**Bloom-Forming Cyanobacteria and Other Phytoplankton in Northern New Jersey Freshwater Bodies**

Tin-Chun Chu and Matthew J. Rienzo

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/54481

## **1. Introduction**

## **1.1. Phytoplankton**

Phytoplankton not only plays a vast role in the aquatic food chain, but some groups are es‐ sential in the production of atmospheric oxygen [1]. Phytoplankton include cyanobacteria, algae and many other groups. Some of the most common types of phytoplankton in North American freshwater bodies include species of Bacillariophyceae (diatoms) as well as thou‐ sands of species of cyanobacteria.

Diatoms are a type of phytoplankton that possess several unique contours due to a cell wall composed of silicon dioxide (SiO2) [2, 3]. The diatoms, or Bacillariophyta, have distinct structures and thus are easily identifiable in a water sample. Diatoms can be found in a large range of pH and dissolved oxygen values as well as in ecosystems with a wide concentra‐ tion of solutes, nutrients, contaminants, and across a large range of water temperatures due to their durable cell walls [2].

There are many species of cyanobacteria, commonly found in freshwater lakes and ponds as well as marine environments. Originally called blue-green algae because of their color, cya‐ nobacteria is a phylum of bacteria that uses photosynthesis to obtain energy. Cyanobacteria are prokaryotes and possess the pigment chlorophyll *a,* which is necessary for oxygenic pho‐ tosynthesis and can be exploited during molecular analysis to detect the presence of cyano‐ bacteria in a sample [4]. Cyanobacteria aided in the transformation of the Earth's atmosphere by producing atmospheric oxygen [1]. Freshwater cyanobacteria can be found as unicellular, filamentous, or colonial cells within the environment. Some of the common

© 2013 Chu and Rienzo; licensee InTech. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2013 Chu and Rienzo; licensee InTech. This is a paper distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Attribution License (http://creativecommons.org/licenses/by/3.0), permits use,distribution, in any provided work is properly

cyanobacteria found in freshwater sources in North America include Synechococcus, Ana‐ baena, Oscillatoria, Nostoc, and Anacystis [2].

humans who ingest those shellfish [11]. This neurotoxin, along with the other cyanotoxins

Bloom-Forming Cyanobacteria and Other Phytoplankton in Northern New Jersey Freshwater Bodies

http://dx.doi.org/10.5772/54481

3

The need for treatment of contaminated freshwater across the world is at an all-time high due to the increase in urbanization. In order to prevent harmful algal blooms from forming, it is necessary to understand the balance between cyanobacteria and their viruses, cyano‐ phage. Cyanophage are viruses that infect cyanobacteria in a species specific manner and are just as ubiquitous as cyanobacteria in ecosystems [13]. So, the first step in possibly de‐ tecting and preventing algal bloom formation is to identify the common species at each sus‐ ceptible freshwater body. Microscopy can be used to identify organisms found within environmental samples. Microscopy allows for identification as well as determination of cell density within the sample. Microscopy, unfortunately, is inefficient and time consuming. As a complement to microscopy, polymerase chain reaction (PCR) can be employed. PCR can be used to prime for conserved regions among all phyla of cyanobacteria and other phyto‐ plankton. In an environmental sample, it is important to first perform PCR using universal cyanobacterial primers in order to determine the presence of cyanobacteria. There have been previous studies in which both universal and phyto-specific primers have been determined to be effective in amplifying the 16s rRNA genes in cyanobacteria [14, 15]. After cyanobacte‐ rial presence has been confirmed, species specific primers are then used to effectively deter‐ mine the profile of the freshwater ecosystem being tested. Using the combined microscopic analysis with molecular techniques allows for an effective and efficient method in determin‐ ing cyanobacterial profiles among freshwater ecosystems. Flow cytometry is another meth‐ od that could be used as a complement to microscopy and PCR. Flow cytometry can exploit the fact that phytoplankton contain chlorophyll *a*. A flow cytometer uses a laser and can per‐ form cell differentiation and quantification based on physical characteristics of cells [16]. With the use of these three methods, a successful profile can be generated observing com‐

pH is a water chemistry parameter that is influenced as much by the external environment than it is internal environment of the water body. The pH of water is partially affected by

CO2 concentration is related to photosynthesis [17]. Since most algal cells (cyanobacteria or phytoplankton) take in CO2 during their growth process, the pH of the water body falls within a favorable range for growth of a particular genus or species. Some species, at condi‐ tions in which the pH is more than 8.6, may be limited in CO2 uptake due to inactive ion transport mechanisms. But, it is also known that photosynthesis can occur at a pH of 9-10 in

Dissolved oxygen is another water chemistry parameter that is affected by both internal and external environments. As algal blooms grow, eventually they will exhaust all essential nu‐ trients available in the water body. When this occurs, there is a decrease in biomass pres‐

some species. Reduction of photosynthesis is noted at pH above 10 in all species [1].

2-). Under basic conditions (pH>7.0), the

produced by cyanobacteria, currently has no antidote [12].

**1.4. Detection and treatment of algal blooms**

mon species at particular water bodies.

**1.5. Water chemistry and lake turnover**

the CO2 system components (CO2, H2CO3, and CO3

## **1.2. Algal blooms**

Although the necessity for cyanobacteria and other phytoplankton in the environment is ap‐ parent, overgrowth in urbanized areas due to eutrophication results in formation of algal blooms, causing deleterious effects to both aquatic life as well as anything that may come in contact with the water. Some of the common algal bloom-forming cyanobacteria include those with filamentous and colonial cells [5].

Eutrophic freshwater ecosystems may contain a high average algal biomass include phyto‐ planktons such as cyanobacteria, chlorococcales or dinoflagellates [1, 6]. Eutrophication is the water body's response to added nutrients like phosphate and nitrates. In urbanized areas, the human factor of nutrient introduction to these ecosystems, otherwise known as cultural eutrophication, has recently been considered as one of the most important factors driving the increase in algal bloom frequency as well as intensity [7]. Fertilizer runoff, car washing, and pet wastes being discarded into storm drains are three major modern events causing changes that disturb existing equilibrium between phytoplankton and other aquatic life, accelerating eutrophication [1]. The algal mat that forms at the water's surface can easily prevent sun from penetrating the lower portions of the water. In figure 1 below, an exten‐ sive algal bloom is seen in Branch Brook State Park Lake in Newark, NJ.

## **1.3. Cyanotoxin**

Algal bloom production can be harmful due to decreased sunlight penetration, decreased dissolved oxygen, and also possible toxin release by certain species of cyanobacteria [8]. Many species of cyanobacteria can produce toxins, posing a further risk for aquatic life. There are about 50 species of cyanobacteria that have been shown to produce toxins which are harmful to invertebrates. Microcystis, Anabaena, Oscillatoria, Aphanizomenon, and Nodularia are a few genera which contain species known to produce cyanotoxins. There are three main types of cyanotoxins. Neurotoxins affect the nervous system, hepatotoxins affect the liver, and dermatoxins affect the skin (NALMS) [9]. It could pose a serious threat for both human and animal health if they consume the water from the contaminated sites. Mi‐ crocystins and other cyanotoxins are heat stable, thus cannot be destroyed by boiling. Also, many cyanotoxins are not easily separated from drinking water if they are dissolved in wa‐ ter. Currently, there are several cyanotoxins that are on the US EPA Contaminant Candidate List (CCL2) which are being evaluated for human toxicity (NALMS) [10]. Exposure routes of these cyanotoxins are dependent on the purpose of the contaminated water. If the contami‐ nated water is part of a reservoir, the exposure route may be ingestion due to improperly filtered drinking water. If the contaminated water is used for recreational use, the exposure route may be skin, ingestion, or inhalation. Human exposure may also come from ingestion of animals that were living in the contaminated water. Saxitoxins, known neurotoxins se‐ creted by several cyanobacterial species including *Anabaena circinalis,* are also known as pa‐ ralytic shellfish toxins (PSTs). These neurotoxins infect shellfish, which in turn infect humans who ingest those shellfish [11]. This neurotoxin, along with the other cyanotoxins produced by cyanobacteria, currently has no antidote [12].

## **1.4. Detection and treatment of algal blooms**

cyanobacteria found in freshwater sources in North America include Synechococcus, Ana‐

Although the necessity for cyanobacteria and other phytoplankton in the environment is ap‐ parent, overgrowth in urbanized areas due to eutrophication results in formation of algal blooms, causing deleterious effects to both aquatic life as well as anything that may come in contact with the water. Some of the common algal bloom-forming cyanobacteria include

Eutrophic freshwater ecosystems may contain a high average algal biomass include phyto‐ planktons such as cyanobacteria, chlorococcales or dinoflagellates [1, 6]. Eutrophication is the water body's response to added nutrients like phosphate and nitrates. In urbanized areas, the human factor of nutrient introduction to these ecosystems, otherwise known as cultural eutrophication, has recently been considered as one of the most important factors driving the increase in algal bloom frequency as well as intensity [7]. Fertilizer runoff, car washing, and pet wastes being discarded into storm drains are three major modern events causing changes that disturb existing equilibrium between phytoplankton and other aquatic life, accelerating eutrophication [1]. The algal mat that forms at the water's surface can easily prevent sun from penetrating the lower portions of the water. In figure 1 below, an exten‐

Algal bloom production can be harmful due to decreased sunlight penetration, decreased dissolved oxygen, and also possible toxin release by certain species of cyanobacteria [8]. Many species of cyanobacteria can produce toxins, posing a further risk for aquatic life. There are about 50 species of cyanobacteria that have been shown to produce toxins which are harmful to invertebrates. Microcystis, Anabaena, Oscillatoria, Aphanizomenon, and Nodularia are a few genera which contain species known to produce cyanotoxins. There are three main types of cyanotoxins. Neurotoxins affect the nervous system, hepatotoxins affect the liver, and dermatoxins affect the skin (NALMS) [9]. It could pose a serious threat for both human and animal health if they consume the water from the contaminated sites. Mi‐ crocystins and other cyanotoxins are heat stable, thus cannot be destroyed by boiling. Also, many cyanotoxins are not easily separated from drinking water if they are dissolved in wa‐ ter. Currently, there are several cyanotoxins that are on the US EPA Contaminant Candidate List (CCL2) which are being evaluated for human toxicity (NALMS) [10]. Exposure routes of these cyanotoxins are dependent on the purpose of the contaminated water. If the contami‐ nated water is part of a reservoir, the exposure route may be ingestion due to improperly filtered drinking water. If the contaminated water is used for recreational use, the exposure route may be skin, ingestion, or inhalation. Human exposure may also come from ingestion of animals that were living in the contaminated water. Saxitoxins, known neurotoxins se‐ creted by several cyanobacterial species including *Anabaena circinalis,* are also known as pa‐ ralytic shellfish toxins (PSTs). These neurotoxins infect shellfish, which in turn infect

sive algal bloom is seen in Branch Brook State Park Lake in Newark, NJ.

baena, Oscillatoria, Nostoc, and Anacystis [2].

2 International Perspectives on Water Quality Management and Pollutant Control

those with filamentous and colonial cells [5].

**1.2. Algal blooms**

**1.3. Cyanotoxin**

The need for treatment of contaminated freshwater across the world is at an all-time high due to the increase in urbanization. In order to prevent harmful algal blooms from forming, it is necessary to understand the balance between cyanobacteria and their viruses, cyano‐ phage. Cyanophage are viruses that infect cyanobacteria in a species specific manner and are just as ubiquitous as cyanobacteria in ecosystems [13]. So, the first step in possibly de‐ tecting and preventing algal bloom formation is to identify the common species at each sus‐ ceptible freshwater body. Microscopy can be used to identify organisms found within environmental samples. Microscopy allows for identification as well as determination of cell density within the sample. Microscopy, unfortunately, is inefficient and time consuming. As a complement to microscopy, polymerase chain reaction (PCR) can be employed. PCR can be used to prime for conserved regions among all phyla of cyanobacteria and other phyto‐ plankton. In an environmental sample, it is important to first perform PCR using universal cyanobacterial primers in order to determine the presence of cyanobacteria. There have been previous studies in which both universal and phyto-specific primers have been determined to be effective in amplifying the 16s rRNA genes in cyanobacteria [14, 15]. After cyanobacte‐ rial presence has been confirmed, species specific primers are then used to effectively deter‐ mine the profile of the freshwater ecosystem being tested. Using the combined microscopic analysis with molecular techniques allows for an effective and efficient method in determin‐ ing cyanobacterial profiles among freshwater ecosystems. Flow cytometry is another meth‐ od that could be used as a complement to microscopy and PCR. Flow cytometry can exploit the fact that phytoplankton contain chlorophyll *a*. A flow cytometer uses a laser and can per‐ form cell differentiation and quantification based on physical characteristics of cells [16]. With the use of these three methods, a successful profile can be generated observing com‐ mon species at particular water bodies.

#### **1.5. Water chemistry and lake turnover**

pH is a water chemistry parameter that is influenced as much by the external environment than it is internal environment of the water body. The pH of water is partially affected by the CO2 system components (CO2, H2CO3, and CO3 2-). Under basic conditions (pH>7.0), the CO2 concentration is related to photosynthesis [17]. Since most algal cells (cyanobacteria or phytoplankton) take in CO2 during their growth process, the pH of the water body falls within a favorable range for growth of a particular genus or species. Some species, at condi‐ tions in which the pH is more than 8.6, may be limited in CO2 uptake due to inactive ion transport mechanisms. But, it is also known that photosynthesis can occur at a pH of 9-10 in some species. Reduction of photosynthesis is noted at pH above 10 in all species [1].

Dissolved oxygen is another water chemistry parameter that is affected by both internal and external environments. As algal blooms grow, eventually they will exhaust all essential nu‐ trients available in the water body. When this occurs, there is a decrease in biomass pres‐ ence, which eventually leads to decaying of the algal bloom, producing a scum that decreases the underlying water's oxygen. This depletion of dissolved oxygen can lead to several changes that include hypoxia, in which the dissolved oxygen concentration has dropped below 4 mg/L, or anoxia, in which there is no detectable oxygen levels in the water, leading to death among most finfish and shell fish [18].

called eutrophication [1, 22]. Eutrophication and harmful algal blooms are serious global en‐

Bloom-Forming Cyanobacteria and Other Phytoplankton in Northern New Jersey Freshwater Bodies

http://dx.doi.org/10.5772/54481

5

In the present study, five lakes in Essex County, New Jersey were sampled in the summ‐ er and fall of 2011. Sites were tested for pH, dissolved oxygen, and temperature to ob‐ serve environmental conditions which harbor algal bloom formation. Samples were subsequently tested for the presence of cyanobacteria and phytoplankton using the three methods described above: Microscopic analysis, polymerase chain reaction, and flow cy‐ tometry. Microscopic analysis was performed to identify individual species of cyanobac‐ teria and other phytoplankton among each site at each of the five lakes tested. Once cyanobacteria were confirmed and several species identified, polymerase chain reaction was used with universal primers to confirm the presence of cyanobacteria as well as spe‐ cies specific primers to confirm the presence of particular species. Flow cytometry was utilized to compare seasonal profiles as well as to compare the cyanobacterial cell con‐

*Synechococcus* sp. IU 625 and *Synechococcus elongatus* PCC 7942 strains were used as controls in this study. Five ml of cells were inoculated in 95 ml of sterilized Mauro's Modified Medi‐ um (3M) [23] in 250 ml Erlenmeyer flasks [24]. The medium was adjusted to a pH of 7.9 us‐ ing 1 M NaOH or HCl. The cultures were grown under consistent fluorescent lighting and at a temperature of 27° C. The cultures were grown on an Innova™ 2000 Platform Shaker

Water samples were collected from several water bodies in Essex County, New Jersey in 2011. Permission was granted from the Essex County Department of Parks, Recreation and Cultural Affairs for sample collections. There were two collection periods in this study: May 2011-August 2011 (Summer Collections) and October 2011-November 2011 (Fall Collections) to observe microorganism profile seasonal differences. Three to five samples were collected at each body of water, varying in location and water movement. The five bodies of water observed in this study were Diamond Mill Pond (Millburn, NJ, USA), South Orange Duck Pond (South Orange, NJ, USA), Clarks Pond (Bloomfield, NJ, USA), Verona Lake (Verona, NJ, USA), and Branch Brook State Park (Newark, NJ, USA). Before collection, each site was tested for pH, dissolved oxygen, and temperature using the ExStickII® pH/Dissolved Oxygen (DO)/ Temperature meter (ExTech® Instruments corp., Nashua, NH, USA). Samples were collected from each water body in 1 L sterile collection bottles (Nalgene, Rochester, NY, USA). The one liter samples were brought to the lab (Seton Hall University, South Orange, NJ, USA) to be further processed. Each sample was run through a coarse filter with a pore size of 2.7 µm (Denville Scientific,

(New Brunswick Scientific, Enfield, CT, USA) with continuous pulsating at 100 rpm.

vironmental issues.

centrations among the water samples.

**2. Materials and methods**

**2.1. Cyanobacterial cultures**

**2.2. Environmental samples**

Seasonal pond or lake turnover could have had a profound effect on the abundance and population shift of phytoplankton when comparing the summer and fall collections. Lake turnover is a natural event that results in the mixing of pond and lake waters, caused by the changing temperatures in surface waters during the shifting of seasons [19, 20]. The density and weight of water change when temperature changes in the freshwater lakes. Water is most dense at 4°C; it becomes less dense when the temperature drops below 4°C, thus rising to the top [20]. This is how fish and other aquatic life can survive during the winter at the floor of the water body, with the warmer water surrounding them towards the sediment [19]. This feature, along with the fact that colder water having a higher capacity for dis‐ solved oxygen, can support the fact that phytoplankton numbers are significantly reduced during the colder months. Pond or lake turnover could affect the phytoplankton survival by keeping the colder water at the surface of the water body, where phytoplanktons need to remain for sunlight and photosynthesis. Because colder surface temperatures do not support phytoplankton growth, the phytoplankton cell numbers and algal blooms should be greatly reduced after the fall turnover occurs, and may return after the spring turnover is complete.

### **1.6. Algal biomass dynamics in Northern New Jersey freshwater bodies**

The New Jersey Department of Environmental Protection (NJDEP) has developed the NJDEP Ambient Lake Monitoring Network, in which lakes and ponds around the state of New Jersey are tested for water quality. The Network tests at least one station and one out‐ let of each water body. At these stations, the NJDEP tests for total depth, profile depth, Sec‐ chi, water temperature, dissolved oxygen, pH, conductivity, phosphorous, nitrates, chlorophyll *a*, and turbidity, among other water quality factors.

Essex County, New Jersey, is one of the most densely populated counties in the state of New Jersey, consisting of a population of 783,969 in a land area of 127 square miles [21, 22]. Essex County is a heavily urbanized county located in the New York Metropolitan area. Essex County contains 12 major highways, three of the nation's major transportation centers (Newark Liberty International Airport, Port Newark, Penn Station), and 1,673 miles of pub‐ lic roads [21]. These factors, combined with the massive industrial centers producing goods ranging from chemicals to pharmaceuticals, contribute to the urbanization of the area. De‐ spite being heavily urbanized, Essex County has several parks, freshwater rivers, lakes, and ponds which contribute to the continued efforts in beautification and habitat diversity of the region. These bodies of water, being continually subjected to harmful elements from man‐ made chemicals and excess nutrient pollution, have seen an increase in phytoplankton blooms. Increases in the amounts of nutrients entering lakes and reservoirs in recent deca‐ des in urbanized settings as well as associated changes in the water body's biologics have contributed to the increase in focus on the problem of nutrient enrichment due to pollution, called eutrophication [1, 22]. Eutrophication and harmful algal blooms are serious global en‐ vironmental issues.

In the present study, five lakes in Essex County, New Jersey were sampled in the summ‐ er and fall of 2011. Sites were tested for pH, dissolved oxygen, and temperature to ob‐ serve environmental conditions which harbor algal bloom formation. Samples were subsequently tested for the presence of cyanobacteria and phytoplankton using the three methods described above: Microscopic analysis, polymerase chain reaction, and flow cy‐ tometry. Microscopic analysis was performed to identify individual species of cyanobac‐ teria and other phytoplankton among each site at each of the five lakes tested. Once cyanobacteria were confirmed and several species identified, polymerase chain reaction was used with universal primers to confirm the presence of cyanobacteria as well as spe‐ cies specific primers to confirm the presence of particular species. Flow cytometry was utilized to compare seasonal profiles as well as to compare the cyanobacterial cell con‐ centrations among the water samples.

## **2. Materials and methods**

## **2.1. Cyanobacterial cultures**

ence, which eventually leads to decaying of the algal bloom, producing a scum that decreases the underlying water's oxygen. This depletion of dissolved oxygen can lead to several changes that include hypoxia, in which the dissolved oxygen concentration has dropped below 4 mg/L, or anoxia, in which there is no detectable oxygen levels in the water,

Seasonal pond or lake turnover could have had a profound effect on the abundance and population shift of phytoplankton when comparing the summer and fall collections. Lake turnover is a natural event that results in the mixing of pond and lake waters, caused by the changing temperatures in surface waters during the shifting of seasons [19, 20]. The density and weight of water change when temperature changes in the freshwater lakes. Water is most dense at 4°C; it becomes less dense when the temperature drops below 4°C, thus rising to the top [20]. This is how fish and other aquatic life can survive during the winter at the floor of the water body, with the warmer water surrounding them towards the sediment [19]. This feature, along with the fact that colder water having a higher capacity for dis‐ solved oxygen, can support the fact that phytoplankton numbers are significantly reduced during the colder months. Pond or lake turnover could affect the phytoplankton survival by keeping the colder water at the surface of the water body, where phytoplanktons need to remain for sunlight and photosynthesis. Because colder surface temperatures do not support phytoplankton growth, the phytoplankton cell numbers and algal blooms should be greatly reduced after the fall turnover occurs, and may return after the spring turnover is complete.

**1.6. Algal biomass dynamics in Northern New Jersey freshwater bodies**

chlorophyll *a*, and turbidity, among other water quality factors.

The New Jersey Department of Environmental Protection (NJDEP) has developed the NJDEP Ambient Lake Monitoring Network, in which lakes and ponds around the state of New Jersey are tested for water quality. The Network tests at least one station and one out‐ let of each water body. At these stations, the NJDEP tests for total depth, profile depth, Sec‐ chi, water temperature, dissolved oxygen, pH, conductivity, phosphorous, nitrates,

Essex County, New Jersey, is one of the most densely populated counties in the state of New Jersey, consisting of a population of 783,969 in a land area of 127 square miles [21, 22]. Essex County is a heavily urbanized county located in the New York Metropolitan area. Essex County contains 12 major highways, three of the nation's major transportation centers (Newark Liberty International Airport, Port Newark, Penn Station), and 1,673 miles of pub‐ lic roads [21]. These factors, combined with the massive industrial centers producing goods ranging from chemicals to pharmaceuticals, contribute to the urbanization of the area. De‐ spite being heavily urbanized, Essex County has several parks, freshwater rivers, lakes, and ponds which contribute to the continued efforts in beautification and habitat diversity of the region. These bodies of water, being continually subjected to harmful elements from man‐ made chemicals and excess nutrient pollution, have seen an increase in phytoplankton blooms. Increases in the amounts of nutrients entering lakes and reservoirs in recent deca‐ des in urbanized settings as well as associated changes in the water body's biologics have contributed to the increase in focus on the problem of nutrient enrichment due to pollution,

leading to death among most finfish and shell fish [18].

4 International Perspectives on Water Quality Management and Pollutant Control

*Synechococcus* sp. IU 625 and *Synechococcus elongatus* PCC 7942 strains were used as controls in this study. Five ml of cells were inoculated in 95 ml of sterilized Mauro's Modified Medi‐ um (3M) [23] in 250 ml Erlenmeyer flasks [24]. The medium was adjusted to a pH of 7.9 us‐ ing 1 M NaOH or HCl. The cultures were grown under consistent fluorescent lighting and at a temperature of 27° C. The cultures were grown on an Innova™ 2000 Platform Shaker (New Brunswick Scientific, Enfield, CT, USA) with continuous pulsating at 100 rpm.

## **2.2. Environmental samples**

Water samples were collected from several water bodies in Essex County, New Jersey in 2011. Permission was granted from the Essex County Department of Parks, Recreation and Cultural Affairs for sample collections. There were two collection periods in this study: May 2011-August 2011 (Summer Collections) and October 2011-November 2011 (Fall Collections) to observe microorganism profile seasonal differences. Three to five samples were collected at each body of water, varying in location and water movement. The five bodies of water observed in this study were Diamond Mill Pond (Millburn, NJ, USA), South Orange Duck Pond (South Orange, NJ, USA), Clarks Pond (Bloomfield, NJ, USA), Verona Lake (Verona, NJ, USA), and Branch Brook State Park (Newark, NJ, USA). Before collection, each site was tested for pH, dissolved oxygen, and temperature using the ExStickII® pH/Dissolved Oxygen (DO)/ Temperature meter (ExTech® Instruments corp., Nashua, NH, USA). Samples were collected from each water body in 1 L sterile collection bottles (Nalgene, Rochester, NY, USA). The one liter samples were brought to the lab (Seton Hall University, South Orange, NJ, USA) to be further processed. Each sample was run through a coarse filter with a pore size of 2.7 µm (Denville Scientific, Metuchen, NJ, USA). Filtrate from the coarse filtered sample was run through a fine fil‐ ter with a pore size of 0.45 µm (Nalgene, Rochester, NY, USA). Both coarse and fine fil‐ ter from each sample were placed in a Thelco™ Model 2 incubator for drying at 37°C (Precision Scientific, Chennai, India). Aluminum foil was sterilized by UV light using a Purifier Vertical Clean Bench (Labconco, Kansas City, MO, USA). Dried filters were placed on sterilized aluminum foil and placed in -20°C freezer for further studies.

concentration and purity were determined with NanoDrop ND-1000 Spectrophotometer

Bloom-Forming Cyanobacteria and Other Phytoplankton in Northern New Jersey Freshwater Bodies

http://dx.doi.org/10.5772/54481

7

DNA extracted from the environmental samples, along with the controls (*S*. IU 625, *S. elongatus* PCC 7942) was amplified using general and specific primers to identify the presence of bacteria, cyanobacteria, phytoplankton, and the dominating species. General primers were used to identify bacteria, cyanobacteria, and phytoplankton by utilizing the bacteria-specific 16s rRNA gene primers 27FB and 785R, PSf and PSr, and CPC1f and CPC1r, respectively. Specific primers were used after phytoplankton and cyanobacteria were detected in the samples. PCR was performed using 6.5 µl nuclease-free deionized water (Promega, Madison, WI, USA), 2.5 µl dimethyl sulfoxide (DMSO), 1 µl of primer in the forward orientation, 1 µl of primer in the reverse orientation, 1.5 µl of DNA sam‐ ple, and 12.5 µl GoTaq® Hot Start Green Master Mix (Promega). Thermocycling was per‐ formed in Veriti 96 Well Thermocycler (Applied Biosystems, Carlsbad, CA, USA). The initial denaturation step was at 95°C for 2 minutes, followed by 35 cycles of DNA dena‐ turation at 95°C for 45 seconds, primer annealing at 50-55°C for 45 seconds, and DNA strand extension at 72°C for 45 seconds, and a final extension step at 72°C for 5 minutes. The amplified DNA was visualized on a 1% agarose gel with ethidium bromide incorpo‐ rated using TAE electrophoresis buffer (Fermentas). The gel was visualized using a 2UV

Transilluminator Gel Docit Imaging System (UVP, Upland, CA, USA).

DNA gene conserved among all diatom species [23].

Table 1.

Primers used in this study were either developed using NCBI BLAST (http:// www.ncbi.nlm.nih.gov/BLAST) or by previous studies in this subject field. The sequences of the selected primers, their target organisms and the size of the amplicons are listed in

General primers included Phytoplankton-Specific PSf/PSr which identified the 16s rRNA gene in all phytoplankton [17]. Universal primers Uf/Ur identified the 16s rRNA gene in all bacteria [17]. General primers 27FB and 785R were utilized to identify the 16s rRNA in all bacteria, cyanobacteria, and phytoplankton [21]. CPC1f/CPC1r are also cyanobacteria specif‐ ic primers which identify the β-Subunit of the phycocyanin gene conserved among all cya‐ nobacteria [15]. AN3801f/AN3801r are also cyanobacteria specific primers, identifying the DNA polymerase III gene conserved in *S.* IU625 and *S. elongatus* PCC 7942. Once cyanobac‐ teria and phytoplankton were identified in a sample, specific primers were obtained and uti‐ lized. Primers specific for *Anabaena circinalis* toxin biosynthesis gene cluster were developed using NCBI BLAST searches: ANAf and ANAr. Primers to locate Microcystis were devel‐ oped in accordance with Herry et al. Diatom presence was identified using primers devel‐ oped in accordance with Baldi et al. 528f with 650r identified the small subunit ribosomal

(Thermo Fisher Scientific, Wilmington, DE, USA).

**2.5. Polymerase Chain Reaction (PCR)-based assays**

## **2.3. Genomic DNA extraction**

Genomic DNA of S. IU 625 and S. elongatus PCC 7942 were extracted using Fermentas® Ge‐ nomic DNA Purification Kit (Fermentas, Glen Burnie, MD, USA). Ten ml of cyanobacteria cells (OD750 nm = ~1) were placed in a 15 ml conical tube. The conical tubes were then cen‐ trifuged and cells were resuspended in 200 µl of TE Buffer. 200 µl of cells were then mixed with 400 µl lysis solution in an Eppendorf tube (Enfield, CT, USA) and incubated in an Iso‐ temp125D™ Heat Block (Fisher Scientific, Pittsburgh, PA, USA) at 65°C for 5 minutes. 600 µl of chloroform were added and emulsified by inversion. The sample was then centrifuged at 10,000 rpm for two minutes in a Denville 260D microcentrifuge (Denville Scientific, South Plainfield, NJ, USA). While centrifuging, the precipitation solution was prepared by mixing 720 µl of deionized water with 80 µl of 10X concentrated precipitation solution. After centri‐ fugation, the upper aqueous phase was transferred to a new tube and 800 µl of the precipita‐ tion solution were added. The tube was mixed by several inversions at room temperature for two minutes and centrifuged at 10,000 rpm for two minutes. The supernatant was re‐ moved completely and the DNA pellet was dissolved by adding 100 µl of 1.2 M NaCl solu‐ tion with gentle vortexing. 300 µl of cold ethanol (100%) was added to enable DNA precipitation and kept in -20°C for 10 minutes. The tube was then centrifuged at 10,000 rpm for three minutes. Ethanol was discarded and the pellet was washed with 70% cold ethanol. The DNA was then dissolved in sterile deionized water, and the DNA concentration and purity were determined with NanoDrop ND-1000 Spectrophotometer (Thermo Fisher Scien‐ tific, Wilmington, DE, USA).

#### **2.4. Chelex® DNA extraction of environmental samples**

All environmental samples underwent a modified Chelex® DNA extraction as follows. Each filter (for both coarse and fine filters) was hole punched 3-4 times at various spots on the filter to produce three to four disks; disks were placed into 1.5 ml Eppendorf tubes. Five hundred microliters of deionized water were added to each tube and each tube was vor‐ texed. Tubes were let stand for 10-15 minutes. All tubes were centrifuged for three minutes at 10,000 rpm to concentrate the pellet. Clear supernatant was discarded from each tube, and 200 µl of InstaGene Matrix (Bio-Rad Laboratories, Hercules, CA, USA) were added. Each tube was vortexed for 10 seconds. The tubes were incubated for two hours in a Polyscience© Temperature Controller water bath (Polyscience, Niles, IL, USA) at 56° C, vortexed for 10 seconds, and placed in an Isotemp125D™ Heat Block (Fisher Scientific, Pittsburgh, PA, USA) for 8 minutes at 100°C. The tubes were then centrifuged for 10 minutes at 10,000 rpm, and the supernatant (containing DNA) was transferred to clean Eppendorf tubes. The DNA concentration and purity were determined with NanoDrop ND-1000 Spectrophotometer (Thermo Fisher Scientific, Wilmington, DE, USA).

#### **2.5. Polymerase Chain Reaction (PCR)-based assays**

Metuchen, NJ, USA). Filtrate from the coarse filtered sample was run through a fine fil‐ ter with a pore size of 0.45 µm (Nalgene, Rochester, NY, USA). Both coarse and fine fil‐ ter from each sample were placed in a Thelco™ Model 2 incubator for drying at 37°C (Precision Scientific, Chennai, India). Aluminum foil was sterilized by UV light using a Purifier Vertical Clean Bench (Labconco, Kansas City, MO, USA). Dried filters were

Genomic DNA of S. IU 625 and S. elongatus PCC 7942 were extracted using Fermentas® Ge‐ nomic DNA Purification Kit (Fermentas, Glen Burnie, MD, USA). Ten ml of cyanobacteria cells (OD750 nm = ~1) were placed in a 15 ml conical tube. The conical tubes were then cen‐ trifuged and cells were resuspended in 200 µl of TE Buffer. 200 µl of cells were then mixed with 400 µl lysis solution in an Eppendorf tube (Enfield, CT, USA) and incubated in an Iso‐ temp125D™ Heat Block (Fisher Scientific, Pittsburgh, PA, USA) at 65°C for 5 minutes. 600 µl of chloroform were added and emulsified by inversion. The sample was then centrifuged at 10,000 rpm for two minutes in a Denville 260D microcentrifuge (Denville Scientific, South Plainfield, NJ, USA). While centrifuging, the precipitation solution was prepared by mixing 720 µl of deionized water with 80 µl of 10X concentrated precipitation solution. After centri‐ fugation, the upper aqueous phase was transferred to a new tube and 800 µl of the precipita‐ tion solution were added. The tube was mixed by several inversions at room temperature for two minutes and centrifuged at 10,000 rpm for two minutes. The supernatant was re‐ moved completely and the DNA pellet was dissolved by adding 100 µl of 1.2 M NaCl solu‐ tion with gentle vortexing. 300 µl of cold ethanol (100%) was added to enable DNA precipitation and kept in -20°C for 10 minutes. The tube was then centrifuged at 10,000 rpm for three minutes. Ethanol was discarded and the pellet was washed with 70% cold ethanol. The DNA was then dissolved in sterile deionized water, and the DNA concentration and purity were determined with NanoDrop ND-1000 Spectrophotometer (Thermo Fisher Scien‐

All environmental samples underwent a modified Chelex® DNA extraction as follows. Each filter (for both coarse and fine filters) was hole punched 3-4 times at various spots on the filter to produce three to four disks; disks were placed into 1.5 ml Eppendorf tubes. Five hundred microliters of deionized water were added to each tube and each tube was vor‐ texed. Tubes were let stand for 10-15 minutes. All tubes were centrifuged for three minutes at 10,000 rpm to concentrate the pellet. Clear supernatant was discarded from each tube, and 200 µl of InstaGene Matrix (Bio-Rad Laboratories, Hercules, CA, USA) were added. Each tube was vortexed for 10 seconds. The tubes were incubated for two hours in a Polyscience© Temperature Controller water bath (Polyscience, Niles, IL, USA) at 56° C, vortexed for 10 seconds, and placed in an Isotemp125D™ Heat Block (Fisher Scientific, Pittsburgh, PA, USA) for 8 minutes at 100°C. The tubes were then centrifuged for 10 minutes at 10,000 rpm, and the supernatant (containing DNA) was transferred to clean Eppendorf tubes. The DNA

placed on sterilized aluminum foil and placed in -20°C freezer for further studies.

6 International Perspectives on Water Quality Management and Pollutant Control

**2.3. Genomic DNA extraction**

tific, Wilmington, DE, USA).

**2.4. Chelex® DNA extraction of environmental samples**

DNA extracted from the environmental samples, along with the controls (*S*. IU 625, *S. elongatus* PCC 7942) was amplified using general and specific primers to identify the presence of bacteria, cyanobacteria, phytoplankton, and the dominating species. General primers were used to identify bacteria, cyanobacteria, and phytoplankton by utilizing the bacteria-specific 16s rRNA gene primers 27FB and 785R, PSf and PSr, and CPC1f and CPC1r, respectively. Specific primers were used after phytoplankton and cyanobacteria were detected in the samples. PCR was performed using 6.5 µl nuclease-free deionized water (Promega, Madison, WI, USA), 2.5 µl dimethyl sulfoxide (DMSO), 1 µl of primer in the forward orientation, 1 µl of primer in the reverse orientation, 1.5 µl of DNA sam‐ ple, and 12.5 µl GoTaq® Hot Start Green Master Mix (Promega). Thermocycling was per‐ formed in Veriti 96 Well Thermocycler (Applied Biosystems, Carlsbad, CA, USA). The initial denaturation step was at 95°C for 2 minutes, followed by 35 cycles of DNA dena‐ turation at 95°C for 45 seconds, primer annealing at 50-55°C for 45 seconds, and DNA strand extension at 72°C for 45 seconds, and a final extension step at 72°C for 5 minutes. The amplified DNA was visualized on a 1% agarose gel with ethidium bromide incorpo‐ rated using TAE electrophoresis buffer (Fermentas). The gel was visualized using a 2UV Transilluminator Gel Docit Imaging System (UVP, Upland, CA, USA).

Primers used in this study were either developed using NCBI BLAST (http:// www.ncbi.nlm.nih.gov/BLAST) or by previous studies in this subject field. The sequences of the selected primers, their target organisms and the size of the amplicons are listed in Table 1.

General primers included Phytoplankton-Specific PSf/PSr which identified the 16s rRNA gene in all phytoplankton [17]. Universal primers Uf/Ur identified the 16s rRNA gene in all bacteria [17]. General primers 27FB and 785R were utilized to identify the 16s rRNA in all bacteria, cyanobacteria, and phytoplankton [21]. CPC1f/CPC1r are also cyanobacteria specif‐ ic primers which identify the β-Subunit of the phycocyanin gene conserved among all cya‐ nobacteria [15]. AN3801f/AN3801r are also cyanobacteria specific primers, identifying the DNA polymerase III gene conserved in *S.* IU625 and *S. elongatus* PCC 7942. Once cyanobac‐ teria and phytoplankton were identified in a sample, specific primers were obtained and uti‐ lized. Primers specific for *Anabaena circinalis* toxin biosynthesis gene cluster were developed using NCBI BLAST searches: ANAf and ANAr. Primers to locate Microcystis were devel‐ oped in accordance with Herry et al. Diatom presence was identified using primers devel‐ oped in accordance with Baldi et al. 528f with 650r identified the small subunit ribosomal DNA gene conserved among all diatom species [23].


with a 488 nm laser was collected using both green and red filters. A 575 nm filter was used to locate carothenoid pigments, while a 675 nm filter was used to locate chlorophyll a pig‐ ments, each of which would be indicative of cyanobacterial presence in the water sample. Blanks were created by using Phosphate Buffered Saline (PBS) and deionized water. Tubes were prepared by hole punching both coarse and find filters and placing them in Eppendorf tubes with 100 µl deionized water, as mentioned above. Cyanobacterial presence was stud‐ ied in the coarse filter from Branch Brook Park site C from July 2011 (Algal Bloom present), Branch Brook Sites C & D (Raw, unfiltered samples), and both Branch Brook Sites C & D Coarse and Fine filters. Flow Cytometry results were analyzed using FlowJo 7.6.5 Flow Cy‐

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The pH, dissolved oxygen, and temperature were analyzed at all sites in this study. These parameters aided in the development of a profile for each water body, highlighting which environmental conditions allowed for cyanobacterial and other phytoplankton overgrowth. In Table 1 below, the range of water chemistry levels determined at all sites from summer and fall collection is displayed. The data indicated that the pH range is broader in the fall than in the summer. Dissolved oxygen levels were similar in two seasons and the tempera‐

**Water Chemistry pH Dissolved Oxygen (mg/L) Temperature (°C)** Summer 7.27 – 8.30 1-10 23.5 – 30 Fall 6.60-9.25 2-11 9.1-16.8

**Table 2.** The range of water chemistry parameters for water samples taken at 20 sites during the summer and fall

Polymerase chain reaction based assays were performed using DNA extracted from both the coarse and fine filters at each site among all water bodies involved in this study collected in both the summer and fall to identify the presence of bacteria, cyanobacteria, and phyto‐

PCR-based assays were performed on the coarse and fine filters from each site collected from each water body during the summer and the fall collections. Primer sets used for these PCR-based assays include CPC1f/CPC1r and 27fB/785r for general identification of cyanobacteria and photosynthetic bacteria, respectively. *Synechococcus* sp. IU 625 and *Syn‐ echococcus elongatus* PCC 7942*,* both lab strains, were used as positive controls in this

tometry Analysis Software (Tree Star, Inc., Ashland, OR, USA).

ture differences ranged between 6.7 and 20.9 °C.

**3.2. Polymerase Chain Reaction (PCR)-based assays**

plankton within each body of water.

**3. Results**

**3.1. Water chemistry**

collections is shown.

**Table 1.** Seven primer sets used for PCR-based assays.

## **2.6. Microscopic analyses**

Microscopic images were acquired using a Carl Zeiss AxioLab.A1 phase contrast micro‐ scope coupled with a Carl Zeiss AxioCam MRc camera (Carl Zeiss Microimaging, Jena, Ger‐ many). Coarse filters (2.7 µm pores) were hole punched one time. The fragment was placed into an Eppendorf tube and 100 µl of deionized water were added. The tubes were left at room temperature for 10-20 minutes. 16 µl of the tube's contents were pipetted onto a micro‐ scope slide and viewed at 400X power under the phase filter. Images of diatoms, phyto‐ plankton and cyanobacteria were compared to the atlas "Freshwater Algae of North America: Ecology and Classification" [2]. Species of cyanobacteria, diatoms, and phyto‐ plankton were identified for use in specific PCR analysis and amplification.

#### **2.7. Flow cytometry**

Flow cytometry was performed on several sites collected from Branch Brook State Park (Newark, NJ) in June 2011 as well as December 2011 by a Guava® EasyCyte™ Plus Flow Cy‐ tometry System (Millipore, Billerica, MA, USA). Fluorescence resulting from the excitation with a 488 nm laser was collected using both green and red filters. A 575 nm filter was used to locate carothenoid pigments, while a 675 nm filter was used to locate chlorophyll a pig‐ ments, each of which would be indicative of cyanobacterial presence in the water sample. Blanks were created by using Phosphate Buffered Saline (PBS) and deionized water. Tubes were prepared by hole punching both coarse and find filters and placing them in Eppendorf tubes with 100 µl deionized water, as mentioned above. Cyanobacterial presence was stud‐ ied in the coarse filter from Branch Brook Park site C from July 2011 (Algal Bloom present), Branch Brook Sites C & D (Raw, unfiltered samples), and both Branch Brook Sites C & D Coarse and Fine filters. Flow Cytometry results were analyzed using FlowJo 7.6.5 Flow Cy‐ tometry Analysis Software (Tree Star, Inc., Ashland, OR, USA).

## **3. Results**

**2.6. Microscopic analyses**

CPC1f

ANAf

528f

PSf

Uf

Cyanobacteria

8 International Perspectives on Water Quality Management and Pollutant Control

Photosynthetic plankton

*Anabaena circinalis*

Diatoms

Phytoplankton

Phytoplankton

7942

**Table 1.** Seven primer sets used for PCR-based assays.

AN380f *S.* IU 625 & *S. elongatus* PCC

27fB Bacteria/

CPC1r AARCGNCCTTGVGWATCDGC

785r ACTACCRGGGTATCTAATCC

ANAr GGGATCCTTTTTGCTGCGCC

650r AACACTCTAATTTTTTCACAG

Ur ACGGYTACCTTGTTACGACTT

PSr CCCTAATCTATGGGGWCATCAGGA

AN380r CAGTAGCAGCTCAGGACTC

**2.7. Flow cytometry**

Microscopic images were acquired using a Carl Zeiss AxioLab.A1 phase contrast micro‐ scope coupled with a Carl Zeiss AxioCam MRc camera (Carl Zeiss Microimaging, Jena, Ger‐ many). Coarse filters (2.7 µm pores) were hole punched one time. The fragment was placed into an Eppendorf tube and 100 µl of deionized water were added. The tubes were left at room temperature for 10-20 minutes. 16 µl of the tube's contents were pipetted onto a micro‐ scope slide and viewed at 400X power under the phase filter. Images of diatoms, phyto‐ plankton and cyanobacteria were compared to the atlas "Freshwater Algae of North America: Ecology and Classification" [2]. Species of cyanobacteria, diatoms, and phyto‐

**Primer Target Organism Sequence Amplicon (bp)**

GGCKGCYTGYYTRCGYGACATGGA

AGAGTTTGATCMTGGCTCAG

GATCTAGCCTCACCTGTTGACTT

GCGGTAATTCCAGCTCCAA

GGGATTAGATACCCCWGTAGTCCT

GAGAGTTTGATCCTGGTCAG

CAAATCACTCAGTTTCTGG

389

740

457

200

150

700

180

Flow cytometry was performed on several sites collected from Branch Brook State Park (Newark, NJ) in June 2011 as well as December 2011 by a Guava® EasyCyte™ Plus Flow Cy‐ tometry System (Millipore, Billerica, MA, USA). Fluorescence resulting from the excitation

plankton were identified for use in specific PCR analysis and amplification.

#### **3.1. Water chemistry**

The pH, dissolved oxygen, and temperature were analyzed at all sites in this study. These parameters aided in the development of a profile for each water body, highlighting which environmental conditions allowed for cyanobacterial and other phytoplankton overgrowth. In Table 1 below, the range of water chemistry levels determined at all sites from summer and fall collection is displayed. The data indicated that the pH range is broader in the fall than in the summer. Dissolved oxygen levels were similar in two seasons and the tempera‐ ture differences ranged between 6.7 and 20.9 °C.


**Table 2.** The range of water chemistry parameters for water samples taken at 20 sites during the summer and fall collections is shown.

#### **3.2. Polymerase Chain Reaction (PCR)-based assays**

Polymerase chain reaction based assays were performed using DNA extracted from both the coarse and fine filters at each site among all water bodies involved in this study collected in both the summer and fall to identify the presence of bacteria, cyanobacteria, and phyto‐ plankton within each body of water.

PCR-based assays were performed on the coarse and fine filters from each site collected from each water body during the summer and the fall collections. Primer sets used for these PCR-based assays include CPC1f/CPC1r and 27fB/785r for general identification of cyanobacteria and photosynthetic bacteria, respectively. *Synechococcus* sp. IU 625 and *Syn‐ echococcus elongatus* PCC 7942*,* both lab strains, were used as positive controls in this study. In figures 1-3 below, selected gel electrophoresis results from these PCR-based as‐ says are displayed.

**Water bodies Sites collected Summer positive detection Fall positive detection**

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Brank Brook State Park A, B, C, D A, B, C, D A, B, C, D

Clarks Pond A, B, C, D, E A, B, C, D ND\*

Diamond Mill Pond A, B, C, D A, C ND\*

South Orange Duck Pond A, B, C, D A, B ND\*

Verona Lake A, B, C A A

**Table 3.** Summary of cyanobacterial detection in the summer and in the fall among 5 water bodies. ND indicates non-

Branch Brook State Park A, B, C, D A, B, C, D A, B, C, D

Clarks Pond A, B, C, D, E A, B, C, D ND\*

Diamond Mill Pond A, B, C, D A ND\*

South Orange Duck Pond A, B, C, D A, B ND\*

**Table 4.** Summary of diatom detection in the summer and in the fall among 5 water bodies. ND indicates non-

detectable. The results showed the fall water samples contain fewer diatoms.

the visual algal bloom observed at these sites.

Verona Lake A, B, C ND\* ND\*

In summary, PCR-based assays are able to detect cyanobacteria in 65% (13 out of 20) of all the sites collected for summer samples and 25% (5 out of 20) of all sites collected for fall samples. As for diatoms, 55% (11 out of 20) of the sites indicated presence of diatoms while 20% (4 out of 20) of the sites showed positive results. Bacteria and photosynthetic plankton are detected in all sites. This study suggested Branch Brook State Park had the most cyano‐ bacteria, diatoms and other phytoplankton among 5 water bodies. The result is consistent to

**Water bodies Sites collected Summer positive detection Fall positive detection**

detectable. The results showed the fall water samples contain fewer cyanobacteria.

**Figure 1.** Results from Branch Brook State Park coarse and fine filters are shown using the CPC1f/CPC1r primer set to detect cyanobacteria. It indicates that the presence of cyanobacteria in all 4 sites (A, B, C & D) of Brank Brook State Park.

**Figure 2.** Results from Clarks, Verona and South Orange Duck Pond coarse and fine filters are shown using the 528f/ 650r primer set to detect diatoms. It indicates that the presence of diatoms in all 4 sites (A, B, C & D) of Clarks Pond and 2 sites of South Orange Duck Pond.

**Figure 3.** Results from Diamond Mill and Clarks Pond are shown using the 27fB/785r primer set to detect bacteria and photosynthetic phytoplankton. This is indicative of bacterial and photosynthetic phytoplankton presence among all sites tested.


study. In figures 1-3 below, selected gel electrophoresis results from these PCR-based as‐

10 International Perspectives on Water Quality Management and Pollutant Control

**Figure 1.** Results from Branch Brook State Park coarse and fine filters are shown using the CPC1f/CPC1r primer set to detect cyanobacteria. It indicates that the presence of cyanobacteria in all 4 sites (A, B, C & D) of Brank Brook State

**Figure 2.** Results from Clarks, Verona and South Orange Duck Pond coarse and fine filters are shown using the 528f/ 650r primer set to detect diatoms. It indicates that the presence of diatoms in all 4 sites (A, B, C & D) of Clarks Pond

**Figure 3.** Results from Diamond Mill and Clarks Pond are shown using the 27fB/785r primer set to detect bacteria and photosynthetic phytoplankton. This is indicative of bacterial and photosynthetic phytoplankton presence among all

says are displayed.

Park.

and 2 sites of South Orange Duck Pond.

sites tested.

**Table 3.** Summary of cyanobacterial detection in the summer and in the fall among 5 water bodies. ND indicates nondetectable. The results showed the fall water samples contain fewer cyanobacteria.


**Table 4.** Summary of diatom detection in the summer and in the fall among 5 water bodies. ND indicates nondetectable. The results showed the fall water samples contain fewer diatoms.

In summary, PCR-based assays are able to detect cyanobacteria in 65% (13 out of 20) of all the sites collected for summer samples and 25% (5 out of 20) of all sites collected for fall samples. As for diatoms, 55% (11 out of 20) of the sites indicated presence of diatoms while 20% (4 out of 20) of the sites showed positive results. Bacteria and photosynthetic plankton are detected in all sites. This study suggested Branch Brook State Park had the most cyano‐ bacteria, diatoms and other phytoplankton among 5 water bodies. The result is consistent to the visual algal bloom observed at these sites.

## **3.3. Microscopic observations**

Each coarse and fine filter were hole-punched, re-suspended in De-Ionized water, and ob‐ served under a phase contrast microscope in order to detect, verify, and determine abun‐ dant species among each water body at each site. Representative images of cyanobacteria and diatoms were displayed in figures 4-7.

**Figure 6.** Diatom images identified from Verona Lake in Verona, NJ. (A) Diatom identified from site A. (B) Diatom identified from site B. (C) Diatom identified from site A. (D) Diatom- Fragilaria identified from site A. (E) Diatom identi‐

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**Figure 7.** Images of Diatoms at Branch Brook State Park in Newark, NJ. (A) Diatom - Asterionella identified from site A. (B) Diatom - Asterionella identified from site A. (C) Diatom identified from site A. (D) Diatom - Asterionella identified from site B. (E) Diatom - Asterionella identified from site B. (F) Diatom - Asterionella identified from site B. (400X)

A comparison was constructed in order to study the effectiveness of using both PCR and mi‐ croscopic analysis in identification of the common species of cyanobacteria and other phyto‐

Microscopic observation suggested that most microbes among the water sample collected were bacteria, cyanobacteria and diatoms. Cell density were determined and recorded dur‐ ing microscopic analysis from each site of the freshwater ecosystems in this study. Cell den‐

fied from site A. (F) Diatom- Fragilaria identified from site B. (400X)

plankton in the water bodies in this study.

**Figure 4.** Cyanobacteiral images identified from South Orange Duck Pond. (A) Filamentous cyanobacteria identified from site B. (B) Rod-Shaped cyanobacteria identified from site B. (C) Synechococcus identified from site B. (D) Filamen‐ tous cyanobacteria identified from site C. (E) Filamentous cyanobacteria identified from site C. (F) Synechococcus iden‐ tified from site B. (1000X)

**Figure 5.** Cyanobacteria identified from Clarks Pond in Bloomfield, NJ. (A) Synechococcus identified from site B. (B) Cyanobacteria identified from site B. (C) Synechococcus identified from site C. (D) Synechococcus identified from site D. (1000X)

Bloom-Forming Cyanobacteria and Other Phytoplankton in Northern New Jersey Freshwater Bodies http://dx.doi.org/10.5772/54481 13

**3.3. Microscopic observations**

tified from site B. (1000X)

D. (1000X)

and diatoms were displayed in figures 4-7.

12 International Perspectives on Water Quality Management and Pollutant Control

Each coarse and fine filter were hole-punched, re-suspended in De-Ionized water, and ob‐ served under a phase contrast microscope in order to detect, verify, and determine abun‐ dant species among each water body at each site. Representative images of cyanobacteria

**Figure 4.** Cyanobacteiral images identified from South Orange Duck Pond. (A) Filamentous cyanobacteria identified from site B. (B) Rod-Shaped cyanobacteria identified from site B. (C) Synechococcus identified from site B. (D) Filamen‐ tous cyanobacteria identified from site C. (E) Filamentous cyanobacteria identified from site C. (F) Synechococcus iden‐

**Figure 5.** Cyanobacteria identified from Clarks Pond in Bloomfield, NJ. (A) Synechococcus identified from site B. (B) Cyanobacteria identified from site B. (C) Synechococcus identified from site C. (D) Synechococcus identified from site

**Figure 6.** Diatom images identified from Verona Lake in Verona, NJ. (A) Diatom identified from site A. (B) Diatom identified from site B. (C) Diatom identified from site A. (D) Diatom- Fragilaria identified from site A. (E) Diatom identi‐ fied from site A. (F) Diatom- Fragilaria identified from site B. (400X)

**Figure 7.** Images of Diatoms at Branch Brook State Park in Newark, NJ. (A) Diatom - Asterionella identified from site A. (B) Diatom - Asterionella identified from site A. (C) Diatom identified from site A. (D) Diatom - Asterionella identified from site B. (E) Diatom - Asterionella identified from site B. (F) Diatom - Asterionella identified from site B. (400X)

A comparison was constructed in order to study the effectiveness of using both PCR and mi‐ croscopic analysis in identification of the common species of cyanobacteria and other phyto‐ plankton in the water bodies in this study.

Microscopic observation suggested that most microbes among the water sample collected were bacteria, cyanobacteria and diatoms. Cell density were determined and recorded dur‐ ing microscopic analysis from each site of the freshwater ecosystems in this study. Cell den‐ sity was calculated and was subsequently plotted against water chemistry parameters, including pH, dissolved oxygen, and temperature for each site during the summer and fall collections.

**Water Body Site Diatoms Cyanobacteria Photosynthetic Bacteria**

Bloom-Forming Cyanobacteria and Other Phytoplankton in Northern New Jersey Freshwater Bodies

A PCR & MI PCR & MI PCR & MI B PCR & MI PCR PCR & MI C PCR PCR PCR & MI D PCR PCR PCR & MI

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A MI MI PCR & MI B MI MI PCR & MI C MI MI PCR & MI D MI MI PCR & MI

A MI MI PCR & MI B MI MI PCR & MI C MI MI PCR & MI D MI MI PCR & MI E MI MI PCR & MI

A MI MI PCR & MI B MI MI PCR & MI C MI MI PCR & MI D MI MI PCR & MI

A MI PCR PCR & MI B MI MI PCR & MI C MI MI PCR & MI

**Table 6.** The correlation between microscope findings and PCR findings from fall collections is depicted.

sensitivities of these water bodies to eutrophication [18].

Each water chemistry factor (pH, DO, temperature) was determined at each site of each wa‐ ter body to gain insight on the environmental conditions that harbor eutrophication and/or algal bloom production. A combination of these physical and chemical properties along with biotic features of the natural water bodies work in a symbiotic manner to determine the

For the summer collections, the pH ranged between 7.27 and 9.20 among all 20 sites. The pH and cell density agree with the fact that there is a certain pH range which favors growth. There are several sites in which the pH was found to be between 7 and 8.5, in which both the highest density of cyanobacteria and diatom were found. As the pH drops below 7, howev‐ er, there were no visible cyanobacteria or diatoms. As the pH increases to over 8.5, the cell

Branch Brook Lake

Clarks Pond

Diamond Mill Pond

South Orange Duck Pond

Verona Lake

**4. Discussion**


**Table 5.** The correlation between microscope findings and PCR findings from summer collections is depicted.

Bloom-Forming Cyanobacteria and Other Phytoplankton in Northern New Jersey Freshwater Bodies http://dx.doi.org/10.5772/54481 15


**Table 6.** The correlation between microscope findings and PCR findings from fall collections is depicted.

## **4. Discussion**

sity was calculated and was subsequently plotted against water chemistry parameters, including pH, dissolved oxygen, and temperature for each site during the summer and fall

14 International Perspectives on Water Quality Management and Pollutant Control

**Water Body Site Diatoms Cyanobacteria Photosynthetic Bacteria**

A PCR & MI PCR & MI PCR & MI

B PCR & MI PCR & MI PCR & MI

C PCR & MI PCR & MI PCR & MI

D PCR & MI PCR & MI PCR & MI

A PCR PCR PCR

B PCR PCR PCR

C PCR PCR PCR

D PCR PCR PCR

A PCR & MI PCR & MI PCR & MI

B PCR & MI MI PCR & MI

C PCR & MI PCR & MI PCR & MI

D MI MI PCR

E PCR & MI MI PCR & MI

A PCR PCR & MI PCR & MI

B PCR PCR PCR

C MI MI PCR

D MI MI PCR

A PCR & MI PCR & MI PCR & MI

B PCR & MI MI PCR & MI

C PCR & MI MI PCR & MI

**Table 5.** The correlation between microscope findings and PCR findings from summer collections is depicted.

collections.

Branch Brook Lake

Clarks Pond

Diamond Mill Pond

South Orange Duck Pond

Verona Lake

Each water chemistry factor (pH, DO, temperature) was determined at each site of each wa‐ ter body to gain insight on the environmental conditions that harbor eutrophication and/or algal bloom production. A combination of these physical and chemical properties along with biotic features of the natural water bodies work in a symbiotic manner to determine the sensitivities of these water bodies to eutrophication [18].

For the summer collections, the pH ranged between 7.27 and 9.20 among all 20 sites. The pH and cell density agree with the fact that there is a certain pH range which favors growth. There are several sites in which the pH was found to be between 7 and 8.5, in which both the highest density of cyanobacteria and diatom were found. As the pH drops below 7, howev‐ er, there were no visible cyanobacteria or diatoms. As the pH increases to over 8.5, the cell Phytoplakton in NJ Freshwater Bodies

1

2

3

density and the amount of visible cells in the samples visibly decrease. It is understood that the optimal pH range for cyanobacteria growth is found to be between 7.5 and 10 [26]. Dur‐ ing fall collections, the pH ranged from 6.60 to 9.25, which again reveals an alkaline environ‐ ment except for one site (Branch Brook site C). The sites with pH ranging between 7 and 8.5 appear to contain the highest cell count of both diatom and cyanobacteria. 15 16 Book Title

Bloom-Forming Cyanobacteria and Other Phytoplankton in Northern New Jersey Freshwater Bodies

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17

4 Figure 10. A comparison between diatom cell density from the summer and the fall collections. 5 Water chemistry parameters include pH, dissolved oxygen, and temperature. the graph shows the number of sites with a high diatom cell density (>6.2x10<sup>6</sup> 6 cells/ml) (Red), sites with a medium diatom

**Figure 9.** A comparison between diatom cell density from the summer and the fall collections. Water chemistry pa‐ rameters include pH, dissolved oxygen, and temperature. the graph shows the number of sites with a high diatom cell density (>6.2x106cells/ml) (Red), sites with a medium diatom cell density (3.2x106 – 6.0x106 cells/ml) (Green), and sites

– 6.0x10<sup>6</sup> 7 cells/ml) (Green), and sites with a low diatom cell density

10 Each water chemistry factor (pH, DO, temperature) was determined at each site of each water 11 body to gain insight on the environmental conditions that harbor eutrophication and/or algal bloom 12 production. A combination of these physical and chemical properties along with biotic features of the

Among the ponds and lakes tested in the summer collections, dissolved oxygen levels ranged from 1 mg/L to 10 mg/L, showing a wide range of dissolved oxygen levels. Because it has been previously reported that algal blooms are known to decrease the dissolved oxy‐ gen levels [18, 27], it was important to detect a profile of cells found at each dissolved oxy‐ gen level. In figures 34 and 35 above, the graph shows both more cyanobacteria as well as diatom cell numbers recorded at sites with a lower dissolved oxygen level (<5 mg/L). This

1

2

3

cell density (3.2x106

with a low diatom cell density (<3.1x106cells/ml) (Grey).

(<3.1x106 8 cells/ml) (Grey).

9 **4. Discussion** 

5 collections. Water chemistry parameters include pH, dissolved oxygen, and temperature. the graph shows the number of sites with a high cyanobacteria cell density (>6.2x10<sup>6</sup> 6 cells/ml) (Red), sites with a medium cyanobacteria cell density (3.2x10<sup>6</sup> – 6.0x10<sup>6</sup> 7 cells/ml) (Green), and sites with a low cyanobacteria cell density (<3.1x106 8 cells/ml) (Grey). **Figure 8.** A comparison between cyanobacterial cell density from the summer and the fall collections. Water chemis‐ try parameters include pH, dissolved oxygen, and temperature. the graph shows the number of sites with a high cya‐nobacteria cell density (>6.2x106cells/ml) (Red), sites with a medium cyanobacteria cell density (3.2x106 – 6.0x106 cells/ml) (Green), and sites with a low cyanobacteria cell density (<3.1x106cells/ml) (Grey).

4 Figure 9. A comparison between cyanobacterial cell density from the summer and the fall

Bloom-Forming Cyanobacteria and Other Phytoplankton in Northern New Jersey Freshwater Bodies http://dx.doi.org/10.5772/54481 17

16 Book Title

density and the amount of visible cells in the samples visibly decrease. It is understood that the optimal pH range for cyanobacteria growth is found to be between 7.5 and 10 [26]. Dur‐ ing fall collections, the pH ranged from 6.60 to 9.25, which again reveals an alkaline environ‐ ment except for one site (Branch Brook site C). The sites with pH ranging between 7 and 8.5

4 Figure 9. A comparison between cyanobacterial cell density from the summer and the fall 5 collections. Water chemistry parameters include pH, dissolved oxygen, and temperature. the graph shows the number of sites with a high cyanobacteria cell density (>6.2x10<sup>6</sup> 6 cells/ml) (Red), sites with

**Figure 8.** A comparison between cyanobacterial cell density from the summer and the fall collections. Water chemis‐ try parameters include pH, dissolved oxygen, and temperature. the graph shows the number of sites with a high cya‐nobacteria cell density (>6.2x106cells/ml) (Red), sites with a medium cyanobacteria cell density (3.2x106 – 6.0x106

– 6.0x10<sup>6</sup> 7 cells/ml) (Green), and sites with a low

a medium cyanobacteria cell density (3.2x10<sup>6</sup>

cyanobacteria cell density (<3.1x106 8 cells/ml) (Grey).

cells/ml) (Green), and sites with a low cyanobacteria cell density (<3.1x106cells/ml) (Grey).

15

1

2

3

appear to contain the highest cell count of both diatom and cyanobacteria.

Phytoplakton in NJ Freshwater Bodies

16 International Perspectives on Water Quality Management and Pollutant Control

1

2

3

5 Water chemistry parameters include pH, dissolved oxygen, and temperature. the graph shows the number of sites with a high diatom cell density (>6.2x10<sup>6</sup> 6 cells/ml) (Red), sites with a medium diatom cell density (3.2x106 – 6.0x10<sup>6</sup> 7 cells/ml) (Green), and sites with a low diatom cell density (<3.1x106 8 cells/ml) (Grey). **Figure 9.** A comparison between diatom cell density from the summer and the fall collections. Water chemistry pa‐ rameters include pH, dissolved oxygen, and temperature. the graph shows the number of sites with a high diatom cell density (>6.2x106cells/ml) (Red), sites with a medium diatom cell density (3.2x106 – 6.0x106 cells/ml) (Green), and sites with a low diatom cell density (<3.1x106cells/ml) (Grey).

4 Figure 10. A comparison between diatom cell density from the summer and the fall collections.

9 **4. Discussion**  10 Each water chemistry factor (pH, DO, temperature) was determined at each site of each water 11 body to gain insight on the environmental conditions that harbor eutrophication and/or algal bloom 12 production. A combination of these physical and chemical properties along with biotic features of the Among the ponds and lakes tested in the summer collections, dissolved oxygen levels ranged from 1 mg/L to 10 mg/L, showing a wide range of dissolved oxygen levels. Because it has been previously reported that algal blooms are known to decrease the dissolved oxy‐ gen levels [18, 27], it was important to detect a profile of cells found at each dissolved oxy‐ gen level. In figures 34 and 35 above, the graph shows both more cyanobacteria as well as diatom cell numbers recorded at sites with a lower dissolved oxygen level (<5 mg/L). This result is important because it displays the correlation between cyanobacteria and other phy‐ toplankton growth and the significant depletion of oxygen in the water column. During the fall collections, the dissolved oxygen levels ranged from 2 mg/L to 11 mg/L, representing a slight increase in dissolved oxygen which may be a result of decrease in biomass among the water bodies tested, or as a result of lake turnover. Although there are equal numbers among the four sites with countable cell numbers, the cell density are minute when com‐ pared to the summer collections. The diatom cell densities appear to be higher among lower dissolved oxygen, although there are still some sites in the higher dissolved oxygen range (8-10 mg/L) that contain cyanobacteria.

keeping gene sequences were exploited. Housekeeping genes are constantly present and active within living cells, but they do not have to be activated to be identified. The small-subunit ribosomal RNA (16S rRNA) gene segment is a housekeeping gene found within all phototrophs. Because the 16S rRNA gene segment is always present within the genome of cyanobacteria and bacteria cells, this gene segment served as the target for environmental PCR. The universal primers used in this study (27fB/785r, PSf/Ur, Uf/PSr) utilized the 16s rRNA segment to identify cyanobacteria, bacteria, and phytoplankton have been identified in previous studies [14, 15, 30]. The specific primer used in this study to identify the species *Anabaena circinalis* was developed using NCBI BLAST, while primers for diatoms and Microcystis have been identified in previous studies [31, 32]. In both the summer and fall collections, PCR proved successful in detecting the presence of cyanobacteria, bacteria and phytoplankton by the general "universal" primers identified in previous studies. After detection of these cells within the lakes, a general profile was

Bloom-Forming Cyanobacteria and Other Phytoplankton in Northern New Jersey Freshwater Bodies

http://dx.doi.org/10.5772/54481

19

Branch Brook State Park site C developed a clearly visible algal bloom during the summer collections in July, 2011. During microscopic observation of the coarse filter collected from this site, several species of cyanobacteria were detected. A species of Oscillatoria was detect‐ ed at site C. Oscillatoria is a type of filamentous cyanobacteria. Oscillatoria, along with other filamentous cyanobacteria, has been previously reported to cause algal blooms [34]. Another cyanobacterium, Radiococcus, was identified at Branch Brook State Park site C. Species of Radiococcus have been detected in small numbers in previous studies [35], but it has not been recorded to cause algal blooms. Because Radiococcus was seen at increased numbers at this site, this cyanobacterium may have been another factor in this algal bloom production

Tables 5 and 6 above show the relationship found between microscopy and PCR. Both tables indicate the similarities found between observations made under microscopic ob‐ servation and PCR. These results prove that although PCR and microscopy may be inef‐ ficient on their own, together they are an effective mechanism to develop a phytoplankton profile for freshwater lakes. These findings correlate with previous stud‐ ies, which have found that it is difficult to distinguish similar cell morphologies by mi‐ croscopy [36]. Although it is inefficient, microscopy still remains the preeminent means for morphotyping, cell counting, biovolume, viability assays, and life cycle stage observa‐ tions of cells in a cyanobacterial or phytoplankton bloom [36]. The combination of the microscopic technique and the molecular technique provided for a well detailed and

Flow cytometry provided a rapid analysis for the overall profile of the sites being tested. Flow cytometry was used to detect the overall photoautotroph presence in the sample by ex‐ ploiting the auto fluorescence mechanisms of all cells containing the photosynthetic pigment chlorophyll *a*. Flow cytometry was able to show the amount of phycocyanin-containing cells

wide analysis of the five ecosystems tested in this study.

when compared to total cells in the sample.

constructed for each lake.

and persistence.

The last factor of water chemistry incorporated into this study was temperature of each site. Temperature has not only been shown to affect the cell size of phytoplankton by controlling enzymatic reactions within the cells, but also to regulate the multiplication rate and standing biomass (phytoplankton population) within the water body. Studies have also shown, though, that it may not be temperature that is limiting the fall and win‐ ter growth but the lack of sunlight for photosynthesis [1, 28]. Water temperature seems to dictate the phytoplankton profile. For example, the cyanobacteria Anabaena has been found to be severely affected by lower temperatures while the diatom Asterionella is not as affected by temperature but a decrease of nutrients in the water body. During the summer collections, the temperatures ranged from 23.5 to 30.2°C. The amount of cyano‐ bacteria and diatom cells appears to be at a peak between 25 and 30 °C. This is impor‐ tant because it has been previously reported that the optimal growth rate of 'algae' (phytoplankton cells) is between 20 and 25°C [1]. As temperature increased from the low‐ est recorded (23.5 °C), there was a clear increase in both cyanobacteria and diatom cell number, which seemed to decrease after 30°C. Also, when comparing the phytoplankton distribution between summer collections and fall collections, there is a clear separation in the cell count between the two seasons. This is another finding that corresponds with previous studies that the combination of decreased temperature and decreased light availability for photosynthesis results in decreased phytoplankton growth rate [1, 29]. The temperature of sites during the fall fell between the ranges of 9.1 and 17.9°C. As stated above and seen in figures 9 and 10, the cell count of both diatom and cyanobacteria cells are greatly reduced. The higher cell counts of both cyanobacteria and diatoms in the fall collections appeared to fall in the temperature range of between 13 and 17.9°C. Below 13°C, there were no readily countable cyanobacteria or diatom cells. This could be due to limited cell growth below the optimal growth rate temperature. Between 13 and 17.9°C, there were cyanobacteria and diatoms, although at a clearly decreased level when com‐ pared to the summer collections and observations. Lake or pond turnover, with a combi‐ nation of decreasing temperature and increasing dissolved oxygen levels, may have resulted in a decreased amount of phytoplankton cells between summer and fall collec‐ tions.

Polymerase Chain Reaction (PCR) provided additional verification on the presence of bacteria, cyanobacteria, and algae in the freshwater ecosystems observed. In order to identify phytoplankton, PCR was employed. In order to identify these sequences, house‐ keeping gene sequences were exploited. Housekeeping genes are constantly present and active within living cells, but they do not have to be activated to be identified. The small-subunit ribosomal RNA (16S rRNA) gene segment is a housekeeping gene found within all phototrophs. Because the 16S rRNA gene segment is always present within the genome of cyanobacteria and bacteria cells, this gene segment served as the target for environmental PCR. The universal primers used in this study (27fB/785r, PSf/Ur, Uf/PSr) utilized the 16s rRNA segment to identify cyanobacteria, bacteria, and phytoplankton have been identified in previous studies [14, 15, 30]. The specific primer used in this study to identify the species *Anabaena circinalis* was developed using NCBI BLAST, while primers for diatoms and Microcystis have been identified in previous studies [31, 32]. In both the summer and fall collections, PCR proved successful in detecting the presence of cyanobacteria, bacteria and phytoplankton by the general "universal" primers identified in previous studies. After detection of these cells within the lakes, a general profile was constructed for each lake.

result is important because it displays the correlation between cyanobacteria and other phy‐ toplankton growth and the significant depletion of oxygen in the water column. During the fall collections, the dissolved oxygen levels ranged from 2 mg/L to 11 mg/L, representing a slight increase in dissolved oxygen which may be a result of decrease in biomass among the water bodies tested, or as a result of lake turnover. Although there are equal numbers among the four sites with countable cell numbers, the cell density are minute when com‐ pared to the summer collections. The diatom cell densities appear to be higher among lower dissolved oxygen, although there are still some sites in the higher dissolved oxygen range

The last factor of water chemistry incorporated into this study was temperature of each site. Temperature has not only been shown to affect the cell size of phytoplankton by controlling enzymatic reactions within the cells, but also to regulate the multiplication rate and standing biomass (phytoplankton population) within the water body. Studies have also shown, though, that it may not be temperature that is limiting the fall and win‐ ter growth but the lack of sunlight for photosynthesis [1, 28]. Water temperature seems to dictate the phytoplankton profile. For example, the cyanobacteria Anabaena has been found to be severely affected by lower temperatures while the diatom Asterionella is not as affected by temperature but a decrease of nutrients in the water body. During the summer collections, the temperatures ranged from 23.5 to 30.2°C. The amount of cyano‐ bacteria and diatom cells appears to be at a peak between 25 and 30 °C. This is impor‐ tant because it has been previously reported that the optimal growth rate of 'algae' (phytoplankton cells) is between 20 and 25°C [1]. As temperature increased from the low‐ est recorded (23.5 °C), there was a clear increase in both cyanobacteria and diatom cell number, which seemed to decrease after 30°C. Also, when comparing the phytoplankton distribution between summer collections and fall collections, there is a clear separation in the cell count between the two seasons. This is another finding that corresponds with previous studies that the combination of decreased temperature and decreased light availability for photosynthesis results in decreased phytoplankton growth rate [1, 29]. The temperature of sites during the fall fell between the ranges of 9.1 and 17.9°C. As stated above and seen in figures 9 and 10, the cell count of both diatom and cyanobacteria cells are greatly reduced. The higher cell counts of both cyanobacteria and diatoms in the fall collections appeared to fall in the temperature range of between 13 and 17.9°C. Below 13°C, there were no readily countable cyanobacteria or diatom cells. This could be due to limited cell growth below the optimal growth rate temperature. Between 13 and 17.9°C, there were cyanobacteria and diatoms, although at a clearly decreased level when com‐ pared to the summer collections and observations. Lake or pond turnover, with a combi‐ nation of decreasing temperature and increasing dissolved oxygen levels, may have resulted in a decreased amount of phytoplankton cells between summer and fall collec‐

Polymerase Chain Reaction (PCR) provided additional verification on the presence of bacteria, cyanobacteria, and algae in the freshwater ecosystems observed. In order to identify phytoplankton, PCR was employed. In order to identify these sequences, house‐

(8-10 mg/L) that contain cyanobacteria.

18 International Perspectives on Water Quality Management and Pollutant Control

tions.

Branch Brook State Park site C developed a clearly visible algal bloom during the summer collections in July, 2011. During microscopic observation of the coarse filter collected from this site, several species of cyanobacteria were detected. A species of Oscillatoria was detect‐ ed at site C. Oscillatoria is a type of filamentous cyanobacteria. Oscillatoria, along with other filamentous cyanobacteria, has been previously reported to cause algal blooms [34]. Another cyanobacterium, Radiococcus, was identified at Branch Brook State Park site C. Species of Radiococcus have been detected in small numbers in previous studies [35], but it has not been recorded to cause algal blooms. Because Radiococcus was seen at increased numbers at this site, this cyanobacterium may have been another factor in this algal bloom production and persistence.

Tables 5 and 6 above show the relationship found between microscopy and PCR. Both tables indicate the similarities found between observations made under microscopic ob‐ servation and PCR. These results prove that although PCR and microscopy may be inef‐ ficient on their own, together they are an effective mechanism to develop a phytoplankton profile for freshwater lakes. These findings correlate with previous stud‐ ies, which have found that it is difficult to distinguish similar cell morphologies by mi‐ croscopy [36]. Although it is inefficient, microscopy still remains the preeminent means for morphotyping, cell counting, biovolume, viability assays, and life cycle stage observa‐ tions of cells in a cyanobacterial or phytoplankton bloom [36]. The combination of the microscopic technique and the molecular technique provided for a well detailed and wide analysis of the five ecosystems tested in this study.

Flow cytometry provided a rapid analysis for the overall profile of the sites being tested. Flow cytometry was used to detect the overall photoautotroph presence in the sample by ex‐ ploiting the auto fluorescence mechanisms of all cells containing the photosynthetic pigment chlorophyll *a*. Flow cytometry was able to show the amount of phycocyanin-containing cells when compared to total cells in the sample.

## **5. Conclusion**

Modified Chelex® DNA extraction is an efficient way to isolate DNA from environmental water samples. When it comes to species identification, PCR-based assays appeared to be more rapid and sensitive than microscopic observation on cyanobacteria and other phy‐ toplankton. Microscopic observation aided in identification of the common genera, while PCR was allowed for identification up to the species level. In addition, flow cytometry was able to provide insight on the phytoplankton profile when used in conjunction with the other two methods. The combination of the three methods can be employed to pro‐ vide a thorough analysis of the water bodies observed in the study Microscopic observa‐ tion also allowed for cell density determination, which was important in seasonal comparisons. Water chemistry parameters (pH, DO, and temperature) were crucial to be incorporated in order to establish the correlation between phytoplankton profile and en‐ vironmental conditions.

**References**

Press, 1984.

5-27.

294-9.

p. 1-3.

[1] C.S. Reynolds, The Ecology of Freshwater Phytoplankton, Cambridge University

Bloom-Forming Cyanobacteria and Other Phytoplankton in Northern New Jersey Freshwater Bodies

http://dx.doi.org/10.5772/54481

21

[2] J.D.Wehr, R.G. Sheath, P. Kociolek, and J.H. Thorp, Freshwater Algae of North America: Ecology and Classification (Aquatic Ecology), Elsevier Science, 2002.

[3] M.J. Leng, and P.A. Barker, "A review of the oxygen isotope composition of lacus‐ trine daitom silica for paleoclimate reconstruction," Earth-Science Reviews, 2005, p.

[4] B.J.F. Biggs, and C. Kilroy, Stream Periphyton Monitoring Manual, The Crown (act‐

[5] A. Zingone, and H.O. Enevoldsen, "The diversity of harmful algal blooms: a chal‐ lenge for science and management," Ocean & Coastal Management, 2000, p. 725-48.

[6] S.B. Watson, E. McCauley, and J.A. Downing, "Patterns in phytoplankton taxonomic composition across temperate lakes of differing nutrient status," ASLO: Limnology

[7] C.R. Anderson, M.R.P. Sapiano, M.B.K. Prasad, W. Long, P.J. Tango, C.W. Brown, and R. Murtugudde, "Predicting potentially toxigenic Pseudo-nitzschia blooms in

[8] T.C. Chu, S.R. Murray, S.F. Hsu, Q. Vega, and L.H. Lee, "Temperature-induced acti‐ vation of freshwater Cyanophage AS-1 prophage," Acta Histochemica, May 2011, p.

[9] G.A. Codd, L.F. Morrison, and J.S. Metcalf, "Cyanobacterial toxins: risk management for health protection," Toxicology and Applied Pharmacology, 2005, p. 264-72.

[11] J. Al-Tebrineh, T.K. Mihali, F. Pomati, and B.A. Neilan, "Detection of saxitoxin-pro‐ ducing cyanobacteria and Anabaena circinalis in environmental water blooms by quantitative PCR," Applied and Environmental Microbiology, 2010, p. 7836-42.

[12] CDC, "Facts about Cyanobacteria & Cyanobacterial Harmful Algal Blooms," 2009.

[13] L.H. Lee, D. Lui, P.J. Platner, S.F. Hsu, T.C. Chu, J.J. Gaynor, Q.C. Vega, and B.K. Lustigman, "Induction of temperate cyanophage AS-1 by heavy metal – copper,"

[14] U. Nübel, F. Garcia-Pichel, and G. Muyzer, "PCR primers to amplify 16S rRNA genes from cyanobacteria," Applied and Environmental Microbiology, 1997, p. 3327-32. [15] J.W. Stiller, and A. McClanahan, "Phyto-specific 16S rDNA PCR primers for recover‐ ing algal and plant sequences from mixed samples," Molecular Ecology Notes, 2005,

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## **6. Future studies**

In order to obtain a larger, more complete profile of phytoplankton growth in New Jersey freshwater ecosystems, flow cytometry must be employed at a larger scale. In the current study, it has been established that flow cytometry is successful in the detection of cells con‐ taining chlorophyll *a.* In order to develop a rapid yet large profile for many freshwater eco‐ systems, fluorescent probes must be employed. As used in PCR, the 16s rRNA segments found in all phototrophs can be detected and probed with fluorescence. With these probes, the flow cytometer can successfully identify different species of cyanobacteria and phyto‐ plankton while analyzing mixed microbial populations [25].

As mentioned above, phosphates and nitrates are two of the most important elements re‐ sulting from pollution that drive the eutrophication in freshwater ecosystems. Also, as the biomass of cyanobacteria and phytoplankton increase, the amount of chlorophyll *a* will in‐ crease. These factors are important in monitoring and identifying ecosystems that are threat‐ ening for algal bloom formation. In order to gain a complete profile for each freshwater ecosystem, these parameters must be incorporated into the future study.

## **Author details**

Tin-Chun Chu and Matthew J. Rienzo

Department of Biological Sciences, Seton Hall University, South Orange, NJ, USA

## **References**

**5. Conclusion**

vironmental conditions.

**6. Future studies**

**Author details**

Tin-Chun Chu and Matthew J. Rienzo

Modified Chelex® DNA extraction is an efficient way to isolate DNA from environmental water samples. When it comes to species identification, PCR-based assays appeared to be more rapid and sensitive than microscopic observation on cyanobacteria and other phy‐ toplankton. Microscopic observation aided in identification of the common genera, while PCR was allowed for identification up to the species level. In addition, flow cytometry was able to provide insight on the phytoplankton profile when used in conjunction with the other two methods. The combination of the three methods can be employed to pro‐ vide a thorough analysis of the water bodies observed in the study Microscopic observa‐ tion also allowed for cell density determination, which was important in seasonal comparisons. Water chemistry parameters (pH, DO, and temperature) were crucial to be incorporated in order to establish the correlation between phytoplankton profile and en‐

In order to obtain a larger, more complete profile of phytoplankton growth in New Jersey freshwater ecosystems, flow cytometry must be employed at a larger scale. In the current study, it has been established that flow cytometry is successful in the detection of cells con‐ taining chlorophyll *a.* In order to develop a rapid yet large profile for many freshwater eco‐ systems, fluorescent probes must be employed. As used in PCR, the 16s rRNA segments found in all phototrophs can be detected and probed with fluorescence. With these probes, the flow cytometer can successfully identify different species of cyanobacteria and phyto‐

As mentioned above, phosphates and nitrates are two of the most important elements re‐ sulting from pollution that drive the eutrophication in freshwater ecosystems. Also, as the biomass of cyanobacteria and phytoplankton increase, the amount of chlorophyll *a* will in‐ crease. These factors are important in monitoring and identifying ecosystems that are threat‐ ening for algal bloom formation. In order to gain a complete profile for each freshwater

plankton while analyzing mixed microbial populations [25].

20 International Perspectives on Water Quality Management and Pollutant Control

ecosystem, these parameters must be incorporated into the future study.

Department of Biological Sciences, Seton Hall University, South Orange, NJ, USA


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Bloom-Forming Cyanobacteria and Other Phytoplankton in Northern New Jersey Freshwater Bodies

http://dx.doi.org/10.5772/54481

23

[31] F. Baldi, C. Facca, D. Marchetto, T.N. Nguyen, and R. Spurio, "Diatom quantification and their distribution with salinity brines in costal sediments of Terra Nova Bay

[32] E. Herry S., A. Fathalli, A.J. Rejeb, and N. Bouaïcha, "Seasonal occurrence and toxici‐ ty of Microcystis spp. and Oscillatoria tenuis in the Lebna Dam, Tunisia," Water Re‐

[33] D.M. Anderson, P.M. Glibert, and J.M. Burkholder, "Harmful Algal Blooms and Eu‐ trophication: Nutrient Sources, Composition, and Consequences," Estuaries, 2002, p.

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[36] K.A. Kormas, S. Gkelis, E. Vardaka, and M. Moustaka-Gouni, "Morphological and molecular analysis of bloom-forming Cyanobacteria in two eutrophic, shallow Medi‐ terranean lakes," Limnologica-Ecology and Management of Inland Waters, 2011, p.

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[17] F. Moatar, F. Fessant, and A. Poirel, "pH modelling by neural networks. Application of control and validation data series in the Middle Loire river," Ecological Modelling,

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[24] T.C. Chu, S.R. Murray, J. Todd, W. Perez, J.R. Yarborough, C. Okafor, and L.H. Lee, "Adaption of Synechococcus sp. IU 625 to growth in the presence of mercuric chlor‐

[25] R.I. Amann, B.J. Binder, R.J. Olson, S.W. Chisholm, R. Devereux, and D.A. Stahl, "Combination of 16s rRNA-targeted oligonucleotide probes with flow cytometry for analyzing mixed microbial populations," Applied and Environmental Microbiology,

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76-113.


**Chapter 2**

**Endocrine Disruptors in Water Sources:**

S. L. Gelover Santiago, C. L. Hernández Martínez and

Water is fundamental for human health and well-being as well as for stimulating diverse socioeconomic activities. Paradoxically, these very activities have contributed to the alteration and deterioration of water supply sources from a microbiological, physical and chemical standpoint, causing sanitary risks for the population. For example: since the end of the 19th century, the role of drinking water in exposing populations to pathogens, and improvements in its quality in order to prevent diarrheic illnesses, has been widely analyzed, debated and documented [1,2]; in the 20thcentury, epidemiological evidence was found of cutaneous lesions [3]and various types of cancer related to hydroarsenicism [4], as well as dental and skeletal

In recent decades the problem of these possible public health risks from so-called emergent contaminants (ECs) has been factored into the problem that includes a wide range of com‐ pounds whose environmental presence and impact have been proven with the advent of new sensitive and reliable quantitative analytical tools [6]: ECs are bioactive substances synthesized and used for the household, agriculture, livestock, industry, personal care products and hygiene (PCPs), and human and veterinary medicine, including byproducts of production and degradation [7].However, beyond the concentrations and environmental persistence of ECs,

> © 2013 Muñoz et al.; licensee InTech. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use,

© 2013 Muñoz et al.; licensee InTech. This is a paper distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

distribution, and reproduction in any medium, provided the original work is properly cited.

**Water Through Nanofiltration**

J. E. Cortés Muñoz, C. G. Calderón Mólgora, A. Martín Domínguez, E. E. Espino de la O,

Additional information is available at the end of the chapter

fluorosis related to fluoride in drinking water [5].

G. E. Moeller Chávez

**1. Introduction**

http://dx.doi.org/10.5772/54482

**Human Health Risks and EDs Removal from**
