Grantee Research Project Results

Final Report: Cyanobacteria and Cyanotoxins in Water Supply Reservoirs – to Develop and Validate a Microarray to Test for Cyanobacteria and Cyanotoxin Genes in Drinking Water Reservoirs as an Aid to Risk Assessment and Management of Water Supplies

EPA Grant Number: R831627
Title: Cyanobacteria and Cyanotoxins in Water Supply Reservoirs – to Develop and Validate a Microarray to Test for Cyanobacteria and Cyanotoxin Genes in Drinking Water Reservoirs as an Aid to Risk Assessment and Management of Water Supplies
Investigators: Rublee, Parke , Henrich, Vincent C. , Burkholder, Joann M. , Glasgow, Howard
Institution: University of North Carolina at Greensboro , North Carolina State University
EPA Project Officer: Aja, Hayley
Project Period: November 1, 2004 through October 31, 2007 (Extended to April 30, 2008)
Project Amount: $594,982
RFA: Microbial Risk in Drinking Water (2003) RFA Text | Recipients Lists
Research Category: Drinking Water , Human Health , Water

Objective:

To develop and validate a gene microarray for the detection of cyanobacteria and cyanotoxin genes in drinking water reservoirs. The microarray can be used to monitor drinking water supplies as an aid to risk assessment and management.

Summary/Accomplishments (Outputs/Outcomes):

Sampling

We proposed to sample 12 water supply reservoirs in North Carolina during a three year sampling period. We accomplished by sampling during summer months from 2004 – 2006. We also took advantage of other ongoing work and were able to sample an additional 16 reservoirs at least once during this same period. Samples were collected either as surface samples taken from shore or dock, or as integrated surface to bottom water samples from docks or piers. Water samples were then split for various analyses. Metadata measures for each sample included temperature, pH, conductivity, dissolved oxygen, orthophosphorus and secchi depth. Samples for DNA extraction consisted of 100 ml water that was drawn through 25 mm GFF filters. Use of this volume of samples and these filters likely missed large filamentous or sheet-like cyanobacteria as well as cyanobacterial mat communities unless they had been fragmented and suspended. Filters were stored in CTAB buffer until extraction by an alcohol-chloroform method. Purified DNA was stored in pH 8 TE buffer and DNA concentration measured on a Thermo Scientific Nanodrop spectrophotometer. Cyanobacteria counts and microcystin concentrations were determined in selected reservoirs where blooms occurred during 2006.

Clone libraries

We selected samples from six lakes sampled in 2006 with high chlorophyll concentrations and histories of cyanobacterial blooms to generate cyanobacterial sequence libraries. Purified DNA from each sample was amplified with generic cyanobacterial primers (CYA106F, CYA781Ra/b: Nubel et al. 1997), the PCR products were cloned competent E. coli, and purified inserts from up to 200 overnight cultures from each lake were then sequenced. A total of 887 readable sequences were collected (from 123 to 187 per lake) and grouped into operational taxonomic units (OTUs) using a criterion that sequences in an OTU had ≥ 97.5% sequence similarity. We found 98 OTUs: 24 OTUs contained multiple sequences (Fig. 1).

Rank abundance curves for the sequence libraries followed expected patterns (Fig. 2). The most abundant OTUs in the combined library were also the most abundant in the individual lake libraries. In each lake there were sequences represented that were unique to each lake. Shannon-Wiener Species diversity values were similar in each lake (1.31 – 1.64), except for Badin Lake in which we recovered less than half the OTUs of any other lake. The combined sequence library had a Shannon-Wiener Species diversity value of 2.03. The rank abundance information can also be used to estimate the total number of cyanobacterial taxa that would be found in each lake with exhaustive sampling, using SACE and Chao1 estimations (Kemp and Aller 2004). These estimates ranged form 27 (SACE) and 24 (Chao1) species in Lake Wheeler, to 171 (SACE) and 177 (Chao1) species in Falls Lake. The combined sequence library estimates were 378 (SACE) and 317 (Chao1) species. This suggests that there are many additional cyanobacterial taxa in the lakes.

We compared the sequences in our library to GenBank entries. First we compared each sequence in each OTU. Not surprisingly, most sequences did not have a close match in GenBank, although some sequences within OTUs had exact matches. We then generated consensus sequences within multiple sequence OTUs both to compare them to GenBank and to design OTU-specific primers (Table 1, 2). Three of the consensus OTU sequences were identical to GenBank entries (OTU 2 = Cylindrosperopsis raciborskii; OTU 8 = Aphanizomenon issatschenkoi; OTU 90 = Nodularia spumigena). An additional 4 OTUs demonstrated ≥ 98% similarity to GenBank entries listed as “uncultured cyanobacteria.” Seven OTUs had ≥ 98% similarity to GenBank entries listed as “uncultured bacteria.” Four OTUs had ≥ 98% similarity to GenBank entries listed as eukaryotic plastids. The remaining OTUs showed ≤ 97% similarity to the closest GenBank entry. Given the difficulty of assigning genera to discrete branches of phylogenetic trees, we have provided only limited indication of taxonomic affiliation for most entries in Table 1.

Primer design

Our strategy in primer design was to target them as much as possible to the V1 through V4 regions of the SSU rDNA sequence, since we had done this successfully for prokaryotic and eukaryotic microbes in previous work (Marshall, et al. 2008) and they provided relatively short amplicons for rapid amplification. We were able to design unique primers 18-32 bp in length to most, but not all, of the OTU sequences in the library (Table 2). Additionally, in order to be amenable to PCR arrays (see section below), we designed primers with similar Tm’s of around 60°C. Because of the relatively high degree of similarity of the different OTU sequences, we used a strategy that sometimes included the same forward or reverse sequence for multiple OTUs, but combined that with a unique primer sequence in the other directions. We then tested the primers against the clone standards to assure amplification of the targeted sequence. When OTUs contained multiple clones we mixed aliquots of clones to produce the standard.

We field tested the primers by running PCR assays across a range of lakes, or by using samples collected over an annual period from three water supply reservoirs: City Lake, Oak Hollow Lake, and Falls Lake, that were sampled from leveraged funding (see description below). We also tested one primer set for the Cylindrospermopsis raciborskii pks gene (Schembri, et al. 2001)

PCR Assays

PCR assays were run on an AB StepOne™ real-time PCR system using 48-well plates. Each plate included three negative controls (no template), 18 samples run in duplicate, and positive control standards which consisted of triplicate samples of three 10-fold serial dilutions of the standard. Preliminary PCR runs established appropriate dilutions of isolated genomic DNA and standards. Reaction mixtures (20 μl) included 20 μl AB Power SYBR Green PCR master mix, 7 μl dd H2O, 1 μl of a 10 μM solution of each primer, and 1 μl of the template, standard (positive control) or water (negative control). Reaction conditions were: 10m at 95ºC; 35 cycles of 95ºC for 15s, 60ºC for 30s, 72ºC for 1m, 80ºC for 15s with detection on; followed by a melt curve analysis. The added step of raising the temperature to 80ºC before fluorescence detection reduces the likelihood of false positives, Further, examination of the melt curve is a quality control step to eliminate false positives.

The results of our PCR assays (Figures 2,3) indicate widespread distribution of the targeted cyanobacteria and considerable variability in abundance across lakes and over a single season. The relative abundance of OTU 23 in 27 reservoirs over three summers spanned more than six orders of magnitude (Fig. 2). Generally, reservoirs with high amounts of the target in one year exhibited the same pattern in other years, although clear peaks (> 10-fold increases) were often evident. Relative abundance of the C. raciborskii pks gene also varied across lakes: it was absent from some lakes and common over multiple years in others (Fig. 2).

Assays of 30 OTU targets over a year in City Lake (Fig. 3) also indicated that relative abundance of OTUs was widely variable. Two patterns of distribution over the year seemed evident: relatively constant abundance throughout the year (e.g. OTUs 14, 23, 36, 87, and 89) or high abundance from June through October, with low abundance in winter and spring (e.g. OTUs 44, 59, 63, 98, and Cylindrospermopsis raciborskii and Psuedanabaena sp.). Despite these apparent patterns of distribution, there were few correlations of OTU abundance with environmental parameters.

There were a few significant correlations among 7 OTU targets and environmental parameters that were tested in three lakes over an annual season (Table 3). Three OTUs showed no correlations, but four showed significant positive correlation with suspended solids and negative correlations with TN:TP ratio. Two of these OTUs also showed a negative correlation with total organic carbon. Only one OTU had a positive correlation with total phosphorus. There were no significant correlations found across 27 reservoirs between OTU23 or the C. raciborskii pks gene and seven environmental parameters (temperature, pH, dissolved oxygen, conductivity, orthophosphate, chlorophyll, secchi depth).

PCR arrays

During the course of this study we shifted our focus from developing a classic silica slide microarray format to developing a PCR array format. This change came about for multiple reasons, including drawbacks to use of the microarray and advantages inherent the emerging PCR array format. First, in extensive consultation with our end user (a municipal water quality laboratory supervisor) and visits to his laboratory it became apparent that the silica slide microarray format was likely not translatable to the municipal water quality laboratory based on the level of technological expertise required and the cost of equipment and supplies. Our experience with microarrays suggested that a high level of expertise was needed, especially for the hybridization step to be completed with consistent quality. Many municipal water quality laboratories do not have budgets that allow employment of technicians with the level of training and experience to use microarrays effectively. Second, while the cost of purchasing pre-made microarray slides may not have been prohibitive once they are mass produced, the commitment of technician time, array reader costs, and reagents required would be marginally affordable. In contrast, by the second year of this grant PCR arrays had developed to the extent that we began to see distinct advantages to their use for cyanobacterial testing. These included: 1) the level of technical expertise was not as high as that required for DNA microarrays. Indeed, we trained both MS candidates and undergraduate students in the three phases necessary for this approach (DNA extraction, quantitative real-time PCR assay, and data review) in just a few weeks. 2) The cost of PCR arrays is lower than the cost of slide microarrays. Not only does it require a less skilled technician, but the PCR array instrument has comparable or lower cost than an Array Scanner, and fewer chemicals are required since there is no hybridization step. 3) The results of PCR arrays can be generated in near real-time. Once a water sample is taken, DNA can be extracted in as little as 1 hour (method dependent) and the PCR assay run takes from 1-3 hours. Thus, samples can be taken and results determined in less than a day, compared to slide microarrays which generally use and overnight hybridization step. 4) PCR arrays are quantitative, while slide microarrays are semi-quantitative at best. PCR arrays compare samples to standards run concurrently with each assay. While this is also possible for the slide microarray, it is technically more challenging. 5) There are multiple quality control points in the PCR array. First, both negative controls and positive control standards are included in each run. Second, a melt curve of the PCR products can be included in each run – the melt curve is a check against false positives, since the melting temperature (Tm) the product is different if an unintended target is amplified. 6) PCR arrays technology is developing rapidly. 7) Finally, PCR arrays offer the possibility of multiplexing, thereby further reducing costs and increasing the number of targets that can be evaluated in each run.

Next steps

In this study we developed primers and protocols that can be used for cyanobacterial PCR arrays by municipal or industrial water quality laboratories. Our approach has been to keep the “end-user” in mind, making an effort to minimize the level of training and resources necessary for routine use. Producing a commercial PCR Array will ultimately involve partnering with industry, such as SA Biosciences, which currently produces PCR arrays for mammalian gene expression, in order to optimize QA and QC. Currently the largest plate format for PCR arrays is 1536-well plate (Roche Diagnostics), although the capabilities are expanding rapidly. In the case of assaying for cyanobacteria, this may not be a limiting constraint, at least for detection of species of primary interest. There are several next steps to take in order to turn this approach into a viable commercial water testing approach:

Develop multiplexing capability: Multiplexing by using specific fluorescent dyes will allow up to a 4-fold increase in the number of targets that can be assayed in a single run. In many cases this is problematic because primers have different Tm’s. In our case we designed primers with similar Tm’s, so adaptation to multiplexing should be relatively easy.
As the number of known target sequences increases, it is likely that the number of targets may surpass the capacity of PCR plates even with multiplexing. Thus, consideration of a tiered approach is warranted. The tiered approach simply means that primary targets are built into an initial assay that can be followed by a choice of second tier of assays dependent upon the results of the initial assay.
Linkage with non-cyanobacterial microbial targets. The development of probes to microbial targets other than cyanobacteria is moving ahead rapidly, along with a growing recognition that metadata collection is necessary to define the environments in which microbes compete successfully. This also suggests that community profiles can be used as predictors of cyanobacterial blooms. Thus, relating microbial community profiles to cyanobacterial abundance is a promising avenue for further research.
Finally, a continuing “thorny” issue is strain differentiation. In the case of cyanobacteria this relates to the toxicity of strains and the potential for lateral gene transfer among them. Our understanding of these issues is not resolved, and continued attention to the specificity of primers and probes is essential for long term success of this approach. We note, however, this has not created an insurmountable obstacle since the literature has system for the presence of potentially harmful cyanobacteria and their toxins which should be of use to water supply managers in order to reduce health risks. To date we have produced prototype components that can serve as the basis for development of a more “user-friendly” real-time (or near real-time) monitoring platform. demonstrated valid data for many taxa. Thus, it is still mostly a concern, rather than a roadblock. Continuing expansion of sequence databases and continued development of analytical tools will help minimize the importance of this consideration.

The development of an array to detect cyanobacteria and cyanotoxin genes can provide multiple functions: a research tool for aquatic scientists to identify factors that promote growth of different cyanobacterial species and their toxins; a prototype early warning system for the presence of potentially harmful cyanobacteria and their toxins which should be of use to water supply managers in order to reduce health risks. To date we have produced prototype components that can serve as the basis for development of a more “user-friendly” real-time (or near real-time) monitoring platform.

Leveraging and outputs: The following accomplishments are due in part to EPA grant #RD083162701-0: Cyanobacteria and cyanotoxins in water supply reservoirs.

Leveraged Funding: Based in part on the funding from this EPA Grant, we applied for and received funds to accelerate the development of a practical application assessment of microbial bioindicators in aquatic ecosystems from the Univ. of NC Competitiveness Research Fund. This has allowed continued sampling of the water supply reservoirs and the installation of automated nutrient sampling devices in these systems.

Integration of Novel Technologies for Safeguarding Potable Water Supplies. $292,010, 12/3/07 – 9/30/08. (Principal Investigators: Parke Rublee, Vincent Henrich, JoAnn Burkholder)

Business Collaboration: The principal investigators and the University have been working with business partners to spin-off a company to further develop and utilize the technology that is being developed as part of the current and past EPA research funding. Helical Sciences, Inc. has been negotiating a licensing agreement with UNCG, and seeking additional funding from the North Carolina Biotechnology Center to advance the commercial development of the technology. Additionally, through Helical Sciences and Southeast TechInventures, a company located in the NC Research Triangle, one Phase I SBIR grant was received and two SBIR Phase II grants were submitted during summer 2008 to NSF and CDC. Although these SBIR grants were not directed at cyanobacteria or cyanotoxins, they were developed based on using the technological approaches that we have been using in the EPA funding.

End user collaboration: We have worked closely with Mr. William Frazier, Water Quality Laboratory Supervisor for the city of High Point, NC. During this study we met frequently with Mr. Frazier to coordinate sampling, discuss his needs in relation to water quality assessment and management, and to provide continued input on our approach. This is an ongoing collaboration.

Table 1. List of operational taxonomic units (OTUs) found in this study with best GenBank match (accession #, description, source location, and % similarity) to the consensus OTU sequence. Taxonomic identification given where possible. Similarity values ≥ 98% are noted in bold. Note that OTUs 16, 71, and 99 are likely eukaryotic chloroplast 16S ribosomal genes.

OTU

Accession

Description

% similarity

AJ007864.1

unidentified cyanobacterium clone LD7

Lake Loosdrecht, Netherlands

96%

Prochlorothrix hollandica

AF516745.1

Cylindrospermopsis raciborskii strain Florida F

Florida, USA

100%

Cylindrospermopsis raciborskii

AF330249.1

Synechococcus sp. LBG2

Lake Biwa, Japan

99%

Synechococcus sp.

EU273090.1

Uncultured bacterium clone TH_d324

Lake Taihu, China

99%

GU131246.1

Uncultured bacterium clone LK15m-37-16S

Lake Kinneret, Israel

99%

FJ204874.1

Uncultured cyanobacterium clone NK2_CYA_2_1

Lake Kastoria, Greece

98%

chloroplast - likely cryptomonas

EF633015.1

Uncultured cyanobacterium clone H1w-5

Salar de Huasco, Chile

92%

DQ158169.1

Uncultured cyanobacterium clone LK1mC-7

Lake Kinneret, Israel

97%

Synechococcus sp.?

EU078536.1

Aphanizomenon issatschenkoi LMECYA 190

Maranhão Reservoir, Portugal

100%

Aphanizomenon issatschenkoi

EU592776.1

Uncultured bacterium clone MFBC7A05

Tucurui Reservoir, Brazil

95%

Synechococcus sp.?

FJ745161.1

Uncultured cyanobacterium clone SHWN_night2_16S_697

estuary, Gerogia, USA

93%

EU168191.1

Heterosigma akashiwo strain CCMP 452 chloroplast

Long Island Sound, USA

92%

Heterosigma akashiwo chloroplast

EF568905.1

Anabaena sp. XPORK15F

Gulf of Finland

96%

Anabaena sp.

DQ166477.1

Uncultured eukaryote clone ML-9-3 plastid

Lake Taihu, China

99%

EF520521.1

Uncultured cyanobacterium clone ADK-SGh02-76

Adirondack Lake, NY, USA

97%

EU283208.1

Uncultured bacterium clone EDP-26

pond, Dongshan Island, China

91%

EF520521.1

Uncultured cyanobacterium clone ADK-SGh02-76

Adirondack Lake, NY, USA

94%

FJ204854.1

Uncultured cyanobacterium clone ND2_CYA_1_8

Lake Doirani, Greece

97%

Psuedanabaena sp.?

DQ393278.1

Spirulina laxissima strain SAG 256.80

Laka Nakuru, Kenya

95%

Spirulina sp.?

AJ007864.1

unidentified cyanobacterium clone LD7

Lake Loosdrecht, Netherlands

92%

EU592812.1

Uncultured bacterium clone MFBC10C06

Tucurui Reservoir, Brazil

95%

FJ490330.1

Uncultured bacterium clone H_10

Dry Valley, Antarctica

92%

EU552070.1

Cylindrospermopsis raciborskii (Raphidiopsis sp. D9)

Billing reservoir, Brazil

95%

Cylindrospermopsis sp.?

FJ204854.1

Uncultured cyanobacterium clone ND2_CYA_1_8

Lake Doirani, Greece

98%

FJ490330.1

Uncultured bacterium clone H_10

Dry Valley, Antarctica

93%

FJ204843.1

Uncultured cyanobacterium clone ND2_CYA_4_32

Lake Doirani, Greece

91%

EU078524.1

Anabaena spiroides LMECYA 161 C20

Agolada de Baixo Reservoir, Portugal

97%

Anabaena sp.

EU168191.1

Heterosigma akashiwo strain CCMP 452 plastid

Long Island Sound, USA

89%

FM242084.1

Anabaena mendotae 04-45

Svet fishpond, Czech Republic

94%

EF520521.1

Uncultured cyanobacterium clone ADK-SGh02-76

Adirondack Lake, NY, USA

95%

EF520521.1

Uncultured cyanobacterium clone ADK-SGh02-76

Adirondack Lake, NY, USA

96%

EU552068.1

Cylindrospermopsis raciborskii CS-511

McKinlay farm dam, QLD, Australia

94%

EU409863.1

Uncultured cyanobacterium clone 16L6

Georgia, USA

92%

EU273090.1

Uncultured bacterium clone TH_d324

Lake Taihu, China

99%

AY742448.1

Nostoc sp. 8941

New Zealand

95%

AY328614.1

Uncultured bacterium HOClCi65

drinking water simulator, USA

98%

FJ204841.1

Uncultured phototrophic eukaryote clone ND2_CYA_1_22 plastid

Lake Doirani, Greece

95%

FJ745161.1

Uncultured cyanobacterium clone SHWN_night2_16S_697

estuary, Gerogia, USA

93%

AJ007864.1

unidentified cyanobacterium clone LD7

Lake Loosdrecht, Netherlands

94%

EU552070.1

Cylindrospermopsis raciborskii (Raphidiopsis sp. D9)

Billing reservoir, Brazil

95%

EF395686.1

Uncultured bacterium clone CBM01H09

Chesapeake Bay, MD, USA

95%

EU552070.1

Cylindrospermopsis raciborskii (Raphidiopsis sp. D9)

Billing reservoir, Brazil

96%

EU592798.1

Uncultured bacterium clone MFBC5F11

Tucurui reservoir, Brazil

98%

FJ204841.1

Uncultured phototrophic eukaryote clone ND2_CYA_1_22

Lake Doirani, Greece

92%

EU168191.1

Heterosigma akashiwo strain CCMP 452 plastid

Long Island Sound, USA

87%

EF520521.1

Uncultured cyanobacterium clone ADK-SGh02-76

Adirondack Lake, NY, USA

97%

FJ204874.1

Uncultured cyanobacterium clone NK2_CYA_2_1

Lake Kastoria, Greece

92%

AJ133160.1

Anabaena sp. strain A277

River Perniönjoki, Finland

94%

EU980182.1

Uncultured cyanobacterium clone TH_f27

Lake Taihu, China

92%

EU255706.1

Uncultured cyanobacterium clone Mat-CYANO-S8

freshwater mat, CA, USA

92%

AY328614.1

Uncultured bacterium HOClCi65

drinking water simulator, USA

95%

EU283259.1

Uncultured bacterium clone PVP-121

pond, Dongshan Island, China

92%

FJ204890.1

Uncultured cyanobacterium clone NV1_CYA_1_12

Lake Volvi, Greece

95%

EU592777.1

Uncultured bacterium clone MFBC9A02

92%

FJ638592.1

Uncultured bacterium clone KCLunmb_25_16

spring sediment, Taiwan

92%

AY742448.1

Nostoc sp. 8941

New Zealand

96%

EU078535.1

Aphanizomenon issatschenkoi LMECYA 166

Vale Michões Reservoir, Portugal

96%

Aphanizomenon sp.

EU552070.1

Cylindrospermopsis raciborskii (Raphidiopsis sp. D9)

Billing reservoir, Brazil

97%

AJ006286.1

Unidentified cyanobacterium clone LD25

Lake Loosdrecht, Netherlands

95%

EU641407.1

Uncultured cyanobacterium clone LW9m-1-3

Lake Michigan, WI, USA

93%

EF632984.1

Uncultured cyanobacterium clone H6w-73

Salar de Huasco, Chile

94%

FJ999606.1

Uncultured cyanobacterium clone B97

South China Sea, China

94%

EU592816.1

Uncultured bacterium clone MFBC10H09

Tucurui reservoir, Brazil

95%

EF520521.1

Uncultured cyanobacterium clone ADK-SGh02-76

Adirondack Lake, NY, USA

97%

EU592789.1

Uncultured bacterium clone MFBC2C08

Tucurui reservoir, Brazil

99%

DQ158169.1

Uncultured cyanobacterium clone LK1mC-7

Lake Kinneret, Israel

94%

EU273090.1

Uncultured bacterium clone TH_d324

Lake Taihu, China

93%

EF632962.1

Uncultured cyanobacterium clone H4s-61

Salar de Huasco, Chile

93%

AY948063.1

Uncultured phototrophic eukaryote clone PRD18G11 plastid

Parker River, MA, USA

99%

DQ158169.1

Uncultured cyanobacterium clone LK1mC-7

Lake Kinneret, Israel

93%

EU980295.1

Uncultured cyanobacterium clone TH_h52

Lake Taihu, China

95%

U70724.1

Unidentified cryptomonad OM283

Cape Hatteras, NC, USA

94%

EF520521.1

Uncultured cyanobacterium clone ADK-SGh02-76

Adirondack Lake, NY, USA

98%

EU375434.1

Uncultured bacterium clone P4O-58

References:

Kemp, P.F. and J.Y. Aller. 2004. Estimating prokaryotic diversity: When are 16S rDNA libraries large enough? Limnology and Oceanography Methods 2:114-125.

Nübel, U., Garcia-Pichel, F., and Muyzer, G. 1997. PCR Primers To Amplify 16S rRNA Genes from Cyanobacteria. Applied And Environmental Microbiology 63:3327–3332.

Schembri, M.A.; Neilan, B.A.; Saint, C.P. 2001. Identification of genes implicated in toxin production in the cyanobacterium Cylindrospermopsis raciborskii. Environ. Toxicol. 16:413–421.

Journal Articles on this Report : 2 Displayed | Download in RIS Format

Publications Views
Other project views:	All 33 publications	6 publications in selected types	All 2 journal articles

Publications
Type	Citation	Project	Document Sources
Journal Article	Marshall MM, Amos RN, Henrich VC, Rublee PA. Developing SSU rDNA metagenomic profiles of aquatic microbial communities for environmental assessments. Ecological Indicators 2008;8(5):442-453.	R831627 (2007) R831627 (Final)	Abstract: Science Direct abstract Exit Other: UNC PDF Exit
Journal Article	Touchette BW, Burkholder JM, Allen EH, Alexander JL, Kinder CA, Brownie C, James J, Britton CH. Eutrophication and cyanobacteria blooms in run-of-river impoundments in North Carolina, U.S.A. Lake and Reservoir Management 2007;23(2):179-192.	R831627 (Final)	Abstract: Informaworld abstract Exit Other: Mendeley abstract Exit

Supplemental Keywords:

RFA, Scientific Discipline, INTERNATIONAL COOPERATION, Water, Health Risk Assessment, Environmental Chemistry, Drinking Water, Environmental Engineering, Environmental Monitoring, microbial contamination, gene microarray assay, early warning, microbial risk assessment, monitoring, cyanobacteria, drinking water system, drinking water contaminants, aquatic organisms, other - risk assessment

Relevant Websites:

Real time physical and chemical data from some of our study sites can be found at the Center for Applied Aquatic Ecology website at NCSU: http://www.ncsu.edu/wq/

Progress and Final Reports:

Original Abstract

The perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Conclusions drawn by the principal investigators have not been reviewed by the Agency.

Grantee Research Project Results

Final Report: Cyanobacteria and Cyanotoxins in Water Supply Reservoirs – to Develop and Validate a Microarray to Test for Cyanobacteria and Cyanotoxin Genes in Drinking Water Reservoirs as an Aid to Risk Assessment and Management of Water Supplies

Objective:

Summary/Accomplishments (Outputs/Outcomes):

References:

Supplemental Keywords:

Relevant Websites:

Progress and Final Reports:

Project Research Results

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