Comparison of Functional Characteristics of Planktonic and Biofilm

Forms of Microbial Communities Upstream and Downstream

from a Wastewater Treatment Plant

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A THESIS

Submitted to

York College of Pennsylvania

in partial fulfillment of the requirements

of the degree of

Bachelor of Science

Completed December 4, 2006

ABSTRACT

In microbiology, functional characteristics are not frequently studied. Instead, more concentration is placed on taxonomic classification. While it is helpful to know the species of a microorganism found in a biofilm, the ecological importance of the species is ignored if functional characteristics are not studied. There are three main objectives of this study: to determine whether or not the released effluent from the Dover Township Wastewater Treatment Facility affects the 1) functional diversity, 2) functional evenness, and 3) functional richness, of the biofilm and planktonic communities in the Little Conewago Creek. In this study, BIOLOG microplates were used. A water sample was taken upstream and downstream from the Dover Township Wastewater Treatment Facility. GN2 and ECO plates were used and three types of samples were created for each site location on the Little Conewago Creek: planktonic at t= 0, planktonic after growth, and biofilm. The results of the data comparison indicated that there was no difference in the functional characteristics between the upstream and downstream samples of the microbial communities, and thus that the Dover Township Wastewater Treatment Facility is functioning properly and is not affecting the functional abilities of the microbial communities in the Little Conewago Creek. Relevant data from the facility supports the conclusion that the facility is not affecting the microbial communities of the creek. Hopefully, this type of research will occur more frequently in the future, so that further knowledge is gained about the dynamic processes that occur within microbial communities.

INTRODUCTION

In 1933, Arthur Henrici discovered that the majority of aquatic bacteria were fixed to some surface rather than having existed as free-floating/planktonic. This discovery led to the initiation of the exploration of biofilms (O’Toole et al. 2000). Since 1933, microbiologists have acquired a strong interest in learning more about the dynamics that take place within the biofilm structure. Many researchers are currently investigating why and how biofilms form and the purposes that they serve (Burmolle et al., 2006; Macalady et al., 2006; O’Connell et al., 2006; Steed and Falkinham III, 2006). Biofilms are composed of numerous types of microorganisms, such as bacteria, fungi, protozoa, and algae, that attach to a substrate and have the ability of existing in a symbiotic relationship. They greatly impact the natural surroundings since they can thrive in almost any aqueous environment. For example, biofilms are frequently found in the human body, causing tooth decay or being part of an infection that was caused by bacteria entering surgical sites via instrument usage (Harshey 2003). Additionally, biofilms are found in environments outside the human body, such as on rocks in a streambed, on the walls of an aquarium (Hovanec and DeLong 1996), or in pipes of a water distribution system (Schwartz et al. 2003). Another main example of the presence of biofilms is in wastewater treatment (Eighmy et al., 1983; Ibekwe et al., 2003).

There are four main stages that occur within the life cycle of a biofilm: initiation, maturation, maintenance, and dissolution (O’Toole et al. 2000). It is believed that initiation of a biofilm occurs in the presence of numerous environmental cues, such as an abundance of nutrients. Numerous microorganisms come together via these cues and form a mature biofilm, a structure that includes several layers of organisms. The maintenance of a biofilm requires the continuance of availability of the environmental cues that initiated the biofilm formation process, i.e. abundant nutrient supply (O’Toole et al. 2000). If biofilm maintenance becomes a problem and nutrients are in short supply, dissolution or detachment occurs. In this stage, the sessile cells return to their planktonic form in order to search for nutrients. Nutrient accumulation will once again initiate biofilm formation (O’Toole et al. 2000).

Biofilm formation is an extremely complex process in that the four main stages of a biofilm life cycle mechanistically vary among different microorganisms. Most bacteria utilize quorum sensing during the initiation process. Quorum sensing (QS) involves the presence of small signal molecules to determine the relative population densities of microbial populations. QS is a gene controller in microbial populations since it will turn on or off genes that can affect the activity of the cells in the population, such as aggregating to form a biofilm (Ghannoum and O’Toole, 2004). This system of cell-to-cell signaling does, however, vary between gram-positive and gram-negative bacteria. Acyl-HSL forms the basis of quorum sensing in gram-negative bacteria, while the release of peptides is involved in gram-positive bacteria communication (Parsek and Fuqua 2004). As previously mentioned, quorum sensing is not the only mechanism by which microbes initiate biofilm formation. Environmental cues such as nutrient availability, temperature, pH, osmolarity, iron content, and oxygen content also play a significant role in this stage (O’Toole et al. 2000). The initiation stage of the life cycle of biofilms is indicated by the formation of numerous microcolonies that arise from sessile cells (Mai-Prochnow et al. 2004).

At some point between the initiation and maturation stages, microbes in a biofilm undergo drastic morphological changes. They must adapt to their new living condition, one that is motion-sedentary versus one that is motion-based. Morphological characteristics vary among different species of bacteria. Two examples include the stalk cells of Caulobacter crescentus and sporulation of Bacillus subtilis and Myxococcus xanthus (O’Toole et al. 2000). One main characteristic of biofilms is that there exists an abundance of extracellular polysaccharides (EPS) around the microorganisms, which function as a shield that keeps the microbes relatively stationary. The composition of EPS varies among different microbes. For example, mannose and glucose compose the polysaccharide that is formed by the psl locus on the PAO1 chromosome of Pseudomonas aeruginosa, whereas stewartan is the EPS formed by Pantoea stewartii (Parsek and Fuqua 2004).

The breaking down of the extracellular polysaccharide matrix is believed to initiate the process of dissolution. Cell surface-associated enzymes that cut through the layer and provide a means of escape for the bacteria to initiate breakdown of the EPS. Microorganism morphology once again changes as the organisms reactivate their means of motility (Parsek and Fuqua 2004). Once their means of motility are activated, the organisms return to their planktonic forms. For example, in P. aeruginosa, Sauer (2002) discovered that the gene pilA expression was shut down during dissolution; this gene is responsible for the function of the type IV pilus that is used in adherence to the biofilm. Following this gene expression shut down, the expression of genes that function in the activation of motility factors was resumed (Parsek and Fuqua 2004).

Microbiological communities are frequently analyzed by the usage of taxonomic diversity or genetic diversity, but the third component of biodiversity, functional diversity, is perhaps the least studied (Zak et al., 1994). A recent molecular technique, such as temperature gradient gel electrophoresis (TGGE), which is based on melting profiles of different microorganisms, has been widely used to study taxonomic and genetic diversity of microbial communities (Muyzer, 1999; Brummer et al., 2003). Another molecular technique, known as denaturing gradient gel electrophoresis (DGGE), which utilizes an increasing strength in a denaturant across the span of the gel to separate the bands of different microorganisms, has also been frequently used to study taxonomic and genetic diversity (Muyzer, 1999; Massieux et al., 2004). A third molecular approach involves the study of rRNA differences between microorganisms; an example is rRNA intergenic spacer analysis (RISA). This method functions via PCR amplification of the intergenic region between the 16S and 23S subunit rRNA genes in the rRNA operon; a sample of the entire microbial community DNA is used in the procedure (Fisher and Triplett, 1999). Another application of rRNA and rDNA is terminal restriction fragment length polymorphism (T-RFLP), which involves the PCR amplification of 16S rDNA to establish a microbial community profile (Martiny et al., 2003).

While all of the aforementioned techniques provide useful information, such as the naming of organisms found in a freshwater source and the increase in knowledge of genetics, they fail to provide a key understanding of microorganisms: their functions in the environment. Ecology is lacking from the taxonomic and genetic components of biodiversity. Therefore, functional diversity fills the gap in knowledge of how microorganisms actually perform in their natural environments. Furthermore, macro-organisms receive much attention in research, rather than microorganisms, which also carry out vital processes in the environment (Zak et al., 1994). One such example of the vital processes microbial communities carry out is the soil microbes that are involved in nutrient transformation and other important processes that take place in the soil that affect the rhizosphere, and consequently, plant growth (Grayston and Campbell, 1996). Functional diversity, therefore, provides important knowledge dealing with the numbers, types, activities, and rates that substrates are utilized by the microbial community (Zak et al., 1994). Functional diversity is most commonly determined by the Shannon index (H’), which involves calculations of the proportions of the substrates (Mills and Wassel, 1980). Two components are involved with functional diversity: substrate/functional richness and substrate/functional evenness. Functional richness is the number of different substrates used by the community, whereas functional evenness provides information as to whether or not there was dominance of the usage of a particular substrate (Zak et al., 1994).

The most widely used medium for analyzing the functional characteristics of microbial communities is the BIOLOG plate, specifically the GN2 (gram-negative 2) and ECO (ecology) plates (Biolog, Inc.). Each well of the microplate contains a dehydrated form of a carbon substrate, along with tetrazolium violet dye and nutrients. The plates function via redox reactions between the microorganism and the tetrazolium violet dye; basically, the dye detects respiration and the dye along with the substrate is ingested into the microorganism to stain the microorganism purple. Purple color in the well, therefore, indicates substrate utilization. The sole carbon sources in the Biolog GN2 plates include carbohydrates, carboxylic acids, amino acids, esters, polymers, alcohols, amides, amines, aromatic chemicals, brominated chemicals, and phosphorylated chemicals; these carbon sources are in 95 of the 96 wells in a GN2 plate, with a different substrate in each well and 1 control well that includes only water (Garland and Mills, 1991). The ECO plate is more ecologically friendly since it has a built in triplicate system. Rather than having 95 different substrates, the ECO plate has 31 different substrates and a control well tested 3 different times within one plate. While the main disadvantage is a substantially reduced number of substrates that are tested, the ECO plate allows for in-plate replication, which is useful in determining the degree of homogeneity of the environmental sample. Moreover, it has been found that GN and ECO plates are equally capable in analyzing microbial communities (Choi and Dobbs, 1999).

One method of utilizing the functional characteristics of microbial populations is by applying them to the setting of a wastewater treatment plant. Wastewater treatment is the world’s most common biotechnological advancement; for example, there are more than 15,000 plants in the United States that process 100 billion liters of wastewater daily (Graham and Smith, 2004). The functional characteristics of microbial communities found upstream and downstream from a wastewater treatment plant can help to determine whether or not the plant is functioning properly. This is accomplished by comparing the functional characteristic values of the upstream and downstream samples and noting any differences in those values. The lesser the difference between the sets of values, the greater the probability the plant is properly removing pollutants before they reach the outfall structure where the treated water is released into a creek or other body of water. To more fully understand the significance of such a comparison, it is important to be familiar with the methods a wastewater treatment plant utilizes to reduce the amount of harmful substances in the effluent. The wastewater treatment process consists of four main steps: 1) primary treatment (large solids are removed from the influent), 2) secondary treatment (activated sludge systems-composed of mixed microbial populations- remove dissolved organic matter), 3) secondary clarification (solids made during secondary treatment are settled, collected, and recycled), and 4) solids digestion (anaerobic or aerobic digestion takes place to reduce the amount of biosolids from the previous treatment steps). Tertiary treatment may be employed in some facilities to further remove nitrogen, phosphorus, and organic carbon (Graham and Smith, 2004). If these steps do not function properly, a disaster in the ecosystem of the creek that receives the effluent from the plant would likely result (subsequently, state laws mandate the amount of allowable materials to be released into streams and creeks).

This is a novel study since most microbial communities are examined using molecular methods, such as rRNA differences, rather than methods that utilize ecological differences. Additionally, no studies have been completed using these methods to compare microorganisms in planktonic and biofilm communities. There are three main objectives of this study: to determine whether or not the released effluent from the Dover Township Wastewater Treatment Facility affects the 1) functional diversity, 2) functional evenness, and 3) functional richness, of the biofilm and planktonic communities in the Little Conewago Creek.

MATERIALS AND METHODS

Pilot Study #1

In order to grow biofilms, four containers were constructed. These containers were clear plastic Rubbermaid TakeAlongs containers, and each had a volume of 1.2 L. Each container had a lid, and four holes were cut equidistant in the lid. The size of the hole cut depended on the size of the rubber stopper that would be placed in the hole. A slit was cut in each rubber stopper in order to insert a sterile glass slide. The stopper and the slide could then be inserted into the container and the lid could be sealed. Before this action was taken, the volume of liquid required to fill the container to two-thirds full was recorded; this value was 700 mL. This volume of liquid consequently covered approximately two-thirds of each slide.

On April 8, 2006, saltwater was collected from the salt marsh guts (marsh creeks) in Chincoteague Bay and placed in a large carboy. The water sample was collected from a boat, and the pH and temperature of that water was also taken. All containers and the 1000 mL graduated cylinder were rinsed with seawater three times. 700 mL of seawater were then added to each container, and the lids with the slides were then sealed on top of the container. The containers were labeled 1, 2, 3, and 4, in the order they were filled. All four containers were then placed into a shaker with the following settings: 65 RPM and 13.0 ºC (conditions that would reflect the natural environment-13.0 ºC was the original temperature of the seawater). The containers remained in the shaker for eight days to allow time for biofilm development on the slides. Samples were then saved for DNA population analysis (n= 12 slides); both sides of the slides were scraped with a sterile disposable cell scraper to remove biofilms and sterile water was used to rinse the slides to bring the total volume of solution to 500 μL/tube. Each set of three slides was rinsed into the same Wheaton tube and then placed into a freezer set at –90 ºC for later analysis. Each tube was labeled with the number of the container of the sample it contained. The fourth slide of each container was set aside for direct cell count; both sides of the slide were scraped with a sterile cell scraper and rinsed with sterile water and placed into a Wheaton tube. 30 μL of buffered formulin were added to preserve the biofilm cells and sterile water was added to bring the total volume per tube up to 500 μL. Each of the four tubes was labeled with the number of the container that the sample came from and was placed into a refrigerator. The absorbance of the planktonic cells in each of the four containers was then measured by setting the Spec20 wavelength to 450 nm and using 4 mL of seawater for each cuvette; one absorbance reading was taken for each sample.

Pilot Study #2

Another collection of seawater was taken from the salt marsh guts of Chincoteague Bay on May 28, 2006 and placed in a large sterile carboy. The temperature of the water was obtained. Shortly after the water sample arrived at York College of Pennsylvania, 150 μL of seawater were pipetted from the carboy into each of the wells of the BIOLOG GN2 and ECO plates. A repeating pipetor was used to expedite the process and minimize bias. Each plate was read immediately so that a planktonic at t = 0 reading was established. After the absorbance of the wells was read (the plates were placed into a plate reader and the appropriate reading protocol was utilized- Biolog GN 590 nm protocol for the GN2 plate and Biolog protocol for the ECO plate). The plates were then placed in an incubator that was set at 22 ºC (original seawater temperature) and placed on a 12 hours light/12 hours dark light regime. Then, 700 mL of seawater from the carboy were placed into two of the previously used plastic containers (cleaned with soap and sterile water) and placed into the shaker at settings of 65 RPM and 22 ºC. After that step was completed, 10 mL of seawater were placed into each well of two Nunclon plates for later plate reading. These two plates were also placed in the shaker. Evaporation of a plate was noticed in one of the wells of one of the Nunclon plates and 5 mL of sterile water were added to that well to maintain equivalent volume across all wells.

On June 29, 2006, the shaker was turned off. It was decided to not only have absorbance readings for the planktonic at t = 0 sample, but also for planktonic after growth in the container and for the biofilm samples. The following procedure was used for the biofilm samples: 1) the procedure began with the biofilm harvesting so that the slides did not dry out, 2) a sterile surgical blade was used to scrape each side of the slide 30 times- this was done for each of the 8 slides, 3) the biofilm scrapings and the sterile water that was used to rinse the slides were pooled into centrifuge tubes, 4) it was determined that a total of 30 mL of liquid was required to inoculate both BIOLOG plates, 5) the centrifuge tubes were vigorously swirled to create a homogenous mixture that allowed accurate representation for each well in the microplate, and 6) 150 μL were pipetted from the centrifuge tube into each well of the GN2 and ECO plates. The following procedure was used for the planktonic samples: 1) the liquids of each plastic container were pooled for 1.4 L total liquid, 2) the sterile beaker was swirled vigorously to create a homogenous solution, and 3) 150 μL were pipetted into each well of the GN2 and ECO plates. The samples from one Nunclon plate were preserved for DNA analysis (both planktonic and biofilm). The following procedure was followed for this step: 1) for preservation purposes, the total volume of the biofilm and planktonic sample was 5% formulin, 2) liquid was pipetted from each well of the Nunclon plate into a large centrifuge tube, 3) each well was rinsed 3 times to remove any remaining planktonic cells and the biofilm was then scraped from each well using a sterile cell scraper, 4) sterile water was used to rinse each well, 5) the biofilm samples were pooled into a large centrifuge tube, and 6) both tubes were placed into a refrigerator. For the other Nunclon plate, absorbance readings were taken of the planktonic samples. After the wells were rinsed with sterile water 3 times, the biofilms were stained and absorbance readings were taken to gain an understanding of the density of the biofilm in each well. The following biofilm density by absorbance protocol was established and followed: 1) each well was rinsed twice with sterile water after the planktonic samples had been removed and all wash water was placed in a container and bleach was added to destroy the microorganisms, 2) 1% crystal violet dye was used to stain each well, 3) 1 mL of the dye was added to the first well and the biofilm was allowed to stain for 5 minutes, 4) the well was washed with sterile water twice and the wash water was discarded into bleach solution, 5) 6 mL of 95% ethanol were added to the stained well to re-elute the crystal violet and allow for an absorbance reading to be taken, 6) the ethanol/crystal violet solution was transferred from the well to a cuvette, 7) 7 mL of 95% ethanol were placed into a cuvette and read at 450 nm; this was the control, and 8) the ethanol/crystal violet solution was placed in a cuvette in the Spec20 and absorbance was recorded at 450 nm and then the procedure was repeated for the remaining five wells. This procedure was completed since the Nunclon plates did not fit into the plate reader.

Wastewater Treatment Plant Study

The Wastewater Treatment Facility study took place at the Dover Township Wastewater Treatment Facility in York County, PA (LAT: 40º00’42”, LONG: 76º48’04”). The plant (NPDES Permit # PA0020826) serves Dover, Conewago, Manchester, and West Manchester Townships. The facility underwent several expansions, with the last one occurring in 1997; it is now able to treat 8 million gallons of wastewater per day (MGD). Technologically speaking, the facility is quite advanced. The presence of motor control centers and computer network systems drastically increase the efficiency of the facility. Steps to treat the wastewater are similar to other plants in the area; the plant makes use of: 1) an influent pump station to receive sewage, 2) a grit removal system to remove larger particles such as sand, gravel, and glass, 3) ferric chloride to remove precipitated phosphates, 4) oxidation ditches where microorganisms use chemically bound oxygen in the anoxic zone of the wastewater, 5) a system of six clarifiers to settle solids that are then transported back to the oxidation ditches, 6) an ecologically friendly disinfection system that uses ultraviolet light disinfection rather than chlorine gas to destroy the DNA of the microorganisms that were left in the water flow from the clarifiers, and 7) the remaining sludge is then pumped into one of three digesters and is mixed and aerated until it becomes stabilized; the stabilized sludge is known as biosolids and can be applied to farmland as long as it meets state and federal requirements. The plant releases its effluent into the Little Conewago Creek, which is located at the rear of the facility.

One-liter samples were taken upstream and downstream from the outfall structure. The temperature of the samples at both sites was 21 ºC, and the pH of the creek water at each site was also obtained (7.60 for the upstream sample and 7.53 for the downstream sample). The upstream sample was located at the right rear corner of the facility approximately 1 meter north of the outfall structure, while the downstream sample was located approximately 183 meters from the outfall structure. Both samples were placed into a Styrofoam cooler to maintain original water temperature. The following procedure was followed once the samples were at York College: 1) two-500mL water samples were poured into a sterile beaker and swirled, 2) a 1000 mL graduated cylinder was rinsed with sterile water, 3) 700 mL of the upstream sample were poured into a biofilm growing container (same type of container as those used in the pilot studies) and the shaker was set at 65 RPM and 21 ºC, 4) the remaining liquid (300 mL) was poured into a sterile 400 mL beaker and was swirled vigorously, 5) 150 μL samples were pipetted into the GN2 and ECO plates and then the plates were placed immediately into the plate reader to obtain a planktonic @ t = 0 absorbance reading, 6) all four plates were placed in an incubator that was set at 21 ºC and 12 hours light/12 hours dark, and 7) the procedure was repeated for the downstream 1 L sample.

Each inoculated plate (containing planktonic at t =0 samples) was read in the plate reader until maximum average well color development (AWCD) was reached. This means that continual reading of the plates must be completed so that maximum AWCD is detected. To obtain AWCD, the following two sums were calculated: 1) sum of absorbance values (all of the absorbance values of the wells were summed and then the control absorbance value was subtracted) and 2) sum of R-C (where R= absorbance value of a given well and C= absorbance value of the control well)- each well’s absorbance value had subtracted from it the control absorbance value and then all of those values (differences) were summed. AWCD values were calculated by taking the sum of R-C and dividing it by the number of substrates in each plate (95 for GN2 and 31 for ECO plate). The AWCD values were placed on separate graphs, corresponding to the separate BIOLOG plates. Once a peak was reached on the AWCD graph, plate reading was no longer continued. The absorbance values at the peak of the graph were used to eventually calculate functional diversity.

To calculate the functional diversity of each plate, two types of values were calculated: p_i and ln of p_i. P_i is defined as the absorbance of 1 substrate divided by the sum of absorbance values (absorbance value of control well was not included). The natural log of each P_i value was then taken (the absorbance value of the control was not included). Functional diversity was then calculated by the following formula: H = -Σ [p_i(ln p_i)]. Substrate/functional richness (S) was found by taking a count of the number of purple wells in each plate. Substrate/functional evenness (E) was calculated by application of the following formula: E = H/(ln S). The above three functional characteristic values were calculated three times for the ECO plate due to the triplicate nature of the plate.

On July 31, 2006, the shaker was stopped for biofilm harvesting. The following procedure was applied for planktonic samples: 1) a 300 mL sample was obtained and was placed into a sterile 400 mL beaker, 2) this sample was stirred continuously while 150 μL were pipetted into each well of the microplates, and 3) a GN2 and ECO plate was inoculated for upstream and downstream samples. The following procedure was completed prior to the planktonic procedure for the biofilm samples: 1) each slide was rinsed with sterile water three times to remove planktonic organisms, 2) both sides of the biofilm slides were scraped 30 times with a sterile surgical blade into 40 mL of sterile water to prevent the biofilms from drying, and 3) after the 40 mL solution was vigorously swirled, 150 μL of the solution were pipetted into each well of GN2 and ECO plates for both upstream and downstream samples. The functional characteristic values were completed as previously mentioned for these plates. A total of 12 plates were read and analyzed (n= 4 for planktonic at t =0, n=4 for planktonic, and n=4 for biofilm).

RESULTS

Maximum Average Well Color Development

The maximum average well color development (AWCD) for the planktonic at t=0

sample occurred on July 20, 2006 for the before plant/upstream (BP) sample and on July 19, 2006 for the after plant/downstream (AP) sample. All AWCD values are reported in Table 1. The maximum AWCD for the BP sample from the GN2 plate was calculated to be 1.398; the mean maximum AWCD for the same sample from the ECO plate was 1.493. The maximum AWCD for the AP sample from the GN2 plate was 1.298, and the mean maximum AWCD for the same sample from the ECO plate was 1.346. The maximum AWCD for the BP and AP planktonic samples occurred on August 10, 2006. The maximum AWCD for the BP planktonic sample for the GN2 plate was 0.853, and the mean maximum AWCD for the same sample for the ECO plate was 0.856. The maximum AWCD for the AP planktonic sample for the GN2 plate was 0.984, and the mean maximum AWCD for the same sample for the ECO plate was 0.973. The maximum AWCD for the BP and AP biofilm samples occurred on August 9, 2006. For the GN2 plate of the BP biofilm sample, the maximum AWCD was 1.394. For the ECO plate of the same sample, the mean maximum AWCD was 1.463. For the GN2 plate of the AP biofilm sample, the maximum AWCD was 1.383. For the ECO plate of the same sample, the mean maximum AWCD was 1.324.

Functional Richness

No difference was observed in the functional richness between the BP and AP samples, as shown in Figures 1-6. The functional richness for the GN2 plate of the BP planktonic at t=0 sample was 92, and the mean functional richness for the ECO plate of the BP planktonic at t=0 sample was 31. The functional richness for the GN2 plate of the AP planktonic at t=0 sample was 94, and the mean functional richness for the ECO plate of the same sample was 31. The functional richness for the GN2 plate of the BP planktonic sample was 76, and the mean functional richness for the ECO plate of the same sample was 24. For the GN2 plate for the AP planktonic sample, the functional richness was 88. For the ECO plate of the same sample, the mean functional richness was 29. For the GN2 plate for the BP biofilm sample, the functional richness was 86. For the ECO plate of the same sample, the mean functional richness was 30. For the GN2 plate for the AP biofilm sample, the functional richness was 86. For the ECO plate of the same sample, the mean functional richness was 28.

Functional Evenness

No difference was observed in the functional evenness between the BP and AP samples, as shown in Figures 1-6. The functional evenness for the GN2 plate for the BP planktonic at t=0 sample was 0.989, and the mean functional evenness for the ECO plate of the same sample was 0.990. The functional evenness for the GN2 plate for the AP planktonic at t=0 sample was 0.984, and the mean functional evenness for the ECO plate of the same sample was 0.986. For the GN2 plate for the BP planktonic sample, the functional evenness was 0.979. For the ECO plate of the same sample, the mean functional evenness was 0.963. The functional evenness of the GN2 plate for the AP planktonic sample was 0.972, and the mean functional evenness of the ECO plate for the same sample was 0.966. For the GN2 plate for the BP biofilm sample, the functional evenness was 0.993. For the ECO plate for the same sample, the mean functional evenness was 0.988. For the GN2 plate for the AP biofilm sample, the functional evenness was 0.989. For the ECO plate for the same sample, the mean functional evenness was 0.985.

Functional Diversity

No difference was observed in the functional diversity between the BP and AP samples, as shown in Figures 1-6. The functional diversity for the GN2 plate for the BP planktonic at t=0 sample was 4.471, and the mean functional diversity for the ECO plate for the same sample was 3.401. The functional diversity for the GN2 plate for the AP planktonic at t=0 sample was 4.472, and the mean functional diversity for the ECO plate for the same sample was 3.376. For the GN2 plate for the BP planktonic sample, the functional diversity was 4.241. For the ECO plate for the same sample, the mean functional diversity was 3.074. For the GN2 plate for the AP planktonic sample, the functional diversity was 4.353. For the ECO plate for the same sample, the mean functional diversity was 3.254. The functional diversity for the GN2 plate for the BP biofilm sample was 4.425, and the mean functional diversity for the ECO plate for the same sample was 3.361. The functional diversity for the GN2 plate for the AP biofilm sample was 4.404, and the mean functional diversity for the ECO plate for the same sample was 3.293.

Statistical Analysis

No statistical analysis was performed in this study due to the nature of the collection of the samples taken from the creek. Only one sample was taken from each site on the creek. Furthermore, statistical analysis was not performed on the ECO plates since the same water samples were used to inoculate each well of the plate, i.e., each ECO plate was composed of three pseudoreplicates.

DISCUSSION

The initial objective of this study was to compare the rate of biofilm formation between saltwater and freshwater samples. While the data from this type of study would have been informative, the pilot studies involving this idea yielded very few results and realistic comparisons. The main purpose of the pilot studies was to become acquainted with using the BIOLOG microplates and becoming familiar with protocols involving biofilms and planktonic forms of microorganisms. To this effect, the pilot studies were successful in that they provided means of improvement for the wastewater treatment study. Many steps and important concepts that I later noticed were missed during the pilot studies were incorporated into the final study. DNA extraction and analysis, which would add the taxonomic component of biodiversity to the study, was eliminated due to lack of time and experience with temperature gradient gel electrophoresis.

Many microbiological studies utilize molecular techniques to identify species of microorganisms, as previously mentioned. The main objective of this study was to use functional characteristics of microbial communities to describe the community, rather than identify the organisms that compose the community. This was accomplished by comparing the functional richness, functional evenness, and functional diversity of microbial communities upstream and downstream from the Dover Township Wastewater Treatment Facility. Furthermore, samples were taken back to the college laboratory to study biofilm and planktonic growth after a period of incubation. The comparison of the values of the functional characteristics of the different samples provided an idea as to whether or not the wastewater treatment plant was functioning adequately and thus whether or not its released effluent affected the functional abilities of the microbial ecosystem in the Little Conewago Creek.

As evidenced by the functional values obtained for both upstream and downstream samples, there is little variation in the functional characteristics of the microbial communities at both sites. This trend was also observed in the laboratory portion of the study with the biofilms and planktonic growth samples. Since statistical tests could not be used to verify my conclusion that there was no difference in the functional characteristics of the microbial communities upstream and downstream, and I could merely compare the values via graphs, official information about the released effluent was obtained from the wastewater treatment facility. A few values from the facility’s report seemed significant in supporting my conclusion. Specifically, these values were percent removal efficiency of total suspended solids, percent removal efficiency of biological oxygen demand, and final fecal coliform counts. Both types of percentages as reported by the facility showed high efficiency in the removal of suspended solids and the reduction in biological oxygen demand. Furthermore, the fecal coliform counts were relatively low (Table 2). Suspended solids affect the environment by increasing the turbidity of the creek water; if the facility released even a relatively small amount of suspended solids, the microbial community would be affected. The increase in turbidity would lead to more available nutrients for the microbial community and would thus likely decrease functional diversity due to competition for the nutrients. In other words, one or multiple species of microorganisms could dominate the community due to released nutrients that are limiting. The weaker competitors that share the same limiting nutrients would eventually become nutrient deprived and would be removed from the community, and hence the functional diversity would be decreased (Tilman et al., 1999).

The same idea can also be applied to the reduction of biological oxygen demand. Biological oxygen demand (BOD) represents the amount of oxygen that is required by the organisms to survive. Therefore, if the removal efficiency of BOD was low, that would indicate the release of many organisms into the creek. The higher the BOD is, the greater the number of organisms and the higher the demand for oxygen. The Dover Township Wastewater Treatment Facility had a mean removal efficiency of BOD for June and July 2006 of 99.4%, which is close to complete efficiency in the reduction of BOD. The low fecal coliform counts also indicate that very few organisms were released into the creek via the effluent. Added species to the creek would alter the functional characteristics of the microbial community. This difference was not observed.

All functional characteristics for the planktonic at t=0 sample were almost identical. This is perhaps the sample that is most representative of the effect of the facility on the microbial communities of Little Conewago Creek. The reason for this is that the samples were collected and transported to the lab within a few hours and were immediately inoculated into the BIOLOG plates. This was not the case with the planktonic and biofilm growth samples. These samples were placed into a shaker and were incubated for a few weeks. Interspecific competition could have taken place during the incubation time period. This might explain the slight difference observed in the functional richness between the upstream and downstream samples. The functional characteristics values of the upstream and downstream biofilm samples, similar to the planktonic at t= 0 samples, were almost identical. This supports the idea that the planktonic microorganisms might have been affected by the incubation time in the shaker (possibly by interspecific competition for a dwindling nutrient supply), but that the biofilm species were largely not affected.

There are very few ways to compare this study to those found in the primary literature. This is due to the planktonic and biofilm aspect of the study and also the upstream versus downstream aspect of this study. The only relevant way to compare this study with other studies is to compare the Shannon Diversity Index values. Comparisons of Shannon Diversity Index (H) values were made with the primary literature. Although none of the studies in these articles were similar to this study, they did provide an idea as to where the H values for this study fell along the H gradient. Martin (2002) reported H values for the human mouth and gut (3.18 for mouth and 3.50 for gut). He also reported H values for aquatic samples (H values ranged from 0.32 to 1.38). Both sets of H values reported by Martin (2002) were overall lower than the H values obtained from this study. Ibekwe et al. (2001) completed a study on the diversity of soil microbial communities. They reported H values substantially lower (1.23, 1.25, and 1.31) than the H values of this study.

High functional diversity values in this study indicate limitations of the study as a whole. Foremost, this study utilized BIOLOG plates, unlike the molecular techniques frequently utilized in most studies involving microbial communities. Assumptions are made when environmental samples are placed in BIOLOG plates. For instance, a colored well in the plate assumes that only one species was capable of utilizing the substrate in that well. In reality, there could have been one microbial species that utilized the substrates in fifty wells. Therefore, it is a significant assumption to make that there is only one species present in each colored well. To avoid any misconceptions, any taxonomic classification was removed from this study; it is solely a functional characteristics study. The number of species is irrelevant in functional characteristics studies because it is the amount and diversity of substrate consumed that is significant. Whether one species or eighty species utilizes the substrate in the colored well is not relevant to the study. While this is a limitation of the study, it is not a drawback, since functional characteristics of microbial communities are not frequently studied.

There are a few suggestions for improving this study and completing further research. Firstly, more samples should be collected in order to complete statistical analysis. This would allow for a more supported conclusion than simply utilizing the data collected by the treatment facility. Secondly, samples should be taken at different seasons. This would allow for a temporal comparison of the microbial communities upstream and downstream from the wastewater treatment facility. Thirdly, DNA extraction and analysis would provide valuable information about the species composition of the microbial communities. All of these suggestions would provide for a thorough analysis of the microbial communities upstream and downstream from the Dover Township Wastewater Treatment Facility and more fully answer the question as to whether or not the facility has an effect on the microbial communities in Little Conewago Creek.

In conclusion, with the information I obtained, it was determined that the Dover Township Wastewater Treatment Plant did not affect the 1) functional diversity, 2) functional evenness, and 3) functional richness, of the biofilm and planktonic communities in the Little Conewago Creek. This indicates that the facility is functioning adequately and has no impact on the aquatic environment surrounding it. This is a significant finding because functional characteristics are sufficient indicators of change in microbial communities. If a microbial community cannot function downstream as well as upstream, that means that the wastewater treatment facility is affecting the environment. Although the Dover Township Wastewater Treatment Facility must comply with strict state and federal regulations, analysis of the functional characteristics of microbial communities in the creek water provides one more check to see that the environment is not being affected. A malfunctioning plant could lead to the release of harmful microorganisms such as Listeria sp. in France (Paillard et al., 2005) and viruses released via the effluent of a wastewater treatment plant in Wisconsin (Sedmak et al., 2005). Upon completion of this study, it is my hope that more researchers will take the opportunity to study not only the taxonomic aspects of microbial communities but also the ecological aspects.

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Table 1. Maximum average well color development (AWCD) values for Upstream (U) and Downstream (D) from the Dover Township Wastewater Treatment Facility.

Sample Type	Maximum AWCD Plate Type
	GN2	ECO^a
Planktonic at t= 0 U	1.398	1.493
Planktonic at t= 0 D	1.298	1.346
Planktonic U	0.853	0.856
Planktonic D	0.984	0.973
Biofilm U	1.394	1.463
Biofilm D	1.383	1.324

^aECO plate AWCD values are presented as the mean of the triplicate.

Table 2. Monthly (June and July 2006) means of percent efficiency in the removal of total suspended solids (TSS), percent efficiency in reducing biological oxygen demand (BOD), and final fecal coliform count, as reported by the Dover Township Wastewater Treatment Facility.