spider mediation of polychlorinated biphenyl transport and transformation across riparian
TRANSCRIPT
Clemson UniversityTigerPrints
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12-2012
Spider Mediation of Polychlorinated BiphenylTransport and Transformation Across RiparianEcotonesDiana DelachClemson University, [email protected]
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Recommended CitationDelach, Diana, "Spider Mediation of Polychlorinated Biphenyl Transport and Transformation Across Riparian Ecotones" (2012). AllDissertations. 1051.https://tigerprints.clemson.edu/all_dissertations/1051
SPIDER MEDIATION OF POLYCHLORINATED BIPHENYL TRANSPORT AND TRANSFORMATION ACROSS RIPARIAN ECOTONES
A Dissertation Presented to
the Graduate School of Clemson University
In Partial Fulfillment of the Requirements for the Degree
Doctors of Philosophy Environmental Toxicology
by
Diana Delach December 2012
Accepted by: Dr. Cindy M. Lee, Committee Chair
Dr. John T. Coates Dr. Peter van den Hurk Dr. David M. Walters
ii
ABSTRACT
Polychlorinated biphenyls (PCBs) contaminate the sediment of the
Twelvemile Creek / Lake Hartwell Superfund Site, and are known to be transported
throughout the resident biota via trophic transport. Riparian spiders have recently
become of interest because they are terrestrial organisms that have significant PCB
exposures derived from aquatic sources. Many riparian spiders primarily consume
insects emerging from contaminated aquatic systems, and these spiders can have a
body burden as high as 2900 ng/g lipid. These emergent insects carry contaminants
out of the river and into the riparian zone where they are captured by spiders,
which effectively directs the contamination towards arachnivorous predators such
as lizards, frogs, and birds.
The enantiomeric fraction (EF) was measured for chiral congeners to
investigate the role of biological systems on transport of PCBs between trophic
levels. The EF values varied between spider species, and indicate that foraging
behavior may influence those parameters. Tetragnathid and basilica spiders were
most similar, whereas both were different from araneid spiders despite all three
spiders belonging to the same order of spiders. All spider taxa were significantly
different from the aquatic prey source Chironomidae.
Two approaches were used to confirm that spiders have the capacity to
metabolize their PCB body burdens. Tetragnathidae spiders were collected along
Twelvemile Creek, their enzymes isolated, and exposed to individual non-‐planar and
co-‐planar congeners. PCBs 88 and 149 were incubated with S9 fractions (extracts
iii
containing microsomal and cytosolic enzymes) from the spiders and qualitatively
assessed for evidence of biotransformation. Tandem mass spectroscopy provided
evidence to support the hypothesis that spiders have the capacity to biotransform
PCBs. Additionally, PCB 61 was incubated with S9 fractions for quantitative analysis
of a planar congener. Numerous compounds were detected after exposure, but OH-‐
PCB 61 was measured at 1.63 (±0.35 SD) ng/g lipid at the Reese Mill sampling site
for enzymes obtained with liquid nitrogen, thus indicating that spiders have the
capacity to metabolize their PCB body burden. In the second approach mass
spectroscopy of whole spider extracts of spiders obtained along the Twelvemile
Creek arm of Lake Hartwell provided structural evidence that spiders can transform
their body burden of PCBs to OH-‐PCBs for congeners with six or fewer chlorines.
Lastly, webs are hypothesized to play a protective role in spider
ecotoxicology. Tetragnathid spiders are able to recycle approximately 90% of their
web material without metabolizing it, thus creating an opportunity for web material
to act as a storage location external to the body. Concentrations in webs ranged
between 154 and 356 ppm, whereas concentrations for spiders at the same
sampling locations ranged from 284 ng/g lipid to 2900 ng/g lipid. The enantiomeric
fraction was also utilized to determine if storage in webs is an enantioselective
process. Results indicate that web storage is enantioselective for PCB 149, with the
(-‐) enantiomer being preferentially retained in web materials. This differs from that
seen in spider samples, where the EF is approximately racemic.
iv
These investigations examined the exposure and toxicological model for
spiders, with the intent of aiding understanding the role spiders play in mediating
transport and transformation across riparian ecotones. Results indicate that
spiders may use a variety of strategies to manage their PCB body burdens ranging
from enantioselective uptake of parent compounds, metabolism to hydroxylated
metabolites, and transfer to web material. Understanding spider mediation of PCB
transport and transformation can help development of strategies that both manage
and mitigate the risks posed to the environment by PCBs at Twelvemile Creek and
Lake Hartwell.
v
DEDICATION
I would be remiss if I didn’t note the contribution on the part of Henry,
Barbara, and Alyssa Delach to this body of work. Their emails, phone calls, and
cards were a constant source of encouragement and support, without which the
completion of this research would have been far more taxing. They provided comic
relief when it was most necessary!
vi
ACKNOWLEDGEMENTS
First I must acknowledge the contribution Dr. Cindy Lee has made to this
work. She took on not only the role of research advisor, but also mentor for myself,
my labmates, and many others across the graduate school. I hope that my future
endeavors will serve to support your already superior reputation.
My committee members had a great impact on this project as well, being sure
to point out not only the points that needed deletion, repeating, or revising, but also
the successes along the way. I learned much from their expertise and kindness.
My labmates– for teaching me everything from how to order supplies to
sample preparation to winning strategies in the faculty-‐student soccer games. The
rewards of working with such fun, intelligent people cannot be underestimated. In
particular, Viet Dang’s experience and patient teaching made this work possible. I
hope that we all have walked away with at least some good stories from our time
spent constructing spider habitats, prowling the river at night for bugs, and
spending long days/evenings/nights in the lab together.
My departmental colleagues in both Environmental Toxicology and
Environmental Engineering have also enriched this work. Your support in and out
of the lab has served to enhance my research experiences. In particular, thank you
to Andrea Hicks, Tim Sattler, Jessica Dahle, Lee Stevens, Yogendra Kanitkar, Kay
Millerick, and Meric Selbes. Anne Cummings’ dedication to maintaining smooth
operation in the labs and with the instruments facilitated the completion of this
work, as well as the work of the other graduate students in the Rich Laboratories.
vii
TABLE OF CONTENTS
Page
TITLE PAGE……………………………………………………………………………………………….. i ABSTRACT...………………………………………………………………………………………………. ii DEDICATION………………………………………………………………………………………………. v ACKNOWLEDGMENTS……………………………………………………………………….……….. vi LIST OF TABLES………………………………………………………………………………………… ix LIST OF FIGURES………………………………………………………………………..………………. x CHAPTER
1. Literature Review Introduction…………………………………………………………..………………………... 1 Compound background………………………………………………………………........ 3 Study area…………………………………………...…………………………………….…….. 4 Arachnid role at Twelvemile Creek / Lake Hartwell
Superfund site……..………………………………………………………………… 7 Ecological role of spiders………………………………………...……………………...… 8 The Spider Family Araneidae…………..………………………….……………..….......12 Exposure…………………………………………………………..…………………….............. 15 Excretion…………………………………………………………………….…………………… 19 Webs…………………………………………………………………..…………………………… 21 PCB Transformation ……………………………………..……………………………......... 25 PCB Metabolism by Spiders…………………………………………………………….... 32 Summary……………………………………………..…………………………………………... 33 References………………………………………………………………………………...…….. 34
2. Chiral Signatures of PCBs in Riparian Spiders Introduction…………………………………………………………………………………….. 47 Materials and Methods……………………………………………………………………... 50 Results…………………………………………………………………………………………….. 54 Discussion…………………..…………………………………………………………………… 60 Conclusions……………………………………………………………………………………… 64 References……………………………………………………………………………………….. 65
viii
Page
3. Spider Metabolism of PCBs: in vivo and in vitro Investigative Approaches
Introduction……………………………………………………………………………………..68 Materials and Methods…………………………………………………………………….. 70 Results…………………………………………………………………………………………….. 78 Discussion……………………………………………………………………………………….. 90 Conclusions……………………………………………………………………………………… 99 References……………………………………………………………………………………….. 100
4. Webs as Substrate for PCB Partitioning Introduction…………………………………………………………………………………….. 106 Materials and Methods……………………………………………………………………... 107 Results…………………………………………………………………………………………….. 111 Discussion……………………………………………………………………….………………. 119 Conclusions……………………………………………………………………………………… 125 References…………………………………………………………………………………..…… 126
5. Conclusions and Recommendations
Conclusions…………………………………………………………………………………….. 129 Recommendations for future work…………………………………………………… 130
APPENDICES
A: Supplemental Figures for Chapter 2……………………………………………... 134 B: Supplemental Tables for Chapter 2………………………………………………. 136 C: Supplemental Table for Chapter 3…………………………………………..…….. 137
ix
LIST OF TABLES Table Page 1.1 Comparison of spider species ecological roles………………………… 12
2.1 GPS coordinates for EPA sampling sites………………………………….. 52
4.1 Web sampling site locations and distances…...………………………… 108
4.2 ΣPCB content in spiders and webs at each sampling location………………………………………………….…….. 112
4.3 Homolog distributions in spiders and webs at
the Reese Mill sampling site………………………………………… 113 B.1 Environmentally stable chiral congener
substitution patterns ………………………………………………….. 136
B.2 Spider pooled-‐sample sizes for each sampling location……………………………………………………………………….136
C.1 SIM paramenters used to screen for PCB metabolites……………… 137
x
LIST OF FIGURES
Figure Page
1.1 Map of Twelvemile Creek / Lake Hartwell Superfund Site………..…………………………………………………… 6
1.2 Tetragnathidae exposure model…………………………………………….. 9 1.3 Spider anatomy……………………………………………………………………... 20 1.4 Different types and functions of silks produced
by orb weaver spiders…..…………………………………………….. 23 1.5 Metabolism of PCBs…………………………………………………………..…… 27 1.6 Thyroid hormone regulation………………………………………………….. 31
2.1 Map of sampling locations……………………………………………………… 51 2.2 Measurements of EF for three spider species and
Chironomidae averaged across all analyzed sites…..………..………………………………………………...................... 56
2.3 NMS plots for both spiders and midges…………………………………... 59
3.1 Map of sampling locations……………………………………………………… 73 3.2 Tetragnathidae in vivo analysis,
SIM settings for m/z = 324………………………….……………….. 80 3.3 Tetragnathidae in vivo analysis,
SIM settings for m/z = 353……..……..…………………………….. 81
3.4 Chromatogram for PCB 88 enzyme incubations……..……………….. 83 3.5 Chromatograms for enzymes with liquid nitrogen
and incubated with PCB 88 at Reese Mill and Robinson Bridge…………….………………………………..…… 85
xi
Figure Page
3.6 Chromatograms and spectra for enzyme incubation with PCBs 88 and 149 at Robinson Bridge……………………. 86
3.7 Chromatogram for positive control………………………………………… 87
3.8 Chromatogram for incubation with PCB 61…………………………….. 88
3.9 Quantification of 2-‐OH-‐PCB 61 after incubation
with S9 fraction…………………………………………………………... 89
3.10 PCB 88 and potential biotransformation pathways…………………. 92
3.11 PCB 149 and potential biotransformation pathways ………………. 94
3.12 PCB 61 and potential biotransformation pathways…………………. 95
4.1 Map of web sampling locations………………………………………………. 109
4.2 Σ PCB concentration for spiders and webs…………………………....... 112
4.3 Homolog patterns of PCB concentrations in spiders and webs...…………….......................................................... 114
4.4 EF values for spiders and webs……………………………………………..... 117
4.5 NMS plots for spiders and webs……………………………………………… 118 A.1 Tetragnathidae EF by site for all congeners…………………………….. 134 A.2 Araneidae EF by site for all congeners……………………………………. 134
A.3 Basilica EF by site for all congeners…………………………………………135
A.4 Chironomidae EF by site for all congeners………………………………. 135
1
CHAPTER ONE
LITERATURE REVIEW
Introduction
Polychlorinated biphenyls (PCBs) contaminate the sediment of the
Twelvemile Creek / Lake Hartwell Superfund Site (US EPA, 2004), and are known to
be transported throughout the resident biota via trophic transport (Walters et al.,
2008). Riparian spiders have recently become of interest because they are
terrestrial organisms that have significant PCB exposures derived from aquatic
sources. Many riparian spiders primarily consume insects emerging from
contaminated aquatic systems, and these spiders can have body burdens greater
than 5000 ng/g lipid (Walters et al., 2010). These emergent insects carry
contaminants out of the river and into the riparian zone where they are captured by
spiders, which effectively directs the contamination towards arachnivorous
predators such as lizards, frogs, and birds.
A better understanding of how spiders function as biovectors will elucidate
how exposure to PCBs is mediated as the contaminants cross ecotones, and can
inform development of policies aimed at mitigating the risks from those
contaminants to humans and wildlife. In particular, investigating PCB uptake,
biotransformation, and storage by spiders can clarify understanding of PCB fate and
transport in the riparian zone at Twelvemile Creek / Lake Hartwell., as well as other
2
aquatic systems contaminated with persistent, bioaccumulative pollutants, to
inform remediation strategy and policy decisions.
Analysis of chiral congeners can indicate biotransformation of PCBs in the
food web. The enantiomeric fraction (EF) is the parameter that is commonly used to
quantify chiral character (See Chapter 2 for a detailed explanation of how the EF is
calculated). The EF can change when the fate and transport parameters change.
One process that can change EF is metabolism, which has been indicated as a source
for enantiomeric enrichment in some species; for example, Buckman et al. (2006)
determined that metabolism in fish produced OH-‐PCBs.
Biochemical assays can also help to elucidate any metabolic pathways that
may exist. If enzymatic activity in PCB-‐exposed spider can be quantified, an increase
in activity may indicate metabolism of PCBs. Similarly, enzymes isolated from
spider tissue and incubated with PCBs may yield metabolites. If these metabolites
can be quantified and their structure confirmed, this, too, can provide the first
evidence of spider detoxification capabilities.
There may be other mechanisms by which spiders regulate an increasing
body burden. Spider webs may function as an outer-‐body tissue, providing a place
to sequester contaminants from sensitive organs. Comparing the PCB content and
congener patterns of web material can begin to describe molecular toxin
management strategy by spiders.
3
Compound Background
Polychlorinated biphenyls are synthetic compounds with a varying number
of chlorines oriented about two biphenyl rings. There are 209 congeners that can be
sorted into different homolog groups, ranging from one chlorine (mono) to ten
chlorine atoms (deca) oriented about the biphenyl rings. Each of the homolog
groups exhibits different fate and transport trends, as the physiochemical properties
are affected by both the chlorine content and orientation. For example, PCB 2, with
an ortho-‐situated chlorine has a log Ciw of -‐4.54; whereas, PCB 4 has a para-‐chlorine
and a log Ciw value of -‐5.19, where Ciw is the solubility of the contaminant in water
(Schwarzenbach et al., 2003). While chemical composition is identical, the change in
substitution pattern between o-‐Cl to p-‐Cl decreases the solubility in water. As
chlorine content increases, the tendency to partition into lipophilic media increases.
All PCBs have low aqueous solubility, high thermal stability, and excellent dielectric
properties. Their prolific use led to significant exposure in the environment. The
stability that makes PCBs suitable in industrial processes is the same that make
them legacy compounds in the environment that experience both long-‐range
transport and large-‐scale distribution (Tanabe et al., 1983).
Production of PCBs began in the 1920s and continued in the United States
until public and scientific concern ceased their manufacture in the 1970s. Fifty
years of production yielded approximately 150,000 metric tons of PCBs (deVoogt
and Brinkman, 1989). Discovery of their human health hazards led to the ban of
their use in 1976 under the Toxic Substances Control Act (U.S. EPA, 1976). PCBs
4
have been detected in all environmental compartments, and matrices ranging from
sediment to fish tissue to human blood. Trophic transfer is one of the main routes of
PCB transport, as their high lipophilicity creates a tendency to both bioaccumulate
and biomagnify through the food chain. PCB congeners can cause a variety of
physiological problems, ranging from thymus, spleen, and liver hypertrophy, as well
as increased liver lipids (Safe, 1990). They may also be responsible for alteration of
Ca2+ homeostasis in neuronal transmission (Kodavanti et al., 1995). There is
evidence that ortho-‐substituted PCBs can influence dopamine concentrations via
inhibition of the tyrosine hydroxylase (Seegal et al., 1990; Shain et al., 1991).
Study Area
The Sangamo-‐Weston Corporation manufactured capacitors using PCBs as
dielectric fluid in Pickens, SC, between 1955 and 1977 (Figure 1.1) (Brenner et al.,
2004). Production using PCBs was ceased because of the impending 1976 ban on its
use in the United States, as it had been linked to cancer and other human health
risks. Improper disposal of production waste led to the contamination of the
sediment in Town Creek, a tributary of Twelvemile Creek and then Lake Hartwell. A
fish advisory was established by the EPA in 1976, as the concentrations of PCBs in
fish greatly exceeded the limit set by the Food and Drug Administration for
commercial seafood (U.S. EPA, 1980; SCDHEC, 2006).
The Lake Hartwell / Twelvemile Creek site was placed on the National
Priority List in 1991, and was later named a Superfund site. The Record of Decision
5
designated two operational units: OU-‐1 addressed the land sources of
contamination, namely the Sangamo-‐Weston plant and six satellite disposal areas,
and OU-‐2 addressed the pollution starting with sediment and surface water
contamination up to fish and other contaminated biota (U.S. EPA, 1994). OU-‐2
includes aquatic habitats in Town Creek, Twelvemile Creek, and Lake Hartwell
(Figure 1.1).
6
Figure 1.1 Map of the Twelvemile Creek / Lake Hartwell Superfund site.
Adapted from Brenner et al. (2004).
7
Arachnid Role at Twelvemile Creek / Lake Hartwell Superfund Site
Recent efforts to monitor the site have determined that the contamination is
moving from the aquatic compartment to the terrestrial compartment of the
landscape (Walters et al., 2008, 2010). Contaminated sediments provide habitat
space for larval aquatic insects. Upon maturation, these invertebrate
metamorphose into winged adults capable of transporting allochthonous carbon,
nitrogen, and PCBs from the contaminated sediment to the neighboring terrestrial
system. Such insects are known as subsidy insects. These emergent insects then
become prey for terrestrial predators. Walters et al. (2010) calculated that avian
wildlife in the Twelvemile Creek watershed, both resident and transient, exhibit PCB
concentrations that exceed threshold limits for negative effects. Spiders are of
particular interest, as they consume primarily insects, and some families can be
considered to be interface specialists, consuming only aquatic species.
Arachnivorous predators, such as lizards, amphibians, and birds, consume spiders.
It is believed that spider-‐mediated transport across the ecotone is a dominant route
into the terrestrial compartment (Walters et al., 2008, 2010; Raikow et al., 2011),
though the mechanisms behind this transport require further investigation.
To date, biochemical pathways of contaminant metabolism in spiders have
yet to be described in the literature by either entomologists or biochemists. Their
ecological function has been described, as has their physiology and diet, but there
are lingering questions about their ability to detoxify and metabolize toxicant body
8
burden. Characterization of present metabolites via tandem mass spectroscopy, or
identification of enzymatic pathways using biomarker suites may contribute to a
more complete understanding of how this process may take place.
Ecological Role of Spiders
Understanding the ecological roles fulfilled by spiders provides insight into
how they may acquire contaminants, how their body burden may be transformed, or
how they facilitate transport of PCBs to other trophic levels. Spiders fulfill a variety
of roles dependent upon where they reside in the ecosystem. Spider families and
species are typically defined by their predation type (Foelix 1982), but will also be
classified by their location within the ecosystem for the purposes of this review.
The foraging habits of spiders directly influence their exposure. Riparian
spiders prey upon aquatic insects, and consume only soft tissues, so capturing the
insects prior to the hardening of the exoskeleton results in more food for spiders
without exerting extra energy to consume more prey. When prey is unavailable and
stored energy (lipids) are utilized the concentrations of contaminants will be
affected. Mobilization of the lipid tissue re-‐exposes the spider to the contaminants,
which may be an important route of exposure due to the “wait and see” foraging
strategy. The slow metabolism of spiders coupled with a stationary predation
technique allows the spider to live for long periods of time without food. Spiders
are consumed by a variety of predators, including but not limited to arachnivorous
birds such as the Carolina wren, lizards, and even other spiders (Figure 1.2). The
9
role of webs in toxicology of spiders has not been previously investigated, but
further discussion of relevant hypotheses is included under the “Excretion” heading
below.
Figure 1.2 Tetragnathidae exposure model. Most tetragnathids are obligate
riparian species and specialized predators of aquatic insects.
The competitive nature of spiders has been much debated. Tretzel (1955)
developed a theory of “intragenerische isolation,” or niche partitioning within
10
genera. He postulated that differences in reproductive seasons, daily patterns of
activity, and horizontal habitat utilization are the result of evolved differences. This
concept builds upon the work of Bristowe (1939, 1941), who stated that different
habitats house different species because they can provide a variety of niches,
resulting in species that specialize by insect size, insect temporal patterns of
activity, and insect modes of transportation. This has been expanded upon by
Łuczak (1963) who found that as the weather patterns changed the niches
expanded and contracted accordingly, resulting in a shifted pattern of community
structure. This interspecific competition theory has been widely accepted. It
explains the evolutionary activity that gave rise to the differences between the three
spider taxa examined in this dissertation: Tetragnathidae, Araneidae, and basilica.
Tetragnathid spiders are specialists of aquatic insects, so they are an ideal
model taxa for investigating aquatic-‐to-‐terrestrial exposure and for making
comparisons to other spiders with different predation tactics. Spiders have evolved
under food-‐limited conditions (Foelix, 1982). Generalist feeding patterns are
reflective of this, as are their low metabolic rates (Carrel and Heathcote, 1976), and
food storage capacity within the digestive system (Foelix, 1982). As sit-‐and-‐wait
foragers, spiders have evolved to expend little energy seeking prey, and to most
efficiently utilize the food intake they do have. Spiders have evolved to fast for long
periods of time, and are disinclined to change foraging behavior due to increases in
prey availability, (Greenstone, 1979). Terrestrial spiders have lived up to 200 days
without feeding (Kaston, 1970).
11
Understanding of placement of spiders in the food web at the Twelvemile
Creek / Lake Hartwell Superfund site has been elucidated in numerous ways. First,
an assessment of the prey captured by webs indicates that spiders predate on
aquatic insects (Walters et al. 2008; personal observation). The variation in insect
contribution has been confirmed by carbon and nitrogen isotope ratios due to the
fact that gut contents are not applicable due to their external digestion (Akamatzu et
al., 2004). Studies also demonstrate that emergent insects constitute a large
proportion of the spider diet (Walters et al., 2008). Walters et al. (2010)
determined that the PCB concentration patterns of chironomids and other emergent
insects did not correlate well with those seen in spiders. The poor correlation could
be due to the fact that the insects move too fluidly up and down river to be good
indicator species at each sampling site; or, they may not represent a large enough
proportion of the spider’s diet to have nearly identical patterns.
Spiders have not been the subjects of toxicology tests to date; rather the
toxins they produce have been of more interest. However, when spiders are
exposed to contamination through the food web they become a part of the
ecotoxicological processes of the ecosystem. Trophic transfer of contaminants will
expose the spiders to both parent compounds and their metabolites. When
exposure of invertebrates can be defined qualitatively and quantitatively we can use
that information to investigate the biovectors of the system and to identify remedy
options to manage the risks of contaminants to wildlife.
12
The Spider Order Araneae
Many spiders are found in the interior of forest patches, spinning webs in the
various trees and shrubbery (Table 1.1). The three spider types investigated herein
belong to the same order, Araneae. One of the investigated families of spiders is
Araneidae, which ranges from riparian ecotones to upland terrestrial areas. They
are solitary spiders that spin orb shaped webs, which are maintained on a near daily
basis (Eisoldt et al., 2011, 2012). Araneid spiders will consume the web from the
previous day and reconstruct a new assembly. The angle of the web is vertical,
which allows for the capture of flying terrestrial insects. Araneidae spiders emerge
in the spring and are active through late fall (Foelix, 1982). During the winter they
retreat underground where they suspend function until warmer temperatures
facilitate motility and predation.
Table 1.1 Comparison of Spider Ecological Roles
Tetragnathidae, which is the main focus of these investigations, is a family
separate from that of Araneidae, however they both fall in the same order, Araneae.
Tetragnathids are obligate riparian predators, and as such are important terrestrial
Feature Araneidae Tetragnathidae Basilica Habitat Location Facultative riparian Obligate riparian Shoreline shrubbery Solitary or communal Solitary Solitary Communal Web orientation Vertical Horizontal Messy Web type Orb Orb Orb Web maintenance Individual, nightly Individual, nightly Communal over year Invertebrate types in diet
Terrestrial, or mix of terrestrial & aquatic
Aquatic Mix of terrestrial & aquatic
13
predators of aquatic emergent insects (Baxter et al., 2005). This has been confirmed
at the Twelvemile Creek Superfund site through use of stable isotope analysis
(Walters et al., 2008). A variety of processes contribute to riparian spider exposure,
including but not limited to contaminant uptake by benthic, larval insects,
maturation, and predator-‐prey interactions (Walters et al., 2010).
Tetragnathidae spiders begin to emerge in March and are ubiquitous along
Twelvemile Creek until about September. They will feed opportunistically upon any
insects that entangle themselves in their orb-‐shaped webs. Their web structure and
proximity secures them in this riparian niche (Gillespie, 1987). Their webs are
angled so as to capture the insects as they emerge from the water column as adults,
but also are spun with silk that is likely too weak to capture terrestrial insects
(Foelix, 1982). To obtain tangled insects the spider travels across the web, subdues
the prey by wrapping it in silk, and then moves it with the checliare (the outer jaws)
to the outer part of the web where it consumes the insect. Wildlife values to assess
risk were calculated to gauge the importance of tetragnathids in the diets of
arachnivorous birds (Walters et al., 2008, 2010). The analysis indicated that the
spiders are a viable and important pathway of contaminant transfer to birds at the
Twelvemile Creek / Lake Hartwell Superfund site.
Patterns in activity are distinctive and correlate with habitat type.
Tetragnathids have been able to survive in many habitat types, but they thrive near
open areas of water with many branches and twigs. This habitat type may be
present in sheltered stream areas, or open lake areas. Gillespie and Caraco (1987)
14
found that spiders around lakes were more prone to relocating webs, whereas
spiders along streams were more stationary. They attributed these patterns to
differences in risk; stationary behavior is indicative of low risk, enhanced by the
amount of vegetation presenting hiding places from arachnivorous predators.
Exposed lake areas also do not have the same amount of shade, which results in
higher temperatures and faster web desiccation, resulting in higher energy
expenditures for the spiders to maintain the webs.
Basilica spiders (Mecynogea lemniscata) belong to the Araneidae family, but
have some unique characteristics distinct from other family members. Basilica
weave communal webs that are maintained over the course of the year (Foelix,
1982). These webs are usually constructed in shoreline shrubbery to allow
predation of both aquatic and terrestrial prey. Over the course of the seasons, the
web becomes messier and messier as the commune continually patches any damage
done to the web procuring prey. These spiders may exhibit a different
contamination profile due to their varied prey sources. Basilica spiders are similar
to Tetragnathidae spiders in that their diet is largely constituted of aquatic prey due
to their proximity and specialization to the riparian ecotone.
PCBs at Twelvemile Creek are transfered between environmental
compartments due to biotransportation by emerged aquatic insects, and are
deposited across the ecotone by these mechanisms. The net flux is out of the aquatic
compartment and into the terrestrial; however, there is also some transfer in the
opposite direction when spiders die and fall from their webs back into the river.
15
While the transfer to the terrestrial ecosystems may reduce the PCB load in Twelve
Mile Creek over time, the problem of PCB contamination is not so much solved as it
is distributed and diluted over a larger area. These deposits can return to the river
in time if they percolate into the ground water, or physical forces such as erosion
reintroduce contaminated soil and plant material to the river. An alternate
transport pathway may see PCB toxicity expressed in the terrestrial system by
oligochetes and other organisms that rework the soil, plant matter, and spider litter.
Exposure
Riparian spiders are exposed to PCB contamination at the Twelvemile Creek
/ Lake Hartwell site via trophic transfer. Spiders consume contaminated emergent
insects and redirect contaminant cycling away from the aquatic zone. Biological
processes such as selective protein binding, tissue transport, and metabolism can
affect and change the contamination profile to which spiders are exposed. For
example, these processes can produce enantiomeric enrichment of chiral congeners,
which results in spiders having different EF values than observed in their prey.
In vivo and in vitro studies can be completed to more fully understand the
mechanisms and effects of a given compound. Such studies must be done so as to
complement each other, too, rather than just one or the other. In vivo assays may
yield information about the biotransformation rate, whereas in vitro parameters can
more fully describe the enzymatic activity resulting from field exposure (U.S. EPA,
16
2004). Conducting these studies in tandem allows for collection of complementary
information.
Life stage contributes to the varying accumulation of contaminants in
ecosystem components. Toxicants vary in their targets, but also when those targets
are susceptible to exposure. Organisms are typically most sensitive to toxicant
exposure when in early development stages, particularly during organogenesis
when the organs develop while in utero, which is when metabolic rates are high, and
all nutrients are utilized for either energy production or growth (Klassen, 2008).
Once an organism reaches full maturity and the metabolism slows and growth stops
the potential for preventative sequestration of toxicants into lipophilic tissues is
greater, which protects the organism from toxicant action. A toxicant body burden
is not inherently dangerous –contaminants pose a threat only when they interact
with target molecules (Walker et al., 2006). It is protective when toxicants are
sequestered in lipid tissue away from the target sites.
The route of uptake for spiders at Twelvemile Creek, is trophic transfer
rather than uptake from the environment (Walters et al., 2008). The contamination
of the Lake Hartwell/Twelve Mile Creek Superfund site is confined to the sediments
in the aquatic system. PCBs are also unlikely to partition into chitin, the material
that makes up the exoskeleton of spiders, so exposure from contact with the
terrestrial environment is negligible. Spiders initiate digestion outside of the body
by regurgitating digestive fluid onto the prey. The spider then ingests a drop of the
predigested fluid and repeats until the prey is mostly consumed. The chelicae are
17
used to break apart the prey such that the soft tissue may be accessed. After
feeding, all that remains is a small ball of cuticular parts (Foelix, 1982). Metabolism
continues in the sucking stomach. The aquatic insects they consume in this manner
transfer contamination from the sediments of the river system to the spiders.
Due to the exposure through trophic transfer, it is important to first
determine the exposure on the part of those emergent insects. Their life cycle
places them in the sediments for the first few instars of their development, which
results in high levels of exposure to lipophilic contaminants that have sorbed onto
the sediment during the most susceptible time of their development. They pump
oxygenated water across their gills to breathe. They may be exposed to
contaminants in the water column this way, but can also export contamination into
the water column with each “exhale.” We can infer that the biotic contaminant
concentration lies somewhere between what would be predicted by equilibrium
with the water and equilibrium with the sediment; typically greater than would be
predicted by water exposure, but less than sediment exposure predictions. A
theoretical concentration at equilibrium for PCBs needs to relate organic carbon
content and octanol partitioning to each other, which, for PCBs, results in the
following relationship:
𝐾!"!#$% = 2.3 × 𝐾!"!.!" (Equation 1)
where Kilipoc is the partitioning coefficient for lipids and organic carbon, and Kow is
the partitioning constant for octanol and water (Schwarzenbach et al., 2003). While
these predictive equations for Kilipoc and Kilipw are useful, the measured quantity
18
known as the biota-‐sediment bioaccumulation factor (BSAF) is defined in Equation
2 as:
𝐵𝑆𝐴𝐹! =!!"#$!!"
(Equation 2)
where Ciorg is the concentration in the organism, and Cis is the concentration in the
sediment. BSAF can be experimentally determined via field samples. BSAF values
are seen to increase with increasing Kiow values for the contaminants, until the Kiow
increases above a value of 107, because compounds with a log Kiow above 7 are
usually too large and lipophilic to partition past the polar head groups in a
membrane.
Predictions for systems at equilibrium prove challenging enough; however, it
must be noted that river systems are open systems, and there may be net flux of
volatile contaminants in or out of the system. For PCBs this flux has been proven to
be both highly temperature dependent and significant. It is believed that PCBs
volatilize out of warm systems and are transported through the atmosphere until
the temperatures are reduced such that net flux is into water. Such behavior has
resulted in PCBs appearing in snow in Antarctica despite the absence of direct
exposure on that continent (Tanabe et al., 1983). At the Twelvemile Creek / Lake
Hartwell system, volatilization may be an important source of PCBs to tetragnathid
webs, which are suspended directly over the water column. If such behavior is
occurring, then spider exposure models need to incorporate this exposure pathway.
19
Excretion
Excretion completes detoxification of toxicants. Lipophilic contaminants are
removed from the organism via solid waste, whereas more hydrophilic
contaminants are excreted with liquid waste. PCB excretion by spiders is complex
in part because they only excrete solid waste. Water must be sourced from prey, so
waste is typically concentrated and dehydrated in the cells where the diverticula of
the midgut extends into the coaxe of the spider’s legs (see Figure 1.3 for anatomy),
though some spiders have a developed midgut area that penetrates the area
between the eyes (Foelix, 1982). Underlying interstitial tissue may also store waste
as crystals once the capacity for storage is exhausted. Guanocytes also serve to
store metabolites as crystals, and may form a cell layer under the hypodermis. The
midgut widens to form the stercoral pocket, or cloacal chamber. On either side of
the stercoral pocket are two thin evaginations called Malpighian tubes. Metabolites
and substances to be removed from the body are concentrated and stored before
they are expelled into the lumen of the Malpighian tubile. Guanine, adenine,
hypoxanthine, and uric acid are the main excretory products, all of which are
concentrated as crystals. The Malpighian tubules feed into the stercoral pocket,
which connects to the anus. Excrement stored in the stercoral pocket periodically
exits the body via the anus. Evolution of orb-‐weavers like Tetragnathidae and
Araneidae has evolved such that the coaxe of the walking legs no longer function to
collect and then excrete waste through the coaxal gland duct (Foelix, 1982). It may
be possible for the PCBs to be crystallized as part of this waste, and sequestered
20
away from the sites of action due to their low solubility in water. Spiders may also
be able to further metabolize OH-‐PCBs and excrete them as quinones or catechols.
Figure 1.3 Spider Anatomy. Adapted from Foelix (1982).
Exoskeleton molts are not expected to influence these concentrations or
function as an excretion pathway due to their high chitin concentration. Chitin is a
biotic macromolecule with functionality similar to both carbohydrates and proteins.
They have high heteroatom content, ring structures, and many functional groups.
The compound does not have much lipophilic character; thus, PCBs are unlikely to
partition into the medium. Being more hydrophilic, the metabolites may partition
into the exoskeleton, but this has yet to be investigated. Studies on other
invertebrates found that when insects shed their exoskeletons the contaminant load
is not reduced; rather, it is concentrated within the soft body tissue (Bartrons et al.,
21
2007). When aquatic insects have just emerged, their exoskeleton has not
hardened. During this so-‐called teneral stage, spiders could have greater exposure
to PCBs and their metabolites. The absence of a thick, chitin-‐rich exoskeleton makes
the soft tissue of those organisms more available to spiders, and facilitates the
trophic transfer of PCBs.
Ecdysone is the molting hormone in arthropods (Chang, 1993) and belongs
to the same gene family as the vertebrate thyroid hormone (Laudet, 1997). Crabs
exposed to oil spills were observed to exhibit different molting patterns as a result
of exposure to thyroid disrupting compounds (Oberdörster et al., 1999), and
supported hypotheses that PAHs from the oil may influence the expression of
ecdysone. Additionally, PCBs were investigated as they have been demonstrated to
interfere with the thyroid hormone system in vertebrates (Cheek et al., 1999;Goldey
et al., 1995;Koopman-‐Esseboom et al., 1994). In those studies the PCBs were not
found to induce molting in arthropods. These studies indicate that species exposed
to PCBs would not molt more than would be expected in clean habitats.
Webs
Another potential excretion pathway is web production. Web structure and
composition has been extensively studied (Herberstein et al., 2000; Higgins and
Rankin, 1999; Opell, 1998). Orb-‐weaving spiders, which are the subject of this
dissertation, rely heavily on silk throughout their entire life cycle (Foelix, 1982).
Spiderlings will send up a small string of silk and parachute on the breeze to
22
disperse from the rest of the brood. Webs are used by adults to both capture prey
and as a location for their mating habits. Silk is also used to create a nest for
fertilized eggs until the spiderlings emerge. Additionally, the webs provide a surface
for pheromone deposition. Males are attracted to females when they come into
contact with pheromones that are embedded in the lipid matrix of the web (Schulz
and Toft, 1993). Orb-‐weaving spiders produce and enlist up to seven different types
of silk (Figure 1.4), each with unique properties and functions (Vollrath and Selden,
2007). Silk is composed of some proteins, carbohydrates, and lipids so as to resist
degradation from ambient humidity. In addition, the sticky substance on the web is
acidic, approximately pH 4, such that the web is protected from bacterial
degradation (Foelix, 1982).
23
Figure 1.4 Different types and functions of silks produced by orb weaver spiders. Adapted from Eisoldt et al. 2011.
Orb-‐webs are constructed such that they use a minimum of resources – just
0.1-‐0.5mg of silk, and a maximum of thirty minutes for construction (Foelix, 1982).
Tetragnathidae web orientation is slightly tilted from vertical, allowing it to
efficiently capture aquatic subsidy insects (Gillespie, 1987). Tetragnathidae webs
are orb-‐shaped where there is ample space, but silk tangles are present all along the
bare branches wherever room is available, thus maximizing the opportunity to
24
capture prey. The close proximity to the water increases probability of capture
partly because emergent insects do not need to travel far before encountering the
webs, but also because the insects that emerge are just barely mature.
Overall, spider silk is more hydrophobic than hydrophilic to help webs
withstand precipitation, humidity, and aridity (Foelix, 1982). The hydrophobicity is
accomplished by glycoproteins and lipids, which coat the silk to prevent desiccation
and enable prey capture (Opell and Bond, 2000). Lipids, and perhaps glycoproteins,
favor the accumulation of hydrophobic contaminants such as PCBs. The lipophilicity
of PCB congeners and their metabolites may cause them to partition into these
lipids, effectively removing them from the body cavity. Out of body sequestration of
contaminants could serve a protective factor, as up to 90% of the web making
materials are recycled without metabolism for creation of the new web (Peakall,
1971). The alternative possibility is that cyclic exposure to the same contaminants
and metabolites may occur. Female and immature tetragnathids rebuild their webs
nightly, consuming the silk material and using it for the next web (Gillespie, 1987;
Opell, 1998). The contaminant concentration in the webs could increase over time
as body burden increases due to sustained predation of contaminated prey. Webs
may also create a new exposure pathway if they are able to collect volatile PCBs and
OH-‐PCBs. The likelihood of volatilization of OH-‐PCBs is considerably less than that
of PCBs because their capability to form hydrogen bonds with water increases their
concentration in water, and hence decreases their fugacity. The contaminant
concentration in the web may then increase independently from spider diet.
25
PCB Transformation
Metabolism of toxicants has various toxicological roles in organisms. It
primarily functions to make compounds more hydrophilic such that they can be
readily removed from the body. In this case, biotransformation leads to enhanced
elimination, detoxification, sequestration, and redistribution. Alternatively,
metabolism can be problematic if the toxicants are instead activated to more toxic
forms. In the case of hydroxylated PCBs, the new physio-‐chemical properties of the
metabolites resulted in greater toxicity than their parent compounds in rats (Purkey
et al., 2004). Similar toxicity trends have yet to be confirmed in invertebrates, but
may have similar behavior. Our understanding of PCB metabolism comes from
studies with non-‐spider organisms; however, such studies can guide investigations
into spiders and other invertebrate predators.
Biotransformation of toxicants involves two phases of action. Phase I
includes reactions that serve to make the toxicant slightly more hydrophilic, in that
they may add or expose a functional group. The first step may be bypassed if there
are compounds that already possess an exposed functional group. Other potential
actions in phase I include oxidation, hydrolysis or reduction of the toxicant. Figure
1.5 displays some of the metabolic pathways of PCBs determined in reptiles, birds,
and mammals. Phase II reactions add a hydrophilic group through a conjugation
reaction. These groups can be sulfate groups, sugars, glutathione, or amino acids.
Some reactions are meant to detoxify activated metabolites, so acetylation or
methylation may be used to inactivate the products of phase I reactions. Overall,
26
hydrophilicity should increase by many orders of magnitude to facilitate excretion.
Spider excrement is only via solids, so increasing hydrophilicity may allow for
incorporation of PCB metabolites into the crystalline structure of the excreted
solids.
The biological half-‐life of PCBs is determined by their susceptibility to
metabolism, and is roughly determined from their bioconcentration rate, or rate of
accumulation (ka) as compared to their rate of elimination (ke). If ka > ke, then
compounds bioaccumulate. These rates are determined by the number and position
of chlorine atoms. Metabolic resistance is great if there are five or more chlorines,
especially if these are para positioned chlorines (Wiberg et al., 1998). For example,
PCB congener 153 is highly resistant to metabolism because it lacks adjacent
hydrogen atoms on the biphenyl system (Borlakoglu and Wilkins, 1993; Bühler et
al., 1988). The result is a half life of approximately 338 days for PCB 153 in humans
(Letcher et al. 2000). Congeners with meta-‐ and para-‐ positioned hydrogen are
more susceptible to metabolism than those with meta-‐ and para-‐chlorine (James,
2001).
All exogenous toxicants need to pass through cells to enter systemic
circulation. All PCBs are lipophilic enough to be able to pass through the lipid
bilayer of the cell membrane without becoming lodged in between the polar head
groups, but from that point the fate of the chemicals is more variable. Equilibrium
partitioning is not appropriate for use in this instance, because biota are not often at
equilibrium with the surrounding environment.
27
Figure 1.5 Metabolism of PCBs. Adapted from Letcher et al. ( 2000).
While PCBs are robust, legacy compounds, they can still be transformed in
the environment. A better understanding of these processes may allow for their
more reliable use as tracers to help understand ecological processes, much as we
have used stable isotopes.
28
Hydroxylated PCBs are formed as a result of detoxifying action by
cytochrome P450 (CYP) 1A and 2B. Detoxifying enzymes typically have very broad
substrate specificity, but these isoforms are known to process mostly xenobiotics
(Klassen, 2008). CYP enzymes are located on the endoplasmic reticulum of cells, and
are found in high concentrations in the liver, as that organ typically encounters most
of the xenobiotics introduced to an organism. CYP is found at low basal expression
levels in all other tissues, too, because these enzymes are an important part of the
defense against toxicants. As part of phase I of detoxification, these enzymes serve
to make hydrophobic compounds slightly more hydrophilic through addition of
polar functional groups. The most prevalent hydroxylated metabolites of PCBs are
p-‐OH substituted. The basic CYP reaction is a monooxygenase reaction, associated
with NADPH-‐CYP450 reductase. The general reaction is written as:
RH + O2 + NADPH + H+ ↔ ROH + H2O + NADP+ (Equation 3)
CYP epoxidation may occur as a result of this reaction, which is typically not
problematic; however, when reorganization does not occur the ring can be
distorted. OH-‐PCBs can be a result of epoxidation or direct insertion of the OH-‐
functionality by CYP1A/2B. Some arene intermediates may be stable for weeks if
the three-‐membered ring experiences the stabilizing effect of two chlorines on
either side of the arene oxide (Reich et al., 1978).
Phase II enzymes may make further modifications to the metabolites.
Enzymes such as glutathione-‐s-‐transferase (GST) serve to make the compound of
interest more hydrophilic by addition of additional polar groups, thus making them
29
likely to be excreted from the organism typically through urine or bile. As a result,
OH-‐PCBs are likely to be present at low, transient levels. GST modifies electrophilic
xenobiotics such as PCBs, and may be able to bind and store these compounds. GST
is abundant in mammals, constituting up to ten percent of liver protein (Klaasen,
2008). OH-‐PCBs can be further processed to become quinines or catechols [(OH)2-‐
PCB] (Amaro et al., 1996). In the laboratory, PCB metabolites may be oxidized if
exposed to air for prolonged periods of time (Letcher et al., 2000).
OH-‐PCBs are hydrophilic enough that they may be excreted, but it is also
possible that they may interact with other proteins (Kania-‐Korwel et al., 2008a).
OH-‐PCBs are typically found in significant concentrations in the plasma; however
they have also been found in the adipose, lung, kidney, and liver tissues in
organisms such as mice, fish, albatross, grey seals, polar bears, and humans (Sinjari
et al., 1998; Klasson-‐Wehler et al., 1987, 1997, 1998; Bergman et al., 1994; Sandau
and Norstrom, 1996; Buckman et al., 2006). Hydroxylated PCBs are known to affect
the mitochondrial membrane, making it more permeable and affecting ATP
production (Stadnicki and Allen, 1979; Ebner and Braselton, 1987; Yamamoto and
Yoshimura, 1973; Narasimhan et al., 1991). When ATP is not generated at the
appropriate levels cellular energy stores are affected, but also ionic and volume
regulation, resulting in a more acidic pH of the cytoplasm.
Endocrine disrupting compounds are a class of emerging toxicants currently
of great interest. OH-‐PCBs have been demonstrated to be weakly estrogenic
(Kramer et al., 1997; Moore et al., 1997), though the studied congeners that
30
exhibited such behavior are not environmentally relevant. Ortho-‐chlorinated
biphenyl metabolites are associated with alterations in vitamin A function and
thyroid hormone metabolism (Brouwer, 1991). The thyroid hormone thyroxine
(T4) functions to increase the metabolic rate and oxygen consumption in an
individual. In invertebrates, the molting hormone ecdysone has a similar structure
as thyroxine, so the presence of OH-‐PCBs in their systems may also negatively affect
spiders. The iodine substitution pattern of T4 (3,3’,4’,5-‐tetraiodo-‐L-‐thyroxine)
resembles the structure of many OH-‐PCB metabolites. Many of the structural
elements of the metabolites can non-‐covalently bind to transthyretin, (TTR) which
functions as a transporter for thyroxine, causing the metabolites to mimic thyroxine
and activate the hormone’s receptor (see Figure 1.6). The metabolites function as
agonists, and induce UDP – glucuronosyl transferase enzymes to glucoronidate and
remove the thyroxine more quickly.
31
Figure 1.6 A. T3 and T4 regulation by the Thyroid; B. Structure of thyroxine (T4).
Source: <http://www.bio.miami.edu/oreilly/ganser/03-‐01-‐05Endo.htm>.
While the concentrations in tissues other than the plasma are not significant,
it is important to note that hormones in blood are typically present at very low
concentrations. Free thyroxine is typically present at trace levels, so mimic
compounds can be effective at very low concentrations. Typically mimic
32
compounds do not “fit” the receptor as well as the intended compound. However,
the affinity of OH-‐PCBs for TTR may be ten times greater than that of T4 (Brouwer
et al., 1998;Lans et al., 1993). Reducing the amount of thyroxine present in the
plasma leads to increased thyroid stimulating hormone (TSH), which creates
hypertrophy (where the volume of an organ or tissue is increased due to the
enlargement of its component cells) or neoplasia (abnormal growth of cells) of the
thyroid. These effects are less problematic in vivo than in vitro (Schuur et al., 1996,
1998, 1999), though they may have an effect on fetal brain development (Brouwer
et al., 1998).
PCB Metabolism by Spiders
The bulk of the research on hydroxylated PCB metabolites (OH-‐PCBs) has
been on mammals, fish, and birds. Since PCBs have been detected in spiders it is
likely that both spiders and their predators will possess metabolites. Research may
expand in time to include other arachnivorous predators such as reptiles and
amphibians. While the number of PCB congeners detected in tissue is typically high,
fewer congeners appear to undergo hydroxylation (Klasson-‐Wehler et al., 1998).
Digestion begins in spiders in the midgut (Figure 1.4), which is expected to
have the same functionality as seen in the liver in vertebrates (Foelix, 1982). The
muscles of this compartment will contract and expand such that a vacuum is created
in the digestive tract, which effectively creates a suction pump that draws the prey-‐
fluid into the tract. The midgut is the only section of the digestive physiology that
33
lacks the thin cuticular coating, thus making it the only area designed for digestion.
First secretory cells empty enzymatic granules into the gut lumen, followed by
resorptive cells that process the nutrients further in food vacuoles before the
metabolites move into interstitial tissue or the hemolymph. The secretory cells may
take up to eight hours to empty all granules, and at that time resorptive cells may
begin to contain excretory products, as well as stores of glycogen and lipids. The
hypothesized process of PCB metabolism described herein is inferred from the
understanding of spider digestion and predation, as well as empirical evidence of
OH-‐PCB generation and activity.
Summary
Ecological and exposure studies tell us that riparian spiders are an important
linkage between the aquatic and terrestrial habitats. Analyses of these
compartments indicate that spiders can act as biovectors, transferring energy,
carbon, and even contamination from aquatic to terrestrial food webs. In particular,
Tetragnathidae spiders occupy a niche that makes them important biovectors.
Their foraging tactics (Table 1.1) differentiate them from other spiders such as
Araneidae and basilica spiders. Less is known about the physiology and
detoxification of organic contaminants by spiders. Understanding these can inform
our interpretation of the spider’s role in contaminant fate, transport, and
transformation.
34
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CHAPTER TWO
CHIRAL SIGNATURES OF PCBS IN RIPARIAN SPIDERS
Introduction
Spiders along Twelvemile Creek and at Lake Hartwell have a PCB body
burden, and they redirect transport of these contaminants from the aquatic to the
terrestrial ecosystems (Walters et al., 2008; Walters et al., 2010; Raikow et al.,
2011). Their body burden is sufficient to pose significant threat to predators
(Walters et al., 2010); however, biotransformation of PCBs within spiders has not
been investigated. Using enantioselective chromatography as a tool, it may be
possible to discern if the changes between trophic levels (in our study, between
emergent insects and spiders) is reflected only by changes in concentration, or if
there are also enantioselective changes in specific congeners that are transferred.
Spiders may be able to regulate their exposure via enantioselective uptake or
retention of PCB congeners.
Seventy-‐eight of the 209 PCB congeners are chiral (Lehmler et al., 2009).
That is, their asymmetric substitution patterns of chlorines about the biphenyl rings
creates non-‐planar conformations, and generates two molecules with the same
elemental composition that cannot be superimposed upon each other. These
atropisomers, called enantiomers, were released into the environment in equal
parts, known as racemic mixtures. Enantiomers possess the same physical and
chemical properties, but differ in their interactions with biological molecules such
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as enzymes and the direction they orient polarized light. Biological interactions
such as enzymatic degradation, enantioselective uptake, and enantiospecific
metabolism can change the ratios and provide insight as to the mechanisms of PCB
fate and transport. Such interactions can yield different adverse and toxicological
effects for individual enantiomers. Enantiomers have different activities, affinities
and efficacies for interacting with receptors and enzymes, resulting in different
effects and even varying toxicities (Kallenborn and Hühnerfuss, 2001). The Three-‐
Point-‐Attachment model finds that enantiomeric specificity on the part of enzymes
or receptors occurs only when there are three nonequivalent binding sites to
discriminate between the enantiomers (Easson and Stedman, 1933), causing
enantioselective toxicities. Diastereomers may have agonist or antagonist
functionality, or participate in enantioselective active transport, such as is seen with
α-‐hexachlorocyclohexane (α-‐HCH) and the blood-‐brain barrier (Hühnerfuss et al.,
1992).
Nineteen chiral PCBs are environmentally stable and feature three or four
ortho-‐chlorine atoms that create the non-‐planar conformation (Lehmler et al.,
2009). Twelve of those were commonly used in commercial mixtures and are
frequently detected in various environmental media: PCB 45, 84, 88, 91, 95, 132,
136, 144, 149, 171, 174, and 183 (see Table B.1 for substitution patterns) (Frame et
al., 1996; Dang, 2007; Dang et al., 2010). A few of these twelve chiral congeners
have been investigated in various aquatic food webs, where fish predators such as
bass and salmon were found to have non-‐racemic EF values (EF≠0.5) although the
49
compounds were released as racemic mixtures (EF=0.5) (Dang 2007; Dang et al.
2010; Wong et al. 2001; Buckman et al. 2006).
Ratios of chiral diastereomers are quantified by the enantiomeric fraction
(EF), defined by Harner at al. (2000) as:
𝐸𝐹 = !!!!
= (!)! ! (!)
(Equation 4)
where A represents the first eluting enantiomer and B the second eluting
enantiomer, or where (+) represents the clockwise optically directed enantiomer
and (-‐) the counterclockwise orientation. An equal concentration of both
enantiomers yields an EF value of 0.5, and is called racemic. Nonracemic EF values
are those that differ from 0.5 in either the positive or negative direction.
PCB chirality has yet to be investigated in terrestrial predators linked to aquatic
food webs. The Twelvemile Creek / Lake Hartwell Superfund site has been the
location of many monitoring and research efforts. Walters et al. (2010) were able
to use isotopic analysis of carbon and nitrogen to determine the trophic placement
of Tetragnathidae, Araneidae, and basilica spiders in the Twelvemile Creek / Lake
Hartwell riparian ecosystem. Tetragnathid and shoreline spiders consumed mainly
aquatic insects, and upland araneid spiders consume primarily terrestrial prey
(Table 1.1). Assessment of how distance from the shoreline affected spider PCB
body burdens indicated that with increasing distance the concentration decreases,
falling below detection limits at 30m (Raikow et al., 2011). The resultant annals of
data cover sediment, benthic organisms, aquatic insects, and fish PCB
50
concentrations and chirality; however, only the most recent investigations have
begun to describe how terrestrial predators are influenced by aquatic
contamination (Walters et al., 2008; Walters et al., 2010).
The goal of this study was to investigate patterns in chirality among three spider
taxa and their prey. The hypothesis tested was that the three spider species show
distinct EF values based on their consumption of aquatic insects. The three spider
taxa have distinct ecological roles that may influence their prey, and as a result, their
EF values. Different values may also be influenced by differences among taxa in
metabolism of chiral congeners. Additionally, it was hypothesized that comparison
with prey species EF values would demonstrate that Tetragnathidae samples would
be distinct from their prey sources. Biotransforming processes may differ between
prey and predator, and may manifest as changes in EF value. Additionally, changes
in bacterial colonies along the exposure gradient may affect the concentrations of
each enantiomer available to be transported through the food web.
Materials and Methods
Sample Collection
Spiders were obtained from along the Twelvemile Creek arm of Lake Hartwell
between June and August 2007 as described by Walters et al. (2010). Samples were
composites of individuals collected at night from either vegetation suspended over
the water column or within two meters of shoreline. Riparian spider taxa
Tetragnathidae, Araneidae, and basilica were collected, and extracted by the EPA lab
51
in Cinncinati, OH. Adult chironomids were also collected at night from boats trolled
across the width of the lake using florescent lights and sweep nets. Sample sizes are
listed in Appendix B, Table B.2. Sampling locations are depicted in Figure 2.1, and
their GPS coordinates are listed in Table 2.1.
Extractions were performed by the EPA. Samples were mixed with 25g of
baked sodium sulfate, dried for one hour, and transferred into Accelerated Solvent
Extractor (ASE) cells (Dionex, Sunnyvale, CA). The extraction was done using
methylene chloride and hexanes.
Figure 2.1 EPA Sampling Locations. Gradient map from Walters et al. (2010). Color gradient indicates contamination of sediment (center) and Tetragnathidae spiders (ribbons at either side, indicating banks of lake).
52
Table 2.1 GPS coordinates for EPA sampling sites
Site Label Coordinates Site Label Coordinates
T12 N 34.734°, W 82.811° I N 34.709°, W 82.835°
O N 34.728°, W 82.813° H N 34.703°, W 82.841°
N N 34.725°, W 82.819° T6 N 34.697°, W 82.842°
K N 34.714°, W 82.829° G N 34.688°, W 82.851°
Hexanes and isooctane were obtained as pesticide grade from Fisher
Scientific, as well as sulfuric acid. Standards to confirm the identity of field samples
for chiral analysis were obtained from AccuStandards (New Haven, CT): PCB 91
(2,2’,3,4’,6-‐pentaCB), PCB 95 (2,2’,3,5’,6-‐pentaCB), PCB 136 (2,2’,3,3’,6,6’-‐hexaCB),
PCB 149 (2,2’,3,4’,5’,6-‐hexaCB), and PCB 174 (2,2’,3,3’,4,5,6’-‐heptaCB). Additional
standards were obtained for use in achiral analysis: Aroclor mixtures 1016, 1242,
and 1260 for instrument calibration; PCBs 14 (3,5-‐diCB) and PCB 169 (3,3’,4,4’,5,5’-‐
hexaCB) for use as recovery standards; and aldrin and PCB 204 (2,2’,3,4,4’,5,6,6’-‐
octaCB) for use as internal standards.
Lipid content in extracts was measured in our lab by a gravimetric method.
Extracts were treated with 4mL of an ethanolic KOH solution to extract any
metabolites present in the extracts (Kania-‐Korwel et al., 2008b). The KOH solution
was removed and used for metabolite analysis, which is described in Chapter 3.
53
Sample Clean-‐up
Organic materials that can cause interference in the chromatograms were
removed through use of cleanup columns. Alumina – sodium sulfate columns (2.5g
and 1.5g respectively) were conditioned with pesticide grade hexanes to remove
any interfering polar compounds. Alumina was 6% deactivated. Extracts received
from the EPA were added to the columns, and eluted with hexanes. Extracts were
further cleaned by centrifugation with sulfuric acid to remove any remaining lipids
in the sample, then solvent exchanged for isooctane (U.S. EPA, 2005).
Chiral Analysis
Enantioselective analysis of five chiral congeners was conducted with an
Agilent 6850-‐GC equipped with a Chirasil-‐dex DB column (25m x 0.25mm) and a
63Ni electron detector. The temperature program began at 100˚C for 2min, then
ramped at 10˚C/min to 170 and held for 10min, then ramped at 8˚C/min to 180˚C
and held for 20min, and finally ramped at 1˚C/min to 190˚ and held for 5min.
Quality of assessment was maintained through use of procedural blanks, laboratory
control samples in duplicate, matrix spikes in duplicate (aldrin and PCB 204,
Accustandard), blank tissue samples, and check standards with each batch of 10
samples. Concentrations were not corrected for recovery. The detection limit did
vary somewhat by congener, but was approximately 25ng/L for chiral PCB
congeners. The EFs for the racemic standards (PCBs 91, 95, 136, 149, and 174)
were between 0.492 (± 0.003 SD) and 0.504 (±0.006 SD).
54
Statistical Analysis
Differences in EF values among different species were assessed by one-‐way
analysis of variance (ANOVA) using Tukey’s test to determine significance (p<0.05).
This assessed the significance of evidence gathered for the hypothesis that EF values
would differ among spider taxa. Analysis of co-‐variance (ANCOVA) was enlisted to
determine if there were changes in spider EF among sampling locations. EF values
were considered to be significantly non-‐racemic if their 95% confidence intervals
did not encapsulate a racemic value of 0.5.
Nonmetric-‐multidimensional scaling statistical analysis (NMS) was
completed using PC-‐ORD 4.0 software (MjM software). NMS is best utilized when
data are not normally distributed, or have discontinuous and unequal scales. The
autopilot mode was utilized such that the program would choose the best solution
at each dimensionality (McCune and Mefford, 1999). The chi squared coefficient was
used as the distance measure in the analysis, as it is the most appropriate measure
enlisted when the domain of data inputted is x ≥ 0 and the range of distance
measures is d ≥ 0 when d = f(x) (McCune et al., 2002).
Results
EF Differences among Spider Taxa
Four chiral congeners (PCBs 91, 95, 149, and 174) were above the detection limit
for entantioselective analysis in the three spider taxa (Figure 2.2). Chiral signatures
for congener 91 were significantly non-‐racemic in favor of the first eluting congener.
55
The average EF (± 1 SD) for Tetragnathidae spiders was 1.0 (± 0.0); no
Tetragnathidae samples contained the second-‐eluting enantiomer above the
detection limit. Araneidae spiders were also significantly non-‐racemic with an
average EF value of 0.90 (± 0.22 SD), and basilica samples also had an average EF of
0.90 (±0.17 SD). These EF values were significantly non-‐racemic across all taxa
(confidence interval, α=0.05). Enantiomeric fractions for PCB 91 did not vary
significantly among taxa (ANOVA, p = 0.16) when data were averaged across all
sample sites. An ANCOVA analysis for PCB 91 enantiomeric fractions along the
exposure gradient among sites for each taxa indicated that the EF did not change
significantly (α=0.05, F=0.1, p-‐value = 0.905; Figure 2.2A).
56
Figure 2.2 EF measurements averaged across sites. Error bars represent 95% confidence interval. Data for spider taxa represent congeners (A) PCB 91, (B) PCB 95, (C) PCB 149, and (D) PCB 174. Panel (E) displays Midge EF data averaged across all sampling locations.
Samples containing PCB 95 had detectable concentrations of both
enantiomers (Figure 2.2B), in contrast to PCB 91 which was skewed in favor of one
enantiomer. Mean (± 1 SD) EFs were 0.23 (± 0.12), 0.20 (± 0.08), and 0.31 (± 0.14)
for tetragnathid, areaneid, and basilica spiders respectively. These values were
57
clearly non-‐racemic, but were not different from one another. (ANOVA, p-‐value =
0.06) Likewise, EFs did not vary spatially along the exposure gradient (ANCOVA,
α=0.05, F=1.24, p = 0.301; Figure 2.2B).
Samples containing congener 149 had approximately equal concentrations of
both congeners. Tetragnathidae spiders had an EF value of 0.55 (± 0.14 ); whereas,
Araneidae spiders had a value of 0.49 (± 0.18 ), and basilica spiders had an EF value
of 0.44 (± 0.05). Only for basilica spiders was this value significantly different from
racemic values (95% confidence interval 0.46 ± 0.03, Figure 2.2C). It is important to
note that the concentration of PCB 149 in basilica spiders fell below detection limits
for enantioselective analysis for all but two sampling sites. EF values did not differ
among taxa (ANOVA, p-‐value = 0.33), or among sampling locations (ANCOVA,
α=0.05, α=0.05, F=0.58, p-‐value=.567; Figure 2.2C).
Congener 174 had an average EF value of 0.92 (± 0.05), 0.85 (± 0.09), and
0.83 (±0.24) for Tetragnathidae, Araneidae, and basilica spiders, respectively.
Confidence intervals indicate that all three species were significantly non-‐racemic in
favor of the first eluting enantiomer. No significant differences existed among the
species (ANOVA, p-‐value = 0.14). ANCOVA analysis did not reveal any significant
differences in EF along the exposure gradient for PCB 174 (α=0.05, F=0.56, p-‐
value=.577; Figure 2.2D).
58
EF Differences between Prey and Spiders
Differences between the EFs of the spider taxa and aquatic insects that serve
as prey for the spiders were measured by considering Chironomidae (midges).
Midges were collected from the same sites, and represent potential prey for the
spiders; however, only three of the congeners investigated were above the detection
limit. Midge samples had fairly consistent EF values across all sampling locations
(Figure 2.2E) that were distinct from those for spiders, except for PCB 95 which is
enriched in the same enantiomer (second-‐eluting) as the midge sample. EF values
had a wide range for different congeners. PCB 91 had an EF of 0.27 (± 0.05 SD),
whereas PCB 95 was close to racemic with an EF of 0.43 (±0.04 SD). PCB 149 has
the greatest EF value, 0.74 (± 0.07 SD), and was the only congener with higher
concentrations of the second eluting enantiomer. A Student’s T test comparing
midges to each spider taxa determined that midge EF values for PCB 95 were
significantly different from Tetragnathidae, Araneidae, and basilica spiders (α=0.05,
p-‐valuetetragnathid = 4.0e-‐6, p-‐valuearaneid = 2.0e-‐8, p-‐valuebasilica = 0.02).
Use of NMS to discern trends in the data revealed that for PCB 95 and 149
spider EF values are distinct from those of Midges. For the plot shown, spider and
midge samples from all species and locations were incorporated (Figure 2.3).
Within the groups the relationships were less clear. Midge samples, while grouped
together, did not indicate any spatial trends. Points that fall outside of the circles all
represent spider samples. Many of the spider samples were difficult to assess using
59
this analysis because of their retention of only one enantiomer, thus they fell outside
of the general area where the majority of spider samples clustered.
Figure 2.3 Nonmetric Multidimensional Scaling (NMS) plots of EFs for PCBs
95 and 149 for both spiders and midges. Spiders and midges are clearly grouped for these two congeners. Points that fall outside of the circles represent spiders.
60
Discussion
The EF results did not support the hypothesis that the three spider taxa
would differ due to differences in their consumption of aquatic insects. ANOVA
analysis showed that average EF values for the three spider taxa were not
statistically distinct from each other. Isotopic analysis by Walters et al. (2010)
indicated that riparian spiders consumed aquatic insects. In particular, the
tetragnathid and araneid spiders consumed mostly aquatic prey; whereas, basilica
spiders consumed approximately half aquatic prey and half terrestrial prey. All of
the samples analyzed were obtained within 2m from the shoreline, and so all would
opportunistically prey upon emergent aquatic insects. Terrestrial insects were
observed to have low PCB concentrations and are not likely to contribute to EF.
Spider enantiomeric fractions are likely very similar because their prey source that
contains PCBs is very similar. Using this theory as a guide to interpret the data
presented here, these spiders may have similar enzymatic capabilities and different
habitat spaces; therefore, the greatest influence on contaminant profile is prey
consumption, not biotransformation.
Chironomidae were selected for comparison with spiders because they
commonly dominate the aquatic insect assemblages (Fairchild et al., 1992; Menzie,
198; Maul et al., 2006). They also are capable of transporting significant quantities
of carbon, nitrogen,and PCBs in the Twelvemile Creek watershed (Walters et al.,
2010). They are a good representative of prey because spiders are opportunistic
predators that feed upon what their webs can capture. Additional enantioselective
61
analyses could be performed on other aquatic insect prey to corroborate the
comparisons discussed here. Midges are compared to Tetragnathidae spiders
because those spiders are obligate aquatic predators, so their EF values should most
closely reflect the influence of aquatic emergent insects.
Prey (midge) EFs and predator (spider) EFs were proven significantly
different for all three PCB congeners – 91, 95, and 149 – via Student’s T test. Midge
samples were nonracemic favoring the second eluting enantiomer for PCBs 91 and
95. Congener 149 was non-‐racemic favoring the first eluting enantiomer.
Tetragnathidae spiders were nonracemic favoring the first eluting enantiomer for
PCB 91. The change for PCB 91 between chironomids and tetragnathids, shifting
towards favoring the first eluting enantiomer, could be due in part to selective
uptake or excretion by spiders. If the spiders do not uptake a great amount of the
second eluting enantiomer, or if they can excrete it efficiently, the EF value would
subsequently be greater than 0.5. Metabolism could also yield these results. If
spiders are able to more easily metabolize, and therefore, preferentially excrete the
second eluting enantiomer the EF value would shift in favor of the first eluting
enantiomer. PCB 95 was nonracemic in both organisms, with prey and predator
both retaining the second eluting enantiomer in greater concentration than the first
enantiomer. The EF became more enriched in the second-‐eluting enantiomer with
the change in trophic level from prey to predator. For PCB 149, midge samples were
nonracemic favoring the first eluting enantiomer and Tetragnathidae samples were
racemic. These data for PCB 95 and 149 indicate that enantioselective metabolism
62
by spiders is likely not occurring as it may for PCB 91. PCB 149 may also be
experiencing enantioselective metabolism as the value changes from prey to
predator.
Walters et al. (2008) determined that midges and other emergent insects
were not good indicator species when compared to local sediment contamination
concentrations. It was proposed that due to the insects’ low mass prevailing winds
could force the populations upstream or downstream at any given time, which
allows for mixing of the populations. Even if the midge populations do vary in
enantiomeric body burden, it would be difficult to discern from field sampling due
to population mixing. The lack of statistical significance in EF values for Midge
samples along the contamination gradient supports the ideas that mixing of
emergent insect populations is occurring. Confirmation that the system has not
changed such that sediment EF is identical along what was previously considered to
be a gradient would need to be obtained in order to assert that population mixing is
occurring. Assuming this to be true, all spider species consuming those mixed
populations would receive the same average enantiomeric mixtures. It can be
concluded, therefore, that because the enantiomeric fractions do not vary among the
spider species that there is no significant difference in contaminant processing
among these three riparian species for PCB congeners 91, 95, 149, and 174.
Dang et al. (2010) investigated the riparian food web in the Lake Hartwell
tributary of Twelvemile Creek. Analysis of the mayfly did not show any statistical
differences among site, providing further evidence for the “mixing” theory proposed
63
by Walters et al. (2010) and supported by midge data herein. EF values were
reported for PCB 91 (0.51 ± 0.03), PCB 95 (0.24 ± 0.03), and PCB 149 (0.35 ± 0.04).
These differ from the data obtained for midges in Lake Hartwell. Such differences
could be a result of the locations having a somewhat different contamination profile.
The EFs for the spider taxa examined in this study do differ from data
reported for aqueous predators in the same watershed. Yellowfin shiner were
analyzed for EF in Twelvemile Creek by Dang et al. (2010) assuming that they were
predators of mayflies. Yellowfin were found to have EF values for PCB 91 and 149
that were also nonracemic in favor of the second eluting enantiomer; whereas, PCB
95 was not above the detection limit. Spider concentrations can be as many as three
times higher than those reported for fish (Walters et al. 2010), so they may have a
sufficient concentration of PCB 95 for enantioselective analysis when yellowfin do
not. Spider and fish EF values were skewed in different directions for PCB 91, but
values for PCB 149 were much more similar. This again may indicate that spiders
experience enantioselection for the first eluting enantiomer of PCB 91. A more
detailed comparison of diet for spiders and yellowfin would need to be completed to
determine the difference in values is not a result of different dietary composition.
It was concluded by Dang et al. (2010) that the nonracemic values for
Yellowfin were due to consumption of nonracemic residues. This same conclusion
holds for Tetragnathidae. The difference in the EF values between the terrestrial
and aquatic predators could also be attributed to diet. Spiders can only consume
insects that emerge from the water column, whereas fish can consume the larval
64
instars, too. Insects that emerge will not acquire more PCB mass, but growth may
dilute the concentration, or metabolism affect the EF. If metabolism of the residues
on the part of the insects changes over the course of their life, the spiders would be a
better representation of the EF for adult insects after they emerge, and shiner values
would reflect an averaging of EF over the life of the insects prior to emersion from
the water column.
The lack of spatial trends for Midge EFs is in accordance with previously
published work (Walters et al., 2010). It has been theorized that their low mass
causes these insects to be easily blown up and downstream, causing them to be poor
indicators of local PCB sediment and food web concentrations. The NMS data
supports this claim, as well as indicates clear differences in the values for spiders
and midges (Figure 2.3). Enantioselective processes that change the EF as PCBs
move up the food chain would yield such a plot.
Conclusions
The hypothesis that each spider taxa would be distinct from the others was
not supported by the data collection. Tetragnathids, araneids, and basilica spiders
had essentially the same EF for each of the congeners; therefore, difference in niche
does not appear to influence the EF profile in spiders. Additionally, we can conclude
that if the spiders are capable of metabolism, the three taxa use the same
mechanism.
65
Comparison of EF values between spider samples and midge samples also
supported the hypothesis that predator EF values would be distinct from prey EF
values. Spider values shifted in the direction favoring retention of the second
eluting enantiomer for PCB 91. The EF data for PCBs 95 and 149 are not as clear.
The change in EF could be a product of metabolism on the part of the spider. If one
enantiomer is preferentially detoxified the EF value would shift to favor the more
recalcitrant enantiomer.
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68
CHAPTER 3
SPIDER METABOLISM OF PCBS: IN VIVO AND IN VITRO
INVESTIGATIVE APPROACHES
Introduction
Toxicants, or parent compounds, are metabolized in an effort to make them
easier to excrete; however, even at low concentrations metabolites have a marked
effect. Hydroxylated PCBs (OH-‐PCBs) in particular are more toxic than their parent
compounds, especially with respect to endocrine disruption (Purkey et al., 2004).
OH-‐PCBs have a structure similar to that of thyroxine (T4), a thyroid hormone that
is transported by transthyretin (TTR). The metabolite has a higher affinity for TTR
than does T4, which alters response by the endocrine system function (Brouwer et
al., 1998). T4 is effective at concentrations of approximately 10pM in humans, so
even at low concentrations OH-‐PCBs can be potent toxicants (Lans et al., 1990).
Different chlorination patterns of PCBs lead to different volatilities (Mackay
et al., 1992a), potentials for biomagnification (Campfens and Mackay, 1997;Mackay
and Fraser, 2000;Letcher et al., 2010), and potentials for metabolism (Schurig et al.,
1995). Congeners that feature chlorine with adjacent hydrogens are easier to
metabolize, and chlorines in meta-‐ or para-‐positions are easier to remove or replace
with hydroxyl groups than are ortho-‐Cl (Letcher et al., 2000). Some congeners are
vulnerable to biotransformation to lower chlorinated congeners via reductive
dechlorination by bacteria (Pakdeesusuk et al., 2003b;Pakdeesusuk et al.,
69
2003a;Pakdeesusuk et al., 2005), or can be metabolized into compounds such as
methlysulfonyl-‐PCBS (MeSO-‐PCBs), methoxy-‐PCBs (MeO-‐PCBs), and hydroxylated
PCBS (OH-‐PCBs) (Letcher et al., 2000;Lehmler et al., 2009).
While accumulation of OH-‐PCBs has been demonstrated in fish (Buckman et
al., 2006;Carlson and Williams, 2001), birds (Klasson-‐Wehler et al., 1998;Verreault
et al., 2006;Helgason et al., 2010;Jaspers et al., 2008), frogs (Nomiyama et al.,
2010),and mammals (Park et al., 2009;Verreault et al., 2009;McKinney et al.,
2006;Hoekstra et al., 2003;Sandau et al., 2000;Guvenius et al., 2002), there has been
little research on invertebrate predators. For example, the Twelvemile Creek / Lake
Hartwell ecosystem has been the focus of many sediment (Pakdeesusuk et al.,
2003b;Pakdeesusuk et al., 2003a;Pakdeesusuk et al., 2005) and fish investigations
(Wong et al., 2001); however, recent analyses have identified that non-‐fish
predators in the riparian zone also participate in contaminant transport (Walters et
al., 2008;Walters et al., 2010). Spiders that consume aquatic emergent insects have
PCB concentrations greater than 5.5ppm (Walters et al. 2010). If other predators in
the food web accumulate and metabolize their PCB body burden it is possible that
spiders can do the same.
It is valuable to know if spiders have the metabolic capacity to metabolize
their PCB body burden because they can transfer those metabolites alongside the
carbon, nitrogen, and PCBs to their predators, namely frogs, lizards, and birds
(Walters et al., 2010). If this is so, then ecological risk assessments may need to be
expanded to incorporate OH-‐PCBs and invertebrates.
70
The goal of this work is to test two hypotheses. First, spiders have the
capacity to metabolize PCBs to produce OH-‐PCBs. Second, metabolism of co-‐planar
PCB 61 will differ from metabolism of the non-‐planar congeners.
The metabolism study had four objectives to explore the hypotheses:
• Screening for OH-‐PCB metabolites generated in vivo by spiders
• An in vitro exposure of spider enzymes to non-‐planar PCBs 88 and 149
• An in vitro exposure of spider enzymes to co-‐planar PCB 61
• Use of biomarker assays to determine the metabolic pathway for PCB
detoxification
Materials and Methods
Sample Collection
Extracts from samples collected along the Twelvemile Creek arm of Lake
Hartwell were provided to the lab by the US EPA and used for the in vivo study.
These samples have previously been analyzed for PCB concentration (see Walters et
al. 2010) and for enantiomeric fraction trends (see Chapter 2 of this dissertation for
EF data and more detail about collection). The extracts were treated to remove OH-‐
PCBs prior to the chiral analysis in Chapter 2, and the metabolite fraction used to
screen for presence of metabolites in spiders from the field.
The in vitro study utilized an enzyme fraction isolated from Tetragnathidae
spiders obtained from two sites along Twelvemile Creek (Figure 3.1). The collection
sites are contaminated by PCBs from the Sangamo-‐Weston point source, and are
71
locations where enzymatic activities are hypothesized to be elevated because of
exposure to contamination. Spiders were collected in jars and frozen with liquid
nitrogen before transport back to the lab. Each site had one pooled sample of
approximately 15 spiders, and each sample had a total organism mass of 1.2g.
Additionally, one pooled sample was collected from the Reese Mill site without
liquid nitrogen, which was analyzed separately than the sample obtained with liquid
nitrogen. Samples were stored in a -‐80˚F freezer until preparation for analysis.
72
Figure 3.1 Sampling locations. RM = Reese Mill, RB = Robinson Bridge. Note that
two types of samples were collected at Reese Mill: spiders collected with liquid nitrogen, and spiders collected without nitrogen.
Sample preparation for in vivo study
Extractions were performed by the US EPA. Samples were mixed with 25g of
baked sodium sulfate, dried for one hour, and transferred into Accelerated Solvent
Extractor (ASE) cells (Dionex, Sunnyvale, CA). The extraction was done using
methylene chloride and hexanes. Analysis of these extracts for enantiomeric
fraction values is discussed in Chapter 2. Hydroxylated recovery standards were
not used for the in vivo experiments due to uncertainty about elution patterns of
metabolites.
These extracts were treated with an ethanol:KOH solution (1:1, v/v) to
deprotonate hydroxylated metabolites such that they would partition from the
neutral organic phase. The aqueous layer was drawn off, and treated with HCl to pH
73
4 in order to reprotonate the metabolites that partitioned into the aqueous layer. A
hexanes:methyl-‐tert-‐butyl-‐ether solution (9:1, v/v) was used to extract metabolites
from the aqueous phase. The organic phase was derivitized with diazomethane that
was synthesized in our lab. Sample clean-‐up columns are described below.
S9 fraction preparation
The in vitro studies used post-‐mitochondrial, or S9, fractions. An S9 fraction
is the supernatant obtained after centrifuging organ homogenant, and contains both
microsomes and cytosol (Greim and Snyder, 2008). The microsomal portion
contains the cytochrome P-‐450 enzymes (CYP) responsible for phase I metabolism,
and the cytosolic portion contains various other enzymes involved in phase II
metabolism. For all components the samples were derivitized and analyzed in
identical manners, though sample preparation differed.
Homogenization buffer was prepared to maintain pH, to prevent ice crystal
damage, to inhibit proteases that would destroy target enzymes, and to prevent
oxidation (0.25M sucrose, 0.05M Tris-‐base at pH 7.4, 1mM
ethylenediaminetetraacetic acid [EDTA, to chelate metal proteases], 1mM
dithiothreitol [DTT, to prevent oxidation], 0.2mM α-‐toluene sulfonyl fluoride [PMSF,
to inhibit proteases]). Whole body samples of Tetragnathidae spiders were
homogenized with 5mL of buffer. A manual tissue tearer was used to homogenate
the sample, taking care to avoid any foaming or bubbles, which could oxidize the
sample. Fifteen spiders were combined to create a sample weight of approximately
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1.2g. Samples were adjusted to identical volume and spun down at 9000 rpm
(10,000 g) at 4˚C for 20min on a Beckman J2021M/E centrifuge with JA-‐20.1 rotor.
The fat layer was aspirated from the top of the extract, and the supernatant stored
at -‐80˚C until analysis. This protocol was adapted from biomarker assays performed
by Truman and van den Hurk (2010).
Enzymatic incubations
S9 fractions from each site were treated with 200µL of a 2ppm concentration
of an individual PCB congener in acetone – PCB 61 (2,3,4,5-‐tetraCB), 88 (2,2;,3,4,6-‐
pentaCB), or 149 (2,2;,3,4;,5;,6-‐hexaCB). Individual neat standards of PCB
congeners were obtained from Accustandard (New Haven, CT). The S9 fractions
were incubated for 24hrs in a 34˚C water bath. NADPH was added to provide the
energy necessary to fuel metabolism. Samples were then removed from the bath
and extracted.
The enzyme incubations used a negative control, created by boiling a
composite S9 fraction, consisting of equal parts from the two sampling sites. Boiling
effectively quenches enzymatic activity, and combining enzymes from both locations
removes site bias. Rat microsomes enriched in CYP2B was used as a positive
control, and a reagent blank was prepared to confirm that positive results were due
to compound transformation and were not artifacts from the reagents. Reagent
blanks consisted of PCBs with magnesium chloride, bovine serum albumin, Tris
buffer at pH 7.4, and NADPH. Enzyme incubations were completed in triplicate.
75
Incubation extraction
The post-‐incubation samples were extracted via accelerated solvent
extraction on a Dionex 200 Accelerated Solvent Extractor (ASE). Cells were packed
with diatomaceous earth and sand. The in vitro experiment used a 2-‐OH-‐tetraCB
recovery standard obtained from Accustandard (New Haven, CT) with recoveries of
34% (± 4 SD). These recoveries are similar to those obtained in other laboratories
(Kania-‐Korwell et al., 2008). Results were not corrected based upon percent
recovery. A 9:1 hexanes:acetone solution (v/v) was used for the extraction. Heating
time was 5min followed by two 2min static cycles. Cells were heated to 100˚C
temperature at a pressure of 1500 psi, followed by a 60% volume flush. Extraction
methods were adopted from Kania-‐Korwell et al. (2008b) and Garcia et al. (2008).
Derivitization of in vivo and in vitro samples
To detect metabolites in a GC-‐MS system, the hydroxyl group needs to be
derivitized to a methoxylated compound. All in vivo samples, S9 extracts, and
hydroxylated standards were derivitized in the laboratory with diazomethane that
was synthesized immediately before use, and concurrent with extraction
procedures. Diazomethane was collected in methyl-‐tert-‐butyl ether, from carbitol
(diethylene glycol ethyl ether) and diazald (N-‐methyl-‐N-‐nitroso-‐p-‐toluene
sulfonamide) under alkaline conditions in a glass diazomethane generator. After one
hour of synthesis on ice, the ether from the outer compartment was collected, and
76
400μL added to each sample. All samples were then stored overnight at -‐20˚C
before clean-‐up.
Sample clean-‐up for in vivo and in vitro studies
A clean-‐up column was prepared with 3.5g of alumina (6% deactivated) and
2.5g anhydrous sodium sulfate. Both in vivo and in vitro samples were cleaned up
on these columns. The samples were eluted with hexanes to a final volume of 10mL.
The solvent was exchanged for isooctane, and samples were condensed to a final
volume of 2mL.
Sample Analysis by GC-‐MS-‐MS
Tandem mass spectroscopy was used for analysis of in vivo and in vitro
samples to determine the structures of the compounds detected. Use of standards to
identify and quantify these compounds would have been ideal; however, obtaining
standards for each potential metabolite was not feasible due to both unavailability
and cost. Instead, mass spectra were used to determine presence and degree of
chlorination for the compounds detected. Different SIM settings were used to
screen for metabolites by homolog series (Appendix C).
Aliquots of the samples with aldrin and PCB 209 as internal standards
(Accustandard) were run on a Varian 4000 GC-‐MS-‐MS with ion-‐trap detection using
electron impact ionization (70 eV) with selected ion monitoring (m/z 306, 308, 310
77
for PCB 61; m/z 324, 326, 328 for PCB 88; m/z 358, 360, 362 for 149). An RTX-‐5
column was used for separation (30m×0.25mm×0.25µm, Restek).
Samples were injected in splitless mode at 215˚C with helium as a carrier gas
at a constant flow rate of 50.6 cm/s. Injected volumes were high at 7µL because
sample concentration fell below detection limits with 1µL injections. Initial oven
temperature was 90˚C and held for 2min, then ramped to 180˚C at an 8˚C/min rate,
held for 10min, and then ramped at 5˚C/min to 200˚C and held for 10min.
Standards for PCB 61, OH-‐PCB 61, and MeO-‐PCB 61 were obtained from
Accustandard (New Haven, CT). PCB and MeO-‐PCB 61 were used to develop the
quantification method and to externally calibrate enzyme samples. OH-‐PCB 61 was
used to optimize the derivitization of metabolites. 2-‐MeO-‐3,4-‐diCB was used as a
recovery standard for these incubations, and recovery averaged 72.0% (±2.3)
among samples. Qualitative data about metabolite structure were obtained for PCBs
88 and 149, as no metabolite standards for these congeners are available from
commercial sources at this time.
Biomarker assays
S9 fractions were used in biomarker assays enlisted to help detail the
metabolic pathway for PCB detoxification. The EROD and PROD assays work
identically, and differ only in their target enzyme: the EROD assay targets the CYP1A
isoform; whereas, the PROD assay targets CYP2B.
78
For the EROD assay, a starting solution of Tris buffer (to maintain pH at 7.4),
bovine serum albumin (to keep exthoxyresorufin in solution), MgCl2 (to maintain
ionic strength), water, and ethoxyresorufin (the substrate) is prepared. Each well of
the plate has 100uL of S9 fraction added to 100uL of starting solution. Addition of
50uL of a 2.5mM NADPH solution starts the reaction. A plate reader set at 530nm
excitation and 585nm emission measures the fluorescence generated when CYP1A
deethylates ethoxyresorufin. The PROD assay uses the same protocol, replacing the
exthoxyresorufin with pentoxyresorufin, thus requiring the use of CYP2B to
complete depentylation of the substrate. The same plate reader settings are used
because the same end product, resorufin, is measured in both arrays.
Results
Field study for in vivo metabolism
The chromatograms for the field samples indicate that many different
compounds are present. The extraction and derivitization procedures ensure that
only OH-‐PCBs are being detected (Kania-‐Korwell et al. 2004); however, many
different congeners could be metabolized to yield multiple metabolites for each
congener. Incidence of chlorine containing compounds was confirmed by the
presence of isotopic ratios for chlorine (Figure 3.2). Such compounds are not
naturally occurring. Screening the same samples under different SIM settings
allows for structure specificity. There is evidence to suggest that more than one
79
homolog class is transformed (Figure 3.3). SIM settings for hepta, octa, and nona-‐
chlorinated compounds did not detect any compounds, suggesting that highly
chlorinated congeners are not metabolized.
Figure 3.2 Tetragnathidae sample for in vivo analysis. The spectra corresponds to the peak indicated in the chromatogram. The scan using SIM settings for m/z=324 for penta-‐chlorinated metoxylated compounds indicates presence of metabolites. Structure could not be discerned, but presence of isotopic ratios for chlorine (100:30 isotopic peaks) indicate that these compounds are not naturally occurring.
80
Figure 3.3 The same Tetragnathidae sample indicated in the previous figure under
different SIM settings, shown here for m/z=353 to screen for hexachlorinated congeners. Spectral results for the peak indicated in the chromatogram confirm that compounds with six chlorines can be metabolized.
Qualitative description of PCB 88 and 149 in vitro metabolism
The incubation results indicated enzyme activity. An identical experimental design
was used for PCBs 88 and 149. The reagent blanks were identical to the negative
controls, and both were significantly different from the samples (see Figure 3.4).
Panel A is the chromatogram for the negative control, and panels B, and C are
chromatograms for the two sample sites where spiders were obtained with liquid
nitrogen. All panels reflect a treatment with PCB 88. In the negative control (Figure
3.4A) there is a peak that elutes at 38min, whereas the samples (Figures 3.4b and
81
3.4C) yielded a peak at 26min. The negative control samples showed peaks that
were dissimilar from both the reagent blanks and the samples obtained with liquid
nitrogen. The samples obtained with liquid nitrogen have chromatograms with
peaks that were not present in the negative controls or the samples obtained
without liquid nitrogen. These peaks in the samples collected with liquid nitrogen
are well defined, and feature unique mass spectra patterns.
82
Figure 3.4 Chromatograms for PCB 88 enzyme incubations. (A) negative control,
(B) Reese Mill, and (C) Robinson Bridge.
83
Additionally, there was good repeatability of results between samples.
Figure 3.5 shows chromatograms for samples incubated with PCB 88. Panels A
through E indicate that each sample had the peak appear at identical retention
times. It is important to note that where the magnitude of the transformation
appears to vary between replicate samples obtained at Reese Mill (Panels C, D, and
E) the experiment had to be modified for the last two replicates to account for low
S9 fraction supplies. For the replicates pictured in panels D and E all reagent
volumes were halved so as to allow for triplicate analysis. Panel F features the mass
spectra that was common to all samples and replicates for incubations with PCB 88,
providing additional evidence that the transformation occurring in the samples is
not only different from the peak seen for PCB 88, featuring a retention time nearly
two minutes after PCB 88, but also that there is a common metabolite generated by
the tetragnathid samples at both sites.
84
Figure 3.5 Chromatograms for enzymes obtained with liquid nitrogen and incubated with PCB 88 at Robinson Bridge (A & B) and Reese Mill (C, D, & E); and (F) a representative mass spectra. All samples were run in triplicate; however, for aesthetic clarity only five are shown here.
85
The chromatographic signal for PCB 149 was distinct from that of PCB 88. In
Figure 3.6, Panel A1 shows a chromatogram with a peak eluting at 26min for PCB
88, and Panel B1 shows a peak at a different time (29min) for PCB 149. The samples
from the same site were treated in the same manner. These peaks also possess two
different spectra, which is not surprising due to the differences in structure of the
parent compounds.
86
Figure 3.6 Chromatograms(1) and mass spectra(2) for enzyme incubations at
Robinson Bridge location for PCB 88(A) and PCB 149(B).
87
Quantification of PCB 61 metabolism
Isooctane blanks displayed no peaks, and both acetone control and negative
controls were identical to those runs (data not shown). Positive controls with rat
microsomes enriched with CYP2B showed multiple peaks with metabolites at high
concentrations(Figure 3.7).
Figure 3.7 Chromatogram for positive control. Note that no solvent peak is present because filament was off for first 10min.
Chromatograms indicated significant metabolism of PCB 61 (Figure 3.8) with
multiple peaks exhibited in addition to those expected at 29min for the recovery
standard and at 31min for 2-‐MeO-‐PCB 61. The standard used was for the ortho-‐
88
hydroxylated metabolite, which was the only standard available at the time. It is
likely that the other peaks represent the 3-‐MeO-‐ and 4-‐MeO-‐2’,3’,4’,5’-‐tetraCB
metabolites or cofactors.
Figure 3.8 Chromatogram for Reese Mill S9 fraction incubation with PCB 61, SIM
m/z = 310. Peak at 31min is for MeO-‐PCB 61 (indicated by thick arrow). The recovery standard elutes at 29min (indicated by thin arrow).
The quantitative data from incubations with PCB 61 indicate that spider
enzymes do have the capacity to generate OH-‐PCB metabolites, and potentially at
significant concentrations. The sample from the Robinson Bridge site did not differ
from the negative control, whereas the enzyme fraction obtained without liquid
89
nitrogen from Reece Mill did show low activity (Figure 3.9). An OH-‐PCB 61
concentration of 0.03ppm (±0.01 SD) was detected for enzymes obtained without
liquid nitrogen from Reese Mill (labeled as “no N2”), whereas enzymes obtained
with liquid nitrogen (labeled as “Reese Mill”) yielded a concentration of 1.63ppm
(±0.35). Robinson Bridge samples did not generate a detectable quantity of 2-‐MeO-‐
PCB61; however, this could be a result of halving the reagent volumes in order to
obtain results in triplicate.
Figure 3.9 Measured 2-‐MeO-‐PCB 61 after incubation with spider S9 fractions.
Metabolic Pathway
Biomarker analyses for CYP1A and CYP2B shed little light on metabolic
processes, as they were unable to detect any enzymatic activity in the spider
samples. It appeared that even for pooled samples, the enzyme concentrations
0
0.5
1
1.5
2
2.5
Negative Control
RM -‐ no N2 RM -‐ N2 Robinson Bridge
Concentration (ppm
)
90
might not have been high enough to yield a measurable signal, as the only
measureable signals came from the positive control (rat microsomes enriched in
CYP2B) for the PROD assay.
Discussion
In vivo anaylsis
In vivo results indicate that metabolites for PCBs with six or fewer chlorines
are present in spiders at the Twelvemile Creek arm of Lake Hartwell. Expectations
were confirmed when metabolites for congeners with seven or more chlorines were
not detected, as such congeners are highly persistent in the environment due to
their recalcitrance to metabolism (Lehmler et al. 2000). If spiders are able to
metabolize their body burden, it is not surprising that the higher chlorinated and
thus more bioaccumulative congeners fail to be detoxified. These analyses provided
data that confirmed the presence of chlorine containing compounds, and while they
could not all be identified, it did indicate that in vitro studies could yield results that
could confirm the enzymatic capabilities of spiders.
Qualitative evidence of metabolism is an important contribution at this time
given the lack of commercially available standards for the selected PCB congeners
(88 and 149). While it was not possible to identify specific compounds with this
analysis, these qualitative results provide compelling evidence that chlorine-‐
containing metabolites are present in spiders – the first evidence of this kind.
91
Selected ion monitoring indicate what PCBs can be metabolized and which
structures are present.
In vitro analyses
The incubation results only had one sample for each site, however the
composite of 15 individuals and the same results from each site indicate a certain
robustness to the findings. Obtaining good recoveries because of the numerous
extractions and derivatization lends validity to the process. Use of diazomethane to
derivitize samples was 80% effective, but recoveries for individual extraction steps
are unknown. Initial samples collected were obtained without liquid nitrogen, and
did not indicate any metabolism. Use of liquid nitrogen allows the enzymes to
remain in their active conformations, whereas samples obtained without it lose
enzymatic activity as the enzymes may denature or change upon death. The sample
collection method was revised, and samples collected with liquid nitrogen were
used to obtained the results presented here. Time constraints prevented the
collection of additional samples; however, all samples had three separate
incubations to assess reproducibility of results, which was good (see Figure 3.5).
Results for PCB 88 incubations indicate that there is enzymatic capacity for
spiders to metabolize PCB 88. In vitro studies investigating PCB metabolism have
been completed, but mainly in mammalian systems (McKinney et al., 2006; Verrault
et al., 2009). The metabolism measured here represents the capacity of spider
enzymes for metabolism, but may not be representative of what occurs in the living
92
organisms. Enzymes that were able to transform the PCBs may not be the primary
enzymes used in detoxification, or may generate different metabolites than would
be generated in the living organism.
The metabolites most likely generated for PCB 88 are pictured in Figure 3.10.
These compounds are formed when adjacent hydrogenated positions are present,
and a hydroxyl group can replace a hydrogen. These are the most favorable
conditions for hydroxylation (James, 2001). While other metabolites are possible,
steric hindrance may bar the generation of 3’-‐OH-‐ and 6’-‐OH-‐2,2’,3,4,6-‐CB
metabolites.
Figure 3.10 PCB 88 and potential metabolite structures.
Results were expected to differ between PCBs 88 and 149 due to their
different chlorination substitution. PCB 88 is penta-‐chlorinated; whereas, PCB 149
93
is hexa-‐chlorinated. Both PCBs 88 and 149 are non-‐planar congeners. Incubations
with PCB 149 yielded a unique chromatographic signal and spectrum from those
obtained for PCB 88. The potential hydroxylated metabolites for PCB 149 are
shown in Figure 3.11. Compared to PCB 88, PCB 149 has an additional chlorine and
just one location where there are two adjacent hydrogenated positions on a ring.
The high level of chlorination for this PCB (six chlorines) makes it a more
recalcitrant compound, so it is possible that only one metabolite for PCB 149 can be
generated. The 4-‐OH-‐ and 5-‐OH-‐2,2’,3,4’,5’,6’-‐CB metabolites are the more likely
compounds to be generated because of the adjacent hydrogens (James, 2001). The
3’-‐hydroxy structure is not likely to be generated due to steric hindrance. Similar to
the previous incubation, there was just one peak generated for the transformed PCB
149. This could also be due to just one metabolite being generated, or co-‐elution of
the 4-‐hydroxy and 5-‐hydroxy compounds.
94
Figure 3.11 PCB 149 and potential metabolite structures
PCB 61 is a planar congener, which are known to have higher metabolism
rates than reported for non-‐planar congeners such as PCBs 88 and 149 (James,
2001). The chlorination pattern for PCB 61 allows for easier hydroxylation because
one ring is completely devoid of chlorines; which allows for many potential
pathways for hydroxylation since there are several adjacent ring positions with
hydrogens, not chlorines (Figure 3.12). Hydroxylated PCB 61 is also noted to be an
endocrine disrupting compound, causing estrogenic effects in fish and wildlife
(Carlson and Williams, 2001). Most importantly, standards were available for
hydroxylated and methoxylated compounds, so quantification could be completed.
95
Figure 3.12 Structure of PCB 61 and potential metabolites.
Quantification of metabolism indicated higher concentrations of MeO-‐PCB 61
generated with enzymes from Reese Mill than for those obtained at Robinson
Bridge, which were not different from the negative control. Detoxifying enzymes
may occur at a higher concentration in spiders at Reese Mill, resulting in higher
activity and greater concentrations of metabolites, as compared to spiders at
Robinson Bridge due to their history of exposure. Spiders at Reese Mill are located
very close to the point source of contamination, and have possibly up-‐regulated
their detoxifying enzymes to handle their PCB body burden. These evolutionary
stresses were not as severe down river at Robinson Bridge, so this same activity is
not seen in that population. The concentration data for spiders at both locations are
96
reported in Chapter 4 (see Table 4.2 and Figure 4.2), which confirms that Reese Mill
spiders have a higher body burden than spiders at Robinson Bridge.
Many peaks other than those identified as 2-‐MeO-‐PCB61 were present in the
chromatogram for the Reese Mill incubation with PCB 61. For some peaks, the mass
spectra did not indicate presence of chlorine containing compounds, so it is likely
that the other compounds were cofactors generated by the S9 fraction in response
to exposure to PCB 61, not metabolites. The S9 fraction contains not just the CYP
isoforms likely responsible for the biotransformation of PCBs, but the entire
enzymatic library available to spiders. Enzymes that have the materials and energy
available to them in the S9 fraction can complete their functions, and subsequently
result in additional peaks in the chromatogram.
Co-‐elution proved to be a challenge to successful identification of metabolite
structure. A single peak yields two possible interpretations: 1) one metabolite was
generated, or 2) multiple metabolites are present but they co-‐elute. Use of ortho-‐
and para-‐substituted metabolite standards confirmed that the method utilized is
capable of separating methoxylated isomers. Commercially obtained standards for
isomers with identical chlorination and different methoxylation patterns were
shown to elute at different times. This check is representative of just two
metabolites for a single PCB congener, as standards for all isomers for PCBs 88 and
149 were not available. The lack of available metabolite standards for these
congeners precluded both quantification and resolution of this question.
97
Spiders are likely to be the organism responsible for metabolizing the parent
compounds. The focus of the investigations to date have been fish and mammals
(Buckman et al., 2006; McKinney et al. 2006; Verrault et al. 2009); however, these
results indicate that spiders may have evolved the capacity to metabolize their
contamination body burden. It is unlikely that spiders are receiving these
compounds from prey. When spiders liquefy and consume insects the OH-‐PCBs are
exposed to the oxygenated environment. Extended exposure to oxygen in the
laboratory can result in OH-‐PCBs transforming to catechols (Lehmler et al., 2009).
Lag time between expelling digestive enzymes onto the prey and consumption of
liquefied tissue may be long enough for catechols and other compounds to form.
Experiments to measure the catechol load in spiders and the OH-‐PCB content in
prey species would be good complementary studies.
Comparison of in vivo and in vitro results
The retention times and mass spectra obtained for PCBs 88 and 149 were
cross referenced with the data obtained for the in vivo study. There were no
incidences where peaks at the retention times of the in vitro study featured the same
mass spectra, which could be due to co-‐elution in the in vivo samples. Alternatively,
these two highly chlorinated PCBs may not be metabolized in the field. If there are
other PCBs that are more amenable to metabolism and less recalcitrant they could
be preferentially metabolized (James, 2001). Continuing input of such PCBs to the
metabolic system of the spider would result in lower concentrations for more easily
98
metabolized compounds, and greater concentrations of the more recalcitrant
congeners.
Likewise, the results obtained for PCB 61 were not present in the field
samples. This was expected, as PCB 61 is not present in the Aroclor mixtures known
to have contaminated the Twelvemile Creek / Lake Hartwell system. The procedure
used in Chapter 4 to analyze spider PCB concentrations did not detect PCB 61.
Pathway description
Biomarker assays were attempted to indicate the metabolic pathway for
PCBs in spiders. EROD and PROD assays would have been able to describe the
enzymatic activity of CYP1A and 2B, respectively, as well as indicate the PCB
detoxification pathway (Yang et al., 2008). There was no detection of enzymatic
activity for spider samples obtained with liquid nitrogen. It is likely that there was
not enough protein in the S9 fractions to generate a detectable signal.
To try to elucidate the pathway, rat microsomes with enriched CYP2B
concentrations were used as positive controls for the incubation experiments. They
were exposed to PCBs 61, 88, and 149 at the same time and in the same way as the
spider samples. The results from this positive control were identical to the results
from Reese Mill and Robinson Bridge samples obtained with liquid nitrogen, which
supports the hypothesis that spiders have the ability to metabolize. These results
support the idea that the same metabolites yielded by CYP2B in rats are generated
by spider S9 fractions. The enzymes in spiders have yet to be determined, and may
99
be deserving of future research; however, the results of these experiments would
direct investigations towards the cytochrome P450 suite of detoxifying enzymes, in
particular CYP2B.
Conclusions The first hypothesis that spiders can metabolize PCBs was supported by both
the in vivo and in vitro studies. The screening of field samples for presence of PCB
metabolites indicated that PCBs with six or fewer chlorines can be metabolized.
PCB metabolites with seven or more chlorines were not present in the samples
analyzed. Their recalcitrance to metabolism is a key driver behind their potential
for bioaccumulation, in conjunction with their increased chlorine character.
Metabolites generated in vitro for PCBs 61, 88, and 149 were not detected in the
field extracts, which could be due to their absence in the environment (PCB 61) or to
a lack of metabolism by spiders in the field (PCBs 88 and 149).
The laboratory studies provide evidence that spiders have the potential to
metabolize PCB congeners. PCBs 88 and 149 were demonstrated to be metabolized
by spider enzymes. Screening with unique SIM parameters for PCB 88 allowed for
detection of a single peak with a retention time and mass spectra different from that
of the parent material. Results for incubations with PCB 149 also had retention
times and mass spectra different from those for the parent material. These results
indicate that spider enzymes do have the potential to metabolize PCBs with as many
as six chlorines.
100
Transformation of PCB 61 to 2-‐OH-‐PCB 61 was quantified, and also supports
the hypothesis that spiders have the potential to metabolize their PCB body
burdens. Chromatograms for PCB 61 incubations differed from those with PCBs 88
and 149 in that there were many detected peaks, which supported the second
hypothesis that metabolism of PCB 61 would produce multiple OH-‐PCBs. This is
likely due to the multiple pathways that are available for OH substitution onto the
second ring of PCB 61; whereas a single likely pathway exists for PCBs 88 and 149.
The peaks that did not indicate presence of chlorine containing compounds may
represent cofactors and other compounds associated with metabolism that were
generated by the S9 fraction.
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CHAPTER 4
WEBS AS SUBSTRATE FOR PCB PARTITIONING
Introduction
Spider webs are one of the most ubiquitous examples of predation strategy in
our environments. The primary function of the spider web is to capture prey. To do
so, the web must support the spider, withstand the force of prey striking and
struggling in the web, and retain prey long enough for the spider to consume the
creatures (Chacon and Eberhard, 1980). Research into the form, chemistry,
materials, and ecology of the webs has been investigated over the past thirty years.;
however, a research gap exists where the characteristics and function of webs are
applied to toxicology and contaminant exposure pathways for spiders. Based upon
information about the composition, construction, and ecological role of webs, it is
hypothesized here that a key element of detoxification of PCBs by spiders may
involve exporting body burdens of contaminants to webs to alleviate stress on the
organism.
Araneidae spiders, which are a spider family that is closely related to
Tetragnathidae spiders, are also orb-‐weaving spiders and use a sticky, spiral thread
to constitute the bulk of the web. It is important to note that the amino acids that
comprise the silk proteins are all chiral, and all oriented in the D-‐amino acid form.
The majority of the protein is in the β-‐sheet formation (Eisoldt et al., 2011;Eisoldt et
al., 2012). The core of the silk proteins is an amphiphilic repetitive sequence of the
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same amino acids, for multiple thread types and across species types (Heim et al.,
2009;Heim et al., 2010). Web extracts of orb-‐weavers include fatty acids, alcohols,
esters, ketones, and low molecular weight hydrocarbons (Prouvost et al., 1999). At
contaminated sites, it is suspected that webs also contain contaminants.
The most important behavior from a toxicological standpoint is that
Tetragnathidae spiders consume their webs and rebuild them daily. Up to 90% of
the web material is recycled without being digested or reworked (Peakall, 1971),
which saves energy and creates a storage location for lipid-‐soluble contaminants.
The goal of the study was to test the hypotheses that spider webs contain
PCBs, and that Tetragnathidae spiders use their webs to store PCBs. Data from
analyses of the total PCBs, chiral PCBs, and homologs were examined for support of
these hypotheses.
Materials and Methods
Sample collection
Webs were collected at locations along Twelvemile Creek (see Figure 4.1 for
sampling locations, Table 4.1 for distances between sites and point source). Web
density along the shoreline varies. Our observations corroborate the claim that
Tetragnathidae spiders require approximately one meter of cubic space to construct
their webs (Gillespie, 1987); however, this varies with available habitat space.
Narrow sections of stream with good tree cover and many branches overlaying the
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water column were host to many more webs than sections that were wider with
poor tree coverage, and hence more accessible to avian predators.
Stainless steel spatulas were cleaned with isooctane prior to collection at
each site, and used to spool webs. Care was taken to avoid collecting extraneous
matter including leaf debris and prey remnants. Non-‐web material was removed by
tweezers during collection, and again before processing in the lab. This was done to
prevent misappropriation of PCB content to webs from the materials captured in the
silk material. Webs were stored at -‐20˚F until processed. Each site had three
composite web samples. Approximately 100 webs were pooled at each site to allow
for sufficient mass for analysis. One representative sample of 15 spiders was
collected along with the webs at each site. All spiders analyzed in this study were
removed from the webs that were collected.
Table 4.1 Sampling locations and their distances from the point source.
Site Distance from Point Source
Distance from Previous Site
Reese Mill 0.3 km 0.3 km Belle Shoals 8.85 km 8.85 km Stewart Gin 16.31 km 7.46 km Robinson Bridge 22.39 km 6.08 km
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Figure 4.1 Map of Web Sampling Locations. (R) = Reference site upstream of Sangamo-‐Weston point source; (RM) = Reese Mill site; (BS) = Belle Shoals site; (SG)= Stewart Gin site; (RB) = Robinson Bridge site.
Sample extraction and clean-‐up
Web samples were weighed and recovery standards PCBs 14 and 169
(Accustandard, Wellington, CT) were added to the cells prior to extraction on
Dionex 200 ASE. PCBs 14 and 169 were used as recovery standards, at 55% (±24
SD) and 30% (±23 SD) respectively across both sample types. Concentrations were
not corrected for recovery.
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A 9:1 hexanes:acetone solution (v/v) was used for the extraction (García et
al., 2008). Heating time was 5min followed by two 2min static cycle. Cells were
heated to 100˚C at 1500psi, using two cycles of 5min heating and 5min static. A
flush volume of 60% was used, and solvent lines were purged for 60sec (Kania-‐
Korwel et al., 2008b). After each sample the system was rinsed with the solvent
mixture to prevent carryover between cells.
The extracts were condensed to 6mL under a steady stream of high purity
nitrogen, and lipid content was measured by a gravimetrical method. Briefly,
samples were cleaned on an alumina-‐sodium sulfate column (3.5g and 1.5g,
respectively). Columns were eluted with hexanes to a final volume of 10mL, then
solvent exchanged for isooctane. Samples were condensed under nitrogen to a final
volume of 2mL for spider samples, and 1mL for web samples. Internal standards of
aldrin and PCB 204 were added before analysis. Quality of assessment was
maintained through use of procedural blanks, laboratory control samples in
duplicate, matrix spikes in duplicate (aldrin and PCB 204, Accustandard), blank
tissue samples, and check standards with each batch of 10 samples.
GC-‐ECD analysis of samples
An HP 6890 gas chromatograph with an RTX-‐5 column (Restek, 60m x
0.25mm x 0.25μm) was used to quantify the PCB content of spider webs. The
temperature program began at 115˚C, and was held steady for 2min. It was then
ramped at a rate of 8°C/min to a temperature of 185°C and held for 8min. Lastly the
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temperature was ramped at a rate of 2°C/min to a final temperature of 265°C, and
held for 20min.
An HP 6850 gas chromatograph equipped with a Chirasil-‐Dex column (25m x
0.25mm) and a 63Ni electron detector was used for enantioselective analysis. The
temperature program began at 100˚C for 2min, then ramped at 10˚C/min to 170 and
held for 10min, then ramped at 8˚C/min to 180˚C. The detection limit did vary
somewhat by congener, but was approximately 25ng/L for chiral PCB congeners.
The EFs for the racemic standards (PCBs 91, 95, 136, 149, and 174) were between
0.492 (± 0.003 SD) and 0.504 (±0.006 SD). Chiral standards were run prior to
samples in every sequence to maintain confidence in the results. Precision was
maintained by repeat injections every fifth sample.
PCB concentrations and EF values among different sampling locations were
assessed by one-‐way analysis of variance (ANOVA) using Tukey’s test to determine
significance (p<0.05). Nonmetric-‐multidimensional scaling statistical analysis
(NMS) was completed using PC-‐ORD 4.0 software (MjM software). The autopilot
mode was utilized, and the chi squared coefficient used as the distance measure
(McCune and Mefford, 1999; McCune et al., 2002).
Results
Spider concentrations were greater than those observed in their respective webs,
though the extent to which they were greater varied (Figure 4.2). Concentration
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ratios between webs and spiders fall sharply to become much more even with
distance from the point source (Table 4.2).
Figure 4.2 ΣPCB concentration (ng/g lipid) for spiders (n=1) and webs (n=3). Error bars indicate one standard deviation in either direction.
Table 4.2 ΣPCB content in spiders and webs at each sampling location. a No PCBs were detected at the Belle Shoal site, which is likely a function of low sample weight.
Sampling Location
ΣPCBspiders (ng/g lipids)
ΣPCBwebs (ng/g lipids)
[spiders] / [webs]
Reese Mill 2902.2 154.4 ± 40.2 18.8 Belle Shoals 899.7 n.d.a -‐-‐ Stewart Gin 284.0 203.8 ± 42.3 1.4 Robinson Bridge 1608.3 356.1 ± 107.9 4.5
This trend is described for the Reese Mill sample site in greater detail in
Table 4.3, which shows the homolog distributions, and is discussed below.. While
the table lists values obtained for the Reese Mill site only, it is representative of the
0
500
1000
1500
2000
2500
3000
3500
Reese Mills
Belle Shoals
Stewart Gin
Robinson Bridge
Σ PCB (ng/g lipid)
spider
web
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patterns observed at all sampling locations where web concentrations were
sufficient for detection. Spiders had greater concentrations for all homolog groups
analyzed except for di-‐chlorinated and nona-‐chlorinated congeners (Table 4.2).
Webs had a concentration of 40.3ng/g lipids of di-‐chlorinated congeners, whereas
spiders did not have detectable quantities of such congeners, and webs also had
nona-‐chlorinated compounds present, whereas spiders did not.
Table 4.3 Homolog concentrations in spiders and webs at the Reese Mill sampling site.
Homolog Class [spiders] (ng/g lipids)
[webs] (ng/g lipids)
Dominant compartment
Di 0 40.3 Webs Tri 135.2 3.9 Spiders Tetra 903.5 75.1 Spiders Penta 1357.5 26.3 Spiders Hexa 396.0 2.7 Spiders Hepta 108.4 1.6 Spiders Octa 1.6 3.2 Webs Nona 0 1.4 Webs
Homolog Patterns
When averaged across the sampling sites, spiders had consistent homolog patterns
among sampling sites (Figure 4.3). The penta-‐chlorinated congeners had the
highest percentages, followed by tetra-‐chlorinated and hexa-‐chlorinated congeners.
The lowest percentages were seen in the di-‐ and octa-‐chlorinated homolog classes,
and no nona-‐chlorinated congeners was measured in spiders at any site other than
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at Belle Shoals. Spiders from the Reese Mill site differed from the other three
locations in that tri-‐chlorinated congeners contributed to their overall PCB
concentration at a higher percentage, comparable to that of hexa-‐chlorinated
congeners at that site (Figure 4.3A).
Figure 4.3 Homolog patterns of PCB concentrations
in spiders (A) and webs (B).
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The web samples had a somewhat different homolog pattern (Figure 4.3B).
There was no consistent concentration pattern among sites; however, nona-‐
chlorinated compounds were observed to be the lowest contributing homolog class,
just as they were in both the spider samples.
Results at the individual sites varied. Reese Mill was the site closest to the
point source, and also had the greatest contribution by di-‐chlorinated PCBs among
the sites analyzed. Webs at Reese Mill had a significant contribution by di-‐
chlorinated PCBs at 26%. The source of these congeners was likely volatilization
from the water column. Webs at the Stewart Gin site did not have an abundance of
di-‐ and tri-‐chlorinated congeners, with less than 1% of the total PCB concentration
being attributed to the lower chlorinated congeners. This differed from Robinson
Bridge, which while further downstream from the point source, featured almost 5%
each of di-‐ and tri-‐chlorinated congeners. The Robinson Bridge site had a
significantly higher contribution of tetra-‐chlorinated congeners to webs than
spiders (48.5% in webs, 10.6% in spiders), which indicates that there is likely input
of these congeners to webs from both spiders and volatilization from the water
column.
Chirality Data
Nearly all web samples contained adequate concentrations of PCBs 91, 95,
and 149 to quantify and assess for chirality. Some of the Stewart Gin replicate
samples did not have high enough concentrations of the chiral PCBs to assess their
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chirality on the Chiralsil-‐Dex column; as a result, the EF graphs for this site reflect
values for only one sample and do not feature error bars. Additionally, the Stewart
Gin site did not have a high abundance of spiders, and a pooled sample of sufficient
mass was not able to be obtained for use in chiral analysis.
In Figure 4.4 the EF values for webs from all four sampling locations is
shown. Both PCB 91 and 95 were approximately racemic. PCB 95 concentrations
fell below detection limits in webs from Belle Shoals and Steward Gin, but at Reese
Mill and Robinson Bridge the EF was found to be approximately racemic. PCB 149 is
significantly nonracemic at all locations, with the second eluting congener being
preferentially retained in the organisms. Haglund and Wiberg (1996) determined
that on the Chiralsil-‐Dex column the (+) enantiomer elutes first, and the (-‐)
enantiomer elutes second for PCB 149. The data for PCB 149 are dissimilar from
that observed for PCBs 91 and 95 in this study, noted in Chapter 2, and as well as
what was observed in leaves by Dang et al. (2010).
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Figure 4.4 Enantiomeric fraction values for chiral PCBs detected in spiders (A) and webs (B). Error bars indicate 95% confidence interval.
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The EF data for PCB 149 also fails to support the hypothesis that webs
exhibit similar EF patterns as spiders (Figure 4.4 The EFs in the spider samples
were racemic (Reese Mill) or less enriched in the second enantiomer than the web
samples (Belle Shoals and Robinson Bridge).
Figure 4.5 NMS plot for spider and web samples. Samples were included for all
sites. The points that fall outside of the circles represent webs.
The NMS plot of web and spider EF values for PCBs 95 and 149 indicated a
different distribution for the two sample types. For the plot shown, web and spider
samples from all species and locations were incorporated (Figure 4.5). Within the
groups the relationships were less clear. Although grouped together, the data for
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webs did not indicate any spatial trends. For spiders, samples closest to the point
source fall near the top of the plot, and the most distant spider sample falls at the
bottom of the oval; however, this trend cannot be deemed significant as only one
pooled spider sample was supplied for each site. Points that fall outside of the
circles all represent web samples.
Discussion
Total PCBs
The change in ratios likely tied to the concentration in spiders decreasing
with distance from the point source. Spider concentration varied by up to an order
of magnitude, whereas web concentration only changed by an approximate factor of
two. It is proposed here that differences in evolution at sampling sites may affect
the concentrations observed. Spiders at Reese Mill have been shown to exhibit
higher metabolic activity (see Chapter 3), which is likely due to their need to
detoxify a more significant body burden than observed at other sampling locations.
If the spiders expend energy metabolizing their body burden they may not have as
great a need to sequester contaminants. Spiders have a lesser body burden at the
more distant sites (see data for Robinson Bridge spiders), which would not place as
great a demand on the spiders to actively detoxify and decrease their PCB
concentrations. This would allow more energy to be directed towards growth and
reproduction (Walker et al., 2006), which could also contribute to a lesser body
burden.
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It is important to note that the transfer of PCBs could move in either
direction – from the spiders to the webs, or the webs to the spider. One anomaly in
the data was that the Belle Shoals site did not have any detectable PCBs in the webs,
which is likely a function of low sample weight. It was not possible to obtain
samples from Belle Shoals in excess of 1g due to low web and spider density at that
site. The river was wider at this location, and there was less tree cover, allowing for
greater access by birds to spiders.
The PCB concentration in webs from all sampling locations were similar,
varying by only a factor of about two, despite variation in spider concentration
among sites. This could be linked to longevity of the material as it relates to the
lifetime of the spider. Spiders accumulate lipid tissue that may remain in their
system over the course of their life; whereas, web material may not last as long as
the lipids within the spider regardless of material recycling (Peakall, 1971). If a web
is destroyed, the contaminated material cannot be consumed by the spider and a
new web must be constructed from new, less contaminated material. The ratio
reflects not so much a chemical limit for the mass of PCBs that can associate with the
material, but rather points towards physical reduction of PCBs exposure when webs
are destroyed.
Homologs
The observed homolog patterns may be explained by contributions from
both volatilization from the stream and spiders. Spiders receive their entire body
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burden of PCBs via trophic transfer. Webs function as a tissue external to the body,
and are suspended directly above the water column. Analysis of homolog fugacity
indicates that lower chlorinated congeners are much more volatile than highly
chlorinated congeners (Schwarzenbach et al., 2003). The distribution for tetra-‐,
penta-‐, and hexa-‐chlorinated congeners in webs supports the hypothesis that
spiders offload their PCB body burden to their webs; however, the higher
percentage of lower chlorinated congeners in webs as compared to spiders fails to
support the spider off-‐loading hypothesis. It is possible that PCBs volatilize from the
water column due to the contaminated sediment of Twelvemile Creek and sorb onto
the webs. If true, then it follows that the PCBs present would more closely mirror
the profile seen in the water column. Dang (2012), using polyethylene passive
samplers, determined that the distribution of PCBs in Twelvemile Creek was skewed
towards the lower chlorinated congeners, so an abundance of lower chlorinated
congeners could be due to volatilization. Additionally, Dang (2012, unpublished
data) determined that about 10% of the PCBs sorbed onto Rhododendron leaves at
a site just down river at Shady Grove in Pickens, SC, were di-‐chlorinated. It was
concluded that because the water column also had detectable concentrations of di-‐
chlorinated congeners that volatilization was the source of the lower-‐chlorinated
congeners.
Volatilization as a source of PCBs to webs at Stewart Gin is not supported;
rather, the abundance of hepta-‐ and octa-‐chlorinated compounds indicated that
PCBs from spiders are the predominant source to webs. The homolog distributions
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of spiders and webs most closely mirror each other at Stewart Gin, again providing
evidence that spiders off-‐load their body burden to webs. The homolog distribution
at the Robinson Bridge site (Figure 4.3), like the data from Reese Mill, provides
evidence that volatilization is the likely supplier of di-‐ and tri-‐chlorinated congeners.
While the contribution of the lower chlorinated congeners is less than what was
observed at Reese Mill, their presence is evidence that the water column is
supplying a portion of the PCBs observed in webs.
A spatial pattern in homolog enrichment appears in the data. Sites closest to
the point source (Reese Mill) have broader PCB distributions in spiders that capture
lower chlorinated congeners, whereas sites more distant (Robinson Bridge) are
enriched in the tetra-‐, penta-‐, and hexa-‐chlorinated congeners. There may be a
change in the source to the spiders. Dang (2012) also determined that there are
ongoing sources of PCBs to Twelvemile Creek. These sources are closer to the Reese
Mill site. The lower chlorinated congeners are the most easily removed from the
ecosystem via volatilization and bacterial degradation (Farley et al., 1996). Such
congeners may not be present at high concentrations at the more downstream
sampling locations; hence, the smaller contribution of lower chlorinated compounds
in webs at those downstream sites as compared to the upstream web distributions.
Turbulence of the water in the stream could also influence volatility of the
PCBs in the water column. High turbulence can reduce the energy necessary to
escape the water phase, thus encouraging higher weight PCBs to volatilize. The
123
process is likely more complicated than web PCB content being derived from a
single source.
While the greater concentrations of di-‐chlorinated congeners in webs can be
explained through fugacity, the presence of nona-‐chlorinated congeners is more
difficult to explain. Nona-‐chlorinated congeners are more bioaccumulative than
lower chlorinated congeners due to their higher chlorine content, and Kow value
(Schwarzenbach et al., 2003). These congeners should preferentially be retained in
the organism. Their presence in the web may be attributed to spiders offloading
their body burden into lipid tissues outside of the body. Spider webs are recycled
by the organisms, with nearly 90% of web material being reused in new webs spun
nightly without being metabolized by the organism (Peakall, 1971). Spiders may be
able to store these contaminants outside of their bodies. The high Kow value,
homolog recalcitrance to metabolism, and recycling of web lipids may all contribute
to the accumulation of highly chlorinated congeners in the web material.
Chirality
The chirality data fail to support the hypothesis that webs are mirrors of the
contamination seen in spiders. Rather, it provides evidence that suggests that PCB
sorption to webs is an enantioselective process. The data from the Twelvemile
Creek arm of Lake Hartwell discussed previously (see Figure 2.2) indicated that the
EF value for spiders at the lake was racemic. The data obtained for the river spiders
indicate that over the course of the gradient down the river the EF values for PCBs
124
95 and 149 both reflect an increasing prevalence of the first eluting enantiomer.
This behavior is not likely attributed to a change in the spider uptake process, but
rather a change in the source of PCBs. The results for PCB 95 are similar to those
obtained for lakeshore spiders (Chapter 2), as are the EF results for PCB 91 and 149
at Reese Mill, but it is possible that with an increased sample size the trend would
be found nonsignificant. Alternatively, the process of off-‐loading the PCB body
burden to the webs could be a non-‐selective process, whereas PCBs sourced to the
webs from the water column via volatilization may have a non-‐racemic signature.
Fugacity should be identical for both enantiomers, but if the starting material in the
water column does not have a racemic signature, then the webs would have an
enriched EF value as well. Previous investigations at this site have indicated that
PCB 95 is racemic in the water column, and PCB 91 is enriched in the first eluting
enantiomer (Dang, 2012). PCB 95 was found to be racemic, which is similar to the
water column but differs from that measured in spiders. PCB 91 in webs was also
racemic, but differed from the values seen for both spiders and the water column.
Comparison between the spider and the web EF data would indicate that
webs are not good indicators for the contamination profile in spiders; however a
larger sample size of spiders would allow for a better assessment of the
contamination profile for that population. The NMS plot of web and spider samples
failed to indicate any spatial patterns (Figure 4.5), but suggested that webs have a
distinct EF profile compared with spiders at the same location. Web EF values were
125
very similar among sites, and resulted in a clear grouping of those samples in the
plot.
Conclusions
The hypothesis that webs have PCB content was confirmed by these
investigations. Homolog patterns support the hypothesis that spiders off-‐load their
body burden to their webs. The distribution pattern for webs roughly mirrors that
of spiders, though with a higher contribution of di-‐ and tri-‐chlorinated congeners, as
well as nona-‐chlorinated congeners. It is likely that while the majority of the highly
chlorinated congeners are sourced from the spiders, most of the mass of lower
chlorinated congeners is due to volatilization from the water column.
Chirality data provide additional support for the spider off-‐loading
hypothesis. The non-‐racemic values for PCB 149 indicate that a biological process is
likely affecting the transport from spiders to webs. NMS plots where web and
spider samples are clearly grouped and do not overlap also suggest
enantioselection.
126
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CHAPTER 5
CONCLUSIONS AND RECOMMENDATIONS
Conclusions
Chirality investigations failed to support the hypotheses that each spider
species would be distinct from the others. The second hypothesis, that spider EF
values would be distinct from prey EF values, was supported by the chirality data.
Spider values shifted in the direction favoring retention of the first eluting
enantiomer for PCB 91 compared to the midges; EF values for PCBs 95 and 149 did
not have a clear shift in direction. This change in EF for PCB 91 could be a product
of metabolism on the part of the spider, or spider off-‐loading of their body burden to
web material.
Evidence from in vivo and in vitro studies support the hypothesis that spiders
can metabolize their PCB body burden. Analysis of field extracts provided evidence
that PCB metabolites are present in spiders located along the Twelvemile Creek arm
of Lake Hartwell. There was no detection of metabolites with seven or more
chlorines. Although these results supported the hypothesis that spider can
transform their PCB body burden, the actual products of metabolism were less clear
due to the number of unidentified peaks in the metabolic fraction. Laboratory
incubations of enzymes with PCBs 88 and 149 provided evidence that these
congeners can be transformed by spider enzymes to a single compound distinct
from the parent material. PCB 61 was partially metabolized to 2-‐MeO-‐PCB 61, and
potentially to other metabolites.
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Web investigations affirmed the hypothesis that webs have measurable
concentrations of PCBs. The concentrations are not significant enough to warrant
their inclusion in ecological risk assessments, but may help spiders manage their
PCB body burden. The hypothesis that spiders are the source of these PCBs was
partially supported due to similarities in the homolog distribution patterns between
spiders and webs; however, the greater presence of di-‐ and tri-‐chlorinated
congeners in webs indicates that volatilization may also contribute to the total PCB
concentration in webs. Changes in chirality from spiders to webs indicate that
biological processes may be affecting the transport of chiral PCBs from spiders to
webs, providing additional evidence that spiders contribute to web PCB content.
Recommendations for Future Work
An exposure study could be completed where prey insects are reared with
exposure to a limited number of PCB congeners, and are in turn fed to spiders. This
would allow for targeted analysis of the transfer between trophic levels, at what
concentrations, and how the chirality is affected at each level of the food chain. Such
a study could also investigate the metabolism of the PCB congeners at each level of
the food chain, or even investigate if trophic transfer of PCB metabolites occurs.
Such investigations would answer lingering questions about the source of OH-‐PCBs
in spider, and whether or not OH-‐PCBs in prey are transformed to catechols during
the feeding process.
131
Such a study could allow for a mass balance to be conducted. This would be
the optimal way to describe fate and transport. An enclosed food web would also
allow for collection of spider excrement, which has yet to be investigated for PCB
content. The material is challenging to collect, as the spiders are suspended above
the water when they release it to the environment, and it drops into the water
column where it dissolves. If spiders are removed from the habitat after controlled
feeding exposures and sequestered in a fish tank for a few days enough excrement
might be collected to begin analyzing what exits the organism via excretion.
A study of this nature was attempted for this dissertation; however, it was
unsuccessful due to low population yield of exposed midges. Additional
complications arose when spiders were unable to spin webs successfully in the
provided enclosures. It is hypothesized that a better prey yield coupled with a
cooler, more humid synthetic habitat for spiders could provide a better study
system.
Additional metabolite studies can also be conducted. The wider array of
metabolite standards now available would allow for consideration of different
parent congeners. Additionally, obtaining standard for 3-‐MeO-‐ and 4-‐MeO-‐PCB61
could allow for a more comprehensive analysis of the data already obtained.
The attempts to determine the metabolic pathway for spiders were
inconclusive. Use of antibodies to identify which enzymes are active could be an
alternative way to determine the pathway. Antibodies for CYP1A and CYP2B can be
developed with fluorescent tags such that when activity is detected there is a
132
measureable signal from the antibodies. This could be challenging, too, because
many of these antibodies have been developed in mammalian systems, and may not
be optimal for use in arthropod systems.
A volatility exposure study could be conducted to better determine the
source of PCBs in webs. A controlled laboratory experiment that uses web material,
water, and the Aroclor mixtures present at this Superfund site could provide
information about which PCBs are volatilizing from the water column, and which of
those sorb on to the webs if at all.
133
APPENDICES
134
Appendix A
Supplemental Figures for Chapter 2
Figure A.1 EF values for chiral congeners at sampling locations in Tetragnathidae.
Figure A.2 EF values for chiral congeners at sampling locations in Araneidae.
0
0.5
1
T6 G H I K N O T12
PCB 91
PCB 95
PCB 149
PCB174
0
0.5
1
T6 G H I K N O T12
PCB 91
PCB 95
PCB 149
PCB174
135
Figure A.3 EF values for chiral congeners at sampling locations in basilica.
Figure A.4 EF values for chiral congeners at sampling locations for Chironomidae.
0
0.5
1
T6 G H I K N O T12
EF
PCB 91
PCB 95
PCB 149
PCB174
0
0.5
1
T6 G H I K N O T12
EF
PCB 91
PCB 95
PCB 149
136
Appendix B
Supplemental Tables for Chapter 2
Table B.1 Environmentally stable chiral congener substitution patterns
PCB Congener Chlorine Substitution Pattern 45 2, 2’, 3, 6 84 2, 2’, 3, 3’, 6 88 2, 2’, 3, 4, 6 91 2, 2’, 3, 4’, 6 95 2, 2’, 3, 5’, 6 132 2, 2’, 3, 3’, 4, 6’ 136 2, 2’, 3, 3’, 6, 6’ 144 2, 2’, 3, 4, 5’, 6 149 2, 2’, 3, 4’, 5’, 6 171 2, 2’, 3, 3’, 4, 4’, 6 174 2, 2’, 3, 3’, 4, 5, 6’ 183 2, 2’, 3, 4, 4’, 5’, 6
Table B.2 Sample sizes (n) for each EPA sampling site. Individuals were pooled
to create samples with approximately 1.5g mass.
Sampling site Tetragnathidae Araneidae Basilica G 4 0 1
T6 3 3 1 H 3 3 3 I 4 4 3 K 3 3 3 N 3 0 1 O 3 3 1 T12 3 4 1
137
Appendix C
Supplemental Tables for Chapter 3
Table C.1 SIM parameters used to screen for PCB metabolites. Three settings were used for each homolog class.
# Cl m/z SIM settings 1 218.57 216 / 218 / 220 2 253.02 251 / 253 / 255 3 287.47 286 / 288 / 290 4 321.92 320 / 322 / 324 5 356.37 354 / 356 / 358 6 390.82 388 / 390 / 392 7 425.27 423 / 425 / 427 8 459.72 458 / 460 / 462 9 494.17 492 / 494 / 496