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Ecotoxicology and Human Environmental Health
Alterations to the intestinal microbiome and metabolome of Pimephales promelas and Mus musculus following exposure to dietary methylmercury Kristin N Bridges, Yan Zhang, Thomas E Curran, Jason Magnuson, Barney J. Venables, Katherine E Durrer, Michael S. Allen, and Aaron P. Roberts Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.8b01150 • Publication Date (Web): 26 Jun 2018 Downloaded from http://pubs.acs.org on June 26, 2018
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Alterations to the intestinal microbiome and metabolome of Pimephales promelas and Mus
2
musculus following exposure to dietary methylmercury
3 a*
4
b
a
a
a
Kristin N. Bridges , Yan Zhang , Thomas E. Curran , Jason T. Magnuson , Barney J. Venables , b
5
b
Katherine E. Durrer , Michael S. Allen , and Aaron P. Roberts
a
6 7
a
8
Texas, 1155 Union Circle, Denton, Texas, 76203 USA
9
b
10
Department of Biological Sciences & Advanced Environmental Research Institute, University of North
Department of Microbiology Immunology and Genetics, University of North Texas Health Science
Center, 3500 Camp Bowie Blvd., Fort Worth, Texas, 76107
11 12
* Corresponding Author:
13
Kristin Bridges
14
[email protected] 15
University of North Texas
16
1155 Union Circle
17
Denton, TX 76203
18 19 20 21 22 23 24 25 26 27 28
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Abstract Mercury is a global contaminant, which may be microbially transformed into methylmercury
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(MeHg), which bioaccumulates. This results in potentially toxic body burdens in high trophic level
33
organisms in aquatic ecosystems, and maternal transfer to offspring. We previously demonstrated effects
34
on developing fish including; hyperactivity, altered time-to-hatch, reduced survival, and dysregulation of
35
the dopaminergic system. A link between gut microbiota and central nervous system function in teleosts
36
has been established with implications for behavior. We sequenced gut microbiomes of fathead minnows
37
exposed to dietary MeHg to determine microbiome effects. Dietary exposures were repeated with adult
38
CD-1 mice. Metabolomics was used to screen for metabolome changes in mouse brain and larval fish,
39
and results indicate effects on lipid metabolism and neurotransmission, supported by microbiome data.
40
Findings suggest environmentally relevant exposure scenarios may cause xenobiotic-mediated dysbiosis
41
of the gut microbiome, contributing to neurotoxicity. Furthermore, small-bodied teleosts may be a useful
42
model species for studying certain types of neurodegenerative diseases, in lieu of higher vertebrates.
43 44
KEYWORDS. Developmental toxicity, maternal transfer, metabolomics, microbiome, methylmercury
45
Introduction
46
Elemental mercury is released into the atmosphere through anthropogenic and natural processes, 1
47
and can undergo global transport before oxidation into its inorganic form by atmospheric components.
48
Inorganic mercury can then be introduced into aquatic ecosystems via wet or dry deposition. In sediment,
49
inorganic forms of mercury may be transformed by bacteria into mono-methylmercury (MeHg), a highly
50
bioavailable form which bioaccumulates and biomagnifies. The primary route of MeHg exposure for
51
adult life stages of aquatic organisms is through diet resulting in potentially high body burdens in
2
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organisms at high trophic levels. Methylmercury forms conjugates with biomolecules containing sulfur,
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providing a mechanism of transport across the blood brain barrier and from maternal diet to developing
54
offspring.
55
transfer.
4-6
Consequently, the primary exposure route for early life stage (ELS) fish is via maternal
5
56
A national dataset of Hg concentrations from adult freshwater fish in Canada reported mean wet
57
weight (WW) axial muscle concentrations ranging from 0.28-0.41 µg/g Hg in sport fish; with maximum
58
concentrations exceeding 10 µg/g. Similarly, WW yellow perch muscle concentrations reported from
59
over 2,000 sampling sites (Great Lakes region) ranged from 0.01-2.6 µg/g Hg. The concentrations
60
reported in wild fish in North America are of concern, as current estimates suggest sub-lethal effects on
61
adult individual fish health begin to occur at WW concentrations as low as 0.2 µg/g, while toxicity in early
62
life stage fish occurs at much lower concentrations.
63
vitreus) eggs in North American lakes ranged from 0.002 – 0.27 µg/g (WW) , with a separate study
64
reporting concentrations ranging from 0.004-0.104 µg/g Hg (WW) in yellow perch (Perca flavescens)
65
eggs. We previously published companion studies showing a range of developmental effects in ELS
66
fathead minnows (FHM) exposed to maternally-transferred MeHg. Results showed WW egg Hg
67
concentrations at the lower end of the reported range of concentrations (low treatment mean: 0.04-0.06
68
µg/g Hg) was sufficient to induce neurological effects.
7
8
3, 5, 9, 10
Concentrations of Hg in walleye (Sander 11
9
10, 12
69
Numerous studies exist which link exposure to metals to neurodegenerative diseases in 13-18
70
vertebrates.
71
from mitochondria-initiated oxidative stress, leading to changes in motor activity.
72
also been shown to preferentially accumulate in the mitochondria of neurons within the CNS, leading to a
73
cascade of biochemical changes which culminate in oxidative stress, neuronal degeneration and altered
74
neurotransmission.
75
developmental exposure to maternally transferred MeHg.
76
have typically focused on the CNS, there is an emerging link between nervous system function and gut
77
microbiota.
78
dietary substrates, forming the basis for bidirectional communication between intestinal microbes and the
79
CNS.
Parkinson’s disease (PD) is characterized by dopaminergic neuron loss in the mid-brain 19-27
22, 23, 25, 26, 28, 29
Changes in motor activity were observed in embryonic FHM following 10, 12
30, 31
24
Similarly, MeHg has
Though studies on neurodegeneration
Interestingly, intestinal microbes produce almost half of the body’s dopamine (DA) from
This relationship is known as the microbiome-gut-brain axis implying a role for enteric
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microbiota in brain function and neuro-development.
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microbiome and Parkinson’s disease (PD) has been established in humans. Transplants of fecal
82
microbiota from PD patients to germ-free mice induced PD associated motor-impairments
83
that the gut microbiome plays an important role in the pathology of some neurological diseases, and that
84
these effects are not species-specific.
85
Recently, a link between altered gut
24
suggesting
To investigate the role of the gut-brain axis in dietary MeHg-mediated neurotoxicity, we fed adult
86
FHM diets with environmentally relevant concentrations of MeHg (0.87 and 5.5 µg/g Hg DW) and
87
characterized the composition of the intestinal microbiome. We previously reported significant decreases
88
in DA concentrations in brains of FHM fed a comparable low-MeHg diet (0.72 µg/g Hg DW). This effect
89
on DA was also seen in the offspring of these animals along with motor-activity abnormalities, both
90
hallmarks of dopaminergic neuron degeneration.
91
body of evidence suggesting small-bodied teleosts and their offspring may serve as surrogates for higher-
92
vertebrate model species typically used to study neurodegenerative diseases in humans. To that end, we
93
replicated the experiment using male CD-1 mice (Mus musculus), and performed metabolomics on the
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mid-brains and gut microbiome analyses of sacrificed animals to compare with fish data.
95
further investigate mechanisms driving neuro-developmental toxicity of MeHg, we performed
96
metabolomics on newly hatched larvae to screen for changes in a range of low molecular weight
97
metabolites, and used the data to generate hypotheses regarding genes that may be differentially
98
expressed. These were subsequently verified using qPCR.
12, 24
Another goal of this study was to add to the growing
12
Finally, to
12
99 100
Materials and Methods
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Animal Care Methods
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ELS fish used in the present study were produced by two cohorts of adult FHM, both of which 10, 12
103
were maintained using the methods described in Bridges et al.
104
Texas Institutional Animal Care and Use Committee (IACUC) approved all FHM protocols (#1303-3).
105
Male CD-1 mice were maintained at the University of North Texas Health Science in Fort Worth, TX under
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IACUC protocol #2014/15-36-A04 (Figure S2).
(Figure S1). The University of North
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Experimental Design Fish Fish received assigned diets twice daily (n = 5 tanks/treatment), for 30-days. Diets included a
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control (0.02 µg/g Hg dry weight (DW)), and low treatment (0.72 ± 0.01 µg/g Hg DW in tanks used for
111
metabolomics , or 0.87 ± 0.08 µg/g Hg DW in tanks used for microbiome sequencing ), with an
112
additional high treatment (5.50 ± 0.6 µg/g Hg DW) in the cohort used for microbiome sequencing (n= 5
113
tanks). Diets were prepared using the methods described in Bridges et al , and analyzed for Hg. The
114
low treatment concentrations were selected to represent Hg exposure from a diet composed of benthic
115
invertebrates and zooplankton in some North American lakes, while the high diet represents those of fish
116
at high trophic levels or in polluted systems.
117
selected to mimic the primary route of environmental exposure.
118
unconsumed food pellets was not considered a significant route of Hg exposure for adult or larval fish
119
based on MeHg dissociation values reported in the literature, waste/unconsumed food removal practices,
120
and the transfer of embryos to clean water shortly after spawn.
121
12
10
10
10
7, 8, 10, 33
Exposure routes for adult and developing fish were 5, 33, 34
Waterborne MeHg from
10, 12, 33
Individual clutches of eggs were removed from breeding tiles in exposure tanks each morning,
122
and transferred to a crystallizing dish containing reconstituted-moderately-hard-water, and methylene
123
blue. Dishes were aerated and covered with parafilm to help prevent evaporation, and water levels were
124
checked twice-daily. Clutches were cultured at 23° C in an environmental chamber on a 16:8 photoperiod
125
(Table S1).
126
were sacrificed in buffered MS-222 (Sigma-Aldrich, St. Louis, MO) at the conclusion of the study and
127
rapidly dissected on ice. All tissues were immediately frozen at -80° C until further analyses were
128
performed.
129
Experimental Design Mice
130
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ELS fish used for further analyses were frozen frozen at -80° C until further use. Adult fish
Dietary exposure is the primary route of MeHg exposure for humans and was therefore deemed
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the most appropriate route of exposure for mice. Diets made from standard pelleted mouse chow
132
(LabDiet, USA) were prepared using the methods described in Bridges et al. , and analyzed for Hg. Mice
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(n = 7 mice/treatment) were fed either a control (0.02 µg/g Hg DW), low (0.43 µg/g ± 0.009 Hg DW), or
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high diet (4.39 ± 0.57 µg/g Hg DW), twice daily for 30-days. Concentrations of Hg in fecal pellets were
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monitored throughout the study (Table S1).
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At the conclusion of the study, mice were sedated using a 2-2-2 tribromoethanol solution, and
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perfused with physiological saline to remove excess blood. Brain tissue was quickly removed from skulls,
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sectioned on ice, and immediately frozen at -80°C. Mouse brains from the high treatment had obvious
139
differences in tissue integrity, making rapid dissections more difficult. Therefore, we only performed
140
metabolomics on midbrains from control and low diet animals, as we were able to dissect and freeze
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these samples within a similar time frame.
142 143
Mercury Determination
144
All biological samples, food, and fecal pellets were analyzed for Hg using a DMA-80 Direct
145
Mercury Analyzer (Milestone Inc., Monroe, Connecticut) according to USEPA Method 7473 (see SI for
146
details).
35
147 148 149
DNA extraction and Preparation for Sequencing Gastrointestinal tissue samples (n= 20) were thawed on ice, and pulverized with a sterilized
150
pestle in a 1.5-mL microcentrifuge tube. Genomic DNA was extracted using the Qiagen DNeasy Blood &
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Tissue Kit (Qiagen, Valencia, CA) following the manufacturer’s instructions with minor modifications. 16S
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rRNA was amplified using universal bacterial primers, which target the V4 hypervariable region , with
153
each sample prepared for PCR in duplicate. Purified PCR products were combined in equimolar ratios
154
and diluted according to the manufacturer’s recommendation for emulsion PCR on the Ion OneTouch™ 2
155
instrument (Life Technologies; refer to SI for details).
36
156 157
IonTorrent Sequencing
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An Ion OneTouch™ 2 instrument was used to prepare template-positive Ion Sphere Particles
159
(ISPs) from amplicon libraries, using the Ion OneTouch 400 Template Kit (catalog #4479878) per the
160
manufacturer’s specifications. Enrichment was performed with the OneTouch ES instrument (Life
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Technologies), followed by quantification of the enriched, template positive ISPs. Quantification was
162
performed using a Qubit 2.0 Fluorometer (Life Technologies) with the Ion Sphere Quality Control Kit
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(catalog #4468656). Enriched ISPs were loaded onto 316 v2 chips (catalog #4483324) and sequenced
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on an Ion Torrent Personal Genome Machine (PGM) using the Ion Sequencing 400 Kit (catalog
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#4482002) per the manufacturer’s instructions.
166 167 168
Sequence Analysis 37
Sequencing reads generated by the Ion Torrent PGM were processed using mothur v.1.36.1.
169
Identification of DNA sequences between samples was accomplished using sample-specific barcodes.
170
Primers and barcode sequences were trimmed, and low-quality reads (homopolymers > 8, length
97% similarity were grouped
176
into operational taxonomic units (OTUs). The Greengenes database was used for taxonomic assignment
177
using an 80% confidence cutoff.
38
Unknown sequences, as well as those from mitochondria, chloroplasts, archaea, and
39
178 179 180
Metabolomics Metabolite extraction was performed by homogenizing tissue samples (n ≥ 5 for all sample types, TM
181
details in Tables S2-3) in a 2:5:2 chloroform:methanol:Mili-Q
182
with D-27 myristate internal standard (IS) before evaporation under a gentle stream of nitrogen. Samples
183
were subjected to two separate derivatization steps and analyzed via gas chromatography-mass
184
spectrometry (GC-MS). The Agilent Fiehn Retention Time Locking Library was used to identify
185
metabololites and generate semi-quantitative relative response factors, which were ratioed against the IS
186
(see SI for details).
water solution. Supernatant was spiked
187 188 189
qPCR Gene Expression Analysis RNA was isolated from entire clutches of just-hatched larvae (n = 5 clutches/treatment) using a
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Promega Maxwell™16 Automated Nucleic Acid Extraction system (Madison, WI) with a Promega
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Maxwell™16 Total RNA Purification Kit. First-strand cDNA was synthesized using an iScript™ Reverse
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Transcription Supermix for RT-qPCR (Bio-Rad, Hercules, CA) and a Biometra Thermocycler
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(LABREPCO, Gӧttingen, Germany), following manufacturer’s instructions.
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Genes chosen for qPCR analysis were selected based on literature availability and their 40-43
195
relevance to the metabolomics data set.
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(Coralville, IA; Table S4). Reactions were prepared using a QuantiTect™ SYBR™ Green PCR Kit
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(Qiagen, Louisville, KY) according to the manufacturer’s guidelines. A Rotor-Gene (Corbett Research,
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Mortlake, Australia) was used for qPCR analysis. Differences in gene expression between treatments
199
were evaluated via statistical analysis of ∆∆Ct values (see SI for details).
Primers were made by Integrated DNA Technologies
200 201 202
Statistical Analyses UniFrac distances and principle coordinate analysis (PCoA) were used to compare differences in 44
203
microbial communities between samples.
204
treatments was determined using an Analysis of Molecular Variance (AMOVA). Overall similarities
205
between treatments were determined using an ANalysis Of SIMilarities (ANOSIM).
206
comparison of relative bacterial abundance between treatments was performed using a Kruskal-Wallis
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test, with a Tukey’s post hoc (p < 0.05 with 1000 Monte-Carlo permutations), performed using the
208
multcomp and coin packages in R (R Development Core Team, 2012). The false positive discovery rate
209
(FDR) for multiple hypothesis testing was controlled for using the Benjamini-Hochberg method.
210
Differences in microbial communities within and among
45
A nonparametric
46
Reports generated by AMDIS using the Agilent Fiehn Retention Time Locking Library were
211
filtered using an in-house R (v. 2.15.2) program that determined acceptable metabolite identification
212
based on similarity between sample retention indices and library retention indices, and a net mass
213
spectral quality scores of 70% or greater as calculated by AMDIS. Metabolite results which met all
214
filtration criteria were included in a two-tailed Welch’s t-test, to determine statistically significant
215
differences (p < 0.05) between treatments.
216
All other data were analyzed using JMP 11.1 (Cary, NC). Normality of all data was determined
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using the Shapiro-Wilk test. Mercury concentrations in larvae were determined using a single factor
218
ANOVA, by adult dietary Hg concentration. The ∆∆Ct values from qPCR analysis were analyzed using a
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single factor ANOVA, by treatment. An α of 0.05 was used to determine statistical significance for all
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tests.
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Results and Discussion
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The adult muscle Hg concentrations achieved in both cohorts of fish are reported in previous 10, 12
224
publications (available in Table S1).
225
are representative of fish muscle concentrations found in freshwater ecosystems in North America.
226
47
227
in exposed larvae that were roughly 0.04 µg/g higher than those of controls (n = 7 clutches/treatment,
228
Table S1).
229
of transfer is sufficient to induce developmental toxicity in several species of teleosts.
230
However, it is important to reiterate that these concentrations 3, 5, 34,
The amount of dietary Hg female FHM transfer to eggs is small, and resulted in WW Hg concentrations
5, 9, 48
Nevertheless, the results reported herein add to the body of evidence indicating this rate 10, 12, 49-51
Though MeHg-mediated effects were observed across all life stages and species, early life
231
stages demonstrated greater sensitivity to Hg exposure. In larval fish, 35 common metabolites were
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included in our statistical analysis (Table S2), 6 of which were significantly (p < 0.05) altered by
233
maternally transferred MeHg exposure (Table 1). These included increased relative abundances of
234
putrescine, L-serine, and glycerol. Conversely, significant decreases were observed in the relative
235
abundance of several long chain fatty acids (FAs), including stearic, palmitic, and oleic acids.
236
Twenty-two of the common metabolites detected in whole larval fish were also detected in the
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mid-brains of mice from the control and low Hg treatments (Tables S2-S3). The WW Hg concentrations
238
measured in mouse mid-brains were as follows: control: 0.002, low: 0.24, and high: 1.69 µg/g Hg (n = 5
239
for all treatments, Table S1). In total, 71 common metabolites (Table S3) were detected in samples of
240
mid-brains, 8 of which had significantly decreased (p < 0.05) abundances (Table 1). These included L-
241
glutamine, O-phosphatidylcholine, dopamine, tagatose, hydroquinone, L-ascorbic acid, inosine 5’-
242
monophosphate, and uracil. The abundance of stearic acid (significant in FHM larvae) in mid-brains of
243
mice was just above the cutoff for statistical significance (p = 0.06). However, when differences in tissue
244
type are considered, in conjunction with the extremely similar abundance ratio (Hg/Control; Tables 1. S2-
245
S3) in that of whole larvae, this change may still have biological significance. None of the significantly
246
altered metabolites in mouse mid-brains were also significant in the metabolomes of whole FHM larvae,
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which we attribute to tissue dilution (whole larvae were used), as many metabolites concentrated in the
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CNS did not have large enough responses to be detected via GC-MS screening. Fortunately, we
249
previously performed targeted analysis of DA via HPLC-MS/MS, in subsamples of larvae used for
250
metabolomics, and brain tissue of adults.
251
mid-brains of mice.
12
Decreased DA concentrations in that study mirror those in the
252 253
Table 1. Metabolites with significantly altered relative abundances detected in A) fathead minnow (FHM) larvae
254
exposed to maternally transferred dietary MeHg and B) mid-brains of male CD-1 mice fed a diet spiked with low
255
concentrations of MeHg; when compared with controls (details and full metabolite list in Tables S2-S3).
Hg/Control
A)
B)
p-value
Putrescine
1.99
0.001
L-serine
2.08
0.02
Glycerol
1.6
0.02
Stearic acid
0.68
0.04
Palmitic acid
0.72
0.04
Oleic acid
0.55
0.04
L-glutamine
0.41
0.01
O-phosphocolamine
0.67
0.02
Dopamine
0.29
0.03
Tagatose
0.42
0.04
Hydroquinone
0.62
0.04
L-ascorbic acid
0.19
0.04
Inosine 5’-monophosphate
0.62
0.04
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Uracil
0.61
0.04
256 257
In spite of the status of Hg as a contaminant of global concern, its effects on the microbiome are 52
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largely unknown
259
to a number of neurodegenerative diseases.
260
neurodegenerative diseases is just now receiving attention, in spite of the clear role of environmental
261
factors in some of these diseases.
262
teleost gut microbiome. As a whole, our results reveal exposure to MeHg can evoke effects on several
263
important pathways including immune function and detoxification, metabolism/energetics, and nervous
264
system structure/function. These effects may occur through a variety of mechanisms, some of which may
265
be mediated by the gut microbiome either through direct or indirect processes. Furthermore, it is
266
unknown whether neurotoxicity precedes microbiome changes, or vice versa, as communication of the
267
gut-brain axis is bidirectional.
. Most human exposure to MeHg occurs through diet, and exposure has been linked
53-55
19, 22, 23, 25
The role of the gut-brain axis in the progression of
Little is known about the effects of mercury exposure on the
32, 56
268
The results of the present study indicate significant treatment differences in gut microbial
269
communities (based on an AMOVA of unweighted UniFrac distances, p < 0.002). As seen in the PCoA of
270
unweighted UniFrac distances (Figure 1A), different microbial species were present in the high MeHg
271
samples, relative to those from the control and/or low. Unsurprisingly, the low and control treatments were
272
more similar (based on an ANOSIM of unweighted UniFrac distances, R = 0.18, p = 0.001), with both
273
treatments showing significant differences from the high treatment (control: R = 0.42, p < 0.0001; low: R =
274
0.34, p < 0.0001). These results were mirrored in the PCoA of weighted UniFrac distances (Figure 1B).
275
Seven phyla showed significant (p < 0.05) differences between treatments (Figure 2A). To further
276
investigate the bacterial community differences, genera with relatively high abundances (with at least one
277
sample > 5%) were identified for multiple comparisons (Figure 2B), with 18 out of 31 selected genera
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showing significant treatment differences (Figure S3).
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0.3
PCo2 (5.8%)
0.2 0.1 0 -0.1 -0.2 -0.3 -0.4 -0.5
-0.3
-0.1
0.1
0.3
PCo1 (9.3%) B
0.3
PCo2 (19.2%)
0.2 0.1 0 -0.1 -0.2 -0.3 -0.4 -0.4
-0.2
0
0.2
0.4
PCo1 (25.2%) Control
279
Low MeHg
High MeHg
280
Figure 1. Dietary MeHg shifted the gut microbial communities of fathead minnow, as seen in the (A) Principle
281
coordinates analysis of unweighted UniFrac distances and (B) principle coordinates analysis of weighted UniFrac
282
distances.
283 284
Proteobacteria and Bacteroidetes were the dominant phyla in guts of fish fed the high MeHg diet
285
(Figure 2A). Bacteria from the Bacteroidetes were further identified at the genus level as Cloacibacterium.
286
While Bacteroidetes did not comprise a dominant portion of the microbiome in fish from the control or low
287
treatments, Proteobacteria remained dominant across treatments (Figure 2A). This is consistent with the
288
findings of other studies which also identified Proteobacteria to be the predominant bacterial phylum in
289
the guts of FHM.
290
differences (p < 0.05) using deeper taxonomic classifications (Figures 2B, S3), including
57-59
However, within the Proteobacteria there were a number of significant treatment
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Gammaproteobacteria (predominant in controls), Xanthomonadaceae, and Rhodobacter (both
292
predominant in the high treatment). Other dominant phyla in samples from the low MeHg include
293
Planctomycetes and Fusobacteria (Figure 2B). Planctomycetes were significantly (p < 0.01) higher in the
294
low treatment than in the high, and were further classified into genera Pirellula and Planctomyces.
295
Fusobacteria was further classified as Cetobacterium, which was significantly (p < 0.01) decreased in the
296
high MeHg treatment relative to controls (Figure S3).
297
298 299 300
Figure 2. Composition of FHM gut microbial communities by diet, classified by (A) phyla with relative abundances >
301
1%, and (B) genera with relative abundances > 5%.
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Changes in composition of the fish gut microbiome suggest an adaptive response to increase
304
MeHg detoxification. Available evidence suggests methylation/demethylation of MeHg by gut microbes,
305
and/or microbiome-mediated changes in intestinal permeability influence the bioavailability of MeHg to the
306
body.
307
associated neurodegeneration.
308
removal were significantly increased (p < 0.05, Figure S3) in one or more of the MeHg exposed
309
treatments. These include Xanthomonadaceae , Cloacibacterium , members of the Deltaproteobacteria
310
FAC87
311
results are in agreement with a study by Hill-Burns et al. , which reported increased abundances of
312
bacteria associated with xenobiotic metabolism in the stool of PD patients. It is worth noting that stool
313
samples do not necessarily accurately reflect the microbiome in the GI tract (which were sequenced in the
314
present study) . Some members of the Verrucomicrobiaceae family are also involved in metabolism of
315
PD associated xenobiotics, and a member of this family identified as Candidatus Xiphinematobacter was
316
significantly increased (p < 0.05, Figure S3) in the MeHg exposed fish, though it is unknown if this
317
particular genus functions in this capacity.
318
significantly increased (p < 0.05, Figure S3) in MeHg exposed fish. However, it is worth noting that some
319
members of this genus are also capable of producing siderophores, the primary function of which is iron
320
chelation, but which may also participate in the chelation of other cations (such as Hg ).
53, 60
Additionally, increased intestinal permeability may contribute to the progression of PD53, 54
Several genera implicated in xenobiotic metabolism and metal
62
61
63
and Comamonadaceae
64
families, and Pirellula
65
(which produces a mercury-reductase). These
54
53
54
Pseudomonas, an opportunistic pathogen, was also
2+ 66, 67
321
Other suspected pathogens that were significantly (p < 0.05) increased (or present only in the
322
high treatment) included Aeromonas, Acinteobacter, and an unclassified member of the Neisseriaceae
323
family (Figures 2, S3). The presence of these bacteria may indicate suppression of immune function,
324
which is also indicated by altered abundances of other bacteria, and supported by the metabolomics data.
325
The abundance of the nucleotides uracil and inosine-5’-monophosphate (I5MP) were significantly
326
decreased (p < 0.05) in the mid-brains of MeHg exposed mice (Table 1).
327
guanine, both of which have important immunomodulatory effects, and play a fundamental role in nervous
328
system development and function. Abnormal metabolism of nucleotides leads to severe neurological
329
disorders associated with failure of dopaminergic neurons to properly develop or differentiate, which may
330
result from impaired mitochondrial function.
68
69
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I5MP is a precursor to
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Environmental Science & Technology
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Other bacteria which produce a variety of compounds with biological functions that influence
332
immunomodulation, antimicrobial properties, and intestinal barrier fortification (with implications for MeHg
333
bioavailability) were significantly decreased in one or more groups of MeHg exposed fish (Figure S3, p
