R E S E A R C H Open Access
Effect of postnatal low-dose exposure to
environmental chemicals on the gut
microbiome in a rodent model
, Vincent Raikhel
, Kalpana Gopalakrishnan
, Heriberto Fernandez-Hernandez
, Luca Lambertini
, Laura Falcioni
, Luciano Bua
, Fiorella Belpoggi
, Susan L.Teitelbaum
and Jia Chen
Background: This proof-of-principle study examines whether postnatal, low-dose exposure to environmental
chemicals modifies the composition of gut microbiome. Three chemicals that are widely used in personal care
products—diethyl phthalate (DEP), methylparaben (MPB), triclosan (TCS)—and their mixture (MIX) were administered
at doses comparable to human exposure to Sprague-Dawley rats from birth through adulthood. Fecal samples were
collected at two time points: postnatal day (PND) 62 (adolescence) and PND 181 (adulthood). The gut microbiome
was profiled by 16S ribosomal RNA gene sequencing, taxonomically assigned and assessed for diversity.
Results: Metagenomic profiling revealed that the low-dose chemical exposure resulted in significant changes in
the overall bacterial composition, but in adolescent rats only. Specifically, the individual taxon relative abundance
for Bacteroidetes (Prevotella) was increased while the relative abundance of Firmicutes (Bacilli) was reduced in all
Betaproteobacteria in MPB and MIX groups, and Deltaproteobacteria in TCS group. Surprisingly, these differences
diminished by adulthood (PND 181) despite continuous exposure, suggesting that exposure to the environmental
chemicals produced a more profound effect on the gut microbiome in adolescents. We also observed a small but
consistent reduction in the bodyweight of exposed rats in adolescence, especially with DEP and MPB treatment
(p< 0.05), which is consistent with our findings of a reduced Firmicutes/Bacteroidetes ratio at PND 62 in exposed rats.
Conclusions: This study provides initial evidence that postnatal exposure to commonly used environmental
chemicals at doses comparable to human exposure is capable of modifying the gut microbiota in adolescent rats;
whether these changes lead to downstream health effects requires further investigation.
Keywords: Phthalate, Paraben, Triclosan, Microbiota
Microbes that live on and inside the human body
(microbiota) comprise about 100 trillion microbial cells
[1–3]; the ratio of human to bacterial cells in the body is
estimated to be approximately 1 to 1 . Commensal
bacteria provide a wide range of metabolic functions that
the human body lacks. They facilitate diverse processes
such as digestion of the nutrients and production of
short-chain fatty acids and offer protection against
pathogen colonization through competition for nutri-
ents, secretion of antimicrobial substances, and micro-
niche exclusion . Commensal bacteria in the gut also
promote angiogenesis and development of the intestinal
epithelium; these bacteria have been shown to be essential
for the normal development and function of the immune
system . However, the mechanistic relationship between
microbiota diversity and biological function under diffe-
rent settings of host genetics or environmental factors
remains obscure. Accumulating evidence suggests that the
identity and relative abundance of many taxa in microbial
communities are associated with environmental factors
* Correspondence: email@example.com;firstname.lastname@example.org
Department of Genetics and Genomic Sciences, Icahn School of Medicine at
Mount Sinai, New York, NY, USA
Department of Preventive Medicine, Icahn School of Medicine at Mount
Sinai, New York, NY, USA
Full list of author information is available at the end of the article
© 2016 The Author(s). Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0
International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and
reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to
the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver
(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
Hu et al. Microbiome (2016) 4:26
including diet and antibiotics [6–10]. How exposure to ex-
ogenous chemicals may influence the microbiome remains
to be studied.
Human exposure to environmental chemicals is ubi-
quitous, and one major exposure source is through
the use of personal care products. The most recent
NHANES survey of environmental chemical exposure
demonstrates measurable concentrations of diethyl
phthalate (DEP), methylparaben (MPB), and triclosan
(TCS) in the vast majority of the US population .
These three chemicals are frequently added to personal
care products; DEP is used to stabilize fragrances and
increase plastic flexibility, while MPB and TCS are
commonly added as preservatives and microbicides .
Exposure to these chemicals has been linked to various
health effects including obesity and other metabolic
diseases [12–15] as well as breast cancer . However,
the underlying mechanism of these associations has not
been clearly elucidated. Although the term “endocrine
disruptors”has often been used to describe these che-
micals, the evidence demonstrating such properties is
conflicting and far from conclusive.
Emerging evidence suggest that the gut microbiome
plays a critical role in human metabolism . Import-
antly, the core microbiome is believed to be established
over the first few years of life in humans, and its com-
position is susceptible to exogenous factors including
diets and antibiotics [18, 19]. Early exposures are im-
portant, as denoted in the Developmental Origins of
Health and Disease (DOHaD) paradigm. In particular,
the adolescent period represents a narrow but pro-
foundly critical window of susceptibility to myriad envir-
onmental exposures and conditions with potentially
lifelong impacts on health and disease. Because MPB
and TCS are commonly used as bactericides or fungi-
cides, these chemicals have the potential to modify the
microbiota, which, in turn, may influence human health.
However, little direct evidence has been reported to sug-
gest any interplay between environmental chemical ex-
posure and the microbiome in human health, especially
in adolescence in humans or in animal models exposed
to chemical doses relevant to humans.
Herein, we employed a rodent model to determine
whether exposure to chemicals found frequently in per-
sonal care products, i.e., DEP, MPB, TCS, and their mix-
ture, administered at doses that result in urinary
biomarker levels comparable to humans , affect the
diversity of the gut microbiome at two developmental
stages. This study stems from a parent study on win-
dows of susceptibility to environmental chemical expos-
ure on mammary gland development; therefore, only
female rats were included in this investigation. We uti-
lized the resources and animals of the parent study and
collected fecal samples from adolescent (postnatal day
(PND) 62) and adult (PND 181) female rats. This proof-
of-principle study was designed to examine the potential
impact of low-dose environmental toxicants on the com-
position of the gut microbiome.
The gut microbiota in SD rats
16S ribosomal RNA (rRNA) gene PCRs were performed
on 150 Sprague-Dawley (SD) rat fecal samples, 100
PND, 62 samples and 50 PND, 181 samples. In total, 17
samples (3 in OIL, 6 in DEP, 4 in MPB, 1 in TCS, and 3
in mixture (MIX)) were excluded because they showed
no or poor DNA amplification. The rats for each treat-
ment groups were housed in multiple cages to minimize
the cage effect. We used a dual-barcoding sequencing
approach to obtain high-quality sequencing data while
minimizing the sequencing cost (illustrated in Additional
file 1: Figure S1A). From a single Illumina MiSeq 250 × 2
pair-end sequencing run, and we generated ~3.7 million
merged high-quality reads (quality score >30 at any po-
sition of the single read). After splitting by the barcodes,
we obtained ~30 k high-quality reads per sample on
average. The technical repeats were used to validate the
reproducibility of the 16S rRNA gene sequencing. The
taxonomy assignment showed that the mean correlation
among the quadruplicates was within the range of 0.991
to 0.994 from phylum to genus level (Additional file 1:
Figure S1B), while the mean correlation across all samples
was 0.79 at the phylum level and 0.63 at the genus level.
Female SD rats were exposed to three chemicals (DEP,
MPB, and TCS) and their mixtures as well as the vehicle
alone (olive oil) from birth to adulthood (PND 1–181).
The fecal droppings were collected from individual rat
at two time points, PND 62 and PND 181. The experi-
mental scheme is illustrated in Fig. 1a. Oral doses were
selected to recapitulate human exposure levels; the uri-
nary biomarker levels in our experiments were compa-
rable to those observed in the US population [20, 21].
The unique feature of our study is the extreme low dose
of exposure; these doses were between 1000 and 10,000-
fold less than the reported NOAEL (no observed adverse
effect level). Figure 1b shows the bacterial composition
and the relative abundance at the phylum level of each
individual sample grouped by treatment at these two
time points. The difference with respect to chemical and
time was apparent. Additional file 1: Figure S2 presents
the bacterial composition and the relative abundance of
individual samples at family levels. Consistent with
previous studies , the dominant phyla in the rat
gut microbiota were Firmicutes,Bacteroidetes,Proteo-
Comparing PND 62 to PND 181, we observed a sig-
nificant reduction in relative abundance of Firmicutes
(41 vs. 47 %; p= 0.005) and TM7 (1 vs. 6 %, p< 0.001)
Hu et al. Microbiome (2016) 4:26 Page 2 of 11
and increase in Bacteroidetes (48 vs. 37 %, p< 0.001),
regardless of the exposure. There was considerable
separation of the overall microbiota diversity between
the fecal samples collected at these two time points
(p= 0.001, by permutational multivariate analysis of
variance (PerMANOVA) test) (Fig. 2a); the mean sample-
to-sample dissimilarity of gut microbiota was much higher
at PND 62 than at PND 181 (Fig. 2a and Additional file 1:
Figure S3A). Compared to PND 62, the samples col-
lected at PND 181 showed higher bacterial community
Fig. 1 Composition of the rat microbiota at the phylum level. Samples were divided by ages (PND 62 or PND 181) and treatments. OIL oil
control, DEP diethyl phthalate, MPB methylparaben, TCS triclosan, MIX mixture of equal quantities of the three environmental chemicals.
aIllustration of the timeline of the environmental chemical treatments and fecal sample collection. bThe bar plots present the relative
abundance of phylum of each individual sample within each treatment group
Fig. 2 Comparison of overall microbiota from rats exposed to varied environmental chemical using nMDS ordination. The Bray-Curtis distance
matrices generated from taxa composition and relative abundance at genus level were visualized in nMDS plot. The ellipses were drawn to
represent the standard error. The texts of the group names were positioned at the center of each group. The significance of the dissimilarity
of overall microbiota between two groups was tested using PerMANOVA. aComparison of overall microbiota between PND 62 and PND 181.
bComparison of overall microbiota between each treatment and oil control at PND 62 (upper panel) or at PND 181 days (lower panel)
Hu et al. Microbiome (2016) 4:26 Page 3 of 11
richness and lower variability within each treatment group
(Additional file 1: Figure S3B).
Chemical-induced changes of gut microbiota in SD rats
When comparing the chemical-treated to control rats, at
phylum level, a significant reduction in abundance of
Firmicutes (47 vs. 60 %, p= 0.004) and an increase of
Bacteroidetes (41 % vs. 29 %, p= 0.003) were observed at
PND 62 but not at PND 181 (Fig. 1b, Additional file 1:
Figure S2). The Firmicutes/Bacteroidetes ratio, a metrics
that is positively associated with obesity in mammals
, was significantly lower in every chemical-treated
group than the control at PND 62. Moreover, the ex-
posed rats exhibited distinct microbiota from the control
rats at PND 62 (Fig. 2b); the PerMANOVA test using
the taxonomic composition at the genus level revealed
significant separation of microbiota diversity in rats
treated with DEP, MPB, TCS, and MIX from that of the
controls (p= 0.02, 0.006,0.005, and 0.04, respectively).
None of these treatments resulted in significant changes
in the microbiota diversity at PND 181. No changes of
average community richness were observed in any
treatment group at either time point (Additional file 1:
Figure S3B). We further compared the overall micro-
biota dissimilarity between the treatments (Additional
file 1: Figure S4), and the PerMANOVA tests (Additional
file 1: Table S1) suggested there were no significant
We performed the linear discriminant analysis (LDA)
effect size (LEfSe) analysis to compare the bacterial com-
position from phylum to genus levels between the
chemical-treated and control groups. Results from PND
62 rats are shown in Fig. 3. At the phylum level, Bacter-
oidetes were increased and Firmicutes were reduced in
all treated rats. Within the Bacteroidetes phylum, all
treatments resulted in an increase in abundance of
Fig. 3 Taxonomic representation of statistically and biologically consistent differences between each environmental chemical treatment and
controls at PND 62 rats. Cladogram plots present the LEfSe results on gut microbiome of environmental chemical-treated rats and controls at
PND 62. Differences are represented in the color for the most abundant class (red indicating increase, green indicating reduction). Each circle’s
diameter is proportional to the taxon’s relative abundance
Hu et al. Microbiome (2016) 4:26 Page 4 of 11
Prevotella species at the genus level (Fig. 3). Interest-
ingly, in comparing the taxa composition associated with
the three individual chemicals and their mixture, MPB
and TCS, the two chemicals most commonly used as
antimicrobial agent, showed similar microbiome shifts.
TCS resulted in increase of Lachnospiraceae, which was
also the major taxon increased in newborn mice exposed
to low-dosage antibiotics in previous studies . Com-
pared to both MPB and TCS, DEP treatment showed
more modest microbiome shifts. However, at the family
level, the increases of Streptococcaceae and Elusimicro-
biaceae were only observed in the DEP-treated animals,
not in the MPB, TCS, or MIX groups. In addition, all
treatments showed a reduction of Lactobacillus.The
Betaproteobacteria at the class level was increased in the
MPB or mixture groups, but not in the DEP- or TCS-
treated rats. Importantly, no taxon was found to signifi-
cantly differ by chemical exposure in the fecal samples
collected at PND 181.
Using the conventional criterion of 97 % sequence
similarity (equal to the species level), we clustered the
sequencing reads and identified a total of 2980 oper-
ational taxonomic units (OTUs). Compared to their cor-
responding controls, the treatment groups at PND 62
resulted in more differential OTUs (p< 0.05, false dis-
covery rate (FDR) adjusted) than at PND 181 (Additional
file 1: Table S2). At PND 62 (Additional file 1: Figure S5),
samples from the DEP and MPB treatment groups showed
an increase in OTUs from Fusobacteria (Fusobacterium
and Leptotrichia genera); this was not apparent in samples
from the TCS- or MIX-treated groups. We also observed
an increase in OTUs from Bacteroidetes/Prevotella genus
with DEP, MPB, or TCS treatment along but not with
MIX. In comparison to the controls, we identified varying
OTUs with DEP, MPB, TCS, MIX treatments (9, 11, 4,
and 5, respectively, p< 0.05, FDR adjusted; Additional
file 1: Table S2); these OTUs correspond to coverages
of ~25, 28, 11, and 6 % of the total bacterial popula-
tion in the controls. In agreement with our observation at
the genus level, environmental chemical treatment in-
creased the relative abundance of OTUs from the Prevo-
tella genus and reduced the relative abundance of OTUs
from the Lactobacillus genus. However, at PND 181, only
three OTUs were statistically significant (pvalue <0.05),
covering 1 % of the population in the MIX treatment
group, while none were found in the other treatment
The mean bodyweight of the experimental rats was
calculated at PND 62 and PND 181; the results are pre-
sented in Table 1. At PND 62, the mean bodyweight of
the exposed rats was consistently lower than that of the
controls; however, the reduction was small and not all
groups reached statistical significance. For example, the
MPB-treated rats had a mean bodyweight of 199.4 g
compared to 209.4 g for the controls; the 10-g difference
(p= 0.0083) represents a bodyweight reduction of <5 %,
with unknown health consequences. At PND 181, the
reduction in the mean bodyweight was much less prom-
inent; although the mean bodyweight in all treated
groups was lower than the controls, the reduction was
Humans are commonly exposed to a broad spectrum of
environmental chemicals at a wide range of doses; con-
cern over such exposure continues to rise because of
suspected or potential adverse health effects. A recent
Centers for Disease Control and Prevention report indi-
cates that all Americans harbor significant levels of
many chemicals in their bodies, many are universally de-
tected and many have concentration levels above the
part-per-billion level . There is a small but growing
body of evidence supporting a role for such exposure in
metabolic dysregulation, exhibited as body size changes
[13, 24–26], insulin resistance, or altered thyroid hor-
mone levels [15, 27].
In the meantime, the gut microbiome has emerged as
a key player in human metabolism [17, 28, 29]. It is thus
reasonable to hypothesize that the exposure to environ-
mental chemicals may modify the gut microbiome and
ultimately influence human health. A recent study by
Narrowe et al. showed the low-level triclosan exposure
altered the gut microbiome of the fathead minnow .
For this study, we selected phthalates, parabens, and
Table 1 Mean bodyweights of environmental chemicals treated SD rats at PND 62 and PND 181
Treatment PND 62 PND 181
Mean bodyweights (g) Standard errors pvalue* Mean bodyweights (g) Standard errors pvalue
DEP 202.9 1.9 0.046 322.0 4.5 0.13
MPB 199.4 2.5 0.0083 327.2 5.3 0.39
TCS 206.5 2.7 0.43 328.5 4.8 0.46
MIX 207.2 2.7 0.56 331.0 3.1 0.63
OIL 209.4 2.5 Reference 334.5 6.3 Reference
*pvalue from Student’sttest
Hu et al. Microbiome (2016) 4:26 Page 5 of 11
triclosan for investigation because they are ubiquitous in
the human environment as well as antimicrobial activ-
ities. Cho et al. demonstrated that exposure of low-dose
antibiotics in mice resulted in substantial taxonomic
changes in the microbiome and associated changes in
the metabolism of carbohydrates to short-chain fatty
acids, as well as the regulation of hepatic metabolism of
lipids and cholesterol . Schubert et al. also reported
that the different structural shifts in the mouse micro-
biome resulting from various antibiotic exposures al-
tered susceptibility to Clostridium difficile colonization
these prevalent environmental chemicals may also
modulate the composition of the gut microbiome. Results
from this study demonstrate such capacity when exposed
early in life, even at very low doses that are comparable to
the human exposure.
Several studies supported by the Human Microbiome
Project report differences in microbiota between chil-
dren and adults [32–36]. Studies also suggest that
variation of microbiota is highest during childhood
and gradually decreases with age [33, 34, 37]. Similar
to the findings in human studies, samples from the
adolescent rats (PND 62) in our experiment also
showed distinctive overall microbiota compared to the
adult rats (PND 181), with higher relative abundance
of Firmicutes and lower relative abundance of Bacter-
oidetes. However, how these two time points translate
into human developmental stages is not totally clear;
thus, caution is warranted in interpreting our find-
ings. Compared to humans, rats have an abbreviated
and accelerated childhood; they develop rapidly dur-
ing infancy and become sexually mature at about
6 weeks of age (PND 42) or at 40 to 60 days .
Humans, on the other hand, develop slowly and do
not reach puberty until the age of 11–12 years .
In rats, the period of PND 55–66 often represents
the adolescent period and the transition to adulthood
begins after the eighth week of postnatal life .
Compared to the adult rats, the gut microbiome of
adolescent rats in our experiment showed lower taxon
richness but higher variance within sample and higher
sample-to-sample dissimilarity. Furthermore, our results
revealed that all three chemicals, at levels comparable to
those humans would likely encounter, significantly al-
tered the overall microbiota diversity and resulted in
more prominent changes at multiple taxon levels in the
adolescent rats. However, the effects were diminished in
the adult rats. We also observed a subtle yet consistent
reduction in the bodyweight of the young rats, which
corresponded with the observed shift in gut microbiota,
in particular the reduced Firmicutes/Bacteroidetes ratio.
It is known that the gut microbiota is continually subject
to a wide variety of perturbations, including various
environmental factors [41, 42]. However, even with these
insults, the gut microbiota is generally stable over time
due to the resilience of commensal microbes to survive
under continuous challenge. In our experiment, the rats
underwent treatment continuously from birth. Although
treatment at the earlier age (adolescent), the gut
cover at a later (adult) stage when the environmental-
induced changes were minimized. These data suggest
that the commensal gut microbiota can develop re-
sistance to the low-dose environmental chemical ex-
posure during development.
Low-dose antibiotic exposure, likely from environmen-
tal sources, showed no significant effect on the bacterial
diversity within the samples . Similar to antibiotics, in
our study, exposure to low-dose environmental chemi-
cals did not reduce the biodiversity of the gut micro-
biota. Nevertheless, environmental chemical exposures
at such low doses were still capable of altering the overall
composition of the gut microbiota. We observed an in-
crease in abundance of Lachnospiraceae in TCS-treated
rats, similar to that previously described in low-dose
antibiotic-treated rodents . However, in contrast to the
increased Firmicutes/Bacteroidetes ratio in antibiotic-
treated mice, we noted an increase in the relative abun-
dance of Bacteroidetes compared to Firmicutes in the
exposed adolescent rats, correlated with an observed
reduction in bodyweight. These results may suggest
different functional mechanisms between the low-dose
antibiotics and the environmental chemicals used in
this study; it may also reflect the inherent differences
between rodents and humans. Such complexity of the
association between environmental exposure and obesity-
related outcomes has been recognized . However,
results on Firmicutes/Bacteroidetes ratio and obesity
from other studies are inconsistent and warrant further
validations [44, 45].
The combined effect of multiple exposures is rarely
considered in environmental investigations. Considering
that many chemicals, like the ones investigated in this
study, are commonly used together in personal care
products, it is unlikely that we encounter environmental
chemicals one at a time. Recent investigations into the
low-dose mixture effects of endocrine disruptors 
demonstrate not only additive but also synergistic or an-
tagonistic effects . In the current study, treatment
with mixture resulted in a distinct microbiome shift that
differed from that of individual chemical or a simple
additive effect, suggesting possible biological interactions
of these chemicals.
The major limitation of the investigation is the lack
of health-related outcomes in the animal model. This
study stemmed from a parent study on the effects of
Hu et al. Microbiome (2016) 4:26 Page 6 of 11
environmental chemicals on normal mammary gland
development, in which established microbiome-related
outcomes, such as obesity or colitis, were not induced.
Nevertheless, by utilizing the resources of the parent
study, we were able to demonstrate that commonly used
environmental chemicals have the capacity to change gut
microbiome composition at a dose that is comparable to
human exposure in the US population. More importantly,
our results suggested that the early-life exposure resulted
in more observable changes in the microbiome compos-
ition. A recent study using a rodent model demonstrated
that altering the gut microbiota during a critical deve-
lopmental window might have lasting metabolic conse-
quences . We are in the process of conducting the
follow-up studies on the potential health outcomes.
Another limitation is the use oral gavage as the route
of exposure. Given the ubiquitous nature of the study
compounds, human exposure is likely to involve multiple
routes, via skin absorption, ingestion, and inhalation .
Several studies showed that breast milk during lactation
also contains these three chemicals or their metabolites
[50, 51]. While is it almost impossible to recreate exact
human exposure scenario, we tried to resolve this issue
by calibrating the exposure dose to achieve similar urin-
ary biomarker concentrations between rats and humans.
Gavage is preferred over other routes of exposure for en-
vironmental chemicals when very low doses are used .
It is difficult to ascertain the true intake when chemicals
are mixed into food or drinking water ad libitum. Al-
though gavage does not perfectly represent a model of hu-
man dietary exposure, this route has been employed for
numerous studies assessing potential carcinogenic hazards
. Lastly, because the parent study was designed to in-
vestigate the underlying mechanisms of environmental ex-
posures and breast cancer, only data on female rats were
available so that any gender-specific effects on micro-
biome cannot be addressed in this investigation.
In summary, our study provides the first evidence
that postnatal exposure to commonly used environ-
mental chemicals at levels comparable to human ex-
posure is able to alter the gut microbiota in a rodent
model. These findings enhance our understanding on
the impact of environmental toxicants on the com-
position of gut microbiome and, potentially, on the
All animal study procedures were performed at the
Cesare Maltoni Cancer Research Centre/Ramazzini
Institute (CMCRC/RI) (Bentivoglio, Italy). The experi-
ment was conducted following the rules established by
the Italian law regulating the use and human treatment
of animals for scientific purposes (Decreto legislativo
N. 26, 2014. Attuazione della direttiva n. 2010/63/UE
in materia di protezione degli animali utilizzati a fini
scientifici. - G.U. Serie Generale, n. 61 del 14 Marzo
2014). Before starting the experiment, the protocol
was examined by the Ethical Committee of Ramazzini
Institute for approval. The protocol of the experiment
was also approved and authorized by the ad hoc commis-
sion of the Italian Ministry of Health and the Mount Sinai
IACUC. Because the original study focuses on windows of
susceptibility in breast cancer, only female SD rats, be-
longing to the colony used in the laboratory of the
CMCRC for over 40 years, were used. The experimental
animals (F1) received the treatment from birth (PND 1)
through milk of dams (F0) exposed to environmental che-
micals from parturition. After weaning, the female off-
spring (F1) were exposed through gavage three times a
week until euthanization at PND 181.
The timeline of the experimental animal treatment
and fecal sample collection is shown in Fig. 1a. The
breeder animals (F0) were weighed weekly, starting after
parturition, and the dose to be administered during lac-
tation was calculated on the basis of the weekly weight.
All the pups (F1) were housed with their dam (F0) until
weaning; then, they were separated and identified by ear
punch; each litter contributed to the study with one fe-
male pup. The animals were randomized in the different
groups of treatment in order to have minimal differences
in bodyweight among them, with a standard deviation of
no more than 10 % from the average. They were housed
in Makrolon cages (cm 41 × 25 × 15) at two or three per
cage, with a stainless steel wire top and a shallow layer
of white firewood shavings as bedding. All animals were
kept in a single room at 23 ± 3 °C and at 40–60 % rela-
tive humidity. Lighting was artificial and the light/dark
cycles were tended to be 12 h each. The F1 generation
received the treatment through breast milk from PND 1
to PND 28 (weaning). Young females were then sepa-
rated from their mothers and weighed individually every
week; they were dosed by gavage following the protocol,
based on the weekly mean bodyweight of each group.
The animals were given the same standard “Corticella”
pellet diet (Piccioni Laboratory, Milan, Italy) for both
breeders and offspring; both feed and tap water were
available ad libitum. Feed and tap water were periodic-
ally analyzed to exclude biological and chemical contam-
ination (mycotoxins, pesticides, arsenic, lead, mercury,
selenium). During the experiment, the mean daily water
and feed consumption were measured per cage; body-
weights were individually measured once a week for the
first 13 weeks and every two weeks until the end of the
experiment. The experimental protocol is outlined in
Hu et al. Microbiome (2016) 4:26 Page 7 of 11
Three chemicals and their mixture were tested along
with a control group exposed to vehicle only. These che-
micals, i.e., diethyl phthalate (CAS # 84-66-2, lot #
STBB0862V, 99 % purity), methylparaben (CAS # 99-76-
3, lot # BCBG0852V, 99 % purity), and triclosan (CAS #
3380-34-5, lot # 1412854 V, 97 % purity) were supplied
in plastic containers by Sigma-Aldrich (Milan, Italy).
Olive oil, supplied in glass bottles (Montalbano Agricola
Alimentare Toscana, Florence, lot # 111275, Italy),
was used as the vehicle to prepare all dosing solu-
tions. Olive oil was tested to be free of the tested
chemicals. The solutions were prepared every week
using glass pipettes, stored in glass bottles, continu-
ously stirred throughout the study, and kept at room
temperature and in the dark; the stability of the solu-
tions was confirmed by gas chromatography-mass
spectrometry (GC-MS) (Neotron Laboratory, Modena,
Italy). Precautions were taken to minimize any plastic
contamination: the compounds were administered
using a 5-ml glass syringe, and the biological samples
were collected in polypropylene vials.
Dosage of chemical exposure
With knowledge of the toxicokinetic properties of the
tested chemicals, we determined oral doses of DEP,
MPB, and TCS that resulted from urinary biomarker
concentrations comparable to those reported for the US
population [20, 21]. Specifically, the oral doses were:
NOAEL/10,000 for DEP and MPB; NOAEL/1000 for
TCS, resulting in 0.1735, 0.105, and 0.05 mg/kg/day final
doses, respectively. The mixture solutions were prepared
by mixing the three chemicals at the selected dose. The
control group received gavage with olive oil alone, which
was the vehicle selected.
The experiment started with 100 dams (F0), 20 in each
experimental group (three chemicals, one mixture and
control). Their newborns (F1) were first exposed to che-
micals postnatally through milk from the exposed dams,
from birth to weaning (PND 28). After weaning, these
pups were exposed through oral gavage three times a
week (on Monday, Wednesday, and Friday), at similar
times of the morning, and adjusted weekly to maintain a
constant dose level in terms of bodyweight, from PND
28 to PND 181.
Fecal samples were collected from all animals of the F1
generation (20 from each test compound) at PND 62.
Afterwards, due to budgetary constraints, 50 rats, 10
from each test compound, were randomly selected and
carried on with the chemical treatment until PND 181
when the fecal samples were collected. After oral gavage
with the test chemicals, each animal was single-caged
for at least 4 h in order to avoid contamination of fecal
droppings from other animals. About 2–3 droppings
from each animal were collected and preserved in cryo-
vials on an ice bed. Forceps were used for collecting
droppings, which were washed and cleaned using sterile
water and 1 % sodium bicarbonate between each sam-
pling to avoid cross contamination. The cryovials were
then stored at −20 °C until shipment to the Icahn School
of Medicine at Mount Sinai.
Fecal DNA extraction and processing
Rat fecal DNA was extracted using the Qiagen DNA
Stool Mini Kit following the protocol from the manufac-
turer (Qiagen, Valencia, CA). Total DNA concentration
was determined by Qubit 2.0 Fluorometer (Life tech-
nologies, Norwalk, CT). The phylogenetically inform-
ative V3–V4 region of 16S rRNA gene was amplified
using universal primer 347F/803R [54, 55]. We designed
a dual-barcoding approach to label the 16S rRNA gene
amplicons from each sample (illustrated in Additional
file 1: Figure S1A). Briefly, the 6-mer barcodes were at-
tached on the 5′ends of both forward and reverse PCR
primers so that 16S rRNA gene PCR amplicons from
each sample contained a unique dual barcode combin-
ation. PCR primers were designed against conserved
sequences to amplify the flanking variable 16S rRNA
gene regions. The primers were synthesized by IDT
(Integrated DNA technology, Coralville, IA), and the se-
quences are shown in Additional file 1: Table S3.
16S rRNA gene sequencing and data analysis
The 16S rRNA gene was then amplified by PCR with
double-barcoded primer pairs. The integrity of the
Table 2 Experimental plan of environmental chemicals
treatment and stool sampling
Group Compound (dose in mg/kg bw)
No. PND 62 PND 181
I DEP (0.1735) 20 20 10
II MPB (0.1050) 20 20 10
III TCS (0.050) 20 20 10
IV MIX (mixture of DEP + MPB + TCS) 20 20 10
V OIL 20 20 10
Total 100 100 50
DEP diethyl phthalate, CAS 84-66-2, MPB methylparaben, CAS 99-76-3, TCS
triclosan, CAS 3380-34-5), MIX mixture of DEP + MPB + TCS in equal quantities,
OIL olive oil control, vehicle alone
Animals were treated from PND 1 to PND 181. The newborns (F1) were first
exposed to chemicals postnatally through milk from the exposed dams, from
birth to weaning (PND 28). After weaning, these pups were exposed through
oral gavage three times a week, from PND 28 to PND 181. Each compound
was administered in olive oil as vehicle by gastric intubation (gavage), starting
with 0.5 ml of olive oil from 4 to 9 weeks of age, and then with 1 ml once adult
Hu et al. Microbiome (2016) 4:26 Page 8 of 11
amplicons was verified by agarose gel electrophoresis.
The resulting ~460-bp sized amplicons were pooled
and then sequenced with the Illumina MiSeq paired-
end sequencing platform. The 2 × 250 pair-end se-
quence fastq data were merged. After removal of the
merged sequencing reads with a length of <400 or
the quality score of < Q30 at more than 1 % of bases,
all sequencing reads were split by barcode and
trimmed of primer regions using CLC Genomic work-
bench 6. Quadruplicate measurements of one sample
and duplicate measurementsofthreesampleswere
processed and sequenced using different barcodes and
batches to test the sequencing reproducibility. The fil-
tered and trimmed high-quality reads were further proc-
essed by QIIME 1.7.0 . We used the command
pick_de_novo_otus.py with the defaulted cutoff = 97 % to
cluster of nearly identical sequencing reads as an
OTU using Uclust. Representative sequences for each
OTU were aligned using PyNAST. The program fur-
ther assigned taxonomy with the Uclust consensus
taxonomy assigner and filtered the alignment to re-
move positions, which are all gaps, and specified as 0
in the lanemask. Finally, the program built a biom-
formatted OTU table. Using Chimera Slayer ,
chimera sequences arising from the PCR amplification
were detected and excluded from the aligned repre-
sentative sequences and the OTU table. All non-singleton
OTUs were retained for performing the log likelihood
ratio test (QIIME command group_significance.py using
g_test statistics) to further identify significant differen-
tial OTUs between each treatment and the normal
controls. The resulted pvalues were adjusted by the
The overall microbiome dissimilarities among all
samples were accessed using the Bray-Curtis distance
matrices [58, 59]. Non-metric multiple dimensional
scaling (nMDS) were used to visualize the dissimilar-
ities. The PerMANOVA procedure [60, 61], with the
maximum number of permutations = 999, was per-
formed to test the significance of the overall micro-
biome differences between the gut microbiota grouped by
PNDs and chemical treatments. The PerMANOVA
procedure using the [Adonis] function of the Rpack-
age vegan 2.0–5  partitions the distance matrix
among sources of variation, fits linear models to dis-
tance matrices and uses a permutation test with
pseudo-Fratios to obtain the pvalues. The diversity
within each microbial community, so-called alpha-
diversity, was calculated using the Shannon Index as
metric and represented the measure of the diversity
at the genus level [63, 64]. Using the LEfSe method
, we further selected the microbiome features sig-
nificantly associated to PNDs and environmental chemical
treatment at various taxonomic ranks.
Additional file 1: Table S1. The significance of the overall microbiota
differences between treatment groups by PerMANOVA (permutational
multivariate analysis of variance) procedure. Table S2. List of differential
OTUs by treatment at 62 days and 181 days. Table S3. The sequences of
dual-barcoding 16S PCR primers. Figure S1. Multiplex double-barcoding
16S rRNA sequencing. 1A. Illustration of multiplex double-barcoding 16S
rRNA sequencing. Figure S2. Profiles of the rat microbiota at the family
level. Figure S3. Microbiota diversity in environmental chemical treatment
and control groups. Figure S4. Comparison of overall microbiota from rats
exposed to varied environmental chemical at PND 62 and PND 181 using
nMDS ordination. Figure S5. The differential OTUs by treatment at PND 62.
(PDF 4.93 mb)
DEP, diethyl phthalate; LEfSe, linear discriminant analysis (LDA) effect size;
MIX, mixture; MPB, methylparaben; OTU, operational taxonomic units;
PerMANOVA, permutational multivariate analysis of variance; PND, postnatal
day; SD, Sprague-Dawley; TCS, triclosan
We thank the OCS genome technology center of New York University
Langone Medical Center for the library preparation and sequencing service.
This work was funded by NIEHS/ NCI: 5U01ES019459 (JC, KG, LL, and ST),
Mount Sinai Children’s Environmental Health Center Pilot Fund, Institution
fund of Ramazzini Institute, Bologna, Italy (FB), and NIDDK: 1K01DK094986-
Availability of data and materials
16S rRNA gene sequencing information has been deposited into EMBL
Nucleotide Sequence Database (ENA) and can be publicly accessed at
JH supervised the overall experiment, implemented the bioinformatics, and
drafted the manuscript. VR, KG, and HFH performed the sample processing
and qPCR. LL participated in the design of the study and helped to draft the
manuscript. FM, LF, LB, and FB performed the animal experiments and
collected the samples. ST participated in the design of the study and helped
to draft the manuscript. JC conceived of the overall study and participated in
its design and coordination and helped to draft the manuscript. All authors
read and approved the final manuscript.
The authors declare that they have no competing interests.
Department of Genetics and Genomic Sciences, Icahn School of Medicine at
Mount Sinai, New York, NY, USA.
Department of Preventive Medicine, Icahn
School of Medicine at Mount Sinai, New York, NY, USA.
Pediatrics, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Department of Oncological Sciences, Icahn School of Medicine at Mount
Sinai, New York, NY, USA.
Cesare Maltoni Cancer Research Centre, Ramazzini
Institute, Bentivoglio, Bologna, Italy.
Received: 12 January 2016 Accepted: 31 May 2016
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