt, P.; Garzón, E.; Caro, A.; Rosa, R.D.; Le Roux, F.; Lautrédou-Audouy, N.; Got, P.; Romestand, B.; De Lorgeril, J.; et al. Use of OmpU porins for attachment and invasion of Crassostrea gigas immune cells by the oyster pathogen Vibrio splendidus. Proc. Natl. Acad. Sci. USA 2011, 108, 2993–2998. [Google Scholar] [CrossRef]
  140. Lasa, A.; Avendaño-Herrera, R.; Estrada, J.M.; Romalde, J.L. Isolation and identification of Vibrio toranzoniae associated with diseased red conger eel (Genypterus chilensis) farmed in Chile. Vet. Microbiol. 2015, 179, 327–331. [Google Scholar] [CrossRef]
  141. Allam, B.; Paillard, C.; Auffret, M. Alterations in hemolymph and extrapallial fluid parameters in the manila clam, Ruditapes philippinarum, challenged with the pathogen Vibrio tapetis. J. Invertebr. Pathol. 2000, 76, 63–69. [Google Scholar] [CrossRef] [PubMed]
  142. Fleming, T.J.; Schrankel, C.S.; Vyas, H.; Rosenblatt, H.D.; Hamdoun, A. CRISPR/Cas9 mutagenesis reveals a role for ABCB1 in gut immune responses to Vibrio diazotrophicus in sea urchin larvae. J. Exp. Biol. 2021, 224, jeb232272. [Google Scholar] [CrossRef]
  143. Ishimaru, K.; Akagawa-Matsushita, M.; Muroga, K. Vibrio penaeicida sp. nov., a pathogen of kuruma prawns (Penaeus japonicus). Int. J. Syst. Bacteriol. 1995, 45, 134–138. [Google Scholar] [CrossRef]
  144. Jangam, A.K.; Angel, R.J.; Jangam, A.K.; Nathamuni, S.; Katneni, V.K.; Avunje, S.; Angel, R.J.; Grover, M.; Shekhar, M.S. Microbial communities associated with stunted growth syndrome in Penaeus vannamei farming. Res. Sq. 2021, preprint. 1–17. [Google Scholar] [CrossRef]
  145. Rapsinski, G.J.; Makadia, J.; Bhanot, N.; Min, Z. Pseudomonas mendocina native valve infective endocarditis: A case report. J. Med. Case Rep. 2016, 10, 275. [Google Scholar] [CrossRef] [PubMed]
  146. Gautam, L.; Kaur, R.; Kumar, S.; Bansal, A.; Gautam, V.; Singh, M.; Ray, P. Pseudomonas oleovorans sepsis in a child: The first reported case in India. Jpn. J. Infect. Dis. 2015, 68, 254–255. [Google Scholar] [CrossRef]
  147. Fernández, M.; Porcel, M.; de la Torre, J.; Molina-Henares, M.A.; Daddaoua, A.; Llamas, M.A.; Roca, A.; Carriel, V.; Garzón, I.; Ramos, J.L.; et al. Analysis of the pathogenic potential of nosocomial Pseudomonas putida strains. Front. Microbiol. 2015, 6, 871. [Google Scholar] [CrossRef]
  148. Alwazzeh, M.J.; Alkuwaiti, F.A.; Alqasim, M.; Alwarthan, S.; El-ghoneimy, Y. Infective endocarditis caused by Pseudomonas stutzeri: A case report and literature review. Am. J. Case Rep. 2020, 12, 105–109. [Google Scholar] [CrossRef]
  149. Beckers, B.; Op De Beeck, M.; Thijs, S.; Truyens, S.; Weyens, N.; Boerjan, W.; Vangronsveld, J. Performance of 16s RDNA primer pairs in the study of rhizosphere and endosphere bacterial microbiomes in metabarcoding studies. Front. Microbiol. 2016, 7, 650. [Google Scholar] [CrossRef] [PubMed]
  150. Hiruy, A.M.; Mohammed, J.; Haileselassie, M.M.; Acharya, K.; Butte, G.; Haile, A.T.; Walsh, C.; Werner, D. Spatiotemporal variation in urban wastewater pollution impacts on river microbiomes and associated hazards in the Akaki Catchment, Addis Ababa, Ethiopia. Sci. Total Environ. 2022, 826, 153912. [Google Scholar] [CrossRef]
  151. Caputo, M.; Zoch-Lesniak, B.; Karch, A.; Vital, M.; Meyer, F.; Klawonn, F.; Baillot, A.; Pieper, D.H.; Mikolajczyk, R.T. Bacterial community structure and effects of picornavirus infection on the anterior nares microbiome in early childhood. BMC Microbiol. 2019, 19, 1–10. [Google Scholar] [CrossRef] [PubMed]
  152. Clarke, K.R.; Gorley, R.N. PRIMER v7: User Manual/Tutorial; PRIMER_E Ltd.: Plymouth, UK, 2015. [Google Scholar]
  153. Grbin, D.; Geček, S.; Miljanović, A.; Pavić, D.; Hudina, S.; Žučko, J.; Rieder, J.; Pisano, S.R.R.; Adrian-Kalchhauser, I.; Bielen, A. Comparison of exoskeleton microbial communities of co-occuring native and invasive crayfish species. J. Invertebr. Pathol. 2023, 201, 107996. [Google Scholar] [CrossRef] [PubMed]
  154. West, R.M. Best practice in statistics: Use the Welch t-test when testing the difference between two groups. Ann. Clin. Biochem. Int. J. Lab. Med. 2021, 58, 267–269. [Google Scholar] [CrossRef]
  155. Morris, R.M.; Rappé, M.S.; Connon, S.A.; Vergin, K.L.; Siebold, W.A.; Carlson, C.A.; Giovannoni, S.J. SAR11 clade dominates ocean surface bacterioplankton communities. Nature 2002, 420, 806–810. [Google Scholar] [CrossRef]
  156. Giovannoni, S.J. SAR11 bacteria: The most abundant plankton in the oceans. Ann. Rev. Mar. Sci. 2017, 9, 231–255. [Google Scholar] [CrossRef]
  157. Oberbeckmann, S.; Loeder, M.G.J.; Gerdts, G.; Osborn, M.A. Spatial and seasonal variation in diversity and structure of microbial biofilms on marine plastics in northern European waters. FEMS Microbiol. Ecol. 2014, 90, 478–492. [Google Scholar] [CrossRef]
  158. Gignoux-Wolfsohn, S.A.; Vollmer, S.V. Identification of candidate coral pathogens on white band disease-infected staghorn coral. PLoS ONE 2015, 10, e0134416. [Google Scholar] [CrossRef] [PubMed]
  159. Roth, T.M.; Crews, A.; Nakano, A. Five years of surveillance for Tularemia Serovar B (Francisella tularensis holarctica) (Olsufjev) (Thiotrichales: Francisellaceae) including two human cases at an endemic site in San Mateo County, California. J. Med. Entomol. 2022, 59, 1787–1792. [Google Scholar] [CrossRef]
  160. Eppinger, M.; Baar, C.; Raddatz, G.; Huson, D.H.; Schuster, S.C. Comparative analysis of four Campylobacterales. Nat. Rev. Microbiol. 2004, 2, 872–885. [Google Scholar] [CrossRef] [PubMed]
  161. Bartlett, A.; Padfield, D.; Lear, L.; Bendall, R.; Vos, M. A comprehensive list of bacterial pathogens infecting humans. Microbiology 2022, 168, 001269. [Google Scholar] [CrossRef]
  162. Pedrotti, M.L.; de Figueiredo Lacerda, A.L.; Petit, S.; Ghiglione, J.F.; Gorsky, G. Vibrio spp. and other potential pathogenic bacteria associated to microfibers in the north-western Mediterranean Sea. PLoS ONE 2022, 17, e0275284. [Google Scholar] [CrossRef] [PubMed]
  163. Xu, Z.; Masuda, Y.; Wang, X.; Ushijima, N.; Shiratori, Y.; Senoo, K.; Itoh, H. Genome-based taxonomic rearrangement of the order Geobacterales including the description of Geomonas azotofigens sp. nov. and Geomonas diazotrophica sp. nov. Front. Microbiol. 2021, 12, 737531. [Google Scholar] [CrossRef] [PubMed]
  164. Zimmerman, A.M.; DePaola, A.; Bowers, J.C.; Krantz, J.A.; Nordstrom, J.L.; Johnson, C.N.; Grimes, D.J. Variability of total and pathogenic Vibrio parahaemolyticus densities in northern Gulf of Mexico water and oysters. Appl. Environ. Microbiol. 2007, 73, 7589–7596. [Google Scholar] [CrossRef] [PubMed]
  165. Johnson, C.N.; Bowers, J.C.; Griffitt, K.J.; Molina, V.; Clostio, R.W.; Pei, S.; Laws, E.; Paranjpye, R.N.; Strom, M.S.; Chen, A.; et al. Ecology of Vibrio parahaemolyticus and Vibrio vulnificus in the coastal and estuarine waters of Louisiana, Maryland, Mississippi, and Washington (United States). Appl. Environ. Microbiol. 2012, 78, 7249–7257. [Google Scholar] [CrossRef] [PubMed]
  166. Riisgård, H. Efficiency of particle retention and filtration rate in 6 species of northeast american bivalves. Mar. Ecol. Prog. Ser. 1988, 45, 217–223. [Google Scholar] [CrossRef]
  167. Kach, D.J.; Ward, J.E. The role of marine aggregates in the ingestion of picoplankton-size particles by suspension-feeding molluscs. Mar. Biol. 2008, 153, 797–805. [Google Scholar] [CrossRef]
  168. Colwell, R.R. Global climate and infectious disease: The Cholera Paradigm. Science 1996, 274, 2025–2031. [Google Scholar] [CrossRef]
  169. Vezzulli, L.; Pezzati, E.; Moreno, M.; Fabiano, M.; Pane, L.; Pruzzo, C.; The VibrioSea Consortium. Benthic ecology of Vibrio spp. and pathogenic Vibrio species in a coastal Mediterranean environment (La Spezia Gulf, Italy). Microb. Ecol. 2009, 58, 808–818. [Google Scholar] [CrossRef]
  170. Holmström, C.; Kjelleberg, S. Marine Pseudoalteromonas species are associated with higher organisms and produce biologically active extracellular agents. FEMS Microbiol. Ecol. 1999, 30, 285–293. [Google Scholar] [CrossRef] [PubMed]
  171. Iijima, S.; Washio, K.; Okahara, R.; Morikawa, M. Biofilm formation and proteolytic activities of Pseudoalteromonas bacteria that were isolated from fish farm sediments. Microb. Biotechnol. 2009, 2, 361–369. [Google Scholar] [CrossRef]
  172. Porter, E.T.; Franz, H.; Lacouture, R. Impact of eastern oyster Crassostrea virginica biodeposit resuspension on the seston, nutrient, phytoplankton, and zooplankton dynamics: A mesocosm experiment. Mar. Ecol. Prog. Ser. 2018, 586, 21–40. [Google Scholar] [CrossRef]
  173. Porter, E.T.; Robins, E.; Davis, S.; Lacouture, R.; Cornwell, J.C. Effects of resuspension of eastern oyster Crassostrea virginica biodeposits on phytoplankton community structure. Mar. Ecol. Prog. Ser. 2020, 640, 79–105. [Google Scholar] [CrossRef]
  174. Porter, E.T.; Blickenstaff, S.; Cornwell, J.C.; Jackson, M.; Tolbert, S.N. Effect of tidal resuspension with oyster biodeposits on nutrient and oxygen dynamics. Mar. Ecol. Prog. Ser. 2022, 686, 37–60. [Google Scholar] [CrossRef]
  175. Thompson, J.R.; Randa, M.A.; Marcelino, L.A.; Tomita-Mitchell, A.; Lim, E.; Polz, M.F. Diversity and dynamics of a north atlantic coastal Vibrio community. Appl. Environ. Microbiol. 2004, 70, 4103–4110. [Google Scholar] [CrossRef] [PubMed]
  176. Kan, J.; Crump, B.C.; Wang, K.; Chen, F. Bacterioplankton community in Chesapeake Bay: Predictable or random assemblages. Limnol. Oceanogr. 2006, 51, 2157–2169. [Google Scholar] [CrossRef]
  177. Siboni, N.; Balaraju, V.; Carney, R.; Labbate, M.; Seymour, J.R. Spatiotemporal dynamics of Vibrio spp. within the Sydney Harbour Estuary. Front. Microbiol. 2016, 7, 460. [Google Scholar] [CrossRef]
  178. Wang, H.; Zhang, C.; Chen, F.; Kan, J. Spatial and temporal variations of bacterioplankton in the Chesapeake Bay: A re-examination with high-throughput sequencing analysis. Limnol. Oceanogr. 2020, 65, 3032–3045. [Google Scholar] [CrossRef]
  179. DePaola, A.; Capers, G.M.; Alexander, D. Densities of Vibrio vulnificus in the intestines of fish from the U.S. Gulf Coast. Appl. Environ. Microbiol. 1994, 60, 984–988. [Google Scholar] [CrossRef]
  180. Harvell, C.D.; Mitchell, C.E.; Ward, J.R.; Altizer, S.; Dobson, A.P.; Ostfeld, R.S.; Samuel, M.D. Climate warming and disease risks for terrestrial and marine biota. Science 2002, 296, 2158–2162. [Google Scholar] [CrossRef] [PubMed]
  181. Pfeffer, C.S.; Hite, M.F.; Oliver, J.D. Ecology of Vibrio vulnificus in estuarine waters of eastern North Carolina. Appl. Environ. Microbiol. 2003, 69, 3526–3531. [Google Scholar] [CrossRef] [PubMed]
  182. Baker-Austin, C.; Trinanes, J.A.; Taylor, N.G.H.; Hartnell, R.; Siitonen, A.; Martinez-Urtaza, J. Emerging Vibrio risk at high latitudes in response to ocean warming. Nat. Clim. Chang. 2013, 3, 73–77. [Google Scholar] [CrossRef]
  183. Burge, C.A.; Mark Eakin, C.; Friedman, C.S.; Froelich, B.; Hershberger, P.K.; Hofmann, E.E.; Petes, L.E.; Prager, K.C.; Weil, E.; Willis, B.L.; et al. Climate change influences on marine infectious diseases: Implications for management and society. Ann. Rev. Mar. Sci. 2014, 6, 249–277. [Google Scholar] [CrossRef]
  184. Sterk, A.; Schets, F.M.; de Roda Husman, A.M.; de Nijs, T.; Schijven, J.F. Effect of climate change on the concentration and associated risks of Vibrio spp. in Dutch recreational waters. Risk Anal. 2015, 35, 1717–1729. [Google Scholar] [CrossRef] [PubMed]
  185. Robins, P.E.; Skov, M.W.; Lewis, M.J.; Giménez, L.; Davies, A.G.; Malham, S.K.; Neill, S.P.; McDonald, J.E.; Whitton, T.A.; Jackson, S.E.; et al. Impact of climate change on UK estuaries: A review of past trends and potential projections. Estuar. Coast. Shelf Sci. 2016, 169, 119–135. [Google Scholar] [CrossRef]
  186. Suzzi, A.L.; Stat, M.; Gaston, T.F.; Siboni, N.; Williams, N.L.R.; Seymour, J.R.; Huggett, M.J. Elevated estuary water temperature drives fish gut dysbiosis and increased loads of pathogenic Vibrionaceae. Environ. Res. 2023, 219, 115144. [Google Scholar] [CrossRef]
  187. Burioli, E.A.V.; Varello, K.; Trancart, S.; Bozzetta, E.; Gorla, A.; Prearo, M.; Houssin, M. First description of a mortality event in adult Pacific oysters in Italy associated with infection by a Tenacibaculum soleae Strain. J. Fish Dis. 2018, 41, 215–221. [Google Scholar] [CrossRef]
  188. Tseng, S.Y.; Liu, P.Y.; Lee, Y.H.; Wu, Z.Y.; Huang, C.C.; Cheng, C.C.; Tung, K.C. The pathogenicity of Shewanella algae and ability to tolerate a wide range of temperatures and salinities. Can. J. Infect. Dis. Med. Microbiol. 2018, 2018, 6976897. [Google Scholar] [CrossRef]
  189. Beach, V.; Clement, J.C.; Kastner, P.D. Draft genome sequence of psychrotolerant Shewanella sp. strain VB17, isolated from marine intertidal sediment near Virginia Beach, Virginia. Microbiol. Resour. Announc. 2020, 9, 10–1128. [Google Scholar] [CrossRef]
  190. Gardade, L.; Khandeparker, L. Spatio-temporal variations in pathogenic bacteria in the surface sediments of the Zuari Estuary, Goa, India. Curr. Sci. 2017, 113, 1729–1738. [Google Scholar] [CrossRef]
  191. Johnson, C.N.; Flowers, A.R.; Noriea, N.F.; Zimmerman, A.M.; Bowers, J.C.; DePaola, A.; Grimes, D.J. Relationships between environmental factors and pathogenic vibrios in the northern Gulf of Mexico. Appl. Environ. Microbiol. 2010, 76, 7076–7084. [Google Scholar] [CrossRef] [PubMed]
  192. Randa, M.A.; Polz, M.F.; Lim, E. Effects of temperature and salinity on Vibrio vulnificus population dynamics as assessed by quantitative PCR. Appl. Environ. Microbiol. 2004, 70, 5469–5476. [Google Scholar] [CrossRef] [PubMed]
  193. Powell, E. 2021 Florida Weather and Climate Summary. Available online: https://climatecenter.fsu.edu/images/docs/Fla_Annual_climate_summary_2021.pdf (accessed on 21 November 2023).
  194. Shiah, F.K.; Ducklow, H.W. Temperature and substrate regulation of bacterial abundance, production and specific growth rate in Chesapeake Bay, USA. Mar. Ecol. Prog. Ser. 1994, 103, 297–308. [Google Scholar] [CrossRef]
  195. Julie, D.; Solen, L.; Antoine, V.; Jaufrey, C.; Annick, D.; Dominique, H.H. Ecology of pathogenic and non-pathogenic Vibrio parahaemolyticus on the French Atlantic coast. Effects of temperature, salinity, turbidity and chlorophyll a. Environ. Microbiol. 2010, 12, 929–937. [Google Scholar] [CrossRef] [PubMed]
  196. King, G.M.; Judd, C.; Kuske, C.R.; Smith, C. Analysis of stomach and gut microbiomes of the eastern oyster (Crassostrea virginica) from coastal Louisiana, USA. PLoS ONE 2012, 7, e51475. [Google Scholar] [CrossRef]
  197. Pierce, M.L.; Evan, J. Gut microbiomes of the eastern oyster (Crassostrea virginica) and the blue mussel (Mytilus edulis): Temporal variation and the influence of marine aggregate-associated microbial communities. mSphere 2019, 4, e00730-19. [Google Scholar] [CrossRef]
  198. Pimentel, Z.T.; Dufault-Thompson, K.; Russo, K.T.; Scro, A.K.; Smolowitz, R.M.; Gomez-Chiarri, M.; Zhang, Y. Microbiome analysis reveals diversity and function of Mollicutes associated with the eastern oyster, Crassostrea virginica. mSphere 2021, 6, 10–128. [Google Scholar] [CrossRef]
  199. Macey, B.M.; Achilihu, I.O.; Burnett, K.G.; Burnett, L.E. Effects of hypercapnic hypoxia on inactivation and elimination of Vibrio campbellii in the eastern oyster, Crassostrea virginica. Appl. Environ. Microbiol. 2008, 74, 6077–6084. [Google Scholar] [CrossRef]
  200. Campbell, V.M.; Chouljenko, A.; Hall, S.G. Depuration of live oysters to reduce Vibrio parahaemolyticus and Vibrio vulnificus: A review of ecology and processing parameters. Compr. Rev. Food Sci. Food Saf. 2022, 21, 3480–3506. [Google Scholar] [CrossRef]
  201. Tokarskyy, O.; Marshall, D.L.; Dillon, J.; Andrews, L.S. Long-term depuration of Crassostrea virginica oysters at different salinities and temperatures changes Vibrio vulnificus counts and microbiological profile. J. Food Prot. 2019, 82, 22–29. [Google Scholar] [CrossRef] [PubMed]
  202. Murphy, A.E.; Kolkmeyer, R.; Song, B.; Anderson, I.C.; Bowen, J. Bioreactivity and microbiome of biodeposits from filter-feeding bivalves. Microb. Ecol. 2019, 77, 343–357. [Google Scholar] [CrossRef] [PubMed]
  203. Rodney, W.S.; Paynter, K.T. Comparisons of macrofaunal assemblages on restored and non-restored oyster reefs in mesohaline regions of Chesapeake Bay in Maryland. J. Exp. Mar. Bio. Ecol. 2006, 335, 39–51. [Google Scholar] [CrossRef]
  204. Searles, A.R.; Gipson, E.E.; Walters, L.J.; Cook, G.S. Oyster reef restoration facilitates the recovery of macroinvertebrate abundance, diversity, and composition in estuarine communities. Sci. Rep. 2022, 12, 8163. [Google Scholar] [CrossRef]
  205. Rezek, R.J.; Lebreton, B.; Roark, E.B.; Palmer, T.A.; Pollack, J.B. How does a restored oyster reef develop? An assessment based on stable isotopes and community metrics. Mar. Biol. 2017, 164, 54. [Google Scholar] [CrossRef]
  206. Bugnot, A.B.; Dafforn, K.A.; Coleman, R.A.; Ramsdale, M.; Gibbeson, J.T.; Erickson, K.; Vila-Concejo, A.; Figueira, W.F.; Gribben, P.E. Linking habitat interactions and biodiversity within seascapes. Ecosphere 2022, 13, e4021. [Google Scholar] [CrossRef]
  207. Copertino, J.L.; Harris, K.; Chute, L.; Walters, L.J. Impact of oyster (Crassostrea virginica) reef restoration on benthic invertebrates and coastal birds in a subtropical estuary. Sustainability 2022, 14, 2371. [Google Scholar] [CrossRef]
  208. Grabowski, J.H.; Hughes, A.R.; Kimbro, D.L.; Dolan, M.A. How habitat setting influences restored oyster reef communities. Ecology 2005, 86, 1926–1935. [Google Scholar] [CrossRef]
  209. Halpern, M.; Izhaki, I. Fish as hosts of Vibrio cholerae. Front. Microbiol. 2017, 8, 282. [Google Scholar] [CrossRef]
  210. Sweat, L.; Busch, S.J.; Craig, C.; Dark, E.; Sailor-Tynes, T.; Wayles, J.; Sacks, P.; Walters, L.J. Temperature and salinity data for both seasons. FigShare, National Museum of Natural History. Dataset. 2023. [Google Scholar] [CrossRef]
  211. Sweat, L.; Busch, S.J.; Craig, C.; Dark, E.; Sailor-Tynes, T.; Wayles, J.; Sacks, P.; Walters, L.J. All ESVs with consensus IDs, sequences (16S, V4 region), and relative proportions per sample. FigShare, National Museum of Natural History. Dataset. 2023. [Google Scholar] [CrossRef]
  212. Sweat, L.; Busch, S.J.; Craig, C.; Dark, E.; Sailor-Tynes, T.; Wayles, J.; Sacks, P.; Walters, L.J. PPM ESVs with consensus IDs, sequences (16S, V4 region), and relative proportions per sample. FigShare, National Museum of Natural History. Dataset. 2023. [Google Scholar] [CrossRef]
  213. Sweat, L.; Busch, S.J.; Craig, C.; Dark, E.; Sailor-Tynes, T.; Wayles, J.; Sacks, P.; Walters, L.J. Sample metadata. FigShare, National Museum of Natural History. Dataset. 2023. [Google Scholar] [CrossRef]
  214. Sweat, L.; Busch, S.J.; Craig, C.; Dark, E.; Sailor-Tynes, T.; Wayles, J.; Sacks, P.; Walters, L.J. Map of collection sites in the Indian River Lagoon. FigShare, National Museum of Natural History. Figure. 2023. [Google Scholar] [CrossRef]
  215. Sweat, L.; Busch, S.J.; Craig, C.; Dark, E.; Sailor-Tynes, T.; Wayles, J.; Sacks, P.; Walters, L.J. Assigned taxonomy (100% matches only, 16S, V4 region) for all PPM ESVs. FigShare, National Museum of Natural History. Dataset. 2023. [Google Scholar] [CrossRef]
Figure 1. Locations and letter codes of oyster reef (OR, aqua circles), lagoon water (LW, yellow squares), and stormwater outfall (SO, blue triangles) sites throughout the Indian River Lagoon system. This color scheme continues throughout.
Figure 1. Locations and letter codes of oyster reef (OR, aqua circles), lagoon water (LW, yellow squares), and stormwater outfall (SO, blue triangles) sites throughout the Indian River Lagoon system. This color scheme continues throughout.
Environments 10 00205 g001
Figure 2. Average percent relative abundances per site in (a) January and (b) July for the 20 most abundant microbial orders from five treatments: lagoon water (LW), oyster reef water (OW), stormwater outfall (SO) water, oyster feces (OF), and oyster pseudofeces (OP).
Figure 2. Average percent relative abundances per site in (a) January and (b) July for the 20 most abundant microbial orders from five treatments: lagoon water (LW), oyster reef water (OW), stormwater outfall (SO) water, oyster feces (OF), and oyster pseudofeces (OP).
Environments 10 00205 g002
Figure 3. Average PPM (a) percent relative abundance and (b) richness in January (diagonal lines) and July (solid) from five treatments: lagoon water (LW), oyster reef water (OW), stormwater outfall (SO) water, oyster feces (OF), and oyster pseudofeces (OP). Letters denote significant differences among groups in each panel (two-way mixed ANOVA and post hoc tests on trimmed means).
Figure 3. Average PPM (a) percent relative abundance and (b) richness in January (diagonal lines) and July (solid) from five treatments: lagoon water (LW), oyster reef water (OW), stormwater outfall (SO) water, oyster feces (OF), and oyster pseudofeces (OP). Letters denote significant differences among groups in each panel (two-way mixed ANOVA and post hoc tests on trimmed means).
Environments 10 00205 g003
Figure 4. Non-metric multidimensional scaling (nMDS) plots of samples based on Bray–Curtis similarities of PPM communities, coded by (a) season and (b) treatment, from five treatments: lagoon water (LW), oyster reef water (OW), stormwater outfall (SO) water, oyster feces (OF), and oyster pseudofeces (OP).
Figure 4. Non-metric multidimensional scaling (nMDS) plots of samples based on Bray–Curtis similarities of PPM communities, coded by (a) season and (b) treatment, from five treatments: lagoon water (LW), oyster reef water (OW), stormwater outfall (SO) water, oyster feces (OF), and oyster pseudofeces (OP).
Environments 10 00205 g004
Figure 5. Heatmap of the average percent relative abundance of the 52 PPM ESVs detected across sites, treatments, and sampling seasons. ESV number is denoted on the left. Identifications are listed at the family level. The number of samples in each group is indicated in the bottom row.
Figure 5. Heatmap of the average percent relative abundance of the 52 PPM ESVs detected across sites, treatments, and sampling seasons. ESV number is denoted on the left. Identifications are listed at the family level. The number of samples in each group is indicated in the bottom row.
Environments 10 00205 g005
Table 1. Details of the collection sites (listed north to south by type): oyster reef (OR), lagoon water (LW), and stormwater outfall (SO).
Table 1. Details of the collection sites (listed north to south by type): oyster reef (OR), lagoon water (LW), and stormwater outfall (SO).
SiteNameCity/TownTypeLat.Long.Temp. (°C)Salinity (ppt)
Jan.Jul.Jan.Jul.
MLAMosquito Lagoon Reef AEdgewaterOR28.9697−80.882014283732
MLBMosquito Lagoon Reef BEdgewaterOR28.9460−80.866013293729
MLCMosquito Lagoon Reef CEdgewaterOR28.9374−80.861513283430
SEBSaint Sebastian RiverSebastianOR27.8553−80.492219322520
VERVero North Relief CanalVero BeachOR27.6967−80.39471931532
WILWildcat CoveFort PierceOR27.4933−80.306117303035
DRIDriftwood MotelJensen BeachOR27.2551−80.229518303030
INDIndian Riverside ParkJensen BeachOR27.2285−80.212718293131
RIVRiver Cove ParkStuartOR27.2112−80.184317283131
HOCHaulover CanalMimsLW28.7365−80.754721291419
MMPMenard-May ParkEdgewaterLW28.9896−80.901220293025
CITCity Point Community ChurchCocoaLW28.4211−80.752515311516
MELMelbourne CausewayMelbourneLW28.0856−80.586216301928
BEABear Point SanctuaryFort PierceLW27.4294−80.281315303335
DJWD.J. Wilcox PreserveFort PierceLW27.5282−80.348115293027
SCWSouth CausewayNew Smyrna BeachSO29.0284−80.903921302821
SVPSpace View ParkTitusvilleSO28.6126−80.8056242800
KIWClaude Edge Front Street ParkMelbourneSO28.0798−80.599714291726
POWPOW/MIA ParkMelbourneSO28.2082−80.66281629720
MOBMo Bay GrillSebastianSO27.8189−80.46902330017
SAVSavannah RoadFort PierceSO27.4194−80.31241728014
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Sweat, L.H.; Busch, S.J.; Craig, C.A.; Dark, E.; Sailor-Tynes, T.; Wayles, J.; Sacks, P.E.; Walters, L.J. Oyster Reefs Are Reservoirs for Potential Pathogens in a Highly Disturbed Subtropical Estuary. Environments 2023, 10, 205. https://doi.org/10.3390/environments10120205

AMA Style

Sweat LH, Busch SJ, Craig CA, Dark E, Sailor-Tynes T, Wayles J, Sacks PE, Walters LJ. Oyster Reefs Are Reservoirs for Potential Pathogens in a Highly Disturbed Subtropical Estuary. Environments. 2023; 10(12):205. https://doi.org/10.3390/environments10120205

Chicago/Turabian Style

Sweat, L. Holly, Sidney J. Busch, Casey A. Craig, Emily Dark, Tess Sailor-Tynes, Jessy Wayles, Paul E. Sacks, and Linda J. Walters. 2023. "Oyster Reefs Are Reservoirs for Potential Pathogens in a Highly Disturbed Subtropical Estuary" Environments 10, no. 12: 205. https://doi.org/10.3390/environments10120205

APA Style

Sweat, L. H., Busch, S. J., Craig, C. A., Dark, E., Sailor-Tynes, T., Wayles, J., Sacks, P. E., & Walters, L. J. (2023). Oyster Reefs Are Reservoirs for Potential Pathogens in a Highly Disturbed Subtropical Estuary. Environments, 10(12), 205. https://doi.org/10.3390/environments10120205

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop