Prepared in Cooperation with the U.S. Fish and Wildlife Service

Monitoring of Wild Fish Health at Selected Sites in the 

Great Lakes Basin: Methods and Preliminary Results

Open-File Report 2014–1027

U.S. Department of the Interior

U.S. Geological Survey
Cover: Left photograph Dr. Luke Iwanowicz and graduate students Cassidy Hahn and Ryan Braham sampling fish.

Right photograph Dr. Vicki Blazer and graduate students Cassidy Hahn and Ryan Braham sampling fish.
Monitoring of Wild Fish Health at Selected Sites in the 

Great Lakes Basin: Methods and Preliminary Results

By Vicki S. Blazer, Patricia M. Mazik, Luke R. Iwanowicz, Ryan Braham, Cassidy Hahn, Heather L. Walsh, and 

Adam Sperry

Prepared in Cooperation with the U.S. Fish and Wildlife Service

Open-File Report 2014–1027

U.S. Department of the Interior

U.S. Geological Survey
U.S. Department of the Interior

SALLY JEWELL, Secretary

U.S. Geological Survey

Suzette M. Kimball, Acting Director

U.S. Geological Survey, Reston, Virginia: 2014 

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Suggested citation:

Blazer, V.S., Mazik, P.M., Iwanowicz, L.R., Braham, Ryan, Hahn, Cassidy, Walsh, H.L., and Sperry, Adam, 2014, 

Monitoring of Wild Fish Health at Selected Sites in the Great Lakes Basin—Methods and Preliminary Results: U.S. 

Geological Survey Open-File Report 2014-1027 p. 31, http://dx.doi.org/10.3133/ofr20141027. 

ISSN 2331-1258 (online)
iii

Acknowledgments

This project was funded by the Great Lakes Restoration Initiative through a grant to Region 3 

Fish and Wildlife Service Contaminants program and by the U.S. Geological Survey’s Environments 

(Fisheries) and Cooperative Fish and Wildlife Research Unit programs. The authors thank the U.S. Fish 

and Wildlife Service personnel for field logistic arrangements and fish collections, especially Jo Ann 

Banda, Steven Choy, Daniel Gefell, Zachary Jorgensen, Jeremy Moore and Sara Warner. We thank 

U.S. Geological Survey histology technicians Darlene Bowing and Kathy Spring for their assistance. 
iv

Contents

Abstract ......................................................................................................................................................................... 1

Introduction.................................................................................................................................................................... 1

Methods......................................................................................................................................................................... 4

Sites Selection ........................................................................................................................................................... 4

Field Methods ............................................................................................................................................................ 5

Laboratory Analysis.................................................................................................................................................... 6

Age Analysis........................................................................................................................................................... 6

Reproductive Health Indicators .............................................................................................................................. 6

Genotoxic/Mutagenic/Carcinogenic Indicators ....................................................................................................... 8

Molecular Endpoints............................................................................................................................................... 8

In vitro Screening Assays of Water Samples........................................................................................................ 10

Results and Discussion ............................................................................................................................................... 10

Fish Collection ......................................................................................................................................................... 10

Morphometric, Condition Factor and hepotosomatic Index ...................................................................................... 12

Smallmouth and Largemouth Bass ...................................................................................................................... 12

White Sucker........................................................................................................................................................ 12

Brown Bullhead .................................................................................................................................................... 13

Gross and Histological Abnormalities....................................................................................................................... 13

Smallmouth and Largemouth Bass ...................................................................................................................... 13

White Sucker........................................................................................................................................................ 15

Brown Bullhead .................................................................................................................................................... 18

Genotoxic/Mutagenic/Carcinogenic Endpoints......................................................................................................... 20

Reproductive Endpoints........................................................................................................................................... 20

Molecular Endpoints................................................................................................................................................. 21

Gene Expression Analysis.................................................................................................................................... 21

Water Analysis ..................................................................................................................................................... 25

Summary and Conclusions.......................................................................................................................................... 25

References Cited......................................................................................................................................................... 26

Figures

1. Sampling sites for fish collections conducted in the Great Lakes Basin during 2010-2011............................ 5

2. Grossly visible lesions observed on smallmouth and largemouth bass ....................................................... 14

3. Microscopic pathology of skin lesions observed on bass............................................................................. 15

4. Grossly visible lesions observed on white sucker........................................................................................ 16

5. Microscopic pathology of skin lesions observed on white sucker ................................................................ 18

6. Grossly visible lesions observed on brown bullhead.................................................................................... 19

Tables

1. Sampling site Areas of Concern and locations in the Great Lakes Basin .................................................... 10

2. Summary of Fishes Collected for Fish Health Assessments in selected Areas of Concern in the 

Great Lakes Basin, fall 2010 and spring 2011 ............................................................................................. 11

3. Morphometric parameters of largemouth and smallmouth bass collected in the Great Lakes Basin, 

2010-20111 ................................................................................................................................................. 12
v 

4. Morphometric parameters of white sucker collected in the Great Lakes Basin, 2010-2011......................... 13

5. Morphometric parameters of brown bullhead collected in the Great Lakes Basin, 2010-2011 .................... 13

6. Percentage of largemouth and smallmouth bass with visible eye or skin lesions, Great Lakes Basin, 

2010-2011 ................................................................................................................................................... 14

7. Percentage of white sucker with visible eye or skin lesions, Great Lakes Basin, 2010-2011....................... 17

8. Percentage of brown bullhead with visible eye, barbel or skin lesions, Great Lakes Basin, 2010-2011 ...... 20

9. Genes chosen for NanoString analysis of individual liver samples .............................................................. 21

10. Regulation in the top 25 target genes between female and male smallmouth bass collected in the 

Great Lakes Basin in the fall 2010............................................................................................................... 22

11. Regulation in the top 25 target genes between female and male smallmouth bass collected in the 

Great Lakes Basin in spring 2011................................................................................................................ 23

12. Regulation of the top 25 target genes between seasons, fall 2010 and spring 2011, in female 

smallmouth bass collected in the Great Lakes Basin................................................................................... 24
vi

Conversion Factors

Inch/Pound to SI

Multiply By To obtain

Length

inch (in.) 2.54 centimeter (cm)

inch (in.) 25.4 millimeter (mm)

foot (ft) 0.3048 meter (m)

mile (mi) 1.609 kilometer (km)

yard (yd) 0.9144 meter (m)

Volume

ounce, fluid (fl. oz) 0.02957 liter (L) 

pint (pt) 0.4732 liter (L) 

quart (qt) 0.9464 liter (L) 

gallon (gal) 3.785 liter (L) 

Mass

ounce, avoirdupois (oz) 28.35 gram (g) 

pound, avoirdupois (lb) 0.4536 kilogram (kg) 

SI to Inch/Pound

Multiply By To obtain

Length

centimeter (cm) 0.3937 inch (in.)

millimeter (mm) 0.03937 inch (in.)

meter (m) 3.281 foot (ft) 

kilometer (km) 0.6214 mile (mi)

meter (m) 1.094 yard (yd) 

Volume

liter (L) 33.82 ounce, fluid (fl. oz)

liter (L) 2.113 pint (pt)

liter (L) 1.057 quart (qt)

liter (L) 0.2642 gallon (gal)

Mass

gram (g) 0.03527 ounce, avoirdupois (oz)

kilogram (kg) 2.205 pound avoirdupois (lb)

Temperature in degrees Celsius (°C) may be converted to degrees Fahrenheit (°F) as °F=(1.8×°C)+32.

Temperature in degrees Fahrenheit (°F) may be converted to degrees Celsius (°C) as °C=(°F–32)/1.8.
1 

Monitoring of Wild Fish Health at Selected Sites in the 

Great Lakes Basin: Methods and Preliminary Results

By Vicki S. Blazer1, Patricia M. Mazik1, Luke R. Iwanowicz1, Ryan Braham2, Cassidy Hahn2, Heather L. Walsh2, 

and Adam Sperry2

Abstract

During fall 2010 and spring 2011, a total of 119 brown bullhead (Ameiurus nebulosus), 136 

white sucker (Catostomus commersoni), 73 smallmouth bass (Micropterus dolomieu), and 59 

largemouth bass (M. salmoides) were collected from seven Great Lakes Basin Areas of Concern and one 

Reference Site. Comprehensive fish health assessments were conducted in order to document potential 

adverse effects from exposure to complex chemical mixtures. Fish were necropsied on site, blood 

samples obtained, pieces of liver, spleen, kidney, gill and any abnormalities placed in fixative for 

histopathology. Liver samples were saved for gene expression analysis and otoliths were removed for 

aging. A suite of fish health indicators was developed and implemented for site comparisons and to 

document seasonal effects and species differences in response to environmental conditions. Organism 

level (grossly visible lesions, condition factor), tissue level (microscopic pathology, organosomatic 

indices, micronuclei, and other nuclear abnormalities), plasma factors (reproductive steroid hormones, 

vitellogenin), and molecular (gene expression) indicators were included. This report describes the 

methods and preliminary results. 

Introduction 

The Great Lakes Restoration Initiative (GLRI) began in 2010, specifically targeting certain 

priorities, including cleaning up toxic substances, restoring wetlands and other habitats, promoting 

nearshore health by protecting watersheds from contaminants in run-off, and evaluating and monitoring 

progress at Areas of Concern (AOCs). AOCs are defined by the United States-Canada Great Lakes 

Water Quality Agreement, Annex 2 of the 1987 Protocol as “geographic areas that fail to meet the 

general or specific objectives of the agreement where such failure has caused or is likely to cause 

impairment of beneficial use of the area’s ability to support aquatic life.” Fourteen beneficial use 

impairments (BUIs) were defined by the International Joint Commission (IJC). These include a number 

of impairments in fish and wildlife populations such as fish tumors or other deformities, degraded fish 

and wildlife populations, loss of fish and wildlife habitat, and restrictions on fish and wildlife 

consumption (IJC 1991). Initially, the focus of AOCs was on legacy contaminants such as metals, 

polyaromatic hydrocarbons and polycyclic aromatic biphenyls. Recent studies recognized that 

chemicals of emerging concern (CEC) may contribute to impaired fish and wildlife health in the Great 

Lakes (IJC, 2009, Klečka et al., 2010; Klaper and Welch, 2011). These CEC include organic substances 

 

1 U.S. Geological Survey.

2 West Virginia University.
2 

such as biogenic hormones (human and animal), brominated flame retardants, pharmaceuticals, personal 

care products, plasticizers, current-use pesticides, and detergents, from human wastewater, agricultural 

and industrial sources. 

There has been a substantive increase in the detection of CEC in the aquatic environment, 

including the Great Lakes watershed (Metcalfe et al., 2003; Li et al., 2010; Blair et al., 2013; Ferguson 

et al., 2013). These contaminants frequently were not regulated and are inadequately monitored by state 

or Federal water-quality programs. The IJC has recognized that while information exists regarding the 

presence of such chemicals in the Great Lakes watershed, few data were available regarding effects of 

exposure. Failure to identify and understand the effects of the complex mixtures of chemical 

contaminants and other environmental stressors on fish and wildlife resources may result in deleterious 

effects on Great Lakes resources with adverse ecological, economic, and recreational consequences. 

Identifying adverse effects on fish health and potential sources of contaminants is necessary for 

addressing management strategies directed toward healthier fish populations. 

With GLRI funding, the U.S. Fish and Wildlife Service (FWS) Environmental Contaminants 

Programs initiated an early warning program to detect and identify CECs in the Great Lakes Basin and 

their effects on fish and wildlife. This program was part of a multiagency monitoring and surveillance 

effort (Ekman et al. 2013) that includes chemical sampling of water and sediment (Lee et al. 2012) and 

caged fish studies at selected sites in addition to identification of potential adverse effects on resident 

wild fishes. The U.S. Geological Survey (USGS) and West Virginia Cooperative Fish and Wildlife 

Research Unit, West Virginia University, developed a suite of endpoints and implemented 

monitoring/surveillance for detection of adverse biological effects in wild fishes. 

The suite of indicators includes biomarkers from the organism to the molecular level. Organismlevel indicators, such as necropsy-based and morphometric observations have been used in numerous 

monitoring programs and, although not as sensitive as histopathological or some other endpoints, 

provide important information at the organism level (Goede and Barton 1990; Schmitt and Dethloff 

2000; Fournie et al. 1996). Tissue or organ-level indicators include endpoints such as hepatosomatic 

(HSI) and gonadosomatic (GSI) indices and the microscopic pathology (histopathology) of various 

tissues. Exposure to contaminants, including estrogenic compounds (Jobling et al., 1996; Jobling et al., 

1998; Hassanin et al., 2002; Sindhe and Kulkarni, 2004) have been shown to influence gonadal growth 

and GSI. Numerous histopathological changes in tissues have been used as biomarkers of exposure and 

(or) environmental stress, including neoplasms and preneoplastic changes of liver and skin (Myers and 

Fournie, 2002; Stentiford et al., 2003; Au, 2004; Lyons et al., 2004). Histopathology of the gonads was 

used to verify sex and stage of gonadal development, as well as identify abnormalities such as testicular 

oocytes (Blazer, 2002; Dietrich and Krieger, 2009). Although effects on the reproductive system have 

been the most commonly documented, other systems can be affected by exposure to CECs and legacy 

contaminants. These include the thyroid and adrenal or interrenal/chromaffin tissue, as well as the 

immune system which can be examined microscopically. 

Subcellular (plasma analyses) and molecular (gene expression) biomarkers are often reflective of 

more recent or acute exposure than the organism or tissue-level biomarkers. Vitellogenin, an egg-yolk 

precursor protein produced in response to estrogen and estrogen agonists, is normally found only in the 

serum of adult female oviparous vertebrates, but can be induced in males and immature females by 

estrogenic compounds or estrogen mimics. The presence of plasma vitellogenin in male fishes is a wellaccepted indicator of exposure to estrogenic endocrine disrupting chemicals (Tyler et al., 2007; 

Denslow et al., 1999; Cheek et al., 2001). In contrast, decreased levels of circulating vitellogenin in 

female fish may result in lowered egg quality (Wheeler et al., 2005; Miller et al., 2007). Hormones, 

including estradiol and 11-keto testosoterone, can be measured in plasma, and abnormal concentrations 
3 

may be indicative of exposure to endocrine disruptors and other contaminants (Munkittrick et al., 1998; 

Sepúlveda et al., 2002; Hinck et al. 2007; Cheshenko et al. 2008). 

Genotoxic pollutants may have mutagenic and (or) carcinogenic properties, that affect a cell’s 

genetic material, causing mutations and in some cases contributing to the tumor development and 

neoplasia (Pinkney et al., 2011; Williams, 2012). A variety of methods have been used with fishes to 

detect exposure to genotoxic compounds. One of the easiest methods for use in field studies is 

assessment of red blood cell micronuclei and other nuclear abnormalities. Blood smears can be made 

immediately after blood collection, fixed, and then stained in the laboratory. This method has been 

widely used for assessing genotoxicity in many fish species (Al-Sabti and Metcalfe, 1995; Ayllón and 

Garcia-Vasquez, 2001; Rodriguez-Cea et al., 2003), including brown bullhead, Ameiurus nebulosus, and 

white sucker, Catostomus commersoni (Metcalfe, 1988; Smith, 1990). Although other methods have 

been used to assess genotoxicity or DNA damage in smallmouth bass, Micropterus dolomieu, 

(Chamberland et al., 2002) and largemouth bass Micropterus salmoides (Sugg et al., 1995; Lingenfelser 

et al., 1997), to our knowledge the micronuclei assay has not been previously evaluted in these species.

The species of choice were either brown bullhead or white sucker (benthic species) and either 

largemouth bass or smallmouth bass (pelagic species). Brown bullhead and white sucker have been used 

extensively in the Great Lakes Basin as watershed indicator species, particularly in relation to skin and 

liver tumors (Smith et al., 1989; Hayes et al., 1990; Premdas et al., 1995; Baumann et al., 1996; Blazer 

et al., 2009 a and b; Rafferty et al., 2009). White sucker have also demonstrated sensitivity to the effects 

of exposure to endocrine disruptors at sites within the Great Lakes Basin and elsewhere (Munkittrick 

and Dixon, 1989; Woodling et al., 2006; Bowron et al., 2009). Bass were a target species for the USGS 

Biomonitoring of Environmental Status and Trends (BEST) monitoring program (Schmitt, 2002; Hinck 

et al., 2007) and have been shown to be sensitive to endocrine-disrupting chemicals (Sepúlveda et al., 

2002; Blazer et al., 2007b; Hinck et al., 2009; Iwanowicz et al., 2009; Blazer et al., 2012). 

There were three major objectives of the research conducted by USGS from 2010 to 2011. The 

first objective was to evaluate the “fish tumor and other deformities” BUI at the St. Louis River AOC in 

Minnesota. This BUI was defined as occurring “when the incidence rates of fish tumors or other 

deformities exceed rates at unimpacted control sites or when survey data confirm the presence of 

neoplastic and preneoplastic liver tumors in bullheads or suckers” (International Joint Commission, 

1991). The current status of this BUI was unknown for many AOCs, including the St. Louis River. The 

incidence of proliferative, possibly preneoplastic, and neoplastic skin and liver lesions was evaluated in 

terms of habitat usage in 200 white sucker captured within the river and estuary in spring 2011 (Blazer 

et al., 2014). 

The second objective was to evaluate fish health at the Ashtabula River AOC in Ohio and 

Conneuat Creek in Ohio (reference site) in spring and fall 2011. The health of largemouth bass and 

brown bullhead was evaluated during 2002–04 prior to remediation and restoration (Blazer et al., 2006a; 

Iwanowicz et al., 2012). During 2010–11, the Ohio Environmental Protection Agency undertook habitat 

restoration projects to increase in-water and shoreline habitat and develop a fish shelf in the lower 2 

miles of the river to provide habitat to forage and spawn. The objective of the 2011 sampling was to 

compare current fish health to pre-remediation findings. In the pre-remediation study, whole-body 

contaminant concentrations correlated to certain biomarkers, particularly immune system endpoints. 

More in-depth analyses are underway to demonstrate whether contaminant loads have decreased and the 

effect a decrease would have on biological endpoints (Iwanowicz et al., U.S. Geological Survey, written 

commun., 2014). 

The third objective was to utilize a suite of endpoints in multiple species, spatially and 

seasonally, to identify potential adverse effects of emerging contaminants on fish health at sites within 
4 

the Great Lakes Basin during 2010–2012. The purpose of this report is to present the methods used in 

the study and preliminary results of research conducted to address this third objective. 

Methods

Sites Selection

Sites selected are AOCs suspected of being affected by CEC in municipal wastewater discharges 

or receiving waters of industrial facilities and (or) potential agricultural or urban nonpoint sources. 

Based on these characteristics, the following locations were selected for the fall 2010 sampling: 

Genesee River (Rochester Embayment AOC, New York), St. Louis River (St. Louis River and Bay 

AOC, Minnesota), Swan Creek (Maumee River AOC, Ohio), Detroit River (Detroit River AOC, 

Michigan) and Fox River (Lower Fox River/Green Bay AOC, Wisconsin). In spring 2011, the 

Milwaukee River (Milwaukee Estuary AOC, Wisconsin), Ashtabula River (Ashtabula River AOC, 

Ohio) and Conneaut Creek (Reference site, Ohio) were added to the list of sampling sites (Figure 1). 

Fish sampling sites are listed in Appendix 1. 
5 

Figure 1. Sampling sites for fish collections conducted in the Great Lakes Basin during 2010-2011.

Field Methods

Attempts were made by FWS personnel to collect 20 mature fish (10 males and 10 females) 

from each of two species at each site by electrofishing, minnow traps, or fyke nets. Spring sampling in 

each year was intended to be conducted during the prespawn period. Fish were anesthetized with MS222 (Tricane Methanesulfonate, Argent Chemical Laboratories, Redmond, Washington), weighed to the 

nearest gram (gm) and measured (total length) to nearest millimeter (mm). Peripheral blood was 

extracted from the caudal vessels using a heparinized syringe. One drop of blood was placed onto each 

of two pre-cleaned glass slides and blood smears were prepared and allowed to dry. Slides were fixed 

with absolute methanol for 10 minutes. The remaining blood was stored on wet ice until centrifuged 

(same day) and plasma aliquoted into two cryovials. Plasma samples were stored in 1.5-mililiter (mL)

polypropylene microcentrifuge tubes (Fisher Scientific, Pittsburgh, Pennsylvania) at -80 degrees 

Celsius (°C) until analyzed. A comprehensive necropsy-based assessment was completed on all fish 
6 

collected (Goede and Barton, 1990; Smith et al., 2002; Rafferty and Grazio, 2006), and all visible 

abnormalities were documented. The liver and gonads were removed and weighed to calculate HSI and 

GSI. Liver weights were not recorded for white suckers because the liver tissue was intertwined with the 

intestine. The HSI was calculated as 100 X (liver weight/body weight – gonad weight). Condition factor 

(KtL) was calculated by using the formula 105 X ([body weight – gonad weight]/total length3). Small 

pieces of liver (2mm or less), spleen, and anterior kidney were placed into RNAlater® solution for 

subsequent molecular analyses. Pieces of gill, liver (5 to 8 pieces, each piece 1-1.5 centimeters [cm]), 

anterior and posterior kidney, spleen, gonad, thyroid and any lesions or abnormalities were placed in 

Z-FixTM (Anatech Ltd, Battle Creek, Minnesota) for subsequent histological analyses. The sagittal 

otoliths were removed from bass species by removing gill arches and the tissue from the soft pallet on 

the roof of the mouth. A lateral cut was then made with bone shears across the anterior section of the 

elongated cartilaginous structure located at the base of the brain cavity, exposing the pair of sagittal 

otoliths. The lapillus otoliths were removed from brown bullhead and white sucker in a similar manner. 

Following extraction, all otoliths were placed in a labeled coin envelope for subsequent processing and 

analysis.

A yeast bioreporter assay was used to determine the presence of chemicals in grab water samples 

capable of initiating estrogen receptor mediated gene transcription. Other in vitro screening assays were 

used to measure whether chemicals were present in these water samples that would lead to ligand 

mediated translocation of the androgen or glucocorticoid receptor from the cytoplasm to the nucleus of 

reporter cell lines. These analyses were performed on extracted discrete grab samples of water collected 

in clean amber bottles and stored on ice in fall 2010. Samples were acidified to pH 3.0 using 

hydrochloric acid and stored in glass bottles at 4 °C prior to extraction. 

Laboratory Analysis

Age Analysis

Sagittal otoliths were prepared by methods modified from Christensen (1964). Briefly, the whole 

otolith was cracked transversely using a scalpel. One side of the cracked otolith was burned with an 

alcohol burner (95% ethanol), cooled immediately in distilled water, and read using a stereoscope. 

Lapillus otoliths were prepared using methods modified from Koch and Quist (2007). Whole lapillus 

otoliths were prepared using a multiple-stage process. First, plastic 2.0-mL flat-top microcentrifuge 

tubes (Fisher Scientific, Pittsburgh, Pennsylvania) have their caps filled with modeling clay, and the 

tapered ends removed to create a cylinder. Singular lapilli were placed into the clay such that the 

“thumb” of the otoliths was embedded into the clay. The vial was filled using the Epoxicure® brand of 

resin and hardener (Buehler Inc., Lake Bluff, Illinois) and allowed to harden. The plastic case was then 

removed and the otoliths sectioned at approximately 0.64 mm thickness using an Isomet low speed saw 

(Buehler Inc. Lake Bluff, Ill.). Sections were read under transmitted light using a stereoscope. All age 

data were collected in a double blind study, meaning that two individuals read each otolith, and the age 

estimates were independent of biological data. 

Reproductive Health Indicators

Reproductive health indicators consisted of the gonadosomatic index (GSI), plasma vitellogenin 

concentrations, reproductive hormones, and gonad histology. 
7 

Gonadosomatic Index

GSI is a ratio of gonad weight to body weight calculated by the formula (gonad weight/[body 

weight – gonad weight]) X 100. 

Vitellogenin

Plasma vitellogenin (Vtg) concentrations were measured using a direct enzyme-linked 

immunosorbent assay (ELISA). The primary antibodies were monoclonal antibodies, including ND-3G2

(small and largemouth bass), ND-2D3 (white sucker), or 1D12 (brown bullhead) (Cayman Chemical 

Company, Ann Arbor, Mich.). The Vtg standards used for the assay were purified from smallmouth 

bass, white sucker or brown bullhead and were prepared at the Center for Human and Environmental 

Toxicology, University of Florida, Gainesville, Florida. Briefly, plasma samples were diluted 1:1000, 

1:5000, 1:10,000, 1:50,000 or 1:100,000 with PBSZ (4.2 millimoles [mM] trisodium phosphate, 5.8 mM 

monosodium phosphate, 150 mM sodium chloride (NaCl), 0.02% sodium azide, pH 7.6). Plasma 

samples were loaded in duplicate and genera specific Vtg standards were loaded in triplicate at a volume 

of 50 microliters (μL) into a 96-well Easy Wash High Binding plate (Costar, Corning, N.Y.) and stored 

overnight at 4 °C in a humidified chamber. Following an overnight incubation the plates were washed 

five times with Tris-buffered saline and Tween 20 (TBST) (10 mM Sigma 7-9, 150 mM NaCl, 0.05% 

Tween-20, pH 7.6) and 300μL of blocking buffer (10 mM Sigma 7-9, 150 mM NaCl, 1% bovine serum 

albumin, 0.05% Tween-20, pH 7.6) was added. Plates were incubated at room temperature for 1 hour 

and washed five times with TBST. The anti-Vtg antibody was diluted 1:1000 in blocking buffer, added 

to all wells, and incubated at room temperature for 1 hour. Plates were then washed five times with 

TBST. The biotinylated secondary antibody (goat anti mouse IgG-biotin) was diluted 1:1000 in 

blocking buffer, added to all wells, and incubated at room temperature for 1 hour. Plates were then 

washed five times with TBST. Strepavidin-alkaline phosphatase was diluted 1:5,000 in blocking buffer, 

added to all wells and incubated at room temperature for 1hour. Plates were then washed five times with 

TBST, and color was developed by adding a development solution (2.7mM 4-nitro-phenyl phosphate, 

30 mM sodium carbonate, 2 mM magnesium chloride (MgCl2, pH 9.6). Plates were incubated at room 

temperature for 30 minutes. Optical density (405 nanometers [nm]) readings were taken every 10 

minutes during this incubation using SpectraMax M4 microplate reader (Molecular Devices, Inc., 

Sunnyvale, California). Concentrations of the unknowns were determined from the standard curves and 

using Softmax Pro TM software (Molecular Devices). The limit of detection was 1 microgram per 

milliliter (μg/mL). 

Reproductive Hormones

Hormones were extracted from 50 μL of plasma twice in a ten-fold excess of diethyl ether 

(Acros Organics, Geel, Belgium), blown to dryness and solubilized in 400μL of room temperature 

phosphate gelatin (PG) buffer (0.1% knox gelatin in Dulbecco’s phosphate-buffered saline [DPBS]).

The sex steroid hormones 17β-estradiol and 11-keto testosterone were measured using ELISA-based 

kits (Cayman Chemical, Ann Arbor, Mich.). Hormone concentrations were measured at 412 nm with a 

SpectraMax M4 microplate reader (Molecular Devices, Inc., Sunnyvale, Calif.). Concentrations of the 

unknowns were determined from the standard curves and using the Softmax Pro TM Program 

(Molecular Devices). The limits of detection were 20 picograms per milliliter (pg/mL) for estradiol and 

1.3 pg/mL for 11-keto testosterone. 
8 

Gonad Histology

Five to seven cross-sections of each gonad were placed in cassettes, routinely processed and 

embedded into paraffin. Blocks were sectioned at 5 micrometers (μm) and stained with hematoxylin and 

eosin. Slides were examined for any abnormalities at the microscopic level. Sections of gonads were 

used to confirm sex, stage of development, percent atretic eggs, and any other abnormalities such as 

occurrence of intersex, fibrosis, abnormal yolk accumulation, ceroid/lipofuscin accumulations, or Sertoli 

cell proliferation and were evaluated after neoplasia as described by Blazer (2002), Leino et al. (2005), 

and Dietrich and Krieger (2009). 

Genotoxic/Mutagenic/Carcinogenic Indicators

Genotoxic/mutagenic/carcinogenic indicators consist of cell nuclear abnormalities and internal 

and external neoplasms.

Red Blood Cell Micronuclei and other Nuclear Abnormalities

Blood smears were stained with Giemsa solution (Fluka Analytical, Saint Louis, Missouri) for 45 

minutes, followed by two, 45-minute distilled water baths using methods modified from Carrasco et al. 

(1990). Stained slides were cover-slipped and evaluated under light microscopy at 600x magnification. 

A minimum of 200 erythrocytes were examined at five stratified random locations on each slide such 

that a minimum of 1,000 erythrocytes were evaluated for abnormalities. The abnormalities were 

recorded as described by Carrasco et al. (1990). Briefly, a micronucleus was defined as a round 

cytoplasmic intrusion having a diameter one-tenth to one-third that of the primary nucleus. Notched 

nuclei are indentations extending well into the nuclear envelope. Lobed nuclei have large evaginations 

of the nuclear envelope with no clear shape or definition. Blebbed nuclei are small evaginations of the 

nuclear envelope that may resemble a micronucleus, but are attached to the nucleus. A binucleated cell

contains two nuclei that are relatively similar in size and not attached.

Proliferative, Preneoplastic and Neoplastic Lesions

Five to seven pieces of liver, and pieces of spleen, kidney, gill, thyroid and any external or 

internal abnormalities were placed in Z-FixTM in the field. Fixed tissue samples were trimmed, placed in 

cassettes, processed, and embedded into paraffin. Blocks were sectioned at 5 μm and stained with 

hematoxylin and eosin. Slides were examined for any abnormalities at the microscopic level. One slide

for each fish, containing pieces of liver, spleen and anterior kidney, were stained using the Perl’ 

Prussian blue method for iron to differentiate pigments within macrophage aggregates and hepatocytes. 

The method stains hemosiderin, an iron-containing protein, while melanin remains black, and 

ceroid/lipofuscin remains yellowish-brown (Luna 1992). Liver sections were examined for 

preneoplastic and neoplastic lesions as described by Blazer et al. (2006b and 2007a). Other 

nonneoplastic lesions such as fibrosis, bile duct proliferation, and inflammation (Wolf and Wolfe 2005) 

were documented. Proliferative skin lesions were identified following the criteria of Blazer et al. 

(2007a).

Molecular Endpoints

At the onset of this research, brown bullhead, white sucker, smallmouth bass, and largemouth 

bass gene sequence databases were sparsely populated. In order to develop primer or probe sets to 

quantify biomarker gene expression it was critical to construct annotated gene databases for these 

species. Total RNA was extracted from a total of 20 smallmouth bass or brown bullhead liver samples 
9 

using EZNA total RNA isolation kits (Omega Bio-Tek, Norcross, Georgia). Transcriptome libraries for 

each species were constructed slightly differently given advances in technology and options during the 

project. For the brown bullhead and smallmouth bass, total RNA was shipped to CoFactor Genomics 

(St. Louis, Mo.). Ribosomal RNA was depleted using a Ribo-Zero kit (Epicentre, Madison, Wis.) and 

samples were normalized with an Evergren normalization kit (Evergen Biotechnologies, Inc., Vernon, 

Connecticut). RNA-seq, 2 x 6 base pair mate-paired libraries were prepared for each species.

Sequencing was performed on an Illumina GAIIx (Illumina, San Diego, Calif.), and each library was 

run in a single lane to yield approximately 2.2 gigabytes (Gb) of sequence. An additional smallmouth 

bass run was performed for transcriptome analysis on total RNA at Duke Institute for Genome Science 

and Policy (Durham, North Carolina). Samples were sequenced on a Roche 454 GS FLX (Roche, 

Branford, Conn.). For white suckers, total RNA was pooled from liver tissues (n=10), slightly raised 

mucoid skin lesions (n=9), raised papilloma-like lip lesions (n=5), and discrete white spots on the skin 

(n=8). As above, ribosomal RNA was depleted from the samples. The RNA was then shipped to the 

Institute for Genome Science core laboratory (Baltimore, Maryland) for library preparation and 

sequencing. RNA-seq libraries were prepared and 100 base pair paired-end reads were achieved on an 

Illumina HiSeq (Illumina, San Diego, Calif.). Raw sequence reads were assembled using CLC 

Genomics workbench and biomarker genes were identified via BLASTx analyses to the National Center 

for Biotechnology (NCBI) RefSeq database for the zebra danio (Danio rerio).

Individual liver samples collected and stabilized in RNA Later® (Life Technologies, Carlsbad, 

Calif.) were prepared for gene expression analysis using NanoString Analysis. Tissue lysate for analysis 

was prepared by lysing approximately 20 milligrams (mg) of liver tissue in 400 microliters (μL) TRK 

Lysis Buffer (Omega Bio-tek, Norcross, Ga.). The tissue was homogenized on a TissueLyser (Qiagen, 

Hilden, Germany) with 5-mm stainless steel beads. Samples were then centrifuged at maximum speed 

for 10 minutes to remove the insoluble tissue components, and the supernatant and stored at -80 ○C until 

shipment. A total of 250 smallmouth bass, 360 largemouth bass, 214 white sucker and 267 brown 

bullhead samples were processed for gene expression analysis. The nCounter analysis for gene 

expression was conducted at the Genomics and Proteomics Core Laboratories at the University of 

Pittsburgh. 

Exploratory analysis of smallmouth bass liver gene expression data was performed using 

NanoStride (http://nanostride.soe.ucsc.edu/) which analyzes NanoString nCounter analysis count data. 

These analyses included expression data from male and female smallmouth bass collected during spring 

2010 and fall 2011 from the St. Louis, Fox and Milwaukee Rivers. Smallmouth bass were not present 

for collection at the other AOCs. Data files generated from the nCounter analysis were uploaded to 

compare the differential expression of genes among groups. Samples were normalized to internal 

housekeeping genes present in the data. Housekeeping genes for this analysis included Ribosomal 

Protein L8 (RPL8), hypoxanthine phosphoribosyltransferase 1 (hprt1), eukaryotic translation initiation 

factor 3D (eif3d) and RBMX2. All groups of two were analyzed using the DESeq statistical test which 

assumes a negative binomial distribution and thus was most appropriate for this type of data. P-values 

were adjusted following Benjamini and Hochberg (1995). The p-value cut off for the generation of 

heatmaps was set to 0.05. Groups of three or more were analyzed using one-way analysis of variance 

(ANOVA) with adjusted p-values and p-value cut offs as described above. 

Additional statistical analysis was needed of the data using the R statistical software (R Core 

Team, 2012). Samples were normalized using the NanoStringNorm package (Waggott et al., 2012) and 

the same four housekeeping genes listed above. Differential expression of genes were then assessed 

using the bioconductor: edgeR package (Robinson et al., 2010). This method produced results that were 

similar to those of the NanoStride software and allows the user to adjust test parameters as necessary. 
10

In vitro Screening Assays of Water Samples

Water samples were filtered by vacuum filtration through a glass fiber filter. Polar analytes were 

captured via solid phase extraction (SPE) using OASIS HLB columns (Ciparis et al., 2012). Samples 

were eluted with methanol and methanol dichloromethane (50:50), concentrated to dryness, and then 

reconstituted in 100 % methanol. For total estrogenicity, extracts were added to the wells of a 96-well 

black plate and diluted 90 % in yeast growth medium. The yeast reporter (strain BLYES) was used to 

determine 17β-estradiol equivalents of each sample extract. Estradiol standards were included on each 

plate and estrogenicity of the sample extract determined by interpolation from the E2 standard curve 

(Sanseverino et al., 2005). In addition, in fall 2010, androgen and glucocorticoid activity was screened 

using a high-throughput live cell assay based on subcellular relocalization of green fluorescent protein 

(GFP)-tagged receptors by collaborators in the National Institute of Health National Cancer Institute 

(Stavreva et al., 2012). 

Results and Discussion

Fish Collection

Fish were collected at seven AOCs and at one Reference site (Table 1).

Table 1. Sampling site Areas of Concern and locations in the Great Lakes Basin. Latitudes and longitured are in 

decimal degrees, North American Datum (NAD) 83 Geographic Coordinate System (GCS).

Area of Concern Stream Name Longitude Latitude

Rochester Embayment Genesee River -77.618 43.234

St. Louis River St. Louis Bay -92.115 46.759

Maumee River Swan Creek -83.532 41.648

Detroit River Trenton Channel (Detroit River) -83.159 42.177

Fox River/Lower Green Bay Fox River -88.005 44.539

Milwaukee Estuary Milwaukee River -87.911 43.032

Ashtabula River Ashtabula River -80.795 41.900

Reference Conneaut Creek -80.545 41.965

Fish were collected in fall 2010 from September 21 to October 19 and in spring 2011 from April 12 to 

May 2. In fall 2010 fish were collected at five AOCs (Table 1). Fish were not collected at the 

Milwaukee River AOC in fall 2010. In spring 2011 an attempt was made to collect fish at the same sites 

in order to compare biological effects seasonally. Additionally, fish were collected at the Ashtabula 

River AOC and Conneaut Creek (reference site) in spring and fall 2011 (Table 2).
11

Table 2. Summary of Fishes Collected for Fish Health Assessments in selected Areas of Concern in the Great 

Lakes Basin, fall 2010 and spring 2011.

[AOC, Area of Concern; M, male; F, female]

Site Date Brown 

bullhead

White 

sucker

Largemouth 

bass

Smallmouth 

bass

Rochester Embayment AOC

 Genesee River Fall 2010

Spring 2011 13 F

7M

6 F

14 M

9 F

10 M

St. Louis River AOC

 St. Louis Bay Fall 2010

Spring 2011

7 F

7 M

3 F

22 M

3 F

4 M

3 F

3 M

Maumee AOC

 Swan Creek Fall 2010

Spring 2011

6 F 

12 M

10 F

10 M

6 F

14 M

Detroit River AOC

 Trenton Channel Fall 2010

Spring 2011 14 F

6 M

0 F

20 M

8 F

12 M

12 F

8 M

Lower Fox River/Green Bay AOC

 Fox River Fall 2010

Spring 2011

18 F

1 M

11 F

9 M

20 F

0 M

Milwaukee Estuary AOC

 Milwaukee River Spring 2011 14 F

6 M

11 F

9 M

Ashtabula River AOC 

 Ashtabula River Spring 2011

Fall 2011

8 F

12 M

7 F

12 M

8 F

12 M

10 F

10 M

Conneaut Creek Spring 2011

Fall 2011

9 F

11 M

10 F

10 M

9 F

11 M

Unfortunately, the only seasonal comparisons that could be made were for white suckers collected in St. 

Louis Bay and Swan Creek, largemouth bass from the Genesse and Detroit Rivers, smallmouth bass 

from St. Louis Bay (low sample sizes) and the Fox River, and brown bullhead from the Ashtabula River 

and Conneaut Creek (Table 2). 
12

Morphometric, Condition Factor and hepotosomatic Index

Smallmouth and Largemouth Bass

An acceptable sample size of smallmouth and largemouth bass was obtained at all sites where 

bass were collected, except for St. Louis Bay where only seven and six smallmouth bass were collected 

in fall 2010 and spring 2011, respectively. Largemouth bass were collected in both fall and spring from 

the Genesee and Detroit Rivers, but from Swan Creek only in the fall. Smallmouth and largemouth bass 

ranged in age from 4 to 14 years (Appendix 1). Swan Creek had the youngest largemouth bass with the 

lowest condition factors. Condition factors were higher in the spring than in fall at the Genesee and 

Ashtabula Rivers. At the Genesee, Detroit, and Ashtabula Rivers, largemouth bass had higher HSI in 

spring than fall (Table 3).

Table 3. Morphometric parameters of largemouth and smallmouth bass collected in the Great Lakes Basin, 2010-

20111. 

[mm, millimeters; gm, gram; yr, year; n, number]

Site Season/year N Length

(mm)

Weight

(gm)

Age

(yr)

Condition 

factor2 

Hepatosomatic

index3 

Largemouth Bass

Genesee River Fall 2010 20 330 ± 10.8 612 ± 57.0 5.5 ± 0.1 1.59 ± 0.04 1.0 ± 0.1

Spring 2011 19 368 ± 10.8 906 ± 95.9 6.7 ± 0.4 1.64 ± 0.02 1.9 ± 0.1

Swan Creek Fall 2010 20 262 ± 8.0 305 ± 36.8 4.8 ± 0.4 1.57 ± 0.02 1.3 ± 0.1

Detroit River Fall 2010 20 355 ± 13.4 881 ± 97.4 6.0 ± 0.3 1.75 ± 0.04 1.4 ± 0.1

Spring 2011 20 350 ± 8.0 731 ± 51.1 5.4 ± 0.2 1.58 ± 0.02 1.8 ± 0.1

Ashtabula River Spring 2011 20 374 ± 11.9 873 ± 82.0 6.6 ± 0.4 1.52 ± 0.03 1.7 ± 0.1

Fall 2011 20 336 ± 11.1 608 ± 72.9 5.7 ± 0.3 1.46 ± 0.04 1.3 ± 0.1

Conneaut Creek Fall 2011 20 339 ± 9.5 636 ± 66.8 6.0 ± 0.5 1.54 ± 0.03 1.3 ± 0.1

Smallmouth Bass

St. Louis River Fall 2010 7 434 ± 17.9 1368 ± 151.8 8.6 ± 1.2 1.60 ± 0.03 1.1 ± 0.1

Spring 2011 6 416 ± 20.2 1259 ± 197.1 6.8 ± 0.6 1.60 ± 0.10 1.7 ± 0.3

Fox River Fall 2010 20 408 ± 6.2 1098 ± 96.1 6.1 ± 0.3 1.76 ± 0.02 1.7 ± 0.1

Spring 2011 20 419 ± 10.2 1185 ± 77.2 6.1 ± 0.2 1.49 ± 0.03 1.7 ± 0.2

Milwaukee River Spring 2011 20 337 ± 9.7 522 ± 79.4 6.4 ± 0.3 1.26 ± 0.05 1.7 ± 0.1

1

Data are presented as mean ± standard error.

2

Condition factor (KtL) is calculated as ([body weight – gonad weight]/length3) X 105

3

Hepatosomatic index (HSI) is calculated as (liver weight/[body weight-gonad weight]) X 102

Smallmouth bass were collected in the fall and spring from the St. Louis River and the Fox 

River. There were no differences in the size or age of smallmouth bass from the St. Louis River between 

fall and spring; however the HSI was higher in the spring than fall. Smallmouth bass from the Fox River 

did not differ in any parameters between the fall and spring. Although smallmouth bass collected in the 

Milwaukee River were of similar age to those from the other sites, they were significantly shorter and 

lighter (Table 3).

White Sucker

White sucker were collected in fall and spring from St. Louis River and Swan Creek, but only in 

the fall at Detroit and Fox Rivers and only in the spring from the Milwaukee River. Ages of white 

sucker ranged from 2 to 16 years (Appendix 1). The Fox and Milwaukee Rivers had the largest and 
13

oldest suckers with the lowest condition factors. Swan Creen in fall and the Detroit River had the 

youngest and smallest suckers. The Detroit River suckers had the highest condition factors (Table 4). 

Table 4. Morphometric parameters of white sucker collected in the Great Lakes Basin, 2010-20111. 

[mm, millimters; gm, gram; yr, year]

Site Season/Year Sample

Size

Length

(mm)

Weight

(gm)

Age

(yr)

Condition 

factor2 

St Louis River Fall 2010 14 404 ± 19.7 833 ± 107.9 7.5 ± 0.90 1.06 ± 0.07

Spring 2011 25 402 ± 6.1 692 ± 30.8 8.0 ± 0.47 1.04 ± 0.01

Swan Creek Fall 2010 18 305 ± 10.0 318 ± 33.3 3.9 ± 0.36 1.06 ± 0.07

Spring 2011 20 445 ± 6.4 959 ± 65.5 7.0 ± 0.51 1.02 ± 0.04

Detroit River Fall 2010 20 279 ± 11.6 254 ± 17.4 2.7 ± 0.12 1.13 ± 0.02

Fox River Fall 2010 19 470 ± 5.5 906 ± 48.3 11.8 ± 0.69 0.83 ± 0.02

Milwaukee River Spring 2011 20 465 ± 10.4 1127 ± 79.4 11.1 ± 0.51 0.96 ± 0.02

1

Data are presented as mean ± standard error.

2

Condition factor (KtL) is calculated as ([body weight – gonad weight]/length3) X 105. 

Brown Bullhead

Brown bullhead were collected at the Genesse and Detroit Rivers only in the spring and from 

Ashtabula River and Conneaut Creek in spring and fall. Bullhead ranged in age from 3 to 14 years 

(Appendix 1). Bullhead from the Detroit River were somewhat smaller and younger than those collected 

from the Genesse River and had higher condition factors and HSI. Mean condition factors were slightly 

higher at both Ashtabula River and Conneaut Creek in spring versus fall (Table 5). 

Table 5. Morphometric parameters of brown bullhead collected in the Great Lakes Basin, 2010-20111. 

[mm, millimters; gm, gram; yr, year]

Site Season/

Year

Sample

Size

Length

(mm)

Weight

(gm)

Age

(yr)

Condition

Factor2 

Hepatosomatic 

Index3 

Genesse River Spring 2011 20 319 ± 11.0 419 ± 29.8 7.8 ± 0.6 1.3 ± 0.03 2.9 ± 0.2

Detroit River Spring 2011 20 295 ± 5.1 394 ± 19.4 5.6 ± 0.3 1.5 ± 0.03 3.5 ± 1.0

Ashtabula River Spring 2011 20 340 ± 6.5 602 ± 37.4 7.7 ± 0.4 1.5 ± 0.04 3.0 ± 0.2

Fall 2011 19 311 ± 8.3 421 ± 34.5 6.7 ± 0.5 1.4 ± 0.03 3.0 ± 0.1

Conneaut Creek Spring 2011 20 349 ± 5.1 633 ± 30.4 7.0 ± 0.5 1.5 ± 0.03 2.9 ± 0.2

Fall 2011 20 336 ± 8.3 559 ± 43.6 6.7 ± 0.3 1.4 ± 0.03 2.6 ± 0.1

1

Data are presented as mean ± standard error.

2

Condition factor (KtL) is calculated as ([body weight – gonad weight]/length3) X 105. 

3

Hepatosomatic index (HSI) is calculated as (liver weight/[body weight-gonad weight]) X 102. 

Gross and Histological Abnormalities

Smallmouth and Largemouth Bass

A variety of grossly observable abnormalities were noted externally. The most common external 

lesions observed in smallmouth and largemouth bass were red raised or eroded areas, melanistic areas

(Figure 2A); slightly raised, smooth mucoid lesions (Figure 2B); and opaque or otherwise abnormal 

eyes. External parasites such as leeches, grubs (cysts containing trematode metacercariae) and black 

spots (melanocyte accumulation around trematode metacercariae) were observed. 
14

Figure 2. Grossly visible lesions observed on smallmouth and largemouth bass: A, slightly raised, mucoid area 

(arrow) on the caudal fin, and B, melanistic areas (arrows) on the caudal fin.

There were site, species, and seasonal differences in the prevalence of the various abnormalities. 

Eye lesions were observed in at least one smallmouth bass from every site, but were not observed in any 

largemouth bass from the Detroit River. Red or eroded lesions were observed in both species and were 

more prevalent in the fall than in the spring (Table 6). 

Table 6. Percentage of largemouth and smallmouth bass with visible eye or skin lesions, Great Lakes Basin, 

2010-2011.

Site Season

year

Percentage of individuals with abnormality

Eye1 Red/eroded2 Parasites3 Melanistic4 Raised5

Largemouth Bass

Genesee River Fall 2010 5 45 20 25 35

Spring 2011 42 11 16 26 11

Swan Creek Fall 2010 30 25 65 10 10

Detroit River Fall 2010 0 15 20 30 5

Spring 2011 0 5 0 0 25

Ashtabula River Spring 2011 70 5 30 5 5

Fall 2011 35 15 0 5 15

Conneaut Creek Fall 2011 50 45 45 0 10

Smallmouth Bass

St Louis River Fall 2010 71 29 71 0 28

Spring 2011 33 0 67 0 17

Milwaukee River Spring 2011 5 15 0 0 5

Fox River Fall 2010 10 25 0 0 10

Spring 2011 5 0 0 10 5

1

Eye abnormalities include opaque, missing, or otherwise abnormal eyes.

2

Includes eroded, reddened, or raised reddened areas and wounds.

3

Parasites included leeches, copepods, and trematodes (black spot, grubs).

4

Melanistic areas are non-raised black areas on body surface, lips, or fins.

5

Raised lesions on body surface, lips, or fins.
15

Microscopically, the red or eroded lesions were generally areas of inflammation and hemorrhage, likely 

induced by infectious agents (Figure 3A). Parasites, which may damage the skin and cause 

microwounds, were also more common in the fall. The slightly raised mucoid skin lesions were 

observed in both species. Histologically, the majority of these lesions were focal areas of hyperplasia 

(Figure 3B). In one smallmouth from the St. Louis River the mucoid lesion was a papilloma (Figure 

3D). Melanistic areas were observed on largemouth bass from all sites, but only on smallmouth bass 

from the Fox River (Table 6). Normally, melanocytes were located in the dermis of the skin (Figure 

3C). Within the melanistic areas there were increased melanocytes in the epidermis, which was 

sometimes slightly thickened (Figure 3D).

Figure 3. Microscopic pathology of skin lesions observed on bass: A, reddened lesion with areas of hemorrhage 

(a) (scale bar equals 100 micrometers [μm]), B, slightly raised mucoid lesions with an area of hyperplastic 

epidermis (a) adjacent to normal skin (b) (scale bar equals 200 μm), C, normal skin of bass with epidermis (a) and 

dermis with melanocytes (arrows), (scale bar equals 50 μm0), and D, microscopic pathology of a melanistic areas 

with a slightly hyperplastic epidermis (a) containing melanocytes (arrows) (scale bar equals 50 μm). 

White Sucker

The gross lesions on white sucker included reddened eroded lesions, slightly raised mucoid 

lesions on the fins and body surface, small raised white spots, hard raised nodules, and larger raised lip 

and body surface lesions (Figure 4).
16

Figure 4. Grossly visible lesions observed on white sucker: A, slightly raised, mucoid area (arrow) on the body 

surface, B, slightly raised lip lesion (arrow), C, large, papillomatous growth on the lip (arrow), and D, large, 

multicolored growth (arrow) on the head and eye. 

In general, white sucker from the Fox and Milwaukee rivers had the highest number of external lesions, 

including eye abnormalities, red/eroded areas and raised lesions. Seasonal comparisons could be made 

only for white sucker from St. Louis River and Swan Creek. In the spring, a higher prevalence of raised 

lesions was noted for white sucker at St. Louis River and of red/eroded lesions for white sucker at Swan 

Creek were noted (Table 7). 
17

Table 7. Percentage of white sucker with visible eye or skin lesions, Great Lakes Basin, 2010-2011.

Site Season

year

Percentage of individuals with abnormality

Eye1 Red/eroded2 Parasites3 Raised4

St. Louis River Fall 2010 7 14 7 14

Spring 2011 4 12 16 56

Swan Creek Fall 2010 6 6 0 6

Spring 2011 0 35 0 10

Detroit River Fall 2010 0 30 15 10

Fox River Fall 2010 11 32 11 63

Milwaukee River Spring 2011 25 30 10 40

1

Eye abnormalities include opaque, missing, or otherwise abnormal eyes.

2

Includes eroded, reddened, or raised reddened areas and wounds.

3

Parasites included leeches, copepods, and trematodes (black spot, grubs).

4

Raised lesions on body surface, fins, and lips. 

The majority of the slightly raised mucoid lesions were hyperplastic lesions (Figure 5A). The raised lip 

and body lesions were generally papillomas (Figure 5B), benign skin tumors, although in some cases 

squamous cell carcinomas were observed (Figures 5C and D). There were differences noted in the types 

of raised lesions found at sample sites. For instance, although 31% of the white sucker from the St. 

Louis AOC had raised lesions, these were primarily slighty raised mucoid lesions. Only 4.5% were 

papillomas, the remaining were hyperplastic lesions (Blazer et al. 2014). Conversely, at Milwaukee 

River, 40% of white sucker had raised lesions and 35% were neoplastic lesions, including papilloma and 

squamous cell carcinoma. More detailed analyses are underway to compare microscopic appearance, 

gene expression and water/sediment chemical concentrations to better understand the progression and 

contributing factors for the observed skin lesions. 
18

Figure 5. Microscopic pathology of skin lesions observed on white sucker: A, slightly raised mucoid lesion with 

hyperplastic epidermis (a) is thickened in comparison to normal skin (b) (scale bar equals 100 micrometers [μm]), 

B, papilloma (a) with extensive proliferation of epithelial cells that vary in size and arrangement; neoplastic cells do 

not extend below the basement membrane (arrows) (scale bar equals 100 μm), C, squamous cell carcinoma with 

neoplastic epithelial cells (a) infiltrating through the basement membrane (arrow) (scale bar equals 50 μm), and

D, cells within the squamous cell carcinoma are pleomorphic, may be multinuceate (thick arrow), and have mitotic 

figures (thin arrow) (scale bar equals 30 μm). 

Brown Bullhead

Lesions observed on brown bullhead included melanistic areas, raised dark lesions on the fins 

and body surface, and slightly raised to large raised lesions on lips and body surface. Barbel 

abnormalities were also evaluated in brown bullhead. These included missing, shortened, deformed, and 

knobbed barbels (with small raised areas) (Figure 6) 
19

Figure 6. Grossly visible lesions observed on brown bullhead: A, melanistic areas on the body surface (arrows), 

B, raised black nodule (arrow) on the body surface, C, mMultiple raised nodules on the lips and mouth (arrows), 

and D, raised nodules (arrows) on the barbels.

Bullhead from the Genesee and Detroit Rivers had similar incidences of the various abnormalities. 

Those from Conneaut Creek had the lowest prevalence of raised and melanistic areas but the highest 

prevalence of red/eroded lesions in both seasons (Table 8). Raised lesions on the lips, body surface or 

barbels were neoplasms, including papilloma, squamous cell carcinoma, osteoma, and melanoma 

(previously described in Blazer et al. 2007a). 
20

Table 8. Percentage of brown bullhead with visible eye, barbel or skin lesions, Great Lakes Basin, 2010-2011.

Site Season

year

Barbel

abnormalities Skin/fin lesions

Raised

areas

Other1 Eye2 Red/

eroded3 Parasites4 Melanistic5 Raised6 

Genesee River Spring 2011 20 40 0 10 5 45 25

Detroit River Spring 2011 35 25 0 5 0 35 20

Ashtabula River Spring 2011 10 35 0 0 0 20 30

Fall 2011 11 0 5 0 0 32 16

Conneaut Creek Spring 2011 5 10 10 15 0 5 10

Fall 2011 10 30 10 15 15 5 10

1

Includes missing, shortened, and deformed barbels.

2

Eye abnormalities include opaque, missing, or otherwise abnormal eyes.

3

Includes eroded, reddened or raised reddened areas, and wounds.

4

Parasites included leeches, copepods, and trematodes (black spot, grubs).

5

Melanistic areas are non-raised black areas on body surface, lips, or fins.

6

Raised lesions on body surface, fins, and lips.

Genotoxic/Mutagenic/Carcinogenic Endpoints

Micronuclei and other nuclear abnormalities of red blood cells, as well as preneoplastic and 

neoplastic skin and liver microscopic lesions were used as markers of exposure to genotoxic/mutagenic 

and (or) carcinogenic compounds. Bass generally expressed micronuclei and other nuclear abnormalities 

ata higher frequency and severity when compared to white sucker or brown bullhead. This micronuclei 

and other nuclear abnormality data are summarized in Braham (2012). Further analyses are underway to 

explore the associations between these genotoxic responses, genotoxic or carcinogenic chemical 

concentrations in water and sediment, and the prevalence and type of various neoplastic and 

preneoplastic lesions. 

Reproductive Endpoints

In order to address possible reproductive endocrine disruption by exposure to complex mixtures 

of chemicals, a suite of biological endpoints including GSI, gonad stage, testicular oocyte prevalence 

and severity, other microscopic gonad abnormalities, plasma vitellogenin, estradiol and 11-ketotestosterone, were measured in each fish. Preliminary analyses of the results indicate exposure to 

estrogenic or anti-androgenic chemicals. Intersex or testicular oocytes were observed in both 

smallmouth and largemouth bass, but not in white sucker or brown bullhead. A high percentage of 

smallmouth bass from both the St. Louis River (low sample size) and Green Bay/Fox River in the fall 

and also from the St. Louis River in spring (low sample size) had testicular oocytes. Interestingly, no 

males were collected from Green Bay/Fox River in the spring. Vitellogenin was also measured in some 

males from these sites. Intersex was not observed in largemouth bass from the Genesse or Detroit Rivers 

in the fall and vitellogenin was measured at low concentrations in a low percentage of bass from these 

sites. In the spring, 1 in 10 males from the Genesse River and 2 in 8 males from the Detroit River had 

testicular oocytes. Interstingly, all the males from these sites had measurable vitellogenin at this time.

Vitellogenin was measured in the fall in some white sucker males, except in the Fox River; 

however, only one male was collected from the Fox River. Brown bullheads were collected only in the 

spring from the Genessee and Detroit Rivers, and all males had measurable vitellogenin. Vitellogenin 

was also measured in all males from the Ashtabula River in spring and fall. 
21

Further analyses are underway to explore associations of vitellogenin concentrations and 

intersex prevalence and severity with presence of estrogenic chemicals in water or sediment measured at 

these sites (Lee et al. 2012), as well as with land use. In addition, the association of these effects with 

other biological endpoints such as reproductive hormones and gonad histology is being explored. 

Molecular Endpoints

Gene Expression Analysis

The transcriptome analyses produced a large number of sequences from which custom code set 

of genes were developed. For smallmouth bass, six housekeeper genes (ribosomal protein L8, 

hypoxanthine phosphoribosyltransferase 1, eukaryotic translation iniation factor 3D, RBMX2, TATA 

box binding protein, and β-actin) were evaluated. Four of these housekeeping genes were identified as 

suitable candidates for normalization (hypoxanthine phosphoribosyltransferase 1, eukaryotic translation 

iniation factor 3D, RBMX2, ribosomal protein L8). Forty-four biomarker genes were selected for 

analysis in individual bass. For brown bullhead, elongation factor α, hypoxanthine 

phosphoribosyltransferase 1, tata box binding protein, and eukaryotic translation iniation factor 3D were 

used as housekeeper genes, and 29 genes were evaluated in individual bullheads. Genes selected for 

gene expression analysis are listed in Table 9. 

Table 9. Genes chosen for NanoString analysis of individual liver samples.

[NA, not applicable]

Bass genes Brown bullhead genes White sucker genes

Vitellogenin Vitellogenin Vitellogenin B1

Estrogen receptors (ER) α, β1, β2 Estrogen receptors α and β G-protein coupled ER 1

Superoxide dismutase Superoxide dismutase Superoxide dismutase

Heat shock proteins 70, 71, 90 α Heat shock proteins 70 and 90 β Heat shock proteins 90 β, 5

Glutathione peroxidase 1 Glutathione peroxidase 1 Glutathione peroxidase 4

Fibroblast growth factor Fibroblast growth factor Fibroblast growth factor

Glutathione S-Transferase Glutathione S-transferase Glutathione S-transferase α

Glucokinase Glucokinase Glucokinase

Thyroid hormone receptors α, β Thyroid hormone receptors α, β Thyroid hormone receptors α

Insulin-like growth factor 1 Insulin-like growth factor 1 Insulin-like growth factor II

CYP1A, CYP3A and CYP17 CYP1A and CYP3A CYP1A, CYP3A, CYP2XB

Catenin β Catenin β Catenin

Aryl hyrdrocarbon receptor Aryl hyrdrocarbon receptor Aryl hyrdrocarbon receptor

Glucocorticoid receptor Glucocorticoid receptor NA

Epidermal growth factor receptor Epidermal growth factor receptor NA

Arginase Arginase NA

3β-Hydroxysteroid dehydrogenase 3β-hydroxysteroid dehydrogenase NA

Transforming growth factor β Transforming growth factor β NA

Androgen receptor Androgen receptor NA

Choriogenin NA Choriogenin
22

Table 9. Genes chosen for NanoString analysis of individual liver samples—Continued

[NA, not applicable]

Bass genes Brown bullhead genes White sucker genes

Epoxide hydrolase 1 NA Epoxide hydrolase 2

Catalase NA Catalase

Ferritin NA Ferritin

Type 1 and II deiodinases NA Iodothyronun deiodinase II

Transforming growth factor β 

Receptor-associated protein 1

NA Transforming growth factor β Receptorassociated protein 1

Apolipoprotein A1 NA Apolipoprotein A1

Phosphoenolpyruvate carboxykinase NA Phosphoenolpyruvate carboxykinase

Warm temperature acclimation 

protein

NA Warm temperature acclimation protein

3-β hydroxysteroid dehydrogenase NA Cytochrome C oxidase III

Hepcidins 1 and 2 NA 60S Ribosomal protein L7

Elongation factor 1α NA Reticluon 1

CYP19A1A (aromatase) NA Trypsin

Cystenin-rich protein NA NA

Metallothionein NA NA

Gene expression profiles were significantly different between male and female smallmouth bass for a 

number of genes at all sites evaluated for fall 2010 (Table 10) and spring 2011 (Table 11). 

Table 10. Regulation in the top 25 target genes between female and male smallmouth bass collected in the Great 

Lakes Basin in the fall 2010. 

[Bold, italicized values are significantly different between the sexes. Positive log2FoldChange values indicate higher 

expression in females. Mean counts are the average number of transcripts counted per sample. Adjusted P-values were 

determined according to Benjamini and Hochberg (1995) to account for the false discovery rate. <, less than]

Gene Mean 

counts log2FoldChange P value Adjusted Pvalue

Vitellogenin 150,590 5.40 <0.001 <0.001

Choriogenin 9,679 4.50 <0.001 <0.001

Estrogen receptor alpha 382 5.57 <0.001 <0.001

Cystenin-rich protein 18 2.42 <0.001 <0.001

Tata box binding protein 75 1.25 <0.001 0.003

Apolipoprotein A1 232,750 -0.87 0.021 0.159

Glucocorticoid receptor alpha 171 0.71 0.036 0.212

Epidermal growth factor receptor 56 -0.78 0.037 0.212

Estrogen receptor beta 1 67 0.66 0.064 0.270

Type 1 deiodinase 31 0.93 0.070 0.270

Transforming growth factor beta receptor 1 201 -0.46 0.066 0.270

Aryl hyrdrocarbon receptor 19 1.06 0.055 0.270

Fibroblast growth factor 38 -0.72 0.083 0.295
23

Table 10. Regulation in the top 25 target genes between female and male smallmouth bass collected in the Great 

Lakes Basin in the fall 2010.—Continued

[Bold, italicized values are significantly different between the sexes. Positive log2FoldChange values indicate higher 

expression in females. Mean counts are the average number of transcripts counted per sample. Adjusted P-values were 

determined according to Benjamini and Hochberg (1995) to account for the false discovery rate. <, less than]

Gene Mean 

counts log2FoldChange P value Adjusted Pvalue

Transforming growth factor beta 75 -0.75 0.098 0.322

Metallotheionen 1,229 -0.83 0.170 0.489

Superoxide dismutase 185 0.44 0.243 0.531

Androgen receptor alpha 128 -0.47 0.234 0.531

3 beta-hydroxysteroid dehydrogenase 15 -0.79 0.221 0.531

Warm temperature acclimation-related protein 918 -0.35 0.240 0.531

Aromatase 2 0.98 0.234 0.531

Type II deiodinase 225 -0.50 0.312 0.629

Thyroid hormone receptor alpha 4 0.81 0.314 0.629

Estrogen receptor beta 2 161 -0.33 0.334 0.640

Ferritin 7 0.29 0.397 0.686

B-actin 5,920 -0.52 0.382 0.686

Table 11. Regulation in the top 25 target genes between female and male smallmouth bass collected in the Great 

Lakes Basin in spring 2011.

[Bold, italicized values are significantly different between the sexes. Positive log2FoldChange values indicate higher 

expression in females. Mean counts are the average number of transcripts counted per sample. Adjusted P-values were 

determined according to Benjamini and Hochberg (1995) to account for the false discovery rate. <, less than]

Gene Mean counts log2FoldChange P value Adjusted P-value

Vitellogenin 203,706 11.78 <0.001 <0.001

Estrogen receptor alpha 707 5.43 <0.001 <0.001

Cystenin-rich protein 24 3.12 <0.001 <0.001

Choriogenin 14,919 6.55 <0.001 <0.001

Tata box binding protein 100 1.26 0.014 0.127

Transforming growth factor beta receptor 1 260 -1.10 0.021 0.136

Phosphoenolpyruvate carboxykinase 1,069 -0.62 0.020 0.136

CYP1A 2,004 -0.70 0.025 0.143

Androgen receptor alpha 138 -0.81 0.076 0.334

Type II deiodinase 193 0.89 0.082 0.334

Apolipoprotein A1 193,207 -0.51 0.087 0.334

Epidermal growth factor receptor 45 -0.58 0.068 0.334

Fibroblast growth factor 35 -0.52 0.109 0.386

Estrogen receptor beta 2 250 -0.70 0.159 0.522

HSP 70 113 1.84 0.170 0.522

Arginase 326 0.75 0.211 0.606
24

Table 11. Regulation in the top 25 target genes between female and male smallmouth bass collected in the Great 

Lakes Basin in spring 2011.—Continued

[Bold, italicized values are significantly different between the sexes. Positive log2FoldChange values indicate higher 

expression in females. Mean counts are the average number of transcripts counted per sample. Adjusted P-values were 

determined according to Benjamini and Hochberg (1995) to account for the false discovery rate. <, less than]

Gene Mean counts log2FoldChange P value Adjusted P-value

Superoxide dismutase 448 -0.44 0.246 0.666

Metallotheionen 4,254 -0.57 0.307 0.743

Beta catenin 133 -0.54 0.301 0.743

Glucocorticoid receptor alpha 229 0.45 0.343 0.751

Transforming growth factor beta 74 -0.47 0.341 0.751

Glutathione peroxidase 1 159 0.46 0.471 0.774

Hepcidin 1 19 0.34 0.385 0.774

Ferritin 9 0.51 0.462 0.774

Aryl hyrdrocarbon receptor 28 0.31 0.407 0.774

As a result gene expression from males and females was examined separately. Seasonal changes in gene 

expression were also observed in female (Table 12) smallmouth bass but not in males. More detailed 

site analyses, species comparisons, and associations of gene expression with other biological endpoints 

are underway. 

Table 12. Regulation of the top 25 target genes between seasons, fall 2010 and spring 2011, in female 

smallmouth bass collected in the Great Lakes Basin.

[Bold, italicized values are significantly different between seasons. Positive log2FoldChange values indicate higher 

expression in the Fall. Mean counts are the average number of transcripts counted per sample. Adjusted P-values were 

determined according to Benjamini and Hochberg (1995) to account for the false discovery rate] 

Gene Mean 

counts log2FoldChange P value Adjusted P-value

Warm temperature acclimation-related protein 5,998 3.47 < 0.001 0.006

Type 1 deiodinase 78 1.34 0.001 0.012

Heat shock protein 70 80 4.13 0.001 0.018

Arginase 229 1.85 0.011 0.125

Glucokinase 434 -2.34 0.021 0.191

Superoxide dismutase 316 0.81 0.050 0.380

Metallotheionen 2,567 1.94 0.117 0.766

Cytochrome P450 3A 733 -0.46 0.135 0.776

Insulin-like growth factor 1 397 -0.40 0.194 0.991

Glutathione peroxidase 1 147 0.07 0.911 1.000

Hepcidin 1 18 -0.13 0.939 1.000

Ferritin 9 -0.04 0.894 1.000

Estrogen receptor alpha 752 0.23 0.567 1.000

B-actin 5,698 -0.13 0.939 1.000

CYP17 4 0.85 0.313 1.000
25

Table 12. Regulation of the top 25 target genes between seasons, fall 2010 and spring 2011, in female 

smallmouth bass collected in the Great Lakes Basin.—Continued

[Bold, italicized values are significantly different between seasons. Positive log2FoldChange values indicate higher 

expression in the Fall. Mean counts are the average number of transcripts counted per sample. Adjusted P-values were 

determined according to Benjamini and Hochberg (1995) to account for the false discovery rate] 

Gene Mean 

counts log2FoldChange P value Adjusted P-value

Glucocorticoid receptor alpha 211 0.02 1.000 1.000

Catalase 2,014 0.17 0.852 1.000

Transforming growth factor beta 64 -0.24 0.955 1.000

Choriogenin 16,688 -0.05 0.934 1.000

Androgen receptor alpha 111 -0.28 0.694 1.000

Cystenin-rich protein 28 -0.15 0.930 1.000

Estrogen receptor beta 1 81 -0.06 0.956 1.000

Transforming growth factor beta receptor 1 182 0.03 0.735 1.000

Vitellogenin 241,913 -0.26 0.515 1.000

Heat shock protein 90A 2,393 -0.11 0.622 1.000

Water Analysis

The data from water analysis were used as part of a larger study documenting the presence of 

androgenic and glucocorticoid activity in watersheds throughout the Northeast and Great Lakes regions 

of the United States. Results are discussed in (Stavreva et al. 2012). 

Summary and Conclusions

The major objective of research for this study was to determine whether there were adverse 

effects on wild fish species in the Areas of Concern (AOCs) in the Great Lakes Basin . The suite of 

biological responses chosen was useful in comparing species, and site and seasonal differences. The 

biological responses indicate potential exposures to chemical contaminants leading to adverse effects on 

fish health. Species differences were obvious. For instance, bass appear to be more sensitive to 

induction of testicular oocytes, whereas all three species showed induction of vitellogenin in males. 

Brown bullhead and white sucker were more susceptible to tumor induction, both skin and liver, than 

were bass. The low sample sizes, particularly for responses that were sex and (or) age related, or related 

to reproductive (gonad) stage, do not allow for any definitive conclusions on the effects on fish 

populations or site differences. The wide geographical area included in this initial study led to difficulty 

in the collection of fish at the same stage of gonadal development, particularly in spring. Further 

analyses are necessary to understand individual responses, such as intersex or plasma vitellogenin, in 

regards to gonad stage, season, and reproductive hormone concentrations. Additional research is needed 

to determine factors contributing to these effects and identify sources. Further studies should be 

conducted that examine potential contributing factors, such as viruses, parasites, specific chemicals or 

chemical mixtures, that may be associated with the neoplasms and putative preneoplastic changes 

observed in skin, liver and testes. In order to remediate or restore habitat for healthy fish populations, it 

will be necessary to understand the risk factors and pathogenesis of the various lesions observed. This 

will require chemical analyses of the individual tissues in conjunction with histopathological analyses 

and gene expression. 
26

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