2003 Progress Report: Microbial Biofilms as Indicators of Estuarine Ecosystem Condition

EPA Grant Number: R829458C002
Subproject: this is subproject number 002 , established and managed by the Center Director under grant R829458
(EPA does not fund or establish subprojects; EPA awards and manages the overall grant for this center).

Center: EAGLES - Consortium for Estuarine Ecoindicator Research for the Gulf of Mexico
Center Director: Brouwer, Marius
Title: Microbial Biofilms as Indicators of Estuarine Ecosystem Condition
Investigators: Lepo, Joe , Proctor, Lita , Snyder, Richard
Institution: University of Southern Mississippi , U.S. Geological Survey , University of West Florida
Current Institution: University of West Florida , University of Southern Mississippi
EPA Project Officer: Hiscock, Michael
Project Period: December 1, 2001 through November 30, 2005 (Extended to May 20, 2007)
Project Period Covered by this Report: December 1, 2002 through November 30, 2003
RFA: Environmental Indicators in the Estuarine Environment Research Program (2000) RFA Text |  Recipients Lists
Research Category: Water , Ecosystems , Ecological Indicators/Assessment/Restoration

Objective:

The overall objective of this research project is to validate microbial biofilms, their chemical composition, community structure, and biogeochemical activity as indices of ecosystem integrity, resiliency, and function. Microbial biofilms (periphyton, aufwuchs) are composed of bacteria, microalgae, and protists in a polymer matrix found on the surfaces of all submerged objects. These communities develop as a result of autotrophic and heterotrophic microbial colonization and growth, reflecting their immediate environment. The U.S. Environmental Protection Agency (EPA) and state agencies have used periphyton assays as indicators of water quality. This project takes a more indepth look at these communities to utilize the information contained beyond simply the algal component. A suite of biofilm analyses will be correlated to ambient water quality analyses, remote sensing data, and novel indicators to be developed by the other participants of the Consortium for Estuarine Ecoindicators Research for the Gulf of Mexico (CEER-GOM).

Progress Summary:

Field deployments and microcosm studies were conducted in the 2003 summer season. Analysis of 2002 samples and consolidation of results into manuscripts continued. The biofilms group spent a great deal of time and effort during the 2003 field season coordinating and supporting the CEER-GOM work in the Pensacola Bay system. The major effort was conducted in East Bay with the coordinated sampling at six stations with the CEER-GOM group, supported by near continuous, weekly water quality data as well as sonde deployments and retrievals. These water quality data, along with the nutrient samples that have been analyzed, have been or will be distributed for use by the entire consortium. The biofilm samples (see Table 1) were targeted for our most intensive analysis, molecular analysis of community structure, along with routine measures of biomass. Other samples (see Table 2) were targeted for biomass analysis only to determine spatial patterns in conjunction with phytoplankton analysis of water column samples by EPA Gulf Ecology Division (GED) and remote sensing of chlorophyll by Dr. Luoheng Han of CEER-GOM. These samples (see Tables 1 and 2) are "in the freezer" and are beginning to be processed as quickly as possible.

Table 1. Summary of Samples Obtained for Molecular Analysis of Community Structure

Experiment
Sampling Date
Area Notes
8
7/24/03
East Bay Stations 6 stations, surface and benthic
9
8/20/03
Santa Rosa Sound 2 stations, surface and benthic
10
8/28/03
East Bay Stations 6 stations, surface and benthic
11
8/29/03
Santa Rosa Sound 2 stations, surface and benthic
12
9/8, 9/10, 9/12, 9/15/03
Santa Rosa Sound 2 stations, surface and benthic 3-, 5-, 7-, and 10-day incubations
13
10/15/03
East Bay Stations 6 stations, surface and benthic
14
11/5/03
East Bay Stations 6 stations, surface and benthic

Table 2. Samples Obtained for Spatial Analysis of Biofilm Response

Sampling Date
Area Notes
6/6/03
East and Escambia 11 EPA stations, surface and benthic
6/16/03
East Bay Grid 40 stations, surface and benthic
7/3/03
Escambia Grid 39 stations, surface and benthic
7/18/03
East and Escambia 11 EPA station, surface and benthic
7/28/03
Han's Flightlines 15 stations, surface
8/18/03
East and Escambia 11 EPA station, surface and benthic
10/6/03
Outfall grid 20 stations, surface and benthic

Significant Results

Microbial Biofilm Indicators Microcosm Experiments. University of Western Florida biofilms' personnel ran microcosm experiments at the EPA GED laboratory during the summer of 2003. Successfully completed experimental runs included balanced N and P nutrient loading, excess N (as NO3¯ or NH4+), excess P, and organic loading using phytoplankton biomass and complex organic mixtures. Stable isotope data collected by Peter Chapman of GED on balanced nutrient loading suggested that the biofilms picked up NO3¯ from the continuous-loading treatment but did not assimilate NO3¯ delivered as two pulses during incubation. Molecular community structure and other analyses are underway.

Habitat Specificity. We characterized microbial biofilm communities developed over two closely located but distinct benthic habitats in the Pensacola Bay estuary using cultivation-independent molecular techniques. The biofilm community structure from the oyster reef setting had greater evenness and species richness compared to the one from the muddy-sand bottom. The vast majority of bacteria in the oyster reef biofilm was related to gamma- and delta- Proteobacteria, the Cytophaga-Flexibacter-Bacteroides cluster, the phyla Planctomyces and Holophaga-Acidobacterium. The same groups also were present in biofilms harvested at the muddy-sand bottom, with the difference that nearly one-half of the community consisted of Planctomyces. Total species richness was estimated to be 417 for the oyster reef and 60 for the muddy-sand bottom with 10.5 percent of the total unique species identified being shared between habitats. The results suggest dramatic differences in habitat-specific microbial diversity that have implications for overall microbial diversity within estuaries.

Bacterial Biofilm Communities in Estuarine Seagrass and Sandflat Habitats. We compared microbial biofilm communities from a seagrass bed and a sandflat habitat in Pensacola Bay, FL. Biofilms were grown for 6 and 10 days on acrylic plates at the surface and 10-15 cm above the sediment surface. Genomic DNA served as a template to amplify 16S rRNA genes and functional genes characteristic for sulfate reducing (dsr) and nitrogen cycling guilds (nifH, nirS, nirK, amoA) of prokaryotes. Sequencing of clone libraries representing functional guilds allowed assignment of individual terminal fragments to taxonomic units and revealed phylogenetic interrelationships. Given the different ecological characteristics of a seagrass and a sandflat environment, the community fingerprints (both 16S rDNA and functional genes) were surprisingly similar for the two habitats indicating a low degree of habitat-specificity for biofilms at these particular locations at that time point. This is in sharp contrast to differences in biofilm communities observed previously between other locations in the Bay. Principal component analysis reflected this finding, although it suggested a significant difference between 16S rDNA fingerprints of 6- and 10-day old biofilms, independent of the habitat type. Nitrogen-cycling metabolic guilds (denitrifiers, ammonia oxidizers, and N fixers) will be addressed by Lita Proctor.

Impact of Sewage Outfall on Biofilm Development and Community Structure. We compared the microbial biofilm communities at a sewage-outfall-impacted site in the Pensacola Bay estuary to biofilms generated in a nearby, more pristine, reference site with similar bathymetric and hydrologic features. Biofilms grown on glass slides over a 7-day period using benthic and floating sampling racks developed under higher nutrient (P, N) and organic loading than those from the pristine site. Terminal Restriction Length Polymorphism (TRFLP) fingerprints differed between benthic and surface biofilm communities from the same site. TRFLP profiles from both sites shared a consistent frame of peaks, with prominent signature peaks (both 16S and dsr) that differed between them. For the benthic biofilms, the effect of different nutrient levels was occluded by a strong effect of low dissolved oxygen (DO).

Biofilm Response to Hypoxic Conditions in the Field. TRFLP analysis of CfoI-digested 16S rDNA produces a 91-bp TRF for the majority of sulfate reducing bacteria (SRB), an observation supported by our sequence data and by the RDP II database. 16S rDNA clones from our comparison of oyster reef to sand-bottom showed a TRF of 91 bp after CfoI restriction that belonged nearly exclusively to the delta-Proteobacteria, which includes SRBs. Plotting the relative area of this peak (as a percentage of the total peak area of the entire TRFLP fingerprint), we observed that benthic biofilms harvested in July and August 2003, at the EPA sampling stations in Pensacola and East Bay showed considerable differences (see Figure 1).


Figure 1. Relative Peak Area of 91-bp Signal in 16S T-RFLP

In the July experiment, the different sites exhibited substantial differences with respect to the relative peak area of this 91-bp signal in benthic biofilms. Whereas it contributes approximately 5 percent to the total peak area for the biofilms grown in the Marsh habitat (creek and pond) and approximately 10 and 13 percent for P15 and P14, respectively, the signal is absent for sites P12, P13, and PB5. In contrast to July, all sites show the signal in August, though with different relative peak areas. This observation gains importance in comparison to the DO for these sites over the two time periods (shown below). Interestingly, the presence of the 91-bp TRF coincides with low DO. Biofilms exposed to more aerobic conditions in July did not show the signal (P13, P14, PB5). The fact that DO was in general lower in the August sampling compared to July would explain the increased 91-bp TRF for these three sites in August.

Because the 91-bp TRF may be contributed by other bacteria, it cannot serve as a sole indicator for low DO; thus, we supported the data by specifically looking at the SRP guild. Without exception, biofilms exposed to hypoxic conditions show substantially more diverse dsr fingerprints compared to biofilms grown under aerobic conditions. Whereas aerobic conditions result in one dominant signal, hypoxia leads to complex fingerprints with a higher number of signals. This relationship was apparent with all three restriction enzymes used (see Figure 2).

Figure 2. T-RFLP Signatures

Interactions and Collaborations

We have extensive collaborations with the EPA GED, which included: (1) collocating samplers with water quality monitoring stations to compare biofilm response to phytoplankton response and nutrients in Escambia and East Bays; (2) conducting stable isotope analysis on biofilms; and (3) coauthoring a review paper with Mike Lewis on biofilms as indicators. Collaborations with other EaGLe programs include: (1) Pacific Estuarine Ecosystem Indicator Research Consortium—carbohydrate analysis of biofilms and use of biofilms to map bioavailability of metals on marsh surfaces; and (2) Atlantic Coast Environmental Indicators Consortium—biofilm samplers in the Neuse River for comparison to phytoplankton response and nutrients as well as biofilm samplers with ACE seagrass work to compare light attenuation effects on seagrasses and biofilm periphyton. Within CEER-GOM we have: (1) provided PCB and dioxin-furan analysis on croakers sampled by Peter Thomas in the East Bay (CDC supported); (2) assisted in arranging trawler charter for fish reproduction group; (3) located biofilm samplers and provided water quality analysis along flight lines covered by Luoheng Han's remote sensing work; (4) collocated biofilm samplers with hypoxia work and benthic invertebrate sampling; (5) provided sonde continuous water quality data for the CEER-GOM group in East Bay; (6) provided boat time and sampling support for fish reproduction, crustacean hypoxia, and macrobenthic indicator groups; (7) provided biofilm pixel data for fractal analysis by Peter Noble; and (8) secured software for multivariate analysis of TRFLP data sets with assistance from Peter Noble. Collocation and integration of biofilm samplers was planned with the Florida Department of Environmental Protection for monitoring of the water quality around the Crystal- and Suwannee-River deltas (grassbeds and nearshore).

Future Activities:

We will continue to correlate a suite of biofilm analyses to ambient water quality analyses, remote sensing data, and novel indicators to be developed by the other participants of the CEER-GOM. In addition, nitrogen-cycling metabolic guilds (denitrifiers, ammonia oxidizers, and N fixers) will be addressed by Lita Proctor.


Journal Articles on this Report : 1 Displayed | Download in RIS Format

Other subproject views: All 27 publications 4 publications in selected types All 3 journal articles
Other center views: All 171 publications 54 publications in selected types All 48 journal articles
Type Citation Sub Project Document Sources
Journal Article Nocker A, Lepo JE, Snyder RA. Influence of an oyster reef on development of the microbial heterotrophic community of an estuarine biofilm. Applied and Environmental Microbiology 2004;70(11):6834-6845. R829458 (2005)
R829458C002 (2003)
R829458C002 (2004)
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  • Supplemental Keywords:

    population, community, ecosystem, watersheds, estuary, estuaries, Gulf of Mexico, nutrients, hypoxia, innovative technology, biomarkers, water quality, remote sensing, geographic information system, GIS, integrated assessment, risk assessment, fisheries, conservation, restoration, monitoring/modeling, Apalachicola Bay, Consortium for Estuarine Ecoindicator Research for the Gulf of Mexico, CEER-GOM, Environmental Monitoring and Assessment Program, Galveston Bay, Mobile Bay, benthic indicators, ecoindicator, ecological exposure, ecosystem monitoring, environmental indicators, environmental stress, estuarine ecoindicator, estuarine integrity., RFA, Scientific Discipline, ECOSYSTEMS, Geographic Area, Water, Ecosystem Protection/Environmental Exposure & Risk, Aquatic Ecosystems & Estuarine Research, estuarine research, Ecosystem/Assessment/Indicators, Ecosystem Protection, Aquatic Ecosystem, Aquatic Ecosystems, Ecological Effects - Environmental Exposure & Risk, Environmental Monitoring, Ecological Monitoring, Ecology and Ecosystems, Biology, Gulf of Mexico, Ecological Indicators, monitoring, ecoindicator, ecological exposure, remote sensing, estuaries, estuarine integrity, Mobile Bay, microbial biofilms, Galveston Bay, Apalachicola Bay, estuarine ecoindicator, environmental indicators, environmental stress, estuarine waters, restoration, water quality

    Relevant Websites:

    http://www.usm.edu/gcrl/contacts/view_vitae.php?id=190 Exit

    Progress and Final Reports:

    Original Abstract
  • 2002 Progress Report
  • 2004 Progress Report
  • 2005 Progress Report
  • 2006
  • Final

  • Main Center Abstract and Reports:

    R829458    EAGLES - Consortium for Estuarine Ecoindicator Research for the Gulf of Mexico

    Subprojects under this Center: (EPA does not fund or establish subprojects; EPA awards and manages the overall grant for this center).
    R829458C001 Remote Sensing of Water Quality
    R829458C002 Microbial Biofilms as Indicators of Estuarine Ecosystem Condition
    R829458C003 Individual Level Indicators: Molecular Indicators of Dissolved Oxygen Stress in Crustaceans
    R829458C004 Data Management and Analysis
    R829458C005 Individual Level Indicators: Reproductive Function in Estuarine Fishes
    R829458C006 Collaborative Efforts Between CEER-GOM and U.S. Environmental Protection Agency (EPA)-Gulf Ecology Division (GED)
    R829458C007 GIS and Terrestrial Remote Sensing
    R829458C008 Macrobenthic Process Indicators of Estuarine Condition for the Northern Gulf of Mexico
    R829458C009 Modeling and Integration